265430 Uncovering geographical clustering of childhood obesity and childhood obesity disparities using hierarchical spatial models

Wednesday, October 31, 2012 : 11:30 AM - 11:50 AM

Brisa N. Sanchez, PhD , Department of Biostatistics, University of Michigan, Ann Arbor, MI
Despite well documented race/ethnic disparities in childhood obesity, and studies suggesting differences in geographical clustering of obesity prevalence by race/ethnicity, no studies have rigorously tested if geographic patterns in obesity prevalence differ significantly by race/ethnicity owing, in part, to the lack of methods to do so. Significant race/ethnic differences in the geographical patterning of obesity trends can shed light into salient environmental causes of persisting disparities. We present multi-level logistic regression models with spatially-autocorrelated random effects to study the geographical patterning of obesity prevalence among children in the State of California, and to examine if geographical patterning in race-ethnic disparities in obesity rates exists. Although the models are complex, model results can be displayed using existing mapping methodologies and are therefore friendly to a wide variety of users.

Learning Areas:
Biostatistics, economics
Chronic disease management and prevention
Public health or related research

Learning Objectives:
Describe the use of spatial models in quantifiying obesity disparities across geographical areas

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I have a PhD in biostatistics, and was the primary author of the work presented
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.