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The Impacts of Residential Segregation on Obesity.
Journal of Physical Activity & Health 2018 November 2
BACKGROUND: This study examined the association between residential segregation and obesity for Whites, African Americans, Hispanics, and Asians. This study considered 3 dimensions of residential segregation, isolation, dissimilarity, and concentration.
METHODS: By combining individual-level data from the Behavioral Risk Factor Surveillance System and county-level data from the County Health Rankings and Roadmaps, the total sample size was 204,610 respondents (160,213 Whites, 21,865 African Americans, 18,027 Hispanics, and 4505 Asians) from 205 counties in the United States. Two-level logistic regression models were performed.
RESULTS: African Americans and Hispanics in counties with high levels of isolation, dissimilarity, and concentration were more likely to be obese; these relationships did not hold true for Whites and Asians. Counties with a higher percentage of populations with the income below the poverty line and a higher percentage of fast food restaurants in the county were associated with a higher likelihood of obesity for all racial/ethnic groups. African Americans and Hispanics with low levels of education and income were more likely to be obese.
CONCLUSIONS: Residential segregation had a contextual influence on weight status, and the context of counties influenced racial/ethnic groups differently. Obesity reduction programs should consider the contextual influence on minority populations and target subgroups living in highly segregated areas.
METHODS: By combining individual-level data from the Behavioral Risk Factor Surveillance System and county-level data from the County Health Rankings and Roadmaps, the total sample size was 204,610 respondents (160,213 Whites, 21,865 African Americans, 18,027 Hispanics, and 4505 Asians) from 205 counties in the United States. Two-level logistic regression models were performed.
RESULTS: African Americans and Hispanics in counties with high levels of isolation, dissimilarity, and concentration were more likely to be obese; these relationships did not hold true for Whites and Asians. Counties with a higher percentage of populations with the income below the poverty line and a higher percentage of fast food restaurants in the county were associated with a higher likelihood of obesity for all racial/ethnic groups. African Americans and Hispanics with low levels of education and income were more likely to be obese.
CONCLUSIONS: Residential segregation had a contextual influence on weight status, and the context of counties influenced racial/ethnic groups differently. Obesity reduction programs should consider the contextual influence on minority populations and target subgroups living in highly segregated areas.
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