HABITAT: A longitudinal multilevel study of physical activity change in mid-aged adults.

BACKGROUND: Little is known about the patterns and influences of physical activity change in mid-aged adults. This study describes the design, sampling, data collection, and analytical plan of HABITAT, an innovative study of (i) physical activity change over five years (2007-2011) in adults aged 40-65 years at baseline, and (ii) the relative contribution of psychological variables, social support, neighborhood perceptions, area-level factors, and sociodemographic characteristics to physical activity change. METHODS/DESIGN: HABITAT is a longitudinal multi-level study. 1625 Census Collection Districts (CCDs) in Brisbane, Australia were ranked by their index of relative socioeconomic disadvantage score, categorized into deciles, and 20 CCDs from each decile were selected to provide 200 local areas for study inclusion. From each of the 200 CCDs, dwellings with individuals aged between 40-65 years (in 2007) were identified using electoral roll data, and approximately 85 people per CCD were selected to participate (N = 17,000). A comprehensive Geographic Information System (GIS) database has been compiled with area-level information on public transport networks, footpaths, topography, traffic volume, street lights, tree coverage, parks, public services, and recreational facilities Participants are mailed a questionnaire every two years (2007, 2009, 2011), with items assessing physical activity (general walking, moderate activity, vigorous activity, walking for transport, cycling for transport, recreational activities), sitting time, perceptions of neighborhood characteristics (traffic, pleasant surroundings, streets, footpaths, crime and safety, distance to recreational and business facilities), social support, social cohesion, activity-related cognitions (attitudes, efficacy, barriers, motivation), health, and sociodemographic characteristics. Analyses will use binary and multinomial logit regression models, as well as generalized linear latent growth models. DISCUSSION: HABITAT will provide unique information to improve our understanding of the determinants of physical activity, and to help identify "people" and "place" priority targets for public policy and health promotion aimed at increasing physical activity participation among mid-aged men and women.

The association between objectively measured neighborhood features and walking in middle-aged adults.

PURPOSE: Explore the role of the neighborhood environment in supporting walking. DESIGN: Cross-sectional study of 10,286 residents of 200 neighborhoods. Participants were selected using a stratified two-stage cluster design. Data were collected by mail survey (68.5% response rate). SETTING: Brisbane City Local Government Area, Australia, 2007. SUBJECTS: Brisbane residents aged 40 to 65 years. MEASURES: Environmental: street connectivity, residential density, hilliness, tree coverage, bikeways, and streetlights within a 1-km circular buffer from each resident's home; and network distance to nearest river or coast, public transport, shop, and park. Walking: minutes walked in the previous week: < 30 minutes, ≥ 30 to < 90 minutes, ≥ 90 to < 150 minutes, ≥ 150 to < 300 minutes, and ≥ 300 minutes. ANALYSIS: The association between each neighborhood characteristic and walking was examined using multilevel multinomial logistic regression, and the model parameters were estimated using Markov chain Monte Carlo simulation. RESULTS: After adjustment for individual factors, the likelihood of walking for more than 300 minutes (relative to < 30 minutes) was highest in areas with the most connectivity (odds ratio [OR] 5 1.93; 99% confidence intervals [CI], 1.32-2.80), greatest residential density (OR 5 1.47; 99% CI, 1.02-2.12), least tree coverage (OR 5 1.69; 99% CI, 1.13-2.51), most bikeways (OR 5 1.60; 99% CI, 1.16-2.21), and most streetlights (OR 5 1.50; 99% CI, 1.07-2.11). The likelihood of walking for more than 300 minutes was also higher among those who lived closest to a river or the coast (OR 5 2.06; 99% CI, 1.41-3.02). CONCLUSION: The likelihood of meeting (and exceeding) physical activity recommendations on the basis of walking was higher in neighborhoods with greater street connectivity and residential density, more streetlights and bikeways, closer proximity to waterways, and less tree coverage. Interventions targeting these neighborhood characteristics may lead to improved environmental quality as well as lower rates of overweight and obesity and associated chromic disease.