Dataset Information

Built and socioeconomic environments: patterning and associations with physical activity in U.S. adolescents.

ABSTRACT:

Background

Inter-relationships among built and socioeconomic environmental characteristics may result in confounding of associations between environment exposure measures and health behaviors or outcomes, but traditional multivariate adjustment can be inappropriate due to collinearity.

Methods

We used principal factor analysis to describe inter-relationships between a large set of Geographic Information System-derived built and socioeconomic environment measures for adolescents in the National Longitudinal Study of Adolescent Health (Wave I, 1995-96, n = 17,294). Using resulting factors in sex-stratified multivariate negative binomial regression models, we tested for confounding of associations between built and socioeconomic environment characteristics and moderate to vigorous physical activity (MVPA). Finally, we used knowledge gained from factor analysis to construct replicable environmental measures that account for inter-relationships and avoid collinearity.

Results

Using factor analysis, we identified three built environment constructs [(1) homogenous landscape; 2) development intensity with high pay facility count; 3) development intensity with high public facility count] and two socioeconomic environment constructs [1) advantageous economic environment, 2) disadvantageous social environment]. In regression analysis, confounding of built environment-MVPA associations by socioeconomic environment factors was stronger than among built environment factors. In fully adjusted models, MVPA was negatively associated with the highest (versus lowest) quartile of homogenous land cover in males [exp(coeff) (95% CI): 0.91 (0.86, 0.96)] and intensity (pay facilities) [exp(coeff) (95% CI): 0.92 (0.85, 0.99)] in females. Single proxy measures (Simpson's diversity index, count of pay facilities, count of public facilities, median household income, and crime rate) representing each environmental construct replicated associations with MVPA.

Conclusions

Environmental characteristics are inter-related. Both built and SES environments should be incorporated into analysis in order to minimize confounding. Single environmental measures may be useful proxies for environmental constructs in longitudinal analysis and replication in external populations, but more research is needed to better understand mechanisms of action, and ultimately identify policy-relevant environmental determinants of physical activity.

SUBMITTER: Boone-Heinonen J

PROVIDER: S-EPMC3152773 | biostudies-literature | 2010 May

REPOSITORIES: biostudies-literature

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Publications

Built and socioeconomic environments: patterning and associations with physical activity in U.S. adolescents.

Boone-Heinonen Janne J Evenson Kelly R KR Song Yan Y Gordon-Larsen Penny P

The international journal of behavioral nutrition and physical activity 20100520

<h4>Background</h4>Inter-relationships among built and socioeconomic environmental characteristics may result in confounding of associations between environment exposure measures and health behaviors or outcomes, but traditional multivariate adjustment can be inappropriate due to collinearity.<h4>Methods</h4>We used principal factor analysis to describe inter-relationships between a large set of Geographic Information System-derived built and socioeconomic environment measures for adolescents in ...[more]

PMID: 20487564

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Project description:BackgroundThere is limited understanding of the extent to which differences in physical activity across the day and week may be associated with mental wellbeing. Such an understanding is needed for better targeting of interventions. In this study, we describe total and temporal patterning of physical activity across the week in adolescents (age 13-14y) and assess their prospective associations with mental wellbeing.Methods1,983 13-14-year-old adolescent participants based in Cambridgeshire and Essex, recruited between 2016 and 2017 into the Get Others Active Trial provided data at baseline and 4 months. Physical activity was measured at baseline using wrist-worn accelerometers across different time segments (whole week, weekday schooltime, weekday out of school, and weekend), and operationalized as average movement-related acceleration for each time segment. Mental Wellbeing at baseline and 4 months was measured using the Warwick Edinburgh MentalWellbeing Scale. Associations between physical activity across different time segments (whole week, weekday schooltime, weekday out of school, and weekend) and mental wellbeing at 4 months were investigated using sex-stratified multi-level regression models, adjusted for covariates, and both adjusted and unadjusted for baseline mental wellbeing.ResultsOur analyses found positive associations between physical activity and mental wellbeing at 4 months, unadjusted for baseline wellbeing. Among girls, positive associations were shown when considering physical activity across the whole week 0.07 (95% CI, 0.03-0.12), and across all separate time periods studied: weekday schooltime 0.07 (95% CI, 0.02-0.11), weekday out-of-school time 0.07 (95% CI, 0.03-0.12), and weekend 0.07 (95% CI, 0.02-0.11). For boys, similar associations were observed for activity across the week 0.07 (95% CI, 0.03-0.11), during weekday schooltime 0.08 (95% CI, 0.04-0.12), and weekday out-of-school time 0.07 (95% CI, 0.03-0.11), but not the weekend 0.01 (95% CI, -0.03-0.05). For both girls and boys, associations were attenuated below significance after adjusting for baseline wellbeing.ConclusionsThis longitudinal analysis showed positive associations between physical activity and later mental wellbeing in both male and female adolescents across most time segments. Higher physical activity throughout the week may be associated with better mental wellbeing in the adolescent population. Further research is required to understand determinants of change in wellbeing over time.Trial registrationRegistration Number: ISRCTN31583496. Registered: 18/02/2014.

Project description:Purpose: Most built environment studies have quantified characteristics of the areas around participants' homes. However, the environmental exposures for physical activity (PA) are spatially dynamic rather than static. Thus, merged accelerometer and global positioning system (GPS) data were utilized to estimate associations between the built environment and PA among adults. Methods: Participants (N = 142) were recruited on trails in Massachusetts and wore an accelerometer and GPS unit for 1-4 days. Two binary outcomes were created: moderate-to-vigorous PA (MVPA vs. light PA-to-sedentary); and light-to-vigorous PA (LVPA vs. sedentary). Five built environment variables were created within 50-meter buffers around GPS points: population density, street density, land use mix (LUM), greenness, and walkability index. Generalized linear mixed models were fit to examine associations between environmental variables and both outcomes, adjusting for demographic covariates. Results: Overall, in the fully adjusted models, greenness was positively associated with MVPA and LVPA (odds ratios [ORs] = 1.15, 95% confidence interval [CI] = 1.03, 1.30 and 1.25, 95% CI = 1.12, 1.41, respectively). In contrast, street density and LUM were negatively associated with MVPA (ORs = 0.69, 95% CI = 0.67, 0.71 and 0.87, 95% CI = 0.78, 0.97, respectively) and LVPA (ORs = 0.79, 95% CI = 0.77, 0.81 and 0.81, 95% CI = 0.74, 0.90, respectively). Negative associations of population density and walkability with both outcomes reached statistical significance, yet the effect sizes were small. Conclusions: Concurrent monitoring of activity with accelerometers and GPS units allowed us to investigate relationships between objectively measured built environment around GPS points and minute-by-minute PA. Negative relationships between street density and LUM and PA contrast evidence from most built environment studies in adults. However, direct comparisons should be made with caution since most previous studies have focused on spatially fixed buffers around home locations, rather than the precise locations where PA occurs.

Project description:BackgroundPhysical activity behaviors among children and adolescents are socioeconomically patterned. Understanding if, and how, the built environment contributes to socioeconomic inequalities in physical activity and for whom built environments are most important, can lead to the identification of intervention entry points to reduce inequalities in physical activity.ObjectiveTo summarize the existing evidence among children and adolescents on (a) whether the built environment mediates the association between socioeconomic position and physical activity and (b) whether socioeconomic position moderates the association between the built environment and physical activity.MethodsA systematic literature search was conducted using PubMed, Embase, PsycINFO and Web of Science. Two independent reviewers screened articles for eligibility, extracted information from included studies and assessed risk of bias with the Quality Assessment Tool for Observational Cohort and Cross-Sectional studies. We performed a narrative evidence synthesis considering the totality of the evidence and by study characteristics such as geographic region, age group, and exposure-outcome assessment methodology. The reporting was conducted in agreement with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement.ResultsA total of 28 papers were included. In general, the studies were of low methodological quality. There was no evidence to support that the built environment functions as a mediator in the relationship between socioeconomic position and physical activity. We observed inconclusive moderation patterns with five studies reporting stronger associations between features of the built environment and physical activity among high socioeconomic positioned youths. Seven studies reported stronger associations among low socioeconomic positioned youth and fourteen studies reported no difference in associations. We observed different moderation patterns across geographical regions (Europe vs. US) indicating that, in Europe, having a walkable neighborhood is important for low socioeconomic positioned youth only. No differences in moderation patterns were observed for younger vs. older children or activity domains.ConclusionCurrent evidence does not support a strong interplay between built environment and socioeconomic position on physical activity in youth. However, given the low quality of the evidence, firm conclusions cannot be made, and additional high-quality research is likely to have substantial impact on the evidence base.

Project description:ObjectivesAlthough socioeconomic status (SES) has been shown to be an important determinant of physical activity (PA) in adults, the association in children and adolescents remains less consistent based on evidence from western developed countries. The purpose of this study, therefore, is to investigate associations between SES and PA among Chinese children and adolescents.MethodsA cross-sectional study was conducted with a self-reported questionnaire in China. The multi-stage stratified cluster sampling method was used, and 2,955 children and adolescents (8-17 years old, 53.4% girls) were enrolled in this study. SES was assessed by measuring parental education levels, perceived family wealth, and Family Affluence Scale II (FAS II). PA was assessed by reliable and valid items from the Health Behavior School-aged Children Surveillance questionnaires. Descriptive statistics were used to report sample characteristics, including demographic characteristics, levels of PA, and SES. The Chi-square test was applied to analyze the differences of PA in gender and school period. Binary logistic regression was used to analyze the association between SES and PA among children and adolescents.ResultsOverall, 10.4% of children and adolescents accumulated moderate-to-vigorous physical activity (MVPA) at least 60 min per day. Boys were more physically active than girls (14.1% vs. 7.2%, p < 0.001). Higher socioeconomic status was positively associated with higher physical activity levels among children and adolescents, especially using FAS and mother education level as SES measures. The association between SES and PA varied by gender and grade group, and the effects of SES are also different on weekdays and weekends.ConclusionThis study found socioeconomic disparities in PA among Chinese children and adolescents, and showed the importance of targeting children and adolescents with low SES intervention priority. Based on these research findings, it is suggested that SES, especially for FAS and mother education level, should be considered when designing and implementing the promotion of regular PA in children and adolescents. Health policymakers may use this information to develop interventions to reduce health inequalities among children and adolescents in the future.

Project description:Researchers investigating relationships between the neighbourhood environment and health first need to decide on the spatial extent of the neighbourhood they are interested in. This decision is an important and ongoing methodological challenge since different methods of defining and delineating neighbourhood boundaries can produce different results. This paper explores this issue in the context of a New Zealand-based study of the relationship between the built environment and multiple measures of physical activity. Geographic information systems were used to measure three built environment attributes-dwelling density, street connectivity, and neighbourhood destination accessibility-using seven different neighbourhood definitions (three administrative unit boundaries, and 500, 800, 1000- and 1500-m road network buffers). The associations between the three built environment measures and five measures of physical activity (mean accelerometer counts per hour, percentage time in moderate-vigorous physical activity, self-reported walking for transport, self-reported walking for recreation and self-reported walking for all purposes) were modelled for each neighbourhood definition. The combination of the choice of neighbourhood definition, built environment measure, and physical activity measure determined whether evidence of an association was detected or not. Results demonstrated that, while there was no single ideal neighbourhood definition, the built environment was most consistently associated with a range of physical activity measures when the 800-m and 1000-m road network buffers were used. For the street connectivity and destination accessibility measures, associations with physical activity were less likely to be detected at smaller scales (less than 800 m). In line with some previous research, this study demonstrated that the choice of neighbourhood definition can influence whether or not an association between the built environment and adults' physical activity is detected or not. This study additionally highlighted the importance of the choice of built environment attribute and physical activity measures. While we identified the 800-m and 1000-m road network buffers as the neighbourhood definitions most consistently associated with a range of physical activity measures, it is important that researchers carefully consider the most appropriate type of neighbourhood definition and scale for the particular aim and participants, especially at smaller scales.

Project description:Physical activity is important for children's health and well-being. Supportiveness for physical activity of home and neighborhood environments may affect children's PA, but most studies are cross-sectional. We examined environmental predictors of change in children's physical activity over two years. Data were from the longitudinal, observational cohort study, 'Neighborhood Impact on Kids'. Participants were children (initially aged 6-12 years) and their parent/caregiver (n = 727 dyads) living in neighborhoods throughout San Diego County, California and King County (Seattle area), Washington, USA. Children's moderate-to-vigorous physical activity (MVPA) was measured using accelerometers at T1 (Time 1 or baseline, 2007-2009) and T2, the two-year follow-up. At T1, parents survey-reported on physical activity (PA) equipment at home and demographics. Neighborhood environment was measured using spatial data in Geographic Information Systems (intersection density; park availability) and in-person audits (informal play space near home; park-based PA facilities; land use; support for walking/cycling). Generalized additive mixed models estimated total effects, then direct effects, of environmental attributes on MVPA at T1. Two-way moderating effects of child's sex and age were examined at T1. To examine associations of environmental exposures with changes in MVPA, we estimated interaction effects of environmental attributes on the association between time and MVPA. On average, children accumulated 146 min/day (standard deviation or SD = 53) of MVPA at T1, and 113 (SD = 58) min/day at T2. There were no significant total or direct effects of environmental attributes on MVPA at T1, and no significant two-way interaction effects of child's age and sex for T1 MVPA. Having informal play spaces proximal to home with more amenities was associated with less MVPA decline from T1 to T2. Higher residential density, higher land use mix, and higher number of PA facilities in nearby parks were unexpectedly associated with greater MVPA decline. Higher quality informal play spaces close to home may help offset declines in MVPA during middle childhood, as they may promote unstructured active play with opportunities for parental or neighbor surveillance. Unexpectedly, environmental factors consistent with higher walkability were associated with greater declines in children's MVPA. As physical activity differs across the lifespan, so may environmental factors that facilitate it.

Dataset Information

Built and socioeconomic environments: patterning and associations with physical activity in U.S. adolescents.

Background

Methods

Results

Conclusions

Publications

Built and socioeconomic environments: patterning and associations with physical activity in U.S. adolescents.

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