40 research outputs found

    Commute Times, Food Retail Gaps, and Body Mass Index in North Carolina Counties

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    Introduction: The prevalence of obesity is higher in rural than in urban areas of the United States, for reasons that are not well understood. We examined correlations between percentage of rural residents, commute times, food retail gap per capita, and body mass index (BMI) among North Carolina residents. Methods: We used 2000 census data to determine each county\u27s percentage of rural residents and 1990 and 2000 census data to obtain mean county-level commute times. We obtained county-level food retail gap per capita, defined as the difference between county-level food demand and county-level food sales in 2008, from the North Carolina Department of Commerce, and BMI data from the 2007 North Carolina Behavioral Risk Factor Surveillance System. To examine county-level associations between BMI and percentage of rural residents, commute times, and food retail gap per capita, we used Pearson correlation coefficients. To examine cross-sectional associations between individual-level BMI (n=9,375) and county-level commute times and food retail gap per capita, we used multilevel regression models. Results: The percentage of rural residents was positively correlated with commute times, food retail gaps, and county-level BMI. Individual-level BMI was positively associated with county-level commute times and food retail gaps. Conclusions: Longer commute times and greater retail gaps may contribute to the rural obesity disparity. Future research should examine these relationships longitudinally and should test community-level obesity prevention

    Is there a link between wealth and cardiovascular disease risk factors among Hispanic/Latinos? : Results from the HCHS/SOL sociocultural ancillary study

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    OBJECTIVE: To examine the relationship between wealth and cardiovascular disease risk factors among Hispanic/Latinos of diverse backgrounds. DESIGN: This cross-sectional study used data from 4971 Hispanic/Latinos, 18-74 years, who participated in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) baseline exam and the HCHS/SOL Sociocultural Ancillary Study. Three objectively measured cardiovascular disease risk factors (hypertension, hypercholesterolemia, and obesity) were included. Wealth was measured using an adapted version of the Home Affluence Scale, which included questions regarding the ownership of a home, cars, computers, and recent vacations. RESULTS: After adjusting for traditional socioeconomic indicators (income, employment, education), and other covariates, we found that wealth was not associated with hypertension, hypercholesterolemia or obesity. Analyses by sex showed that middle-wealth women were less likely to have hypercholesterolemia or obesity. Analyses by Hispanic/Latino background groups showed that while wealthier Central Americans were less likely to have obesity, wealthier Puerto Ricans were more likely to have obesity. CONCLUSION: This is the first study to explore the relationship between wealth and health among Hispanic/Latinos of diverse backgrounds, finding only partial evidence of this association. Future studies should utilize more robust measures of wealth, and address mechanisms by which wealth may impact health status among Hispanic/Latinos of diverse backgrounds in longitudinal designs
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