TY - JOUR
T1 - How important are determinants of obesity measured at the individual level for explaining geographic variation in body mass index distributions? Observational evidence from Canada using Quantile Regression and Blinder-Oaxaca Decomposition
AU - Dutton, Daniel J.
AU - McLaren, Lindsay
PY - 2015/12/8
Y1 - 2015/12/8
N2 - Background Obesity prevalence varies between geographic regions in Canada. The reasons for this variation are unclear but most likely implicate both individual-level and population-level factors. The objective of this study was to examine whether equalising correlates of body mass index (BMI) across these geographic regions could be reasonably expected to reduce differences in BMI distributions between regions. Methods Using data from three cycles of the Canadian Community Health Survey (CCHS) 2001, 2003 and 2007 for males and females, we modelled between-region BMI cross-sectionally using quantile regression and Blinder-Oaxaca decomposition of the quantile regression results. Results We show that while individual-level variables (ie, age, income, education, physical activity level, fruit and vegetable consumption, smoking status, drinking status, family doctor status, rural status, employment in the past 12 months and marital status) may be Caucasian important correlates of BMI within geographic regions, those variables are not capable of explaining variation in BMI between regions. Discussion Equalisation of common correlates of BMI between regions cannot be reasonably expected to reduce differences in the BMI distributions between regions.
AB - Background Obesity prevalence varies between geographic regions in Canada. The reasons for this variation are unclear but most likely implicate both individual-level and population-level factors. The objective of this study was to examine whether equalising correlates of body mass index (BMI) across these geographic regions could be reasonably expected to reduce differences in BMI distributions between regions. Methods Using data from three cycles of the Canadian Community Health Survey (CCHS) 2001, 2003 and 2007 for males and females, we modelled between-region BMI cross-sectionally using quantile regression and Blinder-Oaxaca decomposition of the quantile regression results. Results We show that while individual-level variables (ie, age, income, education, physical activity level, fruit and vegetable consumption, smoking status, drinking status, family doctor status, rural status, employment in the past 12 months and marital status) may be Caucasian important correlates of BMI within geographic regions, those variables are not capable of explaining variation in BMI between regions. Discussion Equalisation of common correlates of BMI between regions cannot be reasonably expected to reduce differences in the BMI distributions between regions.
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U2 - 10.1136/jech-2015-205790
DO - 10.1136/jech-2015-205790
M3 - Article
C2 - 26646691
AN - SCOPUS:84961207092
SN - 0143-005X
VL - 70
SP - 367
EP - 373
JO - Journal of Epidemiology and Community Health
JF - Journal of Epidemiology and Community Health
IS - 4
ER -