Associations between the built environment and physical activity in public housing residents
1 Department of Public Health Sciences, University of Hawaii at Manoa, Honolulu, USA
2 Department of Health and Human Performance, University of Houston, Houston, USA
3 Kansas City University of Medicine and Biosciences, Kansas City, USA
4 Department of Psychology, Castleton State College, Castleton, USA
5 Department of Geography, American River College, Sacramento, USA
6 Department of Basic Medical Science, School of Medicine, University of Missouri-Kansas City, Kansas City, USA
7 Department of Medicine and Cancer Center, University of Minnesota, Minneapolis, USA
International Journal of Behavioral Nutrition and Physical Activity 2007, 4:56 doi:10.1186/1479-5868-4-56Published: 12 November 2007
Environmental factors may influence the particularly low rates of physical activity in African American and low-income adults. This cross-sectional study investigated how measured environmental factors were related to self-reported walking and vigorous physical activity for residents of low-income public housing developments.
Physical activity data from 452 adult residents residing in 12 low-income housing developments were combined with measured environmental data that examined the neighborhood (800 m radius buffer) around each housing development. Aggregated ecological and multilevel regression models were used for analysis.
Participants were predominately female (72.8%), African American (79.6%) and had a high school education or more (59.0%). Overall, physical activity rates were low, with only 21% of participants meeting moderate physical activity guidelines. Ecological models showed that fewer incivilities and greater street connectivity predicted 83% of the variance in days walked per week, p < 0.001, with both gender and connectivity predicting days walked per week in the multi-level analysis, p < 0.05. Greater connectivity and fewer physical activity resources predicted 90% of the variance in meeting moderate physical activity guidelines, p < 0.001, and gender and connectivity were the multi-level predictors, p < 0.05 and 0.01, respectively. Greater resource accessibility predicted 34% of the variance in days per week of vigorous physical activity in the ecological model, p < 0.05, but the multi-level analysis found no significant predictors.
These results indicate that the physical activity of low-income residents of public housing is related to modifiable aspects of the built environment. Individuals with greater access to more physical activity resources with fewincivilities, as well as, greater street connectivity, are more likely to be physically active.