| Why might one think that obesity is something other than someone eating too much, exercising too little, or an expression of genetics? Or that decisions about what one eats aren't based on personal choice? My dissertation explores how structural inequality is perpetuated to individuals, resulting in higher body mass index, limited consumption of healthy foods, and different store composition in local food environments. I test these relationships with two-tiered hierarchical models. All relationships are tested using data from California. Data come from the California Behavioral Risk Factor Surveillance Survey (BRFS),the California Dietary Practices Survey (CDPS), the U.S. Census (2000) and a commercially available market research database from 2004.;In the next case, I demonstrate that healthy food consumption (fruits and vegetables, low- or non fat milk, and whole grains) is a privileged behavior. Demographic differences offered little county-level explanation for healthy food consumption. Both poverty and the built food environment demonstrate how unequal environments lead to unequal, stratified food consumption outcomes. Unhealthy foods are far more equally available to people; cheap calories are not stratified in their availability.;In the final case, I demonstrate that store placement is influenced by racial and income inequality. I find that the degree of county-level poverty and racial segregation shape the local built food environment at the census-tract level, translating structural inequality into local inequality of place. The influence of White/Black segregation is far more pronounced that that of White/Hispanic and White/Asian segregation. Overall, this analysis demonstrates essentially separate but not equal food environments for White and Black, wealthy and poor.;The first case I explore is that of associations between area poverty and body mass index (BMI) for individuals in California counties. I apply a causal logic to the contributions of county poverty, sprawl, and store presence. I find that poverty has the most consistent, robust effect on BMI. Sprawl appears to measure a different process, and is a complementary explanation to county poverty. Demographic variables were not significant after adjusting for poverty. All types of restaurants had an independent effect on BMI, but the presence of retail food stores did not. |
