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An infrequently studied question is how diverse combinations of built environment (BE) features relate to physical activity (PA) for older adults. We derived patterns of geographic information systems- (GIS) measured BE features and explored how they accounted for differences in objective and self-reported PA, sedentary time, and BMI in a sample of older adults. Senior Neighborhood Quality of Life Study participants (N = 714, aged 66–97 years, 52.1% women, 29.7% racial/ethnic minority) were sampled in 2005–2008 from the Seattle-King County, WA and Baltimore, MD-Washington, DC regions. Participants' home addresses were geocoded, and net residential density, land use mix, retail floor area ratio, intersection density, public transit density, and public park and private recreation facility density measures for 1-km network buffers were derived. Latent profile analyses (LPAs) were estimated from these GIS-based measures. In multilevel regression models, profiles were compared on accelerometer-measured moderate-to-vigorous PA (MVPA) and sedentary time and self-reported PA, adjusting for covariates and clustering. Analyses were conducted in 2014–2015. LPAs yielded three profiles: low walkability/transit/recreation (L − L − L); mean walkability/transit/recreation (M-M-M); and high walkability/transit/recreation (H − H − H). Three PA outcomes were more favorable in the HHH than the LLL profile group (difference of 7.2 min/day for MVPA, 97.8 min/week for walking for errands, and 79.2 min/week for walking for exercise; all ps < 0.02). The most and least activity-supportive BE profiles showed greater differences in older adults' PA than did groupings based solely on a 4-component walkability index, suggesting that diverse BE features are important for healthy aging.


Institute for Health and Ageing

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Journal Article

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