{"title":"Determinants of Body Mass Index in Turkey: A Quantile Regression Analysis from a Middle Income Country","authors":"D. Karaoğlan, A. Tansel","doi":"10.21773/BOUN.32.2.1","DOIUrl":null,"url":null,"abstract":"This study investigates the factors that may influence the individual’s Body Mass Index (BMI) in the developing country of Turkey by implementing Quantile Regression (QR) methodology. The analysis is conducted by using the 2008, 2010 and 2012 waves of the Turkish Health Survey (THS) prepared by the Turkish Statistical Institute (TURKSTAT). QR regression results provide robust evidence that additional years of schooling are negatively correlated with an individual’s BMI and this relationship is significantly raised across different quantiles of BMI. We also find a strong negative relationship between being in the labor force and an individual’s BMI, and this relationship increases across the quantiles of BMI implying that an individual is more likely to be obese if he/ she is out of labor force. Our results suggest that other socioeconomic and demographic indicators such as gender, age, marital status and household income are also important factors to explain the variation in an individual’s BMI.","PeriodicalId":35304,"journal":{"name":"Bogazici Journal","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bogazici Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21773/BOUN.32.2.1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 11
Abstract
This study investigates the factors that may influence the individual’s Body Mass Index (BMI) in the developing country of Turkey by implementing Quantile Regression (QR) methodology. The analysis is conducted by using the 2008, 2010 and 2012 waves of the Turkish Health Survey (THS) prepared by the Turkish Statistical Institute (TURKSTAT). QR regression results provide robust evidence that additional years of schooling are negatively correlated with an individual’s BMI and this relationship is significantly raised across different quantiles of BMI. We also find a strong negative relationship between being in the labor force and an individual’s BMI, and this relationship increases across the quantiles of BMI implying that an individual is more likely to be obese if he/ she is out of labor force. Our results suggest that other socioeconomic and demographic indicators such as gender, age, marital status and household income are also important factors to explain the variation in an individual’s BMI.