This study compared two methods for measuring body fat percentage in overweight individuals - skinfold thickness (SF) and bioelectrical impedance analysis (BIA). 85 overweight or obese adults and elderly patients were evaluated. The percentage of body fat estimated by SF was significantly higher than BIA, but a moderate correlation and strong concordance was observed between the two methods. Both SF and BIA showed significant correlations with BMI and waist circumference, but BIA had stronger correlations. The study concluded that while the methods produced different estimates, they provided similar classifications of individuals. BIA also had better correlation with anthropometric indicators, suggesting it may be a preferable method for measuring body fat in clinical practice.
Body Composition Profiling: The Stepping Stone Towards Precision Medicine in ...Chelsea Ranger
Body composition and fat distribution is an unknown factor in many clinical trials conducted in the metabolic area today. Many studies are likely conducted in a population thought to be homogeneous, while those studies actually include subjects with vastly different body compositions associated with completely different metabolic disease profiles. The answer to whom should be included and which subjects respond best to a treatment could lie in body composition.
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
DOI:10.21276/ijlssr.2016.2.4.22
ABSTRACT- Diabetes mellitus, an impaired blood glucose status is a major cause for loss of valuable human life. The
important risk factors include: High familial aggregation, insulin resistance, lifestyle changes due to rapid urbanization
and obesity specially central one. This study was carried out in diabetics (study group) & non-diabetic (control group)
women of 30-50 years age. They were subjected to anthropometric measurement and body composition assessment by
bioelectrical impedance analysis. This include waist circumference (WC), hip circumference (HC), waist hip ratio (WHR),
body mass index (BMI), body fat % (BF %) and lean body mass % (LBM %). It was found that the BMI of study group
was significantly higher as compared to that of controls. Values of WC and WHR were significantly higher in Type 2 DM
women than control. This shows that there is association of abdominal obesity (WC and WHR) with Type 2 DM. BF %
gives the relative percentage of fat in human body. BF% was significantly high in diabetic women than in control. Mean
value of body fat % in study group was 35.67±3.03% while that of controls was 28.29±2.66%. This shows that Asians
having higher BF % at low BMI values and also individuals with a similar BMI can vary considerably in their abdominal
fat mass. In such a situation, body fat would constitute the only true measure of obesity. Key-words- Body Composition, Bioelectrical impedance, Type 2 Diabetes Mellitus
Clinical Usefulness of a New Equation for Estimating Body Fat
(Utilidad clínica de una nueva ecuación para estimar la grasa corporal)
Javier Gómez-Ambrosi, PHD1,2⇓, Camilo Silva, MD2,3, Victoria Catalán, PHD1,2, Amaia Rodríguez, PHD1,2, Juan Carlos Galofré, MD, PHD3, Javier Escalada, MD, PHD2,3, Victor Valentí, MD, PHD2, Fernando Rotellar, MD, PHD2, Sonia Romero, MSC2,3, Beatriz Ramírez, MSC1,2, Javier Salvador, MD, PHD2,3 and Gema Frühbeck, MD, PHD1,2,3
Corresponding author: Javier Gómez-Ambrosi, jagomez@unav.es.
Diabetes Care 2012 Feb; 35(2): 383-388. https://doi.org/10.2337/dc11-1334
Body Composition Profiling: The Stepping Stone Towards Precision Medicine in ...Chelsea Ranger
Body composition and fat distribution is an unknown factor in many clinical trials conducted in the metabolic area today. Many studies are likely conducted in a population thought to be homogeneous, while those studies actually include subjects with vastly different body compositions associated with completely different metabolic disease profiles. The answer to whom should be included and which subjects respond best to a treatment could lie in body composition.
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
DOI:10.21276/ijlssr.2016.2.4.22
ABSTRACT- Diabetes mellitus, an impaired blood glucose status is a major cause for loss of valuable human life. The
important risk factors include: High familial aggregation, insulin resistance, lifestyle changes due to rapid urbanization
and obesity specially central one. This study was carried out in diabetics (study group) & non-diabetic (control group)
women of 30-50 years age. They were subjected to anthropometric measurement and body composition assessment by
bioelectrical impedance analysis. This include waist circumference (WC), hip circumference (HC), waist hip ratio (WHR),
body mass index (BMI), body fat % (BF %) and lean body mass % (LBM %). It was found that the BMI of study group
was significantly higher as compared to that of controls. Values of WC and WHR were significantly higher in Type 2 DM
women than control. This shows that there is association of abdominal obesity (WC and WHR) with Type 2 DM. BF %
gives the relative percentage of fat in human body. BF% was significantly high in diabetic women than in control. Mean
value of body fat % in study group was 35.67±3.03% while that of controls was 28.29±2.66%. This shows that Asians
having higher BF % at low BMI values and also individuals with a similar BMI can vary considerably in their abdominal
fat mass. In such a situation, body fat would constitute the only true measure of obesity. Key-words- Body Composition, Bioelectrical impedance, Type 2 Diabetes Mellitus
Clinical Usefulness of a New Equation for Estimating Body Fat
(Utilidad clínica de una nueva ecuación para estimar la grasa corporal)
Javier Gómez-Ambrosi, PHD1,2⇓, Camilo Silva, MD2,3, Victoria Catalán, PHD1,2, Amaia Rodríguez, PHD1,2, Juan Carlos Galofré, MD, PHD3, Javier Escalada, MD, PHD2,3, Victor Valentí, MD, PHD2, Fernando Rotellar, MD, PHD2, Sonia Romero, MSC2,3, Beatriz Ramírez, MSC1,2, Javier Salvador, MD, PHD2,3 and Gema Frühbeck, MD, PHD1,2,3
Corresponding author: Javier Gómez-Ambrosi, jagomez@unav.es.
Diabetes Care 2012 Feb; 35(2): 383-388. https://doi.org/10.2337/dc11-1334
Cardiovascular diseases are considered as one of the threats to human
health, especially, in individuals with overweight. The aim of this study was to
investigate the effect of eight-week aerobic exercises in 10 to 12 years old overweight
girls. In this study, 27 overweight female student whit 10-12 years old were selected
and were randomly divided into two groups; a) training group (n=17) and b) control
group (n=10). Training group participated into the aerobic training for 8 weeks, with
70-85 percent of heart rate reserve maximum, 3 times a week and 60 minutes in each
session. The variables such as BF, BMI, WHR and VO2max, were measured in two
groups before and after the training period. The average of variables such as BF, BMI
and VO2max were significantly different between two groups (P<0.05). But the
average of WHR were not significantly different between two groups. According to
these results, aerobic exercise in 10-12 years old overweight girls, can have beneficial
effects on some cardiovascular risk factors.
Women who test positive for one of the two breast cancer susceptibility genes, BRCA1 and BRCA2, increase their risk by 45-55 percent. Currently, there are no specific physical activity recommendations for these women. However, research supports the positive effect of exercise on reducing breast cancer risk by reducing BMI, adipose tissue, and damage caused by lipid peroxidation.
The Effect of Surgery Type on the Quality of Life in Breast Cancer Patients:...Crimsonpublishers-IGRWH
The Effect of Surgery Type on the Quality of Life in Breast Cancer Patients: A Mini Review by Kefayat Chaman Ara in Investigations in Gynecology Research & Womens Health
ABSTRACT- Background: Esophageal and Lung carcinoma are the leading cause of years of life lost because of cancer and is associated with the highest economic burden relative to other tumor types. Epidemiological studies identify magnesium deficiency as a risk factor for these types of human cancers. The present studies were performed to concerning the contribution of magnesium to tumorigenesis and investigate the concentration of magnesium in esophageal and lung carcinoma.
Aims and Objective: The aim of this study was to compare the serum magnesium levels of patients with carcinoma of lung and esophagus patients and apparently healthy people.
Material and methods: Study group consisted of 50 clinically diagnosed subjects (Biopsy confirmed 25 cases with Esophageal carcinoma and 25 cases with Lung carcinoma). The control group consisted of 50 healthy subjects were included in the study. Venous blood samples of each lung and esophagus cancer were obtained and serum magnesium level was measured by Atomic Absorption Spectrophotometer measurements.
Results: In the study group, we were found mean concentration of serum magnesium was decreased in esophageal (1.40±0.13 mg %) and lung carcinoma (1.23±0.12 mg %) in comparison to controls (2.08 ± 0.45 mg %).
Conclusions: Serum magnesium was found statistically significantly lower in study group when compared with control (P<0.0001).
Key-words- Lung and Esophagus Carcinoma, Magnesium, Atomic absorption spectrophotometer
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.
Sarcopenic obesity is a chronic condition, which is due to progressively aging populations, the increasing incidence of obesity, and lifestyle changes. The increasing prevalence of sarcopenic obesity in elderly has augmented interest in identifying the most effective treatment. This article aims at highlighting potential pathways to muscle impairment in obese individuals, the consequences that joint obesity and muscle impairment may have on health and disability, recent progress in management with attention on lifestyle management and pharmacologic therapy involved in reversing sarcopenic obesity. Recent findings: It has been suggested that a number of disorders affecting metabolism, physical capacity, and quality of life may be attributed to sarcopenic obesity. Excess dietary intake, physical inactivity, low-grade inflammation, insulin resistance and hormonal changes may lead to the development of sarcopenic obesity. Weight loss and exercise independently reverse sarcopenic obesity. Optimum protein intake appears to have beneficial effects on net muscle protein accretion in older adults. Myostatin inhibition causes favourable changes in body composition. Testosterone and growth hormone offer improvements in body composition but the benefits must be weighed against potential risks of therapy. GHRH-analog therapy is effective but further studies are needed in older adults. Summary: Lifestyle changes involving both diet-induced weight loss and regular exercise appear to be the optimal treatment for sarcopenic obesity. It is also advisable to maintain adequate protein intake. Ongoing studies will determine whether pharmacologic therapy such as myostatin inhibitors or GHRH-analogs have a role in the treatment of sarcopenic obesity.
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.
Cardiovascular diseases are considered as one of the threats to human
health, especially, in individuals with overweight. The aim of this study was to
investigate the effect of eight-week aerobic exercises in 10 to 12 years old overweight
girls. In this study, 27 overweight female student whit 10-12 years old were selected
and were randomly divided into two groups; a) training group (n=17) and b) control
group (n=10). Training group participated into the aerobic training for 8 weeks, with
70-85 percent of heart rate reserve maximum, 3 times a week and 60 minutes in each
session. The variables such as BF, BMI, WHR and VO2max, were measured in two
groups before and after the training period. The average of variables such as BF, BMI
and VO2max were significantly different between two groups (P<0.05). But the
average of WHR were not significantly different between two groups. According to
these results, aerobic exercise in 10-12 years old overweight girls, can have beneficial
effects on some cardiovascular risk factors.
Women who test positive for one of the two breast cancer susceptibility genes, BRCA1 and BRCA2, increase their risk by 45-55 percent. Currently, there are no specific physical activity recommendations for these women. However, research supports the positive effect of exercise on reducing breast cancer risk by reducing BMI, adipose tissue, and damage caused by lipid peroxidation.
The Effect of Surgery Type on the Quality of Life in Breast Cancer Patients:...Crimsonpublishers-IGRWH
The Effect of Surgery Type on the Quality of Life in Breast Cancer Patients: A Mini Review by Kefayat Chaman Ara in Investigations in Gynecology Research & Womens Health
ABSTRACT- Background: Esophageal and Lung carcinoma are the leading cause of years of life lost because of cancer and is associated with the highest economic burden relative to other tumor types. Epidemiological studies identify magnesium deficiency as a risk factor for these types of human cancers. The present studies were performed to concerning the contribution of magnesium to tumorigenesis and investigate the concentration of magnesium in esophageal and lung carcinoma.
Aims and Objective: The aim of this study was to compare the serum magnesium levels of patients with carcinoma of lung and esophagus patients and apparently healthy people.
Material and methods: Study group consisted of 50 clinically diagnosed subjects (Biopsy confirmed 25 cases with Esophageal carcinoma and 25 cases with Lung carcinoma). The control group consisted of 50 healthy subjects were included in the study. Venous blood samples of each lung and esophagus cancer were obtained and serum magnesium level was measured by Atomic Absorption Spectrophotometer measurements.
Results: In the study group, we were found mean concentration of serum magnesium was decreased in esophageal (1.40±0.13 mg %) and lung carcinoma (1.23±0.12 mg %) in comparison to controls (2.08 ± 0.45 mg %).
Conclusions: Serum magnesium was found statistically significantly lower in study group when compared with control (P<0.0001).
Key-words- Lung and Esophagus Carcinoma, Magnesium, Atomic absorption spectrophotometer
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.
Sarcopenic obesity is a chronic condition, which is due to progressively aging populations, the increasing incidence of obesity, and lifestyle changes. The increasing prevalence of sarcopenic obesity in elderly has augmented interest in identifying the most effective treatment. This article aims at highlighting potential pathways to muscle impairment in obese individuals, the consequences that joint obesity and muscle impairment may have on health and disability, recent progress in management with attention on lifestyle management and pharmacologic therapy involved in reversing sarcopenic obesity. Recent findings: It has been suggested that a number of disorders affecting metabolism, physical capacity, and quality of life may be attributed to sarcopenic obesity. Excess dietary intake, physical inactivity, low-grade inflammation, insulin resistance and hormonal changes may lead to the development of sarcopenic obesity. Weight loss and exercise independently reverse sarcopenic obesity. Optimum protein intake appears to have beneficial effects on net muscle protein accretion in older adults. Myostatin inhibition causes favourable changes in body composition. Testosterone and growth hormone offer improvements in body composition but the benefits must be weighed against potential risks of therapy. GHRH-analog therapy is effective but further studies are needed in older adults. Summary: Lifestyle changes involving both diet-induced weight loss and regular exercise appear to be the optimal treatment for sarcopenic obesity. It is also advisable to maintain adequate protein intake. Ongoing studies will determine whether pharmacologic therapy such as myostatin inhibitors or GHRH-analogs have a role in the treatment of sarcopenic obesity.
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.
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
Assessment of Muscle and Fat Mass in Type 2 Diabetes Patients By Dual-Energy ...semualkaira
The aim of this study was to assess the quantitative composition of muscle and adipose tissue in type 2 diabetes
mellitus (T2DM) patients on the basis of dual-energy X-ray absorptiometry for the diagnosis of obesity and sarcopenia.
Normal Weight Obesity Is Associated with MetabolicSyndrome a.docxhenrymartin15260
Normal Weight Obesity Is Associated with Metabolic
Syndrome and Insulin Resistance in Young Adults from a
Middle-Income Country
Francilene B. Madeira1, Antônio A. Silva2*, Helma F. Veloso2, Marcelo Z. Goldani3, Gilberto Kac4,
Viviane C. Cardoso5, Heloisa Bettiol5, Marco A. Barbieri5
1 Physical Education Undergraduate Course, State University of Piauı́, Teresina, Brazil, 2 Department of Public Health, Federal University of Maranhão, São Luı́s, Brazil,
3 Department of Pediatrics and Puericulture, Faculty of Medicine, Federal University of Rio Grande do Sul, Porto Alegre, Brazil, 4 Department of Social and Applied
Nutrition, Josué de Castro Nutrition Institute, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil, 5 Department of Puericulture and Pediatrics, Faculty of Medicine of
Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
Abstract
Objective: This population-based birth cohort study examined whether normal weight obesity is associated with metabolic
disorders in young adults in a middle-income country undergoing rapid nutrition transition.
Design and Methods: The sample involved 1,222 males and females from the 1978/79 Ribeirão Preto birth cohort, Brazil,
aged 23–25 years. NWO was defined as body mass index (BMI) within the normal range (18.5–24.9 kg/m2) and the sum of
subscapular and triceps skinfolds above the sex-specific 90th percentiles of the study sample. It was also defined as normal
BMI and % BF (body fat) .23% in men and .30% in women. Insulin resistance (IR), insulin sensitivity and secretion were
based on the Homeostasis Model Assessment (HOMA) model.
Results: In logistic models, after adjusting for age, sex and skin colour, NWO was significantly associated with Metabolic
Syndrome (MS) according to the Joint Interim Statement (JIS) definition (Odds Ratio OR = 6.83; 95% Confidence Interval CI
2.84–16.47). NWO was also associated with HOMA2-IR (OR = 3.81; 95%CI 1.57–9.28), low insulin sensitivity (OR = 3.89; 95%CI
2.39–6.33), and high insulin secretion (OR = 2.17; 95%CI 1.24–3.80). Significant associations between NWO and some
components of the MS were also detected: high waist circumference (OR = 8.46; 95%CI 5.09–14.04), low High Density
Lipoprotein cholesterol (OR = 1.65; 95%CI 1.11–2.47) and high triglyceride levels (OR = 1.93; 95%CI 1.02–3.64). Most
estimates changed little after further adjustment for early and adult life variables.
Conclusions: NWO was associated with MS and IR, suggesting that clinical assessment of excess body fat in normal-BMI
individuals should begin early in life even in middle-income countries.
Citation: Madeira FB, Silva AA, Veloso HF, Goldani MZ, Kac G, et al. (2013) Normal Weight Obesity Is Associated with Metabolic Syndrome and Insulin Resistance
in Young Adults from a Middle-Income Country. PLoS ONE 8(3): e60673. doi:10.1371/journal.pone.0060673
Editor: Reury F.P Bacurau, University of São Paulo, Brazil
Received November 23, 2012; Accepted March 1, 201.
Assess The Effect of Resistance Training Compared To a Weight Loss Diet Progr...IOSR Journals
To evaluate the effect of a Resistance training program (BT) versus weight loss diet (DR) on body composition, insulin sensitivity and cardiovascular risk factors in obese adolescents. Methods: Thirty obese adolescents with a BMI above the 97th percentile participated in a training program and diet for 12 weeks. They were randomized into two groups: a diet group (DR, n = 16) with a caloric restriction of 500 kcal / day and Strength training group (BT, n = 14) for all major muscle groups, three sessions / week with an intensity of 50-80% (1.RM) for 3 months. Anthropometric and biochemical measurements were performed for all of our subjects before and after the intervention program of 12 weeks. Results: Significant variations of body composition parameters were observed in both groups. The decrease of BMI, body weight, fat mass and (WC) for the group (DR) was more important than the group (BT) (p <0.01><0.05><0.05)),><0.05).><0.05) respectively). Conclusion: Strength training improves much more the sensitivity to insulin and cardiovascular risk factors than weight loss diet program. The latter is more effective for weight loss, BMI and body fat in obese adolescent boys.
Dietary Lifestyle, Way of Life Practices and Corpulence: Towards Present Day Science by Alok Raghav, Aditi, Sneha Gupta, Pratibha Singh, Aman Nikhil, Saba Noor and Jamal Ahmad in Examines in Physical Medicine & Rehabilitation
2. Citation: de Menezes MC, Souza Lopes AC, Cunha LP, Jansen AK, dos Santos LC (2012) An Optimal Method for Measuring Body Fat in Overweight
Individuals in Clinical Practice. Endocrinol Metab Synd S2:002. doi:10.4172/2161-1017.S2-002
Page 2 of 5
Endocrinol Metab Synd Obesity consequences & Weight Management ISSN:2161-1017 EMS, an open access journal
evaluators and the choice of prediction equation for body fat estimation
are essential for the accuracy and reproducibility of ST [10].
BIAhasalsobeenwidelyusedintheevaluationofbodycomposition
because it is noninvasive, portable and easy to use [2]. It is based on
the principle of electrical conductivity to estimate body compartments.
For BIA validation, it is important to consider the conditions under
which it is performed, the type of equipment used and the equation
for calculating body composition [10]. Factors like the position of the
individual, alcohol intake, intense physical activity, and the presence
of edema or fluid retention during certain times in the menstrual cycle
and recent ingestion of food can affect accuracy [3].
Sun et al. [11] compared the %BF predicted by BIA and reference
methods like DXA and indicated that the validity of BIA may be
compromised in obese individuals, as they may have changes in
geometry and body fluid balance. However, it is possible to obtain
satisfactory estimates of longitudinal changes in lean mass and body
fat [11]. Horie et al. [2] compared the %BF obtained by BIA and
plethysmography from 109 severely obese individuals and found
a strong accuracy and agreement between the methods with no
significant differences. Equations have been developed to improve the
accuracy of BIA for estimating body composition.
Fewstudiesintheliteraturehaveassessedtheabilityofthesemethods
to measure body fat among overweight individuals, especially among
obese participants. However, the assessment of body composition in
these individuals can assist in identifying risks of co-morbidities and
monitoring their evolution in clinical practice [2]. The present study
is aimed to assess the agreement between body composition obtained
by BIA and ST and their correlation with anthropometric parameters
among overweight individuals in clinical practice.
Materials and Methods
A total of 85 individuals aged 20 or older, who were receiving
individualized nutritional counseling, were recruited from a primary
health care unit in a Brazilian city from August 2007 to July 2009. All
participants were informed of the goals and methods of the research
and gave their informed consent. The protocol was approved by the
ethical committee of the University of Minas Gerais and the City Hall
of Belo Horizonte.
The criteria for referral for nutritional counseling included obesity
(BMI ≥ 30 kg/m2
) in adults [4], overweight (BMI≥27 kg/m2
) in elderly
[12], and hypertension or diabetes mellitus.
The anthropometric measurements included weight, height, WC,
WHR and arm circumference, following the recommendations of
the World Health Organization (WHO) [4] and Lohman [13]. Body
composition was assessed by the sum of four ST measurements (triceps,
biceps, subscapular and suprailiac) and tetrapolar BIA. Measurements
of weight and height were used to calculate BMI, and classification was
assessed differently among adult [4] and elderly [12] participants.
WC was measured at the midpoint between the lower margin of
the last palpable rib and the top of the iliac crest. The hip circumference
was measured around the widest portion of the buttocks, without
compressing the skin. WHR was calculated from the waist and hip
circumference measurements. Guidelines set by the WHO [8] were
used for the classification of WC and WHR.
ST was measured with Lange skinfold calipers to the nearest
1.0 mm and with the same instruments throughout the study. The
measurements were performed by three trained examiners according
to standard procedures [13]. The %BF was estimated from the sum of
the four skinfolds according to the Durnin & Womersley [14] method
with respect to the age and sex of each individual. All anthropometric
measurements (ST, WC, arm and hip circumference) were measured
three times, and the mean was used for analysis.
ST was measured during the first visit. BIA was measured one week
after the first visit in order to instruct patients about the procedures of
the test [15]. If the individual had a significant weight change during
this period, anthropometric measurements and body composition
were performed again.
BIA was performed using tetrapolar, single-frequency bioelectrical
impedance (Biodynamics Corporation, Model 450. Biodynamics
Corporation 3809 Stone Way N, #100
Seattle, WA 98103-8036, USA). The procedures used to measure
body fat by BIA, including the measurement of height and weight
of patients prior to the BIA test, were those recommended by The
European Society for Clinical Nutrition and Metabolism [15].
The operating procedures of the equipment were used in estimating
%BF from BIA. Lohman’s criteria [16] were used in evaluating %BF
from BIA and ST.
Statistical analyses were performed using Statistical Package for
the Social Sciences, version 17.0 (SPSS Inc., Chicago, IL, USA). The
Kolmogorov-Smirnov test was performed to assess the behavior of
normal variables. For a normally distributed variable, results are
displayed as the mean and standard deviation. Non-normal variables
are expressed as medians and ranges of minimums to maximums.
Thepairedt-testorWilcoxonsigned-ranktestswereusedtocompare
the differences in body fat obtained using BIA and ST, depending on the
distribution of the variables. The Bland-Altman models and Pearson or
Spearman correlation coefficient (r) were respectively used to assess the
agreement between BF values from the two methods (BIA and ST) and
to correlate them with the anthropometric parameters BMI, WC and
WHR. Statistical significance was set at p < 0.05 for all tests.
Results
The characteristics of 85 patients are presented in Table 1. The
majority of the individuals were women (91.8%); the mean age of
participants was 51.8 ± 13.0 years (22;85). Approximately 89% of the
adults were obese and 89% of the elderly were overweight, with a mean
BMI of 33.5 ± 5.3 kg/m2
. The mean WC was 97.7 ± 9.9 cm, and 91.5%
were at risk of complications associated with obesity (classification of
the WHO) [8]. The mean WHR was 0.87 ± 0.67, and the proportion of
inadequacy was also high (56.6%).
Estimates of %BF obtained by ST and BIA were 42.8% (12.6-49.2)
and 40.4% (21.0-51.2), respectively (Table 1). This difference was
significant (p<0.001), although the classification of %BF obtained by
each method was similar (p>0.05) (Figure 1).
Correlations between anthropometric indicators and methods of
body composition assessment are presented in Table 2. BMI and WC
were the parameters that best correlated with BIA and ST (r = 0.453 to
0.707, p<0.05).
We identified a significant correlation between estimates of body
fat measured by BIA and ST (r = 0.58, p<0.001) (Figure 2), and a
strong agreement between these methods (Figure 3). The reduction in
differences between the estimates with increasing values of %BF is a
noteworthy result.
3. Citation: de Menezes MC, Souza Lopes AC, Cunha LP, Jansen AK, dos Santos LC (2012) An Optimal Method for Measuring Body Fat in Overweight
Individuals in Clinical Practice. Endocrinol Metab Synd S2:002. doi:10.4172/2161-1017.S2-002
Page 3 of 5
Endocrinol Metab Synd Obesity consequences & Weight Management ISSN:2161-1017 EMS, an open access journal
Discussion
Estimates of %BF by BIA and ST were significantly different but
produced similar classifications. In addition, a significant correlation
and strong agreement between the methods were observed. Of the
anthropometric variables, BMI indicated the greatest correlation
with the body composition assessment methods. This correlation was
positive and significant and was consistent with the findings of other
studies [17,18].
BMI has been the most widely used anthropometric index in
Variables n Values
Age (years) 85 51.8 ± 13.0
Adults (20 – 59 years)
Elderlies (≥ 60 years)
56
29
65.9%
34.1%
Weight (kg) 85 82.6 ± 14.3
BMI (kg/m2
) 85 33.51 ± 5.3
Adults (%)
Normal range 4 7.2
Overweight 2 3.6
Obese class I 26 46.4
Obese class II 18 32.1
Obese class III 6 10.7
Elderlies (%)
Normal range 2 6.9
Underweight 1 3.4
Overweight 26 89.7
Waist circumference (cm) 83 97.7 ± 9.9
Normal (%) 7 8.4
Increased (%) 7 8.4
Substantially increased (%) 69 83.1
Waist-hip ratio 83 0.87 ± 0.67
Normal (%) 36 43.4
Increased (%) 47 56.6
Percentage of body fat (BIA) 79 40.4 (21.0-51.2)
Percentage of body fat (ST) 79 42.8 (12.6-49.2)
BIA- Bioelectrical impedance analysis; ST- skinfold thicknesses; BMI - Body Mass
Index
Note: Loss of three (WC and WHR) and six (BIA and ST) individuals due to patient
non-attendance or absence of the equipment due to technical problems
Table 1: Demographic and anthropometric characteristics of the participants.
0 0 5.1
94.9
2.4 1.2 4.8
91.6
0
10
20
30
40
50
60
70
80
90
100
Risk of
developing
diseases
associated with
malnutrition
Below mean Above mean Risk of
developing
diseases
associated with
obesity
Bioelectrical impedance analysis Skinfold thicknesses
p>0.05
Figure 1: Comparison of the classification of percentage of body fat,
according to Lohman’s criteria (1992), obtained by bioelectrical impedance
analysis and skinfold thickness.
0
10
20
30
40
50
60
0 10 20 30 40 50 60
%BFskinfoldthickness
% BF Bioelectrical impedance analysis
r=0.58; p<0.001
Figure 2: Correlation between percent body fat (% BF) obtained by
bioelectrical impedance analysis and skinfold thickness.
Note: 0.9797 (LA95%=-8.0519; 10.0113). LM – limits of agreement
Differencebetweenbothmethods
Mean difference between the
methods
0,9797 (LA95%=-8,0519; 10,0113)
Note: LA = limits of agreement
Figure 3: Difference in percentage of body fat obtained by bioelectrical
impedance analysis and skinfold thickness.
Anthropometric variables Method r p-Value
Body mass index BIA1
0.707 <0.001
ST2
0.493 <0.001
Waist circumference BIA1
0.605 <0.001
ST2
0.453 <0.001
Waist-hip ratio BIA1
0.017 0.884
ST2
0.160 0.148
Note: Pearson1
and Spearman2
correlation; BIA - Bioelectrical impedance analysis;
ST - Skinfold thickness
Table 2: Correlation between anthropometric variables and the methods of body
composition assessment (BIA and ST).
4. Citation: de Menezes MC, Souza Lopes AC, Cunha LP, Jansen AK, dos Santos LC (2012) An Optimal Method for Measuring Body Fat in Overweight
Individuals in Clinical Practice. Endocrinol Metab Synd S2:002. doi:10.4172/2161-1017.S2-002
Page 4 of 5
Endocrinol Metab Synd Obesity consequences & Weight Management ISSN:2161-1017 EMS, an open access journal
epidemiological studies; however, this method has limitations, as
obesity reflects an excess of body fat and is not simply a measure of
body weight [5,18]. It should be noted that although this research and
other studies have revealed a positive correlation between BMI and the
percentage of total body fat, its use alone is not advisable.
WC correlated moderately and significantly with %BF. Freitas et
al. [19] evaluated the ability of anthropometric indicators to determine
obesity measured by ST and BIA among 685 adults and seniors. As in
this study, BMI was followed by WC as the best anthropometric index
for diagnosing adiposity.
Among the advantages of using WC are its ease of measurement,
low cost and evidence of its superiority compared to BMI in predicting
the risk of chronic diseases [20]. Several studies have demonstrated the
relationship of WC with hypertension, diabetes mellitus and metabolic
syndrome [21-23]. Despite these findings, its use remains controversial
because of the difficulty in establishing cut-points for different age
groups and ethnic populations.
In contrast to BMI and WC, WHR demonstrated a weak and
non-significant correlation with %BF. Similar studies have suggested
that WHR is not a strong indicator of body fat [4,17] and shows weak
correlations with other anthropometric measures like BMI [18,24].
WHR has been more strongly related to pelvic bone size than to body
fat distribution [25].
The median %BF was greater when measured using ST rather
than BIA (p=0.0001), which corroborates others studies [19,26]. For
instance, Freitas et al. [19], using the same techniques of BIA and ST as
the current study, found that the average %BF obtained for women was
greater for ST (35.4 ± 5.9 vs. 33.5 ± 8.2 for BIA, p<0.01).
Although BIA and ST differ significantly from each other, they
indicated significant moderate correlation. Aristizábal et al. [26]
assessed 123 Colombian adults and verified a significant correlation
between bipolar BIA and the sum of four ST measurements (r = 0.8660).
To our knowledge, the differential results for both methods can be
derived from the different assumptions on which they rely. While ST
estimated body density by the sum of skinfold thickness, BIA estimates
total body water and then calculates the fat and lean mass. Similarly, the
overestimation of %BF measured by ST when compared to BIA may be
explained by the protocol of using four skinfold thicknesses to evaluate
only the upper body, unlike the tetrapolar BIA, which considers the
upper and lower limbs [26].
The agreement between the methods was evaluated by a Bland-
Altman model and indicated that the mean differences in %BF between
the methods were small (mean difference = 0.9797). The differences
were well-distributed around the mean difference and were found
mostly in the range of two standard deviations. A strong agreement
was found, especially among the greater values of %BF. Therefore, the
results from both techniques are more similar among individuals with
increased body fat.
Junior et al. [27] compared %BF measurements from DXA with
those from BIA and ST (the sum of four skinfold thicknesses, protocol
of Durnin & Womersley [14]) and found no significant differences
between them. However, there was no agreement between the estimates
of body composition obtained by BIA or ST in relation to DXA. In
contrast, Kamimura et al. [28] found strong agreement between ST
(protocol proposed by Durnin & Womersley [14]) [0.47 ± 2.8 (-5.0 to
6.0) kg] and BIA [-0.39 ± 3.3 (-6.9 to 6.1) kg] with respect to DXA
among all patients according to Bland-Altman analysis.
The results of this study indicate that BIA has stronger correlations
with the anthropometric indices BMI and WC than with ST. Similarly,
in a study by Freitas et al. [19], the strongest correlation was found
betweenBMIandBIA(r=0.82forwomenandr=0.90formen,p<0.05),
except for women older than 40 years, for whom the correlation of WC
and BIA was greater (r = 0.87).
It should be noted that BIA classified a greater proportion of
individuals as being at ‘’risk of developing diseases associated with
obesity’’, suggesting a potential sensitivity of BIA in assessing disease
risk or a potential tendency to overestimate risk. Sun et al. [11] found
that BIA provides increased values of %BF among individuals classified
as lean by DXA; among these, the %BF was overestimated at 3.03% in
men and 4.40% in women.
Our study demonstrates that the strongest correlation was
observed between BMI and WC (r = 0.803, p<0.001). BMI correlated
significantlywiththevariablesofbodycompositionandanthropometric
measurements, excluding WHR. Similarly, a study by Sampaio et al.
[24] among 634 older adults found a stronger correlation between BMI
and WC (r = 0.86-0.93), compared to WHR (r = 0.34-0.66), in both age
groups and both sexes.
In the present study, %BF obtained by BIA was based on the
equation provided by the equipment because adopting an equation
that has been adapted to the analyzed population is still a limitation of
this method [29]. The difficulties related to the validation of equations,
considering populations with different age groups, ethnicities, genders,
heights, and other characteristics, resulted in an excess of equations,
which can confuse rather than assist in the interpretation of results. In a
multiethnic population (n=12,000) [30] in which the %BF measured by
BIA was based on 51 different predictive equations, none of these was
consistently better than the simpler alternative of BMI.
This study provided important information about which method
should be used in clinical practice, especially in the assessment of
overweight individuals. There was strong agreement and significant
correlation between the methods used to assess body composition.
BIA indicated greater correlations with the anthropometric indices
BMI and WC than with ST. Furthermore, BIA presents an additional
advantage of minimal intra- and inter-observer variability [29].
Although BIA is a method that depends on the individual, adherence to
the protocol recommendations to ensure that the technique is applied
under appropriate conditions can be strengthened through adequate
participant instruction. BIA and ST appear to be equivalent methods
among subjects with greater adiposity, considering that the amount of
body fat estimated by BIA and ST was similar in these individuals.
However, these methods have some limitations and should
not be the only ones applied to individuals and populations. Other
indicators of nutritional status, like BMI and WC, which indicated
strong correlations with body fat in this study, should also be used. We
have highlighted the importance of concomitant assessments of body
composition with total and abdominal obesity. These measures have
an important application in health services and populations because
they are reliable, easy to use and noninvasive. Even so, the difficulty in
determining a specific method to be used remains due to the variability
of the results obtained by different studies. This lack of comparability
is further hampered by differences in population profiles and existing
ways of measuring body composition by BIA (equipment, equations,
polarity, frequency, protocols and cut-off values, hydration status of
individuals) and ST (number of skinfold thickness measurements,
equations, protocols and cut-off values).
5. Citation: de Menezes MC, Souza Lopes AC, Cunha LP, Jansen AK, dos Santos LC (2012) An Optimal Method for Measuring Body Fat in Overweight
Individuals in Clinical Practice. Endocrinol Metab Synd S2:002. doi:10.4172/2161-1017.S2-002
Page 5 of 5
Endocrinol Metab Synd Obesity consequences & Weight Management ISSN:2161-1017 EMS, an open access journal
The difficulty in determining the amount or proportion of body fat
in obese individuals is well recognized. Most current methods used in
this population are limited, either by their inability to accommodate
the large physical size of these subjects, their inaccuracy in assessing
extremely obese subjects or their tendency to produce discomfort to
the subjects evaluated. Recently, plethysmography has been validated
as a reference method for assessing body composition in severely obese
individuals; however, its high cost limits its use in clinical practice [2].
Given that the current health profile of populations is characterized
by a high prevalence of overweight, especially among women, this study
is an important investigation into the applicability of the available
methods for body composition assessment in clinical practice.
References
1. World Health Organization (2006) Obesity and overweight: What are overweight
and obesity? Geneva: World Health Organization.
2. Horie LM, Barbosa-Silva MC, Torrinhas RS, de Mello MT, Cecconello I, et al.
(2008) New body fat prediction equations for severely obese patients. Clin Nutr
27: 350-356.
3. Rezende F, Rosado L, Franceschinni S, Rosado G, Ribeiro R, et al. (2007)
Critical revision of the available methods for evaluate the body composition in
population-based and clinical studies. Arch Latinoam Nutr 57: 327-334.
4. World Health Organization (1995) Physical status: the use and interpretation of
anthropometry. World Health Organ Tech Rep Ser 854: 1-452.
5. Akpinar E, Bashan I, Bozdemir N, Saatci E (2007) Which is the best
anthropometric technique to identify obesity: body mass index, waist
circumference or waist-hip ratio? Coll Antropol 31: 387-393.
6. Frankenfield DS, Rowe WA, Cooney, RN, Smith JS, Becker D (2001) Limits
of body mass index to detect obesity and predict body composition. Nutrition
17: 26-30.
7. Huxley R, Mendis S, Zheleznyakov E, Reddy S, Chan J (2010) Body mass
index, waist circumference and waist : hip ratio as predictors of cardiovascular
risk – a review of the literature. Eur J Clin Nutr 64: 16-22.
8. World Health Organization (2011) Waist Circumference and Waist-Hip Ratio:
report of a WHO Expert Consultation Geneva 8–11.
9. Ketel IJ, Volman MN, Seidell JC, Stehouwer CD, Twisk JW, et al. (2007)
Superiority of skinfold measurements and waist over waist-to-hip ratio for
determination of body fat distribution in a population-based cohort of Caucasian
Dutch adults. Eur J Endocrinol 156: 655-661.
10. Deminice R, Rosa FT (2009) Pregas cutâneas vs impedância bioelétrica na
avaliação da composição corporal de atletas: uma revisão crítica. Rev Bras
Cineantropom Desempenho Hum 11: 334-340.
11. Sun G, French CR, Martin GR, Younghusband B, Green RC, et al. (2005)
Comparison of multifrequency bioelectrical impedance analysis with dual-
energy X-ray absorptiometry for assessment of percentage body fat in a large,
healthy population. Am J Clin Nutr 81: 74–78.
12. Nutrition Screening Initiative (1994) Incorporating Nutrition Screening and
Interventions into Medical Practice. A monograph for phycicians Washington
(DC): The American Dietetic Association.
13. Lohman TG, Roche AF, Martorell R (1992) Anthropometric standardization
reference manual. Abridged Edition Human Kinetics Books Champaign Illinois.
14. Durning JV, Womersley I (1974) Body fat assessed from total body density ad
its estimation from skinfold thickness: measurement on 481 men and women
aged from 16 to 72 years. Br J Nutr 32: 77-97.
15. Kyle UG, Bosaeusb I, Lorenzoc AD, Deurenbergd P, Eliae M, et al. (2004)
Bioelectrical impedance analysis - part I: review of principles and methods. Clin
Nutr 23: 1226–1243.
16. Lohman TG (1992) Advances in body composition assessment. Human
Kinetics.
17. Giugliano R, Melo ALP (2004) Diagnosis of overweight and obesity in
schoolchildren: utilization of the body mass index international standard. J
Pediatr 80: 129-134.
18. 18. Faria ER, Franceschini SC, Peluzio MC, Sant’Ana LF, Priore SE (2009)
Correlation between metabolic and body composition variables in female
adolescents. Arq Bras Cardiol 93: 119-127.
19. Freitas SN, Caiaffa WT, César CC, Cândido AP, Faria VA, et al. (2007) A
comparative study of methods for diagnosis of obesity in an urban mixed-race
population in Minas Gerais, Brazil. Public Health Nutr 10: 883-890.
20. Sampei MA, Sigulem DM (2009) Field methods in the evaluation of obesity in
children and adolescents. Rev Bras Saude Mater Infant 9: 21-29.
21. Bombelli M, Facchetti R, Sega R, Carugo S, Fodri D, et al. (2011) Impact of
body mass index and waist circumference on the long-term risk of diabetes
mellitus, hypertension, and cardiac organ damage. Hypertension 58: 1029-
1035.
22. Sargeant LA, Bennett FI, Forrester T, Cooper RS, Wilks RJ (2002) Predicting
incident diabetes in Jamaica: the role of anthropometry. Obes Res 10: 792-798.
23. Katzmarzyk PT, Janssen I, Ross R, Church TS, Blair SN (2006) The importance
of waist circumference in the definition of metabolic syndrome: Prospective
analyses of mortality in men. Diabetes Care 29: 404-449.
24. Sampaio LR, Figueiredo VC (2005) Correlation between body mass index and
body fat distribution anthropometric indices in adults and the elderly. Rev Nutr
18: 53-61.
25. Oliveira CL, Mello MT, Cintra IP, Fisberg M (2004) Obesity and metabolic
syndrome in infancy and adolescence. Rev Nutr 17: 23-45.
26. Aristizabal JC, Restrepo MT, Estrada A (2007) Assessment of body composition
in healthy adults by anthropometry and bioelectrical impedance. Biomedica 27:
216-224.
27. Junior IFF, Paiva SAR, Godoy I, Santos SMS, Campana AO (2005)
Comparative analysis of methods for assessing body composition in healthy
men and in patients with chronic obstructive pulmonary disease: anthropometry,
bioelectrical impedance and X-ray absorptiometry dual-energy. ALAN 55: 124-
131.
28. Kamimura MA, Avesani CM, Cendoroglo M, Canziani ME, Draibe SA, et al.
(2003) Comparison of skinfold thicknesses and bioelectrical impedance
analysis with dual-energy X-ray absorptiometry for the assessment of body fat
in patients on long-term haemodialysis therapy. Nephrol Dial Transplant 18:
101-105.
29. Kyle UG, Bosaeus I, Lorenzoc AD, Deurenbergd P, Elia M, et al. (2004)
Bioelectrical impedance analysis - part II: utilization in clinical practice. Clin
Nutr 23: 1430–1453.
30. Willett K, Jiang R, Lenart E, Spiegelman D, Willett W (2006) Comparison
of bioelectrical impedance and BMI in predicting obesity-related medical
conditions. Obesity 14: 480–490.
Submit your next manuscript and get advantages of OMICS
Group submissions
Unique features:
• User friendly/feasible website-translation of your paper to 50 world’s leading languages
• Audio Version of published paper
• Digital articles to share and explore
Special features:
• 200 Open Access Journals
• 15,000 editorial team
• 21 days rapid review process
• Quality and quick editorial, review and publication processing
• Indexing at PubMed (partial), Scopus, DOAJ, EBSCO, Index Copernicus and Google Scholar etc
• Sharing Option: Social Networking Enabled
• Authors, Reviewers and Editors rewarded with online Scientific Credits
• Better discount for your subsequent articles
Submit your manuscript at: http://www.omicsonline.org/submission/
This article was originally published in a special issue, Obesity consequences
& Weight Management handled by Editor(s). Dr. Weihong Pan, Pennington
Biomedical Research Center, USA