Effects of buffer size and shape on associations between the built environment and energy balance.
Ontology highlight
ABSTRACT:
SUBMITTER: James P
PROVIDER: S-EPMC4028172 | biostudies-literature | 2014 May
REPOSITORIES: biostudies-literature
Publications
Effects of buffer size and shape on associations between the built environment and energy balance.
James Peter P Berrigan David D Hart Jaime E JE Hipp J Aaron JA Hoehner Christine M CM Kerr Jacqueline J Major Jacqueline M JM Oka Masayoshi M Laden Francine F
Health & place 20140307
Uncertainty in the relevant spatial context may drive heterogeneity in findings on the built environment and energy balance. To estimate the effect of this uncertainty, we conducted a sensitivity analysis defining intersection and business densities and counts within different buffer sizes and shapes on associations with self-reported walking and body mass index. Linear regression results indicated that the scale and shape of buffers influenced study results and may partly explain the inconsiste ...[more]
Similar Datasets
Project description:Built environment factors constrain individual level behaviors and choices, and thus are receiving increasing attention to assess their influence on health. Traditional regression methods have been widely used to examine associations between built environment measures and health outcomes, where a fixed, prespecified spatial scale (e.g., 1 mile buffer) is used to construct environment measures. However, the spatial scale for these associations remains largely unknown and misspecifying it introduces bias. We propose the use of distributed lag models (DLMs) to describe the association between built environment features and health as a function of distance from the locations of interest and circumvent a-priori selection of a spatial scale. Based on simulation studies, we demonstrate that traditional regression models produce associations biased away from the null when there is spatial correlation among the built environment features. Inference based on DLMs is robust under a range of scenarios of the built environment. We use this innovative application of DLMs to examine the association between the availability of convenience stores near California public schools, which may affect children's dietary choices both through direct access to junk food and exposure to advertisement, and children's body mass index z scores.
| S-EPMC5065688 | biostudies-literature
Project description:BackgroundFew studies have assessed the predictors of changes in commuting. This study investigated the associations between physical environmental characteristics and changes in active commuting.MethodsAdults from the population-based European Prospective Investigation into Cancer (EPIC)-Norfolk cohort self-reported commuting patterns in 2000 and 2007. Active commuters were defined as those who reported 'always' or 'usually' walking or cycling to work. Environmental attributes around the home and route were assessed using Geographical Information Systems. Associations between potential environmental predictors and uptake and maintenance of active commuting were modelled using logistic regression, adjusting for age, sex and BMI.ResultsOf the 2757 participants (62% female, median baseline age: 52, IQR: 50-56 years), most were passive commuters at baseline (76%, n = 2099) and did not change their usual commute mode over 7 years (82%, n = 2277). In multivariable regression models, participants living further from work were less likely to take up active commuting and those living in neighbourhoods with more streetlights were more likely to take up active commuting (both p < 0.05). Findings for maintenance were similar: participants living further from work (over 10 km, OR: 0.06; 95% CI: 0.25 to 0.13) and had a main or secondary road on route were more likely to maintain their active commuting (OR: 0.52; 95% CI: 0.28 to 0.98). Those living in neighbourhoods with greater density of employment locations were more likely to maintain their active commuting.ConclusionsCo-locating residential and employment centres as well as redesigning urban areas to improve safety for pedestrians and cyclists may encourage active commuting. Future evaluative studies should seek to assess the effects of redesigning the built environment on active commuting and physical activity.
| S-EPMC5527401 | biostudies-literature
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.
| S-EPMC6540146 | biostudies-literature
Project description:The determinants that underlie a healthy or unhealthy pregnancy are complex and not well understood. We assess the relationship between the built environment and maternal psychosocial status using directly observed residential neighborhood characteristics (housing damage, property disorder, tenure status, vacancy, security measures, violent crime, and nuisances) and a wide range of psychosocial attributes (interpersonal support evaluation list, self-efficacy, John Henryism active coping, negative partner support, Perceived Stress Scale, perceived racism, Center for Epidemiologic Studies-Depression) on a pregnant cohort of women living in the urban core of Durham, NC, USA. We found some associations between built environment characteristic and psychosocial health varied by exposure categorization approach, while others (residence in environments with more rental property is associated with higher reported active coping and negative partner support) were consistent across exposure categorizations. This study outlines specific neighborhood characteristics that are modifiable risk markers and therefore important targets for increased research and public health intervention.
| S-EPMC3795199 | biostudies-other
Project description:The aim of this study was to determine the associations between body size and built environment walkability variables, as well as the mediating role of physical activity and sedentary behaviours with body size.Objective environment, body size (body mass index (BMI), waist circumference (WC)), and sedentary time and physical activity data were collected from a random selection of 2033 adults aged 20-65 years living in 48 neighbourhoods across four New Zealand cities. Multilevel regression models were calculated for each comparison between body size outcome and built environment exposure.Street connectivity and neighborhood destination accessibility were significant predictors of body size (1 SDchange predicted a 1.27 to 1.41 % reduction in BMI and a 1.76 to 2.29 % reduction in WC). Significantrelationships were also observed for streetscape (1 SD change predicted a 1.33 % reduction in BMI) anddwelling density (1 SD change predicted a 1.97 % reduction in BMI). Mediation analyses revealed asignificant mediating effect of physical activity on the relationships between body size and street connectivity and neighbourhood destination accessibility (explaining between 10.4 and 14.6 % of the total effect). No significant mediating effect of sedentary behaviour was found. Findings from this cross-sectional study of a random selection of New Zealand adults are consistent with international research. Findings are limited to individual environment features only; conclusions cannot be drawn about the cumulative and combined effect of individual features on outcomes.Built environment features were associated with body size in the expected directions. Objectively-assessed physical activity mediated observed built environment-body size relationships.
| S-EPMC4581495 | biostudies-literature
Project description:Neighborhood attributes have been shown to influence health, but advances in neighborhood research has been constrained by the lack of neighborhood data for many geographical areas and few neighborhood studies examine features of nonmetropolitan locations. We leveraged a massive source of Google Street View (GSV) images and computer vision to automatically characterize national neighborhood built environments. Using road network data and Google Street View API, from December 15, 2017-May 14, 2018 we retrieved over 16 million GSV images of street intersections across the United States. Computer vision was applied to label each image. We implemented regression models to estimate associations between built environments and county health outcomes, controlling for county-level demographics, economics, and population density. At the county level, greater presence of highways was related to lower chronic diseases and premature mortality. Areas characterized by street view images as 'rural' (having limited infrastructure) had higher obesity, diabetes, fair/poor self-rated health, premature mortality, physical distress, physical inactivity and teen birth rates but lower rates of excessive drinking. Analyses at the census tract level for 500 cities revealed similar adverse associations as was seen at the county level for neighborhood indicators of less urban development. Possible mechanisms include the greater abundance of services and facilities found in more developed areas with roads, enabling access to places and resources for promoting health. GSV images represents an underutilized resource for building national data on neighborhoods and examining the influence of built environments on community health outcomes across the United States.
| S-EPMC6488538 | biostudies-literature
Project description:The importance of health-promoting neighborhoods has long been recognized, and characteristics of local built environments are among the social determinants of health. People with disability are more likely than other population groups to experience geographic mobility and cost restrictions, and to be reliant on 'opportunity structures' available locally. We conducted an ecological analysis to explore associations between area-level disability prevalence for people aged 15-64 years and area-level built environment characteristics in Australia's 21 largest cities. Overall, disability was more prevalent in areas with lower walkability and lower local availability of various neighborhood amenities such as public transport, healthier food options, public open space, physical activity and recreation destinations and health and mental health services. These patterns of lower liveability in areas of higher disability prevalence were observed in major cities but not in regional cities. Our findings suggest that geographically targeted interventions to improve access to health-enhancing neighborhood infrastructure could reduce disability-related inequalities in the social determinants of health.
| S-EPMC7662552 | biostudies-literature
Project description:BackgroundTransport walking has drawn growing interest due to its potential to increase levels of physical activities and reduce reliance on vehicles. While existing studies have compared built environment-health associations between Euclidean buffers and network buffers, no studies have systematically quantified the extent of bias in health effect estimates when exposures are measured in different buffers. Further, prior studies have done the comparisons focusing on only one or two geographic regions, limiting generalizability and restricting ability to test whether direction or magnitude of bias are different by context. This study aimed to quantify the degree of bias in associations between built environment exposures and transport walking when exposures were operationalized using Euclidean buffers rather than network buffers in diverse contexts.MethodsWe performed a simulations study to systematically evaluate the degree of bias in associations between built environment exposures in Euclidean buffers and network buffers and transport walking, assuming network buffers more accurately captured true exposures. Additionally, we used empirical data from a multi-ethnic, multi-site cohort to compare associations between built environment amenities and walking for transport where built environment exposures were derived using Euclidean buffers versus network buffers.ResultsSimulation results found that the bias induced by using Euclidean buffer models was consistently negative across the six study sites (ranging from -80% to -20%), suggesting built environment exposures measured using Euclidean buffers underestimate health effects on transport walking. Percent bias was uniformly smaller for the larger 5 km scale than the 1 km and 0.25 km spatial scales, independent of site or built environment categories. Empirical findings aligned with the simulation results: built environment-health associations were stronger for built environment exposures operationalized using network buffers than using Euclidean buffers.ConclusionThis study is the first to quantify the extent of bias in the magnitude of the associations between built environment exposures and transport walking when the former are measured in Euclidean buffers vs. network buffers, informing future research to carefully conceptualize appropriate distance-based buffer metrics in order to better approximate real geographic contexts. It also helps contextualize existing research in the field that used Euclidean buffers when that were the only option. Further, this study provides an example of the uncertain geographic context problem.
| S-EPMC9482303 | biostudies-literature
Project description:Although dense neighborhood built environments support increased physical activity and lower obesity, these features may also disturb sleep. Therefore, we sought to understand the association between the built environment and objectively measured sleep. From 2010 to 2013, we analyzed data from examination 5 of the Multi-Ethnic Study of Atherosclerosis, a diverse population from 6 US cities. We fit multilevel models that assessed the association between the built environment (Street Smart Walk Score, social engagement destinations, street intersections, and population density) and sleep duration or efficiency from 1-week wrist actigraphy in 1,889 individuals. After adjustment for covariates, a 1-standard-deviation increase in Street Smart Walk Score was associated with 23% higher odds of short sleep duration (?6 hours; odds ratio = 1.2, 95% confidence interval: 1.0, 1.4), as well as shorter average sleep duration (mean difference = -8.1 minutes, 95% confidence interval: -12.1, -4.2). Results were consistent across other built environment measures. Associations were attenuated after adjustment for survey-based measure of neighborhood noise. Dense neighborhood development may have multiple health consequence. In promoting denser neighborhoods to increase walkability, it is important to also implement strategies that reduce the adverse impacts of this development on sleep, such as noise reductions efforts.
| S-EPMC5928457 | biostudies-literature