|Year : 2012 | Volume
| Issue : 3 | Page : 184-188
Assessment of body composition and body mass index of adolescent school children in Imphal-West district, Manipur
Bishwalata Rajkumari1, Brogen S Akoijam2, Joy Singh Akoijam3, Usharani Longjam1
1 Department of Community Medicine, Jawaharlal Nehru Institute of Medical Sciences, Porompat, Imphal, India
2 Department of Physical Medicine and Rehabilitation, Regional Institute of Medical Sciences, Imphal, India
3 Department of Physical Medicine and Rehabilitation, Jawaharlal Nehru Institute of Medical Sciences, Porompat; Regional Institute of Medical Sciences, Imphal, India
|Date of Web Publication||10-Jun-2013|
Assistant Professor, Department of Community Medicine, Jawaharlal Nehru Institute of Medical Sciences, Porompat, Imphal, Manipur - 795 010
Source of Support: None, Conflict of Interest: None
DOI: 10.4103/0972-4958 .113248
Background : Childhood obesity is a precursor for later disease risk and it is important to obtain a better understanding of the body composition and body mass index (BMI) in children. Objective: To determine the body composition and its relation with BMI of adolescents. Materials and Methods: A cross sectional study of 3356 school children in age group 12 to 19 years residing in Imphal-West District, Manipur was conducted during May 2005 to May 2008. BMI and Body composition were determined using the TANITA Body Composition Analyzer (TBF-300, JAPAN). Results: The mean (Standard Deviation) BMI among boys and girls were 18.7 (2.6) and 19.2 (2.8) respectively and the difference was statistically significant (P = 0.000). Multiple linear regression analysis shows that BMI was significantly associated with waist circumference, weight, fat%, total body water (P = 0.000) and fat free mass (P = 0.041) among the boys and inversely associated with height, hip circumference and waist-hip ratio (WHR) (P = 0.000). Among girls, BMI was positively associated with hip circumference (P = 0.035), weight (P = 0.000), fat% (P = 0.000) and total body water (P = 0.000) and inversely associated with height (P = 0.04). Conclusion: Though fat percentage was found to be significantly correlated with BMI, it could explain little of the variation in BMI.
Keywords: Adolescents, Body mass index, Body composition, Fat mass
|How to cite this article:|
Rajkumari B, Akoijam BS, Akoijam JS, Longjam U. Assessment of body composition and body mass index of adolescent school children in Imphal-West district, Manipur. J Med Soc 2012;26:184-8
|How to cite this URL:|
Rajkumari B, Akoijam BS, Akoijam JS, Longjam U. Assessment of body composition and body mass index of adolescent school children in Imphal-West district, Manipur. J Med Soc [serial online] 2012 [cited 2020 Oct 30];26:184-8. Available from: https://www.jmedsoc.org/text.asp?2012/26/3/184/113248
| Introduction|| |
Excess bodyweight is the sixth most important risk factor contributing to the burden of diseases worldwide. The International Obesity Task Force (IOTF) estimates at present 1.1 billion adults overweight, including 312 million who are obese. With the new Asian BMI criterion of overweight at a lower cut-off 23.0 kg/m 2 , the number is even higher (1.7 billion). 
Many adult diseases have their origin during childhood, and excessive weight gain is a precursor to a wide variety of physiologic aberrations.  Adolescence is a decisive period in human life with multiple changes that take place between childhood and adulthood and when body composition changes dramatically with differential changes between boys and girls. The definition of excess body fat is somewhat arbitrary and there is no consensus about fat percentage cut-off for obesity in adolescents. 
BMI is the parameter most frequently used for the screening of excess body fat because it is easy to determine and it tends to correlate well with body fat. In children and adolescents, based on BMI centile curves, IOTF - BMI cut-off points have been recently proposed for each half-year of age, which corresponds to the adult BMI values of 25 and 30 kg/m 2 at the age of 18 years.  BMI does not distinguish between weight associated with muscle weight and weight associated with fat. At any particular BMI, body composition varies greatly in children depending on gender, age, maturity, race, height, and body fat distribution. The extent to which BMI percentile changes may or may not reflect corresponding changes in body fatness (or leanness) in children is not known. 
Information with precise measurement of body composition among children is lacking in our country especially in the north-east region. However, given the relationship between childhood obesity and later disease risks, it is important to obtain a better understanding of the body composition. The present study was planned to determine the body composition and its relation with BMI among adolescents in the north-eastern state Manipur of India.
| Materials and Methods|| |
A total of 3356 adolescents consisting of 1469 boys and 1887 girls studying in 8 th to 12 th standards in schools located in Imphal-West District of Manipur state in India participated in this cross-sectional study. Students with gross bony deformity, acute diarrhea, on long term steroids therapy and absentees were excluded. Sample size was calculated based on a prevalence of 11% obesity,  as one of the objectives of the study was to determine prevalence of obesity and overweight. With a precision of 10% at 5% significance level using the formula for single proportion, a sample size of 3236 was calculated that was rounded off to 3300. First, we purposively selected all three girls-only and all two boys-only schools, so as to have similar number of boys and girls at the end. From the remaining 28 co-education schools in the district, seven were selected by simple random method. Based on the information on the strength of students in the schools collected earlier, the sample size was expected to be met when these 12 schools were covered. There were five government schools and seven private schools.
The study instruments consisted of a structured questionnaire containing characteristics of the respondents, an Anthropometer for height measurement, a non stretchable measuring tape for waist-hip measurement and the TANITA Body Composition Analyser (TBF-300, JAPAN) for measuring body composition.
The TANITA Body Composition Analyzer is a widely used method for estimating body composition which uses bioelectrical impedance and is a relatively simple, quick and non-invasive procedure, which gives reliable and reproducible measurements of body composition with minimal intra - and inter-observer variation. ,,
Height, weight, waist and hip measurement were carried out following the guidelines given in 'The use and interpretation of anthropometry, Report of a WHO Expert Committee'.  All body parameters were recorded with the Body Composition Analyzer.
Data were analyzed using SPSS version 11.5. Descriptive statistics were used and Pearson correlation coefficients were used to assess univariate association between BMI and body parameters. Multiple linear regression analysis was performed using BMI as dependent variable and the parameters like fat%, fat mass, fat free mass (FFM), total body water (TBW), waist, hip, weight, height, waist hip ratio (WHR) and age as the independent variables. A probability value of < 0.05 was considered to indicate statistical significance.
Approval of the Committee for Research and Advanced Studies of Medical Sciences, Regional Institute of Medical Sciences was obtained. Permission of the school authority and verbal consent and assent was sought from the student participants. Individual data with identifiers were kept confidential.
| Results|| |
Of the 3356 students enrolled in the study, males constituted 44% (1469) and females 56% (1887). The age of the students ranged from 12 to 19 years with a median age of 15 years and inter-quartile range of 14-16.
[Table 1] shows the body characteristics of the boys by age showing the median and inter-quartile range of each characteristic. Generally, there was evidence of increase in bodyweight, height, hip circumference, waist circumference, TBW, FFM, fat mass and fat percentage with increase in age. In girls, in general, there was an increasing trend till age 16 years in weight, height and hip circumference [Table 2].
|Table 1: Body characteristics of study participants (boys) by age showing median with inter-quartile range|
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|Table 2: Body characteristics of study participants (girls) by age showing median with inter-quartile range|
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[Table 3] gives the comparison of body parameters between the boys and the girls.
In the univariate analysis, BMI was found to be significantly correlated with fat% (r = 0.907, P = 0.000; r = 0.621, P = 0.000) in girls and boys respectively. BMI was also significantly correlated with other body parameters like fat mass (r = 0.928, P = 0.000 in girls, r = 0.779, P = 0.000 in boys), weight (r = 0.871, P = 0.000 in girls, r = 0.860, P = 0.000 in boys), TBW (r = 0.513, P = 0.000 in girls and r = 0.659, P = 0.000 in boys) etc., Age was also significantly correlated with BMI in the univariate analysis (r = 0.164, P = 0.000 in girls, r = 0.285, P = 0.000 in boys) but in the multivariate analysis this association was no longer seen. Regression analysis of body parameters with BMI as dependent variable among the boys is shown in [Table 4]. BMI was significantly associated with waist circumference, weight, fat%, TBW (P = 0.000) and FFM (P = 0.041) among the boys and inversely associated with height, hip circumference and WHR (P = 0.000). Among the boys, 97% of the variation in BMI could be explained by the variables in the model (R 2 = 0.976, P = 0.000).
|Table 4: Unstandardized and standardized regression coefficients (β ) and standard errors of regression analysis of body parameters with BMI in the study participants (boys)|
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Among girls, BMI was positively associated with hip circumference (P = 0.035), weight (P = 0.000), fat % (P = 0.000) and TBW (P = 0.000) and inversely associated with height (P = 0.040). Among the girls, 96% of the variation in BMI could be explained by the fitted variables (R 2 = 0.969, P = 0.000) [Table 5].
|Table 5: Unstandardized and standardized regression coefficients (β ) and standard errors of regression analysis of body parameters with BMI in the study participants (girls)|
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| Discussion|| |
This study was conducted in a notably large sample of adolescents and is the first study of its kind in the state giving an insight to the body composition of the adolescents. Girls have a higher fat% as compared to boys; this could be due to differences in body fat determined genetically and the level of physical activity. Tyrell and co-workers also reported similar findings. 
The increase in body weight, height, hip circumference, waist circumference, TBW, FFM, fat mass and fat % with increase in age seen especially among the boys could be due to the rapid physical growth taking place during the adolescent period. , Among girls, this increase is seen only up to age of 16 years because by this age girls are more likely to become conscious of their body shape and tend to regulate their diet. Moreover, girls attend puberty at an earlier age leading to earlier growth spurt than boys. , The fat% for boys in this study was lower than the ideal as specified by Quinn.  It was also lower than the mean value 17.8 ± 3.4% among 18 to 25 years old Indian males reported by Sathya Prabha.  Similarly in girls, the range was lower than the one specified by Quinn. This could indicate that adolescents in Manipur are having a leaner body structure with less body fat than the population reported by the above studies.
BMI was found to be significantly correlated with the body parameters measured. Maynard and colleagues in their analysis of the data from the Fels Longitudinal Study also showed a significantly high correlation between BMI and body composition variables.  Similar results were reported by other authors. , Out of the total variance in the BMI, 97% in boys and 96% in girls could be explained by the variables in the models. In this study, weight is the variable that can explain most of the variation in BMI, but fat mass is not though it contributes to weight. The use of BMI to identify children with excess adiposity during the pubertal development has an important limitation; it has been shown that BMI increases in adolescents from both sexes are primarily determined by increases in fat-free mass rather than in body fat compartment.  As suggested by Widhalm and colleagues,  BMI may be used to identify obesity for epidemiological research purposes but not for monitoring of individual treatment of obesity. We also acknowledge that our findings need to be confirmed with the use of other better methods.
Generalization to other school children in the district can be considered as the study sample was large, the schools were selected randomly and there is a general belief that the characteristics of the students in the district are more or less similar.
| Conclusion|| |
Our study population had a leaner body with less fat percentage. Most of the body parameters were correlated to BMI. Though fat % was found to be significantly correlated with BMI, it could explain little of the variation in BMI.
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[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]