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Year : 2017  |  Volume : 6  |  Issue : 1  |  Page : 152

Analysis of Factors Affecting the Body Mass Index in a National Sample of Iranian Children and Adolescents: Bootstrapping Regression

1 Department of Biostatistics and Epidemiology, School of Public Health, Isfahan University of Medical Sciences, Isfahan, Iran
2 Department of Pediatrics, Child Growth and Development Research Center, Isfahan University of Medical Sciences, Isfahan, Iran

Correspondence Address:
Mrs. Shakiba Latifi
Department of Biostatistics and Epidemiology, School of Public Health, Isfahan University of Medical Sciences, Isfahan
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/2277-9175.219417

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Background: This study aims to evaluate the effect of some factors, including birth weight, sex, age, waist circumference, family history of obesity, as well as some lifestyle factors as frequency of breakfast days and physical activity, on the body mass index among a nationally representative sample of Iranian children and adolescents by using bootstrapping regression. Materials and Methods: This study was conducted as the third survey of a school-based surveillance system (CASPIAN-III study). Total participants were 5570 school students, aged 10-18 years, selected by multistage random cluster sampling from urban and rural areas of 27 provinces of Iran. Multiple linear regressions was used to evaluate the effect of various factors on obesity, but in our data the assumptions of this model violated, and possible solutions were not appropriate, therefore the bootstrapping regression based on the observations and errors resampling approaches was used as an alternative. Results: The tests of significance showed that the effects of sex, age, waist circumference, family history obesity and frequency of breakfast days were clearly significant (P < 0.001). The effect of vigorous level of physical activity was significant in comparison to mild physical activity (P = 0.01). In comparison to low birth weight, medium and high birth weight had significant effect on obesity. Conclusions: Bootstrap method is preferable in linear regression because of some theoretical properties like having any distributional assumptions on the residuals and hence allows for inference even if the errors do not follow normal distribution or constant error variance.

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