|Year : 2018 | Volume
| Issue : 4 | Page : 277-281
Body mass index and body fat percentage in assessing obesity: An analytical study among the adolescents of Dibrugarh, Assam
Dimpymoni Saikia1, Sultana Jesmin Ahmed2, Hiranya Saikia3, Ratna Sarma4
1 Demonstrator, Department of Community Medicine, Jorhat Medical College, Jorhat, Assam, India
2 Associate Professor, Department of Community Medicine, Assam Medical College, Dibrugarh, Assam, India
3 Senior Lecturer, Statistics, Department of Community Medicine, Assam Medical College, Dibrugarh, Assam, India
4 Professor, Department of Community Medicine, Gauhati Medical College, Guwahati, Assam, India
|Date of Web Publication||11-Dec-2018|
Dr. Dimpymoni Saikia
Department of Community Medicine, Jorhat Medical College, Jorhat, Assam
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: Body mass index (BMI) is one of the most commonly used indices to measure the weight status of an individual. However, it takes only height and weight of individual into account. The relative body composition can be calculated regardless of height and weight by body fat percentage (BF%). Objectives: The objectives of the study are (1) To assess the prevalence of obesity using BMI and BF% among early adolescents studying in schools of Dibrugarh. (2) To assess the relationship between BMI and BF%. Methods: A cross-sectional analytical study was conducted among 1200 school going adolescents of 10–14 years in Dibrugarh town for 1 year. Weight status was assessed using the World Health Organization-2007 reference for BMI and the McCarthy's body fat reference. Data were presented using percentages and mean with standard deviation. The correlation between the anthropometric variables was calculated using Pearson's correlation coefficient. Kappa statistics was used to analyze the agreement. Results: Total participants included in the analysis were 1096 with a response rate of 91.3%. The prevalence of overweight and obesity by BMI was 20.9% and 10.2%, respectively. According to BF%, overweight was present in 16.4% participants and 10.9% were obese. Of the 625 normal weight participants (according to their BMI), 9.0% were overweight and 1% were obese under BF% criteria. Again, of 682 participants who were normal by BF%, 15.2% were categorized as obese by BMI criteria. BMI and BF% had a significant high positive correlation (r = 0.70 and P < 0.001). The measurement of agreement by Kappa statistics was 0.621 which was significant (P < 0.001). Conclusions: BMI and BF% positively correlate with each other. BMI accompanied by BF% in the studies might give a better picture of the adiposity of an adolescent.
Keywords: Bioelectric impedance analysis, body fat percentage, body mass index, obesity
|How to cite this article:|
Saikia D, Ahmed SJ, Saikia H, Sarma R. Body mass index and body fat percentage in assessing obesity: An analytical study among the adolescents of Dibrugarh, Assam. Indian J Public Health 2018;62:277-81
|How to cite this URL:|
Saikia D, Ahmed SJ, Saikia H, Sarma R. Body mass index and body fat percentage in assessing obesity: An analytical study among the adolescents of Dibrugarh, Assam. Indian J Public Health [serial online] 2018 [cited 2020 May 31];62:277-81. Available from: http://www.ijph.in/text.asp?2018/62/4/277/247223
| Introduction|| |
According to the World Health Organization (WHO) overweight and obesity are abnormal or excessive fat accumulation that may impair health. In the past, when food was scarce obesity was related to wealth and well-being. However, even then the evil of overweight and obesity was recognized by the scholars of the past. In the 6th century, BC the Indian surgeon Sushruta related obesity to diabetes and heart disorders. He recommended physical activity to cure it and its side effects. Hippocrates wrote “Corpulence is not a disease itself, but a harbinger of others.” Now, it is regarded as a forerunner of many life-threatening diseases. The basic anomaly behind obesity is the mismatch between energy intake and energy expenditure. Obesity may be due to an enlargement of fat cell size, known as hypertrophic obesity or an increase in fat cell number called hyperplastic obesity or a combination of both. When fat cells have reached their maximum size and energy intake continues to exceed energy expenditure, fat cells increase in number. When an obese person loses weight the size of fat cells decreases, but the number remains the same threatening future weight gain. While increase in weight correlates to increase in body mass index (BMI), the increase in weight may be due to various reasons such as increase in the muscle mass, increase in adiposity or the bone density. BMI alone may not be sufficient enough to determine the risks associated with increased adiposity because it does not distinguish between increased mass in the form of fat, lean tissue or bone, and hence significant misclassification occurs. Pathology associated with obesity is due to the excess fat mass, so it is an ideal monitoring tool to assess adiposity. Body fat percentage (BF%) by bioelectrical impedance analysis (BIA) is an indirect method of determining the adiposity of the body. It measures the impedance or opposition to the flow of a very small electric current as it passes through the body distinguishing lean tissue mass (which acts as a conductor) and fat mass (which acts as an insulator), through changes in voltage.,
There are several techniques to assess BF% which include underwater weighing (densitometry), air-displacement plethysmography, dual-energy X-ray absorptiometry (DEXA), isotope dilution, BIA, computerized tomography (CT), and magnetic resonance imaging (MRI). However, densitometry, plethysmography, DEXA, and MRI are expensive, inconvenient for the participant, exposure to low dose radiation in case of CT scan and DEXA and comparatively large specialized equipment making their use in large epidemiological studies limited. BIA, by contrast, is relatively simple, and noninvasive which gives reliable measurements of body composition with minimal intra- and inter-observer variability., The results of bio-electric impedance are available immediately and reproducible on repeated measurements., Cross-validation analysis done to estimate body composition by using multiple frequencies (10, 50, 100 Hz) of BIA and compared with those determined by isotope dilution had shown that the prediction equation for BIA was reproducible and valid. Hand-to-foot method of BIA was also found to have high correlation (r = 0.96) with hydrodensiometry.
Globally, about 200 million school children are overweight, of which 40–50 million are obese. Increase in the prevalence of overweight and obesity among children and adolescents globally has become a major public health concern. Meta-analysis on studies related to obesity in adolescents in India showed that the pooled estimates of overweight and obesity ranged from 2%–6% in low prevalence group, 11%–18% in intermediate to 23%–36% in high prevalence group.
Children and adolescents who are obese are likely to be obese during their later life. Moreover, they are more at risk for noncommunicable diseases such as cardiovascular diseases, type 2 diabetes, stroke, cancers, and osteoarthritis. Hence, intervention at the early stage can prevent complications at later life.
Although there are many studies related to the determination of overweight and obesity in Indian adolescents using BMI and other anthropometric measures but studies related to the assessment of obesity among Indian adolescents utilizing both BMI and BF% are very few.
A 10–14 years being school-age children, school becomes an easy access source to reach the children in the majority of the time. Hence, the study was taken up in schools of Dibrugarh.
With this thought, the following study was undertaken to determine the prevalence of overweight and obesity by both BMI and BF% among the early adolescents studying the schools of Dibrugarh town and to assess the relationship between BMI and BF%.
| Materials and Methods|| |
A school-based cross-sectional analytical study was conducted among 10–14 years adolescents studying in the schools of Dibrugarh town. The study was done for 1 year from May 2015 to April 2016.
Taking the prevalence of obesity to be 14.6% with a relative precision of 15% and 95% level of confidence the required sample size is 1040. Taking 10% nonresponse, the final sample size was calculated and rounded off to be 1200.
All the students of 10–14 years studying in Classes V, VI, VII, VIII, and IX of the schools of Dibrugarh town.
- The students who were unwilling to participate in the study were excluded
- Any student having diarrhea or vomiting and was in any state of dehydration at the time of conducting the study was excluded.
Exclusion criteria during the selection of schools
Schools with <20 students in each class or where the annual enrolment per class per year is <20 and schools with only Classes IX and X were excluded from the study.
Stratified sampling technique was used to select the study participants. First, the schools of Dibrugarh town were divided into two categories: Government School (divided into lower primary [LP] and high school) and Private School. Then, the sample size was equally allocated in each of the categories, i.e., 600 each. For the administrative convenience of the study, schools having <20 numbers of students in each class and schools with only Standard- IX and X were excluded from the study. Since the study is a part of academic curriculum with a limited amount of time in our hand, we decided to include only six schools from each category, i.e., six private schools, six government high schools, and six LP Government schools. LP schools contain Class V and the study required students of age 10 years, so to obtain data for that particular age group LP schools were also included in the study. The selection of these schools was done by simple random sampling. Then, we selected equal number of students (i.e., 20) from each of the classes - Class V–IX using simple random sampling technique which is elaborated in [Figure 1].
Prior permission was obtained from the Headmaster/Headmistress/Principal of the schools. A written consent was taken from the parents and assent was taken from the students. The contents of the schedule were validated, and the questions were in both English and local language (Assamese) which translated and retranslated by us and literature experts. All the questions were explained to the students selected for participating in the study, and total confidentiality was assured. Each of the students was interviewed, and the anthropometric measurements were taken. The study also contained a questionnaire (to obtain information on socioeconomic and certain dietary factors), which was sent with the students to be filled up by them with the help of their parents or guardians. The content of the questionnaire is beyond the sphere of the present article as the present study is a part of a larger study so the results of this section have been excluded. Participants who did not return their questionnaires after three subsequent visits were included under “nonresponse.”
The anthropometric measurements included height and weight. Height was measured to the nearest 0.1 cm using stadiometer. Weight was measured to the nearest 0.1 kg using digital weighing machine. BMI was calculated using the equation BMI = weight (kg)/square of height (m2). To determine the weight status of the study, participants' age- and sex-specific WHO 2007 reference for BMI for 5–19-year-old children (z-score) were used. The students were categorized as severe thinness, thinness, normal, overweight, and obese.
To determine the BF% BIA was used. The machine used was Omron Body Composition Monitor – HBF-358-BW. The instrument is calibrated to an accuracy of 5%–50% with an increment of 0.1% for BF% calculated by the manufacturing company (according to the instruction manual of the company). The Categorization of BF% was done using McCarthy percentile values of BF% of boys and girls are to be used – underfat, normal, overweight, and obese.
Data were represented using percentages, mean, and standard deviation. t-test was done to see the difference in means. To analyze the correlation between the measurement variables Pearson's correlation coefficient was calculated. Kappa statistics was used to analyze the agreement. SPSS version 20 (IBM SPSS Statistics Version 20, IBM Corp., Armonk, New York, USA) was used to analyze the data.
Ethical clearance was obtained from the Institutional Ethics Committee (Human) of Assam Medical College and Hospital, Dibrugarh.
| Results|| |
The study initially included equal number of participants from government (600) and private schools (600). However, completed questionnaire was obtained from 527 (86.8%) participants from government schools and 569 (94.8%) participants from private schools. Therefore, the total response rate of the study was 91.3% and analysis of the study was based on those 1096 participants. Of 1096 participants, 50.6% were boys (555). The mean age of the participants was 11.9 + 1.3 years. The mean BMI and the mean BF% are were both found to be significantly higher among girls than among boys as shown in [Table 1].
|Table 1: Mean body mass index, mean body fat percentage of the study participants (n=1096)|
Click here to view
The prevalence of overweight and obesity by BMI was found to be 20.9% and 10.2%, respectively while according to BF% was 16.4% and 10.9% respectively as depicted in [Table 2]. The difference in the means of BMI and BF% among boys and girls were found to be statistically significant.
|Table 2: Prevalence of overweight and obesity of the study participants (n=1096)|
Click here to view
Among the participants, who were overweight according to their BMI, 39.3% fell under normal category of BFs% while 23.1% were under obese category of BF%. Among the participants, who were obese according to their BMI, 15.2% fell under normal category of BF% while 33.0% were under overweight category of BF% as shown in [Table 3].
|Table 3: Distribution of study participants according to body mass index and body fat percentage|
Click here to view
The correlation between BMI and BF% was statistically significant with r = 0.70. [Figure 2] presents the comparison of BMI with BF%.
|Figure 2: Correlation of body mass index with body fat percentage (r = 0.70, P < 0.001).|
Click here to view
Categorizing the total participants according to the presence and absence of overweight and obesity the measure of agreement (Kappa) between BMI and BF% by BIA in detecting overweight-obesity was found to be 0.621 and was statistically significant (P < 0.001).
| Discussion|| |
Due to the various adverse effects of adolescent obesity, it has been recognized as a public health priority. In the present study, according to the WHO 2007 reference criteria for BMI for age and sex almost one-third of the study participants were found to be overweight and obese (30.1%). Whereas according to the BF% criteria overweight and obesity comprised of 27.3% study participants showing a higher estimation of overweight and obesity by BMI criteria. Nevertheless, taking both the criteria into consideration the prevalence of overweight and obesity is quite high. In a study done by Antal et al. among Hungarian school children aged 7–14 years in 2005 the prevalence of overweight and obesity by BMI criteria was 25.5% in boys and 25.9% in girls, whereas by BF% criteria, it was 17.9% for boys and 12.8% for girls.
In the present study, of the participants who were categorized as overweight according to their BMI, 39.3% fell under normal category of BFs% while 23.1% were under obese category of BF%. Among the participants who were obese according to their BMI, 15.2% fell under normal category of BF% while 33.0% were under overweight category of BF%. In the study done by Antal et al. 49% of the boys and 28% of the girls categorized as overweight by BMI were obese according to their BF%.
The correlation of BMI with BF% was found to be strongly positive (r = 0.70, P < 0.001) in the present study. This finding of ours is somewhat similar to the findings of the study by Jelena et al. done in Serbian Republic where they found very strong correlation between BMI and BF% among girls (r = 0.975) and boys (0.752).
A substantial agreement between BMI and BF% by BIA with kappa value of 0.621 was found in the present study. Sampei et al. in Japan found the Kappa agreement to be 0.49 between BMI and BIA for fat evaluation among adolescent. However, point to be noted is that in the present study out of the 625 normal weight participants (according to their BMI), 9.0% were overweight and 1.0% were obese under BF% criteria. Again, of 682 participants who were normal by BF%, 2.5% were categorized as obese and 13.1% (90) as overweight by BMI criteria. This leads us to the fact that BMI which gives us the idea of the weight in relation to height for age and sex might not always give us the idea of the adiposity of the individual missing many cases with higher adiposity or misclassifying those with normal BF% as overweight. Likewise, BF% alone may miss certain individual with higher weight range. BIA is relatively a simple and noninvasive procedure. The instruments available to determine BF% by hand-to-foot BIA method are also inexpensive making it a feasible for researcher to use in their studies. Moreover, the instrument is portable and can be used by any person with minimal training.
Limitations of the study
Predictive equations for determining BF% by BIA are based on factors such as age, gender, and ethnicity. Since our study population had heterogeneous ethnic composition, it was difficult for us to see the influence of ethnicity on our results.
| Conclusions|| |
The prevalence of overweight and obesity is substantial among adolescents. The use of BMI as a tool to determine the weight status of the adolescents remains a valuable tool. However, the addition of BF% estimation by BIA can provide a good predictive capacity to determine excess body fat, especially in large population-based studies.
We acknowledge the schools of Dibrugarh for allowing us to conduct our study.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Dwivedi G, Dwivedi S. History of medicine: Sushruta – The clinician – Teacher par excellence. Tradit Med Res 2007;37:67-77.
Haslam DW, James WP. Obesity. Lancet 2005;366:1197-209.
Häger A. Adipose tissue cellularity in childhood in relation to the development of obesity. Br Med Bull 1981;37:287-90.
Prentice AM, Jebb SA. Beyond body mass index. Obes Rev 2001;2:141-7.
Fortuño A, Rodríguez A, Gómez-Ambrosi J, Frühbeck G, Díez J. Adipose tissue as an endocrine organ: Role of leptin and adiponectin in the pathogenesis of cardiovascular diseases. J Physiol Biochem 2003;59:51-60.
Dehghan M, Merchant AT. Is bioelectrical impedance accurate for use in large epidemiological studies? Nutr J 2008;7:26.
Diaz EO, Villar J, Immink M, Gonzales T. Bioimpedance or anthropometry? Eur J Clin Nutr 1989;43:129-37.
Segal KR, Burastero S, Chun A, Coronel P, Pierson RN Jr. Wang J, et al.
Estimation of extracellular and total body water by multiple-frequency bioelectrical-impedance measurement. Am J Clin Nutr 1991;54:26-9.
Fuller NJ, Jebb SA, Goldberg GR, Pullicino E, Adams C, Cole TJ, et al.
Inter-observer variability in the measurement of body composition. Eur J Clin Nutr 1991;45:43-9.
Demura S, Yamaji S, Goshi F, Kobayashi H, Sato S, Nagasawa Y, et al.
The validity and reliability of relative body fat estimates and the construction of new prediction equations for young Japanese adult males. J Sports Sci 2002;20:153-64.
Lissau I. Overweight and obesity epidemic among children. Answer from European countries. Int J Obes Relat Metab Disord 2004;28 Suppl 3:S10-5.
Hoque ME, Doi SA, Mannan M, Long K, Niessen LW, Mamun AA, et al.
Prevalence of overweight and obesity among children and adolescents of the Indian subcontinent: A meta-analysis. Nutr Rev 2014;72:541-50.
U.S. Department of Health and Human Services. The Surgeon General's Vision for a Healthy and Fit Nation. Rockville, MD: U.S. Department of Health and Human Services, Office of the Surgeon General; January, 2010. Available from: http://www.surgeongeneral.gov
. [Last accessed on 2016 Sep 01].
Nawab T, Khan Z, Khan IM, Ansari MA. Influence of behavioral determinants on the prevalence of overweight and obesity among school going adolescents of Aligarh. Indian J Public Health 2014;58:121-4.
] [Full text]
McCarthy HD, Cole TJ, Fry T, Jebb SA, Prentice AM. Body fat reference curves for children. Int J Obes (Lond) 2006;30:598-602.
Report of a Joint World Health Organization/Food and Agriculture Organization Expert Consultation. Diet, Nutrition and the Prevention of Chronic Diseases. World Health Organization Technical Report Series, No 916. Geneva: World Health Organization; 2003. Available from: http://www.whqlibdoc.who.int/trs/WHO_TRS_916.pdf
. [Last accessed on 2016 Jun 21].
Antal M, Péter S, Biró L, Nagy K, Regöly-Mérei A, Arató G, et al.
Prevalence of underweight, overweight and obesity on the basis of body mass index and body fat percentage in Hungarian schoolchildren: Representative survey in metropolitan elementary schools. Ann Nutr Metab 2009;54:171-6.
Jelena J, Baltic ZM, Milica G, Jelena I, Marija B, Miklka P, et al
. Relationship between body mass index and body fat percentage among adolescents from Serbian Republic. J Child Obes 2016;1:1-5
Sampei MA, Novo NF, Juliano Y, Sigulem DM. Comparison of the body mass index to other methods of body fat evaluation in ethnic Japanese and Caucasian adolescent girls. Int J Obes Relat Metab Disord 2001;25:400-8.
[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3]