Neighborhood Self-Selection: The Role of Pre-Move Health Factors on the Built and Socioeconomic Environment.
Ontology highlight
ABSTRACT:
SUBMITTER: James P
PROVIDER: S-EPMC4626981 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BackgroundBuilt environment and health research have focused on characteristics of home neighborhoods, whereas overall environmental exposures occur over larger spatial ranges.PurposeDifferences in built environment characteristics were analyzed for home and nonhome locations using GPS data.MethodsGPS data collected in 2007-2008 were analyzed for 41 subjects in the Seattle area in 2010. Environmental characteristics for 3.8 million locations were measured using novel GIS data sets called SmartMaps, representing spatially continuous values of local built environment variables in the domains of neighborhood composition, utilitarian destinations, transportation infrastructure, and traffic conditions. Using bootstrap sampling, CIs were estimated for differences in built environment values for home (<833 m of home address) and nonhome (>1666 m) GPS locations.ResultsHome and nonhome built environment values were significantly different for more than 90% of variables across subjects (p<0.001). Only 51% of subjects had higher counts of supermarkets near than away from home. Different measures of neighborhood parks yielded varying results.ConclusionsSmartMaps helped measure local built environment characteristics for a large set of GPS locations. Most subjects had significantly different home and nonhome built environment exposures. Considering the full range of individuals' environmental exposures may improve understanding of effects of the built environment on behavior and health outcomes.
| S-EPMC3318915 | biostudies-literature
Project description:Obesity is a public health problem that is due in part to low levels of physical activity. Physical activity levels are influenced by the built environment. We examined how changes in the built environment affected residents' physical activity levels in a low-income, primarily African American neighborhood in New Orleans.We built a 6-block walking path and installed a school playground in an intervention neighborhood. We measured physical activity levels in this neighborhood and in 2 matched comparison neighborhoods by self-report, using door-to-door surveys, and by direct observations of neighborhood residents outside before (2006) and after (2008) the interventions. We used Pearson ?² tests of independence to assess bivariate associations and logistic regression models to assess the effect of the interventions.Neighborhoods were comparable at baseline in demographic composition, choice of physical activity locations, and percentage of residents who participated in physical activity. Self-reported physical activity increased over time in most neighborhoods. The proportion of residents observed who were active increased significantly in the section of the intervention neighborhood with the path compared with comparison neighborhoods. Among residents who were observed engaging in physical activity, 41% were moderately to vigorously active in the section of the intervention neighborhood with the path compared with 24% and 38% in the comparison neighborhoods at the postintervention measurement (P < .001).Changes to the built environment may increase neighborhood physical activity in low-income, African American neighborhoods.
| S-EPMC3359102 | biostudies-other
Project description:BACKGROUND:Context-free outcome measures, such as overall leisure-time physical activity (LTPA), are habitually applied to study the neighborhood built environment correlates of physical activity. This cross sectional study identifies and empirically tests potential methodological limitations related to the use of context-free measures and discusses how these may help in the interpretation of inconsistent associations between participation in moderate-to-vigorous LTPA and objectively measured neighborhood-level built environment attributes. METHODS:We employ a public participation geographic information system (PPGIS), an advanced participatory mapping method, to study the spatial distribution of moderate-to-vigorous LTPA among adult urban Finnish residents (n 1322). Secondary sources of GIS land-use and sport facility data were used to disaggregate respondent-mapped LTPA by the behavioral context, such as indoor and outdoor sport facilities, green spaces, and other public open spaces. Associations between the use of the identified LTPA settings and a range of objectively measured neighborhood built environment attributes were studied with multilevel logistic regression models. RESULTS:Disaggregated by behavioral context, we observed varied and partly opposite built environment correlates for LTPA. The use of indoor and outdoor sport facilities showed no significant associations with their neighborhood availability, but were significantly associated with personal-level attributes. By contrast, participation in LTPA in green and built public open space shared significant associations with access to and availability of neighborhood green space that persisted after controlling for personal-level covariates. Moreover, neighborhood distances up to 1600 m poorly captured participation in moderate-to-vigorous LTPA, as, on average, 40% of visits were located further from home. However, we found the immediate home environment to be an important LTPA setting for the least active participants. CONCLUSIONS:This study demonstrates that LTPA can be a highly heterogeneous measure regarding both the spatial distribution and the environmental correlates of behavioral contexts. The results show that context-free LTPA outcome measures yield inconsistent associations with built environment exposure variables, challenging the applicability of such measures in designing neighborhood-level built environment interventions.
| S-EPMC7488407 | biostudies-literature
Project description:Understanding contextual influences on obesity requires comparison of heterogeneous communities and concurrent assessment of multiple contextual domains. We used a theoretically-based measurement model to assess multidimensional socioeconomic and built environment factors theorized to influence childhood obesity across a diverse geography ranging from rural to urban. Confirmatory factor analysis specified four factors-community socioeconomic deprivation (CSED), food outlet abundance (FOOD), fitness and recreational assets (FIT), and utilitarian physical activity favorability (UTIL)-which were assigned to communities (townships, boroughs, city census tracts) in 37 Pennsylvania counties. Using electronic health records from 2001 to 2012 from 163,820 youth aged 3-18 years from 1288 communities, we conducted multilevel linear regression analyses with factor quartiles and their cross products with age, age2, and age3 to test whether community factors impacted body mass index (BMI) growth trajectories. Models controlled for sex, age, race/ethnicity, and Medical Assistance. Factor scores were lowest in townships, indicating less deprivation, fewer food and physical activity outlets, and lower utilitarian physical activity favorability. BMI at average age was lower in townships versus boroughs (beta [SE]) (0.217 [0.027], P < 0.001) and cities (0.378 [0.036], P < 0.001), as was BMI growth over time. Factor distributions across community types lacked overlap, requiring stratified analyses to avoid extrapolation. In townships, FOOD, UTIL, and FIT were inversely associated with BMI trajectories. Across community types, youth in the lowest (versus higher) CSED quartiles had lower BMI at average age and slower BMI growth, signifying the importance of community deprivation to the obesogenicity of environments.
| S-EPMC6637223 | biostudies-literature
Project description:IntroductionVarious built environment factors might influence certain health behaviors and outcomes. Reliable, resource-efficient methods that are feasible for assessing built environment characteristics across large geographies are needed for larger, more robust studies. This paper reports the item response prevalence, reliability, and rating time of a new virtual neighborhood audit protocol, drop-and-spin auditing, developed for assessment of walkability and physical disorder characteristics across large geographic areas.MethodsDrop-and-spin auditing, a method where a Google Street View scene was rated by spinning 360° around a point location, was developed using a modified version of the virtual audit tool Computer Assisted Neighborhood Visual Assessment System. Approximately 8,000 locations within Essex County, New Jersey were assessed by 11 trained auditors. Using a standardized protocol, 32 built environment items per a location within Google Street View were audited. Test-retest and inter-rater ? statistics were from a 5% subsample of locations. Data were collected in 2017-2018 and analyzed in 2018.ResultsRoughly 70% of Google Street View scenes had sidewalks. Among those, two thirds were in good condition. At least 5 obvious items of garbage or litter were present in 41% of Google Street View scenes. Maximum test-retest reliability indicated substantial agreement (? ?0.61) for all items. Inter-rater reliability of each item, generally, was lower than test-retest reliability. The median time to rate each item was 7.3 seconds.ConclusionsCompared with segment-based protocols, drop-and-spin virtual neighborhood auditing is quicker and similarly reliable for assessing built environment characteristics. Assessment of large geographies may be more feasible using drop-and-spin virtual auditing.
| S-EPMC6927542 | biostudies-literature
Project description:Optimization of existing measurement tools is necessary to explore links between aspects of the neighborhood built environment and health behaviors or outcomes. We evaluate a scoring method for virtual neighborhood audits utilizing the Active Neighborhood Checklist (the Checklist), a neighborhood audit measure, and assess street segment representativeness in low-income neighborhoods. Eighty-two home neighborhoods of Washington, D.C. Cardiovascular Health/Needs Assessment (NCT01927783) participants were audited using Google Street View imagery and the Checklist (five sections with 89 total questions). Twelve street segments per home address were assessed for (1) Land-Use Type; (2) Public Transportation Availability; (3) Street Characteristics; (4) Environment Quality and (5) Sidewalks/Walking/Biking features. Checklist items were scored 0-2 points/question. A combinations algorithm was developed to assess street segments' representativeness. Spearman correlations were calculated between built environment quality scores and Walk Score®, a validated neighborhood walkability measure. Street segment quality scores ranged 10-47 (Mean = 29.4 ± 6.9) and overall neighborhood quality scores, 172-475 (Mean = 352.3 ± 63.6). Walk scores® ranged 0-91 (Mean = 46.7 ± 26.3). Street segment combinations' correlation coefficients ranged 0.75-1.0. Significant positive correlations were found between overall neighborhood quality scores, four of the five Checklist subsection scores, and Walk Scores® (r = 0.62, p < 0.001). This scoring method adequately captures neighborhood features in low-income, residential areas and may aid in delineating impact of specific built environment features on health behaviors and outcomes.
| S-EPMC5369109 | biostudies-literature
Project description:BackgroundIn the background of an aging population, the risk of cognitive impairment in the older population is prominent. Exposure to complex neighborhood built environments may be beneficial to the cognitive health of older adults, and the purpose of this study was to systematically review the scientific evidence on the effects of neighborhood built environments on cognitive function in older adults.MethodsKeywords and references were searched in Web of Science, Pubmed, PsycINFO, and MEDLINE. Studies examining the relationship between the built environment and cognitive function in older adults were included. The neighborhood built environment as an independent variable was classified according to seven aspects: density, design, diversity, destination accessibility, public transportation distance, blue/green space, and built environment quality. The cognitive function as the dependent variable was classified according to overall cognitive function, domain-specific cognitive function, and incidence of dementia. The quality of the included literature was assessed using the National Institutes of Health's Observational Cohort and Cross-Sectional Study Quality Assessment Tool.ResultsA total of 56 studies were included that met the inclusion criteria, including 31 cross-sectional studies, 23 longitudinal studies, 1 cross-sectional study design combined with a case-control design, and 1 longitudinal study design combined with a case-control design. Most of the studies reviewed indicate that the built environment factors that were positively associated with cognitive function in older adults were population density, street connectivity, walkability, number of public transportation stops around the residence, land use mix, neighborhood resources, green space, and quality of the neighborhood built environment. Built environment factors that were negatively associated with cognitive function in older adults were street integration, distance from residence to main road. The relationship between residential density, destination accessibility, and blue space with cognitive function in older adults needs to be further explored.ConclusionPreliminary evidence suggests an association between the neighborhood built environment and cognitive function in older adults. The causal relationship between the built environment and cognitive function can be further explored in the future using standardized and combined subjective and objective assessment methods, and longitudinal or quasi-experimental study designs. For public health interventions on the cognitive health of older adults, it is recommended that relevant authorities include the neighborhood built environment in their intervention programs.
| S-EPMC10898015 | biostudies-literature
Project description:Built environment research is dominated by cross-sectional designs, which are particularly vulnerable to residential self-selection bias resulting from health-related attitudes, neighborhood preferences, or other unmeasured characteristics related to both neighborhood choice and health-related outcomes.We used cohort data from the National Longitudinal Study of Adolescent Health (United States; Wave I, 1994-95; Wave III, 2001-02; n = 12,701) and a time-varying geographic information system. Longitudinal relationships between moderate to vigorous physical activity (MVPA) bouts and built and socioeconomic environment measures (landcover diversity, pay and public physical activity facilities per 10,000 population, street connectivity, median household income, and crime rate) from adolescence to young adulthood were estimated using random effects models (biased by unmeasured confounders) and fixed effects models (within-person estimator, which adjusts for unmeasured confounders that are stable over time).Random effects models yielded null associations except for negative crime-MVPA associations [coefficient (95% CI): -0.056 (-0.083, -0.029) in males, -0.061 (-0.090, -0.033) in females]. After controlling for measured and time invariant unmeasured characteristics using within-person estimators, MVPA was higher with greater physical activity pay facilities in males [coefficient (95% CI): 0.024 (0.006, 0.042)], and lower with higher crime rates in males [coefficient (95% CI): -0.107 (-0.140, -0.075)] and females [coefficient (95% CI): -0.046 (-0.083, -0.009)]. Other associations were null or in the counter-intuitive direction.Comparison of within-person estimates to estimates unadjusted for unmeasured characteristics suggest that residential self-selection can bias associations toward the null, as opposed to its typical characterization as a positive confounder. Differential environment-MVPA associations by residential relocation suggest that studies examining changes following residential relocation may be vulnerable to selection bias. The authors discuss complexities of adjusting for residential self-selection and residential relocation, particularly during the adolescent to young adult transition.
| S-EPMC2959083 | biostudies-other
Project description:To date, research has rarely considered the role of health in shaping characteristics of the neighborhood, including mobility patterns. We explored whether individual health status shapes and constrains where individuals live. Using the National Longitudinal Study of Adolescent Health data, we examined whether 16 health indicators predicted moving, move quality, and desire to move. 3.8% of adolescents (n=490) reported a move in the past year. In the unadjusted models, 10 health indicators were associated with moving; the magnitude of association for these health indicators was similar to socio-demographic characteristics. 7 of these health-moving associations persisted after adjusting for covariates. Health was also associated with moving quality, with a greater number of past year health problems in the child being associated with moving to a lower income neighborhood and parent disability or poor health being associated with moving to a higher income neighborhood. Almost every poor health status indicator was associated with a greater desire to move. Findings suggest that health status influences moving, and a reciprocal framework is more appropriate for examining health-neighborhood linkages.
| S-EPMC4467831 | biostudies-literature