GIS-measured walkability, transit, and recreation environments in relation to older Adults' physical activity: A latent profile analysis

Abstract

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 Geographical 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 minutes/day for MVPA, 97.8 minutes/week for walking for errands, and 79.2 minutes/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.

Environmental Factors Associated with Older Adult’s Walking Behaviors: A Systematic Review of Quantitative Studies

“…Among the 70 studies, 27 studies (38.6%) did not use stratified sampling methods. Stratification by walkability and SES were used in Africa [27], Asia [48][49][50][51][52][53][54], Europe [55][56][57][58], and North America [59][60][61][62][63][64]. In the individual selection for sampling procedures, two-thirds of the studies randomly selected participants.…”

“…The other common method was convenience/purposive sampling (27.1%). More than half of the studies were on identified projects with multiple publications performed in four continents, Asia (Hong Kong [48][49][50][51][52][53]), Europe (Belgium [55][56][57][58]), North America (USA [39,[60][61][62][63][65][66][67][68][69]), and South America (Brazil [33,34]). Nineteen identified projects (27.1%; three studies in Asia, five studies in Europe, and eleven studies in North America) were associated with only one publication.…”

Growing Healthy Communities Initiative

“…A deeper understanding of the relationship between built environments and physical activity was studied using latent profile analyses of seven GIS (geographic information system) measured built environment features. This study concluded that walkability along with transit and recreation access did contribute to healthy aging among older populations (Todd et al, 2016).…”

Implications of Geographic Information Systems (GIS) for targeted recruitment of older adults with dementia and their caregivers in the community: A retrospective analysis

“…Specifically concerning older adults, one prominent area of study is neighborhood-level analyses of both subjective and objective factors (e.g., built environment, mobility patterns, and perceptions thereof) related to health outcomes for residents such as walkability and related physical activity [[29], [30], [31], [32], [33], [34]]. Disparities in access to health care services has also been explored using GIS [35,36], as well as geographic patterning of chronic conditions in older adults [37,38].…”