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Introduction. Environmental factors are thought to impact obesity; for instance food deserts are urban areas with poor access to fresh foods. Similarly, environmental variance might explain differences in urban physical activity levels. Our prior work examined poverty, obesity and sedentariness in 3,139 counties across the United States. Poverty, obesity and sedentariness track together. Since three quarters of Americans live in cities, we wondered whether cities with the greater rates of poverty had the poorest Walk Score (a geospatial algorithm of an area’s attractiveness of walking; a high score is walk-favorable).
Methods.We analyzed data from 532 American cities (defined as a population >30,000 people), examining data from103,405,474 people. Data on income were available from 102,586,417 people. The Walk Score for all 520 cities was determined from Street Smart Walk Score algorithm derived from the Active Living Research (Robert Wood Johnson Foundation http://activelivingresearch.org/). We compared Walk Score and city demographics between the 100 cities with the lowest povertyprevalence 6.4 ± (SD) 1.7% with the 100 cities of great poverty prevalence 27.4 ± 4.1%.
Results.The cities with greatest poverty had, as expected, lowest median family income ($43,604 ±$10,097 vs.$89,613 ±$19,058; for all 520 cities there was a log linear relationship between these variables r2 = 0.77). Importantly too, the poorer cities had greater populations (197,128 ± 235,305 vs. 109,952 ± 58,375 people). There was no relationship between city population and Walk Score. Unexpectedly, the cities with greater poverty and lower income, have the most favorable Walk Score (50.1 ± 12.2 points) compared to wealthier cities (Walk Score 44 ± 12.2; P<0.001).Discussion.Cities with high poverty rates do not appear to be more unfavorable to walking compared to wealthy cities. Thus, the known association between sedentariness, obesity & poverty may not relate to the walkability of the city.
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