Using multivariate techniques in the construction of a BMI risk index for Metropolitan Statistical Areas in the United States.
Background: The concerns about the long-term impact of the morbidities associated with overweight and obesity are becoming a central issue of public health organizations. Public health studies that have focused on the prevalence of overweight and obesity have analyzed individual factors akin to soc...
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|Summary:||Background: The concerns about the long-term impact of the morbidities associated with overweight and obesity are becoming a central issue of public health organizations. Public health studies that have focused on the prevalence of overweight and obesity have analyzed individual factors akin to socioeconomic, behavioral characteristics and external factors that refer to the food environment or built-environment. There is an association between these factors which can be consolidated and rendered into a useful BMI risk index to predict the prevalence of overweight and obesity in communities. Methods: This study analyzed the relationship between built-environment, the restaurant-environment and weight status in 53 Metropolitan Statistical Areas in the United States. Individual data obtained from the 2002 Behavioral Risk Factor Surveillance System (N=111,704) was linked with Urban-Sprawl data from the Metropolitan Sprawl Index developed by Smart Growth America in 2002 and restaurant data from the 2002 Economic Census of Retail Trade. The combined effects of urban-sprawl, per capita number of limited-service and full-service restaurants on the weight status of the population in specific Metropolitan Statistical Areas were assessed. The analyses were conducted in 2008-2009. Results: Increase in urban sprawl was positively associated with higher community BMI. In high to medium level of urban-sprawl a high ratio of limited-service to full-service restaurants was associated with higher BMI, as the number of full-service restaurants increased the mean BMI of the community decreased. For communities with little urban-sprawl, independent of limited-service restaurant density, increasing the number of full-service restaurants was positively correlated with higher BMI. Conclusions: Further research is required to investigate contextual factors that influence eating behaviors and restaurant preferences within communities and their effects on the communities’ weight status.|