This document provides an introduction and literature review for a thesis on the effect of low glycemic index foods on subjects with type 2 diabetes mellitus. It discusses the definition and types of diabetes, risk factors, symptoms and complications. It reviews the prevalence of diabetes globally and management strategies, with a focus on dietary management and the concepts of glycemic index and load. Specific foods proposed for a low glycemic index multigrain mix are discussed. The objectives of the thesis are outlined.

1. EFFECT OF LOW GLYCAEMIC INDEX FOODS ON SUBJECTS
OF TYPE 2 DIABETES MELLITUS
Thesis
Submitted
By
P. Madhumathi
Under the guidance of
Dr. A. Jyothi
Professor
DEPARTMENT OF HOME SCIENCE
SRI PADMAVATI MAHILA VISVAVIDYALAYAM
TIRUPATI- 517502
2020

2. INTRODUCTION
Diabetes mellitus is the most common metabolic disorder affecting the present generations all
over the world. Diabetes is a chronic disease that occurs either when the pancreas does not produce
enough insulin, a hormone that regulates blood sugar, or when the body cannot effectively use the insulin
it produces. It is a complex illness, characterized by hyperglycaemia with disturbances in the metabolism
of carbohydrate, fat and protein (WHO,2006). The status of diabetes has changed from being considered
as a mild disorder of elderly to one of the major causes of morbidity and mortality affecting the youth and
middle aged people, between 35 and 65 years of age (Mohan et al., 2007). Diabetes is a major cause of
blindness, kidney failure, heart attacks,stroke and lower limb amputation (WHO,2006).
According to the International Diabetes Federation, in 2019 diabetes affects 463million (9.3%)
adults globally, and it is estimated to rise to 578 million (10.2%) by 2030 and 700 million (10.9%) by
2045. (Saeediet al., 2019). In the South East Asia region 82 million people have diabetes and by 2045, it
may rise to 151 million (IDF 2018). According to the IDF, there were 73 million cases of diabetes in
India in 2017, i.e., nearly about 8.8% in adults. In 2015 an estimated 1.6 million deaths were directly
caused by diabetes and another 2.2 million deaths were attributable to high blood glucose in 2012, WHO
projects that diabetes will be the 7th leading cause of death in 2030.
The ADA (2017) has classified diabetes mellitus into Type 1 diabetes mellitus, Type 2 diabetes
mellitus, Gestational diabetes mellitus and specific types of diabetes due to other causes. Among these,
Type 2 diabetes, earlier called as Non Insulin Dependent diabetes mellitus (NIDDM),constitutes more
than 90 per cent of diabetic population, growing constantly and leading to multiple health problems. The
symptoms of Type 2 diabetes are frequent urination (polyurea), excessive thirst (polydypsia), increased
hunger (polyphagia), weight loss, tiredness, lack of interest and concentration, a tingling sensation or
numbness in the hands or feet,blurred vision, frequent infection, slow wound healing, vomiting and
stomach pain (IDF,2017). Diagnostic criteria by the American Diabetes Association includes a fasting
plasma glucose (FPG) level of 126 mg/dL or higher, a 2-hour plasma glucose (PPG) level of 200 mg/dL
or higher during a 75 g oral glucose tolerance test (OGTT). HbA1c is a widely used biomarker for the
adequacy of glycaemic management, reflecting average blood glucose levels over a two to three months
period of time
WHO has identified India as capital of diabetes for its high prevalence rate, for which, factors
such as urbanization, consumption of energy dense food and changes from traditional active life to
modern sedentary and stressful life are some of the major underlying causes. Family history, overweight
and obesity (BMI≥25 kg/m2
) , higher waist circumference, unhealthy diet, physical inactivity, increasing
age, high blood pressure,ethnicity, history of gestational diabetes, poor nutrition during pregnancy are the
possible risk factors associated with Type 2 diabetes (WHO, 2016). Several studies have confirmed that
unhealthy personal habits, such as smoking and excess intake of alcohol, can make diabetes and its
complications worse.
If it is not treated,diabetes can damage the blood vessels, eyes (retinopathy), kidneys
(nephropathy) and nerves (neuropathy) and increase the risk of heart disease and stroke (WHO, 2016).
Hypertension and dyslipidaemia, which includes high triglyceride and low HDL cholesterol, are common

3. in type 2 diabetes and contribute significantly to the incidence of coronary heart disease. Due to lack of
knowledge and awareness of the disease among the diabetics, they remain undiagnosed until major
complications set in and it may lead to further serious complications (Kanojia, 2017).
Diabetes cannot be cured but it is a disorder that can be kept under control through proper
management strategies. The primary goal of management of diabetes is maintaining near normal blood
glucose levels to prevent long term complications. Oral antidiabetic drug is the first line treatment for
type 2 diabetes for controlling the hyperglycaemia. The progressive nature of type 2 diabetes requires a
combination of two or more oral agents in the long term and insulin may also be used as an intermittent or
permanent therapy in some advanced cases of type 2 diabetes mellitus (Ramachandran et al., 2010). But
there are limitations in the use of anti-hyperglycaemic medications, because of the side effects,high cost,
limited action and secondary failure rates (Omodanisi et al., 2017).
A life-time management using anti diabetic drugs alone is expensive and the economic burden
due to diabetes at personal, societal and national levels is huge (Ramachandran et al., 2010). So it is an
urgent need to identify the most appropriate and cost-effective approach for the easy management of the
disease and reduction of disease burden. Well designed randomized control trials have shown that life
style interventions including dietary changes have a vital role in preventing the progression of type 2
diabetes (Esposito et al., 2015). Life style measures include reduced alcohol intake, reduced intake of salt,
reduced sugar intake, increasing physical activity and control of overweight.
For the effective implementation of life style modifications and improvement of quality of life,
knowledge about the disease, risk factors, complications and management of the disease is essential. In
India, studies on diabetes awareness revealthat urban people have more knowledge of diabetes than rural
residents. Several studies have suggested that educating the patient with life style modifications is an
important component of management of type 2 diabetes.
In addition to pharmacotherapy and increased physical activity, nutrition therapy makes an
important component of the overall treatment plan of type 2 diabetes. The nutrition therapy should aim at
delaying and preventing complications of diabetes and also consider blood pressure,serum lipid profile
and body weight goals (ADA, 2015). Dietary prescription should be individualized considering the age,
weight, gender, dietary pattern, habitual eating and regional availability of the foods to achieve better
meal adherence. For achieving metabolic goals, multiple meal planning approaches like carbohydrate
counting, simplified meal plans, exchange lists and glycaemic index are effective (Evert et al., 2014).
Carbohydrate intake has a direct effect on postprandial glucose levels in people with diabetes and
it is the primary macronutrient of the concern in glycaemic management. But there is difference in blood
glucose response after ingestion of the same amount of carbohydrates from different foods (Wolever,
2001). Based on this, the concept of glycaemic index (GI) was first proposed by Jenkins et al in 1981. It is
a system of ranking (0 to 100) of foods which contain carbohydrate, based on their glycaemic response
(Perlstein et al., 1997). Glycaemic Index is defined as the incremental area under the blood glucose
response curve of a 50 g carbohydrate portion of a test food expressed as a percent of the response to the
same amount of carbohydrate from a standard food taken by the same subject (FAO/WHO, 1998).
Glucose has been used as the reference food for international standardization of GI values. The WHO has
classified the foods according to their GI values as low GI foods (GI 55 or less), medium GI (56-69) and
high GI (70 or more). GI data for foods could be used to make priorities for food selection within food
groups as a part of dietary management (Brouns et al., 2005). The GI is acknowledged by a number of
major diabetes associations, including those in UK,Canada, Australia, Europe, and the USA, as a useful
tool for differentiating between carbohydrates (Venter, 2005).
The glycemic response to an ingested food was found to depend not only on the GI but also on
the total amount of carbohydrates ingested, and this led to the concept of Glycaemic Load (GL) (Eleazu,
2016). GI gives ranking of foods based on their blood glucose response,where as the GL takes into
account the amount of available carbohydrate also being consumed in the portion of food.

4. Consumption of high glycaemic index foods like some refined foods, sugars and rapidly digested
starch,induces a rapid increase in blood glucose, thus results in high demand for insulin which could
eventually lead to type 2 diabetes (Maki and Phillips, 2005). Conversely low glycaemic index foods have
slower glycaemic response which may facilitate better glycaemic control and lipid profiles in people with
diabetes (Perlstein, 1997). A reduction in postprandial glucose and insulin concentrations in the blood is
considered beneficial in the prevention and treatment of diabetes mellitus. Evidence from prospective
studies shows that low GI diets are associated with reduced risk of diabetes, CVD,cancer and metabolic
syndrome (Venter,2005).
.
Clinical trials have shown that low Glycaemic Index diets improve glycaemic control in
diabetes, increase insulin sensitivity and beta cell function, reduce food intake and body weight, influence
memory and may improve blood lipids (Venter,2005). In addition to this, satiating effect of lower GI
foods and also reducing episodes of nocturnal hypoglycaemia may be useful for diabetics (Perlstein et al.,
1997). Patients with type 2 diabetes will have a 2 to 3 fold higher risk of CVD and premature mortality
than the generalpopulation. Low GI foods may reduce CVD risk through effects on oxidative stress,
blood Pressure,serum lipids and coagulation factors (Radulian et al., 2009). One more advantage of
ingesting a low GI food is that the postprandial response to the subsequent meal will be attenuated
(Jenkins, 2007).
Several studies stated that cereals like whole wheat, brown rice, finger millet, barley and maize
are having low glycaemic Index. Pulses which are good sources of protein and fibre are also considered as
low GI foods. Many prospective GI studies consider the carbohydrate content of legumes as a slow
releasing which makes them low glycaemic (Mirmiran et al., 2014). Green leafy vegetables, vegetables
and some fruits are having low glycemic index. Studies found many other low GI spices like fenugreek,
kalonji, beneficial for the management of diabetes. The glycaemic index of the foods is affected by some
factors like nature of carbohydrate in the food, seasonalfactors,type of starch present in the food,
physical form of food, cooking and processing, fibre, antinutrients, fat and protein, speed of eating the
food and acidity (Perlstein et al., 1997). These parameters should be considered while calculating the
glycaemic index of foods for better functional quality.
Glycaemic Index in the context of a meal is referred as ‘mixed meal’ and substituting low GI
foods for high GI foods in a meal will reduce the glycaemic response to the meal (Perlstein et al., 1997).
Recent dietary guidelines recommend inclusion of two low GI foods daily or inclusion of one low GI
food at each meal or the replacement of 50% of carbohydrate with low GI choices (FAO/WHO,1998).
The diabetic diet should provide 50-60% of total calories from carbohydrates,25-35% from dietary fat
and 10-15% from protein (Alwan, 1994). Cereals and millets are prime source of carbohydrate, but a
combination of cereal,millet and pulse is found to be more effective with rich energy value, dietary fibre,
protein, minerals and vitamins than the only cerealdiet. So a combination of different low GI foods in
proper proportions, in the form of a composite meal is a better choice instead of selecting them
individually. So it is necessary to educate people about the importance of low GI foods and how to
incorporate them into the diet for the prevention and management of type 2 diabetes. One of the
limitations of following a low GI diet is a lack of acceptable low GI foods and most of the palatable foods
are high GI foods. Therefore the demand for the food industry is to produce foods that are not only
palatable and fast to prepare but also slow to digest (Jenkins, 2007). As the magnitude of type 2 diabetes
is reported high in India in both urban and rural areas,in middle income groups and among
underprivileged people and at lower BMI levels (Nanditha et al., 2016), there is a need to develop and
popularize such therapeutic dietary multigrain products with locally available low glycaemic index foods,
which are cost effective and easily accessible to the people without compromising the palatability.
With this background, the present study has been undertaken as an attempt to make use of the
therapeutic and hypoglycaemic quality of some indigenous foods in the formulation of a multi grain
product for the effective management of type 2 diabetes with the following objectives:

5. 1. To develop and standardize a low glycaemic index multigrain mix,
2. To analyze the nutrient composition and shelf life of the developed low glycaemic index multi
grain mix,
3. To evaluate the glycaemic index and sensory evaluation of the developed low glycaemic index
multigrain mix,
4. To study the effect of supplementation of the developed low glycaemic index multigrain mix on
type 2 diabetics, and
5. To assess the effect of nutrition counseling on type 2 diabetics.
*****

6. 2. Review of literature
Diabetes is now one of the most common global metabolic disorders affecting the young
adults also. Because of the drastic increase in prevalence rate, Type 2 Diabetes Mellitus has
become a high priority public health problem in the world. It is the fifth leading cause of death in
many countries. Complications from diabetes like coronary artery and peripheral vascular
disease, stroke, diabetic neuropathy, amputations, renal failure and blindness, are resulting in
increasing disability, reduced life expectancy and huge health cost for every affected individual
and the society. Diet and life style approaches for prevention and treatment of diabetes should be
given much attention equal to drug therapies. Therefore, an effective preventive and control
protocol for type 2 diabetes mellitus are inevitable in the management of the disease. The scientific
review and expert committee reports may provide a scientific guidance for clinical and self-care practice
recommendations in patient care. The scientific literature related to diabetes and its management
strategies are reviewed here in the following aspects.
2.1. Definition of diabetes mellitus,
2.2. Types of diabetes and diagnostic criteria,
2.3. Risk factors of diabetes mellitus,
2.4. Symptoms and complications of Type 2 diabetes,
2.5. Prevalence of diabetes and projections,
2.6. Management of diabetes,
2.7. Dietary management,
2.8. Effect of individual nutrient in the diet on diabetes:
2.9. Glycaemic index,
2.10. Glycaemic Load,
2.11. Low glycaemic index formulations for diabetes,
2.12. Food ingredients of the developed low glycaemic index multigrain mix,
2.13. Whole grains and diabetes,
2.14. Nutrition counseling.
2.1. Definition of diabetes mellitus:
The name diabetes mellitus has been known for centuries, which was said to derive from its
symptoms, i.e., diabetes, from the Greek diabainein, meaning “to pass through,” describes the frequent
urination, and mellitus, from the Latin meaning “sweetened with honey,” refers to sugar in the urine. It is
called as ‘Madhumeham” in the local language Telugu, in the states of Telangana and Andhra Pradesh.
World Helath Organization (WHO, 2016) defined diabetes mellitus as a chronic disease caused
by inherited or acquired deficiency in production of insulin by the pancreas, or by the ineffectiveness of
the insulin produced and this deficiency results in increased concentrations of glucose in the blood, which
in turn damage many of the body's systems, in particular the blood vessels and nerves.
Diabetes is a disorder of carbohydrate metabolism characterized by impaired ability of
the body to produce or respond to insulin and maintain proper levels of glucose in the blood
(“Diabetes Mellitus”, n.d.). American Diabetes Association (ADA, 2017) defines diabetes as a
group of metabolic diseases characterized by hyperglycemia resulting from defects in insulin secretion,
insulinaction,orboth.

7. Indian Council of Medical Research (ICMR, 2018) defines diabetes mellitus as a syndrome of
multiple etiologies characterized by chronic hyperglycaemia with disturbances of carbohydrate, fat and
protein metabolism resulting from defects in insulin secretion, insulin action or both is often associated
withlongtermcomplications,involvingorganslikeeyes,kidneys,nerves,heartandbloodvessels.
2.2. Types of diabetes mellitus anddiagnosis criteria:
The classification and diagnosis of diabetes are complex but it is now widely accepted
that there are three main types of diabetes, type 1 diabetes, type 2 diabetes and gestational
diabetes (GDM) (IDF (2008). Type 1 diabetes was earlier called as Juvenile-onset diabetes or
insulin dependent diabetes mellitus (IDDM) and type 2 diabetes was called as maturity-onset
diabetes or non-insulin-dependent diabetes (NIDDM). The immune pathogenesis of early onset
diabetes was recognized in the 1970s, and it was acknowledged that both type 1 diabetes and
type 2 diabetes, adopted in the 1990s, are two different diseases (Diapedia, 2013).
Diabetes is diagnosed based on plasma glucose level criteria either Fasting Blood Glucose (FBG),
2 hours postprandial blood glucose (PPG), value after 75g oral glucose tolerance test (OGTT), or A1c
criteria. All the four are equally appropriate for diagnostic tests (ADA,2017).
The diagnosticcriteriafordiabetesbyWHO/IDF(2006) are given intable.1.
Table.1. DiagnosticcriteriaforType 2 diabetesmellitus*byWHO
Diabetesshouldbe diagnosedif
one or more of the following
criteriaare met
Impairedglucose tolerance (IGT)
shouldbe diagnosedif bothof
the followingcriteriaare met
Impairedfastingglucose (IFG)
shouldbe diagnosedif bothof
the followingcriteriaare met
Fastingplasmaglucose ≥7.0
mmol/L(126 mg/dL) or
Fastingplasmaglucose <7.0
mmol/L(126 mg/dL) and
Fastingplasmaglucose 6.1-6.9
mmol/L(110 to 125 mg/ dL),and
Two-hourplasmaglucose ≥11.1
mmol/L(200 mg/dL) followinga
75g oral glucose load,or
Two-hourplasmaglucose ≥7.8
11.1mmol/L (≥140 to <200
mg/dL) followinga75g oral
glucose load
Two-hourplasmaglucose
<7.8mmol/L (140mg/dL)
followinga75g oral glucose load
A randomglucose > 11.1 mmol/L
(200 mg/ dL) or HbA1c ≥ 48
mmol/mol (equivalentto6.5%)…
*Source:WHO/IDF (2006)
The diagnosticcriteriagivenbyIndianCouncil of Medical Research(ICMR,2018) for Indiansare
furnishedin table.2.
Table. 2. DiagnosticcriteriafordiabetesandprediabetesbyICMR**
Parameter Normoglycemia Prediabetes Diabetes
FBG < 110 mg/dl 110-125 mg/dl (IFG) ≥ 126 mg/dl
2- h PG < 140 mg/dl 140-199 mg/dl (IGT) ≥ 200 mg/dl
HbA1c < 5.7% 5.7-6.4% ≥ 6.5%
Randomplasma
glucose*
- - ≥ 200 mg/dl (with
symptomsof diabetes)
*Individualswithrandomplasmaglucose between140-199mg/dl are recommendedtoundergoOGTT

8. ** Source: ICMR (2018).
International Expert Committee 2009 reported that HbA1c is a widely used marker of chronic
glycaemia, reflecting average blood glucose levels over a 2 to 3 months period of time. It is widely used
as the standard biomarker for the adequacy of glycaemic management, with a threshold of ≥ 6.5%. It has
got several advantages over Fasting Blood Glucose and Postprandial Glucose because it is convenient, no
fasting is required, has got greater preanalytical stability and less day-to-day deviations during stress and
illness. But it involves greater cost,limited availability of testing facility in all places. There may be
imperfect correlation between A1c and average glucose insome individuals(ADA,2017).
2.3. Risk factors of diabetes mellitus:
The increasing prevalence of diabetes emphasizes the need for understanding various risk
factors which account for type 2 diabetes mellitus. This helps in preventing or delaying the onset
of type 2 diabetes.
Diabetes results when the beta cells of the pancreas are no longer able to meet the body’s
requirement for insulin which may be increased by obesity or other factors. (Diapedia, 2013).
WHO reported that type 2 diabetes can be determined by interplay of genetic and metabolic
factors. The factors that increase the risk are ethnicity, family history of diabetes, previous gestational
diabetes combined with older age, overweight and obesity, unhealthy diet, physical inactivity and
smoking. Higher waist circumference and higher BMI are associated with increased risk of Type 2
diabetes. (WHO, 2016 and Diapedia, 2013). Ramachandran (2005) stated that the prevalence of
diabetes is more in urban India and the scenario is occurring in rural areas also due to the socio-
economic transition. Ramachandran et al. (2010) reported that the sharp increase in the prevalence
of diabetes in South East Asia regions is observed both in urban and rural areas, which is
associated with the life style transitions towards urbanization and industrialization. This process
of rapid transition from a traditional to an affluent lifestyle is referred to as 'Coca-Colonisation.
(Diapedia, 2013). Psychological stress also is one of the risk factors for type 2 diabetes for the
present day generations with the changed life style.
2.3.1. Age and diabetes:
The risk of Type 2 diabetes mellitus increases with rising age, especially between 40 and 59 years
of age (Gupta et al., 2015) which probably due to less physical exercise, decreasing muscle mass and
gaining body weight with the increasing age. But various studies demonstrated that the adult-onset type 2
diabetes is also increasing dramatically among children, adolescents and younger adults in developed as
well as developing countries due to changed life style, high level of mental stress, consumption of diets
rich in fat and calories and sedentary life style. Htike et al. (2015) reviewed to explore the magnitude
of the evolving problem of type 2 diabetes in younger adults and challenges facing by healthcare workers
in managing this high risk group. In this review it was recognized from the literature that the age of
onset of T2DM has decreased in the last two decades and an increase in obesity along with sedentary
life style have contributed to the downward shift in age of onset of T2DM. Early detection of risk
individuals would help in preventing or postponing the onset of diabetes (Gupta et al., 2015).
2.3.2. Overweight/obesity and diabetes:
Obesity is defined simply as a condition of abnormal or excessive fat accumulation in
adipose tissue, to the extent that health may be impaired (WHO, 2014). Obesity and diabetes
mellitus have a complex relationship and several studies revealed that obese people are more

9. prone to develop type 2 diabetes mellitus. This close relationship led to the connotation ‘diabesity’,
highlighting the fact that the majority of individuals with diabetes are overweight or obese (Leitner et al.,
2017). In obese individuals, the amount of non-esterified fatty acids, glycerol, hormones, cytokines, pro-
inflammatory markers, and other substances which are involved in the development of insulin
resistance, is increased. The pathogenesis in the development of diabetes is based on the fact that the
β-isletcellsof the pancreasare impaired,causingalack of control of bloodglucose (Al-Goblan ., 2014).
Quetelet Index or BMI provides most useful measure of overweight and obesity for both the
genders and for all ages of adults. The article on three decades of research on epidemiology of
diabetes in India by Ramachandran et al. (2014) stated that Indians have a genetic phenotype
characterized by low BMI with high upper body adiposity, high body fat percentage and high
level of insulin resistance. Weight reduction is one of the important therapeutic goals of disease
management for obese diabetics. The classification of BMI according to both WHO and Indian
criteria is given in table.3.
Table.3. Classification of BMI as per WHO and Indian standards
WHO criteria
(BMI kg/m2
)*
BMI Category Indian criteria
(BMI kg/m2
)**
< 18.5 Underweight < 18.5
18.5-24.99 Normal 18.5-22.99
25-29.99 Overweight 23-24.99
≥30 Obesity ≥25
(* WHO, 2000) (**Misra et al., 2009)
Broca’s index isthe easiestmethodtocalculate the ideal bodyweightforheightwhichis
determinedasHeight(incm) – 100. Mundodanet al.(2019) studiedtoidentifynormal range forBroca’s
index thatcorrespondstothe normal range for BMI andto determine the predictiveaccuracyforcut-off
pointsthusobtained.The studyobservedthatBroca’sindex ratiohadstrong correlationwiththe BMI
value andit wasconcludedthatthe individualscanbe advisedontheirideal weight(asperBroca’s
index),withthe upperlimitbeingaround5% lessthanthe calculatedvalue.
The elevated waist circumference with more than 80 cm for women and more than 94 cm for men
in the Caucasian population also shows the accumulation of abdominal fat which may lead to non-
communicable diseases like type 2 diabetes, CVD and stroke (Leitner et al., 2017). Abdominal fat is
considered more lipolytic than subcutaneous fat, and it does not respond easily to the antilipolytic action
of insulin, which causes insulin resistance,and thus type 2diabetes (Al-Goblan ., 2014).
2.3.3. Familyhistory of diabetes:
In the Inter Act case-cohort study, Scott et al. (2012) investigated the association of family
history of diabetes among different family members with incidence of T2D and the extent to which
genetic, anthropometric and lifestyle risk factors mediated this association. It was concluded that family
history remains a strong, independent and easily assessed risk factor for Type 2 diabetes mellitus and

10. prominent lifestyle, anthropometric and genetic risk factors explained only a marginal proportion of the
family history-associated excess risk.
Ramachandran and Snehalatha (2009) mentioned that nearly 75percent of type 2 diabetes patients
in India have first degree family history, indicating a strong familial aggregation in the population.
Sakurai et al. (2013) in a cohort study among 3,517 middle aged men and women
Japanese participants, investigated the relationship between family history of diabetes, the
incident risk of type 2 diabetes and the interaction of these variables with other factors. It was
found that family history of diabetes was associated with the incident risk of diabetes, and these
associations are independent of other risk factors, such as obesity, insulin resistance, and lifestyle
factors in men and women.
Bener et al. (2013) in a cross sectional study, observed the parental transmission of type 2
diabetes mellitus in a highly endogamous population and evaluated its influence on the clinical
characteristics. It was found that the prevalence of diabetes was higher among patients with
a diabetic mother and maternal aunts or uncles when compared to that with a diabetic father
and paternal aunts or uncles. The family history of diabetes mellitus was higher in patients of
consanguineous parents (38.5%) than those of non-consanguineous parents (30.2%). The
development of complications of type 2 diabetes mellitus was higher in patients with either a
paternal or maternal history of diabetes.
Shankar (2016) in a study conducted on 5,444 residents of Dilshad Garden in east Delhi to
understand the socio-economic and demographic factors among patients of Type 2 diabetes mellitus. The
study noted that the prevalence was significantly higher in joint families than in nuclear families.
2.3.4. Personalhabits and diabetes:
The personal habits including the food habits, tobacco usage and alcohol consumption show little
or more effect on onset and management of type 2 diabetes mellitus.
Food habits play an important role in maintaining the blood sugar levels. Healthy eating habits
keep the blood glucose level under control and prevent diabetes complications. Various experimental
studies have proven that vegetarian diet reduces the risk of diabetes. The prevalence of type 2 diabetes
among the vegetarians was compared to that among the non-vegetarians in a hospital-based survey by
Sarwar et al. (2010) among 724 people in the Bijapur district of Karnataka. The study showed that the
BMI is high (29.2 kg/m2
) among the non-vegetarians when compared to that of vegetarians and the
prevalence of diabetes is high among the non-vegetarians.
Various observational studies demonstrated that personal habits like smoking and alcohol
consumption aggravate the disease condition. WHO (2016) reported that active smoking increases
the risk of type 2 diabetes with the highest risk among heavy smokers. Chang (2012) in a review
about the various smoking effects on diabetes mellitus, diabetic complications, and diabetic incidence,
reported that smoking has harmful effects on patients with diabetes and it increases diabetic incidence and
aggravates glucose homeostasis and chronic diabetic complications. In microvascular complications, the
onset and progression of diabetic nephropathy is highly associated with smoking and in macrovascular
complications, smoking is associated with a 2 to 3 times higher incidence of CHD and mortality.
Alcohol consumption, another habit people get addicted to, is considered as a potential
risk factor for the type 2 diabetes, as it influences glucose metabolism in several ways. ICMR
(2018) recommended to avoid alcohol as far as possible and if used, should be taken in

11. moderation without considering it as part of the meal plan. Alcohol provides calories (7 kcal/ g),
which are considered as “empty calories” and in fasting state, alcohol may produce
hypoglycaemia.
A review by Engler et al. (2013) on effect of alcohol consumption by diabetics reported
that self-care adherence is negatively impacted by alcohol use and also negatively alters diabetes
course leading to increased morbidity and mortality.
2.3.5. Lipid profile and diabetes:
Dyslipidemia and hypertension are major modifiable risk factors for type 2 diabetes
mellitus among the Caucasian population and Asian Indians. Lipid abnormalities in patients with
type 2 diabetes, often termed “diabetic dyslipidemia”, are characterized by high total cholesterol,
high triglycerides, low high density lipoprotein cholesterol (HDL-C) and increased levels of Low
density lipoprotein cholesterol (LDL-C). This may cause an increase in the risk of developing
cardiovascular disease in type 2 diabetics. The insulin resistance or deficiency affects the key
enzymes and pathways in lipid metabolism which causes lipid abnormalities in type 2 diabetes
mellitus. In diabetes the associated hyperglycemia, obesity and insulin changes highly accelerate
the progression to atherosclerosis (Bhowmik et al., 2018). The storage of triglycerides in nonadipose
tissues is called ectopic fat storage which is associated with insulin resistance in obese patients with type
2 diabetes mellitus. The mechanisms of ectopic fat depositions in the liver, skeletal muscle, and in and
around the heart, its consequences and the effects of diet and exercise on ectopic fat depositions were
reviewed by Snel et al. (2012)
2.3.6. Occupationanddiabetes:
The literature on the association between occupation of the patient and diabetes is limited where
statistically significant outcomes were found. It depends on the factors like the nature of work, the
physical activity and the stress involved in the work. Work-related stress is thought to be a major risk
factor for type 2 diabetes.
Heden et al. (2014) conducted a study to assess whether low occupational class was an
independent predictor of Type 2 diabetes in men in Sweden over a 35-year follow-up, after adjustment for
both conventional risk factors and psychological stress. It was found that men with unskilled and semi-
skilled manual occupations had a significantly higher risk of diabetes than higher officials. The study
concluded that a low occupational class suggests a greater risk of Type 2 diabetes, independently of
conventional risk factors and psychological stress.
A collaborative study undertaken by Solja et al. (2014) examined whether stress at work, defined
as job strain, is associated with incident of type 2 diabetes independent of lifestyle factors and the findings
from this large pan-European data-set suggested that job strain is a risk factor for type 2 diabetes in men
and women independent of lifestyle factors.
2.4. Symptoms and complications of type 2 diabetes:

12. Apart from the classic symptoms polyuria, polydypsia and polyphagia, the other common
symptoms of type 2 diabetes mellitus are extreme fatigue, blurred vision, weight loss, lack of
interest, recurring infections, slow healing of wounds, tingling, pain, or numbness in the hands or
feet, skin problems and sexual problems (ADA, 2016). Hyperglycaemia is the common effect of
uncontrolled diabetes, and over time can damage the heart, blood vessels, eyes, kidneys, and
nerves (WHO, 2016). Early detection and treatment of diabetes can decrease the risk of
developing long term complications like diabetic neuropathy, nephropathy and retinopathy.
Acute complications like hypoglycaemia and ketoacidosis are also common which are to be
attended to immediately. Dyslipidaemia is also common which increases the risk of heart disease
and stroke in type 2 diabetes. With high levels of serum cholesterol and triglycerides, 50 percent
of people with diabetes die of cardiovascular disease (WHO, 2016).
2.5. Prevalence ofdiabetes and projections:
1. Global prevalence
2. Indian scenario
2.5.1. Globalprevalence:
According to IDF, the current data on global prevalence of diabetes revealed that, in 2019 it is
estimated to be 9.3 percent (463 million people), rising to 10.2 percent (578 million) by 2030 and 10.9
percent (700 million) by 2045 (Saeedi et al., 2019).
The information by WHO (2018) revealed that the number of people with diabetes had
increased from 108 million in 1980 to 422 million in 2014. The global prevalence of diabetes among
adults above 18 years of age had increased from 4.7 percent in 1980 to 8.5 percent in 2014. It reports that
the prevalence of diabetes is increasing rapidly in middle and low income countries. According to WHO,
in 2016, an estimated 1.6 million deaths were directly caused by diabetes and another 2.2 million deaths
were attributed to high blood glucose level in 2012. It was projected by WHO that diabetes will be the 7th
leading cause of death in 2030 and the deaths due to high blood glucose levels occur before the age of 70
years.
International Diabetes Federation (IDF) has been giving data on the prevalence of diabetes and
the projections nationally, regionally and globally, since the year 2000. The worldwide and South East
Asian region which is consisting of India, Srilanka, Bangladesh, Bhutan, Mauritius and Maldives,
data on prevalence and projections for a decade from 2009 to 2018 are shown in Table.4. It was estimated
that in 2009 the global prevalence of diabetes was 285 million, increasing to 366 million in 2011, 382
million in 2013, 415 million in 2015 and 425 million in 2017 (Saeedi et al., 2019).
The figures in the table.4.are showing that, every year the projections had been increasing, based
on the current data and this information gives a conclusion that the rate of prevalence of diabetes is
rapidly increasing. This presents a huge social, financial and health care burden across the world.
Table.4. Global and South East Asian (SEA) prevalence and Prediction of diabetes (in Millions) for a
decade from the year 2009-2018*
Period Worldwide South East Asian
Prevalence Prediction-year prevalence Prediction-year
2009-10 285 438 (2030) 58 101 (2030)
2011-12 366 552 (2030) 71 120 (2030)

13. 2013-14 382 592 (2035) 72 123 (2035)
2015-16 415 642 (2040) 78 140 (2040)
2017-18 425 693 (2045) 82 151 (2045)
*Source IDF Atlas
Figure.1. Worldwide actuals and projections of prevalence of diabetes during a decade (2009-2019)
Figure.1 shows that the actualprevalence (451 million) of diabetes during 2017-18 had crossed
the projections made (438 million) for 2030 in the year 2009, which shows the rapid increase in the
prevalence rate of diabetes worldwide.
The prevalence of diabetes and the number of people of all ages with diabetes for years 2000 and
2030 was estimated by Wild et al. (2004) and reported the prevalence of diabetes for all age-groups
worldwide was estimated to be 2.8 percent in 2000 and 4.4 percent in 2030. It was also reported that
India, China and United Stated of America are the ‘top three’ countries identified with high prevalence of
diabetes. The analysis presented that globally the prevalence of diabetes is similar in men and women but
slightly higher in men less than 60 years of age and in women at older ages. The analysis also reported
that urban population in developing countries is projected to double between 2000 and 2030 and the most
important demographic change to diabetes prevalence across the world appears to be the increase in the
proportion of people above 65 years of age.
Shaw et al. (2010) carried out a meta analysis to estimate the age and sex specific diabetes
prevalence worldwide for all 216 countries for the years 2010-2030 by considering studies from 91
countries, based on WHO and ADA,for age group 20-79 years range. The results revealed that the world
prevalence of diabetes among adults will be 6.4 percent, affecting 285 million adults in 2010 and will
increase to 7.7 percent affecting 439 million adults in 2030, with an increase of 69 percent in number of
adults with diabetes in developing countries and a 2 percent increase in developed countries.
Whiting et al. (2011) reported in an analysis on global estimates of prevalence of diabetes for
2011-2030 from IDF diabetes atlas, considering total 565 data sources that in 2011 there were 366 million
people with diabetes and is expected to rise to 552 million by 2030.
285
366 382
415
451
438
552
592
642
693
2009-10 2011-12 2013-14 2015-16 2017-18
Worldwide actuals and projections in
millions Actuals Projections

14. Ramachandran et al. (2014) reported that 95 percent of people with diabetes have type 2
diabetes mellitus. According to a meta analysis by Nanditha et al. (2016) more than 80 percent of
the people live with type 2 diabetes in the developing countries and the rise in T2DM in South
Asia is estimated to be more than 150 percent between 2000 and 2035. The meta analysis also
stated that out of 60 percent people living with diabetes in Asia, one half contributes from China
and India combined.
Nordstrom et al. (2016) in a study investigated the associations between body fat estimates,
plasma glucose level and the prevalence of diabetes in elderly men and women in relation to
objectively assessed visceral fat volume on a population-based sample of 705 men and 688 women,
all age 70 years. It was found that the higher prevalence of type 2 diabetes in older men (14.6%)
than in older women (9.1%) was associated with larger amount of visceral fat in men.
In another meta analysis from 540 data sources on global estimates for the prevalence of diabetes
for 2015-2040 from IDF diabetes atlas seventh edition, Ogurtsova et al. (2017) reported that in 2015,
about 415 million people aged 20-79 years were with diabetes and predicted to rise to 642 million by
2040. The study also stated that 75 percent of those with diabetes were living in low and middle income
countries. The prevalence of diabetes for South East Asia was reported as 78.3 million in the year 2015
and predicted to rise to 140.2 million in 2040. In the year 2015, about 5.0 million deaths were attributed
to diabetes.
Cho et al. (2017) reported from the IDF diabetes atlas that in 2017 it was estimated that almost
half of all people (49.7%) living with diabetes are undiagnosed. There was an estimated 374 million
people with impaired glucose tolerance (IGT) and it was projected that about 21.3 million live births to
women were affected by some form of hyperglycaemia in pregnancy. In 2017, approximately 5 million
deaths worldwide were attributable to diabetes in the age group of 20-99 years and the global healthcare
expenditure on people with diabetes was estimated to be USD 850 billion.
According to the International Diabetes Federation (IDF, 2018) the figures showed that India
was in the second position worldwide with 72.9 million people with diabetes in 2017 and China was in
top position with 114.4 million. But it is predicted that India may surpass China with 134.3 million people
and reach the top position globally by 2045, leaving China to the second position with 119.8 million.
2.5.2. Indian Scenario:
It is very alarming to know the increasing trend in the prevalence of type 2 diabetes among the
Indian population. In India the first national study on the prevalence of type 2 diabetes was done between
1972 and 1975 by the Indian Council Medical Research (ICMR) and the prevalence among the
individuals above 14 years of age was 2.1 percent in urban population and 1.5 percent in the rural
population while in individuals above 40 years of age, the prevalence was 5 percent in urban and 2.8
percent in rural areas (Mohan et al., 2007).
Purty et al. (2009) stated that according to the population studies, the prevalence had
risen five-fold from 2.1 percent in 1975 to 12.1 percent in 2000. The study furnished the
prevalence rate of diabetes of different surveys as, CURES (Chennai Urban Rural Epidemiology
Study) (age standardized prevalence rate)-14.3 percent, CUPS (Chennai Urban Population

15. Study) (age standardized) -9.3 percent. The overall prevalence in CUPS was 12 percent, in
ADEPS (Amrita diabetes and Endocrine Population Study) from Kerala was 9 percent and a
study from Kashmir showed 1.9 percent.
Ramachandran et al. (2001) illustrated that according to the national urban diabetes
survey (NUDS), the prevalence of diabetes is high in urban India and a large pool of subjects
with impaired glucose tolerance are at high risk of conversion to diabetes.
Reddy et al (2002) reported that there was 24 percent prevalence of diabetes in Andhra
Pradesh (joint state) and 28 percent hypertension on assessing a unique sample of 3307 in Andhra
Pradesh.
Mohan et al. (2007) reported that in the National Urban Diabetes Survey (NUDS),a population
based study conducted in six metropolitan cities across India recruiting 11,216 subjects aged 20 years and
above representative of all socio-economic strata, that the prevalence of type 2 diabetes was 12.1 percent.
This study also revealed that the prevalence in the Southern part of India to be higher with 13.5 percent in
Chennai, 12.4 percent in Bangalore and 16.6 percent in Hyderabad,compared to Eastern India (Kolkatta)
11.7 percent, Northern India (New Delhi) 11.6 percent and Western India (Mumbai), 9.3 percent.
Anjana et al. (2011) reported that India would be 62.4 million people with diabetes and
77.2 million people with prediabetes. The studies also reported from the results of the first phase
of national study ICMR-INDIAB (2008-2011) to determine the prevalence of diabetes and
prediabetes in three states and one union territory of India that the prevalence of diabetes in
Tamilnadu was 10.4 percent, Maharashtra-8.4 percent, Jarkhand-5.3 percent and Chandigarh
13.6 percent. The prevalence of prediabetes was reported as 8.3 percent in Tamilnadu, 12.85
percent in Maharashtra, 8.15 percent in Jarkhand and 14.6 percent in Chandigarh.
Anjana et al. (2015) presented the incidence of diabetes and prediabetes and the
predictors of progression in a population based Asian Indian cohort in an article on 10 years
follow-up of the Chennai Urban Rural Epidemiology Study (CURES) and concluded that Asian
Indians have one of the highest incidence rates of diabetes with rapid conversion from
normoglycaemia to dysglycaemia.
According to IDF (2015) reports, Indian had 69.1 million cases of diabetes in 2015, with
8.7 percent adults (20-79 years). According to a meta analysis by Nanditha et al. (2016) India has
more than 65.1 million people with diabetes, occupying the second position next to China in the
IDF global list of top 10 countries for people with diabetes and also mentioned that occurrence of
type 2 diabetes at a younger age is observed among South Asians. ICMR (2018) reports that as per the
International Diabetes Federation (IDF) estimates, there were 72.9 million people with diabetes
in India in 2017, which is projected to rise to 134.3 million by the year 2045. The prevalence of
diabetes in urban India, especially in large metropolitan cities has increased from 2 percent in the
1970s to over 20 percent at present and the rural areas are also fast catching up.
2.6. Managementofdiabetes:
Diabetes cannot be cured completely, but it is to be managed with proper diet, physical
activity and healthy life style along with the medication prescribed by the physician for leading a

16. healthy normal life. American Diabetes Association suggested that early detection and
hypoglycaemic medication are considered as the primary care for the type 2 diabetes patients.
Literature related to the dietary management and the role of physical exercise and nutrition
counseling in the management of diabetes is presented in the following text.
2.7. Dietary management:
The diabetes diet generally is planned with unnecessary restrictions, inclusion of certain
monotonous food items such as roti for rice eaters, ragi porridge etc., which might be due to
misconceptions, unawareness of the disease and role of diet in its management. In contrast, over
enthusiasm among the literates about the dietary management of diabetes is leading to
unnecessary confusion in the choice of foods and diet plans. This results in either over-nutrition
or under-nutrition of the diabetics. Any restriction on food for a patient will have negative effect
on the psychological aspects of the patient so it is necessary to bring awareness among the
people with type 2 diabetes about their diet for better choice of food. In India any modification
in diet should consider the regional influences on lifestyle, diversity in culinary practices,
economic issues and local cultivation considerations to improve the acceptance among people
with Type 2 Diabetes. The evidence based literature on the role of diet in the management of
diabetes and various dietary approaches to reach the primary goal of achieving normal blood
glucose levels and to promote overall nutritional well being is furnished in the following text.
Before planning a diet, it is necessary to set the goals of planning a diet for people with
type 2 diabetes. The goals of nutrition therapy for type 2 diabetic patients set by American
Diabetes Association id presented in table.5..
Table.5. Goals of nutrition therapy for type 2 diabetes mellitus* as per American Diabetes
Association
S.No Biochemical parameter Goal
1 HbA1c <7%
2 Blood pressure <140/80mmHg
3 LDL-C <100 mg/DL
4 Triglycerides <150 mg/DL
5
HDL-C
>40 mg/Dl for Men
6 >50 mg/Dl foe women
*American Diabetes Association.
ICMR had suggestedtargetsformetaboliccontrol indiabetesforAsianIndiansinthe guidelinesfor
diabetes,whichmayslightlydifferfromthatof international targets.The ideal targetssuggestedby
ICMR for AsianIndiandiabeticsforthe managementof type 2 diabetesare shownintable.6.
Table.6. Ideal targetsfor the managementof diabetesforIndiansbyICMR*
S.No Parameter Ideal target
1 FastingPlasmaGlucose (mg/dl) 80 -110
2 2 hourPostprandial Glucose (mg/dl) 120 – 140
3 Bloodpressure (mmHg) < 130/80

17. *Source ICMR (2018).
Bhupathiraju et al. (2014) on discussing the results of a large US cohort and an updated meta
analyses on well designed RCTs as the diabetic prevention programmes observed that following a healthy
dietary pattern along with life style modification are as effective as or even better than pharmacologic
interventions in preventing type 2 diabetes. Existing guidelines of WHO (2016) for dietary management
of type 2 diabetes recommended a lower calorie intake for overweight and obese patients, and replacing
saturated fats with unsaturated fats,intake of dietary fibre equal to or higher than that recommended for
the generalpopulation and avoiding added sugars, tobacco use and excessive use of alcohol. Education of
patients in groups is a cost-effective strategy.
Kam et al. (2016) in a review on dietary interventions for type 2 diabetes explained the
importance of intervention of diet for diabetics, as to control the fluctuation of blood glucose
which causes various health complications.
2.8. Effectof individual nutrient in the diet on diabetes:
The chemical composition of foods (eg., fat, sugars, dietary fibre content) should be an
important factor influencing food choice, but simply knowing the chemical nature of the
carbohydrate in foods does not indicate their actual physiological effect (FAO/WHO, 1998).The
effect of each nutrient in the diet of a diabetes patient on glycaemic control is discussed further.
2.8.1. Energy:
Various studies explained the pathophysiology as the gradual accumulation of fat in pancreas
affects the functioning of beta cells and results in type 2 diabetes. Weight loss may not be the goal for
every diabetic but reducing the calorie intake may rectify the resulting hyperglycaemia.
A review by Asif (2014) on prevention and control of the type 2 diabetes by changing life
style and dietary pattern, mentioned the following recommended daily energy intake (Kcal/day)
for diabetics:
a) Non-obese diabetic-Between 1500-2500, average allowance 2000 Kcal/day
b) Overweight diabetic-between 800-1500,
c) Under weight diabetics- at least 2500 (including growing children and adolescents).
Various studies have reported that the distribution of total calories from macro nutrients is also to
be considered while planning a diet for people with type 2 diabetes. ADA (2015) reported that
according to various studies, type 2 diabetic people eat on an average 45 percent of calories from
carbohydrates, 36-40 percent from fat and 16-18 percent from protein. There are numerous
4 BodyMass Index (kg/m2) 20 – 23
5
Waistcircumference (cms)
Men < 90
Women< 80
6 GlycatedHaemoglobin(HbAlc])(%) < 7
7 Total Cholesterol (mg/dl) < 200
8
HDL Cholesterol (mg/dl)
> 40 formen
> 50 forwomen
9 LDL Cholesterol (mg/dl) < 100
10 Non-HDLCholesterol(mg/dl) < 130
11 Triglycerides(mg/dl) < 150

18. international guidelines available for the management of Type 2 Diabetes, but following the
country-specific guidelines will show better treatment outcomes in diabetes. The
recommendations by Research Society for the Study of Diabetes in India (RSSDI) and Indian Council
of Medical Research (ICMR) for medical nutritional therapy (MNT) in India for the management of type
2 diabetes mellitus are shown in brief in table.7 (Viswanathan et al., 2019).
Table.7. Recommendations for Medical Nutritional Therapy in India for type 2 diabetes mellitus.
S.No Nutrient RSSDI ICMR
1 carbohydrates 45–65% of total daily
calories (minimum intake:
130 g/day)
55–60% of total daily
calories.
2 Fibre High fiber diet: increased
intake of soluble and
insoluble fibers
Intake of fiber-rich
foods
3 Protein Recommended intake:
10–15% of total daily
calories
Recommended intake:
10–15% of total daily
calories
4 Fat Recommended calorie
intake: no specified ideal
intake
Recommended calorie
intake: 20–25% total
daily calories
5 Sugars Reduced intake of refined
sugars
Avoidance of sugar,
honey, jiggery
Fig. 2. Distribution of calories recommendedby RSSDI
cho
65%
pro
15%
fat
20%
Distribution of calories as-RSSDI

19. Fig. 3. Distribution of calories recommendedby ICMR
Figures.2 and 3 are showing the distribution of calories from the macronutrients
recommended by RSSDI and ICMR respectively.
2.8.2. Carbohydrate:
Several studies have reported that insulin needs are more closely correlated with the
carbohydrate intake than with the total calorie intake. Studies support to have most complex
carbohydrates in the form of polysaccharides like whole grains than rapidly absorbed mono and
disaccharides like sugars for type 2 diabetics. ADA reported that the total amount of
carbohydrate in meals and snacks will be more important than the source or the type, as a
number of factors influence glycemic responses to foods, including the amount of carbohydrate,
type of sugar (glucose, fructose, sucrose, lactose), nature of the starch (amylose, amylopectin,
resistant starch), cooking and food processing (degree of starch gelantinization, particle size)
food form, and other food components (fat and natural substances). Sahay (2012) mentioned that
carbohydrate content of the diet has to provide 50-60 percent of the calories and most of this is to
be in the form of complex carbohydrates with a high fiber content and low glycemic index.
All carbohydrate containing food items do not raise blood glucose to a similar extent
within the same period of time and quantification of these differences has been lead to
introduction of concept of glycemic index by Jenkins et al. (1981). While reviewing the selected
dietary approaches as interventions for the prevention and management of type 2 diabetes, Maki
and Phillips (2015) reported that the dietary carbohydrate is the primary nutrient that influences
postprandial blood glucose and insulin secretion and Glycaemic Index is a tool which allows for
the quantification of the postprandial blood glucose response to dietary carbohydrate from foods.
2.8.3. Protein:
carbohydrates
60%
Protein
15%
fat
25%
Distribution of calorires-ICMR

20. Protein is another important component of dietary strategies for type 2 diabetics and
various clinical trials reported that amino acid leucine has some positive influence on diabetic
patients. Protein intake of 0.8mg/kg is recommended, so as to contribute to 12-20 percent of the
calories. Vegetable proteins are preferable due to their high fiber content and absence of
saturated fat which is present in animal proteins (Sahay, 2012).
In a review, Venn and Green (2007) mentioned that combining foods does influence GI
and addition of protein and fat to a carbohydrate containing meal can reduce the glycaemic
response. The article on dietary substitution for refined carbohydrate for reducing risk of type 2
diabetes by Maki and Phillips (2015) illustrated that low GI and high protein was associated
with less weight gain, when compared with low protein -low GI, low protein-high GI and high
protein-high GI diets.
Kam et al. (2016) mentioned in a review that protein influences the rate of starch
digestion and can improve postprandial glycaemia in type 2 diabetics. ICMR (2018) suggested
the supplementation of foods like cereal and pulse in 4:1 ratio, e.g. idli,dosa, Missi roti, Khichdi,
Dhokla, Khandvi etc., improves the protein quality and also gives satiety.
2.8.4. Fats in the diet:
Fats are essential part of healthy diet but problem arises when consumed in excess,
especially in diabetic patients, there is a risk of blocking of vessels. ICMR (2018) recommended
that fats should provide 20-30 percent of total energy intake for people with diabetes. Goals
should be individualized as evidence is inconclusive for an ideal quantity of total fat intake for
people with diabetes and quality of fat is as important as the quantity.
The findings of a study by Frost et al. (1999) revealed that the GI of a diet is a stronger
predictor of serum HDL-C concentration than dietary fat intake. Sahay (2012) mentioned that fat
content of the diet should be 20-25 percent of the total calories distributed in the ratio of 1:1:1
among saturated fatty acids, mono unsaturated fatty acids (MUFA) and polyunsaturated fatty
acids (PUFA) for diabetics in India.
2.8.5. Fibre content in the diet:
The total dietary fibre (TDF) includes soluble dietary fibre (SDF) and insoluble dietary
fibre (IDF). The plant foods contribute to dietary fibre requirements in the diet but individual
intake is influenced by the nature of source, maturity moisture, proportion in the diet and mode
of processing and preparation of the foods. Various experimental studies revealed that high
dietary fibre in the diet can reduce blood glucose levels, serum cholesterol, avoid constipation
and makes the food low GI. This was supported by a study by Chandalia et al. (2000) that an
increase in the intake of dietary fibre (soluble type) by Type 2 diabetes patients improved
glycaemic control and decreased hyperinsulinaemia in addition to expected lowering of plasma
lipid concentration. The study also suggested that guidelines for patients with diabetes should
increase dietary fibre through the consumption of unfortified foods rather than the use of fibre
supplements. In contrary, the Meta analysis by Wheeler et al. (2012) on macro nutrients, food
groups and eating patterns in the management of diabetes, summarized that the majority of the
reviewed evidence indicated that adding fibre supplement in moderate amounts (4-19 g) to a
daily diet will show little improvement in glycaemia and CVD risk factors.

21. A study was conducted by Jenkins et al. (1982) to observe the relationship between rate
of digestion of foods and postprandial glycaemia. The in vitro study showed a significant
relationship between the glycaemic index and the food fibre content and between the GI and
glucose tapping capacity of foods. It was found that legumes as a group liberated 56 percent less
sugars and oligosaccharides than the 8 cereal foods over 5 hours.
Chandalia et al. (2000) compared the effects of two diets, one with foods containing
moderate amount of fibre (total 24 g with 8 g soluble and 16 g insoluble) and another diet with
high fibre (total 50 g with 25 g soluble and 25 g insoluble) foods on glycaemic control and
plasma lipid concentrations. It was concluded that a high intake of dietary fibre particularly of
soluble type improves glycaemic control, decreases hyperinsulinaemia and lowers plasma lipid
concentrations in patients with Type 2 Diabetes mellitus.
A cohort study by Schulze et al. (2004) with 91,249 young women, to examine the
association between GI, GL and dietary fibre and the risk of Type 2 diabetes, concluded that a
diet high in rapidly absorbed carbohydrates and low in cereal fibre is associated with an
increased risk of type 2 diabetes.
In a meta analysis by Post et al. (2012) reviewed the studies on the effect of
supplementation of 15 g/day dosage of fibre in the diet on HbA1c and FBG in patients with type
2 diabetes and found that there was statistically significant improvement in FBG and HbA1c. It
was stated that the fibre content decreases the glycaemic index of food; the decreased GI would
lead to smaller increases in blood glucose and thus reduced blood glucose and HbA1c.
A review on dietary approaches for the prevention and control of type 2 diabetes by Maki
and Phillips (2015) reported that in the Nurse’s health study, women aged 45-60 years the
combination of high GL and low cereal fibre intake produced a greater risk of type 2 diabetes
when compared with participants in both the low GL and the highest cereal fibre. It was reported
that the mechanism by which fibre decreases the risk of Type 2 diabetes might be a result of
colonic fermentation, short chain fatty acid production and effect of these fatty acids on insulin
sensitivity.
2.8.6. Calcium:
Abnormalities related to calcium are common in adult patients with type 2 diabetes.
Insulin secretion is said to be a calcium dependent process and alterations in calcium flux may
affect the insulin secretion.
Pittas e al. (2007) in a review on role of altered vitamin D and calcium homeostasis in the
development of type 2 diabetes stated from the overall evidence that vitamin D alone probably has no
effect in healthy individuals, but combined vitamin D and calcium supplementation may have a role in the
prevention of Type 2 diabetes mellitus especially in populations those with glucose intolerance. The
vitamin D and calcium deficiency influences post-prandial glycemia and insulin response while
supplementation may be beneficial in optimizing these processes. In relation to calcium intake for type 2
diabetes, the evidence suggested that intakes above 600 mg/day are desirable but intakes above 1200 mg
may be optimal.

22. 2.9. Glycaemic index (GI):
There is a dietary notion that carbohydrate-rich foods have deleterious health effects in
type 2 diabetics and so the consumption should be limited. But several evidence-based studies
have demonstrated that not all carbohydrates are equal and the variations in the physiochemical
properties of complex carbohydrates have been shown to elicit different physiological effects
when consumed. Perlstein et al. (1997) while reviewing the Glycaemic Index in diabetes
management explained the history of GI that, from as long ago as 1550 BC, carbohydrate has
been the main focus of diabetes nutrition management. Since 1930-the scientists have challenged
simple and complex carbohydrates, in 1970- examined the glycaemic impact of range of
carbohydrate containing foods and in 1981- Jenkins et al. (1981) proposed the Glycaemic Index,
initially as a tool for the dietary management of type 1diabetes and later dyslipidaemia. The
scientific literature on GI in relation to dietary management of type 2 diabetes is discussed with
the following sub-headings.
1. Definition of GI,
2. Role of low GI in diabetes diet,
3. Methodology of Calculating GI of foods,
4. Factors affecting GI,
5. Limitations of GI,
6. Suggestions on GI.
2.9.1. Definitionof GI:
The Glycemic Index (GI) is a relative ranking of carbohydrate in foods according to how
they affect blood glucose levels. According to Perlstein et al.(1997) GI is a system of classifying
foods which contain carbohydrate, based on their glycaemic response with the review that the
slower flatter response may facilitate better glycaemic control and lipid profiles in people with
diabetes. The GI is defined as the “incremental area under the blood glucose response curve of a
50 g carbohydrate portion of a test food expressed as percent of the response to the same amount
of carbohydrate from a standard food taken by the same subject” (FAO/WHO, 1998).
ADA defined that it measures how a carbohydrate-containing food raises blood glucose.
Glycaemic index values are grouped into three categories viz., low GI (GI < 55), medium GI (GI
56-69) and high GI (GI >70) (FAO/WHO, 1998) Foods containing carbohydrates that are
quickly digested have the highest glycemic index since the blood sugar response is fast and high.
Slowly digested carbohydrates have a low glycemic index, since they release glucose gradually
into the bloodstream (Brand-Miller et al., 2003). Good scientific evidence is available to suggest
that low GI foods may help to control blood glucose levels and minimize fluctuations in blood
glucose levels for people with Type 2 diabetes, which can help reduce the risk of complications
of diabetes such as heart and kidney problems.
2.9.2. Role ofLow GI in the diabetes diet:
In 1997 a committee of experts was brought together by FAO and WHO to review the
importance of carbohydrate in human nutrition and health. The committee endorsed the use of
the GI method for classifying carbohydrate rich foods and recommended that the GI values of
foods be used in conjunction with information about food composition to guide food choices

23. (Foster-Powel et al., 2002). But in choosing the foods, both GI and food composition must be
considered. Some low GI foods may not always be good because they are high in fat.
Conversely some high GI foods may be a good choice because of convenience or because they
have low energy and high nutrient content (FAO/WHO, 1998). Insulin sensitivity and
concentrations of HDL-Cholesterol, the two metabolic predictors of CHD are influenced by diet.
Dietary carbohydrate with high GI cause a high postprandial glycaemia and insulin response and
are associate with decreased insulin sensitivity and an increased risk of CHD. (Frost et al., 1999).
Brand et al. (1991) compared a low GI diet (eg., porridge, pastas) with a high diet (eg.,
processed cereals and potatoes) on 16 subjects in the treatment of NIDDM (Type 2 diabetics).
The GI of low GI diet was 15 percent lower than that of high GI diet in the study. Results
showed that the glycaemic control was improved on the low GI diet compared with high diet. It
was concluded that low GI diet gives a modest improvement in long term glycaemic control but
not plasma lipids in normolipidaemic well controlled subjects with NIDDM.
The glycaemic index was considered as the beginners’ guide by some researchers.But GI has
proven to be a more nutritional concept than is the chemical classification of carbohydrate (as
simple, complex or sugars or starches or as available or unavailable) permitting new insights into
the relation between physiological effects of carbohydrate rich foods and health (Foster-Powel et
al., 2002). Brand-Miller et al. (2003) opined that low GI dietary advice seems to improve
glycemic control same as newer pharmacological agents which gives patients a choice as well as
reduces the size of the health care burden.
The GI is useful to rank foods by developing exchange lists of categories of low GI foods
such as legumes, pearled barley, lightly refined grains (e.g, whole grain pumpernickel bread or
breads made from coarse flour) pasta etc (FAO/WHO, 1998). In a meta analysis by Bjorck et al.
(2000) on low GI foods, it was indicated that certain low GI breakfasts, capable of maintaining a
net increment in blood glucose and insulin at the time of the next meal, reduced postprandial
glycaemia and insulinaemia significantly following a standardized lunch meal, where as others
had no second meal impact.
Venter (2005) in an editorial mentioned that, clinical trials have shown that low GI diets
improve glycaemic control in diabetes, increase insulin sensitivity and beta cell function, reduce
food intake and body weight, influence memory and may improve blood lipids. The hypothesis
for the underlying mechanism of action that leads to low GI foods is that the carbohydrate in
those foods is absorbed slowly (Jenkins, 2007).
Jenkins et al. (2008) conducted a study to test the effects of low GI diets on glycaemic
control and cardio vascular risk factors in Type 2 Diabetes patients and concluded that 6
months treatment with a low GI diet resulted in moderately lower HbA1C levels compare with a
high cereal fibre diet.
A meta analysis of RCTs was performed by Brand Miller et al. (2003) to determine
whether low GI diets compared with conventional or high GI diets, improve overall glycaemic
control in individuals with diabetes. The results showed that low GI diets reduced HbA1c by
0.43 percent points over and above that produced by high GI diets. The analysis concluded that

24. choosing low GI foods in place of high GI foods or conventional foods has a small but clinically
useful effect on medium term control in patients with diabetes.
A meta analysis was done by Opperman et al. (2004) to critically analyze the scientific
evidence that low GI diets have beneficial effects on carbohydrate and lipid metabolism
compared with high GI diets and found that low GI diets reduced HbA1c by 0.27percent, total
cholesterol by 0.33 mmol/l and LDL- cholesterol by 0.15 mmol/l in type 2 diabetics. The
analysis found no changes in HDL- cholesterol and triglycerides, compared with high GI diets.
Results of this analysis supported the use of GI as a scientifically based tool to enable selection
of carbohydrate containing foods to reduce total cholesterol and to improve overall metabolic
control of diabetes.
Aston (2006) discussed the association of low GI diets with various metabolic risk factors
and opined that low GI foods may increase satiety and delay the return of hunger compared with
high GI foods, which could translate into reduced energy intake at a later time points. He also
expressed that there is much interest in GI from scientists, health professionals and the public but
more research is needed for drawing conclusion about the relationship with metabolic disease
risk.
Jenkins (2007) in a review on 25 years of research on GI, concluded that it allows foods
to be ranked on the basis of the postprandial glyceamia these foods produce and consumption of
low GI diets has been associated with reduced incidence of heart disease, diabetes and also some
forms of cancer. Venn and Green (2007) concluded in a review that high GI carbohydrates
suppress short term (1 hour) food intake more effectively than a low GI carbohydrate, where as a
low GI carbohydrate appeared to be more effective over longer periods (6hours).
A pilot study by Ma et al. (2008) concluded that a low GI diet is viable alternative to the
standard ADA diet and low GI diet achieved equivalent control of HbA1c using less diabetic
medication. Thomas and Elliott (2009) assessed the effect of low GI and GL diet on glycaemic
control in people with diabetes and concluded that a low GI diet can improve glycaemic control
in diabetics without compromising hypoglycaemic events. A thematic review on metabolic effect
of low GI diet by Radulian et al. (2009) concluded that long term compliance to low GI diets
acutely induce favourable effects like rapid weight loss, decrease of fasting glucose and insulin
levels, reduction of circulating triglyceride levels and improvement of blood pressure. The
reduced hyperinsulinaemia associated with a low GI diet may reduce CVD risk through effects
on oxidative stress, blood pressure, serum lipids, coagulation factors, inflammatory mediators,
endothelial function and thrombolytic function.
A study by Jenkins et al. (2012) tested the effect of increased intake of legumes (1 cup/day) as
part of low GI diet in the treatment of Type 2 Diabetes, on glycaemic control, serum lipid levels and
blood pressure. The results showed a reduction in HbA1c by 0.5 percent and a relative reduction in
systolic blood pressure. Wolever et al. (1992) compared the effect of low GI diet (GI-58) with high GI
(GI-86) diet on 6 overweight NIDDM subjects with a randomized cross over design for 6 week duration

25. and found that in low GI diet, the mean serum fructoseamine level was lower than high GI diet by 8
percent and total cholesterol was lower by 7 percent. The study concluded that in overweight patient s
with NIDDM,a low GI diet will improve overall blood glucose and lipid control. Pande et al. (2012)
conducted a prospective study to report significant hypoglycaemic and hypolipidaemic effects in type 2
diabetic subjects who were on complete diet plan with low glycaemic index (GI) and low-medium
glycaemic load (GL) Indian vegetarian snacks and mixed meals for 4 continuous weeks. The results
showed a positive decrease in blood glucose levels and improvement in lipid profile.
In an interventional study, to investigate the effect of a low glycemic index-low glycemic load
(GL = 67–77) diet on lipids and blood glucose of poorly controlled diabetic patients, Afaghi et al. (2012)
administered a low GL diet (energy = 1800–2200 kcal, total fat = 36%, fat derived from olive oil and nuts
15%, carbohydrate = 41%, protein = 22%) to 100 poorly controlled diabetic patients for 10 weeks. The
results showed that HbA1c percentage was reduced by 12 percent and body weight significantly reduced
from 74.0 kg to 70.7 kg. The study demonstrated that low GL diet having lower carbohydrate amount and
higher fat content is an appropriate strategy in blood lipid and glucose response control of type 2 diabetic
patients.
The updated analyses from three large US cohorts and meta analyses by Bhupathiraju et
al. (2014) on the association of glycaemic index and glycaemic load with type 2 diabetes mellitus
provided evidence that higher GI and GL are associated with increased risk of type 2 diabetes
mellitus. The study also showed that the participants who consumed diets that are low in cereal
fibre but with a high GI or GL have an elevated risk of type 2 diabetes.
The studies reviewed by Maki and Phillips (2015) explained that the consumption of high
GI foods which are rich in refined carbohydrates induces a rapid increase in blood glucose
concentration and thus a high demand for pancreatic insulin production, which could lead to
exhaustion of pancreatic β cells and development of type 2 diabetes.
The effect of consumption of desserts with low glycemic index and low glycemic load on
anthropometric and biochemical parameters in patients with type 2 diabetes mellitus was examined by
Argiana et al. (2015) and found a positive impact on arterial blood pressure,fasting blood glucose and
glycosylated hemoglobin at endpoint. It was also observed that anthropometric measurements like body
weight, body mass index and waist circumference were reduced significantly.
A randomized, controlled crossover non blind design, by Kaur et al. (2016) was done to
simultaneously investigate glucose excursion and substrate oxidation in a whole body calorimetre in 12
healthy Chinese male adults attended two sessions consisting of either four low or high glycaemic
meals. The results revealed that, after Low GI meals in the whole body calorimetre, IAUC for glucose
was lower compared to the High GI session. The investigators concluded that the consumption of low GI
meals may be a strategic approach in improving overall glycaemia and increasing fat oxidation in Asians
consuming a high carbohydrate diet.
In a systematic review and meta analysis of Randomized Controlled Trials, Ojo et al. (2018)
concluded that the low GI diet is more effective in controlling HbA1c ( improvement by 0.5%) and
fasting blood glucose level when compared with a high GI diet in patients with type 2 diabetes.
2.9.3. Methodologyofcalculating GI of foods:

26. The GI of food is determined by comparing the acute glycaemic response of a test food to
a standard food in individual subjects. Initially glucose was used as the standard food but
because of the concerns of excessive sweetness and the osmotic effect of glucose solutions, it
was suggested that white bread of known composition be utilized. In this case a conversion
factor is used to compare the results. If white bread is used, it can be multiplied by a conversion
factor of 0.7 to compare it to a glucose standard or if glucose is used as the standard, it can be
multiplied by a conversion factor of 1.4 to compare it to a white bread standard. (Perlstein et al.,
1997).
The glycemic index of a food is defined as the incremental area under the two-hour blood glucose
response curve (AUC) following a 12- hour fast and ingestion of a food with a certain quantity of
available carbohydrate (usually 50 g). The Area under the curve (AUC) of the test food is divided by the
AUC of the standard (either glucose or white bread) and multiplied by 100. Both the standard and test
food must contain an equal amount of available carbohydrate. The result gives a relative ranking for each
tested food (Brouns et al., 2005). The review elaborated the methodology of GI calculation of foods.
The study by Jenkins et al. (1981) was to determine the effect of different foods on the
blood glucose. Sugars and 62 commonly eaten foods were fed individually to groups of 5 to 10
healthy fasting volunteers and blood sugar levels were measured over 2 hours. It was expressed
as percentage of the area under the glucose response curve when the same amount of
carbohydrate was taken as glucose.
The study by Radhika et al.(2010) elaborated the procedure to evaluate the glycaemic
index (GI) of newly developed 'atta mix' roti with whole wheat flour roti in 18 healthy non-
diabetic subjects, who consumed 50 g available carbohydrate portions of a reference food
(glucose) and two test foods in random order after an overnight fast. The reference food was
tested on three separate occasions, while the test foods were each tested once. Capillary blood
samples were measured from finger-prick samples in fasted subjects (- 5 and 0 min) and at 15,
30, 45, 60, 90 and 120 minutes from the start of each food. For each test food, the incremental
area under the curve and GI values were determined. The results showed that the GI of atta mix
roti (27.30) was considerably lower than the whole wheat flour roti (45.1) and concluded that
development of foods with lower dietary glycaemic could help in the prevention and control of
diabetes in South Asian populations, which habitually consume very high glycaemic load diets.
Premakumari et al. (2013) evaluated the glycaemic index of recipes with rice bran to see
the effect of plant fibre in the diets of diabetics on postprandial glycaemia. The GI test was done
in 10 healthy volunteers (adult men and women) of age 20-40 years, by taking glucose as the
reference food.
A study was undertaken by Aston et al.(2007) to determine the glycaemic index (GI) of
various staple carbohydrate-rich foods including various breads, breakfast cereals, pasta, rice and
potatoes, all of which were commercially available in the UK diet and to consider the factors
influencing the GI in 42 healthy adult volunteers. The GI values of 33 foods were measured

27. according to the WHO/FAO recommended methodology. It was stated that the results illustrated
a number of factors which are important in influencing the GI of a food, highlighting the
importance of measuring the GI of a food, rather than assuming a previously published value for
a similar food and concluded that this is useful both to researchers analyzing dietary surveys or
planning intervention studies, and also to health professionals advising individuals on their diets.
2.9.4. Factors affecting GI:
Report of a Joint FAO/WHO Expert Consultation (1998) detailed the factors that influence the
glycaemic properties of foods as, amount of carbohydrate, nature of monosaccharide components
(glucose, fructose, galactose),nature of starch (amylase, amylopectin, starch-nutrient interaction, resistant
starch), cooking or food processing (degree of starch gelatinization, particle size, food form, cellular
structure), other food components (fat and protein, dietary fibre, antinutrients, organic acids).
The analysis on GI in diabetes management by Perlstein et al. (1997) revealed that GI of the food
is affected by factors like nature of carbohydrate, seasonalfactors, type of starch present in the food,
physical form of food and processing, fibre, anti-nutrients, fat and protein content. In addition to these,
Eleazu (2016) in a review on low GI and GL also mentioned some more factors like amylose-amylopectin
ratio, gelatinization, insulin response, variety, particle size and acidity that have an effect on GI of foods.
This will help in making foods low glycaemic by adding protein or fibre with minimum
processing and also in planning low glycaemic formulations for people with type 2 diabetes
mellitus.
2.9.5. Limitations of GI:
Several studies have pointed out that low GI diets have got certain limitations. Mostly the
concept of GI is misused by people in relation to its numerical figures and many health
professionals and people with diabetes view these figures as the sole factor in determining the
suitability of food e.g., Chocolate as low GI –suitable and potato as high GI-unsuitable (Perlstein
et al., 1997).
Venter (2005) in an editorial, mentioned that there is a significant scientific
disagreement among academicians and clinicians as to whether there is true physiological benefit
in consuming a reduced GI or GL diet and lack of data promote controversy.
Venn and Green (2007) consolidated the weak points questioned by several studies on the
usefulness of GI in a review as GI fails to consider the insulin response, there may be the intra
and inter subject variation in glucose response to a food, a loss of discriminating power when
foods are combined in a mixed meal, foods with a high sugar content and those containing both
carbohydrate and fat may have a low GI but may not be regarded as particularly appropriate
choices because of their energy density and nature of dietary fat.
Jenkins (2007) while looking back into 25 years of research on GI found that the major
limitations of following a low GI diet are a lack of acceptable low GI foods. This review also
suggested that food industry must look into production of foods that are not only palatable and
fast to prepare but also slow to digest. The literature concerning GI and GL in individuals with

28. diabetes is complex, although demonstrated a reduction in A1C of 0.2 percent to 0.5 percent in
some studies (ADA, 2015).
2.9.6. Suggestions on Glycaemic Index :
Perlstein et al. (1997) suggested that the GI concept should be incorporated into the client
education because it is an unfamiliar concept to both health professionals and to people with
diabetes and its use may be complicated by old beliefs. The analysis also recommended for a
future research and development in the areas of GI and diabetes prevention, GI and food
industry, resource materials and teaching methods and health professional training.
The joint committee of FAO and WHO (1998) expressed that there is a need to study a large
number of subjects under standard conditions to obtain more precise estimates of the GI and GL of
individual foods.
Brouns et al. (2005) suggested that RCTs on low GI diets will decide the role and value of the GI
as a therapeutic modality and they should be with reasonable number and duration (months and years
rather than weeks and days). Wheeler et al. (2012) in the meta analysis on eating patterns also suggested
for the development of standardized definitions of low GI and to address the low retention rates on lower
GI diets.
A study by Evert et al.(2014) on nutrition therapy for the adults with diabetes recommended
multiple meal planning approaches and eating patterns for achieving metabolic goals and suggested for
future research,to develop standardized definitions for high and low GI diets for evaluation of their
impact on glycaemic control.
2.10. Glycaemic Load(GL):
The glycaemic response to an ingested food not only depends on the GI but also on the
total amount of carbohydrates ingested, and this led to the concept of Glycaemic Load. GL
accounts for how much of carbohydrate is in the food and how each gram of carbohydrate in the
food raises blood glucose levels.
Mathematically, GL = GI × available carbohydrate (g) /100
Where available carbohydrate = total carbohydrate - dietary fiber. GL is classified as: low (< 10),
intermediate (11–19) and high (> 20). GL is a metric used as a basis for weight loss or diabetes
control. (Eleazu, 2016).
The concept of GI had been extended to take into account the effect of the total amount
of carbohydrate consumed. Thus the glycaemic load, a product of GI and quantity of
carbohydrate consumed provides an indication of glucose available.
Eleazu (2016) in a review on the concept of low GI and GL foods, the author suggested that in
view of discrepancies on the results of GI versus GL of foods, any assay on the GI and GL of a food could
be balanced with glycated hemoglobin assays before they are adopted as useful antidiabetic foods.
2.11. Low GI Formulations for diabetes:

29. Many views had been expressed on the role GI in a diet in the management of diabetes and
severalsuggestions had been made to the diabetic diets. Various studies had shown that different foods
raise the blood sugar to variable extent and exhibit different glycemic responses,but when the individual
food is used in a mixed meal or in mixture of certain foods, it exhibits glycemic response in a different
way. This helps in formulating low GI mixtures for nutrition interventions, emphasizing a variety of
locally available manually processed nutrient dense foods, in appropriate proportions and portion sizes for
the individuals with diabetes as practical tools for day-to-day food plan.
In the last 20 years nearly 300-400 separate foods and mixed meals have been subjected to GI
testing in both normal and diabetic individuals all around the world but methodological differences
created confusion regarding clinical interpretation of GI of foods, so the results of different studies have
not been directly comparable. (Venn and Green, 2007).
Itagi (2003) conducted a study to exploit the nutritional and clinical efficacy of a millet based
diabetic composite food among local people and popularize the product. A composite diabetic mix was
developed from regional millets like foxtail and little millet (80%) along with wheat (10%) and black
gram dal (10%) and spice mixture (8%). These millets increased four times its volume after cooking thus
providing 19-22 per cent of dietary fibre. The glycaemic index was noted in six non diabetics when
tested against 50 g carbohydrate load. Intervention study of four weeks (80 g mix/day) revealed that the
blood glucose in six non-diabetics and nine diabetics reduced to 17 and 19 percent and HDL cholesterol
increased to 2 and 6 per cent respectively. Besides, intervention with foxtail millet mix exhibited
considerable reduction in triglycerides without apparent changes in total cholesterol values in
experimental volunteers as compared to little millet mix. In feeding trial (4 weeks),60 per cent of
diabetics switched over to normal ratio at TC;HDL and LDL.HDL cholesterol along with maintenance of
body weight. As part of the study, the therapeutically potential diabetic mix was popularized through print
media exhibitions, melas, displays and seminars in many diabetic centres,health clubs and clinics.
Jenkins et al. (2007) in a review on research over 25 years opined that GI has potential
therapeutic utility and to make it a practical reality, the food industry would be instrumental in developing
a wider range of readily available and acceptable low GI foods.
Jenkins et al. (2008) included low GI breads (including pumpernickel, Rye pita, quinoa and flax
seeds),breakfast cereals (Large flake oat meal, oat bran and bran buds), pasta,parboiled rice, beans, peas,
lentils and nuts in the low GI diet while testing the effects of low GI diet on glycaemic control and
cardiovascular risk factors in T2 DM patients.
Ankita (2005) conducted an experiment to develop a composite flour with wheat,bajra, maize,
flaxtail millet, Bengal gram and barley and evaluate quality of the low glycaemic composite flour for
missi roti. GI was evaluated in both diabetic and non-diabetics. It was found that the composite flour
made with wheat, Bengal gram and barley in 3:1:1 ratio was acceptable with the lowest GI (50±21.29)
and so suggested for diabetic patients in place of plain flour.
A study was conducted by Rajvinder.et al.(2008) to find out the impact of indigenous fibre rich
therapeutic premix containing locally available ingredients like wheat, Bengal gram, dried peas, defatted
soya flour, barley and fenugreek seeds in different proportions, on blood glucose levels of 30 type 2
diabetics (41-50 years of age). The premix was given as chapathi in the breakfast for 90 days to the
selected subjects. The results revealed that there was a significant reduction in FBG and PPGafter 90
days. It was also observed that the there was a decrease in the diabetic symptoms among the subjects and
dosage of hypoglycaemic drug was reduced after the supplementation.

30. Ankita et al. (2010) had undertaken an investigation to make use of the therapeutic quality of
wheat in the formulation of supplementary foods for the better and effective management of type 2
diabetes. Glycaemic index, Rheological feasibility, sensory acceptability and other functional properties
of three products, chapati, dhalia and noodles prepared with dicoccum wheat as base ingredient along
with some suitable functional ingredients were done and found that inclusion of hypoglycaemic
ingredients made all the three designed foods into low glycaemic category with dhalia (35.20) having
lowest, followed by chapati (41.49) and noodles (43.58). The glycaemic load calculated, also followed the
similar trend with designed dhalia (6.04) having lowest followed by chapati (7.38), and noodles (8.25)
compared to the control ones. The study suggested to include the enriched dicoccum wheat chapatiin the
diet for the management of diabetes more effectively and to avoid further secondary complications.
Ijarotimi et al. (2015) in a study, formulated and evaluated nutrient compositions and
antidiabetic potentials of multi-plant based functional foods from locally available food materials.
In the study, the food materials were processed as raw,blanched and fermented flour samples and
blended to obtain nine different samples and the glycaemic index and anti-diabetic potentials were
determined using rat models. The findings of the study showed that these functional foods contain
appreciable amount of protein, fiber, carbohydrate content within the recommended value for diabetic
patients, low glycaemic index and glycaemic load properties and with antidiabetic activities which were
statistically comparable to metformin (a synthetic anti-diabetic drug). The study recommended the
formulated functional foods for individuals at risk of diabetes or diabetic patients.
Ahmed and Urooj (2015) compared in vitro hypoglycemic effects and starch digestibility
characteristics of wheat based composite functional flour for diabetics. In the study, two composite flours
were formulated using wheat,psyllium, barley and oat at two different levels [product I with wheat flour
(75 %), psyllium (5 %),oat (10 %) and barley (10 %) and product II with wheat flour (60 %),psyllium
(10 %), oat (15 %) and barley (15 %)]. Chapathies were prepared from all formulations and various
starch fractions were analyzed using controlled enzymatic digestion. Product-I showed better starch
digestibility characteristics with significantly lower starch digestibility index. It was suggested that
consumption of the composite flours might be helpful in establishing stable blood glucose pattern due to
the redistribution of nutritionally important starch fractions and inhibition of carbohydrate digestion in the
gastrointestinal tract.
Hossain et al. (2018) developed a low Glycemic index multi wholegrain flour for diabetic persons
as well as for people of all age groups and assessed for glycaemic index and compared with the market
flours. The product was found to be a high energy value supplementary food source with high nutrition.
The study reported that the results of this study were highly inspiring the people to utilize multi
wholegrain flour in food preparation particularly in the preparation of bread.
2.12. Food ingredients of the developed low GI multigrain mix:
The medicinal effects and health benefits of foods have been recognized in India since many
centuries. The present day planning of therapeutic diets based on functional foods can be applied to many
Indian traditional foods like whole grains, legumes, oilseeds, nuts, vegetables, fruits, spices, condiments,
and many fermented products. Consumption of such foods on a regular basis not only provides required
nutrients in adequate quantities but also improves health, immunity and also prevents some disorders. The

31. nutritive value and health benefits of following ingredients used in the formulation of the low glycaemic
index multigrain mix in the present study are discussed here.
1. Barley
2. Wheat
3. Finger millet
4. Soya bean
5. Kalonji
6. Drumstick leaf powder
2.12.1.Barley(Hordeum vulgare L):
National barley food council (NBFC, 2017) recommended barley (Plate No.1) as a smart choice
for type 2 diabetes and pre-diabetes, because it contains essential vitamins, minerals and excellent source
of dietary fibre particularly β-glucan which promotes healthy blood sugar by slowing down the glucose
absorption. Referring to findings of a clinical trial, the council mentioned that subjects who ate muffins or
cookies enriched with barley β-glucan experienced significant reductions in glucose and insulin responses
compared to that with corn starch or whole wheat flour.
Plate.No.1. Barley seeds
NBFC explained very clearly in comparison with other grains that, regardless of the form of
grain, whether whole grain or processed, barley supplies a ready source of β-glucan soluble fibre
throughout the kernel. Barley is a great source of dietary fibre, both soluble and insoluble fibre. The
soluble fibre is effective in reducing the risk of heart disease by lowering blood cholesterol and reduces
the risk of type 2 diabetes by slowing down the absorption of sugar. The insoluble fibre helps in lowering
the risk of colon cancer by maintaining regular bowel movement.
NBFC also mentioned that a serving of barley contains less than half gram of fat and only 100
calories with plenty of vitamins and mineral like niacin, thiamine, selenium, iron, magnesium, zinc,
phosphorus and copper. Barley is rich in antioxidants and phytochemicals also which help decrease the
risk of certain diseases such as CVD, diabetes and cancer.
Robyn (2010) called barley as a ‘secret weapon to help control diabetes’, which has a unique
profile of nutrients to make it a great defender and was once known as a ‘food of the gladiators’. The
author explained that the soluble fibre present in barley has the ability to form a gel when it is mixed with
liquids in the stomach, and the gel slows down the emptying of the stomach which prevents carbohydrates
from being absorbed too quickly and raising the blood glucose levels. The articles had given the nutritive
value of barley as one cup of cooked whole grain barley contains 14 g of total fibre (Soluble fibre-3g and
insoluble fibre-11g), one cup of cooked pearl barley contains 6 g of total fibre (soluble fibre-2 g and

32. insoluble fibre-4g). GI is 25 and rich in magnesium, a mineral which acts as a co-factor in more than 300
enzymes in the body including those involved in the production and secretion of insulin and the use of
glucose.
Mishra et al. (2010) in an analytical review of plants for anti diabetic activity explained that the
chemical constituents of barley are saponin, tannin and lignin and the effect of it on diabetes is by
decreasing plasma triglyceride level and insulin sensitizing activity.
Mirmiram et al. (2014) reviewed several studies on the effects of barley and its products on
glucose tolerance and insulin resistance index and attributed the beneficial effects of barley to its high
content of β-glucan. The review stated that in a randomized cross over study, cooked barley with white
rice reduced area under the curves of plasma glucose and insulin concentrations and also increased
satiety. It also mentioned the investigations on the hypolipidaemic properties, antioxidant and anti-
inflamatory activities of barley products.
2.12.2.Wheat(Triticum aestivum):
Wheat (Plate No.2) is a worldwide staple food and the most common food preferred to have, in
place of rice, by most of the individuals with type 2 diabetes mellitus in India. The major wheat species
grown throughout the world is Triticumaestivum,usually called ‘common’ or ‘bread’ wheat. Wheat is not
only a major source of starch and energy but also provides a number of components which are essential or
beneficial for health like protein, vitamins, dietary fiber, and phytochemicals. Various studies on the
potentials of wheat in the treatment and dietary management of diabetes are discussed here.
Plate.No.2. Whole wheat grains
Kumar et al. (2011) in a review on the nutritional contents and medicinal properties of wheat
opined that, it is essential to understand the molecular and genetic control of various aspects of plant
growth of wheat, to enhance the quality as well as the quantity of proteins, starches and the content of
vitamins, essential amino acids, minerals and other healthy components of wheat. It was mentioned that
the whole wheat,which includes bran and wheat germ, provides protection against diseases like diabetes
by improving insulin sensitivity and decreasing the disordered insulin function.
The results of a review on functional foods based diet for the management of type 2 diabetes by
Mirmiram et al. (2014) showed that wheat bran and whole wheat are rich sources of magnesium which is
a cofactor of enzymes involved in glucose metabolism and insulin secretion, potassium, dietary fibre,
phenolic acids, tocopherols, carotenoids and antioxidants. The analysis reported that whole wheat could
improve postprandial glucose response, HbA1C, lipid disorders and other CVD risk factors in diabetes
patients

33. According to a case report presented by Eapen (2017) when a diabetic patient incorporated wheat
porridge for his breakfast and dinner along with other food, the PPGcame down and shot up when the
patient stopped taking wheat porridge. This had drawn a conclusion that the diet modification with whole
grains and legumes had protective role in lowering the postprandial glycaemia. The review by
Visvanathan et al. (2019) recommended to fortify wheat flour with soluble viscous fibre and legume flour
(eg., gaur gum, chick pea flour, barley etc) for people with type 2 diabetes.
2.12.3.Fingermillet (Ragi)((Eleusine coracana L) :
Finger millet (Plate No.3) is grown extensively in various parts of India and Africa. In India, after
wheat,rice, maize, sorghum, and bajra, ragi ranks sixth position in production. Ragi has high content of
calcium (0.38%), dietary fibre (18%) and protein (6%–13%) with vitamin A, vitamin B and phosphorus.
Ragi is considered as an ideal food for diabetics because of its low sugar content and slow release of
glucose into the blood. (Priyanka et al., 2017).
Plate.No.3. Finger Millet
LakshmiKumari and Sumathi (2002) studied the effect of consumption of finger millet based
diets on hyperglycemia in six type 2 diabetic subjects. All the experimental diets were planned to contain
75 g equivalent of carbohydrate load to compare glycemic response with a 75 g glucose load. The results
revealed that the consumption of finger millet based diets significantly lowered the plasma glucose levels,
mean peak rise, and area under the curve which was attributed to the higher fiber content of finger millet
and the presence of antinutritional factors in whole finger millet flour, known to reduce starch
digestibility and absorption, when compared to that of rice and wheat.
The analysis on millets by Kam et al. (2016) mentioned that there are evidences to support that
millet protein can increase insulin sensitivities and reduce blood glucose and triglyceride levels. Also
mentioned that millets are high in nutritional content, gluten free,have low GI, high energy, high dietary
fibre and protein with balanced amino acid profile. The review mentioned a study on diabetic rats which
demonstrated that finger millet may help reduce subcapsular cataract and may reverse
hypercholesteraemia.
2.12.4.Soya bean(Glycine max):
The soya bean (Plate No.4), native to East Asia, is a species of legume widely grown for
its edible bean. It is the most important bean economically, providing vegetable protein for

34. millions of people in the world and ingredients for many chemical products. Soya bean has got
several uses like soya milk, from which tofu and tofu skin are made. Fermented soya foods
include soya sauce, fermented bean paste. Defatted soya bean meal is a fat-free cheap source of
protein for animal feeds and many packaged meals. Soya bean products, such as textured
vegetable protein (TVP), are used as meat and dairy substitutes.
Soya chunks (Plate No.5) are defatted soya flour product, a by-product of extracting soya
bean oil. It is often used as a meat analogue or meat extender. It is quick to cook, with
protein content comparable to certain meats. It is a low cost, high protein content with long shelf
life. Soya beans contain significant amounts of phytic acid, dietary minerals like calcium, iron,
magnesium, phosphorus, potassium and B vitamins thiamin. The seeds contain 17 percent oil and
63 percent meal, 50 percent of which is protein (“Soyabean”, n.d.) Because soya beans contain
no starch, they are a good source of protein for diabetics.
Plate No.4. Soya bean seeds
Plate.No.5. Defatted soya chunks
In a study by Anderson et al. (1998) substituted soya protein as half of the daily protein
intake, for animal protein to observe the therapeutic value in diabetic nephropathy with resultant
slowing of deterioration of renal function and decreasing proteinuria, in 8 type 2 diabetes

35. patients with obesity, hypertension, and proteinuria. The results showed no distinct effects on
renal function or proteinuria in the subjects and soya-protein intake was also associated with a
significant reduction in serum cholesterol and triacylglycerol concentrations. It was concluded
that further studies are required in this aspect.
Hermansen et al. (2001) conducted a crossover trial to evaluate the effect of dietary
supplement of soya protein, isoflavones, and cotyledon fiber (Abalon) on cardiovascular risk
markers, blood glucose, and insulin levels in twenty type 2 diabetic subjects. The subjects were
randomized to double-blind supplementation for 6 weeks with Abalon (soya protein -50 g/day)
with high levels of isoflavones (minimum 165 mg/day) and cotyledon fiber (20 g/day) or placebo
(casein -50 g/day) and cellulose (20 g/day), with a 3-week wash-out period. The results reported
that beneficial effects were observed with dietary supplementation of Abalon on cardiovascular
risk markers in type 2 diabetic subjects.
Reynolds et al. (2006) conducted a meta analysis in which 41 randomized controlled trials with
isolated soya protein supplementation, with an objective to examine the effect of soya protein
supplementation on serum lipid levels in adults. The analysis reported that soya protein supplementation
was associated with a significant reduction in mean serum total cholesterol (-5.26 mg/dl), low-density
lipoprotein cholesterol (-4.25 mg/dl), and triglycerides (-6.26 mg/dl) and a significant increase in high-
density lipoprotein cholesterol (0.77 mg/dl) which indicated that soya protein supplementation reduces
serum lipids among adults with or without hypercholesterolemia. It was suggested that replacing foods
high in saturated fat,trans-saturated fat,and cholesterol with soya protein may have a beneficial effect on
coronary risk factors.
Chang et al. (2008) conducted a study to investigate the effect of soya bean on blood glucose and
lipid concentrations, and antioxidant enzyme activity in type 2 diabetes mellitus patients with a basal diet
(control group) and a basal diet with 69 g/d of soya bean (soya bean group) for 4 weeks. The
supplementation was in the form of Pills with roasted soya bean powder provided to the soya bean
supplementation group three times a day. The results of this study suggested that soya bean
supplementation would be helpful to control blood glucose and serum lipid in diabetic patients and have
potential use in the disease management of patients with type 2 diabetes mellitus.
The effect of consumption of soya protein isolate (SPI) on serum lipids in adults with diet
controlled type 2 diabetes was determined by Elizabeth et al. (2009) in comparison with milk protein
isolate (MPI). The results revealed that the SPI consumption reduced serum LDL cholesterol, LDL
cholesterol:HDL cholesterol ratio and apolipoprotein B:apolipoprotein A-I ratio compared with MPI but
no effect was found on serum total cholesterol, HDL cholesterol, triacylglycerol, apolipoprotein B, or
apolipoprotein A-I. The study demonstrated that consumption of soya protein can modulate some serum
lipids in a direction beneficial for CVD risk in adults with type 2 diabetes.
In a review by Parvin et al. (2014) on functional foods and diabetes, it was mentioned that soya
bean is important functional food for diabetes for its isoflavones and bioactive peptides, which have
favourable effect on glycaemic control and insulin sensitivity, dyslipidaemia and kidney function. The
anti-diabetic effect of soya bean was mainly attributed by various studies, to the interaction with
oestrogen receptors (ERs),which are considered as key modulators of glucose and lipid metabolism and
regulate insulin biosynthesis and secretion as well as β cell survival of pancreas. The review also revealed
some interesting facts about the soya protein that it decreases the atherogenic apolipoproteins and
increases biosynthesis of HDL-C,include LDL-C receptors,increase biosynthesis and excretion of bile
acids, decrease gastrointestinal absorption of steroids, induce favourable changes in hormonal status
including the insulin and glucagon ratio and thyroid hormones which lead to improvement of
dyslipidaemia. Finally it was mentioned that soya beans are effective in the weight management also for
diabetics.

36. As isoflavones found in soya products have a chemical structure similar to estrogen,
leading to adverse estrogenic effect in men, particularly in type 2 diabetes mellitus, Sathyapalan
et al. (2017) in a randomized double-blind parallel study, observed the changes in total
testosterone levels as the primary outcome and the changes in glycemia and cardiovascular risk
markers as the secondary outcome in two hundred men with Type 2 Diabetes Mellitus. Fifteen
grams of soya protein with 66 mg of isoflavones or15 g soya protein alone without isoflavones
daily as snack bars for 3 months were administered to the test groups. The results revealed that
there was no change in either total testosterone or in absolute free testosterone levels with either
of the interventions. Glycemic control improved with a significant reduction in hemoglobin A1c
(-4.19). Cardiovascular risk improved with a reduction in triglycerides, C-reactive protein, and
diastolic blood pressure.
Ramdath et al. (2017) summarized in a review, the evidences on the cardiovascular
benefits of non-protein soya components in relation to known CVD risk factors such as
hypertension, hyperglycemia, inflammation, and obesity, beyond cholesterol lowering effect and
suggested from the available evidence that non-protein soya constituents improve markers of
cardiovascular health. The review reported that many studies supported the role of soya
isoflavones in improving the glycaemic control with soya foods rather than with soya isolates.
Sidhu and Tasleem (2017) while reviewing the functional foods of India mentioned that
consumption of Soya bean based products reduce the risk of osteoporosis, reduce LDL-cholesterol,
increase HDL-Cholesterol, help in chronic renal disease, lower the coronary artery diseases and protect
against cancers. The review also mentioned that the cereallike wheat, barley and oats are rich in many,
dietary fibre, other nutrients and phytochemicals which are associated with CVD,type 2 diabetes
mellitus, bowel function and colon cancer.
Husain and Bhatnagar (2018) developed soya flour and evaluated the sensory attributes
and chemical composition of parathas enriched with soya flour by replacing wheat flour with soya
flour at different levels (10%, 15%, 20% and 25%). The parathas incorporated with 20 percent soya flour
quality was found to be the most acceptable with 18.39g protein, 43.33 mg calcium and 19.94 mg
isoflavones. The study recommended the incorporation of soya flour to enhance the sensory and
nutritional of wheat flour.
2.12.5.Kalonji (Nigella Sativa):
Kalonji also called as onion seeds (Plate No.6) belongs to family Ranunculaceae. The seeds are
known as Habbatul barakali in Arabic which means ‘seeds of blessing’. The seeds are also mentioned in a
number of religious texts where they are recommended as a cure for everything except death (Al Bukhari,
1976) The seeds are flattened, ablong, angular, funnel shaped, small 0.2 cm long and 0.1 cm wide in size,
black in colour externally and white inside, with slight aromatic odour and pungent bitter taste (Paarakh,
2010). These seeds are used for centuries for medical and culinary purposes which possess several
pharmacological properties.
A review of medical uses and pharmacological activities of Nigella Sativa by Gilani et al. (2004)
reported that N,Sativa is called as Kalonji in South Asia, Arabic name is Habat-Ul-Sauda and the english
name is black cumin which is used as spice, carminative, condiment and aromatic. Studies on rats
revealed that the blood glucose lowering effect was due to the inhibition of hepatic gluconeogenesis and
might prove useful in the treatment of type 2 diabetes.

37. Plate.No.6. Kalonji seeds
A study was conducted by Najmi et al. (2008) to know the adjuvant effect of N.Sativa on various
clinical and biochemical parameters of the insulin resistance syndrome, where the experimental group
was given 2.5ml of Nigella sativa oil in addition to tablet atorvastatin 10 g once a day and 500 mg of
metformin twice a day for a period of 6 weeks. The results showed significant improvement in total
cholesterol, LDL-C and FBG level, which could give a conclusion that N.Sativa oil has a significant
activity in diabetic and dyslipidaemic patients.
Effectiveness,safety and tolerability of powdered Nigella Sativa on serum lipid levels, blood
sugar, blood pressure and body weight in adults were studied on 123 patients in a randomized double
blind controlled trial by Qidwai et al. (2009) and the results revealed that a favourable impact was noted
but not significant due to small sample size.
The Nigella Sativa seeds powder was orally administered to 10 hypercholestorolemic
patients to evaluate for their effect on lipid profile by Bhatti et al. (2009). The results
demonstrated that 1 g dosage of the Nigella Sativa seeds for 2 months could reduce
total cholesterol, HDL, LDL and triglycerides level to highly significant extent.
Bamosa et al. (2010) conducted a study to see the effect of Nigella Sativa on the glycaemic
control of patients with type 2 diabetes mellitus. The study was conducted in 94 patients, randomly
divided into three groups and capsules containing N.Sativa were administered orally in a dose of 1,2 and
3 g/day for three months. The results revealed that fasting blood glucose was reduced by56 mg/dl and
HbA1c by 1.52% It was observed that a dose of 2 g/day caused significant reduction in fasting blood
glucose, 2 hours postprandial glucose and HbA1c without significant change in body weight. It was
observed that 1 g/day dosage also showed the trends in improvement but insignificant and with the 3
g/day dosage no further benefits were observed more than that with 2 g/day dosage. The study concluded
that 2 g/day dosage of N.Sativa might be a beneficial adjuvant to oral hypoglycaemic agents in type 2
diabetic patients.

38. Paarakh (2010) in a comprehensive review on Nigella sativa Linn, furnished the other names of
the herb as Upakunchika, Ajaji, Kalvanjika, Kalika, Kunchika, Kalaunji and black cumin, It was
described it as a small elegant herb mostly found and cultivated in Punjab, Himachal Pradesh Gangetic
plains, Bihar, Bengal, Assam and Maharashtra in India and also in Syria, Lebanon, Isrealand South
Europe. Traditionally the seeds were considered as appetizer, stimulant, diuretic, acrid, thermogemic,
carminative, anodyne, deodorant, digestive, constipating, sudonific, febrifuge, expectorant, pugative and
abortifacient. The review concluded that, Nigella sativa plant is popular as a cure for multiple diseases
and reported to possess antidiabetic, antitumour, cardiovascular activities along with other
pharmacological activities.
Akash et al. (2011) conducted a comprehensive literature on alternative therapy of type 2
diabetes with Nigella Sativa and concluded that studies had been done on anti-diabetic effect of
N.Sativa in recent years and results were satisfactory but its exact mechanism against type 2
diabetes is to be confirmed.
A review by Mathur et al. (2011) on antidiabetic properties of the spice plant nigella
sativa, concluded that nigella sativa seeds and nigella sativa oil possess antidiabetic activity
which is partly mediated by stimulated glucose induced insulin release from β cells, reduced
gluconeogenesis in liver, antioxidant activity and reduced glucose absorption from intestine.
A study by Sabzghabaee et al. (2012) looked at the clinical evaluation of 2 g of N.Sativa
for the treatment of hyperlipidaemia in a randomized placebo controlled clinical trial in Iran for 4
weeks on adults of above 18 years of age. Significant decrease was observed in LDL-C,
triglycerides and total cholesterol in the treatment as compared to the placebo aim of the study.
No benefits were noted on FBG and HDL-C.
Ahemed et al. (2013) described Nigella sativa as a miracle herb in a review on the
therapeutic potential of the plant, the black seeds and oil of which were very popular in food and various
traditional systems of medicine like Unani, Tibb, Ayurveda and Siddha, used in the treatment of different
diseases and ailments. It is native to Southern Europe, North Africa and Southwest Asia and cultivated in
many countries like Middle East, India, Pakistan, Syria, Turkey and Saudi Arabia. The review revealed
that N.Sativa has been extensively studied for its biological and therapeutic activities and shown wide
spectrum of activities like diueretic, antihypertensive, antidiabetic, anticancer and antiinflamatory. The
therapeutic activities of the plant are due to the presence of thymoquinone (TQ), a major active chemical
component.
Because of its low level of toxicity, the Nigella Sativa seeds are used in foods like flavouring
additive in breads and pickles. The review presented the nutritive value of the seeds as follows:
Protein-26.7%, fat-28.5%,carbohydrate-24.9%, crude fibre-8.4%, total ash-4.8% and various vitamins
and minerals like copper, zinc and iron. From various investigations on effective glycaemic control in
type 2 diabetic patients, the review also recommended a dose of 2 g /day of Nigella Sativa seeds adjuvant
to oral hypoglycaemic agents in type 2 diabetes mellitus patients.
In a RCT, Rasheed et al. (2014) studied the therapeutic evaluation of 2 g of kalonji
(Nigella sativa) in dyslipidaemia for 60 days. The control group was given Lipotab (R) and the
results revealed that there was overall improvement without any significant side effects and
toxicity.

39. The effects of Kalonji (Nigella sativa) on HbA1c, FBS, PPBS and lipid profile of newly
diagnosed type 2 diabetic patients was evaluated in a study by Shaafi and Kulkarni (2017) on 2
groups with 50 subjects in each group. One group was given hypoglycaemic drugs and other
group was advised 2 g of N.Sativa in addition for 8 weeks. The results revealed that N.Sativa
lowered the biochemical parameters after 8 weeks and concluded that it is appropriate to give
N.Sativa to diabetes patients along with the conventional medication.
2.12.6. Drumstick leaves(MoringaOleifera):
Drumstick plant is also known as Moringa Pterygosperma Gaerth, member of
Moringaceae family, native of the sub-Himalayan northern parts of India. It is cultivated
throughout tropical and subtropical areas of the world with various names like drumstick tree,
horseradish tree and malunggay. Moringa is rich in nutrition with the presence of a variety of
essential phytochemicals in its leaves, pods and seeds. The leaves of M. oleifera (Plate.No.7)
are rich in minerals like calcium, potassium, zinc, magnesium, iron and copper and also
vitamins like beta-carotene of vitamin A, vitamin B such as folic acid, pyridoxine and nicotinic
acid, vitamin C, D and E. When 8 ounces of milk can provide 300–400 mg of calcium, Moringa
leaves can provide 1000 mg. Moringa leaf powder has 28 mg of iron powder and can be used as
a substitute for iron tablets (Gopalakrishnan et al., 2016). The phytochemicals present in it
make Moringa a good medicinal agent which has been used in Indian herbal medicine. Various
studies on the effect of Moringa on diabetes are reviewed here.
Plate.No.7. Drumstick leaves and drumstick leaf powder
A review by Mbikay (2012) on the therapeutic potential of Moringa Oleifera leaves in chronic
hyperglycaemia and dyslipidaemia, had shown that its leaves are rich in potassium, calcium, phosphorus,
iron, vitamin A and D, essential amino acids, antioxidants such as β carotene,vitamin C and flavonoids.
Based on the available experimental evidence, the review concluded that M. oleifera leaf powder holds
some therapeutic potential for chronic hyperglycemia and hyperlipidemia.
Nambiar et al. (2010) examined the anti-dyslipidaemic effect of Moringa Oleifera in 35 type 2
diabetic patients, by giving 4.6 g/day of Moringa leaf powder in tablet form for 50 days. The results
revealed that total cholesterol lowered by 1.6 percent, HDL increased by 6.3 percent.

40. Kumari (2010) conducted a study to investigate clinically the hypoglycemic effect of leaves of
Moringa oleifera in Type 2 Diabetes Mellitus. The experimental group was administered Moringa oleifera
leaves powder (8gm) per day in three divided doses for 40 day and the results revealed that there was a
significant reduction in fasting blood glucose and postprandial blood glucose levels and blood lipid levels,
when compared to that of the control group.
Ghiridhari et al. (2011) conducted a study in which type 2 diabetic subjects (60) were given
Moringa oleifera leaf powder in the form of tablets 2/day and after three months, the results showed a
decrease of PPGby 29 percent in comparison to control group and HbA1c by 0.4 percent.
Ravi (2013) investigated the scientific basis for the use of Moringa oleifera leaves in NDDM in
obese patients. It was found that supplementation of 50 g powder of Moringa oleifera leaf for 40 days in
their food regularly, decreased serum glucose and LDL significantly and concluded that the leaves of
Moringa oleifera have definite hypoglycemic and hypocholesterolemic activity in type 2 diabetes mellitus
in obese people.
In a review by Varmani and Garg (2014) on health benefits of Moringa oleifera-a miracle tree, it
was mentioned various studies have shown that Moringa and its components possess wound healing, anti-
inflammatory, antioxidant, antimicrobial & anti-helminthic, antipyretic, anti-diabetic, antihypertensive,
lipid lowering, antifertility, antitumor, hepatoprotective, antiulcer properties etc. It was suggested that the
medicinal potential of this promising healer, wide availability and easy cultivation offer immense
opportunities as a commercially viable medicinal and nutritional supplement in a developing country.
The presence of flavanoids gives Moringa leaves the antidiabetic and antioxidant properties.
(Gopalakrishnan et al., 2016).
Omodanis et al. (2017) reviewed the potentials of Moringa Oleifera in the treatment and
management of diabetes and its possible applications in the treatment of other diseases and found that, it
is a very promising medicinal plant which can be used in the management and treatment of diabetes with
minimal side effects and it has got anti-hyperlipidaemic effect also.
Taweerutchana et al. (2017) in a randomized placebo controlled study to observe the effect of
Moringa oleifera leaf capsules on glycaemic control in the therapy of type 2 diabetes patients, concluded
that Moringa oleifera leaf had no effect on glycaemic control and no adverse effects in type 2 diabetic
patients and needs further investigation.
Table.8. Nutritive value of foods ingredients included in the low glycaemic index multigrain mix
(Gopalan, 1989)
S.No Food
Stuff
Moisture
gm
Protein
Gm
Fat
Gm
Crude
fibre
Gm
carbohydrates
gm
Energy
Kcal
Calcium
mg
Phosphorus
Mg
Ir
m
1 Barley 12.5 11.5 5 1.2 67.5 361 42 296 8
2 Finger
millet
13.1 7.3 1.3 3.6 72 328 344 283 3
3 Wheat 12.8 11.8 1.5 1.2 71.2 346 41 306 5
4 Soya bean 8.1 43.2 19.5 3.7 20.9 432 240 690 10
5 Defatted
soya
flakes**
- 52.94 11.76 23.5 35.29 588 353 81 10
6 81Drumsti
ck leaves
(fresh)
75.9 6.7 1.7 0.9 12.5 92 440 70 0.
7 Drumstick - 27.1 2.3 19.2 38.2 205 2003 204 28

41. leaf
powder*
8 Kalonji** 8.06 17.8 22.2 10.5 44.2 375 931 499 66
(Gopalan et al., 1989), * (Gopalakrishnan et al., 2016), ** (Soybean, n.d.)
The nutritive value (as per the food composition tables) of the food ingredients included in the formulated
low glycaemic index multigrain mix in the present study is shown in table.8.
2.13. Whole grains and diabetes:
A study by He et al. (2010) investigated the relationship between whole grain and its components
like cerealfibre, bran and germ and all- cause and CVD-specific mortality in type 2 diabetics and
concluded that whole grain and bran intakes were associated with reduced all-cause and CVD specific
mortality in women T2 diabetics.
A review by Parvin et al. (2014) on functional foods based diet as a novel dietary approach for
management of type 2 diabetes stated that consumption of whole grains, cerealfibre, bran and germ could
decrease all-cause and CVD-cause mortality by modifying the main risk factors like Triglycerides, LDL-
C levels and blood pressure.
2.14. Nutrition education/counseling:
In India the prevalence of diabetes is very high but the awareness and knowledge regarding
diabetes among the public either general or diabetics is inadequate in both urban and rural regions.
Because of this, people remain undiagnosed until major complications of the disease are seen. As soon as
the disease is diagnosed, most of the cases depend on hypoglycaemic medication alone as advised by the
physician, ignoring the life style modification, which is part of diabetes management. Outcomes of
management of diabetes can be improved at the primary care level with basic interventions such as
medication, health and lifestyle counseling with individual and group education with regular follow-up.
Data on the level of awareness is important to plan and implement any diabetes control programme.
Various studies on role of nutrition counseling and awareness of diabetes are reviewed here.
In a study by Knowler et al. (2002) to know the effect of intervention of life style and metformin,
a 16 lesson curriculum covering diet, exercise and behavior modification was designed with individual as
well as group sessions. The results revealed that the participants assigned to the life style intervention had
more weight loss and a greater increase in leisure physical activity when compared to the participants who
received metformin or placebo.
On a comment on the study by Brand-Miller et al on low GI diet for diabetes, Franz (2003)
mentioned that primary nutrition intervention in T2 diabetes can focus on educational approaches such as
reduced energy intake, modest weight loss and basic carbohydrate counting which have been
demonstrated to produce better outcomes than from a low GI diet approach. He also commented that such
educational approaches reduce HbA1c by 20 percent compared with the 7.4 percent from the low GI diet.
A study by Deepa et al. (2005) to assess the awareness of diabetes in an urban South Indian
population in Chennai for people with 20 years and above reported that 75.5 percent of whole population
knew about a condition called diabetes and 25 percent of the Chennai population was unaware of it.
Knowledge of the role of obesity and physical inactivity in producing diabetes was very low and 22.2
percent know that diabetes can be prevented.

42. A Meta analysis by Deakin et al. (2005) opined that group based training for self management
strategies in people with T2DM are effective by improving diabetes knowledge, thereby reducing the
fasting blood glucose levels, HbA1c,systolic blood pressure levels, body weight and the requirement for
diabetes medication.
Murugesan et al. (2007) in a study done to find out the levels of awareness on diabetes in urban
adult Indian population concluded that the awareness levelwas poor among women and subjects with low
education. This study highlighted the need for strategies to spread awareness on diabetes in the general
population and diabetic subjects.
Amano et al. (2007) conducted a 3-month, randomized controlled, parallel-group trial to evaluate
whether GI-based nutrition education for four individual sessions improves blood glucose control more
than a conventional nutrition education in type 2 diabetic participants. With the positive results showed in
HbA1c (the average change −0.46 ± 0.33% in the GI group and −0.21 ± 0.43% in the conventional group
respectively) it was concluded that GI-based nutrition education is effective in improving blood glucose
control in participants with type 2 diabetes or impaired fasting glucose and could be considered a useful
tool.
Yoo et al. (2007) conducted a study to observe the effects of a comprehensive lifestyle
modification program (CLMP) for 4 months and follow-up sessions for 9 months on glycemic control and
body composition in patients with type 2 diabetes. The programme included education on exercise and
diet and also counseling on stress management and self-monitoring of their diabetic health. The results
showed that there were statistically significant differences in fasting blood sugar and HbA1c levels
between the two groups after the programme and found that it was a useful programme for diabetics.
Ma et al. (2008) conducted a study to compare the effects of a low-glycemic index diet to the
American Diabetes Association (ADA) diet on HbA1c among individuals with type 2 diabetes with an
intervention of eight educational sessions (monthly for the first six months and then at months 8 and 10),
focused on either a low-GI or an ADA diet. The results showed that both interventions achieved similar
reductions in mean HbA1c and improvements in HDL cholesterol, triglycerides, and weight loss at 6
months and at 12 months. The low-GI diet group was less likely to add or increase dosage of diabetic
medications.
In another study by Rani et al. (2008) among rural population in India on knowledge, attitude and
practice of diabetes and diabetic retinopathy and to evaluate the influence of knowledge of diabetic
retinopathy on attitude and practice, the results suggested that aggressive and comprehensive awareness
models on diabetes and diabetic retinopathy need to be propagated o educate rural population.
It was reported by Somannavan et al. (2008) that the awareness of a condition called ‘Diabetes’
increased significantly from 75.5 percent in 2001-2002 (CURES) to 81 percent in 2007 (PACE) in a study
conducted to determine the effectiveness of a large scale multipronged diabetes awareness programme
provided through community involvement in Chennai.
The KAP of type 2 diabetes patients was assessed by Shah et al. (2009) in Sourashtra region,
Gujarat. The study showed that 46 percent of the population knew the pathophysiology of diabetes, 50
percent knew the complications of diabetes and a positive factor was that most of the patients believed in
self care and were willing to change.
Adepu and Ari (2010) conducted a prospective, randomized study to assess the influence of
structured patient education on therapeutic outcomes in patients with type-2 diabetes and hypertension.

43. The results showed a significant (p<0.05) improvement in KAP and a statistically significant change in
Blood Pressure and capillary blood glucose score in test group patients.
Raj and Angadi (2010) has undertaken a hospital based cross-sectional study in 730 type 2
diabetic patients (Mean age was 56.64 years),to assess the knowledge, attitudes and practices regarding
prevention and control of diabetes mellitus among patients attending the diabetic clinic, Karnataka.
Results revealed that 35 percent of respondents had poor, 59.9 percent average and 24.8 percent had good
knowledge, majority (60-90%) of the respondents had positive attitudes3 and 6.4% of the respondents
were taking extra care in case they were injured and 40.7 percent were exercising regularly.
Harati et al. (2010) in a cluster-controlled trial, aimed to assess the effect of lifestyle
modification on risk factors for non-communicable diseases (NCDs) and the development of
Type 2 diabetes at the community level in all, 3098 and 5114 individuals in intervention and
control groups, respectively in Tehran, Iran . The study intervention involved improvement in
diet, increase in the level of physical activity, and reduction in cigarette smoking through
educational interviews, lectures, and publication and outcome was measured by fasting plasma
glucose (FPG), 2-hour plasma glucose (PPG) and change in NCD risk factors. The study stated
that lifestyle intervention resulted in a significant decrease in the incidence of Type 2 diabetes
and better control of NCD risk factors in a population-based setting.
Praveena et al. (2011) conducted a randomized prospective controlled study to assess the impact
of patient counseling on treatment outcomes and quality of life in hypertensive and type 2 diabetes
mellitus patients, improving their knowledge, attitude and practice. With the positive results, it was
concluded that improvement in knowledge of the disease and its management had positive impact on
treatment outcomes and quality of life Physical Component Summary (PCS) and counseling had no effect
on Mental Component Summary (MCS) of the patient's quality of life.
Malathy et al. (2011) studied the effect of a diabetes counseling programme on knowledge,
attitude and practice among 207 (85 males and 122 females) type 2 diabetes mellitus patients in Erode
district of South India. The test group received counseling at each visit and information leaflets. KAP was
assessed and the blood glucose and lipid levels were evaluated at baseline and final follow-up. The results
showed that the KAP score of test group patients were improved and the postprandial blood glucose
(PPBG) levels, total cholesterol, triglycerides and low density lipoprotein levels were decreased in the test
group. The study concluded that patient counseling might be an important element in diabetes
management programmes.
A review by Chang (2012) concluded that educating patients on the importance of not smoking
and engaging in smoking cessation programs are important strategies for the management of diabetes.
The review suggested that education regarding brief screening questions and the efficacy of very brief
alcohol interventions should be disseminated to treatment providers so that such intervention will be
implemented in practice to a greater degree (Engleer et al., 2013).
Adachi et al. (2013) conducted a study to evaluate the effectiveness of a structured individual
based lifestyle education programme for 6 months to reduce the HbA1c level in type 2 diabetic patients.
The secondary endpoints were the changes in fasting plasma glucose, lipid profile, blood pressure,BMI,
energy, and nutrient intakes (whole day and each meal). The results showed a decrease in HbA1c by 0.7
percent and a greater decrease in mean energy intake at dinner, a greater increase in mean vegetable
intake for the whole day, breakfast,and lunch in the intervention group where as a tendency towards

44. improvement was observed in the other secondary endpoints. The study concluded that individualized
education programmes are better than usual diabetes care and education.
An article by Deepa et al. (2014) focused on the level of awareness and knowledge of diabetes in
the generalas well as the diabetic population in four regions of India, Chandigarh, Tamilnadu, Jharkand
and Maharashtra with total 16607 subjects of more than 20 years of age, based on the first phase of the
ICMR-INDIAB study, (The Indian Council of Medical Research India Diabetes Study (Phase I)- Indian
Council of Medical Research India Diabetes 4). Results of the study showed that 43.2 percent of overall
study population had heard about a condition called diabetes, where urban residents had higher awareness
rate of 58.4 percent than rural people (36.8%). Knowledge among male (46.7%) was more than that of
female (39.6%). The study also showed that the diabetics (72.7%) know more about the effect of diabetes
on other organs than the general public (51.5%).
Ramachandran et al. (2014) opined from the suggested evidence that a large portion of type 2
diabetes may be preventable by life style modification by enhancing awareness about the disease among
the public and the health care providers.
IDF (2011) was predicting India as ‘diabetes capital of world’ with the prevalence of about 80
million diabetes cases in India by 2025. With this reference, Shashank (2015) in an expert detailed review
of the medical literature on diabetes with an Asian Indian context felt that the goal of health care experts
in India should be to transform India into a ‘diabetes care capital in the world’. Considering the high cost
incurred at various steps of screening, diagnosis, monitoring, and management, the review expressed the
need to implement the cost-effective measures of diabetes care,result-oriented organized programs
involving patient education and updation of the medical fraternity on various developments in the
management of diabetes.
A study by Al-Rasheedi (2014) was conducted to evaluate the impact of the educational
level on glycemic control among patients with type 2 diabetes mellitus. This study found that the
rate of patients with poor glycemic control is 67.7 percent and the rate of adherence to diet (68%)
and exercise (79.4%) was also poor. This study observed that educational level of the patient
with type 2 diabetes may not be a good predictor of better therapeutic compliance. The study
suggested that educational programs that emphasize adherence to treatment regimens as a whole,
especially to diet and to exercise are required for glycemic control as compared to compliance of
medications alone.
According to ADA (2017) comprehensive group diabetes education programme, including
nutrition therapy or individualized education sessions decreased A1C by 0.5-2 percent in Type 2 Diabetes
Mellitus.
Krishnan et al. (2015) in a study investigated the impact of diet counseling on anthropometric
measurements,plasma glucose, HbA1c,serum lipid profile and blood pressure levels in 150 adult
subjects with type 2 Diabetes Mellitus . The subjects were grouped into three groups, those who were
attending only one session on diet and exercise counseling (Group I), those who were to attend only
dietary counseling with periodic follow-up (Group II), and those who were attending both dietary and
exercise counseling with periodic follow-up (Group III). The results showed that Group III participants
were more involved with their interactions with the counselor; subjects who received periodic, intensive
diet counseling did not show symptoms of progression to diabetic complications and insulin therapy for
the management of their disease. The investigators concluded that a six-month counseling program had a
positive effect on the management of Type 2 Diabetes Mellitus.

45. A study conducted by Mounica et al. (2015) to assess the KAP of diabetes and hypertension
among 50 adult hypertensive patients and 50 diabetics of above 20 years age,concluded that the
respondents had good knowledge but poor attitude and practice towards the disease. The authors opined
that motivation and counseling, stressing the importance of lifestyle modifications and self management
are required for the patients with chronic diabetes and hypertension.
Kusumneela et al. (2015) conducted a study to assess the nutritional status of type 2 diabetic
patients and observe the effect of diet counseling on 40 patients with type 2 diabetes aged between 30 to
60 years. Each subject had 7 sessions of diet counseling with a nutritionist during the first year of study
and thereafter one session for every three months. It was concluded that the diet counseling had positive
impact on biochemical parameters and there was a significant change in the blood sugar levels after the
diet counseling.
Anjana et al. (2011) reported about the awareness of diabetes and its complications among the
Indian populations, from the final results of ICMR-India DIABetes (INDIAB 2008-2011) that 58.45
percent of the urban residents and 36.8% of the rural residents know about what is diabetes.
WHO (2016) reported that all people with diabetes need counseling on healthy diet and regular
physical activity, adapted to their capabilities interventions to promote healthy lifestyles; patient
education to facilitate self-care; regular screening for early detection and treatment of complications
through a multidisciplinary team.
An institutional study was conducted by Kanojia (2017) with an objective to determine the
knowledge, attitude and practice of diabetes among non-diabetic rural population of 18 years and above
age group in Utter Pradesh,India. The results showed that 69.3 percent never heard about the disease,
30.4 percent heard of it, 33.5peercent had no idea about this, 48.2 percent do not know that physical
activity is necessary to prevent diabetes and 38.3% had no idea about the relation between weight and
diabetes. The study concluded that the knowledge about diabetes was poor and very few people had an
idea about the risk factors and management strategies,hence health education is an important part of
diabetes management.
The awareness and knowledge regarding diabetes mellitus was assessed by Sridhar et al. (2017)
among 100 diabetic and 50 non-diabetic subjects of aged 20-80 years. It was found from the analysis that
among diabetic patients 46 percent had poor knowledge, 45 percent had medium knowledge and 9 percent
had good knowledge regarding Diabetes Mellitus where as 64 percent of non-diabetics had poor
knowledge, 34 percent of non-diabetics had medium knowledge and 2 percent of non-diabetics had good
knowledge regarding Diabetes Mellitus. The study concluded that diabetic patients had more knowledge
regarding diabetes mellitus than non-diabetic subjects.
In a cross sectional study by Rathod et al. (2018) to assess the baseline levels of (KAP)
knowledge, attitude and practices of general population of Vadodara,the results showed that overall
60.12 percent of respondents scored 100 percent in the questions related with knowledge, 23.54 percent
scored 100 percent in the attitude questions and 12.80 percent scored 100 percent in practice questions. It
was concluded that the responders had good knowledge but poor attitude and practice towards diabetes
and it can be overcome this by increasing quality of health education.
Di Onofrio et al. (2018) conducted a 9 months nutrition motivational programme for 69 patients
with type 2 diabetes aged between 50-70 years, to verify the effectiveness of nutritional intervention in
improving the health of the patients. Quarterly group meetings were held and after 9 months, clinical and
metabolic parameters were analyzed. The results of the study demonstrated a reduction in daily
consumption of energy, guidelines were followed in energy distribution through carbohydrates, proteins
and fat, usage of sweeteners were reduced and fruit was preferred to a snack, after the programme. The

46. study concluded that a nutritional motivational intervention may be useful in improving dietary habits and
health status of patients with Type 2 diabetes.
An observational study was undertaken by Pot et al. (2019) with a pretest posttest design aimed to
pilot a 6-month multi-component outpatient group-based nutrition and lifestyle intervention programme
on glycaemic control and use of glucose lowering medication in 74 motivated Type 2 diabetic patients in
Netherlands. The results of the study revealed that the participants had reduced their medication or
eliminated it completely after the 6 months programme and the secondary outcomes were significantly
lower and plasma lipids remained unchanged except for a decrease in triglyceride levels. It was also
observed that the self-reported quality of life was significantly higher while experienced fatigue and sleep
problems were significantly lower. With this, the pilot study concluded that a 6-month multicomponent
group-based program in a routine care setting could improve glycaemic control and reduce the use of
glucose lowering medication in motivated Type 2 diabetics.
The results of studies conducted by different countries to know the level of knowledge and
awareness of diabetes among the general public as well as the diabetics in the respective countries are
furnished here. Various studies on the level of knowledge and awareness of diabetes among the public
whether general public or diabetic patients done in different Asian countries including India are
consolidated in table.9.
Table. 9. Studies on level of awareness of diabetes among the public (general or diabetic) in different
Asian countries.
S.No Authors/year Country Sample size/type Results
1 Deepa et al. (2014) India 16607 subjects of
>20 years of age,
general and
diabetics (ICMR-
INDIAB study-
Phase-1)
Overall 43.2% heard about
diabetes, with 58.4% urban and
36.8% rural, male- 46.7% and
female- 39.6%, 72.7%- diabetics
and general public -51.5% know
about the effect of diabetes on
other organs.
2 Wee et al. (2002) Singapore 1337 subjects,
General public
Well aware of diabetes except in
few areas.
3 Naeema et al. (2002) Pakistan type 2 diabetes
patients
Awareness about the risk of
complications was satisfactory
with misconceptions regarding
diet, insulin and diabetes.
4 Al-Maskari et al.
(2013)
United Arab
Emirates
(UAE)
275 diabetes
patients
31% poor knowledge, 72%
negative attitude towards having
the disease.
5 Islam et al. (2014) Bangladesh 3014 adults of 30-
89 years- general
public
93% heard about diabetes, 4%
knew about glucose tolerance,
50% knew physical inactivity as a
risk factor.
6 Herath et al. (2017) SriLanka 277 healthy
literate individuals
77% above moderate knowledge
on diabetes but 90% had poor
attitude, 65% taking refined
sugars, 80% had no exercise,
>50% never had their blood sugar
levels checked.
7 Karaoui et al. (2018) Lebanon 207 urban adult Higher knowledge with university

47. patients with
diabetes mellitus
degree than with intermediate or
primary schooling.
A cross sectional survey conducted by Wee et al. (2002) in Singapore on 1337 subjects, to
evaluate the knowledge of diabetes among the general public, revealed that the public was well informed
about diabetes except for a few areas.
A study was conducted in Pakistan by Naeema et al. (2002) to assess the generalcharacteristics
and KAP of type 2 diabetes patients attending the out-patient department of an institute of diabetology
and endocrinology. The results showed that overall awareness about the risk of complications was
satisfactory but there were common misconceptions regarding diet, insulin and diabetes. This study also
highlighted the need for better health information to the patients through awareness programmes so as to
change the attitude of the public.
KAP of patients towards the management of diabetes was assessed on a random sample of 575
diabetic patients in United Arab Emirates by Al-Maskari et al. (2013) and the results reported poor
knowledge of diabetes in 31 percent of patients and negative attitude towards having the disease in 72
percent patients. With this, it was concluded by the investigators that awareness programmes are essential
for all diabetics in UAE to improve their understanding, compliance, management and ability to cooperate
with the disease.
Islam et al. (2014) conducted a study to assess the KAP of type 2 diabetes among the general
community in rural Bangladesh in 3014 adults of 30-89 years age group. The results showed that 93
percent of people reported to have heard about diabetes, 4 percent knew what glucose tolerance was and
50 percent knew that physical inactivity is a risk factor. It was concluded that knowledge of diabetes and
its risk factors is very limited in rural Bangladesh
A study was conducted to identify the level of KAP related to diabetes among the generalpublic
in Southern Srilanka by Herath et al. (2017). The sample was 277 healthy literate individuals who have
not attended any diabetes education programmes earlier in last two years. Even though the results showed
that 77 percent of people had either moderate or above moderate knowledge on diabetes, the attitude
towards diabetes was poor (90%) which demonstrated that level of education had no significant effect on
attitude. The study also showed negative practice among the public by reporting that more than half of the
subjects never had their blood sugar levels checked,above 65 percent was taking refined sugars and 80
percent had no exercise. Therefore the authors felt it necessary to give more emphasis on issue of poor
attitude and practice towards diabetes mellitus among general public in Srilanka.
Sami et al. (2017) examined various studies to explore relationship of Type 2 diabetes with
different dietary habits, patterns and practices and its complications. The review suggested that patients
with type 2 diabetes require reinforcement of diabetes education including dietary management through
stakeholders (health-care providers, health facilities, etc.) to encourage them to understand the disease
management better,for appropriate self-care and better quality of life. The authors opined that active and
effective dietary education may prevent the onset of diabetes and its complications, so the health
professionals should have an orientation about the cultural beliefs, thoughts, family and communal
networks of the patients and inform the patients to make changes in their nutritional habits and food
preparations.
An analysis by Karaoui et al. (2018) in a cross sectional study conducted in Lebanon among 207
urban adult patients with diabetes mellitus showed that patients with university degree had a significantly
higher knowledge and practice score than patients with intermediate or primary schooling. Patients who

48. reported following a special diet had a higher knowledge score. No difference was found by gender and
age for knowledge and practice scores. The authors suggested well targeted interventions such as
improving the communication between the pharmacist and the patient.
A cross sectional study was conducted among diabetic patients by Venkatesan et al. (2018) to
find the barriers for diabetic medication adherence among them. The prevalence of low adherence for
treatment is 45.4 percent. The common reasons observed by the study are lack of knowledge about the
disease, lack of transport to health facility, cost of drugs in private hospitals and side effects. The study
suggested that there is a need to strengthen the set up of primary health care system by providing not only
drugs but also in providing quality health education and quality care to promote drug adherence for better
health outcomes among patients.
Most of the patient’s management of diabetes takes place within the family and family members
play an important role in the self management of the disease. Baig et al. (2015) reviewed family-based
interventions for adults with diabetes published from 1994 to 2014 and assessed their impact on patients’
diabetes outcomes and the extent of family involvement. It was reported that only two studies were found
with substantial family involvement that reported improvement in HbA1c. The authors opined that there
is much work to be done to fully understand the role of family members in family-based diabetes self-
management interventions and their effect on patients’ diabetes outcomes.
In summary the literature reviewed had explained the definition of type 2 diabetes
mellitus, its symptoms, complications, risk factors and the serious consequences if not treated.
The literature also demonstrated that the prevalence rate of the disease is rapidly rising globally
and nationally, increasing the health burden of the individuals as well as the nation. It had thrown
light on the treatment strategy, dietary management, need for life style modification and
importance of nutrition counseling to the patients with type 2 diabetes. Though there were
limitations, most of the literature supported that inclusion of low glycaemic index foods and
formulations with such foods in the dietary management for patients with the type 2 diabetes
have therapeutic effect on glycaemic control, lipid profile, hypertension and obesity. Based on
the supporting studies, the present study was undertaken to see the effect of a developed and
evaluated low glycaemic index multigrain formulation and nutrition counseling for the
management of type 2 diabetes, on blood glucose levels, HbA1C and lipid profile. The
methodology and results of the study are discussed in the following chapters.
*****

49. 3. Methodology
India is known for high prevalence of diabetes and lack of awareness about the disease
among people could also be one of the reasons for the increasing rate of prevalence. Along with
hypoglycaemic- medication, life-style modifications including appropriate dietary changes are
very important to prevent or delay the progression of the disease. So currently emphasis should
be given on bringing awareness and positive attitude among diabetic patients, towards diabetes
care and dietary management, through counseling which can be turned into a good practice for
the better control of the disease. It is also necessary to formulate different hypoglycaemic dietary
products which are readily available and easily accessible to type 2 diabetics for a quick choice.
The management of diabetes needs an integrated approach, rather than a single approach.
Hence the present investigation was undertaken to study the effect of the following interventions
type 2diabetes.
1. Intervention of a developed and standardized low glycaemic multigrain mix, and
2. Intervention of Nutrition counseling, with a structured counseling programme.
In this chapter, the material and methods used during the course of investigation are
elaborated in the following headings:
3.1. Place and period of study,
3.2. Experimental design,
3.3. Selection of sample and sample size,
3.4. Enrollment of study subjects,
3.5. Development of interview schedule and collection of data,
3.6. Assessment of nutritional status of subjects:
3.6.1. Anthropometric measurements and body composition,
3.6.2. Dietary assessment,
3.7. Biochemical assessment (FBG, PPBG, HbA1C, lipid profile, BP),
3.8. Clinical assessment
3.9. Assessment of knowledge, attitude and practice on diabetes,

50. 3.10. Development of low glycaemic index multigrain mix and standardization,
3.11. Development of aids and brochures for nutrition counseling,
3.12. Pilot study,
3.13. Ethical committee approval,
3.14. Intervention of the developed low glycaemic index multigrain mix,
3.15. Intervention of Nutrition counseling sessions,
3.16. Statistical Analysis.
3.1. Place and period of study:
The entire study was planned at department of Homescience, Sri Padmavati Mahila
Visvavidyalayam, Tirupati, AP, India. The study was conducted in Hyderabad city, Telangana
state, for the convenience of the investigator and also to get a heterogeneous sample from the
cosmopolitan population. The study was conducted in two randomly selected outpatient health
clinics, Vivekananda Health Centre, Sunrays Diagnostic centre-Speciality poly clinic and from
diabetic individuals living in residential colonies in Hyderabad city, Telangana, India, with the
prior permission from the authorities to conduct the study. The analysis of nutrient composition
and shelf-life evaluation of the developed low glycaemic index multigrain mix were carried out
at Quality control laboratory, Rajendranagar, Hyderabad. The assessment of glycaemic index of
the developed product and the clinical analysis of the study subjects were done at Sunrays
Diagnostic Centre, Namalagundu, Hyderabad.
3.2. Experimental design:
The experimental design of the present study is presented in the figure.4. The whole study
was undertaken in three phases as pre-intervention phase, intervention phase and post-intervention phase
as presented in the research design.
In phase-I, the pre intervention phase, sample selection, base-line data collection, base-
line assessment of knowledge and dietary assessment, pre-tests of anthropometry, biochemical
and clinical, development and standardization of low glycaemic index multigrain mix for
intervention and development of curriculum, aids and brochures for nutrition counseling were
carried out. A total of 125 people who met the inclusion criteria were randomly allocated to four
groups, with one control group (Group I) and three experimental groups (Group-II, Group-III and
Group-IV), with a minimum of 30 people in each group. The management of diabetes needs an
integrated approach, so in the present study, two different interventions like nutrition counseling
and intervention of low glycaemic index multigrain mix were carried out. The three study groups
were formed on the basis of type of treatment given to the subjects in each group. Base-line data

51. collection included the information about the demographic background, health history, personal
and dietary habits and physical activity which were collected with the help of a structured
interview schedule from the subjects of all the four groups. Anthropometry, biochemical
parameters and nutrient intake were also recorded for all the four groups at base-line.
In phase-II, the intervention phase, the interventions were administered to the three
experimental groups for a period of 90 days with a final number of 30 subjects in each group
after considering the drop outs. The intervention programmes were named with different
captions to enhance the significance of the programme and to attract the participants so as to
minimize the drop outs. Among the experimental groups, group-II received only nutrition
counseling and it was named as NEED (Nutrition Education to Eliminate Diabetes symptoms)
group; group-III received both nutrition counseling and dietary intervention and was named as
FEED (Food and Education to Eliminate Diabetes symptoms) group and group-IV received only
dietary intervention and was named as FED (Food to Eliminate Diabetes symptoms) group.
In phase-III, the post intervention phase, the end-line assessment of knowledge, attitude
and practice, assessment of nutritional status, post-tests of anthropometry, biochemical and
clinical tests were carried out to all the four groups with a final total of 120 subjects. The data
were computerized and analyzed for statistical results.

52. Experimental Design
ase
III-
Post
Intervention
Phase
I-Pre
Intervention
Phase
II-Intervention
(90
days)
Random allocation to control and experimental groups
Data Collection: Informed Consent, demographic background, disease history
Baseline Assessment: KAP, Anthropometry, Biochemical, Clinical and Dietary
Group-I
Normal
Routine diet
Group-II
Nutrition
Counseling only
n=30
Group-IV
Multigrain mix
only
Group-III
Both nutrition counseling
and multigrain mix
n=30 n=30
Total Patients with Type II Diabetes Screened (n=183)
Inclusion Criteria met (n=125) Inclusion Criteria Not met (n=58)
Group-I
Control (n=30)
Group-II
NEED (n=30)
Group -III
FEED (n=32)
Group-IV
FED (n=33)
n=30
Dropout n=2
Reasons
a) didnot like the
multigrain mix
( n=1)
b) Abdominal
discomfort (n=1)
Dropout n=3
Reasons
a) didnot like
the multigrain
mix( n=1)
b) Out of
station (n=2)
1.Development and Standardization of low Glycaemia Index multigrain mix
2.Development of aids and brochures for nutrition counseling

53. Figure.4. Flowchart of the experimental design ofthe present investigation
3.3. Selectionofsample and sample size:
The present study was conducted in two randomly selected out-patient health clinics in
Hyderabad city and the adult diabetic patients visiting any of these two study sites for their
regular check-up and diabetic individuals living in residential colonies, were initially screened.
Patients of both genders with type 2 diabetes, aged between 35-65 years and consented to
participate in the study were included in the study. The individuals who are aged less than 35 and
more than 65 years, type 1 diabetic patients, very sick with history of serious diabetic
complications, other co-morbidities such as heart diseases, renal and hepatic impairments, any
mental disorder or cancer, with any implanted electronic device, known to be allergic or
intolerant to any of the ingredients found in the study product, pregnant or nursing mother and
not willing to participate in the study were excluded from the study. The patients who were
included in the study were randomly assigned to control and study groups with a minimum of 30
participants in each group. Assuming 95 as critical Index and 80% power, standard deviation of
HbA1C as 3 and expected difference between two groups is 2.5 units, and also considering the
drop outs of 20 percent, the minimum required sample size is 29 in each group.
3.4. Enrollment of study subjects:
Out of total 183 diabetic patients initially screened, 125 patients who met the inclusion
criteria were included and 58 people who came under exclusion criteria were excluded from the
study. Out of 125 subjects included, 30 people to control group (group-I), 30 people to NEED
group, 32 people to FEED group, and 33 people to FED group were assigned randomly. During
the course of intervention of dietary product, total 5 subjects, 2 from FEED group and 3 from
FED group were dropped out of the study due to various reasons like abdominal discomfort,
disliking the taste of the product and going out of station. A final total of 120 subjects had
participated in the 90 days period of the study, with 30 subjects in each group. The participants
were informed of all possible expected benefits and possible harmful effects arise from the study
and an informed written consent was obtained from them.
3.5. Developmentof interview schedule and collectionofdata:
A personal interview schedule was developed and pre-tested to elicit information on the
general profile, disease profile, diet history and laboratory investigations of the study subjects.
The first part of the schedule covered the demographic information of the subjects, which
includes age, gender, education, occupation, family type and monthly income. Before setting any
counseling programme, it is important to assess the knowledge, attitude and practice of the
subjects. So the second part of the schedule was structured to obtain information about the
diabetes awareness of the study subjects, and their attitude towards disease, personal habits and

54. dietary practices. Both open ended and close ended questions were used in the schedule
(Annexure).
3.6. Assessmentof nutritional status of subjects:
Specific dietary and nutritional counseling recommendations depend on the current
nutritional status of the patients. Assessment of nutritional status of the subjects is necessary to
identify appropriate areas of change in their diet and lifestyle. In the present investigation,
nutritional status of the subjects was assessed by recording their anthropometric measurements
and food and nutrient intake.
3.6.1. Anthropometric measurements and body compositionof the subjects:
Prospective epidemiological studies showed that excess weight and obesity, increase the
risk of coronary heart disease, stroke and type 2 diabetes mellitus. Increased abdominal fat
accumulation is an independent risk factor for cardiovascular disease. Some studies have
suggested that waist circumference is a better predictor for diabetes. In the present study, the
anthropometric measurements like height (cm), weight (kg) and waist circumference (inches) of
the study subjects, at both base line and end line, were measured with calibrated standard
equipment (Annexure). Body composition was determined by using a commercially available
digital weight scale incorporating 8 electrode bioelectrical impedance body composition analyzer
(Tanita BC-601-Annexure) (Plate.No.8). The readings of body weight, BMI ( kg/m2), body fat
(%), bone mass (%), total body water (%), and visceral fat (ranking) were automatically
displayed on the equipment with the pre-entered personal data (age, gender, height and level of
physical activity) of the corresponding subject. Height was recorded nearest to 0.1cm, weight
nearest to 0.1Kg and waist circumference nearest to 0.1 inch.

55. Plate.8. Recording the readings of body composition of the participant from the body
composition analyzer
3.6.2. Dietaryassessment:
Nutritional status of the subjects can be assessed by measuring the food intake. In the
present study, nutritional status of the subjects, both pre and post- intervention, was assessed by
recording their food intake by frequency of consumption of foods and 24 hour dietary recall
method (Annexure-). Nutrient intake was calculated using the Indian food composition tables
(Gopalan et al., 1989 and Longvah et al., 2017) and the Application (App) ‘Count what you eat’
developed by National Institute of Nutrition (NIN, 2016). Accurate estimation of dietary intake is
essential for assessing the effect of diet on the disease, so a set of standardized household
measurement tools was used during dietary survey to help the participants to estimate the portion
size they consumed.
3.7. Biochemicalanalysis:

56. The primary goal of treating diabetes is to keep the blood glucose under control, so the
biochemical analysis is important for monitoring periodical changes in blood glucose and lipid
profile. A series of biochemical investigations like blood pressure (BP), fasting blood glucose
(FBG), postprandial blood glucose (PPBG), glycosylated heamoglobin (HbA1c) and lipid profile
(total cholesterol, LDL cholesterol, HDL cholesterol, VLDL Cholesterol and triglycerides) of the
study subjects were carried out. Blood samples were drawn from the subjects by a trained
laboratory technician from the diagnostic centre for biochemical analysis. The readings were
recorded, at both pre and post intervention period.
3.8. Clinical assessment:
The goal of diabetes management is to prevent the development of long term
complications of the disease. The treatment selection will depend on the stage of the disease and
the individual characteristics of the patient. Clinical analysis was done using the personal
interview schedule by interacting with the subjects, to assess the classic symptoms like polyuria,
polydipsia, polyphagia, weight loss, blurred vision, numbness, tiredness, wound healing time and
also the long term complications like diabetic retinopathy, diabetic neuropathy, and diabetic
nephropathy.
3.9. Assessmentof knowledge, attitude and practice:
Diabetes as a chronic disease requires continuous medical care with ongoing self-
management education and support to the patients for preventing or reducing the risk of long-
term complications. But before educating the patients, it is required to know the level of
awareness of the subjects. So in the present study, the knowledge, attitude and practice on
diabetes and its management among the study subjects were assessed using the structured
questionnaire. The questionnaire was administered to both control and intervention groups at both base-
line and end-line follow-up. Each question had multiple responses. Score 1 was awarded for each
correct answer and none for an incorrect answer. Thus the maximum possible attainable score for
knowledge, attitude and practice was 35, 19 and 18 respectively. The resulting score was given
as shown in table.10.
Table.10. Scoring pattern of knowledge, attitude and practice among the subjects
S.No Knowledge (total score=35) Attitude (Total score=19) Practice (Total score=18)
Level Score % Level Score % Level Score %
1 Inadequate 0-10 <30 Negativ
e
0-11 <60 Negative 0-11 <60
2 Moderate 11-21 30-60 Positive 12-19 > 60 Positive 12-18 >60
3 Good 22-35 >60 - - - - - -

57. 3.10. Developmentand standardization of low glycaemic index multigrain
mix:
3.10.1.Selectionoffood ingredients:
Criteria for developing the low glycaemic index dietary product for type 2 diabetics, were
that the ingredients should be locally available with hypoglycaemic and other therapeutic
property. The product should be filling with rich dietary fibre and complex carbohydrates, as
major energy source is from carbohydrates. Finally the product should be palatable and cost
effective with better shelf-life. The developed multigrain mix contained raw ingredients like
whole wheat (Triticum aestivum), barley (Hordeum vulgare), finger millet (Eleusine coracana),
defatted soy chunks (Glycine max), drumstick leaf powder (Moringa oleifera) and kalonji
(Nigella Sativa) in right proportions.
A preliminary informal interaction with patients with type 2 diabetes revealed that most
of the diabetics prefer wheat to rice for maintaining their blood glucose levels. Introducing
products made up of staple and familiar foods will have more acceptability than a completely
new food item. So wheat, a staple cereal, was selected as one of the major ingredients of the
study product, along with other cereals like barley and finger millet, for their functional and
therapeutic properties. Cereals and millets are deficient in lysine, an essential amino acid, while
most of the legumes are rich in lysine and combination of cereals and pulses improves the quality
of protein. And also the presence of higher amount of protein reduces the GI of the meal.
Therefore soya, a protein rich pulse, was added to the multigrain mix, in the form of defatted
chunks. Addition of drumstick leaf powder enhances the nutritive value of the product with
vitamins and minerals and also adds dietary fibre which makes the food low GI. Spices like
kalonji, add not only flavour to the multigrain mix but many other medicinal values also. The
product was preferred in the form of coarse granules (rava) to fine flour as the particle size
influences the digestion rate and consequent metabolic effects of grains (Heaton et al., 1988) and
also the glycemic index is affected by much processing.
3.10.2.Procurementand processing ofraw ingredients:
For the present investigation, the whole grains, wheat, barley and finger millet, were
procured from a local wholesale grain market in required lots for every fortnight. The grains
were cleaned to remove the dust and any unwanted matter and sundried for 6 to 7 hours. The
cleaned grains were then ground coarsely and sieved to obtain coarse granules of uniform size by
removing the fine flour if any. Kalonji seeds were procured from local wholesale spice market
and cleaned to remove dirt and dust. The cleaned kalonji seeds were ground coarsely in a
household blender and stored in air tight containers. Fresh drumstick leaves were obtained from
a local vegetable market or directly plucked from drumstick trees in domestic yards. Leaves were
separated from the stalks, washed under running water to remove dust and any foreign matter
and drained. The cleaned leaves were shade dried for two to three days and powdered. The
drumstick powder was stored in air tight containers, ready for mixing with other ingredients.
Readily available defatted soy chunks, packed in air tight packets, were procured from local
wholesale grain market fortnightly and ground slightly in household blender to have similar
particle size.

58. 3.10.3.Preparationofthe multigrain mix:
The low glycaemic multigrain mix was prepared by mixing all the ground raw
ingredients (Plate.No.9) manually in the proportions shown in table.11.
Table.11. Proportions of raw food ingredients of the developed low glycaemic index multigrain
mix
S.No Food ingredients %
1 Wheat rava (Triticum aestivum) 35
2 Barley rava (Hordeum vulgare) 30
3 Finger millet rava (Eleusine coracana) 10
4 Defatted Soy chunks (Glycine max) 20
5 Drumstick leaf powder (Moringa Oleifera) 1.5
6 Kalonji (Nigella Sativa) 3.5
No salt was added to the prepared raw multigrain mix. To improve the quality of cereal
and pulse protein, minimum ratio of cereal protein: pulse protein of 4:1 is to be maintained
and in terms of grains cereal: pulse, the ratio should be 8:1 (Kam et al., 2016).
Plate.No.9.. Raw ingredients of the developed low glycaemic index multigrain mix

59. Plate.No.10.The developed low glycaemic index multigrain mix.
The final product, the multigrain mix shown in Plate No.10, was packed in double zip
lock pouches with 60 g of low glycaemic index multigrain mix in each packet.
3.10.4.Analysis of nutrient composition of the developed mix:
The developed low glycaemic index multigrain mix was analyzed for nutrient
composition in duplicates. Analysis of proximate principles, crude fibre, moisture content, ash,
gluten content, vitamins and minerals was done using standard procedures of the Association of
Official Analytical Chemist (AOAC). Carbohydrate and energy values were computed.
3.10.4.1 Moisture:
Water is a major constituent of most food products. It is essential to determine the
moisture content as the chemical composition of foods is expressed on moisture free basis.
Moisture content also helps in determining the shelf life of the product. The moisture content of the
multigrain mix was determined using the procedures of IS1155:1968. (Annexure-)
3.10.4.2. Crude Protein:
Protein has been identified as an important component for dietary strategies for diabetes.
It can influence the rate of starch digestion and improve postprandial glycaemia (Kam et al.,
2016). Therefore protein content of the multigrain mix was estimated using the procedure of
AOAC 992.23 (Annexure-).
3.10.4.3. Crude Fat:

60. The incidence of cardiovascular diseases in type 2 diabetes has been directly related to
abnormal lipid levels. The fat content of the low glycaemic multigrain mix was analyzed using
the procedure described in AOAC 2003.06 (Annexure-).
3.10.4.4. Crude Fibre: Dietary fibre is effective in lowering blood cholesterol and slows down
the absorption of sugar, so reduces the progression of diabetes and risk of heart diseases (Post et
al., 2012). The fibre content of the multigrain mix was analyzed using the procedure explained in
AOAC 962.09 (Annexure-).
3.10.4.5. Ash:
The ash content of food stuff is the inorganic residue remaining after the organic matter
has been burnt away. This helps determining the amount and type of minerals in the food. The
ash content of the multigrain mix was analyzed using the procedure explained in IS115:1968
(Annexure).
3.10.4.6. Carbohydrate:
The total carbohydrate content was calculated by difference method after subtracting the
sum of the values of moisture, crude protein, crude fat, ash and crude fibre from 100. (Gopalan,
2004).
3.10.4.7. Energy:
The energy content of the multigrain mix was determined by multiplying the protein, fat
and carbohydrate contents with their respective physiological fuel value (calorific value) as
follows:
Energy (Kcal/100 g) = [(% protein x 4) + (% carbohydrate x 4) + (% fat x 9)]
3.10.4.7. Gluten:
Gluten is a substance found in wheat,oats, barley and rye. It comprises of a combination of stored
proteins called prolamins that conjoin with starch. The gluten content of the multigrain mix was
determined using procedure described in IS 1155:1968. (Annexure-).
3.10.4.8. Minerals:
Mineral content like Iron, Calcium and Zinc of the multigrain mix was determined using
the method explained in AOAC 953.01 (3.2.01) (Annexure-).
3.10.4.9. β Carotene:
Beta carotene content of the multigrain mix was determined using he procedure described
by Zakaria et al. (1979) (Annexure-).
3.10.5. Sensoryevaluation of the developed low glycaemic index multi grain
mix:
Sensory evaluation is a scientific discipline that analyses and measures human responses
to the composition of food, e.g. appearance, touch, odour, texture, temperature and taste, for the
purpose of improvement or acceptance of the food product. In the present study, initially two

61. products, Product-I and Product-II, were developed for sensory evaluation, to select one of them
for the intervention. Product-I contained raw ingredients like wheat, barley, maize, defatted soy
chunks, drumstick leaf powder and kalonji and Product-II contained raw ingredients like wheat,
barley, finger millet, defatted soy chunks, drumstick leaf powder and kalonji. The two products
were cooked in the form of upma and presented for sensory evaluation. Green chilli, salt to taste
and seasoning with little cooking oil, mustard seeds and cumin seeds were added to upma to
enhance the palatability. Sensory evaluation of the developed products was done with twenty
trained panel members. A five point Hedonic scale was used to assess different sensory attributes
namely appearance, taste, flavour, texture and overall acceptability. The two products for
evaluation were coded and placed in a random manner. The recipes were presented in clean and
well-ventilated area, with a glass of water to rinse the mouth. The panelists were instructed to
evaluate each sample as per regulations given in score card (Annexure-). From the sensory mean
scores and comments of the panel, product-II (with wheat, barley, finger millet, defatted soy
chunks, drumstick leaf powder and kalonji) was selected for intervention.
3.10.6.Microbiologicalevaluationof the developedlow glycaemic index
multigrain mix:
“Shelf life” is defined as the estimated period during which the food maintains its safety
and sensory qualities at a specific storage condition (FAO/WHO, 2016). It is expected to retain
its desired sensory, chemical, physical, microbiological and functional characteristics of the food
product during the shelf-life period for the safety of the consumer. So in the present study, the
shelf-life of the developed low glycaemic index multigrain mix was evaluated for total bacterial
count (TBC) and total mould count (TMC) at monthly intervals for a period of 90 days by the
method of Cruikshank (1975).(Annexure) To extend the shelf-life, a sample of the developed
mix was irradiated with gamma rays. Total bacterial count (TBC) and Total Mould count (TMC)
were tested for every 30 days for the irradiated product also. The result of the microbiological
test revealed that the developed low glycaemic index multigrain mix was acceptable with a shelf
life of more than 90 days under normal storage conditions.
3.10.7.AssessmentofGlycaemic Index of the developed multigrain mix:
The glycemic index indicates the extent of rise in blood sugar in response to a test food
in comparison with the response to an equivalent dose of glucose, a reference food. The concept
of glycemic index (GI) of the foods is considered as physiological basis for ranking carbohydrate
foods, which are useful in planning diabetic diets (Jenkins et al., 1981). Hence in the present
study, the glycaemic response of the developed low glycaemic index multigrain mix was
determined in a scientific approach on non diabetic volunteers. The internationally accepted GI
methodology (WHO/FAO, 1998 and Brouns etal., 2005) was used for measuring and calculating
the GI of foods.
Thirteen healthy volunteers (adult men) aged between 20-25 years were selected for the
assessment of glycaemic index of the developed multigrain mix. Personal information like name,
age and anthropometric measurements like height and weight of the volunteers were recorded. A
written informed consent was obtained from the subjects volunteered for the glycaemic index
test. The comparison of GI of test food with that of reference food (glucose) was done on three

62. different visits with an interval period of one-week for each session. For each testing session the
subjects attended after a 10 hrs overnight fast as instructed. The subjects were instructed not to
consume unusually large meals, drink alcohol or do unusual vigorous physical activity on the
previous day. They were also instructed to avoid walking or cycling to the testing laboratory on
the day of testing while coming for the test.
Subjects were served with 50 g portions of glucose (dextrose monohydrate) in 250 ml of
water to drink within 10 minutes, on two occasions. On the third visit of the experiment, all the
subjects were requested to consume the test food i.e., the developed low glycaemic index
multigrain mix in the form of upma (Plate No.12), within 15 minutes. The subjects were given
250 ml of water to drink along with test food (Plate No.13). The portion size of the test food may
vary according to the quantity of carbohydrate available in that food. So the portion size of test food
(85g) was calculated to provide 50g of available carbohydrate (total carbohydrate minus dietary
fibre) ( Brouns et al., 2005), from the proximate analysis of the developed multigrain mix, which is
equal to the 50g of glucose load of reference food given earlier. To improve the palatability of
the product, salt to taste, green chilli and seasoning with cumin seeds and mustard seeds were
added while cooking upma with the low GI multigrain mix. To measure the blood glucose level of
the volunteers, whole blood was obtained by finger-prick method (Plate.No.11) with Glucometer with a
glucose test strip (Accu‐chek Active) in fasting state and at 15, 30, 45, 60, 90 and 120 minutes from the
commencement of consumption of the food. The Incremental area under curve (IAUC) to the test and
reference food was calculated according to the method recommended by FAO/WHO (1998) and
Brouns et al. (2005) ignoring the area below the fasting base line. The GI of the food was
calculated as the mean value of all the subjects. The two outliers were excluded from the data-
set, because they can have influence on the results of statistical analysis.
Area under glucose curve of test meal
Glycaemic index (GI) = ——————————————————— X100
Area under glucose curve of reference mean

63. Plate No.11. obtaining blood from the volunteers by the trained lab technician for glycemic index
test

64. Plate No.12. Upma made with the developed low GI multi grain mix consumed by the volunteers
for glycaemic index test
Plate.No.13. Volunteers consuming the upma made with the formulated multigrain mix for
glycaemic index test
3.10.8.Packing ofthe product for supplementation:

65. Though the microbiological analysis of the product had ensured shelf life of more than 90
days, the low glycaemic index multigrain mix was prepared once in 15 days to retain the
freshness. The developed and standardized low glycaemic index multigrain mix (Plate No.14)
was packed in butter paper pouches with 60g of product in each packet (Plate No.15). All the
weighment was done with electronic kitchen scales. The packed pouches ready for intervention
were kept in air tight containers in a dry place at room temperature and the subjects were also
asked to store the pouches once distributed, in air tight containers in dry places to avoid any
spoilage.
Plate No.14. The developed low glycaemic index multigrain mix ready for packing
Plate No.15. Packing of 60g of the developed low glycaemic index multigrain mix

66. 3.11. Developmentof aids and brochures for nutrition counseling:
The aim of the nutrition counseling for diabetic patients is to bring awareness of the
disease among the patients and make them understand the importance of dietary management for
good control of the disease. Counseling also brings positive changes in knowledge, attitude and
practice among the participants for the positive modification of life style. Appropriate tools are
necessary for making any counseling plan more effective. In the present study, diabetes
information folders, both in local language (Telugu) and English (Annexure-), picture charts and
demonstrations were used to reach out the study subjects with information effectively. The
information folders contain information on diabetes, symptoms and desirable dietary
modifications. The base-line patient information obtained with the help of suitably designed and
pre-tested questionnaire helped to develop the appropriate diet counseling plan for both one-to-
one and group counseling. The tools used in the study are given in annexure-
3.12. PILOT STUDY:
A pilot study was conducted to evaluate the feasibility of the study and test the study tools with
ten type 2 diabetic subjects. The pilot study included the collection of data regarding the knowledge,
attitude and practice of study subjects on diabetes mellitus, food habits, likes and dislikes, anthropometric
measurements,body composition and dietary assessment. Nutrition counseling was given to the same
group. One week later the post test was done. The tool and the counseling structure were found feasible
for the study. The pilot study samples were excluded from the main study.
3.13. EthicalCommittee Approval:

67. An institutional ethical committee discussion meeting was held at the department of
Home Science, SPMVV, Tirupati. During the meeting the members were explained the details of
the present project and objectives of the study. The approval of the committee was obtained for
conduct of the study (vide letter.IEC Ref No. SPMVV/Acad/C1/VI/2018 Dt 15.10.2018) as per
the approved project proposal. The procedures were followed in accordance with the ethical
standards of SPMVV, Tirupati.
3.14. Intervention of low glycaemic index multigrain mix:
In the present study, the intervention of low glycaemic index multigrain mix was given to
FEED and FED groups (Plate No.16). Each subject in these two groups was requested to
consume 60g of the product per day for ninety days. The multigrain mix was supplemented without
disturbing the daily dietary pattern of the subjects in FEED and FED groups. But the selected
subjects were asked to consume the low glycaemic index multigrain mix by replacing any of the
main meals of the day preferably breakfast. Though the results of microbiological test of the
study product assured shelf life for more than 90 days, the subjects were given the product
packed in double zip lock pouches for every fifteen days. Because of this, freshness of the
product was maintained and also facilitated the investigator to monitor the subjects by meeting
them often. The subjects participating in dietary intervention were asked to cook and consume
the low glycaemic multigrain mix in different forms like porridge, upma or idli, to avoid
monotony. The amount of water, salt to taste and seasoning to be added were explained and
demonstrated initially to all the study subjects in FEED and FED groups. Each subject was given
an identity number to note down the flow of supply of the multigrain mix. The comments or
discomforts if any expressed by the subjects were recorded. The control group and NEED
(exposed to only nutrition counseling) received the recipe at the end of the study period.
Plate No.16. Distribution of low GI multigrain mix to the subjects of FEED group

68. 3.15. Intervention of nutrition counseling sessions:
In the present investigation, NEED and FEED groups received the nutrition counseling
intervention, during each visit over a period of 90 days, with the help of suitable counseling plan
(Annexure-.. ) and tools. In the first interacting sessions, the subjects were provided with the
information folders. The control group and FED group (exposed to only dietary intervention)
received nutrition counseling and information folders at the end of the study period. Individual as
well as group sessions (Plate No.17) were carried out and each counseling session was for about
one hour. For each visit there was a 10 days interval in the first 30 days and at 20 days interval
for the remaining 60 days of the intervention period. Demonstrations of some easy recipes were
given during counseling sessions. Even off the sessions, the investigator was accessible to the
subjects over telephone, for any assistance in this regard. Social media like whatsapp was used
for sending information to literate subjects. Group discussions were conducted to share the
patient experience among the study subjects. Counseling sessions were carried out in local
language (Telugu). Issues related to diabetes, its causative factors, symptoms, short and long
term complications, disease management including recommendations for physical activity and
nutrition, foot care and incidence of hypoglycaemia were explained during the counseling
sessions. Importance of healthy life style and behavioural changes was emphasized during the
counseling period. Since support of family members plays a vital role in a patient’s disease
management, involving them in diabetes diet care counseling may bring positive outcomes. So in
the present study, spouse or family members of the study subjects also were invited to attend the
nutrition counseling sessions along with the subjects.

69. Plate No.17. Group nutrition counseling to the subjects of NEED group by the investigator
3.16. StatisticalAnalysis:
The data were computerized and analyzed using SPSS package 20.0 version. Mean
values, standard deviation, independent sample student’s t-test, paired t-test, chi-square test and
one way ANOVA were used in appropriate situations. The means were tested for significance by
critical difference. The results were presented and discussed in the following chapter.
*******
4. Results and discussion

70. Type 2 Diabetes mellitus is considered as the most common disease across the world,
especially in India, which requires continuous medical care with multi-dimensional risk
reduction strategies. It is a lifestyle disease and various studies revealed that slight modification
in the life style will bring positive results in the treatment of the disease. Several studies have
reported a positive impact of patient counseling on glycaemic control and quality of life
outcomes among the patients with type 2diabetes. Various experimental studies proved that the
concept of glycaemic index plays an important role in the dietary management of type 2 diabetes.
With this background, the present study was undertaken to elucidate the therapeutic effect of
intervention of a low glycaemic index multigrain mix and nutrition counseling on parameters
like blood sugar level, HbA1C and lipid profile among the type 2 diabetics.
Data on general profile of the subjects, their personal habits, dietary practices, disease
history, clinical symptoms, medical care, physical activity, anthropometry, body composition,
biochemical parameters and also level of awareness of the disease were collected and analyzed at
both base line and end line. The results obtained in the present study are tabulated and presented
with graphs and figures followed by discussion of the same in the chapter under the following
subheadings.
4.1. General profile of the subjects,
4.2. Disease profile of the subjects,
4.3. Personal habits of the subjects,
4.4. Possible risk factors among the subjects,
4.5. Interventions,
4.5.1. Nutrition Counseling,
4.5.1.1. Effect of nutrition counseling on physical activity,
4.5.1.2. Effect of nutrition counseling on attitude towards management of diabetes,
4.5.1.3. Effect of nutrition counseling on knowledge attitude and practice,
4.5.1.4. Effect of nutrition counseling on frequency of consumption of various foods,
4.5.2. Dietary intervention-intervention of low glycaemic index multigrain mix,
4.5.2.1. Sensory evaluation of the developed multigrain mix,
4.5.2.2. Analysis of nutrient composition of the developed multigrain mix,
4.5.2.3. Microbiological evaluation of the developed multigrain mix,
4.5.2.4. Assessment of glycamic index of the developed multigrain mix,
4.6. Effect of interventions on Anthropometric measurements and body
composition,
4.7. Effect of interventions on biochemical parameters,
4.8. Effect of interventions on clinical symptoms of diabetes,
4.9. Effect of interventions on long term complications of diabetes,
4.10. Effect of intervention on intake of nutrients.
4.11. Participants’ compliance to intervention of nutrition counseling,
4.12. Participants’ compliance to intervention of low glycaemic index multigrain mix.
4.1. Generalprofile of the subjects:

71. A final total of 120 subjects had participated in the 90 days period of the study. Based on
the treatment given, total selected subjects were divided into four groups, control group, NEED,
FEED and FED groups with 30 subjects in each group randomly allocated. The control group did
not receive any intervention but NEED group received only nutrition counseling, FEED group received
both dietary intervention and the nutrition counseling and FED group received only dietary intervention.
The pre- and post-tests were carried out to all the four groups. The demographic characteristics of the
subjects are presented here.
Table.12. Demographic characteristics of the selected subjects of all the groups
S.No Characteristics
Control (n=30) NEED (n=30) FEED (n=30) FED (n=30) Total (N=120)
n % n % n % n % n %
1
Gender Female 12 40.00 10 33.33 14 46.67 12 40.00 48 40.00
Male 18 60.00 20 66.67 16 53.33 18 60.00 72 60.00
2
Age (years)
35-45 8 26.67 8 26.67 11 36.67 5 16.67 32 26.67
45-55 10 33.33 12 40.00 11 36.67 17 56.67 50 41.67
55-65 12 40.00 10 33.33 8 26.67 8 26.67 38 31.67
3
Ethnicity
Andhra Pradesh 1 3.33 5 16.67 5 16.67 1 3.33 12 10.00
Telangana 29 96.67 25 83.33 24 80.00 29 96.67 107 89.17
South India 0 0.00 0 0.00 1 3.33 0 0.00 1 0.83
North India 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00
4
Marital status
Unmarried 0 0.00 1 3.33 0 0.00 0 0.00 1 0.83
Married 27 90.00 28 93.33 29 96.67 27 90.00 111 92.50
Divorcee 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00
Widow/widower 3 10.00 1 3.33 1 3.33 3 10.00 8 6.67
5
Education
Illiterate 3 10.00 2 6.67 1 3.33 6 20.00 12 10.00
Primary 1 3.33 6 20.00 1 3.33 2 6.67 10 8.33
High school 18 60.00 11 36.67 11 36.67 11 36.67 51 42.50
College 5 16.67 6 20.00 10 33.33 8 26.67 29 24.17
University 3 10.00 5 16.67 7 23.33 3 10.00 18 15.00
6
Occupation
Employee 8 26.67 12 40.00 14 46.67 2 6.67 36 30.00
Business 6 20.00 2 6.67 4 13.33 9 30.00 21 17.50
Professional 4 13.33 7 23.33 5 16.67 8 26.67 24 20.00
Home maker 8 26.67 6 20.00 5 16.67 8 26.67 27 22.50
Daily wage 2 6.67 0 0.00 0 0.00 0 0.00 2 1.67
Any other 2 6.67 3 10.00 2 6.67 3 10.00 10 8.33
7
Family type Joint 6 20.00 8 26.67 6 20.00 9 30.00 29 24.17
Nuclear 24 80.00 22 73.33 24 80.00 21 70.00 91 75.83
8 Monthly
income(₹)
<10000 11 36.67 8 26.67 3 10.00 11 36.67 33 27.50
10000-24999 11 36.67 13 43.33 15 50.00 11 36.67 50 41.67
25000-50000 5 16.67 5 16.67 6 20.00 8 26.67 24 20.00
>50000 3 10.00 4 13.33 6 20.00 0 0.00 13 10.83

72. The demographic characteristics of the selected subjects of the present study are shown in
table.12. The general profile included details of gender, age,ethnicity, marital status, education,
occupation, type of family, and monthly income of the subjects.
4.1.1. Gender:
The percentage distribution of male and female subjects among all the groups is presented in
table.12.1. The results showed that out of total 120 subjects, the male subjects (n=72; 60%) were more
than female subjects (n=48; 40%). The groupwise results also showed the similar distribution of the
gender among the selected subjects of all the groups.
It was observed that in the present study the personal habits like consumption of alcohol, lack of
physical activity, high glycemic load from white rice and unhealthy food habits were found to be more
among the male than female subjects. This might be the reason for more percentage of men having type 2
diabetes than that of women among the selected subjects in the study.
The results were on par with the study by Reddy et al. (2002) where it was reported that male
diabetics (26%) were more than female (9%) diabetics out of 24 percent diabetics of total sample of 3307
in Andhra Pradesh (joint state). Priyanka and Angadi (2010) also found 67.1percent males and 31.9
percent females in a hospital based study in Bijapur and Di Onofrio et al. (2018) found male (68%) and
female (32%) in Italy. According to IDF, it is estimated that in 2019 the prevalence of diabetes in women
is to be less (9.0%) than that in men (9.6%) (Saeedi et al., 2019). Nordstrom et al. (2016) reported that in
recent years the prevalence of type 2 diabetes mellitus is higher in older men than in women which is
associated with difference in visceral fat accumulation.
4.1.2. Age:
The percentage distribution of age among the selected subjects is shown in table.12.2. The
selected subjects fall in the age group of 35 to 65 years and it was grouped into three age groups as, 35-45
years,45-55 years and 55-65 years in the study. The mean age was 49 years among 120 subjects. Overall
the highest percentage (41.67%) of diabetics was found in the age group of 45-55 years,followed by 55-
65years age group (31.67%) and 35-45 years age group (26.67%). Similar trend was observed in NEED,
FEED and FED groups but in control group, the highest percentage of diabetics (40%) was found in the
age group of 55-65 years,the oldest age group of the study.
Being over 45 years of age is one of the risk factors of degenerative diseases like type 2 diabetes.
Central obesity and insulin resistance are frequently found among the elderly people which may be due to
the decrease in lean body mass and increase in body fat,particularly visceral fat that often accompanies
aging. In the study, the mean visceral fat (11.98) and the mean waist circumference (39.23 inches) (vide
table.30) were indicating the centraladiposity. Physical inactivity and lack of proper personal care and
diet are common among the Indian elderly people. This might be the reason for the maximum percentage
of subjects found in the age group of 45-55 years in the study. But it is alarming to find about one-fourth
of the subjects in the youngest age group of 35-45 years in the study. The reason for this may be the
sedentary life style, and increased consumption of fats (table.45.6) predisposing to obesity (table.31). The

73. psychological factors like work related stress also might be a reason for the young adults finding with
type 2diabetes in the study.
The results of the study are similar to the results of Gupta et al. (2015), where it was reported that
the greatest number of diabetics was between 40 and 59 years of age in India. Wild et al. (2004) reported
that the prevalence of diabetes is similar in men and women globally but it is slightly higher in men less
than 60 years of age and women at older ages. Htike et al. (2015) also found that an increase in obesity
along with sedentary life style have contributed to the onset of Type 2 diabetes mellitus in young adults.
4.1.3. Ethnicity:
The percentage distribution of ethnicity of the selected subjects of all the groups is shown in
table.12.3. The ethnicity was classified into four regions as, Telangana state, Andhra Pradesh, Other
southern states and Northern state. Overall the maximum percentage of subjects (89.17%) belonged to
Telangana state and 10 percent of the subjects were from Andhra Pradesh. Only 0.83 percent belonged to
the other southern states. The results of individual groups also followed the similar trend with the
maximum percentage of subjects from Telangana state.
Though Hyderabad city where the study was conducted is a cosmopolitan city, being the capital
of Telangana, the majority of the subjects were found to be the settlers of Telangana. The high prevalence
of obesity (table.31), one of the risk factors of type 2 diabetes was observed among the subjects of
Telangana area residing in Hyderabad city. The shift in lifestyle in terms of high daily calorie intake (vide
table.45.1) and low levels of physical activity might be the prime reason for the remarkably high
prevalence of obesity. The reasons that might have caused obesity among the subjects were: the regular
consumption of non-vegetarian food (table.14.1) and alcohol (table.15.1) on all occasions irrespective of
the gender which was found to be the cultural habit of Telangana people; groundnut being one of the
important commercial crops of Telangana, its usage as chutney or snacks was found to be high among the
selected subjects (table.24.4); being the dwellers of urban city, the subjects were habituated to eat junk
food which are high in saturated fat; majority of the selected subjects were using motor vehicles either
own or public transport, for reaching the work places which explained the sedentary life style of the
subjects.
The observations of the present study are supported by a study by Ramachandran and Snehalatha
(2009) where it was also reported that lifestyle changes with weight gain and decreased energy
expenditure contribute to the existing insulin inertia in urban areas. This study also reported that the major
changes in dietary patterns, decreased physical activity due to improved transportation, the availability of
energy saving devices, and the high level of mental stress are associated with modernization. It was
reported that the prevalence of diabetes in Andhra Pradesh (joint state) was 24 percent (Reddy et al.,
2002) and in Hyderabad city it was 16.6 percent (Mohan et al., 2007). According to the latest IDF
estimates, the prevalence is higher in urban (10.8%) than in rural (7.2%) areas (Saeedi et al., 2019). The
prevalence of diabetes is rapidly increasing among the poor in the urban slum dwellers and the middle
class (Mohan et al., 2007).
4.1.4. Maritalstatus:

74. The percentage distribution of marital status of the selected subjects was presented in table.12.4.
The marital status of the subjects was classified as married, unmarried, divorced and widow or
widower. The results showed that out of total 120 subjects, majority (92.5%) of the subjects were
married followed by unmarried (0.83%) and widows or widowers (6.67%) in the study. The
groupwise results also showed the similar observations as regards the marital status of the subjects.
Divorcees were found to be nil in all the groups.
It was observed that after marriage the attitude towards personal care regarding weight gain and
physical activity seems to be reduced among the selected subjects due to other priorities which might
have caused obesity (table.31), a risk factor for diabetes. Another interesting factor observed among
the subjects was endogamy and consanguinity which is common in the state of Telangana. This may
cause genetic disorders like type 2 diabetes where heredity is one of the risk factors (table.13.2). This
could be one of the potential reasons for the maximum percentage of diabetics among the married
subjects. Due to family and financial burden the married subjects neglect to go for health check-up
which leads to diabetic complications.
The results of the study in regards to marital status of the subjects are comparable with the study
by Mounica et al. (2015) where it was also presented that the married diabetics are 98 percent. The
family history due to endogamy is supported by Bener et al. (2013) where it is found that the family
history of diabetes mellitus is higher in patients of consanguineous parents (38.5%) than those of
non-consanguineous parents (30.2%).
4.1.5. Education:
The education of the patients helps to equip themselves with knowledge on the disease that
facilitates them to manage the disease better. The educational background of the selected subjects of
all the groups is presented in table.12.5. The level of Education of the subjects was grouped as
Primary, High school, College, University education and illiterates. Overall illiterates were found to
be 10 percent and among the educated,8.33 percent had primary school education, 42.5 percent had
high school education, 24.17 percent went to college and 15 percent of subjects were postgraduates.
The groupwise results displayed a different pattern of education among the selected subjects. The
maximum (20%) illiterates were found in FED group where as in the FEED group it was the least
(3.3%). As regards the primary and high school education, it was the maximum (63.3%) in control
group and was the least (39.9%) in FEED group. Graduates and postgraduates were the maximum
(56.6%) in FEED group with the minimum (26.7%) in control group.
The results of the study revealed that the prevalence of type 2 diabetes was more among the
educated subjects than those in illiterates or with primary school education. This indicated that the
educational level of the subjects may not be a good predictor of better glycaemic control. In-spite of
having knowledge about the importance of appropriate diet and exercise in the control of diabetes,
there was poor adherence to diet and exercise among the educated subjects. Poor physical activity and
more exposure and inclination towards consumption of junk foods and fatty foods was observed
among the educated which resulted in risk factors of diabetes like obesity and high waist
circumference and sedentary life style.

75. . The observations of the study were consistent with that of Al-Rasheedi (2014) where it was also
observed that education level of the patient with type 2 diabetes may not be a good predictor of better
therapeutic compliance. The percentage distribution of educational level among the subjects FED
group matches with that of a study by Sridhar et al. (2017) where it was 19 percent illiterates and 43
percent primary and secondary school education. In the present study the percentage of illiterates was
less when compared to that of various studies by Malathy et al. (2011), Adepu and Ari (2010) and
Mounica et al. (2015) wherein it was 29.2 percent, 28.2 percent and 30 percent respectively.
4.1.6. Occupation:
The data on occupation of the subjects are presented in table 12.6. Occupation of the subjects
was grouped as employee, business, professional, home maker, daily wage labourer and any other
occupation. Other occupation comprised of retired people and commission agents. Out of 120
subjects, 30 percent of the sample was employed, 20 percent was professionals and 17.5 percent was
business people. Home makers were 22.5 percent. The percentage of people who were living on daily
wages was 1.67and 8.33 percent of subjects were engaged in other occupations.
There was slight deviation in the groupswise results where the majority (63.33%) of employed
and professional was found in NEED and FEED groups and the least (6.67%) in FED group. FED
group was found with maximum (30%) business people. The majority of home makers (26.67%)
were found in control and FED groups whereas in FEED group it was the least (16.67%).
Occupation of the patient might not be a risk factor for diabetes but other factors like stress
associated with each type of occupation and eating pattern habituated to may cause diabetes. The
findings of the study revealed that about two-thirds of the study group was formed with employees,
professionals and business people. It may be attributed to obesity, physical inactivity and stress which
made them vulnerable to diabetes. Non-adherence to planned diet and physical exercise (table.17) due
to lack of time might be leading to obesity (table.31) among the working people. It was also observed
that working people were eating outside food rich in saturated fat,on regular basis instead of carrying
home-food which was causing weight gain and central obesity. The results showed that home-makers
constitute about one-fourth of the total selected subjects. Lack of awareness of the disease,stress,
physical inactivity and improper diet pattern were observed to be the reasons which might be causing
diabetes among the housewives in the study.
The observations of the present study are supported by Solja et al. (2014) where the findings
showed that job strain is a risk factor for type 2 diabetes in men and women independent of other lifestyle
factors. Stress has major effects on metabolic activity by stimulating the release of various hormones,
which can result in elevated blood glucose levels. Mohan et al. (2007) also found that the shift from
manual labour related work to physically less demanding office jobs for the past few decades is
leading to obesity which is causing the increased prevalence of diabetes.
4.1.7. Type of family:
The type of familymaynotbe a causative factorfor diabetesbutthe factorslike psychological
tensionsorstress,percapitaincome andfamilyburdensmayleadtodiabetes. The percentage
distribution of selected subjects according to the type of family they belonged to is shown in

76. table.12.7. The type of family was classified as joint and nuclear family. The results showed that out
of total 120 selected subjects, the majority of subjects (75.83%) were from nuclear families and one-
fourth of the study group (24.17%) was from joint families. The similar trend was observed among
the four groups with a majority from nuclear families.
From the results it was observed that in nuclear families the economic burden was less due to
less number of family members which increases the affordability of food when compared to joint
families. This contributed to increase the living standards of the subjects resulted in unhealthy eating
habits with consumption of calorie rich foods and large portion sizes. Overeating of energy dense foods
(table.45.1) causes obesity (table.31), a risk factor for diabetes and this might be the reason for the high
prevalence of type 2 diabetes among the nuclear families in the study. The family provides supports in
case of depression, stress and anger among the family members, but it was observed that this support is
lacking in nuclear families with limited number of family members. The unsupported stress is causing
elevated blood sugar levels leading to type 2diabetes among the selected subjects.
In contrary to the results of the study, Shankar (2016) in a study in Delhi reported that the
prevalence of type 2 diabetes mellitus is significantly higher in joint families than in nuclear families.
But the observations of the study in the management of stress are supported by Baig et al. (2015) where
it is stated that family support is not shown directly to control the glycemic state but strong family ties
can provide an environment where the patients can receive the management with utmost satisfaction and
happiness.
4.1.8. Monthly income:
It isimportantto know the income of the patients with type 2 diabetes because it affects the
quality and quantity of food that is consumed which is one of the key factors in the management of
diabetes. The data on grouping of the selected subjects according to the classification of monthly income
are displayed in table.12.8. Based on the monthly income, the subjects were classified into 4 groups as
lower income (<10,000/-), lower middle income (10000/- to 24999/-), upper middle income (25000/- to
50000/-) and high income group (>50000/-). The income-wise classification of the subjects showed that
out of total 120 selected subjects, the majority (61.67%) belonged to lower-middle income and upper-
middle income group together, followed by low income group (27.5%) and high income group (10.83%).
The group-wise data showed a different income distribution among the selected subjects of each
group. In control (53.34%) and NEED (60%) groups the majority belonged to middle income group. The
FEED group showed the least (10%) percentage of low income, the highest (70%) percentage of middle
income and maximum (20%) percentage of high income groups. In FED group majority (63.34%) was
middle income group but high income group was found nil.
The results of the study revealed that the prevalence of type 2 diabetes was high among the
middle income and high income groups when compared to that of low income group. Most of the
educated and employed were found in upper middle and high income groups which raised the standard of
living of the subjects falling under this category. It can be attributed to the increased affordability that left
the subjects in upper middle income and high income groups with high accessibility to calorie rich
unhealthful diets, fast-foods, rich in saturated fatty acids, more animal foods (table.14.1), sugary

77. beverages and highly refined cerealfoods which cause obesity (table.3). The subjects were able to afford
motor vehicles for transportation which was causing the physical inactivity. The shift from traditional to
modern life style practices with rising living standards were observed to be the major contributors to the
high prevalence of type 2 diabetes among the middle and high income groups in the study.
The results of the study are consistent with the study by Mohan et al. (2007), where it is reported
that according to CUPS (Chennai Urban Population Study) the prevalence of type 2 diabetes is higher in
middle income group (12%) compared to the lower income group (6.5%). The study also reported that
high calorie intakes by high-income groups in India are largely due to high intakes of refined cereals and
carbohydrates.
4.2. Diseaseprofile of the subjects:
It is important to know the disease profile of the subjects like duration of the disease,family
history of the disease and medication, before any treatment of diabetes and the details of which among the
selected subjects are presented in table.13.
. Table. 13. Disease profile of the selectedsubjectsof all the groups
4.2.1. Duration of disease:
Duration of disease is an important aspect in ascertaining the overall health of the patient
for taking further steps in the treatment. The data on the duration of diabetes that the selected
subjects were suffering from it are presented in table.13.1. The duration was grouped into
four slabs as less than a year i.e., newly diagnosed, 1 to 5 years duration, 5 to 10 years and
more than 10 years. Overall it was observed that the majority (38.3%) was found between 1
S.
No
Parameter
Control (n=30) NEED (n=30) FEED (n=30) FED (n=30) Total(N=120)
n percent n Percent n percent n percent N percent
1 Duration of
diabetes
<1 year 5 16.7 8 26.7 4 13.3 3 10.0 20 16.7
1-<5 15 50.0 10 33.3 10 33.3 11 36.7 46 38.3
5-<10 7 23.3 7 23.3 9 30.0 9 30.0 32 26.7
>10 3 10.0 5 16.7 7 23.3 7 23.3 22 18.3
Family history of
disease
Mother 10 33.3 10 33.3 6 20.0 8 26.7 34 28.3
2 Father 7 23.3 5 16.7 5 16.7 7 23.3 24 20.0
Both 4 13.3 8 26.7 8 26.7 2 6.7 22 18.3
Grand
parents 0 0.0 5 16.7 3 10.0 1 3.3 9 7.5
None 10 33.3 6 20.0 10 33.3 13 43.3 39 32.5
Medication
Drugs 29 96.7 27 90.0 27 90.0 26 86.7 109 90.8
Insulin 0 0.0 2 6.7 2 6.7 0 0.0 4 3.3
3 No
medication 1 3.3 1 3.3 1 3.3 4 13.3 7 5.8

78. to 5 years duration followed by 5 to 10 years duration (26.7%), newly diagnosed (less than
one year) subjects (16.7%) and the least (18.3%) in long duration of more than 10 years.
The groupwise data showed that the majority (26.7%) of newly diagnosed was found in
NEED group and the least (10%) was found in FED group. The duration of 1 to 5 years was
found the maximum (50%) in control group. The duration of more than 5 years was found
the maximum (53.3%) in FEED and FED groups. The control group was found with the least
(10%) percentage of subjects suffering for long duration of 10 years and above.
It was observed from the results that the majority of subjects in each group and overall
were suffering from diabetes for more than five years duration. Being the age of above 45
years is a non modifiable risk factor for type 2 diabetes and the mean age of the selected
subjects was found to be 49 years (table12.2). When there is a family history of parents being
diabetic the risk of getting diabetes will be more than 65 percent. In the study it was found
that more than two-thirds (66.6%) of the selected subjects had the family history of parents
being diabetic (table.13.2) which shows that the subjects were at high risk of type 2 diabetes
mellitus at the early age itself. Majority of the subjects were found to be obese (table.31),
another risk factor for diabetes due to the consumption of unhealthful diets with high energy,
high fat and low fibre. This shows that the subjects were negligent of weight gain in the
younger age which led them to obesity. It indicates that due to lack of knowledge (table.18)
of the above mentioned risk factors the selected subjects were landed at health risk which
may be the reason for finding the majority of them suffering for the longer duration.
The results of the study are on par with the results of various studies by Malathy et al.
(2011), Sridhar et al. (2017) and Priyanka and Angadi (2010) where it was found that
majority of the subjects (39.4%, 42% and 35% respectively) were suffering from the disease
for more than 5 years. Shah et al. (2009) reported a mean duration of 8.2 years in a study in
Gujarat.
4.2.2. Family history:
The family history of diabetes is one of the risk factors of type 2 diabetes. Knowing the family
history of disease of a diabetic is important to take steps in the treatment of diabetes and other
associated complications. So in the present study the data on family history of the selected subjects
were collected which are displayed in table.13.2. Overall the results of the study showed that,
majority (28.3%) of the selected subjects had the history of mother being diabetic followed by father
(20%), both mother and father (18.3%) and grandparents (7.5%). Percentage of subjects who did not
report any family history of diabetes was 32.5 percent. It showed that the total inheritance of the
disease from the immediate parents was about two-thirds (66.6%) of the total subjects in the study.
The groupwise results of family history of disease also showed similar trend with a maximum
percentage of parents being diabetic in each group. It was the maximum (76.7%) in NEED group and

79. the minimum in FED group (56.7%). The maximum percentage of subjects with no family history of
diabetes was found in FED group (43.3%) and the minimum was in NEED group (20%).
It was observed from the results that about 67.5 percent of the study population had a genetic
contribution to their disease. Endogamy, where marriages are performed within the family may be
one of the reasons for having high risk of family history of diabetes in the study. Due to lack of
knowledge of the risk factors of diabetes, it seems that the majority of the subjects have neglected to
go for health check-ups till the symptoms of diabetes are seen. It was alarming to observe that about
one-third (33.4%) of the study population had reported ‘no family history’ which indicates a rapid
emergence of diabetes among the general population without genetic risk, which is a threat to the
general public. It indicated that other factors like obesity, high waist circumference, body fat
(table.30) and other life style practices were the causative factors with lack of family history. It
reminds of the need for life style interventions which can delay the onset of type 2 diabetes mellitus.
The observations of the study are similar to the reports of Ramachandran and Snehalatha (2009)
where it is mentioned that nearly about 75 percent of type 2 diabetes patients in India have a first
degree family history, which indicates a strong familial aggregation in this population. Sridhar et al.
(2017) in a study also reported that 63 percent of diabetics were having family history of disease. The
results of the study are consistent with that of a study by Kang e al. (2008) where the results showed
that the percentage of mother (43%) being diabetic was the maximum, followed by father (17%) and
grandparents being diabetic (7%).
4.2.3. Medication:
The details of medication taken by the selected subjects of the study are shown in table.13.3. It
was observed that out of total120 subjects, the majority (90.8%) of the subjects was on
hypoglycaemic medication, very few (3.3%) were on insulin injection and the remaining (5.8%)
subjects were not taking any medication for diabetes. The similar results were found groupwise also
with the majority of subjects taking hypoglycaemic drugs as part of treatment. In control and FED
groups none was reported taking insulin injections. Of all the groups it was the FED group where the
majority (13.3%) of subjects was not on any hypoglycaemic drugs.
From the results it was observed that the majority of the subjects were having positive attitude
towards the adherence to medication as prescribed by the physician in a desciplined way. It wasvery
few who were not taking medication for diabetes and the non-compliance to medication was
intentional. The most common reasons reported for non-adherence to medication were lack of
knowledge about the disease and complications, the high cost of drugs and not experiencing the
instant relief.
The results of the study in regards to adherence of medication are on par with that of Al-Rasheedi
(2014) where the adherence to the diabetic medications among the patients was about 88
percent. The reasons for non adherence of medication found in the study are matching with the
barriers found in a study by Venkatesan et al. (2018) for the low adherence for treatment of diabetes
where the prevalence of low adherence for treatment is very high (45.4%) when compared to the
present study.

80. 4.3. Possible risk factors among the subjects:
The risk factors associated with diabetes can be said as irreversible risk factors like aging,
genetic, race and ethnicity and reversible risk factors such as diet, physical activity and personal
habits like smoking. Figure.5 shows the various risk factors possible for the prevalence of type 2
diabetes among the subjects of the present study. The global report on diabetes by WHO (2016)
reported that type 2 diabetes is determined by ethnicity, family history of diabetes and previous
gestational diabetes combined with older age above 45 years (Maki et al., 2015), over weight and
obesity, unhealthy diet, physical inactivity and smoking to increase risk. Anjana et al. (2011)
mentioned that the significant risk factors found in the ICMR-INDIAB study were age,family history
of diabetes, abdominal obesity, hypertension and income status.
From the results it was found that majority (73%) of the subjects were aged above 40 years
(table.12.2), the parents being diabetic was 65.8 percent (table.13.2) having a first relative as a
diabetic is one of the major non modifiable risk factors , obese (≥25 kg/m2
) were 69.2 percent,waist
circumference 39.23 inches (99.64cm) (table..30.2) the mean percentage of carbohydrates to total
calorie consumption was 65.90 percent (table.45.4) and 39 percent of subjects were leading inactive
or sedentary life style. For early detection Indian Diabetic Risk score (IRDS) was set using four
simple variables like age, family history, regular exercise and waist circumference as,high risk score
-60, moderate 30-50 and low risk <30, out of 100 (Mohan et al., 2007).
Fig.5. Possible risk factors of type 2 diabetes among the subjects
4.4. Personalhabits of the subjects:
73%
65.80% 69.20% 65.90%
39%
Age above 45
years
Family history
parents
Obesity CHO
consumption
per day
Sedentary life
Risk factors of type 2 diabetesamongthe subjects
Risk factors

81. Current evidence indicates that personal habits like eating pattern, physical activity, smoking and
alcoholism are important factors that increase the complications of diabetes. In the present study the
details of food habits, alcohol consumption and tobacco use were collected which show the behavior
and attitude of the subjects towards the management of the disease. The data on the details of
personal habits of the subjects among all the groups are presented in table .14.
Table.14. Personalhabits of the selected subjects of all the groups
S.No Habits
Control (n=30) NEED (n=30) FEED (n=30) FED (n=30) Total(N=1
n percent n percent n percent n percent N per
Food habits
Vegetarian 3 10.0 6 20.0 10 33.3 3 10.0 22 1
1 Non-vegetarian 27 90.0 23 76.7 18 60.0 26 86.7 94 7
Ova-vegetarian 0 0.0 1 3.3 2 6.7 1 3.3 4 3
Alcohol consumption
Alcoholic 14 46.7 14 46.7 10 33.3 10 33.3 48 4
2 Non alcoholic 14 46.7 16 53.3 18 60.0 18 60.0 66 5
Ex alcoholic 2 6.7 0 0.0 2 6.7 2 6.7 6 5
3
Tobacco use
Smoker 1 3.3 4 13.3 1 3.3 3 10.0 9 7
Ex smoker 2 6.7 0 0.0 3 10.0 1 3.3 6 5
Chewing 3 10.0 2 6.7 0 0.0 0 0.0 5 4
Snuff dipping 0 0.0 0 0.0 0 0.0 0 0.0 0 0
Not at all 24 80.0 24 80.0 26 86.7 26 86.7 100 8
Diet is an important factor for the onset as well as the treatment of type 2 diabetes. The data of
food habits of the selected subjects are presented in table.14.1. The food habits were categorized into
vegetarian, non-vegetarian and ova-vegetarian in the study. The overall results of the food habits showed
that majority (78.3%) of the subjects were non-vegetarians, followed by vegetarians (18.3%) and ova-
vegetarians (3.3%). The groupwise results also showed the similar percentage distribution of food habits
among the subjects of all the groups with the maximum non-vegetarians in control group (90%) followed
by FED (86.7%), NEED (76.7%) and FEED (60%). Among the vegetarians, the maximum was found in
FEED group (33.3%) followed by NEED (20%).
The results of the study showed a high prevalence of diabetics among non-vegetarians as
compared to vegetarians. The increased consumption of animal food (table.24.2) increases the intake of
fat (table.45.6) which leads to obesity especially the centralobesity, a leading risk factor for type 2
diabetes. The lack of knowledge about diabetes and the dietary management among the subjects in the
study might be the main reason for the increased consumption of animal food ignoring the vegetarian
diet.
The results of the study are supported by Sarwar et al. (2010) where it was reported that the BMI
is higher (29.2 kg/m2
) among the non-vegetarians when compared to that of vegetarians and semi
vegetarians and the prevalence of diabetes also is higher among the non-vegetarians. American Dietetic
Association suggests that appropriately planned vegetarian diets are healthful, nutritionally adequate and
provide health benefits in the prevention and treatment of certain diseases. In contrast to the results of
the study Adepu and Ari (2010) found 53.7 percent vegetarians and 46.3 percent mixed vegetarians.

82. The alcoholism is another personal habit that shows an impact on onset and management of
diabetes. The details of alcoholics among the selected study subjects are given in table.14.2. The results
showed that overall the non-alcoholics were more than half (55%) of the total 120 selected subjects,
followed by alcoholics (40%) and ex-alcoholics (5%). Among the groups, the results showed that the
maximum (60%) non-alcoholics were found in FEED and FED groups and the maximum (46.7%)
alcoholics were found in control and NEED groups.
The results showed that the overall ratio of alcoholics and non-alcoholics was 45:55 in the study.
The reason for finding about fifty percent of alcoholics among the diabetics may be because of the habit
of binge drinking which was observed to be more among the people of Hyderabad city in Telangana
(table12.3). Binge drinking causes obesity and increased waist circumference that develops insulin
resistance. Lack of knowledge of the disease among the subjects may also be one of the reasons for
continuing the habit of drinking even after diabetes is diagnosed. The results of the study are matching
with the reports of Mounica et al. (2015) where alcoholics were 54.1 percent. But surprisingly in a study
by Adepu and Ari (2010) non-alcoholics were found to be 91.2 percent.
Smoking is said to be a risk factor for developing type 2 diabetes and further complications like
CVD. The data on tobacco usage among the selected subjects are shown in table.14.3. From the overall
results it is encouraging to find a majority (83.3%) of non-smokers and a least percentage of smokers
(7.5%) and ex-smokers (5%) in the study. The groupwise results also followed the same trend with
majority of non-smokers. But tobacco chewing was found in control (10%) and NEED (6.7%) groups.
Snuff dipping was found to be nil in all the groups.
The results of the study are comparable with a study by Malathy et al. (2011) where it is also
found a minimum (12.4%) percentage of smokers and maximum (87.6%) of non-smokers and another
study by Adepu and Ari (2010) also found 94.7percent of non-smokers among the diabetic patients. In
contrary to the results of the study, a higher (45.4%) percent of smokers was found among the diabetic
patients by Karaoui et al. (2018) in a study in Lebanon. Reddy et al. (2002) reported that smoking rate is
24 percent in Andhra Pradesh (joint state) which is higher than that found in the present study.
4.5. Interventions:
In the present study the following two interventions were administered to the subjects and the
effect of each intervention was observed primarily on various parameters like anthropometric
measurements,biochemical parameters,clinical symptoms and complications and dietary assessment.
The effect of intervention on behavioural change and attitude towards management of diabetes also was
observed.
1. Nutrition counseling,
2. Dietary intervention: intervention of low glycaeemiic index multigrain mix.
4.5.1. Nutrition counseling:
Nutrition counseling was intervened for 90 days to randomly selected type 2 diabetics
with structured curriculum and teaching techniques. The results of effect of nutrition counseling
on various aspects are furnished here.
4.5.1.1. Effectofnutrition counseling on personal habits:
Table.15. Effectof nutritioncounselingonpersonal habitsof the subjectsof all the groups
Personal habits Control (n=30) NEED (n=30)* FEED (n=30)*

83. S.No
Before
(percen
t)
After
(percen
t)
Diff
(perce
nt)
Before
(perce
nt)
After
(perc
ent)
Diff
(perc
ent)
Before
(percen
t)
After
(per
cent
)
Diff
(percent)
B
(p
1 Alcoholics 46.67 46.67 0.00 46.67 46.67 0.00 33.33 33.33 0.00
2 Non alcoholics 46.67 46.67 0.00 53.33 53.33 0.00 60.00 60.00 0.00
3 Ex-alcoholics 6.67 6.67 0.00 0.00 0.00 0.00 6.67 6.67 0.00
Frequency of
consumption
Daily 10.00 6.67 3.33 6.67 0.00 6.67 6.67 3.33 3.33
Weekly 13.33 10.00 3.33 13.33 10.00 3.33 13.33 10.00 3.33
4 Fortnightly 6.67 6.67 0.00 13.33 16.67 -3.33 0.00 6.67 -6.67
Monthly 10.00 16.67 -6.67 6.67 13.33 -6.67 10.00 10.00 0.00
Occasionall
y
6.67 6.67 0.00 6.67 6.67 0.00 3.33 3.33 0.00
Quantity (ml) ≤ 90 16.67 23.33 -6.67 30.00 40.00 -10.00 26.67 26.67 0.00
5 >90 30.00 23.33 6.67 16.67 6.67 10.00 6.67 6.67 0.00
6 Smokers 3.33 3.33 0.00 13.33 13.33 0.00 3.33 3.33 0.00
7 Ex-smokers 6.67 6.67 0.00 0.00 0.00 0.00 10.00 10.00 0.00
8 Non smokers 80.00 80.00 0.00 80.00 80.00 0.00 86.67 86.67 0.00
9 Tobacco Chewing 10.00 10.00 0.00 6.67 6.67 0.00 0.00 0.00 0.00
10 Number of Cigarettes/day ≤
5
3.33 3.33 0.00 10.00 10.00 0.00 3.33 3.33 0.00
6
-
1
0
0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
≥
1
1
0.00 0.00 0.00 3.33 3.33 0.00 0.00 0.00 0.00
The effect of nutrition counseling on the personal habits among the selected subjects of all the
groups is presented in table.15. The results showed that overall there was no change observed in the
number of alcoholics, smokers, tobacco chewing and snuff dipping among the subjects after the
intervention period and the similar results were found among all the groups also. But the frequency of
consumption of alcohol was shifted from daily and weekly to fortnightly and monthly in NEED, FEED
and control groups after the study period. Overall it was observed that the quantity of alcohol
consumption more than 90 ml per day was reduced and shifted to less than 90 ml per day. Similar results
were found in control, NEED and FED groups also but there was no change in FEED group in regards to
the per day quantity.
Bringing positive changes in the attitude towards alcoholism which is a potential risk factor for
type 2 diabetes that may cause insulin resistance and pancreatic beta cell dysfunction among the diabetic
patients is part of nutrition counseling. In the present study a contrast effect was observed between the
two groups NEED and FEED that were exposed to the intervention of nutrition counseling. It was
observed that the effect of intervention was positive in NEED group where as it was null in FEED group.
The educational background (table.12.5) and the level of knowledge about the disease (table.18) were

84. found to be higher among the subjects of FEED group when compared to NEED group but a gap was
observed between knowledge and practice in regards to personal habits. The poor adherence to personal
habits with the high educational level may be because of the over self confidence among the subjects of
FEED group and the regular follow up programmes may change this attitude. Surprisingly some positive
change was observed even in control and FED groups but the impact was less when compared to that in
NEED group.
The results of the study are consistent with Di Onofrioetal.(2018) where a reduction in intake of
calories from alcohol (from 103.18 to 92.40 Kcal) was found after the motivational intervention. The
findings of the study are on par with Al-Rasheedi (2014) where it was found that educational level may
not be a good predictor of better therapeutic compliance.
Smoking is an independent and modifiable risk factor for type 2diabetes that may cause micro
and macro-vascular complications. Smoking is associated with insulin resistance,inflammation and
dyslipidaemia (Chang, 2012). Cessation of smoking is recommended to prevent cardiovascular
complications of diabetes and educating the patients in this regard is one of the important strategies of
management of diabetes. But in the present study patient counseling did not show any effect on tobacco
use among the subjects. It was found that the duration of study period is too short to bring any changes in
personal habits but it was good to observe that neither new cases have been added nor any increase in the
number of cigarettes, which might be due to the effective counseling on personal habits.
4.5.1.2. Effectofnutrition counseling on type of exercise among the subjects:
Physical exercise improves blood glucose controlin type 2 diabetes, reduces cardiovascular risk
factors, contributes to weight loss, improves overall well-being and may delay the progression of the disease.
So in the present study the type of physical exercise that the subjects are following was elicited before and
after the intervention period and the effect of nutrition counseling on the attitude towards it was observed.
Table.16.Effectof nutritioncounselingontype of physical exercise done bythe subjectsof all
the groups
S.No
Type of
exercise
Control (n=30) NEED (n=30)* FEED (n=30)* FED (n=30) Total (N=120)
Before
(perce
nt)
After
(perc
ent)
Diff
(per
cent
)
Befor
e
(perc
ent)
After
(perc
ent)
Diff
(per
cen
t)
Before
(perce
nt)
After
(per
cent
)
Diff
(per
cen
t)
Befor
e
(perc
ent)
After
(per
cent
)
Diff
(per
cent
)
Before
(percen
t)
After
(per
cent
)
Di
ff
(p
er
ce
nt
)
1
Brisk walk 50.0 50.0 0.0 66.7 80.0
-
13.3 53.3 70.0
-
16.7 53.3 46.7 6.7 55.8 61.6
5.
8
2
Jogging 3.3 0.0 3.3 6.7 10.0 -3.3 0.0 0.0 0.0 0.0 3.3 -3.3 2.5 3.3
-
0.
8
3
Cycling 6.7 3.3 3.3 0.0 0.0 0.0 3.3 0.0 3.3 0.0 0.0 0.0 2.5 0.8
1.
7
4
Swimming 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.
0

85. 5 Other
aerobics 0.0 0.0 0.0 10.0 6.7 3.3 10.0 6.7 3.3 0.0 0.0 0.0 5.0 3.3
1.
7
6
Yoga 0.0 0.0 0.0 13.3 23.3
-
10.0 16.7 16.7 0.0 6.7 6.7 0.0 9.2 11.7
2.
5
7
Others 3.3 0.0 3.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8 0.0
0.
8
The effect of nutrition counseling on type of exercise done by the selected subjects
among all the groups is presented in table .16. From the results an increase in percentage of type
of physical activity like brisk walk (NEED and FEED groups), jogging and yoga (NEED group)
was observed among the subjects of NEED and FEED groups which shows a positive impact of
nutrition counseling on the subjects. In contrast, either a reduction or no change was observed
after the study period among the subjects of control and FED groups, which were not exposed to
nutrition counseling. This showed a positive impact of nutrition counseling on the importance of
exercise and type of exercise in the management of diabetes in NEED and FEED groups. This
had an effect on improving the bone mass and reducing the visceral fat (table.30.8) and
improving the blood glucose levels in NEED and FEED groups after the intervention.
4.5.1.3. Effectofnutrition counseling on attitude of the subjects towards the
managementof diabetes:
Table.17. Effect of nutrition counseling on the attitude of the subjects towards the management
of diabetes amongall the groups.
Among the chronic diseases,diabetes is one of the most demanding in terms of behavioural
changes among the patients. The American Diabetic Association has advised that educating the
patients on self-management is essential to impart knowledge and skills that are essential for self-care
and lifestyle changes. But before starting the treatment,knowing the attitude of the patient towards
the management of disease is important.
The effect of intervention of nutrition counseling on attitude of the selected subjects in the study
towards the management of diabetes is presented in table.17. The aspects of management observed
were attitude towards physical exercise,adherence to planned diet and medication as prescribed by
Aspect of
management
Control (n=30) NEED (n=30)* FEED (n=30)* FED (n=30) Tota
S.No
Before
(perce
nt)
After
(perc
ent)
Diff
(per
cent
)
Before
(perce
nt)
After
(perc
ent)
Diff
(per
cen
t)
Befor
e
(perc
ent)
After
(perc
ent)
Diff
(per
cen
t)
Before
(perce
nt)
After
(perc
ent)
Diff
(per
cent
)
Befor
e
(perc
ent)
1
Physical
exercise
Yes
60.0 60.0 0.0 83.3 86.7 -3.3 70.0 80.0
-
10.0 53.3 50.0 3.3 66.7
No
40.0 40.0 0.0 16.7 13.3 3.3 30.0 20.0 10.0 46.7 50.0 -3.3 33.3
2
Planned
diet
Yes 70.0 80.0
-
10.0 76.7 93.3
-
16.7 80.0 100.0
-
20.0 86.7 90.0 -3.3 78.3
No 30.0 20.0 10.0 23.3 6.7 16.7 20.0 0.0 20.0 13.3 10.0 3.3 21.7
3
Medication
Yes 100.0 100.0 0.0 93.3 100.0 -6.7 100.0 100.0 0.0 100.0 100.0 0.0 98.3
No 0.0 0.0 0.0 6.7 0.0 6.7 0.0 0.0 0.0 0.0 0.0 0.0 1.7

86. the physician. The overall results (N=120) showed that there was an increase in the positive attitude
towards all the three aspects of management, physical exercise (2.5%),planned diet (12.5%) and
medication (1.7 % with cent percent acceptance) after the intervention period.
The groupwise results also showed similar increase in the positive attitude towards planned diet
among all the groups but the percentage increase was observed to be more among the subjects of
intervention-groups, NEED (16.7 %) and FEED (20 %). An increase in positive attitude was observed in
intervention groups, NEED (3.3 %) and FEED (10 %) towards physical exercise but there was no change
in control group and an increase in negative attitude was observed in FED group. Non-adherence to
medication was observed only in NEED group before intervention but that was changed to cent percent
positive after the nutrition counseling. This showed that nutrition counseling had a positive impact on
changing the negative attitude towards the aspects of management of diabetes in NEED and FEED groups
when compared to that of non-intervention groups. The effect of changed attitude was observed to be
reflected positively in anthropometry (table.33), biochemical indices (table.39) and intake of nutrients (
table.49).
Similar observations are found by Malathy et al. (2011) where a shift in the attitude of
patients was observed after the patient counseling that have an impact in improving the
perception about disease, diet, and lifestyle changes and thereby on glycemic control and the
complications of diabetes.
4.5.1.4. Effectofnutrition counseling on Knowledge, attitude and practice of
diabetes:
Knowledge about the disease plays an important role in the management of type 2 diabetes.
Patientswithtype 2diabetesshouldhave positive knowledge,attitudeandpractice whichpreventthe
occurrence of chronic complicationsassociatedwithdiabetes,whichinfluence the qualityof life of
patients.Inthe presentstudythe effectof nutritioncounselingonthe level of knowledge aboutthe
disease wasassessedamongthe selectedsubjects.
Table.18.Effectof nutritioncounselingonlevel of Knowledge amongthe subjectsof all the groups.
* Groups exposedtonutritioncounseling,*significant
The effectof nutritioncounselingonknowledgescoresamongthe selectedsubjectsof all the
groupsafterthe interventionperiodisshown intable.18,comparing with the two intervention-groups,
NEED and FEED. The knowledge scores were graded as inadequate knowledge (scores between 0-10),
S.No
Knowledge
Scores
Control (n=30) NEED (n=30)* FEED (n=30)* FED (n=30) Total (N=120)
B
(perc
ent)
A
(perc
ent)
Diff
(per
cent
)
B(pe
rcen
t)
A(per
cent)
Diff
(per
cent
)
B
(per
cent
)
A
(perc
ent)
Diff
(per
cent
)
B
(perc
ent)
A
(perc
ent)
Diff
(per
cent
)
B
(per
cent
)
A
(perc
ent)
Diff
(per
cent
)
1
Inadequate
(0-10) 33.3 33.3 0.0 6.7 3.3 3.3 6.7 0.0 6.7 26.7 20.0 6.7 18.3 14.2 4.2
2
Moderate
(11-21) 43.3 40.0 3.3 43.3 13.3 30.0 43.3 6.7 36.7 70.0 60.0 10.0 50.0 30.0 20.0
3
Good
(22-35) 23.3 26.7 -3.3 50.0 83.3
-
33.3 50.0 93.3
-
43.3 3.3 20.0
-
16.7 31.7 55.8
-
24.2

87. moderate knowledge (scores 11-21) and good knowledge score (22-35 score) with a total of 35.
Of total 120 subjects, the base-line results showed that the majority (50 %) of the subjects were
having moderate knowledge followed by good knowledge score (31.7 %) and inadequate knowledge
score (18.3 %). After the intervention it was observed that there was a statistically significant
(p<0.05) increase (24.2 %) in good score with a reduction in poor and moderate knowledge scores.
The groupwise results showed that the initial poor knowledge scores were more in non-
intervention groups (control-33.3 % and FED- 26.7%) when compared to that of intervention groups,
NEED and FEED (6.7 %). A positive impact of intervention of nutrition counseling was observed
among the subjects of intervention groups (NEED-33.3 % and FEED-43.3 %) after the intervention.
Post-intervention, the intervention groups had a significantly higher proportion of correct
responses to the questions about the disease when compared with the non-intervention
groups. After the intervention period there was no change observed in poor knowledge score in
control group but good score was increased slightly (3.3 %) in FED group and better improvement
(16.7 %) was observed in good score but less than that of intervention groups.
It is surprising to observe from the overall results that more than 80 percent of the subjects were
having medium to good knowledge levels in the study. The reasons for having better knowledge
scores may be that the diabetics are said to have more knowledge than the general public and there
may be fair chances of gaining knowledge regarding certain aspects of disease management with the
increased duration of the disease. (table.13.1).The difference in the initial knowledge level between
the groups may be because of the difference in educational background of the subjects. The
percentage of educated subjects was observed to be more in the intervention groups than that in non-
intervention groups (table.12.5). The higher educational background in intervention groups might
have resulted in higher perception of knowledge after the effective counseling. The higher level of
knowledge in NEED and FEED groups where higher percentage of employed and professionals
(table.12.6) were found shows that occupation of the subjects also has got an association with the
perception of knowledge. Figure.6 depicts the impact of nutrition counseling on knowledge scores of
subjects of all the groups.
Fig.6. Impact of nutrition counseling of knowledge scores of subjects of all groups

88. *Groups exposed to nutrition counseling
The results of the study are similar to Priyanka and Angadi (2010) where it was found in a
hospital based knowledge study in Bijapur, that the majority (59.9 %) of the subjects were with good
knowledge scores followed by medium (24.8 %) and poor (15.35 %) scores among the diabetics.
Deepa et al. (2014) reported that urban residents had higher awareness rate (58.4 %) when compared
to that of rural population (36.8 %) in ICMR India diabetes study. The poor knowledge level in the
present study was less when compared to the reports of other studies, 46 percent in Sridhar et al.
(2017) and 31 percent in Al-Maskari et al. (2013).
Severalstudies from different countries have reported that the disease awareness levelamong the
diabetic patients or the general public is not satisfactory (Naeema et al., 2002, Murugesan et al., 2007,
Al-Maskari et al., 2013, Islam et al.,2014 and Karaoui et al., 2018) which may cause an increasing in
the prevalence of diabetics. Several studies (Murugesan e al., 2007, Sridhar et al., 2017 and Deepa et
al., 2014) also supported that the diabetics will have more knowledge about the disease than the
general public. Similar to the observations of the present study a study by Priyanka and Angadi
(2010) also found that withlong duration of diabetes, knowledge also increased and the highest good
knowledge score (35%) was found among the patients with more than 5 years duration of disease in
particular.
The effect of educational background and occupation on the level of knowledge observed in the
study is supported by Murugesan et al. (2007) awareness of diabetes among diabetic patients.
The increase in knowledge score among the subjects after the counseling is similar to the results
of Malathy et al. (2011) where it is also reported an increase in knowledge scores by 24 percent after
a diabetes counseling among the diabetic patients in Erode district. Somannavan et al. (2008) reported
that multipronged diabetes awareness programme increased the awareness among the public in
Chennai.
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
Before (%) After (%) Before (%) After (%) Before (%) After (%) Before (%) After (%)
Control (n=30) NEED (n=30)* FEED (n=30)* FED (n=30)
poor (0-10)
Moderate (11-21)
Good (22-35)

89. It was observed from the base-line results of anthropometry and body composition (table.32) and
biochemical indices (table.38) that the higher level of knowledge about the disease found in the study
initially has not shown any impact on the maintenance of body weight or glycaemic control among
the subjects which shows that there is a gap between knowledge and practice before the intervention
period. But after the intervention it is encouraging to observe a positive impact of the increased
knowledge levels on good glycaemic control (table.39) as well as on the reduction of body weight and
visceral fat (table.33). A positive effect of improved knowledge level among the subjects was
observed in inclusion of millets in the diet and reduced intake of animal foods (table.24). Still the
follow up programmes with longer duration may fill the gap between knowledge and the practices to
show better outcomes with significant improvements in the disease management.
Table.19. Effect of nutrition counseling on level of attitude among the subjects of all the groups.
Attitude
Scores
Control (n=30) NEED (n=30)* FEED (n=30)* FED (n=30) Total (N=120)
B
(perce
nt)
A
(perc
ent)
Diff
(per
cent
)
B
(perc
ent)
A
(perc
ent)
Diff
(perc
ent)
B
(per
cent
)
A
(perc
ent)
Diff
(per
cent
)
B
(perc
ent)
A
(per
cent
)
Diff
(pe
rce
nt)
B
(perc
ent)
A
(per
cent
)
Diff
(perce
nt)
P valu
Negative
(0-11) 93.3 86.7 6.7 80.0 56.7 23.3 73.3 60.0 13.3 100.0 93.3 6.7 86.7 74.2 12.5
0.003
Positive
(12-19 ) 6.7 13.3 -6.7 20.0 43.3 -23.3 26.7 40.0
-
13.3 0.0 6.7 -6.7 13.3 25.8 -12.5
B-Before,A-After,*exposedtonutritioncounseling,**significant
The grades of attitude scores of the selected subjects among all the groups before and after the
intervention period are presented in table.19. The attitude scores were assessed as negative attitude
(scores 1-11) and positive attitude (scores 12-19) with a total of maximum 19. Of total 120 subjects,
initially the majority (86.7%) of the subjects showed negative attitude towards the disease and very
few (13.3%) had positive attitude. In the present study a significant (p=0.003) increase (25.8%) was
found in the positive attitude after the intervention among the subjects.
Fig.7. Impact of nutrition counseling on attitude scores of subjects of all the groups

90. Figure.7 represents the impact of nutrition counseling on attitude scores of selected subjects of all
the groups. The groupwise results showed that the initial negative attitude score was found the
maximum in FED group (100 %) followed by control group (93.3 %), NEED group (80.0 %) and
FEED group (73.3 %). After the intervention period the maximum percentage of decrease in negative
attitude scores was observed in intervention groups, NEED group (23.3 %) and FEED group (13.3%)
and the minimum in non-intervention groups, control and FED (6.7 %).
The negative attitude observed initially in the study was reflecting on the base-line reports of
mean body weight (table.32), blood glucose control and lipid profile (table.38) of the subjects which
were higher than the normal values. This shows that there lies a gap between higher knowledge level
and attitude of the subjects at base-line. But after the intervention in the present study some positive
change was observed in the attitude of the subjects which was the maximum in NEED group (43.3 %)
followed by FEED group (40.0 %), the two groups exposed to intervention of nutrition counseling,
when compared to non-intervention groups, FED (6.7 %) and control group (13.3 %). It explains that
the nutrition counseling has narrowed down the gap between the knowledge and the attitude of the
subjects regarding the disease at base-line. The impact of the changed attitude can be observed in the
better outcomes as regards the anthropometric measurements (table.33) and glycaemic indices
(table.39) after the intervention period.
The difference in initial attitude scores between the groups can be attributed to the higher
educational background and higher level of occupation among the intervention groups where the
chances of exposure to the disease through television, social media and colleagues are observed to be
more. The intervention of nutrition counseling added value to this which resulted in increasing the
positive attitude among the subjects of intervention groups. But the most notable finding is that there
was a gap between the knowledge and the attitude of the subjects which was not shown to be
increased as expected to the knowledge levels. It may be because of the customs and false beliefs like
avoiding consumption of fruits totally and millets that might be affecting on the change of attitude.
Unless the attitude is changed it cannot be translated to a good practice.
0.0
20.0
40.0
60.0
80.0
100.0
Before
(%)
After
(%)
Before
(%)
After
(%)
Before
(%)
After
(%)
Before
(%)
After
(%)
Control (n=30) NEED (n=30)* FEED (n=30)* FED (n=30)
Negative (0-11)
Positive (12-19 )

91. The results of the study are similar to Malathy et al. (2011) where it is found an increase (50%) in
attitude scores after the diabetes counseling but it is higher than the results of the present study. Al-
Maskari et al. (2013) found higher percentage (72%) of negative attitude among the patients in UAE
which is comparable to the results of the study. In contrary to the findings of the study Priyanka and
Angadi (2010) found 60-90 percent positive attitude among the patients in Bijapur.
Table.20.Effectof nutritioncounselingonlevel of practice amongthe subjectsof all the groups
S.No
Practice
Scores
Control (n=30) NEED (n=30)* FEED (n=30)* FED (n=30) Total (N=120
B
(per
cent
)
A
(perc
ent)
Diff
(perc
ent)
B
(per
cent
)
A
(per
cent
)
Diff
(per
cent
)
B
(perce
nt)
A
(per
cent
)
Diff
(per
cent
)
B
(perc
ent)
A
(perc
ent)
Diff
(per
cent
)
B
(perc
ent)
A
(per
cent
)
Diff
(per
cent
)
1
Negative
(0-10 ) 66.7 56.7 10.0 43.3 13.3 30.0 46.7 10.0 36.7 50.0 43.3 6.7 51.7 30.8 20.8
2
Positive
(11-18) 33.3 43.3 -10.0 56.7 86.7
-
30.0 53.3 90.0
-
36.7 50.0 56.7 -6.7 48.3 69.2
-
20.8
B-Before, A-After,*groupsexposedtonutritioncounseling,**significantly
The practice scores of the selected subjects among all the groups before and after the intervention
period is presented in table.20. The practice scores were assessed as negative scores (scores from 0-
10) and positive scores (scores from 11-18) with a total of 18. The results of overall subjects revealed
that the initial ratio of positive and negative practice scores was 48:52 but after the intervention
period the ratio was changed to 69:31. The increase (20.8%) in positive practice scores was
statistically significant at 0.05 level (p=0.000).
The individual groupwise results showed that the maximum negative practice scores among the
groups were observed in control group (66.7%) followed by FED group (50%), FEED group (46.7%)
and NEED group (43.3%) before intervention. But after the intervention period the maximum
(36.7%) reduction in negative practice scores was observed in FEED group followed by NEED
(30.0%), FED group (6.7%) control group (10.0%).The findings of the study revealed that the initial
positive scores were more among the subjects of intervention groups, NEED (56.7%) and FEED
(53.35) than that of non-intervention groups, control (33.3%) and FED (50.0%).
The higher level of knowledge and the poor practice scores observed in the study explains that a
large gap is laying between these two which left the subjects with the poor glycaemic control
(table.38) and poor management of the disease before intervention period. The moderate level of
initial positive practice scores among the intervention groups may be because of the higher
educational and socioeconomic background of the subjects found in the intervention groups
(table.12). The positive practice scores were observed to be increased among the subjects of the
intervention groups NEED (86.7 %) and FEED (90.0 %) after the intervention of nutrition counseling
which was reflected in the better outcomes in regards to anthropometric measurements (table.33),
blood glucose levels, lipid profile (table.38) and clinical symptoms (table.43). Still it appears that the
higher knowledge on diabetes did not translate into a good practice among the subjects of intervention
group as regards the physical activity, smoking and alcohol consumption. The ninety days period of
study may be too short to observe changes in long standing personal habits, the gap may be filled with

92. extended counseling programmes and regular follow up. Figure.8 shows the improvement in the
practice scores of the subjects after the nutrition counseling.
Fig.8. Impact of nutrition counseling on practice scores of subjects of all the groups
In contrary to the results of the present study, Malathy et al. (2011) found only 2.85 percent increase
in the practice score after the counseling which is very low comparatively.
4.5.1.4. Effect of nutrition counseling on frequency of consumption of
various foods:
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
Before
(%)
After
(%)
Before
(%)
After
(%)
Before
(%)
After
(%)
Before
(%)
After
(%)
Control (n=30) NEED (n=30)* FEED (n=30)* FED (n=30)
Negative (0-10 )
Positive (11-18)

93. A dietary survey was done to assess the nutritional status of the subjects. Food frequency is one
of the methods of diet survey to assess the frequency of consumption of each food item by the
individuals. The selection of foods and the frequency of their consumption by the patients with type 2
diabetes mellitus over a period of time explain the attitude and practice of the patients towards the
dietary management of the disease. In the present study food frequency questionnaire was used to
assess the dietary intake of the subjects and the effect of nutrition counseling on the food frequency
was observed.
Table.21. Effect of nutrition counseling on frequency of consumption of cereals and millets by the
subjectsof all the groups
S.No Food groups
Never
Daily
Once Twice
Before
(percent)
After
(percent)
Diff
(percent)
Before
(percent)
After
(percent)
Diff
(percent)
Before
(percent)
After
(percent)
Diff
(percent)
1
Rice
Control
(n=30)
0.0 0.0 0.0 63.3 73.3 -10.0 30.0 26.7 3.3
NEED
(n=30)*
0.0 0.0 0.0 63.3 93.3 -30.0 26.7 6.7 20.0
FEED
(n=30)*
0.0 0.0 0.0 46.7 86.7 -40.0 43.3 6.7 36.7
FED
(n=30)
0.0 0.0 0.0 73.3 83.3 -10.0 26.7 16.7 10.0
Total
(N=120)
0.0 0.0 0.0 61.7 84.2 -22.5 31.7 14.2 17.5
2
Wheat
Control
(n=30)
3.3 10.0 -6.7 46.7 53.3 -6.7 26.7 13.3 13.3
NEED
(n=30)*
3.3 10.0 -6.7 66.7 73.3 -6.7 3.3 0.0 3.3
FEED
(n=30)*
3.3 0.0 3.3 56.7 66.7 -10.0 0.0 10.0 -10.0
FED
(n=30)
3.3 0.0 3.3 56.7 56.7 0.0 16.7 13.3 3.3
Total
(N=120)
3.3 5.0 -1.7 56.7 62.5 -5.8 11.7 9.2 2.5
3
Millets
Control
(n=30)
63.3 63.3 0.0 10.0 6.7 3.3 0.0 0.0 0.0
NEED
(n=30*)
36.7 20.0 16.7 43.3 50.0 -6.7 0.0 0.0 0.0
FEED
(n=30)*
50.0 23.3 26.7 20.0 16.7 3.3 0.0 0.0 0.0
FED
(n=30)
60.0 50.0 10.0 13.3 16.7 -3.3 0.0 0.0 0.0
Total
(N=120)
52.5 39.2 13.3 21.7 22.5 -0.8 0.0 0.0 0.0

94. The frequency of consumption was assessed as‘never consumed’,consumed daily once or
twice or thrice, consumed weekly once or twice or thrice, consumed fortnightly or monthly or
occasionally. The frequency of consumption of cereals and millets by the selected subjects of all the
groups before and after the intervention is shown in table.21.
From the results of frequency of consumption of cereals and pulses, it was found that out of total
120 subjects the majority (61.6%) of the subjects were eating rice only once a day. Fifty percent of the
subjects (14.2%) who were consuming rice twice a day before intervention has changed to once a day rice
consumption after the intervention period. Wheat was consumed by 56.6 percent of the subjects daily
once and this was increased by 5.8 percent after the intervention period. More than half of the subjects
(52.5%) were never consumed millets but after intervention it was reduced (39.2%) and shifted to daily
once (22.5%), weekly once (11.7%) and weekly twice or thrice (9.2%).
The groupwise results revealed that before intervention eating rice thrice a day was observed
maximum (6.7%) in NEED group followed by control(3.3%) and FED (3.3%) and after the intervention
period this was observed ‘nil’ in all the groups. Change in attitude to consume rice only daily once was
observed the maximum in FEED group (40%), followed by NEED group (30%) control and FED groups
(10%). Wheat was observed to be never consumed by 3.3 percent of subjects in each group before
intervention but it has become nil in FEED and FED groups and in fact increased (by 6.7% each) in
control and FED groups. Daily once consumption of wheat was observed the maximum in NEED group
before (66.7%) and after (73.3%).
Never consuming the millets was the maximum by control group (63.3%) followed by FED
(60%), FEED (50%) and NEED (36.7%) and after intervention there was a maximum reduction observed
in intervention groups FEED (26.7%) and NEED (16.7%) whereas in non-intervention groups it was least
(10%) in FED group and no change observed in control group. Daily once consumption of millets was
increased by in NEED group (6.7%) and in FED group (3.3%) and reduced by 3.3 percent in control and
FEED groups. In NEED group weekly once consumption of millets was increased by 10 percent and
weekly twice was increased by 20 percent in FEED group. Occasionalconsumption of millets had
become nil in NEED,FEED and FED groups after the intervention period.
The results of food frequency of cereals and millets revealed that there were positive changes in
the consumption pattern of cereals and millets by the subjects which were observed more in NEED and
FEED groups when compared to that of FED and control groups. The change of frequency of rice eating
from thrice a day to once a day was a positive change for diabetics. This had resulted in decreased intake
of total calories per day and carbohydrates (table.49) which can help reducing the body weight in long run
and good glycaemic control (table.39). All the subjects of NEED and FEED groups had included wheat in
their diet after the intervention. It was interesting to note that millets had been made part of the diet in
NEED and FEED groups after the intervention which is a positive impact of nutrition counseling. This
showed that nutrition counseling had positively influenced the people in the reduced consumption of rice
and its frequency and increasing the consumption of millets. The survey revealed that the majority of
millets included were finger millet in the form of porridge and jowar as roti.

95. Table.22. Effect of nutrition counseling on frequency of consumption of pulses by the subjects of all the
groups
S.No Food
Groups
Never
Daily
Once Twice Th
Before
(percent)
After
(percent)
Diff
(percent)
Before
(percent)
After
(percent)
Diff
(percent)
Before
(percent)
After
(percent)
Diff
(percent)
Before
(percent)
Af
(per
1
Red
Gram
Dal
Control
(n=30)
0.0 0.0 0.0 16.7 20.0 -3.3 6.7 0.0 6.7 0.0 3
NEED
(n=30)*
0.0 0.0 0.0 26.7 30.0 -3.3 6.7 6.7 0.0 13.3 0
FEED
(n=30)*
0.0 0.0 0.0 33.3 43.3 -10.0 0.0 3.3 -3.3 3.3 0
FED
(n=30)
0.0 0.0 0.0 33.3 26.7 6.7 3.3 0.0 3.3 0.0 0
Total
(N=120)
0.0 0.0 0.0 27.5 30.0 -2.5 4.2 2.5 1.7 4.2 0
2
Green
Gram
Dal
Control
(n=30)
36.7 20.0 16.7 0.0 3.3 -3.3 0.0 0.0 0.0 0.0 0
NEED
(n=30)*
10.0 6.7 3.3 6.7 6.7 0.0 0.0 0.0 0.0 6.7 0
FEED
(n=30)*
10.0 10.0 0.0 6.7 0.0 6.7 0.0 0.0 0.0 6.7 0
FED
(n=30)
10.0 20.0 -10.0 3.3 0.0 3.3 0.0 0.0 0.0 3.3 0
Total
(N=120)
16.7 14.2 2.5 4.2 2.5 1.7 0.0 0.0 0.0 4.2 0
3
Black
Gram
Dal
Control
(n=30)
43.3 43.3 0.0 13.3 13.3 0.0 0.0 3.3 -3.3 0.0 0
NEED
(n=30)*
33.3 20.0 13.3 23.3 23.3 0.0 0.0 0.0 0.0 0.0 0
FEED
(n=30)*
6.7 3.3 3.3 20.0 13.3 6.7 0.0 0.0 0.0 0.0 0
FED
(n=30)
13.3 13.3 0.0 13.3 23.3 -10.0 0.0 0.0 0.0 0.0 0
Total
(N=120)
24.2 20.0 4.2 17.5 18.3 -0.8 0.0 0.8 -0.8 0.0 0
4
Bengal
Gram
Dal
Control
(n=30)
73.3 76.7 -3.3 6.7 3.3 3.3 0.0 0.0 0.0 0.0 0
NEED
(n=30)*
76.7 66.7 10.0 0.0 3.3 -3.3 0.0 0.0 0.0 0.0 0
FEED
(n=30)*
70.0 66.7 3.3 3.3 0.0 3.3 3.3 0.0 3.3 0.0 0
FED
(n=30)
86.7 90.0 -3.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0
Total
(N=120)
76.7 75.0 1.7 2.5 1.7 0.8 0.8 0.0 0.8 0.0 0
5
Others
Control
(n=30)
100.0 96.7 3.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0
NEED 90.0 96.7 -6.7 3.3 3.3 0.0 0.0 0.0 0.0 0.0 0

96. The frequency of consumption of pulses among the selected subjects before and after the
intervention is shown in table.22. The pulses included were the commonly used dhals like red gram
dhal, green gram dhal, blackgram dhal, Bengalgram dhal and any other pulses reported were grouped
as ‘others’. Red gram dhal being a commonly used pulse, never consumed was reported nil. The
results of total subjects showed that the maximum never consumed dhal was Bengalgram dhal
(76.7%) followed by black gram dhal (24.2%) and green gram dhal (16.7%). Daily consumption was
the maximum for redgram (27.5%) followed by blackgram (17.5%), greengram (4.2%) and
Bengalgram (2.5%). There was an increase in weekly thrice consumption for redgram (8.3%),
followed by blackgram (5%) and greengram (2.5%). The occasional use of Bengalgram was increased
by 5 percent.
Individual groupwise results showed that the consumption of redgram was more in FED group
followed by FEED group. The daily consumption of redgram was increased after the intervention
period in FEED (10%), NEED (3.3%) and control group (3.3%) whereas it was decreased in FED
group (6.7%) after the intervention. The maximum increase in weekly thrice consumption of redgram
was observed in NEED (20%) and FED (16.7%) groups.
The consumption of greengram was very less in control group when compared to that of
experimental groups. The weekly once consumption was observed to be increased in NEED (53.3%),
FEED (36.7%) groups after the intervention of nutrition counseling.
The percentage of never consumption of blackgram was the minimum (6.7%) in FEED group and
after intervention still reduced (3.3%). Whereas it was maximum in control group (43.3%) followed
by NEED (33.3%) and FED group (13.3%). A reduction of 13.3 percent was observed in NEED
group after the counseling but no there was change in non-intervention groups. In FEED group
weekly twice (3.3%) and weekly thrice (16.7%) consumption of blackgram was increased after the
intervention.
The maximum never consumption of Bengalgram in FED group (86.7%) was increased to 90
percent after the intervention where as in NEED (10%) and FEED (3.3%) groups it was reduced. The
occasional use of Bengalgram was increased in NEED (6.7%) and FEED (20%) after the intervention.
Only in NEED and FEED groups consumption of other pulses like kidney beans was observed
weekly once or fortnightly.
It was found from the results that the increased usage of pulses was more observed in FEED
group than in the other groups. After intervention, in NEED and FEED groups, the frequency of
consumption of pulses was shifted from never to occasional and weekly once to thrice or daily once.
In FED group frequency of consumption of pulses was better than that of control group but less than
(n=30)*
FEED
(n=30)*
93.3 96.7 -3.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0
FED
(n=30)
100.0 96.7 3.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0
Total
(N=120)
95.8 96.7 -0.8 0.8 0.8 0.0 0.0 0.0 0.0 0.0 0

97. NEED and FEED groups. As the percentage of low income and lower middle income groups (
table.12) was more in FED and control groups than in NEED and FEED groups, the less affordability
also might be a reason for less consumption of pulses in FED and control groups. And also the level
of education (table.12.5) was higher in FEED group and the good knowledge scores (table.18) about
the disease were more in NEED and FEED groups than the other groups. The effect of intervention of
nutrition counseling was greater among the intervention groups in regard to consumption of pulses.
Table.23. Effect of nutrition counseling on frequency of consumption of vegetables, fruits and dairy
productsby the subjectsof all the groups
S.No Food Groups
Never
Daily
Once Twice
Before
(percent)
After
(percent)
Diff
(percent)
Before
(percent)
After
(percent)
Diff
(percent)
Before
(percent)
After
(percent)
D
(perc
1
Other
Vegetables
Control
(n=30)
0.0 0.0 0.0 23.3 6.7 16.7 73.3 80.0 -6
NEED
(n=30)*
0.0 0.0 0.0 16.7 6.7 10.0 66.7 86.7 -20
FEED
(n=30)*
0.0 0.0 0.0 3.3 0.0 3.3 86.7 96.7 -10
FED
(n=30)
0.0 0.0 0.0 10.0 10.0 0.0 80.0 83.3 -3
Total
(N=120)
0.0 0.0 0.0 13.3 5.8 7.5 76.7 86.7 -10
2
Green
Leafy
Vegetables
Control
(n=30)
0.0 3.3 -3.3 0.0 3.3 -3.3 0.0 0.0 0
NEED
(n=30)*
0.0 0.0 0.0 13.3 10.0 3.3 3.3 3.3 0
FEED
(n=30)*
0.0 0.0 0.0 6.7 6.7 0.0 0.0 0.0 0
FED
(n=30)
3.3 3.3 0.0 0.0 3.3 -3.3 0.0 0.0 0
Total
(N=120)
0.8 1.7 -0.8 5.0 5.8 -0.8 0.8 0.8 0
3
Potato
Control
(n=30)
10.0 10.0 0.0 3.3 0.0 3.3 0.0 0.0 0
NEED
(n=30)*
26.7 16.7 10.0 3.3 3.3 0.0 0.0 0.0 0
FEED
(n=30)*
6.7 10.0 -3.3 0.0 0.0 0.0 0.0 0.0 0
FED
(n=30)
10.0 10.0 0.0 0.0 3.3 -3.3 0.0 0.0 0
Total
(N=120)
13.3 11.7 1.7 1.7 1.7 0.0 0.0 0.0 0
4
Fruits
Control
(n=30)
3.3 6.7 -3.3 10.0 13.3 -3.3 0.0 0.0 0
NEED
(n=30)*
16.7 0.0 16.7 16.7 16.7 0.0 0.0 0.0 0
FEED
(n=30)*
3.3 0.0 3.3 40.0 53.3 -13.3 0.0 0.0 0

98. FED
(n=30)
13.3 0.0 13.3 13.3 20.0 -6.7 0.0 3.3 -3
Total
(N=120)
9.2 1.7 7.5 20.0 25.8 -5.8 0.0 0.8 -0
5
Dairy
Group-I
(n=30)
10.0 6.7 3.3 23.3 30.0 -6.7 43.3 43.3 0
NEED
(n=30)*
3.3 0.0 3.3 73.3 56.7 16.7 10.0 36.7 -26
FEED
(n=30)*
3.3 0.0 3.3 30.0 33.3 -3.3 40.0 50.0 -10
FED
(n=30)
0.0 0.0 0.0 36.7 36.7 0.0 46.7 46.7 0
Total
(N=120)
4.2 1.7 2.5 40.8 39.2 1.7 35.0 44.2 -9
The frequency of consumption of vegetables, fruits and dairy products by the selected subjects of
all the groups before and after the intervention is presented in table.23. The vegetables were grouped as
green leafy vegetable (GLV), potato and other vegetables. Potato being the most commonly used
vegetable among the roots and tubers, it was specifically reported. Of total 120 selected subjects, ‘never’
and occasional consumption of other vegetables was observed nil. Vegetables were taken daily twice by
76.7 percent and it was increased to 86.7 percent after the intervention period. Mostly GLV were
consumed weekly once (25%) or twice (27.5%) or thrice (26.7%). Potato was never consumed by 13.3
percent and it was reduced by 1.7 percent after the intervention. The consumption of potato was observed
the maximum weekly once (23.3%) followed by weekly twice (10%) and weekly thrice (6.7%) and it was
reduced after the intervention period.
The results of fruit consumption showed that ‘Never’ consumption of fruits among the total
subjects (N=120) was 9.2 percent but reduced to1.7 percent after the intervention period. The percentage
of subjects consuming fruits was observed the maximum in daily (20%) followed by weekly once
(15.8%), weekly twice (14.2%) weekly thrice (9.2%), fortnightly (12.5%), monthly (6.7%) and
occasionally by (14.2%). The frequency of consumption of fruits was increased after the intervention.
Dairy products were never consumed by 4.2 percent and it was reduced by 2.5 percent after
intervention. The frequency of consumption of dairy was observed the maximum daily once (40.8%)
followed by daily twice (35%), daily thrice (15.8%) and weekly once (0.8%).
The results of individual groups, as regards the consumption of vegetables showed that the
majority of the subjects of all the groups was consuming daily twice with the maximum by FEED group
(86.7%), followed by FED (80%), NEED (66.7%) and control (73.3%) groups. This was reported to be
increased in all the groups after the intervention with a maximum in NEED (20%),followed by FEED
(10%), control (6.7%) and the least in FED group (3.3%). The FED group was found with never
consuming GLV and there was no change even after the intervention period. In NEED and FEED groups
there was an increase of 26.7 percent in the weekly thrice consumption after the intervention which is a
positive change.
Regarding the consumption of potato, the majority of subjects who never consumed was found
the maximum in NEED group (26.7%) followed by control group (10%), FEED (6.7%) and FED (10%)

99. group at base-line. After intervention no change was observe in control and FED group but in FEED
group 3.3 percent of people stopped eating potato. Majority of persons in the groups were consuming
potato weekly once.
As regards consumption of fruits, a negative attitude of never eating fruits was observed the
maximum in NEED group (16.7%) followed by FED (13.3%), FEED and control (3.3%) but after the
intervention surprisingly in all the three experimental groups ‘never’ eating has become nil whereas it was
increased in control group. Daily consumption of fruits was observed the maximum in FEED group
(40%).The consumption of weekly thrice was increased in NEED,FEED and FED groups at end-line
Occasional and monthly consumption of fruits was reduced in all the groups which shows that the
frequency of consumption fruits is increased after the intervention period.
From the results of consumption of dairy products it was observed that except in FED group,
there were subjects who never consumed dairy products in control (10%), FEED (3.3%) and NEED
(3.3%) groups. The daily once consumption was observed the maximum in NEED (73.3%) followed by
FED (36.7%), FEED (30%) and control (23.3%) groups. In NEED group there was an increase observed
in the frequency of daily twice (26.7%) and in FEED group daily once (3.3%) and twice (10.0%)
consumption of dairy products after the intervention. Weekly once taking dairy was started by 3.3 percent
each in NEED and FEED groups. Fortnightly, monthly and occasion consumption of dairy was nil in
FEED and FED groups. A positive impact of nutrition counseling was observed among the subjects of
NEED and FEED groups on intake of dairy products which was reflecting in calcium intake (table.49.8)
and bone mass (table.33.6).
The findings of the study regarding the frequency of consumption of vegetables and fruits showed
a positive impact of nutrition counseling in NEED and FEED groups. The results showed that in spite of
better socio-economic and educational background among the subjects of NEED group, a negative
attitude towards consumption of fruits was observed. The nutrition counseling might have helped them to
change the attitude positively after the intervention. Consumption of fruits in place of snacks was
observed in NEED and FEED groups after the nutrition counseling. Though the consumption of
vegetables was good in all the groups with twice a day frequency, the increase was observed to be more
among the subjects of intervention groups. Fruits and vegetables contain soluble dietary fibre which
delays glucose absorption from the small intestine and thus help preventing the sudden increase in blood
glucose levels following a meal (Asif 2014). This effect with subsequent glycaemic control was resulted
in the improvement in blood glucose levels (table.39) among the subjects of intervention groups in the
study. Consumption of GLV was shifted from weekly once or twice to thrice a week in NEED and FEED
groups when compared to that of control and FED groups. This resulted in increased intake of calcium
and iron (table.49.8) among the subjects after the intervention. The frequency of potato consumption was
reduced in FEED group after the intervention. It was good to observe that all the subjects in the
experimental groups started eating fruits and the frequency was increased more in FEED and NEED
groups.
The results of the study in regards to fruits consumption are supported by Di Onofrio et al. (2018)
where the consumption of fruits and vegetables was increased significantly after the nutrition
motivational intervention.

100. Table.24. Effect of nutrition counseling on frequency of consumption of animal foods, nuts and dry fruits
by the subjects of all the groups
S.No Food
Groups
Never
Daily
Once Twice
Before
(percent)
After
(percent)
Diff
(percent)
Before
(percent)
After
(percent)
Diff
(percent)
Before
(percent)
After
(percent)
Diff
(percent
1
Eggs
Control
(n=30)
16.7 16.7 0.0 6.7 6.7 0.0 0.0 0.0 0.0
NEED
(n=30)*
20.0 20.0 0.0 16.7 13.3 3.3 0.0 0.0 0.0
FEED
(n=30)*
40.0 40.0 0.0 6.7 3.3 3.3 0.0 0.0 0.0
FED
(n=30)
13.3 13.3 0.0 6.7 6.7 0.0 3.3 0.0 3.3
Total
(N=120)
22.5 22.5 0.0 9.2 7.5 1.7 0.8 0.0 0.8
2
Meat
Control
(n=30)
10.0 13.3 -3.3 3.3 3.3 0.0 0.0 0.0 0.0
NEED
(n=30*)
33.3 26.7 6.7 0.0 3.3 -3.3 0.0 0.0 0.0
FEED
(n=30)*
53.3 46.7 6.7 0.0 0.0 0.0 0.0 0.0 0.0
FED
(n=30)
13.3 10.0 3.3 0.0 3.3 -3.3 0.0 0.0 0.0
Total
(N=120)
27.5 24.2 3.3 0.8 2.5 -1.7 0.0 0.0 0.0
3
Fish
Control
(n=30)
20.0 16.7 3.3 0.0 3.3 -3.3 0.0 0.0 0.0
NEED
(n=30)*
36.7 36.7 0.0 0.0 3.3 -3.3 0.0 0.0 0.0
FEED
(n=30)*
53.3 53.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0
FED
(n=30)
23.3 20.0 3.3 0.0 3.3 -3.3 0.0 0.0 0.0
Total
(N=120)
33.3 31.7 1.7 0.0 2.5 -2.5 0.0 0.0 0.0
4
Ground
Nut
Control
(n=30)
3.3 0.0 3.3 6.7 16.7 -10.0 0.0 0.0 0.0
NEED
(n=30)*
10.0 0.0 10.0 0.0 0.0 0.0 0.0 0.0 0.0
FEED
(n=30)*
3.3 0.0 3.3 23.3 3.3 20.0 0.0 0.0 0.0
FED
(n=30)
0.0 3.3 -3.3 26.7 16.7 10.0 0.0 0.0 0.0
Total
(N=120)
4.2 0.8 3.3 14.2 9.2 5.0 0.0 0.0 0.0
5
Nuts
Control
(n=30)
40.0 43.3 -3.3 10.0 6.7 3.3 0.0 0.0 0.0
NEED
(n=30)*
43.3 53.3 -10.0 10.0 3.3 6.7 0.0 0.0 0.0

101. FEED
(n=30)*
26.7 30.0 -3.3 16.7 6.7 10.0 0.0 0.0 0.0
FED
(n=30)*
26.7 26.7 0.0 16.7 16.7 0.0 0.0 0.0 0.0
Total
(N=120)
34.2 38.3 -4.2 13.3 8.3 5.0 0.0 0.0 0.0
6
Dry
fruits
Control
(n=30)
40.0 50.0 -10.0 6.7 3.3 3.3 0.0 0.0 0.0
NEED
(n=30)*
53.3 73.3 -20.0 6.7 0.0 6.7 0.0 0.0 0.0
FEED
(n=30)
30.0 53.3 -23.3 13.3 0.0 13.3 0.0 0.0 0.0
FED
(n=30)
40.0 43.3 -3.3 3.3 3.3 0.0 0.0 0.0 0.0
Total
(N=120)
40.8 55.0 -14.2 7.5 1.7 5.8 0.0 0.0 0.0
The frequency of consumption of eggs, meat, fish, nuts and dry fruits among the selected subjects
of all groups before and after the intervention period is presented in table.24. From the results it was
observed that of total 120 subjects eggs were never taken by 22.5 percent of subjects and there was no
change observed even after the intervention period. The consumption of eggs daily once was observed the
maximum in NEED group (16.7%) and weekly once was the maximum in FED group (33.3%) before
intervention period. After the intervention in NEED and FEED groups the frequency of consumption of
eggs weekly twice and thrice was increased.
Though majority (78.3%) of subjects was non vegetarians (table.14.1) among the total subjects,
the never consumed meat was 27.5 percent before intervention and after the intervention it was reduced in
the experimental groups. Most of the subjects were taking meat once in a week with a majority in FED
(50.0%) followed by control group (46.7%), NEED (40percent) and FEED (23.3%) groups and after the
intervention period it was increased. Only subjects of NEED group were observed to be taking weekly
thrice and after the nutrition counseling it had become nil. This was supported by Di Onofrio et al. (2018)
where a decrease in meat consumption was reported after a motivational programme in Italy. . The
occasional consumption was increased by 3.3 percent in FEED group where as it was reduced in other
groups.
The results showed that consumption of fish was not regular among the subjects of all the groups.
Fish was never taken by maximum subjects of FEED group (53.3%) followed by NEED (36.7%), FED
(23.3%) and control (20%) groups but this was reduced in control and FED groups after the intervention
period. The reduced intake of animal products had shown an effect on fat intake (table.49.6) and
triglycerides (table.39.10) and visceral fat (table.33.8).
Since groundnut is the most commonly used nut in Telangana area where it is a major
commercial crop, the frequency of its consumption was recorded in specific. It was observed that very
few subjects were never consuming groundnut with a maximum (10%) in NEED group. The daily once
consumption was observed the maximum in FED (26.7%) followed by FEED (23.3%) group.
Surprisingly daily once consumption of groundnut was observed nil in NEED group. In NEED group

102. daily thrice was taken by 3.3 percent of the subjects but it was reduced after the nutrition counseling. The
weekly thrice frequency by FEED group was reduced to weekly once or fortnightly at end-line.
Fortnightly use of groundnut was increased in all the groups with maximum in NEED (26.7%) followed
by FEED (13.3%). Occasional use was increased in FEED and FED groups whereas in control group it
was increased.
When the frequency of consumption of nuts is observed, it showed that the never eating nuts was
increased in NEED and FEED groups with a maximum of 10 percent in NEED group after the
counseling. Daily once was reduced with maximum in FEED (10percent) followed by NEED (6.7%) and
control (3.3%). As regards nuts occasional usage was more among the groups. The effect of reduced
intake of nuts especially groundnut had a positive effect on weight reduction and visceral fat (table. 33)
and fat intake (table.49.6) but negatively affected the protein intake (table.49.2).
An increase in ‘never’ consumption of dry fruits was better observed in FEED (23.3%) and
NEED (23.0%) groups than that of non-intervention groups after the intervention. The impact of nutrition
counseling can be observed in reducing the consumption of nuts and dry fruits. Dry fruits were taken
occasionally by majority of subjects in all the groups. Reduced intake of dry fruits had resulted in better
glycaemic control in intervention groups (table.38).
Table.25. Effect of nutrition counseling on frequency of consumption of sweets, aerated drinks and
bakery items by the subjects of all the groups
S.No
Food
groups
Never
Daily
Once Twice
Before
(percent)
After
(percent)
Diff
(percent)
Before
(percent)
After
(percent)
Diff
(percent)
Before
(percent)
After
(percent)
Dif
(perc
1
Sweets
Control
(n=30)
26.7 23.3 3.3 0.0 0.0 0.0 0.0 0.0 0.0
NEED
(n=30)*
53.3 63.3 -10.0 0.0 0.0 0.0 0.0 0.0 0.0
FEED
(n=30)*
23.3 36.7 -13.3 0.0 0.0 0.0 0.0 0.0 0.0
FED
(n=30)
20.0 23.3 -3.3 0.0 0.0 0.0 0.0 0.0 0.0
Total
(N=120)
30.8 36.7 -5.8 0.0 0.0 0.0 0.0 0.0 0.0
2
Aerated
Drinks
Control
(n=30)
40.0 36.7 3.3 0.0 0.0 0.0 0.0 0.0 0.0
NEED
(n=30)*
33.3 63.3 -30.0 0.0 0.0 0.0 0.0 0.0 0.0
FEED
(n=30)*
50.0 66.7 -16.7 0.0 0.0 0.0 0.0 0.0 0.0
FED
(n=30)
43.3 53.3 -10.0 3.3 0.0 3.3 0.0 0.0 0.0
Total
(N=120)
41.7 55.0 -13.3 0.8 0.0 0.8 0.0 0.0 0.0
3 Biscuits Control
(n=30)
13.3 6.7 6.7 30.0 33.3 -3.3 3.3 6.7 -3.

103. NEED
(n=30)*
16.7 30.0 -13.3 3.3 0.0 3.3 0.0 3.3 -3.
FEED
(n=30)*
10.0 20.0 -10.0 30.0 10.0 20.0 0.0 0.0 0.0
FED
(n=30)
6.7 3.3 3.3 10.0 16.7 -6.7 10.0 0.0 10.
Total
(N=120)
11.7 15.0 -3.3 18.3 15.0 3.3 3.3 2.5 0.8
Other
Bakery
Items
Control
(n=30)
46.7 23.3 23.3 0.0 0.0 0.0 0.0 0.0 0.0
4 NEED
(n=30)*
33.3 33.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0
FEED
(n=30)*
36.7 33.3 3.3 0.0 0.0 0.0 0.0 0.0 0.0
FED
(n=30)
26.7 26.7 0.0 3.3 0.0 3.3 0.0 0.0 0.0
Total
(N=120)
35.8 29.2 6.7 0.8 0.0 0.8 0.0 0.0 0.0
The frequency of consumption of foods like sweets,aerated drinks, biscuits and other bakery
foods among the selected subjects before and after the intervention is shown in table.25. Being aware of
the fact that intake of sweets and empty sugars are restricted during diabetes, usually there will be a
craving for such foods among the patients with diabetes. The never consumption of sweets was observed
the maximum in NEED group (53.3%) followed by control group (26.7%), FEED group (23.3%) and
FED group (20%) at base-line. After the nutrition counseling this was observed to be further restricted
by NEED (10%) and FEED (13.3%) groups. It shows that in NEED and FEED groups after the nutrition
counseling the consumption of sweetened foods was controlled and shifted to occasional or monthly
consumption when compared to control group. These results of the study are supported by Di Onofrio et
al. (2018) where it was found that after nutrition motivation consumption of ice-cream, sweets and
candies was reduced significantly. The reduced intake of sweets might have resulted in reducing the
blood glucose levels and HbA1C in NEED and FEED groups (table.39).
In the similar way, the ‘never’ consumption of aerated drinks was observed to be increased
among the subjects of NEED (30%) and FEED (16.7%) and FED (10%) groups after the study period.
Majority of groups was observed consuming them occasionally and monthly. After the intervention the
occasional consumption was reduced in the experimental groups and was shifted to never taking when
compared to control group where it was shifted to monthly consumption.
Never consumption of biscuits and daily was increased in NEED (13.3%) and FEED (10%)
groups after the intervention. In the same way daily once taking biscuits was reduced by 3.3 percent and
20 percent in NEED and FEED groups and monthly or occasional use was increased.
All the groups had reported occasional consumption of other bakery foods which was shown to
be increased further after the intervention period. The change in the frequency of consumption of
biscuits and other bakery food might have helped in reducing the glycaemic control (table.39) and fat
intake (table.49.6).

104. 4.5.2. Intervention of low glycaemic index multigrain mix:
In the present study a low glycaemic index multigrain mix was developed with locally
available hypoglycaemic foods and assessed for sensory evaluation, nutritive value, shelf life
and glycaemic index for the intervention to the randomly selected patients with type 2 diabetes
for a period of ninety days.
4.5.2.1. Sensoryevaluationof the developed multigrain mix:
In the present study initially two products, product-I and Product-II were developed and
analyzed for sensory evaluation. Product-I contained raw ingredients like wheat, barley, maize,
defatted soy chunks, drumstick leaf powder and kalonji and Product-II contained raw ingredients
like wheat, barley, finger millet, defatted soy chunks, drumstick leaf powder and kalonji. Both
the products were presented in the form of upma for sensory evaluation. The scores of sensory
evaluation of both the products I and II are given in table.26. The results of the sensory
evaluation showed that product –I scored a mean total score of 3.19±20 and product-II scored
mean total score of 3.26±29 on a 5 point Hedonic scale (Annexure-). The score for overall
acceptance for product-I was 3.41 whereas for product-II it was 3.64 on a 5 point hedonic scale.
As the product-II got better overall acceptance and mean scores than product-I, product –
II was selected for further investigation in the present study.
Table.26. Scores of sensory evaluation of the developed products
S.No Sensory attributes Sensory scores
Product-I Product-II
1 Appearance 3.05 2.94
2 Colour 3.05 3.00
3 Consistency 3.29 3.52
4 Odour/smell 2.88 3.00
5 Texture 3.35 3.23
6 Taste 3.29 3.52
7 Overall acceptance 3.41 3.64
8 Mean 3.19 3.26
9 ±Sd 0.20 0.29
4.5.2.2. Analysis of nutrient compositionof the developed multigrain mix:
The developed low glycaemic index multigrain mix was analyzed for nutrient
composition in duplicates. The nutrient profile per 100g as well as per 60 g (daily dose) of the
product is furnished in table.27.
Table.27. Nutrient composition of the developed low glycaemic index multigrain mix
S.No Nutrient Quantity
Per 100 g
Per 60 g
product

105. 1 Energy 342.60 Kcal 205.56 Kcal
2 Crude
Carbohydrates
62.68percent 37.60 g
3 Crude Protein 17.93percent 10.75 g
4 Crude Fat 2.24percent 1.34 g
5 Moisture 10.25percent 6.15 g
6 Ash 3.06percent 1.8 g
7 Crude Fibre 3.84percent 2.30 g
8 Gluten Nil Nil
9 Beta Carotene 12.7 μg/100gm 7.62 μg
10 Calcium 2074.84 mg/Kg 1244.90 mg
11 Iron 84.04 mg/Kg 50.42 mg
12 Zinc 29.24 mg/Kg 17.54 mg
The results of analysis of nutrition composition of the multigrain mix showed that 100 g
of the multigrain mix will be providing with 342.60 Kcal of energy, crude carbohydrate 62.68
percent, crude protein 17.9 percent, crude fat 2.21 percent, moisture 10.25percent, ash 3.06
percent, crude fibre 3.84 percent, beta carotene 12.7 μg, calcium 2074.84 mg/Kg, Iron 84.04
mg/Kg and zinc 29.24 mg/Kg.
The subjects were asked to consumed 60 g of the product per day and it provided with
205.56 Kcal of energy, 37.60 g of crude carbohydrates, crude protein 10.75 g, crude fat 1.34 g
and 2.30 g of crude fibre. Sixty grams of multigrain mix contained 6.15 g of moisture, 1.8 g of
ash, 7.62 μg of beta carotene and the minerals like Calcium 1211.90 mg, Iron 50.42 mg and Zinc
17.54 mg.
Crude carbohydrate was computed by subtracting the sum of all the percentage values of
moisture, crude protein, crude fat, ash and crude fibre from 100.
Percentage crude carbohydrate = 100 % - (% moisture + % crude protein + % crude fat +
% ash + % crude fibre)
= 100 % - (10.25 % + 17.93% + 2.24% + 3.06% + 3.84%)
= 100 % - 37.32 %= 62.68%.
Energy was calculated using the following formula.
Energy (Kcal/100 g) = [9% protein x 4) + (% carbohydrate x 4) + (% fat x 9)]
= [(17.93% x 4) + (62.68% x 4) + (2.24% x 9)]
= 71.72 + 250.72 + 20.16 = 342.60 Kcal.
The results of nutrient composition of the multigrain mix showed that the total energy
205.56 Kcal/60g was contributed by carbohydrates, protein and fat by 73 percent, 20.9 percent
and 5.86 percent respectively. Though the percentage contribution of energy through
carbohydrates was high, the presence of complex carbohydrates and high protein content made
the multigrain mix low glycaemic. The inclusion of cereal (wheat, barley and finger millet) and
pulse (defatted soya chunks) in 4:1 ratio in the multigrain mix resulted in good amount of protein
(10.75 g/60 g). This is required for the subjects in the present study as the results of nutrient
intake revealed that the protein intake by the subjects was less than the recommended allowance.
(table.48.2). Since the processed soya was used, it can be assumed that trypsin inhibitors were
reduced making the protein bioavailable.

106. The results showed that 60 g of multigrain mix contained 1244.90 mg of calcium which
is almost double the amount of RDA (600 mg/day) for adults. The iron content also was high
with 50.42 mg/60 g when compared to the RDA for iron i.e., 17-21mg/day (ICMR, 2010) for
adults. This could be due to the inclusion of foods viz., finger millet and drumstick leaf powder
which are very good sources of calcium and iron in the multigrain mix. This resulted in the
statistically significant improvement in the bone mass (table.33.6) in FEED and FED groups
after the intervention of low glycaemic index multigrain mix.
Similar nutrient composition is found in a study by Ijarotimi et al. (2015) where it is reported
a higher range of crude protein 23.22-30.39 g/100g in the multi-plant based functional foods made to
evaluate antidiabetic potentials, where defatted soyabean was one of the ingredients. Ankita et al. (2010)
developed a low glycaemic composite dhalia in 50:20:30 ratio of bulgar broken wheat, steamed pearl
millet and green gram which was identified as the most nutrient rich product with 20.63 g/100g protein.
Husain and Bhatnagar (2018) developed parathas by replacing wheat with soya at different
levels and the results showed that paratha with 20 percent soy flour was the most acceptable with
18.39g protein, 43.33 mg calcium and 19.94 mg isoflavone. Hossain et al. (2018) in a study on
formulations for type 2 diabetics, also got similar nutritive values with protein-12.40 percent,fat-
3.33 percent, crude fiber-2.87 percent and energy 385.24Kcal for one of the low Glycemic Index
Multi-Whole Grain formulated flour samples using whole grains of wheat, wheat bran, rye,
maize, soya, barley, chickpeas and plantain husk in different ratios.
Though the product was made of wheat and barley, the seeds known for gluten content,
surprisingly the multigrain mix had shown to be gluten free (below 20 mg/Kg is considered as
gluten free (FSSAI, 2019). There is no scientific evidence that gluten free foods will have
hypoglycaemic effect for type 2 diabetics, but it is safe for people with celiac disease.
4.5.2.3. Microbiologicalevaluationof the developed multigrain mix:
The shelf life of the developed multigrain mix was evaluated through the microbiological
evaluation. The results of microbiological evaluation of the product at monthly intervals are
presented in table.28. The microbiological evaluation of the developed low glycaemic index
multigrain mix was carried out at monthly intervals for a period of 90 days (Annexure-). A
sample of the developed mix was irradiated with gamma rays to test the extended period of shelf
life. The results showed that the total bacterial count (TBC) and total mould count (TMC) were
at below detectable level till the end of 120 days period for both the irradiated and normal
samples. The results indicated that the developed low glycaemic index multigrain mix was safe
for the entire study period of 90 days for human consumption under normal storage conditions at
room temperature (30±20C) without radiation also. But to retain the freshness, the product was
supplied to the subjects at every fortnight.
Table.28. Microbiological evaluation of the developed low glycaemic index multigrain
mix
S.No Product
sample
30 days/ cfu/ml 60 days/ cfu/ml 90 days/ cfu/ml 120 days/ cfu/ml
TBC TMC TBC TMC TBC TMC TMC TMC
1 Normal BDL BDL BDL BDL BDL BDL BDL BDL

107. 2 Irradiated BDL BDL BDL BDL BDL BDL BDL BDL
TBC-Total bacterial count, TMC-Total mould count, BDL-Below detectable level
Cfu-colony forming unit
4.5.2.4. Assessmentof Glycaemic Index of the developedmultigrain mix:
In the present study the developed multigrain mix was assessed for glycaemic index in 13
healthy male volunteers. The comparison of GI of test food with that of reference food (glucose)
was done on three different visits (two visits for reference food and one visit for test food) with
an interval period of one-week for each session. The two outliers were excluded from the data-
set, because the abnormal values can have influence on the results of statistical analysis. The
Incremental area under the curve (IAUC) of reference food (mean value of two occasions) and
test food of 11 volunteers are shown in table.29. The results showed that the mean values of
IAUC of reference food and test food were 277.06±55.83 and 141.83±42.66 respectively. The
ratio of these two values (f : r) gave the glycaemic index of the product i.e., 51.51±11.73. This
can also be obtained by taking mean of individual GI ratio of all the volunteers. The glycaemic
index < 55 is considered as low glycaemic index hence the developed multigrain mix was said to
be a low glycaemic index multigrain mix. As the developed multigrain mix exhibited low GI
values it can be considered as a healthier dietary option for the patients with type 2 diabetes
mellitus.
Ankita et al. (2010) also followed similar procedure to find the GI of the designed diet
supplements like wheat dahlia and found it as low glycaemic index (35.20). Ankita (2005)
reported that GI of a composite flour, blended with wheat, Bengal gram and barley in 3:1:1 ratio,
was tested on both diabetic and non-diabetic individuals and was found low glycaemic with GI
of 50.
Table.29. Incremental area under the curve (IAUC) of the subjects with reference food (r) and
test food (f)
S.No Subjects IAUC
r
IAUC
f
GI ratio
(f : r)
1 1 329.55 129.45 39.28
2 2 353.40 162.45 45.96
3 3 319.65 206.40 64.57
4 4 190.20 113.55 59.70
5 5 265.12 100.95 38.07
6 6 278.10 104.10 37.54
7 7 225.45 141.67 62.83
8 8 214.95 118.20 54.98
9 9 252.75 156.00 61.72
10 10 265.12 100.87 38.04
11 11 353.40 226.20 64.00

108. 12 Mean 277.06 141.83 51.51
13 ±sd ±55.83 ±42.66 ±11.73
Figure.9 depicts the difference in the incremental area under the curve of reference food
(glucose) and the test food (low glycaemic index multigrain mix). The figure explains that the
curve of reference food is above the curve of multigrain mix which shows that the area under
the curve of reference food is more than that of low glycaemic index multigrain mix.
Fig.9. IAUC of reference food and the test food
4.6. Effectof intervention on anthropometric measurements and body
composition:
Anthropometry is used to assess the nutritional and health status of individuals that provides
detailed information on different components of body structure, especially muscular and fat components.
Any changes in the anthropometric measurements show the nutritional status of the subjects. The effect
of both the interventions, intervention of nutrition counseling and intervention of low glycaemic index
multigrain mix, on anthropometric measurements and body composition is presented and discussed here.
Table.30. Effect of interventions on mean anthropometric measurements and body composition of all the
subjects (N=120)
S.No Body composition
Before After Diff P value
Mean ±sd Mean ±sd Mean percent
1 Weight (kg) 71.58 13.19 71.77 13.10 -0.19 -0.27 0.676(NS)
2 Waist cir 39.23 4.87 39.13 5.17 0.10 0.25 0.512(NS)
0
100
200
300
400
1 2 3 4 5 6 7 8 9 10 11
IAUC of referenceandtest food
IAUC f IAUC r

109. (inches)**
3 BMI(kg/m2) 27.80 5.24 27.64 4.91 0.16 0.56 0.182(NS)
4 Body fat (percent) 33.38 9.77 33.34 9.26 0.03 0.10 0.874(NS)
5 Body muscle
(percent) 44.69 8.35 44.63 8.36 0.06 0.12
0.747(NS)
6 Bone mass
(percent) 2.55 0.42 2.58 0.41 -0.02 -0.95
0.036*
7 Body water
(percent) 46.27 5.69 46.18 5.13 0.09 0.19
0.626(NS)
8 Visceral fat (Rank) 11.98 4.01 11.70 3.98 0.28 2.36 0.045*
*Significant,NS-Notsignificant,**1inch=2.54cm
The mean values of anthropometric measurements and body composition of all the selected
subjects (N=120) before and after the intervention are presented in table.30. The anthropometric
measurements includes height (cm), body weight (Kg), waist circumference (inches), BMI (kg/m2
) and
body composition which comprised of percentages of body fat, body muscle mass, bone mass, total body
water and ranking of visceral fat. The mean height of the subjects was 160.9 ±8.85 cm. The body weight
of the subject ranged between 34.4 -113.7 Kg with a mean of 71.58±13.19 Kg. The mean value of waist
circumference was 39.23±4.87 inches (99.64 cm) and the mean BMI was 27.80±5.24 kg/m2
ranged
between 12.30 to 47.30 Kg/m2
. The mean values of body composition were as follows: body fat
33.38±9.77 percent, body muscle mass 44.69±8.35 percent,body bone mass 2.55±0.42 percent, total body
water 46.27±5.69 percent and visceral fat 11.98±4.01 (Rank).
Table.31. Classification of BMI of subjects of all the groups according to Indian criteria
S.No
BMI Classification
(kg/m2)
Control (n=30) NEED (n=30) FEED (n=30) FED
Before
(percent)
After
(percent)
Diff
(percent)
Before
(percent)
After
(percent)
Diff
(percent)
Before
(percent)
After
(percent)
Diff
(percent)
Before
(percent) (p
1 <18.5 underweight 3.3 3.3 0.0 3.3 3.3 0.0 0.0 0.0 0.0 0.0
2 18.5-22.99 Normal 13.3 13.3 0.0 16.7 20.0 -3.3 6.7 6.7 0.0 10.0
3 23-24.99
Overweight 10.0 10.0 0.0 6.7 6.7 0.0 16.7 16.7 0.0 36.7
4 ≥25 obesity 73.3 73.3 0.0 73.3 70.0 3.3 76.7 76.7 0.0 53.3
The classification of BMI according to the Indian criteria for BMI classification is presented in
table.31. According to the results, alarmingly majority (70 %) of subjects were obese (BMI ≥25 kg/m2
),
which is one of the risk factors for type 2 diabetes and 20 percent of the subjects were overweight (BMI
23-24.99 kg/m2
). This indicates the poor level of awareness regarding calorie intake and physical exercise
in reducing the body weight among the participants. Only 14 percent of the subjects were having normal
BMI (BMI 18.5-22.99 kg/m2
) and 2 percent were under weight (BMI <18.5kg/m2
).
The overall mean body weight after the intervention (table.30) was 71.77±13.10Kg, the mean
waist circumference was 39.13±5.17 inches (99.39 cm) and mean BMI was 27.64±4.91 kg/m2
. The mean
values of body composition were as follows: body fat 33.34±9.26 percent,body muscle mass 44.63±8.36
percent, body bone mass 2.58±0.41 percent,total body water 46.18±5.13 percent and visceral fat (Rank)
11.70±3.98.

110. The results revealed that after intervention, there was no statistically significant decrease in body
weight and other components of body composition except for bone mass and visceral fat. A statistically
significant (p=<0.05) increase in overall mean bone mass (p=0.036) and a significant decrease in mean
visceral fat (p=0.045) were observed after intervention when compared to that of before intervention.
Overall there was an increase in body weight by 0.27 percent and waist circumference was
decreased by 0.25 percent (mean difference 0.10 inches). The overall mean BMI was decreased by 0.56
percent. Though it was statistically insignificant, there was a trend of reduction of mean values of body
composition which is a good sign in the management of diabetes. Similar to the study, Ma et al. (2008)
also found a reduction of 0.12 inches in waist circumference,6 months after the dietary education
Table.32. Base-line anthropometric measurements and body composition (mean values) of the
subjects of all the groups
Table.33. End-line anthropometry and body composition (mean values) of the subjects of all the
groups
S.No
Body
composition
Control (n=30) NEED (n=30) FEED (n=30) FED (n=30)
Mean ±sd Mean ±sd Mean ±sd Mean ±sd
1 Weight
(kg) 71.02 12.51 72.66 15.36 73.55 10.64 69.08 13.37
2 Waist cir
(inches) 39.30 5.59 39.10 4.23 39.83 4.58 38.67 4.91
3 BMI
(kg/m2) 27.29 4.66 28.69 6.83 28.92 4.96 26.28 3.50
4 Body fat
(percent) 33.52 9.19 33.22 12.25 34.84 10.16 31.93 6.35
5 Body
muscle
(percent) 44.13 7.74 45.02 7.62 44.98 8.07 44.62 9.78
6 Bone mass
(percent) 2.54 0.39 2.56 0.37 2.60 0.38 2.52 0.51

111. S.No
Body
composition
Control (n=30) NEED (n=30) FEED (n=30) FED (n=30)
Mean ±sd Mean ±sd Mean ±sd Mean ±sd
1 Weight
(kg) 71.24 12.84 72.30 14.86 72.58 10.39 70.97 13.83
2 Waist cir
(inches) 39.47 6.75 38.95 4.00 39.52 4.53 38.57 4.92
3 BMI
(kg/m2) 27.46 4.66 28.54 6.57 28.16 4.09 26.40 3.48
4 Body fat
(percent) 33.23 9.25 33.09 11.77 34.77 8.96 32.28 5.94
5 Body muscle
(percent) 44.51 8.11 45.02 7.61 44.44 7.65 44.56 9.85
6 Bone mass
(percent) 2.54 0.39 2.59 0.35 2.64 0.38 2.54 0.49
7 Body water
(percent) 45.85 4.66 46.33 6.72 46.12 5.13 46.40 3.47
8 Visceral fat
(Rank) 12.17 4.21 12.23 4.06 11.27 3.3 11.13 4.15
The mean values of anthropometric measurements and body composition of selected subjects of
all the four groups before and after the intervention are presented in Tables.32 and 33, respectively.
The groupwise results also showed more or less similar to that of the overall observations with
not much variation between the groups also. At the base-line the maximum mean body weight (table.32.1)
was observed among the subjects of FEED group (73.55±10.64 Kg) and the minimum was in FED group
(69.08±13.37 Kg). The end-line body weight (table.33.1) also was observed to be the maximum in FEED
group (72.58±10.39 Kg) with reduction and the minimum was observed in FED group (70.97±13.83 Kg)
with a slight increase.
The results of base-line mean waist circumference (table.32.2) showed that the maximum was
found among the subjects of FEED group (39.83±4.58 inches) and the minimum was in FED group
(38.67±4.91 inches). The same trend was repeated with the end line results (table.33.2) with the
maximum mean waist circumference in FEED group (39.52±4.53 inches) and the minimum in FED group
(38.57±4.92 inches).
Before intervention period the maximum mean BMI (table.32.3) was found in FEED group
(28.92±4.96 kg/m2
) and the minimum mean BMI was found in FED group (26.28±3.50 kg/m2
). But after
the intervention (table.33.3) the maximum mean BMI was found among the subjects of NEED group
(28.54±6.57 kg/m2
) and the minimum was in FED group (26.40±3.48 kg/m2
).
The results of base-line body composition revealed that the mean body fat (table.32.4) was higher
in FEED group (34.84±10.16 %) and the least was found in FED group (31.93±6.35%). The end-line also
7 Body water
(percent) 45.53 4.89 46.47 7.37 46.22 6.02 46.85 3.75
8 Visceral fat
(Rank) 11.93 4.10 12.63 4.13 12.13 3.55 11.23 4.12

112. showed (table.33.4) the FEED group with the highest mean body fat (34.77±8.96 %) and the FED group
with the least mean body fat (32.28±5.94 %).
The results of the initial mean muscle mass (table.32.5) showed that the maximum was found in
NEED group (45.02±7.62%) and the minimum was found in control group (44.13±7.74 %). The end-line
mean muscle mass (table.33.5) was found to be the maximum in NEED group (45.02±7.61 %) and the
minimum in FEED group (44.44±7.65%).
The base-line mean bone mass (table.32.6) was found to be the highest among the subjects of
FEED group (2.60±0.38%) and the least was found in FED group (2.52±0.51%). The end-line mean bone
mass (table.33.6) was found the maximum in FEED group (2.64±0.38%) and the minimum was found in
control (2.54±0.39%) and FED groups (2.54±0.49%).
Before intervention period the mean total body water (table.32.7) was found to be the highest
among the subjects of FED group (46.85±3.75 %) and the least was found in FEED group
(46.22±6.02%). The same after the intervention period (table.33.7) was found with the maximum in FED
group (46.40±3.47 %) and the minimum in control group (45.85±1.66 %).
The initial readings of mean visceral fat (table.32.8) showed that the highest was found in NEED
group (12.63±4.13) and the least in FED group (11.23±4.12). The readings after the intervention period
(table.33.8) showed that NEED group was with the highest rank (12.23±4.06) and the FED group was
with the least ranking of visceral fat (11.13±4.15).
In spite of having the higher level of knowledge about the disease and higher educational
background, the FEED group was found with the highest mean values of body weight, waist
circumference,BMI and body fat among all the groups. This shows the gap between knowledge and
attitude of the subjects which resists the subjects to follow good practices in the management of diabetes.
But here the nutrition counseling played a key role in changing the negative attitude of the subjects in
achieving the better outcomes which was observed in the post intervention results discussed further.
Fig.10. Impact of interventions on anthropometry and body composition among the subjects of all the
groups

113. The effect of interventions on anthropometric measurements and body composition of selected
subjects of all the groups is depicted in figure.10.
Table. 34. Effect of interventions on anthropometric measurements and body composition (mean
difference) of subjects of all the groups
S.No
Body
composition
Control (n=30) NEED (n=30) FEED (n=30) FED (n
Mean
diff
percen
t
P
value Mean
Diff
perc
ent
P
value Mean
diff
percen
t
P value
Mean
diff percen
1 Weight (kg)
-0.22 -0.31 0.452 0.36 0.50 0.277 0.97 1.32
0.003*
-1.89 -2.74
2 Waist
circumference
(inches) -0.17 -0.42 0.768 0.15 0.38 0.279 0.32 0.79 0.076 0.10 0.26
3 BMI(kg/m2) -0.17 -0.64 0.171 0.15 0.52 0.268 0.76 2.63 0.066 -0.12 -0.44
4 Body fat
(percent) 0.29 0.86 0.232 0.13 0.39
0.648
0.07 0.20
0.924
-0.35 -1.11
5 Body muscle
(percent) -0.38 -0.87
0.036
* 0.00 0.00
1.000
0.54 1.21
0.392
0.06 0.14
6 Bone mass
(percent) 0.00 -0.13 0.787 -0.03
-
1.30
0.016
* -0.04 -1.67 0.295 -0.02 -0.66
7 Body water
(percent) -0.33 -0.72 0.344 0.13 0.29
0.627
0.10 0.21
0.848
0.45 0.96
8 Visceral fat
(Rank) -0.23 -1.96
0.017
* 0.40 3.17
0.259
0.87 7.14
0.023*
0.10 0.89
*Significant,
0
10
20
30
40
50
60
70
80
before after before after before after before after
Control NEED FEED FED
Weight (kg)
Waist cir (inches)
BMI (kg/m2)
Body fat (%)
Body muscle (%)
Bone mass (%)
Body water (%)
Visceral fat (Rank)

114. The difference in the mean values of anthropometric measurement and the body composition of
the selected subjects before and after the intervention period are shown in table.34. The figures in the
table are also representing the percentage difference and significance of difference within the groups.
The results showed that there was a reduction in mean body weight (table.34.1) in NEED (0.5%)
and FEED (1.32 %) groups after the intervention when compared to that of base reports which was
significant (p=0.003) in FEED group. Whereas an insignificant increase in body weight was observed
in control (0.31%) and FED (2.74%) groups after intervention. Usually the poorly controlled diabetics
tend to gain weight and in obese patients with type 2 diabetes reducing calorie intake improves
glycaemic control more rapidly than does weight loss (Ma et al., 2008). After the intervention period,
the mean waist circumference (table.34.2) was insignificantly decreased in all the three experimental
groups when compared to that of control group with a maximum decrease in FEED group (0.79%).
Though it was not statistically significant, the maximum increase was observed in mean BMI
(table.34.3) in FEED group (2.63 %,mean difference 0.76 kg/m2
) followed by NEED group (0.52%).
As the mean body weight showed an increase after intervention in control and FED groups, the BMI
also was observed to be increased.
The results showed that the mean body fat (table.34.4) was decreased in NEED group (0.39%)
and FEED group (0.20%) after the intervention, whereas in FED group there was an increase (1.11%).
Various studies demonstrated that reducing excess body fat directly reduced the risk of certain
conditions such as hypertension, heart diseases, type 2 diabetes, the gynic issues of women and certain
types of cancers.
The muscle mass was expected to be increased but there was no change in mean body muscle
mass (table.34.5) in NEED group after the intervention and in fact an insignificant decrease was
observed in FEED and FED groups. As the muscle mass increases, the rate at which energy (calories)
is burnt increases,which in turn increases the basal metabolic rate (BMR). This helps to reduce excess
body fat levels and lose weight in a healthy way. The intervention period of 90 days might be too short
to observe the impact of the intervention as regards to the muscle mass to improve.
There was a positive impact of intervention observed on mean bone mass (table.34.6) with the
maximum increase in FEED group (1.67 %) followed by NEED group (1.30 %) and FED group (0.66%).
The increase in mean bone mass was statistically significant in NEED group (p=0.016). The aging
increases the resorption of calcium from the bones so it is important to maintain healthy bones by
having food rich in calcium and by doing weight-bearing exercises. It is unlikely to undergo
noticeable changes in bone mass in the short term. But the consumption of low glycaemic index
multigrain mix with high amount of calcium (table.27.10), might have resulted in the increased
bone mass in FEED and FED groups where the major contributing factor might be the inclusion
of drumstick leaf powder and finger millet, the two calcium rich foods, in the mix. Nutrition
counseling had a positive impact on increased consumption of green leafy vegetables and dairy
products (table.23) which might have resulted in the increase of bone mass in NEED group.

115. From the results the impact of the intervention on the mean total body water (TBW) percentage
(table.34.7), was observed with the highest decrease of 0.96 percent in FED group followed by NEED
group (0.29%) and FEED group (0.21%) when compared to that of control group where an increase of
0.72 percent was observed. Total Body Water is the total amount of fluid in the body expressed as a
percentage of total weight. The average total body water percentage ranges for a healthy female from 45
to 60 percent and for male from 50 to 65 percent. The mean total body water percentage in the present
study before and after intervention was 46 percent which was very low. As the total body water
percentage increases the body fat percentage decreases.The percentage decrease of mean total body water
was comparatively less in NEED and FEED groups which showed that the effect of counseling on
increased intake of fluids emphasized during the counseling sessions was positive.
It is quite interesting to note that after the intervention period there was reduction in visceral fat
(table.34.8) in all the three experimental groups. The maximum decrease wasobserved in FEED group
(7.14 %) which was statistically significant (p=0.017) followed by NEED group (3.17 %) and FED group
(0.89 %) when compared to that of control group where it was increased by 1.96 percent which was
statistically significant (p=0.017). The distribution of fat changes with the age and gets shifted to the
abdominal area, even if the body weight and body fat remains constant. Visceral fat is located in the
abdominal area,surrounding the vital organs for protection. Visceralfat is considered healthy with a
ranking between 1 and 12. A healthy level of visceral fat reduces the risk of certain diseases like heart
disease, high blood pressure and may delay the onset of type 2 diabetes. In the present study, the results
showed that the mean visceral fat ranged between 11.23 and 12.63 among the three experimental groups
before intervention but it was reduced to 11.13 to 12.23 after the intervention which was a good
improvement. This positive change can be attributed to nutrition counseling as it was better observed in
NEED and FEED groups than that of FED group where it could bring positive attitude towards physical
exercise (table.17.1). Physical exercise enhances glucose uptake into the cells which increases blood flow
in the muscle and enhances glucose transport into the muscle cell. Physical exercise is inversely
associated with intra-abdominal fat distribution and can reduce body fat stores (Sami et al., 2017).
The loss of body weight is associated with improvements in CVD risk factors and glycaemic
control in type 2 diabetes. A modest weight reduction also may lead to reductions in fasting plasma
glucose and triglyceride and long term benefits in patients with type 2 diabetes. In the present study it was
observed that the improvement in anthropometric measurements had shown positive effect on
biochemical indices (table.39) among the subjects of all the intervention groups. The low-glycaemic
index multigrain mix with its high amount of protein and fibre increases satiety and facilitates the control
of food intake which might have resulted in weight loss as well as good glycaemic and lipidemic control
among the subjects in the present study. It was observed that the reduction in visceral fat might have
positively affected the lowering of LDL-C and triglycerides that reduces the CVD risk factors.
When the components of body composition were observed,the two groups which were exposed
to intervention of nutrition counseling, NEED and FEED groups, showed positive out- comes when
compared to that of control and FED groups. The results showed that the intervention of nutrition
counseling had a positive impact on increasing the knowledge of disease, positive attitude and positive

116. practices towards diabetes (tables.18,19 and 20). This reflected in reducing the consumption of animal
food and fat intake (vide table.24), reduced intake of nutrients like energy, carbohydrates and fat (vide
table.49) and increased physical activity (vide table.16) which might have resulted in the weight
reduction tendency in NEED and FEED groups. Weight management is one of the important aspects
of management of type 2 diabetes. As majority of the subjects in the study were obese and it takes
time to find a significant reduction in the body weight. Though the weight reduction was not
statistically significant, it was encouraging to observe the majority of the subjects looking worn-out
physically, which shows the trend in weight reduction in the short span of 90 days.
From the end-results when the outcomes are compared between NEED and FEED groups, the
two groups underwent the nutrition counseling programme, better improvements in the anthropometry
and body composition were observed among the subjects of FEED group. The level of perception of
knowledge from the counseling sessions may be more among the subjects of FEED group where
higher educational background (table.12.5) and higher level of good knowledge score (table.18) were
found. Higher income level (table.12.8) also was found in FEED group which increases the
affordability for including more fruits, variety of millets and pulses in the diet, consumption of which
reduces the body weight with high dietary fibre content. As the FEED group was exposed to
intervention of low glycaemic index multigrain mix also, the consumption of low GI mix might have
increased satiety with high fibre content and reduced the need for intake of energy rich foods. The
attitude towards adherence to physical exercise as a part of diabetes management was observed more
in FEED group than that of NEED group (table.17) which will have impact on the weight loss.
When the end-results are compared between the two FEED and FED groups, where the
intervention of low glycaemic index multigrain mix was administered, better outcomes in the
anthropometric measurements and body composition were observed among the subjects of FEED
group. At the base-line itself the literacy level and the level of knowledge about the disease were
found more among the subjects of FEED group when compared to that of FED group. Added to that
the FEED group was exposed to nutrition counseling sessions also which imparted more knowledge
and information about diabetes and its care which might have changed the attitude of subjects of
FEED group towards the consumption of high energy foods, that was lacking in FED group. Though
the low glycaemic index multigrain mix exerted similar impact on anthropometry in both the groups,
the increased physical activity by the subjects of FEED group implemented as a result of nutrition
counseling might have resulted in reduced body weight and other measurements of anthropometry.
The results of anthropometric measurements explained that among the three intervention groups,
after the intervention period the maximum positive impact was better exhibited in FEED group with
both the interventions, nutrition counseling and low glycaemic index multigrain mix, followed by the
NEED group with the intervention of nutrition counseling alone and the least impact of intervention
observed in FED group comparatively where intervention of the low glycaemic index multigrain mix
alone was administered.
Regarding body weight-loss in contrary to the present study, better changes were observed in a
study by Amano et al. (2007) where there was a reduction of 2.2 Kg in body weight, 0.9kg/m2
in BMI
and 1.8 percent in body fatpercentage after 3 months of GI based nutrition education among patients
with type 2 diabetes. But Argiana et al. (2015) showed that consumption of desserts with low GI/GL in

117. a balanced hypo-caloric diet has a positive impact on anthropometric parameters like body weight,
body mass index and waist circumference,of patients with T2DM.
The present study is supported by Krishnan et al. (2015) case study where there was a reduction
in mean body weight by 0.7 kg and in mean BMI by 0.25 kg/m2
after 180 days of diet counseling to
type 2 diabetics. But Pot et al. (2019) showed a higher reduction in body weight (4.9Kg), BMI (1.70
kg/m2
) and waist circumference (3.7 inches) in a 6 months pilot study on nutrition and life style
intervention. Afaghi et al. (2012) showed the body weight significantly reduced from 74.0 ± 5 kg to
70.7 ± 4.6 kg on intervention of a low GL diet for 10 weeks.
.
Table.35. Comparisonof anthropometricmeasurementsandbodycompositionof subjectsafterthe
interventionbetweenthe groups.
ANOVA
After Mean Sum of Squares DF Mean
Square
F Sig.
Between
Groups
3.502 3 1.167 .003 1.000
Within Groups 12954.785 28 462.671
Total 12958.287 31
The results of one way ANOVA test showing the comparison of difference in anthropometric
measurements and body composition after the intervention between the groups are presented in
table.34. The results showed that there was no statistically significant difference between the groups
after intervention in the mean values of anthropometric measurements and body composition.
Table.36. Correlation of various demographic variables with anthropometric measurements and body
composition of all the subjects
S.No Demographic variables
Anthropometric measurements and body composition
Weight
waist
circumf
erence
visceral
fat
BMI
Body
fat
body
muscle
bone
mass
body
water
1 Gender
Female
Male
2 Age > 40 years

118. 40 – 50 years
0.023*
*
50 – 60 years
0.022*
*
> 60 years
3 Income
< 10000
10000 – 25000
25000 - 50000
> 50000 0.035**
4 Education
Illiterate 0.057
Primary
High School
College
University
5 Occupation
Officer/supervisor
Business
Professional
Home Maker
0.033*
*
Daily wage
labourer 0.022**
Anyother,specify 0.066
** significant(p=<0.05),
The correlation of various demographic variables with the anthropometric measurements and
body composition of the selected subjects is shown in table.36. The results showed that there was no
significant correlation between gender and any of the anthropometric measurements after the intervention.
There was no significant correlation found between age and anthropometric measurements except for
bone mass. The correlation was significant (p=<0.05) between age group above 40 years (40-50 years
p=0.023 and 50-60 years p=0.022) and bone mass. When income of the subjects was considered, no

119. significant correlation was found between income and any of the anthropometric measurements except
between income above 50000/- and waist circumference (p=0.035). No significant correlation was found
between education and anthropometric measurements but a trend was observed (p=0.057) between
illiterates and bone mass. A significant correlation was found between home maker and bone mass
(p=0.033) and between daily wage labourer and total body water percentage (p=0.022) but for other
anthropometric measurement and body composition no significant correlation was found with occupation.
This shows that bone mass was sensitive to age but other anthropometric measurements were not
influenced by the demographic variables.
4.7. Effectof interventions on biochemicalparameters of the subjects:
Any changes in the biochemical indicators are useful in the assessment of health status of
individuals. In the present study blood tests were carried out to find out the readings of various
biochemical parameters of the selected subjects and the effect of each intervention on the biochemical
parameters was observed.
Tab Table.37. Effect of interventions on biochemical parameters of all subjects
(N=120)
S.No Parameter
Before After Diff
P value
Mean ±sd Mean ±sd Mean percent
1 FBG (mg/dl ) 141.46 44.25 113.49 24.25 27.97 19.77 0.000*
2 PPG(mg/dl) 221.38 74.24 177.96 50.08 43.43 19.62 0.000*
3 nnHbA1c (percent) 7.70 1.42 7.42 1.29 0.28 3.61 0.000*
4 Systolic (mmHg) 122.80 13.03 123.19 9.41 -0.39 -0.32 0.628(NS)
5 Diastolic (mmHg) 81.50 8.50 80.77 8.77 0.73 0.90 0.358 (NS)
6 Total cholesterol
(mg/dl)
183.56 31.12 177.90 26.67 5.66 3.08
0.034*
7 HDL C (mg/dl) 42.19 5.90 43.40 5.48 -1.20 -2.85 0.001*
8 LDL C (mg/dl) 103.04 26.31 98.13 24.30 4.92 4.77 0.031*
9 VLDL (mg/dl) 39.61 15.34 36.43 11.22 3.19 8.05 0.009*
10 Triglycerides
(mg/dl)
210.60 96.49 184.06 62.57 26.54 12.60
0.002*
*Significant,NS –Notsignificant
The mean values of biochemical parameters of the selected subjects (N=120) before and after the
intervention period of 90 days are presented in table.37. The biochemical parameters tested in the study
were fasting blood glucose level (FBG), postprandial glucose level (PPG),HbA1C (percent), Systolic
pressure (mmHg), diastolic pressure (mmHg), total cholesterol (mg/dl), HDL-cholesterol (mg/dl), LDL-
cholesterol (mg/dl), VLDL(mg/dl) and triglycerides.
The base-line results showed that the mean readings of fasting blood glucose (FBG) level and
postprandial glucose (PPG) were 141.4±44.25mg/dl and 221.3±74.24 mg/dl respectively which were
above the normal values. After intervention it was observed that the mean FBG and PPGwere
113.49±24.25mg/dl and 177.96±50.08 mg/dl respectively. There was statistically significant (p=<0.05)
decrease in the means of FBG (19.77percent, p=0.00) and PPG (19.62percent, p=0.00) respectively.

120. The initial mean HbA1c was 7.7±1.42 percent and post intervention it was 7.42±1.29 percent,the
overall mean difference in HbA1c was 0.28 percent points (3.61%) which was statistically significant
(p=0.00). The readings of mean systolic and mean diastolic pressures were before intervention
122.80±13.03 mmHg and 81.50±8.50 mmHg respectively and the same after intervention were
123.19±9.41 mmHg and 80.77±8.77 mmHg respectively which were within the normal range but there
was no statistically significant difference found after intervention.
The lipid profile of the subjects revealed that the mean values of total cholesterol were 183.56
mg/dl, LDL-Cholesterol -103.04 mg/dl and HDL-Cholesterol- 42.19 mg/dl. The mean values of VLDL
(39.61 mg/dl) and triglycerides (210.60 mg/dl) were higher than the normal values. There was
statistically significant (p=<0.05) improvement in mean total cholesterol by 3.08 percent (p=0.034),
HDL-C 2.85percent (p=0.001), LDL-C 4.77 percent (p=0.031), VLDL 8.05 percent (p=0.009) and
triglycerides by 12.60 percent (p=0.002) in mean difference after intervention.
Fig.11. Impact of interventions on biochemical parameters of all the subjects
Figure.11 depicts the impact of interventions on biochemical parameters of all the selected
subjects. Overall the results of biochemical parameters of all the subjects showed a statistically
significant (<0.05) positive impact of intervention on parameters like blood glucose levels, HbA1c
and lipid profile. The impact of each treatment on biochemical parameters of individual groups,
control, NEED,FEED and FED after the intervention was observed in the following tables Table.38
and table.39 respectively.
Table.38. Base-line biochemical parameters (mean values) of subjects of all the groups
0
50
100
150
200
250
before
after
Parameter Control (n=30) NEED (n=30) FEED (n=30) FED (n=30)

121. T
a
ble.39.End-line biochemical parameters(meanvalues) of subjectsof all the groups
The groupwise results of the biochemical indices showed that the initial mean readings of fasting
blood glucose level and postprandial glucose level were above the normal range among the subjects of
all the groups.
Before intervention period the maximum mean FBG (table38.1) was found in FED group
(166.5±45.21 mg/dl) and the minimum was observed in NEED group (127.73±36.67 mg/dl). The
mean PPG (table.38.2) was found the maximum with FED group (260.60±75.04 mg/dl) before
intervention period and the minimum was found with NEED group (196.70±62.61 mg/dl). After the
intervention period the highest mean FBG (table.39.1) was found in control group (122.43±33.58
mg/dl) and the least was observed in NEED group (108.87±13.50 mg/dl). The post intervention results
revealed that the highest mean PPG (table.39.2) was in control group (193.77±60.84 mg/dl) and least
mean PPGwas found in NEED group(163.33±39.69 mg/dl).
The base-line results of mean HbA1c (table.38.3) showed that the maximum was found in FEED
group (7.86± 1.51%) and the minimum was found in NEED group (7.35±1.25%). The end-line results
S.No Mean ±sd Mean ±sd Mean ±sd Mean ±sd
1 FBG (mg/dl ) 133.53 45.16 127.73 36.67 138.10 38.95 166.47 45.21
2 PPG(mg/dl) 212.97 77.49 196.70 62.61 215.27 65.08 260.60 75.04
3 HbA1c (percent) 7.83 1.53 7.35 1.25 7.86 1.51 7.74 1.32
4 Systolic (mmHg) 120.33 14.49 129.07 16.62 121.27 9.78 120.53 6.68
5 Diastolic (mmHg) 82.03 9.71 83.63 9.46 79.07 6.68 81.27 7.07
6 Total cholesterol
(mg/dl)
177.17 25.98 192.13 29.07 184.97 42.54 179.97 20.38
7 HDL C (mg/dl) 43.60 5.58 39.83 4.05 42.27 8.07 43.07 4.29
8 LDL C (mg/dl) 100.10 12.64 109.57 26.03 101.37 36.67 101.13 23.00
9 VLDL (mg/dl) 33.50 15.17 42.80 17.01 41.37 14.36 40.96 12.35
10 Triglycerides (mg/dl) 167.50 75.71 214.13 84.82 206.70 71.79 254.07 124.03
S.No Parameter Control (n=30) NEED (n=30) FEED (n=30) FED (n=30)
Mean ±sd Mean ±sd Mean ±sd Mean ±sd
1 FBG (mg/dl ) 122.43 33.58 108.87 13.50 111.77 24.72 110.90 17.90
2 PPG(mg/dl) 193.77 60.84 163.33 39.69 170.00 45.56 184.73 45.91
3 HbA1c (percent) 7.64 1.32 7.25 1.17 7.44 1.37 7.34 1.26
4 Systolic (mmHg) 121.17 7.69 127.10 12.61 122.50 9.49 122.00 4.98
5 Diastolic (mmHg) 80.10 7.78 82.47 5.84 81.43 6.91 79.07 12.60
6 Total cholesterol
(mg/dl)
178.77 20.02 177.00 26.29 172.10 36.85 183.73 18.08
7 HDL C (mg/dl) 43.77 4.53 41.48 4.73 43.37 7.39 44.97 4.05
8 LDL C (mg/dl) 95.60 13.18 101.33 24.84 95.53 33.79 100.03 20.07
9 VLDL (mg/dl) 39.40 13.46 34.40 8.98 33.17 7.31 38.73 12.64
10 Triglycerides (mg/dl) 202.77 86.52 172.63 44.62 166.53 36.02 194.30 63.20

122. of mean HbA1C (table.39.3) showed the maximum in control group (7.64±1.32%) and minimum in
NEED group (7.25±1.17).
The initial and final readings of mean systolic and mean diastolic pressures were found to be
normal among the subjects of all the groups. The mean systolic pressure (table.38.4) was ranging from
120.33±14.49 to 129.07±16.62 mmHg before intervention period and the mean diastolic pressure
(table.38.5) was ranging from 79.07±6.68 to 83.63±9.46 mmHg. After the intervention group the mean
systolic pressure (table.39.4) ranged between 121.17±7.69 and 127.10±12.61 mmHg and the mean
diastolic pressure (table.39.5) ranged between 79.07±12.60 and 82.47±5.84 mmHg.
The base-line results of mean total cholesterol (table.38.6) showed the highest in NEED group
(192.13±29.07 mg/dl) and the least was found in control group (177.17±25.98 mg/dl). The highest
base-line mean HDL-C (table.38.7) was found in control group (43.60±5.58 mg/dl) and the least was
found in NEED group (39.83±4.05 mg/dl). The maximum mean LDL-C (table.38.8) was observed in
control group (100.10±12.64 mg/dl) and the minimum mean LDL-C was found in NEED group
(109.57±26.03 mg/dl) at base-line. The mean VLDL (table.38.9) was the maximum in NEED group
(42.80±17.01 mg/dl) at base-line and the minimum in control group (33.50±15.17 mg/dl). The initial
readings of mean triglycerides (table.38.10) were found to be very high among the majority of the
subjects with the highest in FED group (254.07±124.03 mg/dl) and minimum in control group
(167.50±75.71 mg/dl).
The end-line results of mean total cholesterol (table.39.6) revealed that the maximum was found
in FED group (183.73±18.03 mg/dl) and minimum cholesterol was found in NEED group
(172.10±36.85 mg/dl). The highest mean HDL-C (table.39.7) after the intervention was observed in
FED group (44.97±4.05 mg/dl) and the least was observed in NEED group (41.48±4.73 mg/dl). The
end-line mean LDL-C (table.39.8) showed that the maximum was found in NEED group
(101.33±24.84 mg/dl) and the minimum mean LDL-C was found in FEED group (95.53±33.79
mg/dl). The post intervention mean VLDL (table.39.9) was found with the highest in control group
(39.40±13.46 mg/dl) and least mean VLDL in FEED group (33.17±7.31 mg/dl). After the intervention
period the mean triglycerides (table.39.10) were found with the maximum in control group
(202.77±86.52 mg/dl) and the minimum in FEED group (166.53±36.02 mg/dl).
Table. 40. Effect of interventions on biochemical parameters (mean difference) of subjects of all the
groups

123. S.No Parameter
Control (n=30) NEED (n=30) FEED (n=30) FED (n=3
Mean
diff
percent
P value Mean
diff percent
P value Mean
diff percent
P value Mean
diff perce
1 FBG (mg/dl ) 11.10 8.31 0.219 18.87 14.77 0.001* 26.33 19.07 0.003* 55.57 33.38
2 PPG(mg/dl) 19.20 9.02 0.207 33.37 16.96 0.006* 45.27 21.03 0.002* 75.87 29.11
3 HbA1c
(percent)
0.19 2.39
0.175
0.10 1.36
0.039*
0.43 5.43
0.001*
0.40 5.13
4 Systolic
(mmHg)
-0.83 -0.69
0.708
1.97 1.52
0.207
-1.23 -1.02
0.397
-1.47 -1.22
5 Diastolic
(mmHg)
1.93 2.36
0.282
1.17 1.39
0.331
-2.37 -2.99
0.017*
2.20 2.71
6 Total
cholesterol
(mg/dl)
-1.60 -0.90 0.729 15.13 7.88 0.010* 12.87 6.96 0.052* -3.77 -2.09
7 HD-C
(mg/dl)
-0.17 -0.38
0.844
-1.65 -4.14
0.011*
-1.10 -2.60
0.134
-1.90 -4.41
8 LDL-C
(mg/dl)
4.50 4.50
0.162
8.23 7.51
0.074
5.83 5.75
0.315
1.10 1.09
9 VLDL
(mg/dl)
-5.90 -17.61
0.032*
8.40 19.63
0.003*
8.20 19.82
0.000*
2.23 5.44
10 Triglycerides
(mg/dl)
-35.27 -21.05
0.039*
41.50 19.38
0.004*
40.17 19.43
0.000*
59.77 23.52
*significant,
The difference in mean values and the percentage difference between the pre- and post-
intervention period of all biochemical parameters among the subjects of all the groups are presented in
table.40. From the results it was observed that groupwise there was significant positive difference in all
the mean values of the biochemical parameters except the mean systolic and mean diastolic pressures
after the intervention. There was statistically significant (p=<0.05) decrease in means of FBG, PPGand
HbA1c in the experimental groups after intervention when compared to that of control group. FBG had
switched over to normal range after the intervention in NEED,FEED and FED groups, whereas in control
group though there was reduction, the values were still higher than the normal range. PPGvalues had
come down to pre-diabetic stage after intervention in all the groups.
The results showed a statistically significant reduction in the mean values of FBG with the
highest in FED group (33.38%; p=0.00) followed by FEED group (19.07%; p=0.003) and NEED group
(14.77%; p=0.001) and the least (8.31 %) and) in control group which was insignificant. In the case of
PPGalso a significant reduction was found in the mean values with the highest in FED group (29.11%;
p=0.00) followed by FEED group (21.03 %; p=0.002) and NEED group (16.96 %; p=0.006) when
compared to the control group (9.02%) where the difference was insignificant.
From the results it was observed that a significant reduction was found in HbA1C after the
intervention period, where the highest percentage reduction was observed in FEED group (5.43%,
p=0.001) followed by FED group (5.13%, p=0.002), NEED group (1.36%, p=0.039) and in control group
(2.39%) it was statistically not significant.
In regards to the blood glucose levels, it showed that the groups treated with food intervention of
low GI multigrain mix (FED) and food intervention along with nutrition counseling (FEED) had shown

124. better results when compared to the group treated with nutrition counseling alone (NEED). Despite
having the highest percentage of illiterates (table.12.5) and the highest poor knowledge score about the
disease (table.18), it is interesting to note that the FED group with food intervention had shown better
outcomes. This clearly explains the positive impact of the low glycaemic index multigrain mix
consumed by the subjects for 90 days of intervention period. A reduction of 0.4 percent points of
HbA1c in FEED group (from 7.86%to 7.44%) and FED group (from 7.74% to 7.34%), the groups which
were exposed to the intervention of low glycaemic index multigrain mix, was a significant positive
change. Whole wheat, barley, finger millet, defatted soy flakes, drumstick leaf powder
(Moringa Oleifera) and Kalonji (Nigella Sativa) present in the multigrain mix consumed by
the subjects in the present study, might have exerted an impact on lowering the blood
glucose levels due to the hypoglycemic effect. The effect of individual ingredients in the
multigrain mix on lowering the blood glucose levels to desirable levels is discussed further.
The cereals like wheat and barley are rich in dietary fibre, many nutrients and phytochemicals
which are associated with type 2 diabetes mellitus. The whole wheat, which includes bran and wheat
germ, provides protection against diabetes by improving insulin sensitivity and decreasing the
disordered insulin function. Being a rich source of magnesium which is a cofactor of enzymes
involved in glucose metabolism and insulin secretion, the whole wheat rava (35%) in the
multigrain mix might have shown impact on improving the fasting blood glucose, postprandial
glucose response and HbA1c among the subjects who have received the intervention of low GI
multigrain mix in the present study. Barley is an excellent source of dietary fibre particularly β-
glucan which promotes healthy blood sugar by slowing down the glucose absorption. So the
barley rava (30%) in the multigrain mix might have exerted a positive impact on lowering the
FBG, PPG and HbA1c among the subjects of FEED and FED groups in the study. Ragi (10%) is
another ingredient included in the multigrain mix which is considered as an ideal food for
diabetics because of its low sugar content and slow release of glucose into the blood. The results
of blood glucose levels in the present study confirmed that the consumption of finger millet
lowers the plasma glucose levels, mean peak rise, and area under the curve (table.29) which may
be due to the higher fiber content of finger millet and the presence of anti-nutritional factors
known to reduce starch digestibility and absorption.
The soya included in the multigrain mix is a legume with high protein content and long
shelf life. The addition of soya chunks (20%) with the cereals, the whole wheat, barley and ragi,
in the multigrain mix intervened in the present study improved the biological value of the protein
by complementing each other the missing amino acids lysine in cereals and methionine in soya.
And also because of less starch content in soya, the soya protein is a good source of protein
for patients with type 2 diabetes. Since the soya chunk is a processed food, the trypsin inhibiting
factor might be reduced making the protein bioavailable too. The presence of high protein content in
the multigrain mix made the product a low glycaemic index food which proved to be helpful to control
blood glucose and serum lipid in diabetic patients. The isoflavones present in the soya chunks might be
the responsible factors for improving the glycaemic control observed in the study after the intervention
among the subjects of FEED and FED groups.
The inclusion of Kalonji (Nigella sativa) seeds in the multigrain mix might have
improved the therapeutic value of the product in the present study because the kalonji seeds are
known to possess antidiabetic activity. From the available scientific evidence the antidiabetic
activity of kalonji seeds is mediated by stimulated glucose induced insulin release from β cells,
reduced gluconeogenesis in liver and reduced glucose absorption from intestine. Various studies

125. found that the major active chemical component responsible for the therapeutic activities of the
seeds is due to the presence of thymoquinone (TQ). The hypoglycaemic effect of the kalonji
seeds are proved by the results of the present study with reduced mean values of FBG, PPG and
HbA1c after the intervention among the subjects of FEED and FED groups who consumed the
low GI multigrain mix which contains kalonji seeds (3.5%) during the intervention period.
Kalonji also added aroma to the cooked product which increased the level of acceptance of the
multigrain mix by the subjects of the present study.
The drum stick leaf (Moringa oleifera) powder (1.5%) is another ingredient included in
the low glycaemic index multigrain mix which is also proved to hold some therapeutic potential
for chronic hyperglycemia. The available experimental evidence had shown that the presence of
flavanoids gives drumstick leaves the antidiabetic and antioxidant properties. So the drum stick
powder present in the multigrain mix may also be a responsible factor for the reduction of blood
glucose levels after the intervention among the subjects of FEED and FED groups in the present
study.
Thus from the results of biochemical parameters it is observed that the low glycaemic
index multigrain mix formulated from the indigenous foods in the present study has shown to
exert positive impact on the biochemical indices among the subjects of FEED and FED groups.
Overall the complex carbohydrates and the fibre content in the multigrain mix may be the
responsible factors for lowering the blood glucose levels after the intervention. Vegetable
proteins are preferable to animal protein due to their high fiber content and absence of saturated
fat and addition of protein to a carbohydrate containing meal can reduce the glycaemic response.
The ratio of cereal to pulse in 4:1 was included in the multigrain mix in the present study which
improves the protein quality and also gives satiety. Low GI foods may increase satiety and delay
the return of hunger compared with high GI foods, which could translate into reduced energy
intake at a later time points. This might be the reason for the sustainability for longer period after
the consumption of the low GI multigrain mix reported by the subjects of the intervention groups
in the present study. From the results of biochemical reports on blood glucose levels it was
shown that compliance to low GI diets for longer time may induce favourable effects like rapid
decrease of fasting glucose and insulin levels and improvement of blood pressure.
The intake of calcium above 600 mg/day is desirable but intakes above 1200 mg may be optimal
(Pittas et.al., 2007) in optimizing glucose metabolism. The low GI multigrain mix developed in the
present study is providing with good amount of calcium, 1244.90 mg per 60 g of low GI multigrain
mix (table.27) because of the presence of the two calcium rich food ingredients, drum stick leaf
powder and finger millet. As the insulin secretion is dependent on calcium, the supplementation of
calcium may be beneficial in optimizing glucose metabolism. This might also be a reason for the
reduction in blood glucose levels and HbA1c among the subjects of food intervention groups in the
present study.
It is expected to observe better results in FEED group which had double effect of both the
interventions, the nutrition education as well as the low GI multigrain mix, with lower initial readings
than that of FED group which was exposed to single intervention of low GI multigrain mix, but the end
results were found similar in both the groups. It may indicate that the effect of low GI multigrain mix was
better observed than that of nutrition counseling in FEED group.
In NEED group, another group exposed to nutrition counseling, also a significant
difference in mean values of FBP, PPG and HbA1c was observed after the intervention which is

126. encouraging to observe for a short period of 90 days of nutrition counseling programme. This
may be mainly because of the positive change in the attitude of the subjects after getting exposed
to the nutrition counseling that turned into good practices which is highly appreciable. The
various factors that might have brought positive change in the attitude among the subjects of
NEED and FEED groups through the nutrition counseling are analyzed and discussed here in
comparison with that of control group.
In the present study the nutrition counseling to the subjects was aimed at imparting
knowledge about diabetes and its care which motivates them to change the negative attitude
towards the disease management for taking necessary self-care. In the present study from the
post-intervention results, the reduced glucose control indices have shown a positive change in the
behaviour among the subjects of NEED and FEED groups towards dietary adherence and
physical activity.
It was observed that the knowledge perceived during the counseling sessions have motivated the
intervention group to engage in appropriate dietary practices related to reduced intake of high glycaemic
index foods like high amount of rice (table.21), empty calories, sweets and energy intake (table.49.1). The
intake of carbohydrate, which has a direct effect on postprandial glucose levels in people with diabetes,
was reduced (table.49.4) after the intervention of nutrition counseling. This could be effective in reducing
the blood glucose levels after the intervention in NEED and FEED groups when compared to that of
control group.
From the results it was observed that the attitude towards adherence to consumption of low
glycaemic index foods was changed positively among the intervention groups after the intervention of
nutrition counseling. The intake of dietary fibre that slows down the glucose absorption was enhanced by
means of increased intake of fruits and vegetables in particular green leafy vegetables (table.23) and
inclusion of whole grains, millets (table.21) and whole grams (table.22) in the form of sprouts in the food
basket by NEED and FEED groups.
A positive change was observed in the attitude of the subjects in the intervention group towards
good dietary practices for the management of diabetes after the intervention which might have resulted in
good glycaemic control shown in the results of biochemical parameters. They include, having timely
meals, following six meal pattern with three main meals and snacking in between and reduced frequency
of eating outside food.
An interesting feature regarding the barriers for not adhering to the planned diet observed before
exposure to the nutrition counseling was that the subjects had shown to overcome the barriers after the
intervention of nutrition counseling sessions in NEED and FEED groups. The barriers where the change
was observed include lack of time, lack of knowledge, lack of patience, cannot resist, lack of family
members’ support and irregular work schedule. This indicates that nutrition counseling had brought
change in the attitude towards dietary management which may be the reason for improved glycaemic
control reflected in the end-line results of biochemical parameters in the intervention groups in the present
study.

127. It is well established that involving in regular physical activity improves blood glucose control in
patients with type 2 diabetes mellitus along with positively affecting the lipid profile, blood pressure and
overall quality of life. In the present study along with the changed dietary practices,effect of nutrition
counseling was positive in changing the attitude of the subjects towards increasing the physical activity
(table.16) level, duration of physical activity and type of physical exercise involved, with a maximum in
NEED group followed by FEED group. It was observed that practice of walking was increased among the
subjects avoiding the usage of motor vehicles for shorter distances that helps control blood glucose levels
and improves the ability of body to use insulin. These positive practices in regard to physical activity
might have reflected in the biochemical indices in the present study. The post-intervention results of
blood glucose levels and HbA1c reveal that the increased physical activity among the subjects might be
one of the reasons for the improved blood glucose control after the intervention of nutrition counseling.
From the post-intervention results of blood glucose levels it was observed that the mean
differences in FBG, PPGand HbA1c were higher in FEED group than that in the NEED group. This
parity between the groups though not significant, may be because of the difference in the duration of the
disease, literacy level and economic status among the subjects which affect the perception rate and
adherence to the instructions.
As the duration of the disease is concerned, in the present study the long duration of more than 5-
10 years was found more in FEED group (table.13.1) than in NEED group and the newly diagnosed cases
were found more in NEED group than in FEED group. The longer the duration of diabetes, the higher is
the knowledge and perception about the disease. So this could be a reason for the FEED group to perceive
more knowledge during the nutrition counseling sessions and put them into good practices which had
reflected in the better results of blood glucose levels after the intervention.
The literacy level was found higher in FEED group than in NEED group (table.12.5) in the
present study. Patients with higher educational background are more likely to equip themselves with
knowledge about the disease which helps them to manage diabetes in a better way and that may be the
reason for the subjects of FEED group to show better outcomes after the intervention when compared to
that of NEED group.
The income level influences the socioeconomic status and the affordability of the family that
affects the attitudinal change among the patients of diabetes in translating the perceived knowledge into
good practices. The upper-middle income and high income groups were found more in FEED groups than
in NEED group in the present study. So the subjects of FEED group can afford to have healthier foods
and adhere to the nutrition counseling better than that of NEED group which had resulted in better
outcomes in FEED group regarding the blood glucose levels after the intervention.
Along with the nutrition counseling repeated reinforcement and motivation will bring
out a positive change in attitude and practices towards the disease among the patients of
diabetes.
The present study is supported by Itagi (2003) where the intervention of a millet based composite
food also exhibited a significant reduction in blood glucose levels, total cholesterol and HDL among the
diabetics. Similar findings were also observed by Kang et al. (2008) after supplementation of a
premix with wheat, defatted soy flour and barley for 90 days. The hypoglycaemic effect of

128. finger millet was studied by Lakshmi kumari and Sumathi (2002) where it was concluded that
the antinutritional factors in finger millet are responsible for reducing the starch digestibility
and absorption. Ahmed and Urooj (2015) inferred in an in vitro study that consumption of wheat based
composite flours with barley and oats might be helpful for stable blood glucose pattern due to the
redistribution of nutritionally important starch functions and inhibition of carbohydrate digestion in the
gastrointestinal tract. A dose of 2 g/day of Nigella sativa had an effect on the glycaemic control among
the type 2 diabetics and caused a significant reduction in FBG, PPGand HbA1C and improvement with
reference to total cholesterol and LDL-C.(Najmi et al., 2008, Bamosa et al., 2010 and Ahmad et al.,2013).
Brand Muller et al. (2003) found similar results with HbA1C, in a meta analysis on low GI diets
where HbA1c was reduced by 0.43 percent points over and above that of high GI diets. In various studies
the intervention of low glycaemic index diet resulted in reduction of HbA1c by 0.5 percent (Jenkins et al.,
2008, Jenkins et al., 2017 and Ojo et al., 2018). The United States Food & Drug Administration has
proposed a reduction of 0.3 to 0.4 percent in HbA1c value as therapeutically meaningful (Jenkins et al.,
2012). This is supported by a study by Ghiridhari et al. (2011) where it showed a reduction in PPGby 29
percent and HbA1c by 0.4% after 3 months of intervention of 2 tablets of Moringa leaf powder per day. It
is supported by a review by Mbikay (2012) which concluded that Moringa leaf powder shows some
therapeutic effect on chronic hyperglycaemia.
The present study as regards the effect of nutrition counseling is supported by studies of
Kusumaneela et al. (2015) and Pot et al. (2019) where diet counseling and life style interventions are
administered showed a significant reduction in blood glucose levels among the type 2 diabetics. The
expectation of obtaining better results on extension of the counseling programme in the present study is
proved in a meta analysis on group based training for self management strategies for T2DM by Deakin et
al. (2005) that a 6 months training brought down HbA1C by 1.4 percent.
From the results it was found that there were about 40 to 57 percent of hypertensive patients
(vide tabe.44.4) among the subjects of all the groups and the mean values of systolic and diastolic blood
pressures were observed to be normal at both base-line and end-line. Being on medication for
hypertension might be the reason for the normal values found in the study. In NEED group there was an
insignificant reduction in both systolic and diastolic pressures after the intervention which could be due to
the effective counseling on diet care for hypertension. In FED group diastolic pressure was reduced by
2.20 mmHg which might be due to the blood pressure lowering effect of soya present in the low
glycaemic index multigrain mix. Some of the isoflavones of soya have been shown to reduce risk for
hypertension through the effect of vasodilation and inhibition of key enzyme involved in the regulation of
blood pressure (Ramdath et al., 2017). But in FEED group where higher literacy level was found among
the subjects, the effect of both the interventions was not positive regarding the hypertension. This shows
that illiterates adhere to the advices of the physician better than the literates.
The results of lipid profile had shown a significant (p=<0.05) positive difference in majority of
the mean values of total cholesterol, LDL-Cholesterol, HDL- Cholesterol, VLDL and triglycerides after
the intervention among the subjects of experimental groups when compared to that of control group. The
mean values of total cholesterol were at desirable levels (<200mg/dl) in all the groups before and after the
intervention, but in NEED and FEED groups a statistically significant (p=0.010 and p=0.05 respectively)

129. reduction was observed when compared to that of control and FED groups where there was an
insignificant increase was found.
The mean HDL-C levels were increased in all the experimental groups but statistically
significant in NEED (p=0.011) and FED (p=0.009) groups when compared to that of control group. The
highest increase of HDL-C was observed in FED group (4.41%) followed by NEED group (4.14%). The
defatted soy chunks in the multigrain mix might have exerted the hypolipidaemic effect on the serum
lipids. A significant increase from the present border level (35-45 mg/dl) to the desirable HDL-C level of
>50 mg/dl among the subjects of diabetics can be expected in the present study with the extended period
of intervention of low glycaemic index foods and nutrition counseling.The mean LDL-Cholesterol values
were at desirable level (<130mg/dl) among all the groups even before and after the intervention. There
was a statistically insignificant reduction in mean values of LDL-C in all the groups.
The results showed a significant reduction in VLDL and triglycerides among the three
experimental groups where as a significant increase was observed in control group. Before intervention
the mean values of triglycerides were observed to be at high risk range (>200 to 499mg/dl) among all the
groups but post-intervention the mean values of triglycerides had come down from high risk to border line
(150-199 mg/dl). The maximum reduction was observed in FED group (23.52 %,p=0.006)) followed by
FEED (19.43%, p=0.000) and NEED group (19.38%, p=0.004) which were statistically significant, when
compared to that of control group where there was 21.05 percent (p=0.039) increase in the mean values of
triglycerides. Majority of the subjects (table.14.1) were non-vegetarians and reported to be heavy eaters of
animal food. The fat consumption (table.48.7) also was high among the subjects which might be the
reasons for the high readings of triglycerides among the subjects in the present study.
From the results it was observed that the intervention of the low GI multigrain mix has
shown to be effective in improving the lipid profile among the subjects of FEED and FED
groups in the present study. The soya chunks, barley, kalonji seeds and drumstick leaf powder
present in the low glycaemic index multigrain mix administered to the subjects of the
intervention groups in the present study might be the responsible factors in lowering the total
cholesterol, LDL-C and triglycerides. The chemical constituents of barley, saponin, tannin and
lignin may have effect on decreasing the plasma triglyceride level and insulin sensitizing activity
in type 2 diabetes. It may be β-glucan the soluble fibre in barley that is responsible for improving
glycaemic control and lowering plasma lipid concentrations in patients with Type 2 Diabetes
mellitus. The soy-protein intake may be associated with a significant reduction in serum
cholesterol, low-density lipoprotein cholesterol and triglycerides and a significant increase in
high-density lipoprotein cholesterol. Various studies also demonstrated that consumption of soy
protein can modulate some serum lipids in a direction to lower the CVD risk in adults with type
2 diabetes and decrease the atherogenic apolipoproteins and increase biosynthesis of HDL-C,
include LDL-C receptors, increase biosynthesis and excretion of bile acids, decrease
gastrointestinal absorption of steroids, induce favourable changes in hormonal status including
the insulin and glucagon ratio and thyroid hormones which lead to improvement of
dyslipidaemia.
From the results of the present study the improvement in the lipid profile of the subjects might be
because of the food ingredient ‘Nigella Sativa’ present in the low GI multigrain mix, that exerts a
therapeutic protective effect in diabetes by decreasing oxidative stress and preserving pancreatic beta-cell

130. integrity. It shows that the attainment of better glycemic control may also improve the lipid profile in
patients with type 2 diabetes. The most important action of Nigella Sativa which may be responsible for
its beneficial effect is its insulin sensitizing action. Various studies found that the various components of
Nigella sativa that show impact on the lipid profile may be thymoquinone, thymol, various unsaturated
fatty acids, lipase and tannins. The drumstick leaf powder (Moringa Oleifera) was proved to be effective
in the treatment and management of diabetes with minimal side effects and has got anti-hyperlipidaemic
effect also.
The results of biochemical readings in the present study showed that low GI multigrain
mix formulated in the study with various food ingredients with beneficial effect in the
management of type 2 diabetes with high fibre content, high protein and other therapeutic
components, might be responsible for the reduction of hyperglycaemia. This in turn reduces
CVD risk through effects on oxidative stress, serum lipids, blood pressure, coagulation factors,
inflammatory mediators, endothelial function and thrombolytic function.
When the post-intervention results of lipid profile of both the groups, FEED and FED exposed to
intervention of low GI multigrain mix, are compared, the FEED group had shown better improvement
than the FED group. As the subjects of FEED group were given even the intervention of nutrition
counseling, the double effect of the interventions can be observed in FEED group as regards the lipid
profile of the subjects. The difference between the groups, though not statistically significant, can be
attributed to the effect of nutrition counseling which might have changed the attitude of the subjects in
FEED group to put the perceived knowledge during the counseling sessions into good practice towards
the management of serum lipids.
From the results of lipid profile it was observed that the NEED group, which was given only
intervention of nutrition counseling, also exhibited more or less similar improvement to that of FEED
group in the lipid profile after the intervention period. The various factors of nutrition counseling that
might have affected the reduction of serum lipids and increase in HDL-C in among the subjects of NEED
and FEED groups are discussed further.
It was observed that the initial intake of nutrients like energy, carbohydrates and fat (table.48)
was more than the requirement by the subjects of NEED and FEED groups. As the excess amount of
energy is converted to fat and deposited in adipose tissue, majority of the subjects were found obese
(table.31) in the study which may contribute to high cholesterol and low level of HDL-C. After the
intervention of nutrition counseling though not statistically significant, the energy intake was observed to
be reduced among the subjects of FEED and NEED groups (table.49.1). This could be the effect of
nutrition counseling which might have brought change in the attitude of the subjects towards reducing the
excess consumption of rice, (table.21), sweets and sugars that caused decreased energy intake at end-line.
Eating saturated fat and trans fats can raise the total serum cholesterol level which may cause
CVD and stroke. As majority of the subjects in the study were non-vegetarians (table.14.1) the
consumption of saturated fat through animal food will be high which might have caused obesity (table.31)
among them that leads to insulin resistance and hyperlipidaemia in diabetics. Obese diabetics are more
prone to cardiovascular diseases and hypertension with unfavourable plasma lipid profile. The post
intervention results of food frequency showed a reduction in the frequency of consumption of animal food

131. and baked food items (table.24) which might have resulted in reduction of total serum cholesterol, LDL-
C, VLDL and triglycerides.
The positive impact of nutrition counseling was observed in changing the attitude towards other
dietary practices among the subjects of NEED and FEED groups. They include, eating small and frequent
meals instead of having heavy meals at a time which increases the insulin demand; limiting the frequency
of eating outside fast foods and junk foods rich in saturated fat and reduced frequency of consumption of
groundnuts after the intervention. An increase in physical activity by the subjects of NEED and FEED
groups might have reflected in weight loss and waist circumference,body fat percentage and visceral fat
(table.33) that may be the reason for the reduction in the LDL-C and triglycerides after the intervention.
Despite the difference in educational background and economic status among the subjects of two
groups NEED and FEED, no significant difference was found between the groups in the improvement of
lipid profile after the intervention. It may indicate that, there may not be any association between the
perception of knowledge and the attitude to change. Irrespective of knowledge levels, attitude to adhere to
the life style changes is important that shows the positive outcomes.
The positive effect of soya on lipid profile observed in the present study is supported by various
studies (Reynolds et al., 2006, Chang et al., 2008, Elizabeth et al., 2009 and Sidhu and Tasleem, 2018)
where the soy protein supplementation resulted in a reduction of total cholesterol, LDL, triglycerides and
an increase in HDL. Similar to the present study, Sabzghabaee et al. (2012) and Shafi and Harish (2017)
in two different studies found that Nigella sativa is an effective hypoglycaemic and hypolipidaemic food
ingredient. Similar to the findings of the present study Ravi Teja (2013) found that supplementation of the
powder of Moringa oleifera leaf has definite hypoglycemic and hypocholesterolemic activity in type 2
diabetes mellitus in obese people. The effect of low GI foods on serum lipids in the present study is
supported by Jenkins et al. (2008) where an increase in HDL is found by 1.7 mg/dl after the intervention
of a low GI diet. The effect of drum stick leaf powder on lipid profile observed in the present study is
confirmed by a review by Mbikay (2012) where it is concluded that Moringa oleifera leaf powder has
some therapeutic quality for chronic hyperlipidemia.
Ma et al. (2008) also showed similar results regarding the lipid profile after the educational
sessions on low GI diet among the type 2 diabetics with a reduction of 15.06 mg/dl in mean cholesterol,
6.06 mg/dl in LDL and an increase of 0.83 mg/dl in mean HDL. The impact of nutrition counseling
observed in 90 days span on the reduction of VLDL and triglycerides in NEED and FEED groups in the
present study is better when compared to a study by Krishnan et al. (2015) where there was reduction but
the mean differences of VLDL and triglycerides were less than that of the present study even after 180
days of intervention of diet counseling.
T able.41. Comparison of biochemical parameters between the groups after the intervention
ANOVA
After Mean Sum of Squares dF Mean Square F Sig.
Between
Groups
3.502 3 1.167 .003 1.000
Within Groups 12954.785 28 462.671

132. Total 12958.287 31
The results of one way ANOVA test for the comparison of difference in biochemical parameters
of all the subjects, after the intervention between the groups are presented in table.41. There was
no significant difference found in the biochemical parameters between the groups NEED, FEED,
FED and control after the intervention period.
Table.42. Correlation of various demographic variables with biochemical parameters of all the subjects
S.No Demographic variables FBG
PPG
total
cholesterol
Triglycerides
HbA1c HDL-C LDL-C VLDL
1 Gender
Female
Male
2 Age
> 40 years
40 – 50 years 0.013*
50 – 60 years
> 60 years 0.040*
3 Income
< 10000
10000 - 25000
25000 - 50000
> 50000
4 Education
Illiterate 0.013*
Primary
High School
College
University
5 Occupation
Officer/supervisor
Business 0.046**
Professional
Home Maker

133. Daily wage
labourer 0.001* 0.000*
Others
0.002*
0.005* 0.000* 0.027* 0.005*
* significant (p=<0.05)
The association between various demographic variables and the biochemical parameters of the selected
subjects is presented in table.42. The results showed that there was no significant correlation found
between gender and the biochemical parameters of the subjects. A significant correlation was found
between the age group 40-50 years and HDL-C (p=0.013) and between the age group above 60 years and
HbA1c (p=0.040). But for other biochemical indices there was no significant correlation with age and
income of the diabetic. Except between illiterates and HbA1c (p=0.013) there was no significant
correlation found between the other educational levels and the biochemical parameters. Occupation has
shown significant correlation with few parameters like business people with HDL-C (p=0.046), daily
wage labourer with HbA1c (p=0.001) and total cholesterol (p=0.000), other occupation like collection
agents, with PPG(0.002), total cholesterol (p=0.005), HDL-C (p=0.000), VLDL (p=0.027) and
triglycerides (0.005). This shows that the biochemical parameters were not influenced by the gender but
sensitive to age and occupation of the subjects.
4.8. Effectof interventions on clinical symptoms of diabetes among the
subjects:
Clinical assessment reveals the medical history and physical signs of the disease. Early detection
of clinical symptoms of type 2 diabetes and steps taken to eliminate them will improve the health
condition of the patients with type 2 diabetes. When compared to the general population, patients
with type 2 diabetes mellitus have a twofold increase in the risk for heart disease and stroke and also
increase in the risk for renal failure. So it is necessary to monitor and check the clinical symptoms
regularly to avoid the long term complications and the progression of disease. In the present study the
effect of each intervention on various clinical symptoms of type 2 diabetes mellitus among the subjects of
all the groups was observed.
Table.43.Effectof interventionson clinical symptoms of diabetes among the subjects of all the
groups
*Significant B-Before,A-After
S no Symptoms Control (n=30) NEED (n=30) FEED (n=30) FED (n=30) Total (N=120)

134. The percentage distribution of clinical symptoms among the selected subjects before and after the
intervention period is presented in table.4. Along with the classic symptoms of polyuria, polydipsia
and plyphagia, the other symptoms observed were tiredness or easy fatigue, lack of concentration or
interest, tingling sensation or numbness of limbs, slow wound healing, any skin problems after the
diagnosis of diabetes and sexual problems.
The overall (N=120) baseline results showed that among the clinical symptoms, the majority
(62.5%) of subjects reported tiredness followed by polyurea (40%), poludipsia (39.2%), polyphagia
(37.5%), tingling sensation or numbness of limbs (39.2%), wound healing (9.2%),skin problems
(15%) and sexual problems (20%) which were indicative of poorly controlled diabetes mellitus
among the subjects. It was 4.2 percent of subjects who did not report any symptoms of diabetes which
shows that the condition of hyperglycaemia may be asymptomatic too.
From the overall results after the intervention a reduction was observed in all the symptoms
except the skin and sexual problems which were in fact observed to be increased insignificantly. A
statistically significant (p=<0.05) reduction was observed with a maximum reduction in the symptoms
like tiredness (35%, p=0.000), followed by symptom of lack of interest (19.2%, p=0.000) and
symptom of numbness or tingling sensation in the hands (10.8%, p=0.028). Though it was statistically
not significant, the percentage of subjects who reported nil symptoms also was increased by 1.7
percent after the intervention which was a good sign of improvement of health.
Fig.12. Impact of interventions on clinical symptoms of diabetes among all the groups
B
(per
cent
)
A
(per
cent
)
Diff
(perce
nt)
B
(per
cent
)
A(pe
rcen
t)
Diff
(perc
ent)
B
(per
cent
)
A
(per
cent
)
Diff
(per
cent
)
B
(per
cent
)
A
(per
cent
)
Diff
(perc
ent)
B
(per
cent
)
A
(per
cent
)
Diff
(per
cent
)
1 Polyuria 50.0 46.7 3.3 30.0 33.3 -3.3 40.0 33.3 6.7 40.0 36.7 3.3 40.0 37.5 2.5
2 Polydipsia 36.7 33.3 3.3 53.3 46.7 6.7 26.7 26.7 0.0 40.0 40.0 0.0 39.2 36.7 2.5
3 Polyphagia 20.0 43.3 -23.3 30.0 33.3 -3.3 40.0 23.3 16.7 60.0 46.7 13.3 37.5 36.7 0.8
4 Tiredness 53.3 60.0 -6.7 63.3 23.3 40.0 70.0 16.7 53.3 63.3 10.0 53.3 62.5 27.5 35.0
5 Lack interest 16.7 16.7 0.0 43.3 16.7 26.7 30.0 3.3 26.7 23.3 0.0 23.3 28.3 9.2 19.2
6 Tingling
sensation 36.7 36.7 0.0 46.7 43.3 3.3 26.7 10.0 16.7 46.7 23.3 23.3 39.2 28.3 10.8
7 Wound
healing 20.0 6.7 13.3 3.3 3.3 0.0 10.0 6.7 3.3 3.3 3.3 0.0 9.2 5.0 4.2
8 Skin
problems 10.0 13.3 -3.3 16.7 16.7 0.0 23.3 23.3 0.0 10.0 10.0 0.0 15.0 15.8 -0.8
9 Sexual
problems 3.3 10.0 -6.7 23.3 23.3 0.0 20.0 16.7 3.3 33.3 33.3 0.0 20.0 20.8 -0.8
10 None 10.0 6.7 3.3 0.0 0.0 0.0 6.7 13.3 -6.7 0.0 3.3 -3.3 4.2 5.8 -1.7

135. Figure.12 represents the difference in percentage of clinical symptoms of diabetes among the
selected subjects of all the four groups after the intervention. From the individual groupwise results, it
was observed that in FEED and FED groups, there was reduction in the percentage of all the
symptoms where as in NEED group an increase was observed in symptoms like polyuria and
polyphagia and in control group polyphagia and tiredness were observed to be increased.
From the results it was found that ‘tiredness’ was the symptom majority of the subjects reported
in all the groups before intervention with the maximum in FEED group (70%) followed by NEED
and FED groups (63.3%) and the minimum in control group (53.3%). Polyuria was reported the
maximum in control group (50.0%) and the minimum in NEED group (40%). Polydipsia was
observed the maximum in NEED group (53.3%) and the minimum was in FEED group (26.7%).
Polypghagia was the maximum in FED group (60%) and the minimum in control group (20.0%).
Numbness which is also a common symptom among the type 2 diabetics was observed the maximum
in NEED and FED groups (46.7%) and the minimum in FEED group (26.7%). The highest
percentage of skin problems was observed in FEED group (23.3%).
It is surprising to observe a drastic drop in the percentage of subjects suffering from tiredness
after the intervention in FEED and FED groups by 53.3 percent and in NEED group by 40 percent,
whereas an increase was observed in control group. Similarly maximum reduction was observed in
‘lack of interest’ in NEED and FEED groups (26.7%) followed by FED group (23.3%) and no change
in control group. In FEED (16.7%) and FED (23.3%) groups ‘numbness’ also showed a positive
change at end-line. ‘Polyphagia’ was reduced in FEED (16.7%) and FED (13.3%) groups after the
intervention.
The symptom tiredness or fatigue, referred to as ‘diabetes fatigue syndrome’ in clinical practice
is a common symptom occurring in persons with diabetes, which may be caused by a variety of
factors like lifestyle, nutritional, medical, psychological, glycemic, personal habits or endocrine
factors. In the present study about 50 to 70 percent of the subjects have reported tiredness before the
intervention which might be due to the consumption of high glycaemic index foods, high calorie food,
alcoholism and lack of physical exercise by the subjects. This may be due to the high affordability
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
Before
(%)
After (%) Before
(%)
After (%) Before
(%)
After (%) Before
(%)
After (%)
Control (n=30) NEED (n=30) FEED (n=30) FED (n=30)
Polyuria
Polydipsia
Polyphagia
Weight loss
Tiredness
Lack interest
Tingling sensation
Wound healing
Skin problems
Sexual problems

136. and exposure to such high calorie and high glycaemic foods in FEED group where high literacy and
high income was found among the subjects and in NEED and FED groups due to lack of knowledge
about the effect of consumption of high glyaemic foods.
But it is encouraging to observe a reduction in tiredness symptom in all the three experimental
groups significantly (p=0.05) after the intervention. Similarly symptoms like lethargy or lack of
interest and numbness also were observed to be reduced after the intervention in all the three
experimental groups, NEED, FEED and FED groups. It is noticed that subjects in experimental
groups did not show any progression in symptoms like skin and sexual problems which shows a
positive impact of both the interventions, the nutrition counseling as well as the low glycaemic index
multigrain mix, on the reduction of suffering from the diabetes symptoms among the subjects and a
sign of improvement in the health of the individuals.
From the post-intervention results of clinical symptoms it was observed that consumption of low
glycaemic index multigrain mix showed an improvement in the clinical symptoms among the subjects of
FEED and FED groups. It indicates that hypoglycaemic foods may minimize the clinical symptoms of
type 2 diabetes mellitus by acquiring HbA1c target and normal blood sugar levels. “The upma made with
intervened multigrain mix is stomach filling”, “feeling healthy” and “able to attend the work” were some
of the general comments received by the subjects of FEED and FED groups during the intervention period
after consuming the low glycaemic index multigrain mix and the same was reflected in the end-results
with reduced hunger, tiredness and lack of interest. Consumption of drum stick leaf powder which is
known to be rich in potassium, calcium, phosphorus, iron, vitamin A and D, essential amino acids,
antioxidants such as β carotene,vitamin C and flavonoids, through the low GI multigrain mix might be
responsible for the improved general health and wellness of the diabetic subjects reported in the present
study. The fibre content in the low GI multigrain mix might have improved the glycaemic control and
also prolonged the distension of the gastrointestinal tract and delayed the return of hunger, by slowing
gastric emptying. The presence of barley in the low GI multigrain mix might be responsible for the
increased satiety with its high content of β-glucan. No hypoglycaemic incidents were observed among the
subjects during the study period in FEED and FED groups which might be due to the effect of low GI
diet that can improve glycaemic control in diabetics without compromising the hypoglycaemic
events.
When the improvement in the clinical symptoms is compared between FEED and FED groups,
the two groups that were given intervention of low glycaemic index multigrain mix, the final result was
observed to be more in FEED group which was exposed to intervention of nutrition counseling also. It
seems that in addition to the effect of low GI multigrain mix, the nutrition counseling also helped the
subjects of FEED group in the improvement of clinical symptoms of diabetes. The counseling sessions
might have facilitated the subjects of FEED group to change their attitude towards weight management
(table.33.1) and glycaemic control (table.39) which was absent among the subjects of FED group.
In NEED group, the other group where intervention of nutrition counseling was administered
along with FEED group, also some improvement was observed in the clinical symptoms after the
intervention when compared to that of control group. The nutrition counseling might have changed the
attitude of the subjects to adhere to the planned dietary practices like having timely meals with frequent
intervals, reduced consumption of high glycaemic index foods and increasing the consumption of low
glycaemic index foods like fibre rich millets (table.21) which resulted in improved glycaemic control

137. without any episodes of hypoglycaemia during the study period in the present study. Increased
consumption of fruits and vegetables (table.23 ) after the counseling might have increased the intake of
dietary fibre which might increase satiety and decrease the symptoms like polyphagia due to the
result of colonic fermentation and short chain fatty acid production that have an effect on insulin
sensitivity.
For patients with diabetes numbness is one of the most common complications where patients
may experience losses in sensation and also foot ulceration which can be reduced with increased physical
activity that improves the blood circulation. In the present study the nutrition counseling had changed the
attitude towards increasing the physical activity level which resulted in the decreased percentage of
numbness among the subjects of NEED and FEED groups which was not observed in control and FED
groups. Increased physical exercise might have also reduced the body weight (table.33.1) of the subjects
in NEED and FEED groups which results in significant improvement in the clinical symptoms of
diabetes.
But when these two groups, FEED and NEED groups, were compared with the improvement in
the clinical symptoms, better results were observed in FEED group. Especially the cases of polyuria and
polyphagia were observed to be increased in NEED group whereas a reduction was observed in FEED
and FED groups. This indicates that the effect of intervention of low GI multigrain mix on clinical
symptoms of diabetes was positive with better outcomes. But the results of biochemical indices showed
that nutrition counseling was effective in the glycaemic control in the NEED group (table.39) after the
intervention which may eliminate the suffering from the symptoms among the subjects of NEED group in
long run.
Similar results were found by Kusumaneela et al. (2015) where it is reported that there was 100
percent polyuria among both the male and female subjects, polyphagia in 26.3 percent males and 47.3
percent females and polydypsia in 47.3 percent in males and 42.8 percent females and there is
improvement after the diet counseling. Similar to the present study Kang et al. (2008) also reported that
tiredness (73%) was the most common symptom followed by polydypsia (60%), polyphagia (47%)
and burning sensation under feet (40%) and there was a decrease in the diabetic symptoms at
the end of the 90 days period of the premix supplementation.
4.9. Effect of interventions on long term complications of diabetes
among the subjects:
Over a period of time if the blood glucose is not controlled in type 2 diabetes, it may lead to
impairment and dysfunctioning of various organs like blood vessels, nerves and kidneys due to the effect
of hyperglycaemia. Diabetic retinopathy may lead to blindness, neuropathy results in loss of sensation in
the nerve extremities and diabetic nephropathy may lead to kidney failure. In the present study the effect
of each intervention on the progression of the complications of diabetes among the selected subjects was
observed and the results are presented here.

138. Table.44. Effect of interventions on long term complications of diabetes among subjects of all the
groups
The effect of intervention on the long term complications of diabetes among the selected subjects
of all the groups is presented in table.44. The long term complications observed in the study were
diabetic retinopathy, diabetic neuropathy, diabetic nephropathy, hypertension, thyroid problem and
any other complications. The overall (N=120) results before the intervention revealed that among the
long term complications of diabetes, majority (42.5%) of the subjects reported hypertension, followed
by neuropathy-(23.3%), retinopathy (17.5%), nephropathy (4.2%), thyroid (5.8%) and other
complications like chronic body pains (5.0%). The percentage of subjects reported none of the long
term complications was 20.8 percent.
After the intervention overall there was an insignificant increase in complications like retinopathy
(1.7%), neuropathy (2.5%) and thyroid cases (1.7%). But an insignificant decrease was observed in
complications like nephropathy (1.7%), hypertension (2.5%) and other complications (1.7%). The
intervention period of 90 days may be too short to observe any changes in long term complications
but still the intervention could show some positive effect on some of the complications. The
observations of the effect on each treatment will be clear from the groupwise results which are
discussed further.
Among the long term complications at base-line majority of the subjects have reported
hypertension with the highest in NEED group (56.7%). The next highest percentage was found with
retinopathy in NEED group (33.3%) followed by neuropathy with the maximum in FEED group
S.No
Complications
Control (n=30) NEED (n=30) FEED (n=30) FED (n=30) Total (N=120)
Before
(perce
nt)
After
(perc
ent)
Diff
(perc
ent)
Before
(perce
nt)
After
(perc
ent)
Diff
(perc
ent)
Before
(perce
nt)
After
(perce
nt)
Diff
(perc
ent)
Before
(perce
nt)
After
(perc
ent)
Diff
(perc
ent)
Befor
e
(perc
ent)
After
(percen
t)
Diff
(perc
ent)
P
value
1
Retinopathy
10.0 16.7 -6.7 33.3 33.3 0.0 20.0 20.0 0.0 6.7 6.7 0.0 17.5 19.2 -1.7
0.74
0
2
Neuropathy
16.7 23.3 -6.7 23.3 26.7 -3.3 30.0 30.0 0.0 23.3 23.3 0.0 23.3 25.8 -2.5
0.53
9
3
Nephropathy
0.0 0.0 0.0 6.7 6.7 0.0 6.7 3.3 3.3 3.3 0.0 3.3 4.2 2.5 1.7
0.74
0
4
Hypertension
50.0 50.0 0.0 56.7 56.7 0.0 40.0 40.0 0.0 46.7 40.0 6.7 54.2 51.7 2.5
0.70
4
5
Thyroid
6.7 6.7 0.0 3.3 3.3 0.0 10.0 16.7 -6.7 3.3 3.3 0.0 5.8 7.5 -1.7
0.09
6
6 Other
complication
3.3 0.0 3.3 3.3 3.3 0.0 10.0 6.7 3.3 3.3 3.3 0.0 5.0 3.3 1.7
0.25
0
7
None
33.3 23.3 10.0 10.0 10.0 0.0 20.0 16.7 3.3 20.0 26.7 -6.7 20.8 19.2 1.7
0.87
4

139. (30.0%). About one-third of the subjects reported no complications in control group initially.
After the intervention not much changes were observed among the experimental groups but in
control group an increase was observed in the case of retinopathy (6.7%), neuropathy (6.7%) and
‘none’ of the complications was decreased by 10% which indicates that new complications have been
added during the intervention period. In NEED group neuropathy was observed to be increased by 3.3
percent and in FEED group new thyroid cases were added by 6.7 percent. Better outcomes were
observed in FED group with a reduction in neuropathy (3.3%), hypertension (6.7%) and an increase
in percentage (6.7%) of subjects reported ‘none’ of the complications after the intervention which is a
good sign of improvement in health.
Long term complications such as retinopathy, nephropathy and neuropathy can have a distressing
impact on the quality of life of the patient with type 2 diabetes and any improvement in the symptoms
may increase the confidence of the subjects in the treatment and recovery process. The results of the
study showed a very little improvement in the complications of diabetes in FEED and FED groups
after the intervention of low glycaemic index multigrain mix which demonstrated that there is a
relationship observed between diet and diabetic complications also. The low GI foods may contribute
to glycaemic control through the promotion of insulin sensitivity, reducing fluctuations in blood
glucose levels and reducing daily insulin requirements that can improve the condition of diabetic
complications. From the results it was observed that FEED and FED groups showed a reduction in
nephropathy after the intervention. In the present study the soya protein present in the low GI
multigrain mix might be responsible for the improvement in nephropathy as various studies proved
that the high intake of animal protein may cause hyperfiltration and glomerular hypertension that may
result in renal damage in diabetics and it may be protected with the substitution of soya protein
(Anderson et al., 1998). Soybean is said to be an important functional food for diabetes for its
isoflavones and bioactive peptides, which have favourable effect on glycaemic control and insulin
sensitivity, dyslipidaemia and also kidney function. As majority of the subjects in the study were non-
vegetarians (table.14.1) the consumption of high amounts of animal protein may aggravate kidney
problems and calcium losses. Being the richest source of minerals like calcium, phosphorus and iron,
the drum stick leaf (Moringa oleifera) powder in the low GI multigrain mix may recover the calcium
loss. A reduction in hypertensive cases was observed in FED group which may be due to the
drumstick leaf powder that may decrease the systolic and diastolic blood pressure in diabetes.

140. Fig.13. Impactof interventionsonlongtermcomplicationsamongthe subjectsof all the groups
Figure.13 depicts the impact of interventions on long term complications of diabetes among the
selected subjects of all the four groups.
From the post-intervention results it is observed that there was no change in the diabetic
complications among the subjects of in NEED group where nutrition counseling was the intervention.
But the positivity observed here was that there was no progression of complications after the
intervention either, which could be due to the effect of nutrition counseling that might have brought
awareness of the diabetic complications and the care to be taken. Long term complications are
chronic in nature and takes longer time for any change to be observed among the type 2 diabetics but
arresting the progression of disease itself is considered as a good achievement in the management of
diabetes.
An increase in diabetic peripheral neuropathy was observed in NEED group where as no change
was observed in FEED group after the intervention of nutrition counseling. Following a regular
physical exercise such as walking and running has been shown to improve neuropathic symptoms by
increasing the function and nerve conduction. In addition to this, exercise improves glucose control
and combat other complications related to diabetes, such as obesity and hypertension, thus making an
improvement in general health of patients with diabetes. But in the present study, though the attitude
of the subjects in FEED and NEED group was changed positively towards doing regular physical
exercise,it seemed to be not sufficient to observe any changes in neuropathy in the short duration of
ninety days of study period and a continuous practice of physical activity may exhibit better outcomes
in long run.
When the post-intervention results of diabetic complications are compared between groups,
whether it is between NEED and FEED groups with nutrition counseling or between FEED and FED
0.0
10.0
20.0
30.0
40.0
50.0
60.0
Before
(%)
After (%) Before
(%)
After (%) Before
(%)
After (%) Before
(%)
After (%)
Control (n=30) NEED (n=30) FEED (n=30) FED (n=30)
Retinopathy Neuropaty Nephropathy Cardiopathy Thyroid Other complications None

141. groups with intervention of low GI multigrain mix, the improvements between the groups was flatter
but the low GI multigrain mix was shown to be more effective.
Here it can be referred back (methodology) to captions of the intervention programmes where
each experimental group in the present study was named with the type of treatment given to the subjects
of each group with an objective to eliminate the diabetic symptoms among the subjects after the
completion of the intervention period. They are NEED-Nutrition Education to Eliminate Diabetic
symptoms, FEED –Food and Education to eliminate Diabetic symptoms and FED- Food to Eliminate
Diabetic symptoms. From the end-line results of clinical symptoms and the long term complications, it
can be noted that the interventions were effective in achieving the purpose of reducing the clinical
symptoms and complications among the subjects through better glycaemic control, improved lipid profile
and decreased BMI.
The present study is supported by Krishnan et al. (2015) where the results also indicated that
subjects who received periodic intensive diet counseling did not show any symptoms of progression to
diabetic complications and also did not progress to insulin therapy for the management of their disease.
The study also concluded that a six-month counseling program clearly indicated that this intervention had
a positive effect on the management type 2 diabetes mellitus.
4.10. Effectof interventions on the nutrient intake of the subjects:
1. The goal of management of diabetes is to achieve and maintain the blood glucose levels in the
normal range, a lipid profile that reduces the risk for vascular disease and blood pressure levels in the
normal range to prevent or slow down the rate of development of the chronic complications of diabetes by
modifying nutrient intake and lifestyle. In the present study the nutrient intake of the subjects was
assessed by dietary survey through 24 hour recall method which shows the nutritional status and the
attitude of the subjects also towards the dietary practices. The intake of total energy, protein,
carbohydrates, fat,calcium and iron per day were calculated at both base and end line using an
‘Application (App)’ developed by NIN,Hyderabad. The effect of each intervention on the intake of the
nutrients by the selected subjects is observed and the results are presented here.
Table.45.Effectof interventionsonnutrientintake by all the subjects(N=120)
S.No Nutrients
Before After Diff
P value
Mean ±sd Mean ±sd Mean percent
1 Energy (K cal) 1933.51 562.05 1844.50 391.89 89.01 4.60 0.072 (NS)
2 Protein (g) 45.98 15.83 43.95 11.15 2.03 4.42 0.142 (NS)
3 Energy from Protein
(%)
9.51 9.53 -0.02 -0.21
-
4 Carbohydrates (g) 318.56 84.50 303.03 58.15 15.53 4.88 0.035*
5 Energy from
Carbohydrate (%)
65.90 65.71 0.19 0.29
-
6 Fat (g) 42.39 24.17 40.98 17.10 1.42 3.34 0.508 (NS)

142. 7 Energy from fats (%) 19.73 19.99 -0.26 -1.32 -
8 Calcium (mg) 322.00 177.38 337.65 158.61 -15.65 -4.86 0.301 (NS)
9 Iron (mg) 18.52 9.30 19.28 8.80 -0.76 -4.10 0.441(NS)
*Significant, NS-Not significant
The nutritional status of the selected subjects (N=120) before and after the intervention period is
presented in table.45. From the overall results the intake of proximate principles per day before
intervention revealed that the mean energy intake was 1933.51±562.05 Kcal, protein 45.98±15.83 g,
carbohydrates 318.56±84.50 g and fat 42.39±24.17g. The results showed the distribution of energy from
macronutrients as carbohydrates (65.9%), proteins (9.51%) and fat (19.73%) per day. The calcium intake
was 322±177.38 mg/day and iron intake was 18.52±9.30 mg/day.
The results after the intervention period (table.45.1) showed an insignificant reduction (4.6%) of
the mean energy intake with 1844.50±391.89 Kcalper day. A significant (p=0.035) reduction was
observed in the mean intake of carbohydrates (4.88%) at end-line. Whereas no significant difference was
found in the mean intake of protein (4.42%) and mean intake of fat (3.34%) after the intervention period.
The increase in mean calcium intake (4.86%) and mean iron intake (4.10%) was not statistically
significant.
As majority of the subjects in the present study were found obese (table.31) the energy
requirement of an obese diabetic cannot be compared with that of a normal healthy individual. So it is
necessary to calculate the daily energy requirement of the subjects to compare with the energy intake that
was assessed during the dietary survey from the selected subjects in the present study which is elaborated
in the table.46.
Table.46. Assessment of energy requirement of the subjects
Calculation of energy requirement
The ideal body weight was assessed using Broca’s Index *
Height (in cm) –100 (The mean height was 160.9 cm)
= 169.9-100 = 60.90 cm.
The energy requirement for obese and overweight diabetics = 20Kcal/Kg body weight/day.
So the energy requirement = 60.9*20 = 1218 Kcal per day.
*( Mundodanetal.,2019)
From the table.46, it was found that the energy requirement of the subjects in the study as1218
Kcalper day with an assessed idealbody weight of 60.90 Kg (table.46). The usual recommended energy
intake for diabetics who are overweight will be 800-1500 Kcal/day (Asif, 2014). The results of dietary
assessment showed that the energy intake of the subjects assessed during the dietary survey before

143. (1933.51Kcal) and after the intervention (1844.50 Kcal) period was more than the requirement i.e., 1218
Kcalper day.
Though the total energy intake is more important than the exact proportions of carbohydrate,
protein and fat in the diet of a diabetic, it is also necessary to observe the diet with the proportion and type
of carbohydrate, the nutrient which is a major concern in type 2 diabetes. So the proportion of the macro
nutrients in the diet of the subjects in the present study was assessed and compared with the
recommended ratio.
Table.47. Comparison of energy distribution from the macro nutrients with the recommendations
of ICMR
S.No Macro
nutrient
Recommended distribution of
calories*
(Ideal energy 1218 Kcal/day)
Actual distribution of calories
(Actual energy intake1933.51
Kcal/day)
Difference
(g)
% Kcal G % Kcal G
1 Carbohydrates 60 730.8 182.7 65.9 1274.1 318.5 135.8↑
2 Proteins 15 182.70 45.6 9.51 183.8 45.9 0.3↑
3 Fat 25 304.50 33.8 19.73 381.4 42.3 8.5↑
(↑ excess),*(Viswanathan et al., 2019)
The comparison of energy distribution from carbohydrates,proteins and fats with that of the
recommended ratio is presented in table.47. The results revealed that the energy from carbohydrates
(65.90%) was more than the recommended ratio (60%) and the energy from protein (9.51%) and fat
(19.73%) was less than that was recommended. But in terms of quantity, the results explained that the
consumption of carbohydrates and fats was,135.8 g and 8.5 g per day respectively, in excess of the
recommended intake. This pattern of dietary intake can be said as a ‘high carbohydrate- high fat diet’ in
which case it should be in the form of complex carbohydrates with a high fiber content and low
glycemic index. The excess intake of carbohydrates and fats might be the reason for finding majority of
the subjects with obesity in the present study.
The protein consumption of 45.9 g per day observed in the study appeared to be the same as the
recommended intake but percentage wise it can be considered as too low (9.51%) and if it is calculated
with the ideal energy intake (1218*9.51%) it comes to only 28.95 g and there will be a deficit of 16.65 g
(45.6-28.95) per day. Other way if the protein requirement is calculated based on body weight also, it
should be 60.9g of protein taking 1g/kg/day with the ideal body weight as 60.9 Kg where the deficit will
be 15 g (60.9g-45.9g). Though the majority of the subjects were non-vegetarians, the results showed that
the protein intake was less than the required amount which may be due to the variation in the type of
animal food.
The groupwise results of nutrient intake, the effect of nutrition counseling on the nutrient intake,
the impact of nutrient intake on anthropometric measurements and glycaemic and lipidaemic control are
discussed further.
Table.48. Base-line mean values of nutrient intake of subjects of all the groups
Nutrients
Control (n=30) NEED (n=30) FEED (n=30) FED (n=30)
Mean ±sd Mean ±sd Mean ±sd Mean ±sd

144. 1 Energy (Kcal) 1928.23 352.32 2024.90 678.83 1989.53 727.52 1791.37 342.98
2 Protein (g) 44.33 11.13 48.90 17.70 48.93 19.50 41.77 12.16
3 Protein percent 9.20 - 9.66 - 9.84 - 9.33 -
4 Carbohydrates (g) 325.10 52.68 339.97 104.95 317.97 100.83 291.20 57.95
5 Carbohydrate
percent
67.44 - 67.16 - 63.93 - 65.02 -
6 Fat (g) 38.10 16.55 43.00 26.15 46.90 26.12 41.57 25.64
7 Fat percent 17.78 - 19.11 - 21.22 - 20.88 -
8 Calcium (mg) 286.47 157.58 332.03 153.51 374.50 181.54 295.00 199.11
9 Iron (mg) 18.20 7.82 21.23 9.35 18.10 11.27 16.56 7.69
Table.49. End-line mean values of nutrient intake of subjects of all the groups
S.No Nutrients
Control (n=30) NEED (n=30) FEED (n=30) FED (n=30)
Mean ±sd Mean ±sd Mean ±sd Mean ±sd
1 Energy (Kcal) 1941.03 463.79 1902.60 391.67 1864.73 353.98 1669.63 277.18
2 Protein (g) 46.90 13.48 46.47 9.35 43.27 8.69 39.17 10.66
3 Protein percent 9.66 9.77 9.28 9.38
4 Carbohydrates (g) 318.33 69.35 311.37 53.26 299.90 53.52 282.50 47.78
5 Carbohydrate percent 65.60 65.46 64.33 67.68
6 Fat (g) 43.30 18.76 41.87 16.74 42.90 15.17 35.83 16.47
7 Fat percent 20.08 19.80 20.71 19.32
8 Calcium (mg) 313.83 163.22 350.67 103.52 383.90 177.34 302.20 166.38
9 Iron (mg) 20.23 9.55 22.83 8.68 17.87 8.07 16.20 7.29
The nutritional status of the subjects in each group before and after the intervention is presented in
tables.48 and 49 respectively. The groupwise results of dietary assessment also showed more or less
similar to that of overall observations of daily nutrient intake. At base-line the maximum mean total
energy intake was observed in NEED group (2024.90±678.83 Kcal) and the minimum in FED group
(1791.37±342.98 kcal). NEED and FEED groups (48.9g) were found with the maximum mean protein
intake whereas the FED group (41.77±12.16 g) with the least. The mean carbohydrate intake was
found in NEED group (339.97±104.95 g) and the least in FED group (291.20±57.95 g). The maximum
mean fat intake was found in FEED group (46.90±26.12 g) and the least in control group (38.10±16.55
g). The highest mean calcium intake was found in FEED group (374.50±181.54 mg) and the highest
iron intake was found in NEED group (21.23±9.35 mg).
After the intervention period a reduction was observed in all the three intervention groups in the
mean intake of the nutrients. The end-line results revealed that the maximum mean intake of total
energy was found in control group (1941.03±463.79 Kcal) and the least was found in FED group
(1669.63±277.18 Kcal). The mean intake of protein was observed to be reduced in the intervention
groups whereas an increase was observed in control group with the maximum of 46.90±13.48 g. The

145. mean intake of carbohydrate was reduced in all the groups with a maximum in control group
(318.33±69.35 g). The mean intake of fat also was reduced in the intervention groups with the least in
FED group (35.83±16.47 g) and an increase was found in control group with the highest of
43.30±18.76 g. The mean intake of calcium was increased in all the groups whereas a reduction was
observed in mean iron intake in FEED and FED groups.
Fig.14. Impact of interventions on the nutrient intake of the subjects of all the groups
Graph
Figure.14 shows the nutrient intake of the subjects before and after the interventions. It is depicting a
narrow difference in mean intake of the nutrients after the intervention among the groups.
Table.50. Effect of interventions on intake of nutrients (mean difference) by the subjects of all the
groups
S.No
Nutrients
Control (n=30) NEED (n=30) FEED (n=30)
FED (
Mean
diff
percent
P
value
Mean
diff percent
P
value
Mean
diff percent
P
value
Mean
diff pe
1 Energy (Kcal) -12.80 -0.66 0.881 122.30 6.04 0.341 124.80 6.27 0.281 121.73 6
2 Protein (g) -2.57 -5.79 0.307 2.43 4.98 0.460 5.67 11.58 0.070 2.60 6
3 Protein percent -0.46 -5.00 - -0.11 -1.14 - 0.56 5.69 - -0.05 -0
4 Carbohydrates (g) 6.77 2.08 0.594 28.60 8.41 0.151 18.07 5.68 0.263 8.70 2
5 Carbohydrate
percent
1.84 2.73 - 1.70 2.53 - -0.40 -0.63 - -2.66 -4
6 Fat (g) -5.20 -13.65 0.219 1.13 2.64 0.822 4.00 8.53 0.369 5.73 13
7 Fat percent -2.30 -12.94 - -0.69 -3.61 - 0.51 2.40 - 1.56 7
8 Calcium (mg) -27.37 -9.55 0.298 -18.63 -5.61 0.525 -9.40 -2.51 0.811 -7.20 -2
9 Iron (mg) -2.03 -11.17 0.331 -1.60 -7.54 0.470 0.23 1.29 0.914 0.36 2
*Significant
The difference in mean values of nutrients before and after the intervention among the four
groups is presented in table.50. There was a reduction in total energy intake per day after the intervention
(table.50.1) was observed in NEED (6.0%),FEED (6.27%) and FED (6.8%) groups when compared to
that of control group where there was 0.66 percent increase was observed after the intervention. The
difference was statistically significant (p=<0.05) in the FED group (p=0.033).
Regarding the mean protein intake (table.50.2), though statistically insignificant, post intervention
results showed a decrease in the experimental groups, NEED (5.0%), FEED (11.6%) and FED group
(6.2%) when compared to that of control group where it was increased by 5.8 percent. But when the
proportion of protein to total calories was observed (table.50.3) it showed an increase in NEED,FED and
with a maximum in control group (5.0%) where as a decrease was observed in FEED group (5.7%).

146. There was a statistically insignificant reduction in mean carbohydrate intake observed after the
intervention (table.50.4) in all the groups with a maximum in NEED (8.4%) followed by FEED (5.7%),
FED (3.0%) and control group (2.1%). But the proportion of carbohydrates (table.50.5) to the total
energy showed an increase in FEED (0.6%) and FED (4.1%) groups whereas a decrease was observed in
NEED (2.5%) and control group (2.7%).
The mean fat intake (table.50.6) was observed to be reduced insignificantly after the intervention
in all the three experimental groups with a maximum in FED group (13.8%) followed by FEED group
(8.5%) and NEED (2.6%) whereas an insignificant increase was observed in control group (13.6%). The
proportion of fat to total energy (table.50.7) was increased in NEED group (3.6%) where as it was
reduced in FEED (2.4%) and FED (7.5%) groups.
Calcium intake (table.50.8) was increased insignificantly in all the groups after the intervention
with maximum in control group (9.6%) followed by NEED (5.6%), FEED (2.5%) and FED (2.4%)
groups, but still less than RDA for adults (600 mg/day) (ICMR, 2010) in all the groups. Iron intake
(table.50.9) was reported to be increased insignificantly in NEED (7.5%) and control (11.2%) groups
where as it showed a decrease in FEED (1.3%) and FED (2.2%) groups. As majority of the subjects were
non-vegetarians, the iron intake was meeting the RDA for adults (17-21 mg/day) (ICMR, 2010) in all the
groups except the FED group where it was slightly less than the RDA for iron.
From the results it is observed that the total mean energy intake was more than the energy
requirement per day in all the groups but in FED group it was the least. As rice is the staple food and most
of the subjects were consuming rice thrice a day (table.21), the initial total calorie intake was observed to
be more among the study population. It was observed that the majority of working people were eating
outside and the readily available ‘junk foods’ and ‘fast foods’ are generally rich in fats and calories. As
the majority of the subjects were found to be non-vegetarians (table.14.1) in the present study, the intake
of fat was found to be high. The high intake of energy and fat over a period of time might have caused
obesity (table.31) among the subjects in the present study.
In the present study after the intervention period, a positive effect was observed on the intake of
nutrients in NEED and FEED groups with the intervention of nutrition counseling. In NEED and FEED
groups, a reduction was observed in the end-line results of mean intake of total calories, carbohydrates
and fat when compared to that of control group. It might be the nutrition counseling that have brought a
positive change in the attitude of the subjects in the present study to reduce the consumption of energy
rich foods especially the quantity and frequency of rice consumption (table.21) which was observed to be
more among the subjects before intervention. Inclusion of fruits and vegetable including green leafy
vegetables was increased might be as an effect of counseling which could increase the dietary fibre that
causes satiety which reduces the need for rice consumption.
As the consumption of animal foods was reduced, the animal fat intake was observed to be
reduced after the intervention among the subjects of NEED and FEED groups. Due to the positive effect
of nutrition counseling the consumption of biscuits and other bakery foods (table.25) rich in saturated and
hydrogenated fat also was observed to be reduced. It was reported that the habit of eating outside deep
fried foods like vada and puri on regular basis which increases the fat intake was reduced after the
intervention of nutrition counseling among the subjects of NEED and FEED groups. The frequency of
consumption of nuts especially the groundnuts which are high-fat with high-energy content was reduced

147. (table.24.4) which also might have resulted in the reduced fat intake after the intervention of nutrition
counseling.
From the end-line results of nutrient intake a reduction was observed in the mean intake of
protein in NEED and FEED groups when compared to that of base-line observations. It was observed in
the study that, rice being the staple food was contributing considerable amount of protein in the diet of the
subjects. When the intake of rice was reduced for the sake of calories and carbohydrates after the
intervention, it seems that the intake of protein also was proportionately reduced. And also the reduced
consumption of nuts also might have resulted in the reduction in mean protein intake after the
intervention. The reduction in mean intake of protein might have resulted in the reduction of muscle mass
(table.33.5) observed in NEED and FEED groups. But a positive impact of nutrition counseling was
observed in the inclusion of dairy foods and variety of pulses in the diet after the intervention, which can
compensate the protein gap in due course.
An increase in the mean calcium intake was observed in NEED and FEED groups though not
significant, after the intervention of nutrition counseling which may be due to the increased consumption
of dairy products (table.23.5) and green leafy vegetables (table.23.2) by the subjects in the present study.
This might have resulted in an increase though insignificant, in the iron intake also in NEED group.
When the effect of assessment of nutrient intake on anthropometric measurements and body
composition (table.34) was observed among the groups, it showed a positive effect in NEED and FEED
groups when compared to that of control and FED groups. The energy balance may have an effect on
body weight, blood pressure, and lipid levels directly. The reduction in total calories, carbohydrates and
fat intake might have resulted in the reduction of body weight, waist circumference,BMI, body fat and
visceral fat with a significant reduction in body weight and visceral fat in FEED group. The increased
bone mass (table.34.6), significant in NEED group, might be the result of the increased intake of calcium
observed at the end of the study period.
The impact of nutrient intake on glycaemic and lipidemic control (table.39) was observed to be
positive in NEED and FEED groups when compared to that of control group. The reduced intake of total
calories and carbohydrates had resulted in the improved glycaemic control significantly including HbA1c
after the intervention among the subjects of NEED and FEED groups. The decreased intake of fats in the
diet might have improved the total serum cholesterol, LDL-C, VLDL and triglycerides and an increase in
the HDL-C levels among the subjects after the intervention. It appears that the improvement in metabolic
indicators after the intervention had shown an improvement in clinical symptoms and general health of
the subjects in NEED and FEED groups in the study.
When the assessment of nutrient intake was compared between NEED and FEED groups, the two
groups that were exposed to nutrition counseling, a mixed end-result was observed between both the
groups. The reduction of mean energy intake and fat intake was observed better in FEED group which
had received the intervention of low glycaemic index multigrain mix also. Whereas in NEED group, the
reduction in intake of mean carbohydrate and increase in intake of mean calcium and iron were observed
better. Since the literacy level (table.12.5) and the level of knowledge (table.18) on the disease were
found more in FEED group, the importance of maintaining the energy balance in the management of
diabetes may be better perceived during the counseling sessions and better practised.

148. Surprisingly in FED group also, where only low GI multigrain mix was intervened to the subjects
without any counseling sessions, a reduction was observed in the intake of total mean calories and mean
fat intake after the intervention period. Soluble fibre has the ability to form a gel in the stomach when it
mixes with liquids and that slows down the emptying of stomach. The low GI multigrain mix has
contributed good amount of protein and dietary fibre which may result in increasing the satiety and
sustainability for longer gap between the meals after its consumption for ninety days of intervention
period. This might have reduced the need for the consumption of rice and other fatty rich junk foods by
the subjects of FED and FEED groups that resulted in reduction in energy and fat intake after the
intervention period. The reduced energy and fat intake had shown better outcomes in glycaemic control
and improvement in lipid profile in FED group (table.39) but had not resulted in the reduction of mean
anthropometric measurements like body weight, BMI and body fat percentage (table.33) after the
intervention and in fact an increase was observed in these measurements. This may be due to the physical
exercise regimen, the importance of which was emphasized during the counseling sessions to NEED and
FEED groups which prompted them to have more awareness but it was absent in FED group. The positive
attitude towards physical exercise (table.17.1) was found less in FED group may be because of the lower
educational background of the subjects and low knowledge level about the disease. A combined
intervention programme of low glycaemic index food and nutrition counseling with long-term follow-up
may prove sustained benefits.
Kusumaneela et al. (2015) also reported similar initial intake of nutrients by the type 2 diabetes in
Vijayawada, as follows: energy 1992.60 Kcal, protein 49.84g, carbohydrates 307.38 g, fat 49.45 g,
calcium 40.91 mg and iron 34.25 mg in a dietary education programme. In contrary to the present study,
the Intake of nutrients was very high in South Italy reported by Di Onofrio et al. (2018) where the total
energy was 2152.88 Kcal, protein 119.07 g and fat was 100.83 g in a nutritional motivational intervention
study for type 2 diabetics.
Similar difference in total energy intake was found in a study by Amano et al. (2007) where a
reduction of 6 percent was found after a 3 months of GI based nutritional education. But after 6 months
of nutrition education a difference of 31.2 percent was found in energy intake in another study by Ma et
al. (2008). Di Onofrio et al. (2018) reported a 26.23 percent reduction in energy intake after a 9 months
nutrition motivational intervention programme.
In contrary to the present study regarding the post intervention intake of protein, an increase of
5.3 percent in protein intake was found in Kusumaneela et al. (2015) after the dietary education and 2.1
percent was found in the proportion of protein in Ma et al. (2008) which was after 6 months of dietary
education.
Similar to the results of present study, the increase in proportion of carbohydrate was 0.27 percent
in Ma et al. (2008) and 1.7 percent in Amano et al. (2007) after the GI based dietary education. A
reduction of 1.6 percent and 2.83 percent was observed in Amano et al. (2007) and Ma et al. (2008)
respectively in regards to proportion of fat to total calories after dietary education which were
comparatively higher than the results of the present investigation. Surprisingly there found a 50 percent
decrease in fat consumption after 3 months of nutrition motivational intervention, which was higher
when compared to the present study, reported by Di Onofrio et al. (2018) where it was high at baseline
also with 100.83g intake per day.

149. Table.51. Comparison of nutrient intake of subjects between the groups after the intervention
ANOVA
After Mean Sum of Squares df Mean Square F Sig.
Between
Groups
27147.220 3 9049.073 .021 .996
Within Groups 10480895.391 24 436703.975
Total 10508042.611 27
The results of one way ANOVA test for comparison of mean values of nutrient intake
after the intervention between the groups is shown in table.51. The results showed that the
difference after the intervention in the intake of nutrients was not statistically significant between
the groups.
Table.52. Correlation of various demographic variables with nutrient intake of all the subjects

150. * significant (p=<0.05),
The correlation of various demographic variables with the nutrient intake of all the subjects is
shown in table.52. There was no significant correlation found between the gender, age, income
and education of the subjects with the nutrient intake. But a trend (p=>0.05) was observed
between age group 40-50 years and iron intake. When the correlation between occupation and
nutrient intake was observed, a significant correlation was found between daily wage labourer
and intake of protein (p=0.000) and intake of fat (p=0.005) and also between other occupations
and intake of protein (p=0.026). This shows that the intake of nutrients was not influenced by
gender, age, income and level of education but occupation has shown little influence on the
intake of protein and fat.
S.N
o Demographic variables Energy Protein carbohydrates Fats Calcium Iron
1 Gender
Female
Male
2 Age
< 40 years
40 – 50 years 0.081
50 – 60 years
> 60 years
3 Income
< 10000
10000 – 25000
25000 – 50000
> 50000
4 Education
Illiterate
Primary
High School
College
University
5 Occupation
Officer/supervisor
Business
Professional
Home Maker
Daily wage
labourer
0.000*
0.005*
Others
0.026*
0.065

151. 4.11. Participants’compliance to intervention of nutrition counseling:
Nutrition counseling was provided for the subjects and their family members during their visits.
The overall compliance to nutrition counseling has been found satisfactory. An encouraging part of the
study was that the participants were very enthusiastic and interested to attend all the sessions. This
reflects the thirst for information among diabetic patients and need for such programmes to be conducted
for patients with diabetes. It was interesting to note that the subjects tend to show the highest compliance
with certain dietary recommendations like consumption of vegetables, sprouts and whole grain products,
doing physical exercise daily at least for 30 minutes and reducing the consumption of sweetened
beverages and bakery food. Results indicated that after the intervention, the subjects did not show any
symptoms of progression to diabetic complications. It was found that the picture charts and brochures
provided with the subjects during the sessions were quite useful for their day-today dietary management.
It was expressed by majority of the subjects that the results of anthropometric measurements and
biochemical parameters at the end of the study period were quite encouraging for the implementation of
the knowledge perceived during the intervention period into good practice.
4.12. Participants’compliance to intervention of low glycaemc index
multigrain mix:
The participation of subjects in the dietary intervention programme was quite satisfactory. The
overall compliance report on consumption of the low glycaemic index multigrain mix was very good.
All the participants were able to tolerate the formula very well. The positive general comments observed
on the consumption of multigrain mix were that the product was giving fullness, produced satiety with
the recommended quantity, energized and enabled to sustain for longer period after the consumption.
The subjects also expressed that they were happy with such ready to cook, nutritious products and there
was no need to add any spices further. The participants also experienced a feeling of overall better health
during the intervention period with reduced physical symptoms of diabetes (table.43). This is supported
by many studies that glycemic control affects the appearance, better mood, sense of well-being and
progression of the complications of chronic diabetes. The few discomforts expressed during the initial
period of intervention were that the product was increasing body heat, burping up with the smell of
kalonji and disliking of the colour (light grey colour with the presence of Nigella sativa) and flavour
(strong flavour of Nigella sativa) of the product. But at the end of the study period, the subjects started
liking the aroma of the cooked product.
The study was designed to test the following hypotheses that,
Hypothesis I : Nutrition counseling to type 2 diabetic patients will significantly increase the knowledge
of the disease and show positive effect on blood sugar levels, HbA1c and lipid profile and
Hypothesis II : Intervention of low glycaemic index multigrain mix to type 2 diabetic patients will
significantly reduce the blood sugar levels, HbA1c and improve the lipid profile.
The present investigation supports Hypothesis-I that the nutrition counseling has a positive
impact on significantly increasing the knowledge level among the patients of type 2 diabetes and a

152. positive effect on significantly lowering the blood glucose levels including HbA1c and significantly
improving the lipid profile of the type 2 diabetic patients. Hence the hypothesis-I is accepted.
The present study supports, Hypothesis-II that the intervention of low glycaemic index multigrain
mix to type 2 diabetic patients has a positive effect on significantly lowering the blood glucose levels
including HbA1c and significantly improving the lipid profile among the patients of type 2 diabetes
mellitus. Hence the hypothesis-II is accepted.
The results of the study in regards to nutrition counseling confirms that nutrition counseling
imparts the required knowledge of the disease among the type 2 diabetic patients and the improvement in
knowledge of diabetes and its management had positive impact on treatment outcomes and quality of life.
The interest and curiosity showed by the participants during the sessions revealed that the diabetic
patients are in need of such counseling sessions. But from the results, at the end of the study it was felt
that more than imparting knowledge, the aim of any nutrition or diet counseling for the patients with type
2 diabetes mellitus should aim at changing the attitude of the patients towards changing the life style that
turns the little or more knowledge perceived or existing into good practices.
As regards the low glycaemic index multigrain mix, the results of the study proved that low
glycaemic index formulations with hypoglycaemic plant foods have some therapeutic effect on blood
glucose levels and lipid profile of the patients with the type 2 diabetes. The results confirmed that the
promising healing and medical potential of the developed multigrain mix can help solving the health care
of the patients with type 2 diabetes without any side effects. The full cooperation and enthusiasm to
collect the pouches of the product during the study period and the demand for the product even after the
study period by the participants showed that the diabetic patients are in need of such effective
formulations. So the study suggests that such simple and safe formulations made with the concept of low
glycaemic index with complex carbohydrates and high protein content can be recommended and
popularized among type 2 diabetic patients.
The interesting part of the current study is use of two different kinds of interventions, the
intervention of nutrition counseling and the intervention of low glycaemic index multigrain mix among
three groups. The findings of the study showed that the group (FEED group) where both the interventions
were administered had shown better outcomes. Nutrition counseling brought a positive change in the
attitude of the subjects to adhere to the good practices which showed a positive impact on the metabolic
indices or anthropometric measurements. Whereas the consumption of low glycaemic index multigrain
mix showed a direct effect on the biochemical parameters and anthropometric measurements but without
the knowledge about the importance of physical activity regimen and care of the disease. So it can be
concluded that a combined programme with a low glycaemic index diet or formulations added with
nutrition education or counseling may have more beneficial outcomes than restricted to a single
intervention of either nutrition counseling or low glycaemic index diet.
Future line of work:
 Patent rights to be applied for low glycaemic index multigrain mix,
 The product will be made ready for the public use after obtaining the patent rights,
 Exploitation of locally available millets for improvising the multigrain mix,

153.  Some more preparations out of the multigrain mix are to be developed and standardized.
Limitations of the study:
 The study period can be extended further for better results if time and finance are
permitted.
 Sample size can be increased for better comparison of results,
 Gender specific analysis can be done for better comparison and conclusion of the results,
 The assessment of GI of the product can be carried out with diabetic volunteers also.
****
******

154. 5. Summary and Conclusion
Type 2 diabetes mellitus is a progressive metabolic disorder, representing one of the biggest
public health problems with a major impact on the lives and well-being of individuals and families
worldwide. Because of its chronic nature and the expensive medication required to control the
complications, diabetes has become a costly disease which is sometimes beyond the reach of majority of
people. With its rapid growth, the economic burden of diabetes care on families is increasing rapidly in
developing countries like India, which is also affecting the mental health of the individuals with pain,
anxiety and stress. The lack of awareness about diabetes among the people is aggravating the existing
situation or leaving many cases undiagnosed. So it is necessary to introduce cost-effective treatment
strategies which are simple and also making nutrition counseling a part of the treatment strategies.
The current evidence shows that the concept of low glycaemic index (GI) is one of the effective
dietary approaches for good glycaemic control in patients with T2DM. Glycaemic Index is a ranking of
foods based on the postprandial blood glucose response compared with reference food (glucose) and low
glycaemic index foods are those with a GI of 55 or less.
Hence the present investigation was undertaken with the objectives to develop and standardize a
low glycaemic index multigrain mix, to analyze the nutrient composition and shelf life of the developed
low glycaemic index multi grain mix, to evaluate the glycaemic index and sensory evaluation of the
developed low glycaemic index multigrain mix, to study the effect of intervention of the developed low
glycaemic index multigrain mix on glycaemic and lipidemic control in type 2 diabetics, and also to assess
the effect of intervention of nutrition counseling on improving the blood glucose levels and lipid profile
in patients with type 2 diabetes mellitus.
The whole study was undertaken in three phases as pre-intervention phase, intervention phase and
post-intervention phase in Hyderabad city, Telangana. In phase-I, a total of 125 people who met the
inclusion criteria were randomly allocated to four groups, with one control group and three experimental
groups with a minimum of 30 people in each group. Base-line data collection included the information
about the demographic background, health history, personal and dietary habits which were collected with
the help of a structured interview schedule from the subjects of all the four groups. Anthropometry,
biochemical indices and dietary assessment were also recorded for all the four groups at base-line.
Initially two low glycaemic index multigrain products, Product-I and Product-II, were developed
for sensory evaluation, to select one of them for the intervention. From the sensory mean scores and
comments of the panel, product-II, with Wheat rava (Triticum aestivum) (35%), Barley rava (Hordeum
vulgare) (30%), Finger millet rava (Eleusine coracana) (10%), Defatted Soya chunks (Glycine max)
(20%), drumstick leaf powder (Moringa Oleifera) (1.5%) and kalonji (Nigella Sativa) (3.5%) was selected
for intervention. The nutrient composition, shelf life and glycaemic index of the developed multi grain
mix were analyzed and packed in butter paper pouches with 60g of product in each packet for
intervention.
A structured curriculum, teaching aids like picture charts and diabetes information
brochures were developed for the effective nutrition counseling. A pilot study was conducted to
evaluate the feasibility of the study and test the study tools and was found feasible for the study. The

155. approval of the institutional ethical committee was obtained to conduct the study as per the
approved project proposal.
In phase-II, the intervention phase, the interventions were administered to the three
experimental groups for a period of 90 days with a final number of 30 subjects in each group
after considering the drop outs. Among the three experimental groups, NEED group received
only nutrition counseling, FEED group received both nutrition counseling and dietary
intervention and FED group received only dietary intervention of low glycaemic multigrain mix.
In phase-III, the post intervention phase, the end-line assessment of knowledge, attitude
and practice, assessment of nutritional status, post-tests of anthropometry, biochemical and
clinical tests were carried out to all the four groups with a final total of 120 subjects. The data
were computerized and analyzed for statistical results.
The salient findings of the study are summarized here:
 Out of total 120 study subjects, there were 48 (40%) female and 72 (60%) male subjects.
Groupwise also male subjects were more than female subjects in each group.
 The age group was 35 to 65 years and the mean age was 49 years. The highest percentage
(41.67%) of diabetics was found in the age group of 45-54 years,followed by 55-65 (31.67%)
years and 35-44 (26.67%) years age groups.
 The maximum percentage of subjects (89.17%) belonged to Telangana state and very few from
Andhra Pradesh (10%) and other southern states (0.83%).
 The marital status of the subjects showed that the majority of subjects were married (92.5%) with
unmarried (0.83%) and widows or widowers (6.67%).
 Illiterates were found to be 10 percent and among the educated,majority were with school
education (50.83%) followed by graduates and post graduates (39.17%).
 Thirty percent of the sample was employed, followed by professionals (20%) and 17.5 % were
business people (17.5%) and home makers (22.5 %). The percentage of people who were living
on daily wages was 1.67 and 8.33 percent of subjects were engaged in other occupations like
commission agents..
 The type of living showed that majority of subjects (75.83%) were from nuclear families and one-
fourth of the study group (24.17%) was from joint families.
 The annual income of the subjects showed that majority of subjects belonged to lower-middle
income group (41.67%) followed by upper-middle income (20%), low income group (27.5%) and
high income groups (10.83%).
 Family history of the disease, a risk factor for type 2 diabetes, showed that, history of mother
being diabetic was 28.3 percent followed by father (20%), both mother and father (18.3 %) and
grandparents being diabetic (7.5 %). The percentage of subjects who did not report any family
history of diabetes was 32.5.
 Newly diagnosed (less than one year) subjects were 16.7 percent followed by duration of 1-5
years (38.3%) and 5 to 10 years (26.7%). The percentage of subjects suffering for long duration
of more than 10 years was 18.3.

156.  When medication was observed,only 3.3 percent was on insulin injection, 90.8 peercent was
taking hypoglycaemic agents and the remaining 5.8 percent of subjects were not taking any
medication for diabetes.
 Majority of subjects (78.3%) were non-vegetarians. Vegetarians and ova-vegetarians were 18.3
percent and 3.3 percent respectively.
 Alcoholics and ex-alcoholics were 40 percent and 5 percent respectively and non-alcoholics were
55 percent. There was no change in the percentage of alcoholics after the intervention, but
difference was observed in the frequency of alcohol consumption.
 It was found that 83.3 percent of the subjects were not using tobacco at all and smokers (7.5 %)
and ex-smokers (5%) were found less. Tobacco chewing was found to be 4.2 percent. Snuff
dipping was found to be nil. There was no change observed in the number of smokers, tobacco
chewing and snuff dipping after the intervention of nutrition counseling among the subjects.
 People who were doing regular exercise before intervention (66.7 %) overall was increased after
intervention (69.2 %) and it was the maximum in FEED group (10%), which could be the effect
of nutrition counseling.
 Overall 78.3 percent people were following regular diet plan which was increased to 90.8 percent
after the intervention of nutrition counseling. The maximum percentage of difference was
observed in FEED group (20%), followed by NEED group (16.7%) and FED group (3.3%) after
the intervention.
 Hypoglycaemic drugs were regularly taken by majority of the subjects (98.3 %) as per the
physician’s advice and after the intervention, raised to 100 percent.
 The glycaemic index of the developed product was found to be 51.51 after the GI test,which is
considered as low GI.
 The nutrient composition of the developed low glycaemic index mix was assessed and found
energy (342.60 Kcal), protein (17.3%), carbohydrates (62.68 %), fat (2.24 %),crude fibre(
3.84%), Beta carotene (12.7 μg/100gm), calcium (2074.84 mg/Kg), iron (84.04 mg/Kg),
zinc (29.24 mg/Kg) and gluten free.
 Of total 120 subjects, the base line results showed that 18.3 percent of subjects were having
inadequate knowledge about the disease, where as 50 percent were having moderate knowledge
and 31.7 percent were having good knowledge. A significant increase (p<0.05) was found in the
knowledge levels after the intervention (24.2%) and inadequate knowledge score was reduced to
14.2 percent. After intervention, ‘good knowledge’ score was improved significantly in NEED
and FEED groups where as it was less in FED group, which could be due to the effective
nutrition counseling.
 Initially the negative attitude towards the disease was 86.7 percent and positive attitude was only
13.3 percent. A significant increase (p<0.05) was found in the positive attitude after the
intervention among the subjects of NEED group (23.3%) and FEED group (13.3%), when
compared to that of control group (6.7%) and FED group (6.7%).
 Initially the percentage of negative and positive practices of disease control among the total
subjects was 51.7 percent and 48.3 percent respectively. The overall positive practice scores
were significantly improved by 20.8 percent after the intervention. A significant increase
(p<0.05) was found in the positive practice in NEED group (30%) and in FEED group (36.7%)

157. when compared to that of control (10%) and FED group (6.7%) after intervention of nutrition
counseling.
 From the food frequency tables, it was found that majority (61.6%) of people was eating rice only
once a day followed by twice a day (31.6%) and thrice a day (3.33%). Wheat was consumed by
56.6 %percent daily once and 42.5 percent of people were consuming millets once a day. More
than half of the people were never taking millets. After the intervention there were positive
changes in the consumption pattern of cereals and millets by the subjects which were observed
more in NEED and FEED groups when compared to that of FED and control groups.
 It was found that red gram dhal was consumed by all the subjects at different frequencies but the
consumption of other pulses like green gram dhal (83.4%), black gram dhal (76%) and Bengal
gram (23%) also was found. After intervention, the percentage of never eating green gram dhal
and Bengal gram dhal was decreased in NEED group, though not significant.
 Majority (99%) of people was consuming green leafy vegetables but frequency was once or twice
a week and was slightly improved after the intervention. A positive reduction was observed
among the subjects in the frequency consumption of potato after the intervention. The number of
people who never consumed fruits before intervention had become nil in all the test groups after
intervention which was a positive effect. The percentage of dairy products never consumed was
4.16 percent, which was reduced to 1.66 percent after the intervention.
 Among nuts and oil seeds,groundnut was consumed by majority (95.84%) of people followed by
other nuts (65.84%) and dry fruits (59.17%). After intervention, the consumption of nuts was
positively decreased.
 Majority (69.17%) of people were consuming sweets,58.34 percent were consuming aerated
drinks. Biscuits and other bakery items were consumed by 88.34 percent and 64.17 percent
respectively. Post intervention results revealed that there was a positive decrease in the
consumption of sweets,aerated drinks, biscuits and other bakery items.
 Over all percentage of never eating egg was 22.5 percent before and there was no change after
intervention. In NEED group 3.33 percent was taking meat daily thrice, which was shifted to
daily once after intervention. Fish was eaten by 66.67 percent of people before intervention which
was increased to 68.34 percent after intervention.
 The mean height of the subjects was 160.9 cm. The mean weight was 71.58 Kg and ranged
between 34.4 -113.7 Kg. The mean value of waist circumference was 39.23 inches (99.64 cm).
After intervention, in FEED group there was statistically significant (p=<0.05) decrease in body
weight which could be the effect of nutrition counseling. Overall there was a 0.25percent
decrease in mean waist circumference.
 The overall mean BMI was found to be 27.80 kg/m2
. Alarmingly according to Indian criteria of
BMI classification, majority (70%) of people were obese which is one of the risk factors for type
2 diabetes, followed by overweight (20%), normal BMI (14%) and under weight (2%). After
intervention, the overall mean BMI was decreased.
 The overall mean values of body composition were body fat (33.38 %), body muscle mass (44.69
%),body bone mass (2.55 %),total body water (46.27 %) and visceral fat (11.98). After
intervention a significant (p=<0.05) increase in overall mean bone mass and a significant
decrease in mean visceral fat were found when compared to that of control group.
 The mean readings of fasting blood sugar (FBG) level and postprandial glucose (PPG) were
141.4 mg/dl and 221.3 mg/dl respectively. After intervention there was significant (p=<0.05)

158. decrease found in the means of FBG (113.49 mg/dl) and PPG (177.96 mg/dl) . The mean HbA1c
was 7.7 percent and post intervention the overall mean difference in HbA1c was 3.61 percent
which was significant (p=<0.05). The findings showed that the intervention of low GI multigrain
mix resulted in positive improvement in HbA1C among the FEED and FED groups, which was
significant when compared to that of control group.
 The lipid profile of the subjects revealed that the mean values of VLDL (39.61 mg/dl) and
triglycerides (210.60 mg/dl) were higher than the normal values. The mean values of total
cholesterol were 183.56 mg/dl, LDL-Cholesterol -103.04 mg/dl and HDL-Cholesterol- 42.19
mg/dl. There was significant improvement found in total cholesterol (3.08 %), HDL-C (2.85 %),
LDL-C (4.77 %), VLDL (8.05 %) and triglycerides (12.60 %) in mean differences after
intervention.
 Among the clinical symptoms, the majority (62.5%) of subjects reported tiredness followed by
polyurea (40%), poludipsia (39.2%), polyphagia (37.5%), tingling sensation or numbness of
limbs (39.2%), wound healing (9.2%),skin problems (15%) and sexual problems (20%). Seven
percent of the subjects reported none of the diabetes symptoms. After the intervention, a
significant difference (p<0.05) was observed in symptom-tiredness (35%), followed by the
symptom-lack of interest (19.2%) and numbness or tingling sensation in the hands and feet
symptom (10.8%).
 Among the long term complications of diabetes, majority (42.5%) of the subjects reported
hypertension, followed by retinopathy (17.5%), neuropathy (23.3%), nephropathy (4.2%),thyroid
(5.8%) and other complications like body pains (5%). The percentage of subjects reported none of
the long term complications was 25 percent.
 The intake of proximate principles per day revealed the mean energy intake as 1933.51 Kcal,
protein 45.98 g (9.51% of total calories), carbohydrates 318.56 g (65.90% of total calories) and
fat 42.39g (19.73% of total calories). The intake of iron was 18.52 mg/day. The energy intake
was reduced by 6.0 -6.8 percent in the experimental groups after intervention and it was
significant in FED group. A significant decrease (p=<0.05) was observed in carbohydrate intake
among the total subjects. An insignificant increase was observed in calcium intake and iron.
 Participants’ compliance to intervention of nutrition counseling as well as the intervention of low
glycaemic index multigrain mix was found satisfactory.
In the present study, impact of the two interventions, the nutrition counseling for bringing
awareness of disease that improves the glycaemic and lipidemic control and the intervention of low
glycaemic index multigrain mix for the glycaemic control and improvement in lipid profile, was proven
positive on type 2 diabetic patients.
Addition of indigenous food ingredients that are having hypoglycaemic effect, to staple food like
wheat at optimum level of acceptability may be responsible for reducing the glycaemic index of the
designed multigrain mix and also enhancing the nutritive value of the product. The formulation was easy
to prepare, safe, non-toxic and cost effective. The results of the study on effect of low glycaemic index
foods on subjects of type 2 diabetics concluded that the designed low glycaemic index multigrain mix can
be recommended for including in the diet of patients with type 2 diabetes mellitus for achieving good
glycaemic control, improving lipid profile and to check the progression of the disease.

159. Positive messages related to lifestyle modification like changes in diet, increasing physical
activity, cessation of smoking and stress management which influence the progression of type 2 diabetes
were taken care in nutrition counseling sessions in the present study. The impact of the intervention of
nutrition counseling was effective in increasing the knowledge levels about the disease among the study
subjects which could bring positive attitudes and practices for the better management of diabetes. The
results of the study showed that nutrition counseling was effective in good glycaemic control and
controlling the further development of complications of the disease. So the study concluded that bringing
awareness through nutrition counseling among the patients of type 2 diabetes mellitus is considered as the
best tool in the management of type 2 diabetes.
Nutrition counseling to diabetic patients enables them to choose proper diet for the management
of diabetes and ready-to-cook low glycaemic index formulations make a quick choice to even illiterate
patients and also save the time. So it can be suggested that dietary intervention combined with nutrition
counseling is needed to improve the standard of diabetic care.
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