American Journal of Public Health Research
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American Journal of Public Health Research. 2014, 2(3), 86-90
DOI: 10.12691/ajphr-2-3-4
Open AccessArticle

Predicting Obesity among Adolescents in the United States Using Modified Logistic Model

Eleanor K. Jator1,

1Austin Peay State University, Clarksville, TN 37043

Pub. Date: April 24, 2014

Cite this paper:
Eleanor K. Jator. Predicting Obesity among Adolescents in the United States Using Modified Logistic Model. American Journal of Public Health Research. 2014; 2(3):86-90. doi: 10.12691/ajphr-2-3-4


Obesity among adolescents is still on the rise and various reasons have been attributed to this increase. Obesity has been associated with many diseases, as well as, increase in healthcare costs. Concentration index and logistic regression have been extensively used to measure inequalities in health, including obesity, but these methods require each parameter to be calculated discretely. In this study, the logistic regression model is modified to predict the degree of obesity distribution that might be associated with multiple variables including income and race among adolescents in the United States. Unlike the methods currently used, the modified logistic model (MLM) can capture all variables at the same time in a single equation. The results produced by the model are comparable with those obtained when concentration index is used in a shorter time. It is hoped that this study will shorten the time to estimate or predict obesity rates among various races using existing Medical Expenditure Panel Survey (MEPS) data based on socioeconomic status. The ultimate goal is to develop targeted intervention strategies. Using existing data yields faster, reliable results since the sampling and collection utilize standard procedures. Results can easily be generalized due to random sampling and the MLM has the potential to predict the rate of obesity without performing further statistical analysis.

modified logistic regression Income obesity concentration index socioeconomic inequality adolescents

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[1]  Ogden CL, Carroll MD, Curtin LR, Lamb MM. & Flegal KM.(2010) Prevalence of high body mass index in U.S. children and adolescents, 2007-2008. JAMA, 303(3), 242-249.
[2]  Raj, M. & Kumar, K. R. (2010). Obesity in children & Adolescents. Indian J Med Res, 132, 598-607.
[3]  Flegal, K. M. (1999). The obesity epidemic in children and adults: current evidence and research issues. Medicine Science Sports Exercise, 31(11 Supplment 1).
[4]  Sheperd, T. M. (2003). Effective management of obesity - Research findings that are changing clinical practice. Journal of family practice, 52(1), 34-42.
[5]  Sundquist, J., & Johansson, S. (1998). The influence of socioeconomic status, ethnicity, and lifestyle on body mass index in a longitudinal study. International journal of epidemiology, 27, 57-63.
[6]  Sorlie, P. D., Backlind, E. & Keller, J. B. (1995). U.S. mortality by economic, demographic, and social characteristics: The National Longitudinal Mortality Study. American Journal of Public Health, 85(7), 949-956.
[7]  Wang, G. and. Dietz, W. H. (2002). Economic Burden of Obesity in Youths Aged 6 to 17 Years: 1979-1999. Pediatrics, 109(5), e81. Retrieved September 28, 2013 from
[8]  Kaplan, G, A., Pamuk, E, R., Lynch, J. W., Cohen, R. D. & Balfour, J. L. (1996). Inequality in income and mortality in the United States: analysis of mortality and potential pathways. British Medical Journal, 312(7037), 999-1003.
[9]  Moore, S. D. & McCabe, G. P. (2003). Introduction to the Practice of Statistics. W. H. Freeman and Company, New York.
[10]  Wagstaff, A., Paci, P. & Doorslayer, E. V. (1991). On the measurement of inequalities in health. Social Science & Medicine, 33(5), 545-557.
[11]  Kuczmarski, R. J., Ogben, C. L. & Guo, S. S. (2000). CDC growth charts for the United States methods and development. National Center for Health Statistics. Vital Health Stat 11. 2002; No 246.
[12]  Zhang, Q. & Wang, Y. (2004). Socioeconomic inequality of obesity in the United States: do gender, age, and ethnicity matter? Social Science & Medicine, 58(6), 1171-1180.
[13]  Goodman, E. (1999). The role of socioeconomic status gradient in explaining differences in US adolescent health (1999). American Journal of Public health, 89(10), 1522-1528.
[14]  Williams, D. R. (1992). Black-white differentials in blood pressure: The role of social factors. Ethnicity and Disease, 2, 126-141.