Neighborhood Built Environment Characteristics Research Articles

Association between neighborhood built environment and resident leisure walking – A cross-sectional study in China

IntroductionPhysical activity has a vital influence in promoting health and sustainable development of society and environment. Leisure walking, as a widely embraced low-cost physical activity, can effectively help reduce the prevalence of chronic diseases and enhance health. Improving the neighborhood built environment may affect the quality of leisure walking, as an activity that depends upon features of the built environment. MethodsUsing data from the 2015 China Health and Nutrition Survey, we obtained a sample of 1006 residents from 134 neighborhoods in nine provinces east of the Heihe-Tengchong Line in China. We used logit mixed-effect models and linear mixed-effect models to measure associations between neighborhood built environment characteristics and leisure walking durations within urban, suburban, county-seat, and rural neighborhoods. We differentiated between leisure walking on weekdays and weekends. ResultsResidents in rural neighborhoods that had dirt or paved roads had shorter leisure walking durations compared with residents in rural neighborhoods that had mainly gravel roads. Residents in urban neighborhoods that had gyms had shorter leisure walking durations compared with residents in urban neighborhoods for which the nearest gym was outside the neighborhood. The presence of parks did not show any significant association with leisure walking durations in any neighborhood type. The presence of bus stops was associated with greater leisure walking durations in county-seat neighborhoods, as were more restaurants in suburban neighborhoods. ConclusionSeemingly mundane built environment factors such as road pavement type appeared to be more closely associated with the duration of leisure walking than previously studied parks. Different built environment factors were associated with leisure walking duration within specific neighborhood types. Further research should focus on the characteristics of leisure walking behavior in various spatial contexts and during different time periods to continue to reveal the complex interactions between built environment factors and leisure walking.

Validation of the physical activity neighborhood environment scale using geographic information systems among urban men and women in regional China

AimsTo examine the concurrent validity of the Chinese version of Physical Activity Neighborhood Environment Scale (PANES-CHN) among urban adults in regional China. MethodsWith multistage sampling approaches, 801 eligible urban adults aged 35–74 years were recruited from Nanjing municipality of China between July and September of 2019. The neighbourhood built environment features were measured subjectively with PANES-CHN and objectively with geographic information system. The concurrent validity of PANES was assessed using Spearman’s correlations (rs). ResultsAmong the total 801 participants, the mean age was 54.4 (standard deviation = 11.5), while 48.7 % were men. Overall, of all the five objectively-measurable built environment characteristics, the Spearman correlations were examined significant between subjective and objective measurements for commercial facilities (item 2) (rs = 0.19, 95CI%=0.12, 0.25), recreational facilities (item 6) (rs = 0.10, 95CI%=0.02, 0.16), traffic junctions (item 12) (rs = 0.15, 95CI%=0.07, 0.22), medical/education facilities (item 17) (rs = 0.22, 95CI%=0.15, 0.29), but not for public transport stops. Similar scenarios were observed for participants aged 35–60 years, with sufficient physical activity, men or women. The rs value for medical/education facilities (item 17) was significantly higher in participants aged 35–59 years (0.28 vs. 0.13; p = 0.04) than those aged 60 + years. ConclusionsPANES-CHN generally has an acceptable validity for assessing built environment characteristics among urban adults in China, which implies that PANES-CHN can be used to measure built environment attributes in health-related population studies.

Neighborhood built environment, obesity, and diabetes: A Utah siblings study

BackgroundThis study utilizes innovative computer vision methods alongside Google Street View images to characterize neighborhood built environments across Utah. MethodsConvolutional Neural Networks were used to create indicators of street greenness, crosswalks, and building type on 1.4 million Google Street View images. The demographic and medical profiles of Utah residents came from the Utah Population Database (UPDB). We implemented hierarchical linear models with individuals nested within zip codes to estimate associations between neighborhood built environment features and individual-level obesity and diabetes, controlling for individual- and zip code-level characteristics (n = 1,899,175 adults living in Utah in 2015). Sibling random effects models were implemented to account for shared family attributes among siblings (n = 972,150) and twins (n = 14,122). ResultsConsistent with prior neighborhood research, the variance partition coefficients (VPC) of our unadjusted models nesting individuals within zip codes were relatively small (0.5%–5.3%), except for HbA1c (VPC = 23%), suggesting a small percentage of the outcome variance is at the zip code-level. However, proportional change in variance (PCV) attributable to zip codes after the inclusion of neighborhood built environment variables and covariates ranged between 11% and 67%, suggesting that these characteristics account for a substantial portion of the zip code-level effects. Non-single-family homes (indicator of mixed land use), sidewalks (indicator of walkability), and green streets (indicator of neighborhood aesthetics) were associated with reduced diabetes and obesity. Zip codes in the third tertile for non-single-family homes were associated with a 15% reduction (PR: 0.85; 95% CI: 0.79, 0.91) in obesity and a 20% reduction (PR: 0.80; 95% CI: 0.70, 0.91) in diabetes. This tertile was also associated with a BMI reduction of −0.68 kg/m2 (95% CI: −0.95, −0.40) ConclusionWe observe associations between neighborhood characteristics and chronic diseases, accounting for biological, social, and cultural factors shared among siblings in this large population-based study.

Road Traffic Injuries and the Built Environment in Bogotá, Colombia, 2015-2019: A Cross-Sectional Analysis.

Nine in 10 road traffic deaths occur in low- and middle-income countries (LMICs). Despite this disproportionate burden, few studies have examined built environment correlates of road traffic injury in these settings, including in Latin America. We examined road traffic collisions in Bogotá, Colombia, occurring between 2015 and 2019, and assessed the association between neighborhood-level built environment features and pedestrian injury and death. We used descriptive statistics to characterize all police-reported road traffic collisions that occurred in Bogotá between 2015 and 2019. Cluster detection was used to identify spatial clustering of pedestrian collisions. Adjusted multivariate Poisson regression models were fit to examine associations between several neighborhood-built environment features and rate of pedestrian road traffic injury and death. A total of 173,443 police-reported traffic collisions occurred in Bogotá between 2015 and 2019. Pedestrians made up about 25% of road traffic injuries and 50% of road traffic deaths in Bogotá between 2015 and 2019. Pedestrian collisions were spatially clustered in the southwestern region of Bogotá. Neighborhoods with more street trees (RR, 0.90; 95% CI, 0.82-0.98), traffic signals (0.89, 0.81-0.99), and bus stops (0.89, 0.82-0.97) were associated with lower pedestrian road traffic deaths. Neighborhoods with greater density of large roads were associated with higher pedestrian injury. Our findings highlight the potential for pedestrian-friendly infrastructure to promote safer interactions between pedestrians and motorists in Bogotá and in similar urban contexts globally.

The neighborhood built environment and COVID-19 hospitalizations.

Research on the associations between the built environment and COVID-19 outcomes has mostly focused on incidence and mortality. Also, few studies on the built environment and COVID-19 have controlled for individual-level characteristics across large samples. In this study, we examine whether neighborhood built environment characteristics are associated with hospitalization in a cohort of 18,042 individuals who tested positive for SARS-CoV-2 between May and December 2020 in the Denver metropolitan area, USA. We use Poisson models with robust standard errors that control for spatial dependence and several individual-level demographic characteristics and comorbidity conditions. In multivariate models, we find that among individuals with SARS-CoV-2 infection, those living in multi-family housing units and/or in places with higher particulate matter (PM2.5) have a higher incident rate ratio (IRR) of hospitalization. We also find that higher walkability, higher bikeability, and lower public transit access are linked to a lower IRR of hospitalization. In multivariate models, we did not find associations between green space measures and the IRR of hospitalization. Results for non-Hispanic white and Latinx individuals highlight substantial differences: higher PM2.5 levels have stronger positive associations with the IRR of hospitalization for Latinx individuals, and density and overcrowding show stronger associations for non-Hispanic white individuals. Our results show that the neighborhood built environment might pose an independent risk for COVID-19 hospitalization. Our results may inform public health and urban planning initiatives to lower the risk of hospitalization linked to COVID-19 and other respiratory pathogens.

Association Between Perceived and Objective Measures of School Neighbourhood Built Environment and Active Transport to School in New Zealand Adolescents

School neighbourhood built environment (BE) characteristics are related to active transport to school (ATS) among adolescents. This study examined objectively measured and perceived school neighbourhood BE correlates of ATS in adolescents and compared school neighbourhood BE features in rural versus small-to-medium urban areas. We analysed data from adolescents (n=95; 68.4% under 16 years of age; 58.9% female) from 11 schools located in small-to-medium urban areas and rural settings in Otago, New Zealand, who were familiar with their school neighbourhood environment and living within 4.8 km from school. Adolescents reported perceptions of their school neighbourhood using a modified version of Neighbourhood Environment Walkability Scale for Youth (NEWS-Y) questionnaire. Objectively measured BE features were generated using Geographic Information Systems (GIS). In a multivariate analysis, perceived residential density (odds ratio (95% CI): 0.17 (0.04, 0.82)) and traffic safety concerns (0.13(0.02, 0.95)) were negatively associated with adolescents' ATS rates, but those associations were no longer significant once distance to school was taken into account. Compared to small-to-medium urban area schools, perceived land use mix diversity and recreational facilities and objectively measured intersection density in school neighbourhoods were higher, whereas perceived residential density and land use mix accessibility and objectively measured neighbourhood walkability were lower in rural schools (all p < 0.05). Future initiatives should address both perceived and objectively measured school neighbourhood BE to promote ATS among adolescents.

Examining the Contribution of the Neighborhood Built Environment to the Relationship Between Neighborhood Disadvantage and Early Childhood Development in 205,000 Australian Children.

We examined associations between neighborhood built environment features and early childhood development (ECD), and tested the contribution of the built environment to associations between neighborhood disadvantage and ECD. Spatial neighborhood built environment measures were linked to participant addresses in the 2015 Australian Early Development Census (AEDC) for children ∼5 years old living in Australia's 21 most populous cities. The 2015 AEDC contains teacher-reported national data on five key child development domains for children in their first year of formal full-time schooling (approximately 5 years old). AEDC scores were classified as 'developmentally vulnerable' (≤10th centile). Using multilevel modeling, 44 built environment measures were tested with developmental vulnerability on at least one domain of the AEDC, adjusting for socioeconomic factors and neighborhood disadvantage. The dataset consisted of 205,030 children; 89.2% living in major cities. In major cities, children with more early childhood education and care services (OR 0.997) and preschool services (OR 0.991) exceeding Australian standards, and access to healthier food outlets within 3200 m of their home (OR 0.999) had decreased odds of developmental vulnerability, controlling for socioeconomic factors and neighborhood disadvantage. Neighborhood disadvantage remained significantly associated with developmental vulnerability after adjustment for child/family variables and neighborhood built environment characteristics. The neighborhood built environment had small effects on the neighborhood disadvantage-ECD relationship at the national level. Few built environment measures were associated with ECD. Small effects at the population level may have wide-ranging impacts; modifying the built environment at scale are promising levers for supporting good child outcomes.

Using Convolutional Neural Networks to Derive Neighborhood Built Environments from Google Street View Images and Examine Their Associations with Health Outcomes.

Built environment neighborhood characteristics are difficult to measure and assess on a large scale. Consequently, there is a lack of sufficient data that can help us investigate neighborhood characteristics as structural determinants of health on a national level. The objective of this study is to utilize publicly available Google Street View images as a data source for characterizing built environments and to examine the influence of built environments on chronic diseases and health behaviors in the United States. Data were collected by processing 164 million Google Street View images from November 2019 across the United States. Convolutional Neural Networks, a class of multi-layer deep neural networks, were used to extract features of the built environment. Validation analyses found accuracies of 82% or higher across neighborhood characteristics. In regression analyses controlling for census tract sociodemographics, we find that single-lane roads (an indicator of lower urban development) were linked with chronic conditions and worse mental health. Walkability and urbanicity indicators such as crosswalks, sidewalks, and two or more cars were associated with better health, including reduction in depression, obesity, high blood pressure, and high cholesterol. Street signs and streetlights were also found to be associated with decreased chronic conditions. Chain link fence (physical disorder indicator) was generally associated with poorer mental health. Living in neighborhoods with a built environment that supports social interaction and physical activity can lead to positive health outcomes. Computer vision models using manually annotated Google Street View images as a training dataset were able to accurately identify neighborhood built environment characteristics. These methods increases the feasibility, scale, and efficiency of neighborhood studies on health.

Adolescents' perceptions of school neighbourhood built environment for walking and cycling to school

Walking is a more common transport mode to school than cycling among adolescents in many countries worldwide. Adolescents' and their parents' have different perceptions of walking versus cycling to school. This study compared adolescents' perceptions of school neighbourhood built environment characteristics for walking versus cycling to school. Adolescents familiar with their school neighbourhoods (n=411; age: 15.0 ± 1.2 years; male: 31.3%) from six secondary schools in Dunedin, New Zealand completed an online survey about their travel to school and perceptions of their school neighbourhood environments for walking and cycling to school. Overall, 32.8% of adolescents walked to school, and only 1.2% cycled. More adolescents reported sufficient footpaths than cycle paths (77.9% vs 42.3%) in their school neighbourhoods. Compared to walking, adolescents reported that their school neighbourhood environments provided less support for cycling to school, including fewer crossings/signals for cyclists versus pedestrians (52.8% vs 69.3%), fewer street lights (cycling vs walking; 57.9% vs 70.3%) and fewer destinations within easy cycling versus walking distance from their school (65.5% vs 50.4%) (all p<0.05). Active transport users perceived lower traffic volume, higher traffic speed, and fewer hilly streets along the walking and cycling routes to school than motorised and mixed transport users (all p<0.05). Future active transport interventions in school neighbourhoods need to be tailored to address walking- and/or cycling-specific barriers, including built environment and traffic safety in a local context.

Data to Decisions: Methods to Create Neighbourhood Built Environment Indicators Relevant for Early Childhood Development.

Healthy development in the early years lays the foundations for children’s ongoing physical, emotional, and social development. Children develop in multiple contexts, including their local neighbourhood. Neighbourhood-built environment characteristics, such as housing, walkability, traffic exposure, availability of services, facilities, and parks, are associated with a range of health and wellbeing outcomes across the life course, but evidence with early years’ outcomes is still emerging. Data linkage techniques were used to assemble a dataset of spatial (objectively-measured) neighbourhood-built environment (BE) measures linked to participant addresses in the 2015 Australian Early Development Census (AEDC) for children living in the 21 most populous urban and regional Australian cities (n = 235,655) to help address this gap. This paper describes the methods used to develop this dataset. This linked dataset (AEDC-BE) is the first of its kind worldwide, enabling opportunities for identifying which features of the built environment are associated with ECD across Australia at scale, allow comparisons between diverse contexts, and the identification of where best to intervene. National data coverage provides statistical power to model real-world complexities, such as differences by city, state/territory, and remoteness. The neighbourhood-built environment can be modified by policy and practice at scale, and has been identified as a way to help reduce inequitable early childhood development outcomes.

The Impacts of Housing Characteristics and Built-Environment Features on Mental Health.

In this study, we examined the relationships between housing characteristics, neighborhood built-environment features, and people’s mental health in Hong Kong, an Asian city well known for its high-density and high-rise housing. The potential mediating effects of people’s perceived living environment were also considered in the analysis. We collected data from 221 participants from two communities in Hong Kong, i.e., Sham Shui Po (SSP) and Tin Shui Wai (TSW), using a stratified random sampling approach. Big datasets were also used to derive relevant built-environment features at the street block level. We used structural equation modeling to explore the complex relationships among housing characteristics, built-environment features, and mental health. The results indicate that the associations between built-environment quality and people’s mental health are weak. For communities with relatively poor housing conditions (i.e., SSP in this study), the impact of housing characteristics on mental health may be more direct; for communities with relatively good housing conditions (i.e., TSW in this study), the effect of housing characteristics on mental health may be indirect. Our findings shed light on the importance of considering different contexts in developing policies related to housing and built environment and mental health.

The built environment and early childhood development: qualitative evidence from disadvantaged Australian communities

ABSTRACT This paper explores neighborhood-built environment features related to ‘better than expected’ and ‘as expected’ early childhood development outcomes (ECD) in 14 Australian disadvantaged communities. This paper draws from mixed methods data collected in the Kids in Communities Study – an Australian investigation of community effects on ECD – in communities across five states and territories. In total, 93 interviews and 30 focus groups were conducted with service providers and parents, and geographic information systems were used to create built environment measures for each local community. Housing factors (e.g. better affordability, tenure, less high-density public housing) were consistently related to disadvantaged local communities with ‘better than expected’ ECD outcomes. Physical access to services and public transport, living in a walkable area, having high-quality public open space, and a mix of local destinations was perceived to be consistently important by community members in disadvantaged communities regardless of ECD outcomes. Findings may help policymakers to consider neighborhood features that contribute to better ECD outcomes.

Cultivating social capital in diverse, low-income neighborhoods: The value of parks for parents with young children

Neighborhood built environment features, including parks, may contribute to social capital, but these relationships have not been adequately explored in communities of color. Our study focused on a specific subset of this population—a national sample of diverse, low-income parents with young children (n = 1,611)—to assess relationships between social capital, parks (e.g., access, visit frequency, and satisfaction), and other aspects of the built environment (e.g., perceptions of neighborhood walkability, traffic, and crime). We found that park satisfaction (a measure of park quality) was strongly linked to social capital among low-income parents, but park use frequency and access (both related to park quantity) were not. Neighborhood walkability and safety from crime were also strong positive correlates of social capital. Despite social benefits of parks, moderate to low ratings of park satisfaction, neighborhood walkability, safety from crime, and social capital within our sample suggest that inequities in park and neighborhood quality may prevent families who might benefit the most from social capital (i.e., low-income minority populations) from enjoying key resources needed to cultivate it. Cities hoping to enhance social capital in vulnerable communities would be wise to invest in quality parks and built environment features that create opportunities for positive social interactions among low-income parents with young children.

Low-carbon built environments and cardiometabolic health: a systematic review of Australian studies

ABSTRACT Australian cities offer potential for public health impact through low-carbon built environment design interventions, given their high per capita carbon footprint and with car use being a large proportion of transport mode share. Certain neighbourhood built environment features have been shown to influence uptake of active travel (walking and cycling), and thus may have beneficial associations with cardiometabolic health outcomes, such as obesity and type 2 diabetes. This systematic review synthesised Australian evidence on associations between low-carbon built environment attributes (green space and those promoting active transport) and cardiometabolic health in adults. Six databases were systematically searched; 33 articles met the inclusion criteria and 22 were included in a meta-analysis. We found strong evidence for an association of higher levels of walkability with lower risk of overweight/obesity, while there was some evidence linking higher land use mix and supportive walking/cycling infrastructure with lower overweight/obesity risk. Australian policy and advocacy efforts favouring more walkable neighbourhoods (compact, dense, and mixed-use) may have dual benefits for population health and the sustainability of cities. These findings highlight the importance of urban planning and public health practitioners working together to achieve healthy and sustainable cities for all.

Investigating associations between physical activity-related neighborhood built environment features and child weight status to inform local practice.

Despite evidence of the importance of neighborhood built environment features in relation to physical activity and obesity, research has been limited in informing localized practice due to small sample sizes and limited geographic coverage. This demonstration study integrated data from a local pediatric health system with nationally available neighborhood built environment data to inform local decision making around neighborhood environments and childhood obesity. Height/weight from clinic visits and home neighborhood measures from the U.S. Environmental Protections Agency and WalkScore were obtained for 15,989 6-17 year olds. Multilevel models accounted for the nested data structure and were adjusted for neighborhood income and child sociodemographics. In 9-17 year olds, greater street connectivity and walkability were associated with a 0.01-0.04 lower BMIz (Ps=.009-.017) and greater residential density, street connectivity, and walkability were associated 5-7% lower odds of being overweight/obese (Ps=.004-.044) per standard deviation increase in environment variable. 45.9% of children in the lowest walkability tertile were overweight or obese, whereas 43.1% of children in the highest walkability tertile were overweight or obese. Maps revealed areas with low walkability and a high income-adjusted percent of children overweight/obese. In the Kansas City area, data showed that fewer children were overweight/obese in more walkable neighborhoods. Integrating electronic health records with neighborhood environment data is a replicable process that can inform local practice by highlighting the importance of neighborhood environment features locally and pointing to areas most in need of interventions.

Active Transport to School and School Neighbourhood Built Environment across Urbanisation Settings in Otago, New Zealand.

The school neighbourhood built environment (BE) can facilitate active transport to school (ATS) in adolescents. Most previous studies examining ATS were conducted in large urban centres and focused on BE of home neighbourhoods. This study examined correlations between school-level ATS rates among adolescents, objectively measured school neighbourhood BE features, and adolescents’ perceptions of the school route across different urbanisation settings. Adolescents (n = 1260; 15.2 ± 1.4 years; 43.6% male) were recruited from 23 high schools located in large, medium, and small urban areas, and rural settings in Otago, New Zealand. Adolescents completed an online survey. School neighbourhood BE features were analysed using Geographic Information Systems. School neighbourhood intersection density, residential density and walkability index were higher in large urban areas compared to other urbanisation settings. School-level ATS rates (mean 38.1%; range: 27.8%–43.9%) were negatively correlated with school neighbourhood intersection density (r = −0.58), residential density (r = −0.60), and walkability index (r = −0.64; all p < 0.01). School-level ATS rates were also negatively associated with adolescents’ perceived safety concerns for walking (r = −0.76) and cycling (r = −0.78) to school, high traffic volume (r = −0.82), and presence of dangerous intersections (r = −0.75; all p < 0.01). Future initiatives to encourage ATS should focus on school neighbourhood BE features and minimise adolescents’ traffic safety related concerns.

Is the perceived neighborhood built environment associated with domain-specific physical activity in Latin American adults? An eight-country observational study

BackgroundCharacteristics of the neighborhood built environment are associated with physical activity (PA). However, few studies with representative samples have examined environmental correlates of domain-specific PA in Latin America. We examined the associations of the perceived neighborhood built environment with domain-specific PA in a large sample of adults from eight Latin American countries.MethodsThis study examined data from 8185 adults (aged 18–65 years) from eight Latin American countries. The Neighbourhood Environment Walkability Survey - Abbreviated (NEWS-A) scale was used to assess perceptions of land use mix–diversity, land use mix-access, street connectivity, walking/cycling facilities, aesthetics, safety from traffic, and safety from crime. Perceived proximity from home to public open spaces (metropolitan parks, playgrounds, public squares) and to shopping centers was also measured. Transport-related and leisure-time PA were assessed using the long form of the International Physical Activity Questionnaire. Both logistic and linear regression models were estimated on pooled data.ResultsPerceptions of higher land use mix-access (OR: 1.40; 95% CI: 1.22,1.61), the existence of many alternative routes in the neighbourhood (1.12; 1.04,1.20), slow speed of traffic (1.19; 1.03,1.35) and few drivers exceeding the speed limits (1.09; 1.03,1.15) were associated with greater odds of reporting at least 10 min/week of transport-related PA. Perceptions of higher levels of land use mix-diversity, better aesthetics and greater safety from crime, the presence of crosswalks and pedestrian signals, and greater proximity of shopping centers were associated with more min/week of transport-related PA. Perceptions of higher land use mix-diversity (1.12; 1.05,1.20), higher land use mix-access (1.27; 1.13,1.43), more walking/cycling facilities (1.18; 1.09,1.28), and better aesthetics (1.10; 1.02,1.18) were associated with greater odds of engaging in at least 10 min/week of leisure-time PA versus none. Perceptions of higher land use mix-diversity were associated with more min/week of leisure PA.ConclusionsDifferent perceived neighborhood built environment characteristics were associated with domain-specific PA among adults from Latin America countries. Interventions designed to modify perceptions of the neighbourhood built environment might influence initiation or maintenance of domain-specific PA.Trial registrationClinicalTrials. Gov NCT02226627. Retrospectively registered on August 27, 2014.

Association between Perceived Neighborhood Built Environment and Walking and Cycling for Transport among Inhabitants from Latin America: The ELANS Study.

Purpose: This study aimed to examine the associations of the perceived neighborhood built environment with walking and cycling for transport in inhabitants from Latin American countries. Methods: This cross-sectional study involved 9218 participants (15–65 years) from the Latin American Study of Nutrition and Health, which included a nationally representative sample of eight countries. All participants completed the International Physical Activity Questionnaire-Long Form for measure walking and cycling for transport and the Neighborhood Environment Walkability Scale-Abbreviated. Furthermore, perceived proximity from home to public open spaces and shopping centers was assessed. Results: Perceived land use mix-access (OR: 1.32; 95%CI: 1.16,1.50) and the existence of many alternative routes in the neighbourhood (1.09 1.01,1.17) were associated with higher odds of reporting any walking for transport (≥10 min/week). Perceived slow speed of traffic (1.88 1.82,1.93) and few drivers exceeding the speed limits (1.92; 1.86,1.98) were also related to higher odds of reporting any walking for transport. The odds of reporting any cycling for transport (≥10 min/week) were higher in participants perceiving more walking/cycling facilities (1.87 1.76,1.99), and better aesthetics (1.22 1.09,1.38). Conclusions: Dissimilar perceived neighborhood built environment characteristics were associated with walking and cycling for transport among inhabitants from Latin America.

Google Street View Derived Built Environment Indicators and Associations with State-Level Obesity, Physical Activity, and Chronic Disease Mortality in the United States.

Previous studies have demonstrated that there is a high possibility that the presence of certain built environment characteristics can influence health outcomes, especially those related to obesity and physical activity. We examined the associations between select neighborhood built environment indicators (crosswalks, non-single family home buildings, single-lane roads, and visible wires), and health outcomes, including obesity, diabetes, cardiovascular disease, and premature mortality, at the state level. We utilized 31,247,167 images collected from Google Street View to create indicators for neighborhood built environment characteristics using deep learning techniques. Adjusted linear regression models were used to estimate the associations between aggregated built environment indicators and state-level health outcomes. Our results indicated that the presence of a crosswalk was associated with reductions in obesity and premature mortality. Visible wires were associated with increased obesity, decreased physical activity, and increases in premature mortality, diabetes mortality, and cardiovascular mortality (however, these results were not significant). Non-single family homes were associated with decreased diabetes and premature mortality, as well as increased physical activity and park and recreational access. Single-lane roads were associated with increased obesity and decreased park access. The findings of our study demonstrated that built environment features may be associated with a variety of adverse health outcomes.

Cyclist crash rates and risk factors in a prospective cohort in seven European cities

Increased cycling uptake can improve population health, but barriers include real and perceived risks. Crash risk factors are important to understand in order to improve safety and increase cycling uptake. Many studies of cycling crash risk are based on combining diverse sources of crash and exposure data, such as police databases (crashes) and travel surveys (exposure), based on shared geography and time. When conflating crash and exposure data from different sources, the risk factors that can be quantified are only those variables common to both datasets, which tend to be limited to geography (e.g. countries, provinces, municipalities) and a few general road user characteristics (e.g. gender and age strata). The Physical Activity through Sustainable Transport Approaches (PASTA) project was a prospective cohort study that collected both crash and exposure data from seven European cities (Antwerp, Barcelona, London, Örebro, Rome, Vienna and Zürich). The goal of this research was to use data from the PASTA project to quantify exposure-adjusted crash rates and model adjusted crash risk factors, including detailed sociodemographic characteristics, attitudes about transportation, neighbourhood built environment features and location by city. We used negative binomial regression to model the influence of risk factors independent of exposure. Of the 4,180 cyclists, 10.2 % reported 535 crashes. We found that overall crash rates were 6.7 times higher in London, the city with the highest crash rate, relative to Örebro, the city with the lowest rate. Differences in overall crash rates between cities are driven largely by crashes that did not require medical treatment and that involved motor-vehicles. In a parsimonious crash risk model, we found higher crash risks for less frequent cyclists, men, those who perceive cycling to not be well regarded in their neighbourhood, and those who live in areas of very high building density. Longitudinal collection of crash and exposure data can provide important insights into individual differences in crash risk. Substantial differences in crash risks between cities, neighbourhoods and population groups suggest there is great potential for improvement in cycling safety.