Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Burton NW

PROVIDER: S-EPMC2664805 | biostudies-other | 2009

REPOSITORIES: biostudies-other

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

Burton Nicola W NW Haynes Michele M Wilson Lee-Ann M LA Giles-Corti Billie B Oldenburg Brian F BF Brown Wendy J WJ Giskes Katrina K Turrell Gavin G

BMC public health 20090305

<h4>Background</h4>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 physic ...[more]

PMID: 19265552

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Project description:PurposeThe aim was to use accelerometer data to describe day-to-day variability in physical activity in a single week, according to sociodemographic variables, in mid-aged Australian adults.MethodsData were from participants in the How Areas in Brisbane Influence HealTh and AcTivity (HABITAT) study who took part in a 2014 sub-study (N = 612; Mean age 60.6 [SD 6.9; range 48-73]). Participants wore a triaxial accelerometer (ActiGraph wGT3X-BT) on their non-dominant wrist for seven days, and data were expressed as acceleration in gravitational equivalent units (1 mg = 0.001 g). These were, used to estimate daily acceleration (during waking hours) and daily time spent in moderate-vigorous physical activity (MVPA, defined as ≥ 100mg). Coefficient of variation (calculated as [standard deviation/mean of acceleration and MVPA across the seven measurement days] * 100%) was used to describe day-to-day variability.ResultsAverage values for both acceleration (24.1-24.8 mg/day) and MVPA (75.9-79.7 mins/day) were consistent across days of the week, suggesting little day-to-day variability (at the group level). However, over seven days, average individual day-to-day variability in acceleration was 18.8% (SD 9.3%; range 3.4-87.7%) and in MVPA was 35.4% (SD 15.6%; range 7.3-124.6%), indicating considerable day-to-day variability in some participants. While blue collar workers had the highest average acceleration (28.6 mg/day) and MVPA (102.5 mins/day), their day-to-day variability was low (18.3% for acceleration and 31.9% for MVPA). In contrast, variability in acceleration was highest in men, those in professional occupations and those with high income; and variability in MVPA was higher in men than in women.ConclusionResults show group-level estimates of average acceleration and MVPA in a single week conceal considerable day-to-day variation in how mid-age Australians accumulate their acceleration and MVPA on a daily basis. Overall, there was no clear relationship between overall volume of activity and variability. Future studies with larger sample sizes and longitudinal data are needed to build on the findings from this study and increase the generalisability of these findings to other population groups.

Project description:ObjectivesCross-sectional studies have found some built environmental attributes to be associated with residents' lower levels of mobility (functional capacity to walk outside the home). However, less is known about what environmental attributes are related to mobility decline. This longitudinal study examined area-level associations of specific environmental attributes with mid-to-older aged adults' changes in walking mobility.MethodsData collected from 4,088 adults (aged 46-71 years at baseline) who participated in a cohort study in Brisbane, Australia were used. The outcome was the change in self-reported mobility score (SF-36) from 2013 to 2016, which were aggregated at the neighborhood (N = 156) and suburb (N = 99) levels, due to the known lack of sensitivity in SF-36 subscales to individual changes. Linear regression analysis examined associations of mobility change with seven environmental attributes measured at baseline (residential density, intersection density, land use mix, density of walking/bike paths, park density, bus stop density, density of social incivilities), adjusting for confounding variables.ResultsParticipants on average reported 4% of mobility decline during the 3-year study period. It was found that greater land use diversity was consistently associated with less decline in walking mobility, while greater density of social incivilities was associated with more decline in walking mobility. The latter finding was significant only at the neighborhood level. No consistent associations were observed for residential density, intersection density, density of walking/bike paths, park density, and bus stop density.DiscussionOur findings suggest that mid-to-older aged adults who live in areas with lower land use diversity and more social incivilities may be at risk of developing mobility limitations. Recommended policies to slow residents' mobility decline and to achieve aging in place include improving these environmental attributes where needed and advising older adults to relocate to safer, mixed-use neighborhoods.

Project description:Little is known about patterns of associative multimorbidity and their aetiology. We aimed to identify patterns of associative multimorbidity among mid-aged women and the lifestyle and socioeconomic factors associated with their development.Participants were from the Australian Longitudinal Study on Women's Health. We included 4896 women born 1946-51, without multimorbidity in 1998. We identified multimorbidity patterns at survey 6 (2010) using factor analysis, and related these patterns to baseline lifestyle and socioeconomic factors using logistic regression. We dichotomised factor scores and determined odds ratios (ORs) with 95% confidence intervals (CIs) for associations between characteristics and odds of a high versus low factor score.We identified five multimorbidity patterns: psychosomatic; musculoskeletal; cardiometabolic; cancer; and respiratory. Overweight and obesity were respectively associated with increased odds of having a high score for the musculoskeletal (adjusted ORs 1.45 [95% CI 1.23, 1.70] and 2.14 [95% CI 1.75, 2.60]) and cardiometabolic (adjusted ORs 1.53 [95% CI 1.31, 1.79] and 2.46 [95% CI 2.02, 2.98]) patterns. Physical inactivity was associated with increased odds of a high score for the psychosomatic, musculoskeletal and cancer patterns (adjusted ORs 1.41 [95% CI 1.13, 1.76]; 1.39 [95% CI 1.11, 1.74]; and 1.35 [95% CI 1.08, 1.69]). Smoking was associated with increased odds of a high score for the respiratory pattern. Education and ability to manage on income were associated with increased odds of a high score for the psychosomatic pattern (adjusted ORs 1.34 [95% CI 1.03, 1.75] and 1.73 [95% CI 1.37, 1.28], respectively) and musculoskeletal pattern (adjusted ORs 1.43 [95% CI 1.10, 1.87] and 1.38 [1.09, 1.75], respectively).Distinct multimorbidity patterns can be identified among mid-aged women. Social inequality, physical activity and BMI are risk factors common to multiple patterns and are appropriate targets for reducing the risk of specific multimorbidity groups in mid-life women.

Dataset Information

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

Publications

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

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