1. The study measured body mass index (BMI), body fat percentage, and skinfold thickness among medical students in Sabah, Malaysia using various assessment methods.
2. On average, the students' BMI was 21.95±0.59 kg/m2, body fat percentage was 16.98±1.37%, and skinfold thicknesses ranged from 17.44±1.24 mm to 23.04±1.23 mm.
3. Reliability testing found the three-site skinfold thickness calculation had excellent internal consistency for males and acceptable consistency for females. Measurements also had good reliability for males compared to females. Further research on determinants of obesity over time is
Anthropometric measurements adult and paediatricsSusan Jose
this presentation gives a detailed information regrading the adult and pediatric measurements. it gives a good intrepretation and understanding of the subject.
Anthropometric measurements adult and paediatricsSusan Jose
this presentation gives a detailed information regrading the adult and pediatric measurements. it gives a good intrepretation and understanding of the subject.
Nutritional Anthropometry- Measurement of the variations of the physical Dimensions & the gross composition of the human body at different age levels and degrees of nutrition.
Anthropometric measurements are a series of quantitative measurements of the muscle, bone, and adipose tissue used to assess the composition of the body. The core elements of anthropometry are height, weight, body mass index (BMI), body circumferences (waist, hip, and limbs), and skinfold thickness
Assessment of body composition , strength, endurance, flexibility agility power coordination speed . tests for all the above mentioned components. health and skill related physical fitness
Relationship of body mass index, fat and visceral fat among adolescentsSports Journal
In the present study the researcher studied out the correlation of Body mass index, Fat and visceral fat
among adolescents. Data was statically analyzed using descriptive statistics and Pearson Product Multi
Correlation Coefficient was used (PPMCC). It was find out that body mass index was significantly
correlated with fat and visceral fat and on the other hand fat was also significantly correlated with
visceral fat among adolescents.
Nutritional Anthropometry- Measurement of the variations of the physical Dimensions & the gross composition of the human body at different age levels and degrees of nutrition.
Anthropometric measurements are a series of quantitative measurements of the muscle, bone, and adipose tissue used to assess the composition of the body. The core elements of anthropometry are height, weight, body mass index (BMI), body circumferences (waist, hip, and limbs), and skinfold thickness
Assessment of body composition , strength, endurance, flexibility agility power coordination speed . tests for all the above mentioned components. health and skill related physical fitness
Relationship of body mass index, fat and visceral fat among adolescentsSports Journal
In the present study the researcher studied out the correlation of Body mass index, Fat and visceral fat
among adolescents. Data was statically analyzed using descriptive statistics and Pearson Product Multi
Correlation Coefficient was used (PPMCC). It was find out that body mass index was significantly
correlated with fat and visceral fat and on the other hand fat was also significantly correlated with
visceral fat among adolescents.
Comparing BMI and hand grip strength of Tsinghua University Beijing and Unive...IOSR Journals
Abstract: Background: This study was an illustrated cross sessional study of male and female students of
Tsinghua University Beijing China and University of Sindh Pakistan students. The study objectives were to
describe normative data and compare the BMI and hand grip strength of dominant hand of both universities
students. The study elaborated that health and fitness status of universities lifestyle of young male and female
students are significantly related to the desire level of general health and fitness level and observed the attitude
of students towards health assessment activities and status.
Obesity is defined as excessive unhealthy accumulation of body fat. India has the third largest obese population in the world after United States of America and China. Prevalence of obesity has reached epidemic proportions in parts of India. In some urban areas, up to a third of the population is either overweight or obese. Childhood and adolescent obesity is also rising rapidly. If this trend continues, certain sections of Indian society may start seeing declining life expectancy in India after many decades of steady progress. Early diagnosis of overweight and obesity may prevent progression to more severe forms associated with complications. In this review, we examine the usefulness of Body Mass Index in diagnosis of obesity in Asian Indian population and the debate surrounding the call for a downward revision of “normal” range in this population.
Application of Binary Logistic Regression Model to Assess the Likelihood of O...sajjalp
Abstract: This study attempts to assess the likelihood of overweight and associated factors among the young students by analyzing their physical measurements and physical activity index. This paper has classified four hundred and fifteen subjects and precisely estimated the likelihood of outcome overweight by combining body mass index and CUN-BAE calculated. Multicollinearity is tested with multiple regression analysis. Box-Tidwell Test is used to check the linearity of the continuous independent variables and their logit (log odds). The binary regression analysis was executed to determine the influences of gender, physical activity index, and physical measurements on the likelihood that the subjects fall in overweight category. The sensitivity and specificity described by the model are 55.9% and 96.9% respectively. The increase in the value of waist to height ratio and neck circumference and drop in physical activity index are associated with the increased likelihood of subjects falling to overweight group. The prevalence of overweight is higher (27.8%) in female than in male (14.7%) subjects. The odds ratio for gender reveals that the likelihood of subjects falling to overweight category is 2.6 times higher in female compared to male subjects.
Keywords: Overweight, Waist to Height Ratio, Neck Circumference, Binary Logistic Model, Odds Ratio
1
Running head: OBESITY
3
Running head: OBESITY
Obesity
Lauren Urquiza
Chamberlain University
NR503 Population Health, Epidemiology, & Statistical Principles
January 2018
Obesity
Obesity is a chronic medical condition and a significant health concern in the United States that is increasing worldwide. More than one third of the adults in the U.S. are obese. It is a leading cause of preventable illness and death (Centers for Disease Control and Prevention [CDC], 2016). This global epidemic is a leading concern for adults and for children who are predisposed to becoming obese as adults. This paper will discuss the significance of obesity in Florida, provide a background of the disease, review current surveillance and reporting methods, conduct a descriptive epidemiological analysis, discuss diagnosis and screening for prevention tools, develop an evidence based plan along with measureable outcomes to address obesity as an advanced practice nurse, and conclude with an overview of the main points presented.
Background and Significance
According to the CDC (2016), obesity is defined as “weight that is higher than what is considered as a healthy weight for a given height.” It involves excessive weight gain and accumulation of fat. In order to determine obesity, Body Mass Index or BMI is used to indirectly calculate a person’s body fat and health risk based on weight in relation to height. A BMI of 25.0 or above is considered overweight and 30.0 or greater is considered obese. Athletes with a greater amount of muscle mass may have a higher BMI even though they do not have excess body fat. Waist circumference is also used as a tool to diagnose obesity.
There are many causes that contribute to obesity, including behavioral, genetic, hormonal, environmental, and social factors. Increase in caloric intake, unhealthy eating habits, decrease in physical activity, certain medications, age, lack of sleep, quitting smoking, pregnancy, and certain medical disorders can contribute to weight gain (Mayo Clinic, 2018). Driving cars has replaced walking and riding bikes, technology has replaced engaging in physical activity, and easy access to cheaper foods has replaced nutritional importance. Most people are aware when weight is gained. Obvious signs and symptoms are tighter clothes, excess fat, and increased weight on a scale. Being overweight or obese increases the risk for many health diseases. Obesity may cause low endurance, breathing issues, excessive sweating, and joint discomfort. It can also lead to diabetes, gastroesophageal reflux disease, coronary heart disease, hypertension, high cholesterol, stroke, depression, and even certain types of cancer such as bowel, breast, and prostate cancer (Mayo Clinic, 2018).
Below is a map that highlights the obesity prevalence across the U.S. in 2016 according to the CDC. There is no significant difference in overall prevalence between men and women. The prevalence of women with a BMI > 35 ...
Management of Excess Weight and Obesity: A Global PerspectiveCrimsonPublishersIOD
Non-communicable diseases (NCDs), especially, hypertension, excess weight, obesity, metabolic syndrome, type-2 diabetes, and vascular diseases,
have increased rapidly in the last two decades and have reached an epidemic status worldwide. Some experts have compared this increase in the
incidence of these diseases as “tsunamis”. Tsunamis’ are seasonal and unpredictable whereas, these diseases are predictable and not seasonal. So, what
are we going to do about this situation? Are we going to sit and wait for some miracle to happen? What are the member nations of the United Nations,
World Health Organization, NCD Task Force going to do about this, besides writing and publishing scary reports of future economic and healthcare
disasters? In this overview, we would like to discuss briefly the salient findings on this topic, initiate a healthy dialogue, request suggestions, positive
comments, and offer few suggestions.
ABDOMINAL OBESITY AND ITS ASSOCIATED RISK FACTORS - AN UPDATEindexPub
Background: India has a serious Abdominal Obesity (AO) concern with a frequency of 24.8%, particularly among metropolitan especially in women. Generalised obesity (GO) & AO, both of which are associated with greater rates of mortality & morbidity. In India, AO is more prevalent than GO (24.5%), & it has been associated to a number of health hazards, including the metabolic syndrome, insulin resistance, & cardiovascular diseases (CVD), high blood pressure & PCOS.
Obesity is a chronic, debilitating, life long disease giving rise to many other diseases. Severe obesity is
associated with co-morbidities including type 2 DM, hypertension, dyslipidemia, obstructive sleep apnoea,
obesity hypoventilation syndrome, polycystic ovarian syndrome, stateohepatosis, asthma, back and lower
limb degenerative problem, cancer and premature death. Morbid obesity has acquired epidemic proportions in the west. Traditional approaches to weight loss including diet, exercise and medication achieve no more than 5-10 % reduction in body weight with high relapse rates. So far, there was no effective remedy for morbid obesity. Bariatric surgery is the only effective means of achieving long term weight loss in the severely obese. The international guideline for bariatric surgery are BMI > 40 kg/m2 BMI > 35 kg/m2 together with obesity related disease. Bariatric surgery can achieve sustained weight loss durable to at least 15 years and causes marked improvement in co-morbidities.
1Running head OBESITY 4Running head OBESITY.docxvickeryr87
1
Running head: OBESITY
4
Running head: OBESITY
Obesity
NR503 Population Health, Epidemiology, & Statistical Principles
January 2018
Obesity
Obesity is a chronic medical condition and a significant health concern in the United States that is increasing worldwide. More than one third of the adults in the U.S. are obese. It is a leading cause of preventable illness and death (Centers for Disease Control and Prevention [CDC], 2016). This global epidemic is a leading concern for adults and for children who are predisposed to becoming obese as adults. This paper will discuss the significance of obesity in Florida, provide a background of the disease, review current surveillance and reporting methods, conduct a descriptive epidemiological analysis, discuss diagnosis and screening for prevention tools, develop an evidence based plan along with measureable outcomes to address obesity as an advanced practice nurse, and conclude with an overview of the main points presented.
Background and Significance
According to the CDC (2016), obesity is defined as “weight that is higher than what is considered as a healthy weight for a given height.” It involves excessive weight gain and accumulation of fat. In order to determine obesity, Body Mass Index or BMI is used to indirectly calculate a person’s body fat and health risk based on weight in relation to height. A BMI of 25.0 or above is considered overweight and 30.0 or greater is considered obese. Athletes with a greater amount of muscle mass may have a higher BMI even though they do not have excess body fat. Waist circumference is also used as a tool to diagnose obesity.
There are many causes that contribute to obesity, including behavioral, genetic, hormonal, environmental, and social factors. Increase in caloric intake, unhealthy eating habits, decrease in physical activity, certain medications, age, lack of sleep, quitting smoking, pregnancy, and certain medical disorders can contribute to weight gain (Mayo Clinic, 2018). Driving cars has replaced walking and riding bikes, technology has replaced engaging in physical activity, and easy access to cheaper foods has replaced nutritional importance. Most people are aware when weight is gained. Obvious signs and symptoms are tighter clothes, excess fat, and increased weight on a scale. Being overweight or obese increases the risk for many health diseases. Obesity may cause low endurance, breathing issues, excessive sweating, and joint discomfort. It can also lead to diabetes, gastroesophageal reflux disease, coronary heart disease, hypertension, high cholesterol, stroke, depression, and even certain types of cancer such as bowel, breast, and prostate cancer (Mayo Clinic, 2018).
Below is a map that highlights the obesity prevalence across the U.S. in 2016 according to the CDC. There is no significant difference in overall prevalence between men and women. The prevalence of women with a BMI > 35 is 18.3% compared to 12.5% of men. The.
Role of Daily life style and Medication in Prevention and treatment of obesityPriyankaKilaniya
The rising prevalence of overweight and obesity underscores the need for enhanced intervention strategies to tackle this significant public health issue. Increases in energy expenditure through exercise and other physical activity may be a crucial component of effective interventions to enhance initial weight loss and prevent weight regain. achieve these outcomes, it is recommended to engage in appropriate levels of exercise and physical activity, with 60 to 90 minutes per day being the recommended duration. Epidemiological surveys in England reveal that obesity is prevalent, defined as a body mass index (BMI) of greater than 30 kg/m2. This study is the first to report the prevalence of general obesity and abdominal obesity in the adult population of Spain, based on weight, height, and waist circumference measurements. Diet, smoking, and physical activity are significant lifestyle factors that can significantly impact body weight and fat accumulation. The PREDIMED study, a randomized dietary primary prevention trial conducted in Spain, assessed the relationship between lifestyle and obesity risk. A study assessed 7,000 high-cardiovascular risk subjects, determining a healthy lifestyle pattern (HLP) based on Mediterranean diet adherence, moderate alcohol consumption, daily physical activity of 200kcal/day, and non-smoking.
Neck Circumference as an Indicator of Overweight and Obesity in Young Adultssajjalp
Abstract Neck circumference (NC) measurement is one of the simple screening measurements, that can be used as a marker of upper body fat distribution to notice overweight. The objective of this study is to evaluate the relationship between NC and overweight/obesity. In this cross-sectional study a total 198 college students (120 Female, 78 Male) aged 18-23 years were participated using convenience method. Anthropometric measurements of ﰀﰁﰂﰃﰄﰅﰁﰀﰆﰇﰄﰈﰄﰆﰉﰄﰊﰀﰂﰈﰄﰃﰆﰊﰋﰋﰌﰈﰃﰍﰅﰎﰆﰁﰌﰆﰁﰏﰄﰆﰎﰂﰍﰃﰄﰐﰍﰅﰄﰀﰆﰌﰑﰆﰇﰌﰈﰐﰃﰆﰏﰄﰊﰐﰁﰏﰆﰌﰈﰎﰊﰅﰍﰒﰊﰁﰍﰌﰅﰓﰆﰔﰁﰂﰃﰄﰅﰁﰀﰆﰇﰍﰁﰏﰆﰕﰖﰆﰗﰘﰙﰆﰋﰉﰆﰑﰌﰈﰆﰉﰊﰐﰄﰆ ﰊﰅﰃﰆﰗﰘﰚﰆﰋﰉﰆﰑﰌﰈﰆﰑﰄﰉﰊﰐﰄﰆﰊﰅﰃﰆﰛﰜﰝﰆﰗﰆﰞﰟﰆﰠﰎﰡﰉ2 are identified as overweight. The percentages of the male and female ﰀﰁﰂﰃﰄﰅﰁﰀﰆ ﰇﰍﰁﰏﰆ ﰛﰜﰝﰆ ﰗﰆ ﰞﰟﰆ ﰠﰎﰡﰉ2 were 9% and 15.8% respectively and with high NC were 47.4% and 23.3 % respectively. In both male and female students, there were significant and positive correlation of neck circumference with body weight (male, r=0.572; female, r=0.629; p=0.001), waist circumference (male, r= 0.407; female, r= 0.623; p=0.001), hip circumference (male, r=0.546; female, r=0.579; p=0.001), BMI (male, r= 0.532; female, r= 0.588; p=0.001), waist to hip ratio (female, r = .376; p= .001), and waist to height ratio (male, r= 0.33; female, r= 0.574; p=0.001). A significant and independent association was found between NC and overweight levels using multiple regression analysis in young adults. This study indicates neck circumference is a simple screening measure that can be used to identify overweight/obesity.
Keywords: neck circumference, body mass index, overweight, anthropometry
ABSTRACT- Background: Malnutrition constitutes a major public health concern worldwide and serves as an indicator
of hospitalized patient’s prognosis. Nutritional support is an essential aspect of the clinical management of children
admitted to hospital. Malnutrition has been long associated with poor quality, poor diet and inadequate access to health
care, and it remains a key global health issue that both stems from and contributes to weakness, with 50% of childhood
deaths due to principal under nutrition.
Methods: The present hospital based cross sectional study was conducted in April to Dec 2015 among 300 rural
adolescents of 9-18 years age (146 boys and 154 girls) attending the outpatient department at Patna Medical College and
Hospital, Bihar, India, belonging to the all caste communities. The nutritional status was assessed in terms of under
nutrition (weight-for-age below 3rd percentile), stunting (Height-for-age below 3rd percentile) and thinness (BMI-for-age
below 5th percentile). Diseases were accepted as such as diagnosed by pediatrician, skin specialist and medical officer.
Results: The prevalence of underweight, stunting and thinness were found to be 31%, 22.3% and 30.7% respectively. The
maximum prevalence of malnutrition was observed among early adolescents (23% - 54%) and the most common
morbidities were diarrhoea (16.7%), carbuncle / furuncle (16.7%) and scabies (12%).
Conclusion: Malnutrition among hospitalized under five children and around suffers moderately high rates of
malnutrition. Present nutrition programs attention on education for at risk children and referral to regional hospitals for
malnourished children. Screening tools to classify children at risk of developing malnutrition might be helpful.
Key-words- Malnutrition, Hospitalized children, Morbidities, Prevalence, Stunting
2. Zin et al. Body fat percentage, BMI and skinfold thickness among medical students
South East Asia Journal of Public Health 2014;4(1):35-40
Body mass index (BMI) is an index of weight-for-height
for categorizing overweight and obesity in adults.4-6
It is
calculated as a person’s weight in kilograms divided by
the square of his height in meters (kg/m2
). WHO
classify overweight and obesity as a BMI greater than or
equal to 25 and 30 respectively; however, BMI may not
correspond to the same degree of fatness in different
individuals.4,6,7
The measurement of the human body, in terms of the
dimensions of bone, muscle, and adipose (fat) tissue, is
the study of anthropometry.5
The United States National
Health and Nutrition Examination Survey [(Center for
Disease Control and Prevention (CDC)]5
used
anthropometric measurement data to evaluate: body
composition changes that occur over the adult lifespan,
health and dietary status, and disease risk. Generally,
CDC used the following anthropometry measures for
nutritional assessment: weight, head circumference,
recumbent length, standing height, upper leg length,
upper arm length, arm circumference, abdominal (waist)
circumference, and skinfolds.5
Skinfold measurement is a widely used body
composition testing method for assessing body fat
percentage (BFP).5
A skinfold caliper is used for
measuring thickness of skin and transformed or
computed into body fat composition in percentage.
Different type of skinfold caliper measures a double
layer of skinfold thickness in mm, mostly from three to
nine different anatomical sites around the body.5,6
The health risks associated with obesity are not always
constant. Some literature argues about the relationship
between health risks and a lower BMI in Asian
populations, as evidenced by a high prevalence of type 2
diabetes mellitus and cardiovascular risk factors that
occur at a BMI below 25 kg/m2
.8
Furthermore, there is
also evidence of a higher percentage of body fat among
Asian subjects at a similar BMI cut-off point compared
to Caucasian subjects, indicating the risk of obesity-
related diseases among Asians increases from a lower
BMI of 23 kg/m2
.8-10
Obesity statistics in Malaysia as
reported by the National Health and Morbidity Survey
1996 were: adult males 15.1% were overweight and
2.9% obese and adult females 17.9% were overweight
and 5.7% obese.11
Furthermore, there was little
difference between rural and urban populations and
racial variation; Malays were more obese than Indians
and Indians were more obese than Chinese.11
Healthcare
costs for obesity can be both direct – preventive,
diagnostic and treatment services – and indirect – costs
refer to the value of salary lost by people unable to work
because of illness or disability, as well as the value of
future earnings lost by premature death and ultimately
the quality of life lost to society.12
The objective of the present study was to explore body
weight and body fat in Year 2 medical students of
Sabah, Malaysia by using different types of nutritional
assessment methods. The study would also report on the
prevalence of obesity, average BMI and body fat
composition among the medical students, and examine
the reliability and accuracy of different types of
anthropometric measurement tools.
Materials and Methods
This cross-sectional study was conducted among Year 2
medical students of School of Medicine, University
Malaysia Sabah to analyze anthropometric parameters
in relation to height, weight, skinfold and BMI, and
predicting body fat percentage. All students of year 2
were included when they were attending a nutritional
practical class on the day of survey.
Students were thoroughly explained and demonstrated
the different types of nutritional measurements.
Students conducted the examination in pair and they
measured each other’s anthropometric parameters. For
consistency, only the right side of the body was used to
measure the skinfold thickness. The student pinched the
skin at the appropriate site and raises the double layer of
skin and the underlying adipose tissue, but not the
muscle. Skinfold measurements immediately after
physical activity were not allowed because there might
be a possible fluid shift to the skin and incorrect
estimates.13
As per CDC guidelines for measurement,
the calipers were applied (1 cm) below and at right
angles to the pinch, and a reading in millimeters (mm)
taken two seconds later.5
To prevent measurement error,
we measured twice and the mean of two measurements
was taken or a third measurement was done (if two
measurements differed greatly), then the median value
taken.
Three standard measurement tools were used: TANITA
Body Composition Analyzer (SC 330 model, Max
270kg, Min 2 kg, e=0.1 kg, T=10 kg, Body Fat %;
Range 3–75%, Increment 0.1%), SECA Height and
Weight Scale, and Accu-Measure for Skinfold
measurement available at the School of Medicine,
Universiti Malaysia Sabah.5,7,14-16
Proper instruction and
a demonstration had been given before the assessment.
Four site skinfold thickness, namely triceps, abdomen,
supra-iliac and sub-scapular was measured and body fat
composition calculated by Accu-Measure and Lab A6-3
alternative skinfold measurement formula using three
sites skinfold (Abdomen, Supra-iliac, Triceps)17
; Male
{(0.39287 × sum of three skinfolds) – (0.00105 × [sum
of three skinfolds]2
) + (0.15772 × age)– 5.18845} and
Female {(0.41563 × sum of three skinfolds) – (0.00112
× [sum of three skinfolds]2
) + (0.03661 × age) +
4.03653}.
Data analyses have been done using statistical package
SPSS 21 available in the Universiti Malaysia Sabah.
Descriptive statistics for baseline indicators and skinfold
thickness and body fat composition were shown for all
students. Regression analysis for BMI, weight, height
and skinfold body fat was done. Obesity was calculated
according to the Malaysia Obesity Classification: under
nutrition (<18.5 kg/m2
), normal (18.5-22.9 kg/m2
), over
weight (≥23 kg/m2
), and obese (≥27.5 kg/m2
).10
Reliability tests for body fat composition measurements:
skinfolds — triceps, abdomen, supra-iliac, sub-scapular
and three sites — and body analyzer have been done.
36
3. Zin et al. Body fat percentage, BMI and skinfold thickness among medical students
South East Asia Journal of Public Health 2014;4(1):35-40
The ethical permission of the study was granted by the
Ethical Committee, School of Medicine, University
Malaysia Sabah, Sabah State, Malaysia.
Results
Anthropometric data was collected from 40 students.
The mean age of the students was 20.18 years. In
analysis, mean of baseline anthropometric
measurements were: weight 59.39±2.10 kg, height
1.63±0.01 m, BMI 21.95±0.59 kg/m2
; and skinfold
thickness in four sites were: triceps 20.37±1.14 mm,
abdominal 23.04±1.23 mm, supra-iliac 17.44±1.24 mm
and sub-scapular 19.22±1.11 mm. Furthermore, the
mean body fat percentages calculated by different skin-
fold thickness were: abdominal 24.13±1.11%, supra-
iliac 20.35±1.35%, subscapular 21.83±1.01%, and alter-
native three-site 19.46±1.02% (Table 1).
According to the Malaysia Obesity Classification,10
students’ BMI was classified into underweight (male
10%, female 21%), normal weight (male 57%, female
63%), pre-obese/overweight (male 24%, female 11%),
and obese (male 10%, female 5%) (Table 2).
In reliability testing, body fat percentages in different
methods were compared with standard body fat analyzer
(TANITA) readings and following readings were found
(Table 3):
Three-site skinfold thickness calculation
reliability test (Cronbach’s alpha); male 0.906
(excellent internal consistency) and female 0.67
(acceptable internal consistency)
Reading for skinfold thickness in millimeters
(Body Fat Interpretation Chart) reliability test
(Cronbach’s alpha); 1) Triceps – male 0.888 and
female 0.504, 2) Abdomen – male 0.887 and
Female 0.565, 3) Supra-iliac – male 0.855 and
female 0.609, and 4) sub-scapular – male 0.861
and female 0.634.
37
Table 1: Descriptive statistics: skinfold measurement and selected baseline indicators (n = 40)
Variables Mean Std. Error Minimum Maximum
Age 20.18 0.07 19.00 21.00
Weight (kg) 59.39 2.10 41.00 94.30
Height (m) 1.63 0.01 1.50 1.80
Body Mass Index (BMI kg/m2
) 21.95 0.59 16.90 35.50
Mean Body Fat % measured by Body
Composition Analyzer
16.98 1.37 3.10 42.10
Triceps Skinfold Thickness (mm) 20.37 1.14 5.00 41.00
Abdominal Skinfold Thickness (mm) 23.04 1.23 6.40 40.00
Supra-iliac Skinfold Thickness (mm) 17.44 1.24 4.40 36.00
Sub-scapular Skinfold Thickness (mm) 19.22 1.11 9.00 41.00
Body Fat % by Triceps Skinfold 22.60 1.29 3.90 35.20
Body Fat % by Abdominal Skinfold 24.13 1.11 6.20 35.20
Body Fat % by Supra-iliac Skinfold 20.35 1.35 3.90 35.20
Body Fat % by Sub-scapular Skinfold 21.83 1.01 9.50 35.20
Body Fat % by Three site Calculation 19.46 1.02 3.91 33.43
Gender Obesity Classification Frequency (%) BMI Range
Male
Underweight (BMI<18.5) 2 (10%) 16.95–17.75
Normal Weight (BMI 18.5 - 22.9) 12 (57%) 18.89–22.88
Pre-Obese (BMI 23.0 - 27.4) 5 (24%) 24.47–26.86
Obese (BMI ≥ 27.5) 2 (10%) 27.78–30.12
Female
Underweight (BMI<18.5) 4 (21%) 17.01–18.31
Normal Weight (BMI 18.5 - 22.9) 12 (63%) 19.33–22.76
Pre-Obese (BMI 23.0 - 27.4) 2 (11%) 23.15–24.62
Obese (BMI ≥ 27.5) 1 (5%) 35.49
Total: Male and Female 40 16.95–35.49
Table 2: BMI classification of Year 2 medical students
Reliability Models Cronbach’s alpha
Male Female
BFP Alternative three site Calculation and Body Fat Analyzer 0.906 0.670
BFP by Skinfold Thickness (Triceps) and Body Fat Analyzer 0.888 0.504
BFP by Skinfold Thickness ( Abdominal ) and Body Fat Analyzer 0.887 0.565
BFP by Skinfold Thickness ( Supra-iliac ) and Body Fat Analyzer 0.855 0.609
BFP by Skinfold Thickness ( Sub-scapular ) and Body Fat Analyzer 0.861 0.634
Table 3: Reliability test for different methods of body fat percentage
4. Zin et al. Body fat percentage, BMI and skinfold thickness among medical students
South East Asia Journal of Public Health 2014;4(1):35-40
Discussion
Based upon the Malaysia Obesity Classification, the
study showed a higher prevalence of overweight (24%)
and obese (10%) among male students and a lower
prevalence of overweight (11%), and obese (5%) among
female students. Male students were found to be obese
than the national level when compared with findings of
the Malaysia National Health and Morbidity Survey
1996,11
which reported that 2.9% obese among adult
males, and 5.7% obese among adult females.11
As
reported by many studies, BMI is commonly used to
determine overweight and obesity in clinical and field
research settings.18,19
However, there is some debate
about the relationship between BMI and body fat; three
studies have highlighted that BMI does not distinguish
between lean and fat body mass.19-20
Moreover, Peltz et
al. reported that BMI is neither reliable nor sufficient
for identifying individuals with obesity and the
incidence of obesity based solely on BMI has the poten-
tial to be substantively biased.21
On the other hand, some studies reported that
distribution of body fat acts as a predictor of metabolic
disturbances, cardiovascular disease, cancers, and
premature mortality.19,22-23
There are various methods
which can estimate body adiposity. The most
commonly used method, the skinfold thickness
measurement – which assesses body fatness through the
use of calipers at particular body sites – has shown a
strong correlation with reference methods.24,25
Another
assessment method, the body composition analyzer
which measures body fatness through bioelectrical
impedance analysis (BIA) – is widely used in clinical
and research settings.26,27
BIA has been widely used as a
validated measurement of body adiposity when
compared to reference methods such as underwater
weighing (UWW) and dual energy X-ray
absorptiometry (DEXA).26-28
In our study, body fat
percentage (BFP) measured by different methods were:
body composition analyzer (16.98 ± 1.37%), triceps
skinfold (22.6±1.29%), abdominal skinfold
(24.13±1.11%), supra-iliac skinfold (20.35±1.35%), sub
-scapular skinfold (21.83±1.01%) and the alternative
three-site calculation formula (19.46±1.02%), but there
was no consistency between the methods. Some studies
suggested that, age, gender, ethnicity, and physical
activity level are also recommended to be considered for
greater precision in the BIA and skinfold equation.29,30
Measurement reliability is the most essential factor in
every research. It is directly related to data quality.
Generally, probability of any relationships among
variables of the study could be increased by reducing
errors in the measurement. Lohman and colleagues’
standardization of measurement techniques in
anthropometry, developed by late 1980s, could be used
as a guide and reference for reliable anthropometric
measurements.31,32
However, there is still a problem in
the uniformity of method when collecting reliable data
and reporting the statistics of a reliability
assessment.31,33-35
This study also calculated reliability test for different
measurements of body fat percentage (BFP).
Cronbach’s alpha is commonly accepted for describing
measurement of internal consistency by George and
Maller Simple Guide; ≥0.90 (excellent), 0.7≤ – <0.9
(good), 0.6≤ – < 0.7 (acceptable), 0.5 ≤ – < 0.6 (poor)
and < 0.5 (unacceptable).36,37
The reliability test for the
alternative three-sites skinfold calculation for body fat
percentage (BFP)17
showed excellent and acceptable
internal consistency – Cronbach’s alpha; male 0.906 and
female 0.67. The test of BFP from reading the skinfold
thickness for triceps, abdomen, sub-scapular and supra-
iliac showed good to poor internal consistency where
male were good and female were poor to acceptable –
Cronbach’s alpha for four sites; male (0.888, 0.887,
0.855, 0.861) and female (0.504, 565, 609, 634). The
body fat percentage of females, our BFP findings had a
lower reliability power compared to the males. There is
a similar report about the difference between the sexes
regarding fat deposit – women have greater abdominal
subcutaneous fat and far less intra-abdominal fat than
men – and body fat mass – different formula for male
and females’ BMI/body fat and skinfold thickness rela-
tionship.30
There are some limitations in this study. This is a cross-
sectional observation and provides an association
between variables. Unlike a longitudinal observation, a
cross-sectional study could not verify changes in the
effects of the variables. Next, the measurements were
taken by the students themselves who followed the
instructions provided by the researcher. Finally, in this
purposive and one-point cross-sectional study neither
other important variables (e.g. BMI, such as race,
height, age, and sex) nor changes throughout life were
able to be analyzed.
Conclusion
Our study showed a higher level of overweight and
obesity among male medical students than the
Malaysian national standard. This is important because
overweight and obesity are preventable but are the fifth
leading cause of global deaths in 2013. Moreover, they
are risk factors for diabetes, heart diseases and cancers.
Furthermore, body fat percentage measurements had an
excellent to good internal consistency and greater
reliability for male students – skinfold thickness reading
and alternative three-sites skinfold calculation – and a
relatively acceptable to poor internal consistency and
lower reliability for female students, but lower than the
male students’ results – skinfold thickness reading and
alternative three-sites skinfold calculation. Finally, the
relatively lower internal consistency and reliability for
the measurement of skinfold thickness and body fat
composition among female students will need more
facts and further studies about the differences in body
fat distribution among female students and subsequent
effects on measurements are recommended.
Acknowledgement
We appreciate (2012-2013) Year 2 Medical Students
and Medical Lab Year 2 Practical for their support in
38
5. Zin et al. Body fat percentage, BMI and skinfold thickness among medical students
South East Asia Journal of Public Health 2014;4(1):35-40
this study. Furthermore, I fully acknowledge support of
Professor Dr D. Kamarudin D. Mudin - School of
Medicine, University Malaysia Sabah in his fullest
support to my writing.
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