OBESITY AND LOCATION IN MARION COUNTY, INDIANA MIDWEST STUDENT SUMMIT, APRIL Samantha Snyder, Purdue University

Transcription

1 OBESITY AND LOCATION IN MARION COUNTY, INDIANA MIDWEST STUDENT SUMMIT, APRIL 2008 Samantha Snyder, Purdue University

2 Organization Introduction Literature and Motivation Data Geographic Distributions ib ti and Correlations Methods Results Conclusions Discussion

3 Introduction Obesity is defined as a BMI of 30 or higher; overweight is defined as a BMI of 25 to 29.9; normal weight is defined as a BMI of 18.5 to Between 1980 and 2000, obesity and overweight have increased dramatically over all segments of the adult population. Disparities in prevalence exist across racial groups, education and income levels, and geography. Indiana (2005) 35.1% overweight, 27.2% obese (10 th in country) Marion County (2005) 35% overweight, 29.5% obese Trends in grocery retailing show unequal distribution of large chain grocers with respect to racial composition and income level.

4 Literature and Motivation Predominately conducted in fields of public health, epidemiology, and nutrition Emerging contribution from economics Unequal access to food retailers Cummins and Macintyre, Morland et al., Moore and Diez Roux, Zenk et al., Chung and Myers, Jr. Linking access directly to health Jeffery et al., Mandal and Chern, Chou et al., Morland et al., Gallagher, Rose and Richards, Wrigley et al.

5 Literature and Motivation It is agreed upon that environmental factors do play some role in idnividual health levels, for example, BMI. How does food retailer access impact BMI? While there are some variables we were able to measure, there are many we weren t. How can we build an accurate model of the determinants of BMI that incorporates known environmental factors and also allows for spatial dependence due to un-modeled factors?

6 Data 3,811 adults randomly selected and interviewed by telephone in Marion County, Indiana. Data collected on demographic and behavioral variables, and BMI and geocoded. Sample shows similar trends and associations as seen nationally. Respondents aggregated to census tracts to calculate a percent obese for each tract.

7 Data Names, addresses, and establishment type for each food retailer in Marion County, Indiana collected from Marion County Health Department. Food retailers defined into three categories: large chain grocery store, small grocery store, and convenience store. Counts of each type performed by census tract.

8 Data Census tract level variables for Marion County Median family income Percentage of African American residents Percentage of residents with some education past a high school diploma Percentage of households without a car

9 Geographic Distributions and Correlations

10 Geographic Distributions and Correlations

11 Geographic Distributions and Correlations

12 Methods Creation of spatial weights matrix Global Moran s I on raw values Measures spatial correlation (clustering) of census tract measures OLS with spatial diagnostics Spatial lag model Further refinement Two-stage least squares with instrumental variables

13 Results Queen contiguity matrix Census tract obesity levels are positively correlated with their neighbors levels

14 Results

15 Results

16 Results OLS Variable Coefficient Std. Error t-statistic Probability Constant Median Family Income e e % African American % > High School Diploma % No Car Large Chain Grocery Small Grocery Convenience Test Value Probability LM Lag LM Lag (Robust) LM Error LM Error (Robust) SARMA

17 Results Spatial Lag Variable Coefficient Std. Error t-statistic Probability W % Obese Constant Median Family Income e e % African American % > High School Diploma % No Car Large Chain Grocery Small Grocery Convenience

18 Further Refinement Aggregate census tracts with low sampling Heteroskedasticity Select weighted RHS variables for inclusion Two stage least squares with instrumental variables Aggregated data Individual level data More comprehensive food environment More exhaustive definition of retailer types

19 Conclusion Food retailer distribution in Marion County is highly tied to demographic characteristics such as income levels and racial composition. Patterns of levels of obesity also match these demographic distributions. ib i While both retailer distribution and obesity are correlated with population characteristics, retail access does not seem to be associated with obesity levels, once demographics are controlled. Spatial correlation, however, still exists to some degree.

20 Discussion What is it about the environment/neighborhood that could be contributing to spatial patterns in obesity levels? Can we model these factors? What do these relationships (and lack of relationships) imply for policymakers? Behavior, education, nutrition, public health, etc. What about the equity argument? How can these questions/research be adapted to address childhood obesity?