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dc.contributor.authorBelasco, Eric J.
dc.contributor.authorChidmi, B.
dc.contributor.authorLyford, C. P.
dc.contributor.authorFuntanilla, M.
dc.identifier.citationBelasco, E.J., B. Chidmi, C.P. Lyford, M. Funtanilla. "Using Quantile Regression to Measure the Differential Impact of Economic and Demographic Variables on Obesity" Journal of Health Behavior and Public Health. Vol. 2, No. 2 (2012): 35-45.en_US
dc.description.abstractThe fight against obesity in the U.S. has become a pressing priority for policy makers due to many undesirable outcomes including escalating health care costs, reduced quality of life and increased mortality. This analysis uses data from the 2007 Behavioral Risk Factor Surveillance System (BRFSS) to evaluate the relationship between behavioral, economic, and demographic factors with BMI while explicitly accounting for systematic heterogeneity using a quantile regression. Results suggest that the effect of exercise, smoking, occupation, and race vary by sizeable amounts from high to low BMI-quantiles. This strongly indicates that future research efforts and policy responses to obesity need to account for these differences in order to develop more effective policies.en_US
dc.subjectPublic healthen_US
dc.titleUsing Quantile Regression to Measure the Differential Impact of Economic and Demographic Variables on Obesityen_US
mus.citation.journaltitleJournal of Health Behavior and Public Healthen_US
mus.identifier.categoryBusiness, Economics & Managementen_US
mus.identifier.categoryHumanities, Literature & Artsen_US
mus.relation.collegeCollege of Agriculture
mus.relation.collegeCollege of Agricultureen_US
mus.relation.departmentAgricultural Economics & Economics.en_US
mus.relation.universityMontana State University - Bozemanen_US

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