Built Environment Determinants Research Articles

A case-control study of behavioural and built environment determinants of COVID-19 transmission in sheltered markets

BackgroundIn July 2021, amid occasional COVID-19 community transmission, an outbreak in a seafood wholesale centre propagated secondary clusters in sheltered markets in Singapore. This period offers a unique chance to study COVID-19 transmission risk factors related to environmental features and personal behaviours in markets. Only 40 % of the population was vaccinated during this period. MethodsA two-tier case-control study was conducted. The first tier entailed site assessments of markets where primary cases, presumed to have acquired COVID-19 at the seafood wholesale centre, worked. Markets with secondary cases (case markets) were compared against those without (control markets). The second tier comprised telephone questionnaires administered to individuals who worked at or visited the three markets with the highest number of secondary cases, with respondents either testing positive or negative for SARS-CoV-2. ResultsAssessment of 38 markets showed that markets “seeded” with more primary cases were more likely to experience a secondary outbreak (adjusted odds ratio, aOR: 2.0; 95 % confidence interval, CI: 1.3–4.7). From 333 visitor responses, maintaining social distancing (aOR: 0.34; 95 % CI: 0.11–1.06) and completing vaccination (aOR: 0.25; 95 % CI: 0.07–0.95) decreased infection risk, while using public washrooms increased the risk (aOR: 3.12; 95 % CI: 0.87–11.00). Among 86 staff responses, statistically significant risk factors were gender and mask type: male staff (aOR: 0.14; 95 % CI: 0.02–0.62) and those wearing surgical/N95 masks (aOR: 0.10; 95 % CI: 0.01–0.71) had lower infection risk. Wider aisles of the markets correlated with a higher chance of secondary transmission (aOR: 2.5; 95 % CI: 1.3–6.7). ConclusionThese findings underscore the importance of considering both built environment features and individual behaviours in devising effective measures to mitigate COVID-19 transmission in markets and community hubs in general. The observed association of wider market aisles with increased risk could be attributed to these facilitating the gathering and intermingling of more individuals, underlining the importance of maintaining social distancing. The identified individual risk factors among different populations within the market environment highlight the need for population-specific measures for infection prevention.

Dynamic neighborhood isolation and resilience during the pandemic in America's 50 largest cities

Planners have been in the war against neighborhood isolation for a long time. But studies have largely focused on the isolation within a neighborhood, ignoring its disconnectedness with the city and other neighborhoods based on human mobility. Analyses of human mobility data in America's largest 50 cities indicate that poor neighborhoods—regardless of its racial characteristics—are far less connected with mainstream neighborhoods (nonpoor and white neighborhoods) than nonpoor neighborhoods, and the gap is even wider during the pandemic. We also explored the resilience of neighborhoods in recovering the connection with the city and mainstream neighborhoods, and its built environment determinants. Our findings offer new insights for equitable neighborhood planning and policymaking in the context of the COVID-19 pandemic.

Measuring the Spatial-Temporal Heterogeneity of Helplessness Sentiment and Its Built Environment Determinants during the COVID-19 Quarantines: A Case Study in Shanghai

The COVID-19 outbreak followed by the strict citywide lockdown in Shanghai has sparked negative emotion surges on social media platforms in 2022. This research aims to investigate the spatial–temporal heterogeneity of a unique emotion (helplessness) and its built environment determinants. First, we scraped about twenty thousand Weibo posts and utilized their sentiments with natural language processing (NLP) to extract helplessness emotion and investigated its spatial–temporal variations. Second, we tested whether “helplessness” was related with urban environment attributes when other real estate economic and demographic variables were controlled using the ordinary least squares (OLS) model. Our results confirmed that helplessness emotion peaked in early April when the lockdown started. Second, residents in neighborhoods characterized by higher rents and property management fees, higher population density, lower housing prices, lower plot ratios, or surrounded by less tree view and higher perceived visual complexity, are found to exhibit higher degree of “helplessness”. This study provides an effective data-driven framework to utilize social media data for public sentiments monitoring. The helplessness emotion identified is a unique mental distress under strict quarantine measures, which expands the growing literature of urban governance in the post-pandemic era. Decision makers should pay attention to public opinions and design tailored management measures with reference to civic emotion dynamics to facilitate social sustainability and resilience in face of future crises.

Examining Increasing Racial Inequities in Opioid Overdose Deaths: a Spatiotemporal Analysis of Black and White Decedents in St. Louis, Missouri, 2011-2021.

The third wave of the opioid overdose crisis-defined by the proliferation of illicit fentanyl and its analogs-has not only led to record numbers of overdose deaths but also to unprecedented racial inequities in overdose deaths impacting Black Americans. Despite this racialized shift in opioid availability, little research has examined how the spatial epidemiology of opioid overdose death has also shifted. The current study examines the differential geography of OOD by race and time (i.e., pre-fentanyl versus fentanyl era) in St. Louis, Missouri. Data included decedent records from the local medical examiners suspected to involve opioid overdose (N = 4420). Analyses included calculating spatial descriptive analyses and conducting hotspot analyses (i.e., Gettis-Ord Gi*) stratified by race (Black versus White) and time (2011-2015 versus 2016-2021). Results indicated that fentanyl era overdose deaths were more densely clustered than pre-fentanyl era deaths, particularly those among Black decedents. Although hotspots of overdose death were racially distinct pre-fentanyl, they substantially overlapped in the fentanyl era, with both Black and White deaths clustering in predominantly Black neighborhoods. Racial differences were observed in substances involved in cause of death and other overdose characteristics. The third wave of the opioid crisis appears to involve a geographic shift from areas where White individuals live to those where Black individuals live. Findings demonstrate racial differences in the epidemiology of overdose deaths that point to built environment determinants for future examination. Policy interventions targeting high-deprivation communities are needed to reduce the burden of opioid overdose on Black communities.

Contribution of the built environment to inequity in loneliness by neighbourhood disadvantage in Australia

ABSTRACT Disadvantaged areas have higher loneliness levels than advantaged areas, though studies rarely identify objective built environment determinants of loneliness by neighbourhood disadvantage. We studied the contribution of objective walkability components (residential density, street connectivity, and land use mix) and overall walkability in the relationship between neighbourhood disadvantage and loneliness using cross-sectional data from 3778 individuals aged 48-77 years old living in 200 neighbourhoods in Brisbane, Australia. Residential density only partly contributed to the observed inequity in loneliness across neighbourhood disadvantages, among all walkability components. Moreover, the overall walkability could not explain inequity in loneliness across neighbourhood disadvantages.

Built-environment Determinants of Active Travel Behavior of Older Adults in Xiamen, China

Built-environment Determinants of Active Travel Behavior of Older Adults in Xiamen, China

Spatial equity implications and neighborhood indicators of ridehailing trip frequency and vehicle miles traveled in the phoenix metro region.

Early optimism for ridehailing services to complement existing public transit services and offer individuals another shared mobility service with reduced travel costs and improved travel times have largely proven to be unsubstantiated. This unwelcomed outcome, in part due to the popularity of ridehailing services among wealthier populations and restrictions on the less-expensive ridesharing service in some urban settings, has likely instead resulted in heightened disparities in access to this on-demand mobility option for historically-marginalized populations and under-resourced communities. This hypothesis is examined by estimating the macro-level socioeconomic and built environment determinants of ridehailing pick-ups and drop-offs in the Phoenix metro region with spatial lag of X modeling. A geographically weighted regression (GWR) model of vehicle miles traveled was then estimated using route-level ridehailing data from a third-party mileage tracking app to identify zonal attributes associated with this measure of vehicle-based exposure. Together, study findings highlight the benefits and drawbacks of greater ridehailing service activity, identifying a need for programs and interventions that safeguard and improve access to affordable high-quality mobility options for transportation disadvantaged neighborhoods.

Modelling geographical heterogeneity of diabetes prevalence and socio-economic and built environment determinants in Saudi City - Jeddah.

Type-2 diabetes is a growing lifestyle disease mainly due to increasing physical inactivity but also associated with various other variables. In Saudi Arabia, around 58.5% of the population is deemed to be physically inactive. Against this background, this study attempts explore the spatial heterogeneity of Type-2 diabetes prevalence in Jeddah and to estimate various socio-economic and built environment variables contributing to the prevalence of this disease based on modelling by ordinary least squares (OLS), weighted regression (GWR) and multi-scale geographically weighted (MGWR). Our OLS results suggest that income, population density, commercial land use and Saudi population characteristics are statistically significant for Type-2 diabetes prevalence. However, by the GWR model, income, commercial land use and Saudi population characteristics were significantly positive while population density was significantly negative in this model for 70.6%, 9.1%, 26.6% and 58.7%, respectively, out of 109 districts investigated; by the MGWR model, the corresponding results were 100%, 22%, 100% and 100% of the districts. With the given data, the corrected Akaike information criterion (AICc), the adjusted R2, the log-likelihood and the residual sum of squares (RSS) indices demonstrated that the MGWR model outperformed the GWR and OLS models explaining 29% more variance than the OLS model, and 10.2% more than the GWR model. These results support the development of evidence-based policies for the spatial allocation of health associated resources for the control of Type-2 diabetes in Jeddah and other cities in the Arabian Gulf.

Jointly modeling bus and taxi ridership: A Bayesian multivariate spatial analysis accounting for cross‐ridership correlation

AbstractUnderstanding the spatial patterns of transit ridership and their ascribable factors is critical for urban and transportation planning. Existing studies predominantly examine a single type of transit ridership but neglect important cross‐ridership correlation. This study aims to develop a Bayesian multivariate spatial modeling approach for jointly analyzing multiple ridership. In particular, cross‐ridership correlation is estimated using correlated spatially unstructured residuals, correlated spatial random effects, or the combination of both. The proposed approach is applied to a case study of Wuhu, China, where the correlation between bus and taxi ridership is accounted for in the modeling of transit ridership and their built environment determinants. Results show that accounting for cross‐ridership correlation significantly improves model‐fitting, but the fashion used to induce such a correlation matters. Furthermore, the role of built environment in determining transit ridership could be over‐estimated without considering cross‐ridership correlation. This study contributes to statistical modeling of transit ridership by applying a spatial multivariate approach, which can improve our understanding of the underlying processes of multiple ridership, their interactions, as well as their associations with physical environments.

COVID-19 exacerbates unequal food access

Inequality to food access has always been a serious problem, yet it became even more critical during the COVID-19 pandemic, which exacerbated social inequality and reshaped essential travel. This study provides a holistic view of spatio-temporal changes in food access based on observed travel data for all grocery shopping trips in Columbus, Ohio, during and after the state-wide stay-at-home period. We estimated the decline and recovery patterns of store visits during the pandemic to identify the key socio-economic and built environment determinants of food shopping patterns. The results show a disparity: during the lockdown, store visits to dollar stores declined the least, while visits to big-box stores declined the most and recovered the fastest. Visits to stores in low-income areas experienced smaller changes even during the lockdown period. A higher percentage of low-income customers was associated with lower store visits during the lockdown period. Furthermore, stores with a higher percentage of white customers declined the least and recovered faster during the reopening phase. Our study improves the understanding of the impact of the COVID-19 crisis on food access disparities and business performance. It highlights the role of COVID-19 and similar disruptions on exposing underlying social problems in the US.

A tale of two social groups in Xiamen, China: Trip frequency of migrants and locals and its determinants

Across developing countries, there are hundreds of millions of migrants residing in cities, and meeting their travel demand has become increasingly important yet challenging. While a growing number of scholars have studied this demand and its determinants in the West, limited research has been conducted in China. Taking Xiamen, China, as an example, this study compares the migrants’ and locals’ travel behaviors (frequency of trips by walking, cycling, public transport, and motor vehicle) and comparatively explores their sociodemographic and built environment determinants. The findings show that (1) migrants depend more on non-driving-alone modes, such as public transport and walking, compared with locals; (2) both sociodemographic and built environment variables (e.g., population density, land use mix, and distance to commercial centers) can significantly predict the travel behaviors of locals; and (3) sociodemographic variables significantly predict migrants’ different mode trip frequency, whereas built environment indicators have significant but minor impacts on their behaviors. This study highlights the importance of context and population differentiation and calls for more in-depth research on migrants’ travel behaviors as well as their determinants. The results and findings can help decision makers undertake more informed countermeasures to accommodate the travel demands of all residents in cities, regardless of whether they are migrants or locals.

Promoting activity participation and well-being among children and adolescents: a systematic review of neighborhood built-environment determinants.

The objective of this review was to identify, evaluate, and synthesize the findings on built-environment determinants and their relation to participation in different domains of activities, including physical activity, recreational and social activities, and well-being in childhood and adolescence. Creating supportive environments for children and adolescents is a priority in society. To ensure informed decision making and policy changes, initiatives need to rely on systematic development and the use of evidence-based knowledge. Thus, it is necessary to critically review the current evidence on the relationship between features of the built environment and health in a more specific and detailed manner to better understand the health-promoting potential of neighborhood built environments. This review included studies on children and adolescents between five and 18 years of age, which examined relationships between one or several neighborhood built-environment determinants and participation in activities and/or well-being. The studies had to report test statistics for associations between built-environment determinants and the outcomes, which means that descriptive cross-sectional studies were not eligible for inclusion. A four-step search strategy was utilized to identify peer-reviewed studies within six databases. The search was limited to English articles published since January 2010. A data extraction form was developed and used to mine the descriptive details of each included study. The included studies were further assessed for methodological quality by three reviewer pairs independently, using the standard critical appraisal tools from JBI. Due to the methodological heterogeneity of the included studies, a narrative summary of the quantitative findings was conducted. The 127 studies included in the review were mainly cross-sectional (87.4%). The built environment was most extensively studied in relation to the outcomes active travel (n = 54) and unspecified physical activity (n = 46). The evidence suggests that a composite determinant of facilities and amenities is related to more unspecified physical activity. Furthermore, less traffic exposure and more safety features, pedestrian infrastructure for walking and cycling, shorter distances to facilities and greater walkability supported active travel behavior. Fewer studies (n = 11) examined the built-environment determinants of organized sports and well-being, and limited, as well as contradictory, evidence existed for the relationship between the built environment and well-being. The following determinants potentially support active travel behavior: less traffic exposure and more safety features, pedestrian infrastructure for walking and cycling, shorter distances to facilities and greater walkability. A high facility and amenity index might promote unspecified physical activity. Policies and planning processes should consider these determinants to strengthen children's and adolescents' health and well-being. However, there are remaining research gaps and important avenues for future research that need to be addressed before more specific and robust conclusions can be drawn.

Examining threshold effects of built environment elements on travel-related carbon-dioxide emissions

Understanding how built environment features are associated with travel-related carbon-dioxide (CO2) emissions is essential for planners to encourage environmentally sustainable travel through transportation and land use policies. Applying gradient boosting decision trees to the data from the Minneapolis-St. Paul metropolitan area, this study addresses two gaps in the literature by identifying critical built environment determinants of CO2 emissions, and more importantly, illustrating threshold effects of built environment elements. The results show that three neighborhood-level built environment factors have the strongest influences on CO2 emissions: distance to the nearest transit stop, job density, and land use diversity. The distance to downtowns also has a substantial impact. This study further confirms that built environment variables are effective only within a certain range. These threshold effects offer valuable implications for planners to achieve desirable environmental benefits efficiently.

Built environment determinants of pedestrians’ and bicyclists’ route choices on commute trips: Applying a new grid-based method for measuring the built environment along the route

To better understand the role of the built environment in route choices among pedestrians and bicyclists, this study explores the built environment distribution along commute routes in two neighbourhoods in Tampere, Finland. A new grid-based method is developed to enable a more sophisticated analysis of the built environment along the route.The data consist of 73 commute routes collected with the Sports Tracker® smartphone application, of which 18 are made by foot and 55 by bicycle. To find the most relevant spatial scale, the values of each built environment variable are calculated with five buffer sizes for each cell of the grid covering the research area. Five statistics describing the distribution of the built environmental variables along each shortest and actual route are then calculated and compared.The results show that besides determining whether a significant association is found, different spatial scales for the analysis produce dissimilar findings in strength and even the direction of the correlations found. The most significant associations are found mainly with the smallest buffer (15m). Of the five built environment statistics calculated, the mean value of most built environmental variables had the most consistent correlation with route choice. Also, standard deviation and the third quartile of several built environmental variables along the routes correlate with route choice. The most significant associations with route choice are found with intersection density, institutional land use, slope, and age of buildings.

Spatially-varying effects of built environment determinants on walking

•This study explores the spatially-varying relationship between walking and built environment.•Geographically Weighted Regression is utilized for a spatially-sensitive analysis.•This approach enhanced the understanding about the influential pattern of variables at various geographic scales.•The coefficients spatially vary depending on the site-specific characteristics.

Socio-demographic and built environment determinants of car use among older adults in Iran

Internationally, an age-friendly built environment, including safe, affordable, and convenient transportation, has been identified as crucial in enhancing the quality of life for increasingly large numbers of elderly people. This study presents data on the urban travel and mobility patterns of older adults in Shiraz, Iran – a country where the population is ageing faster than the average of western societies. The relationship between car use and socio-demographic and built environment variables is investigated through Ordinary Least Squares and Geographically Weighted Regression models. These models show that the main determinants of car use among older adults are: employment status; household size; car ownership rate; trip purpose; property prices; and mixed land-uses. Also, the study reveals that car dependency is significant and more pronounced among wealthier individuals, who tend to be clustered in the northern section of the city. The population density and road network design characteristics do not affect car use among older adults, while a mix of land-uses tends to attenuate car dependency. Gender gaps in car use are much wider than in the West, and some level of spatial mismatch between travel needs and car access is observed in the southern section of the city. Clearly, Iranian cities must move away from the current car-centric development model.

Built environment determinants of bicycle volume: A longitudinal analysis

This study examines determinants of bicycle volume in the built environment with a five-year bicycle count dataset from Seattle, Washington. A generalized linear mixed model (GLMM) is used to capture the bicycle volume change over time while controlling for temporal autocorrelations. The GLMM assumes that bicycle count follows a Poisson distribution. The model results show that (1) the variables of non-winter seasons, peak hours, and weekends are positively associated with the increase of bicycle counts over time; (2) bicycle counts are fewer in steep areas; (3) bicycle counts are greater in zones with more mixed land use, a higher percentage of water bodies, or a greater percentage of workplaces; (4) the increment of bicycle infrastructure is positively associated with the increase of bicycle volume; and (5) bicycling is more popular in neighborhoods with a greater percentage of whites and younger adults. It concludes that areas with a smaller slope variation, a higher employment density, and a shorter distance to water bodies encourage bicycling. This conclusion suggests that to best boost bicycling, decision-makers should consider building more bicycle facilities in flat areas and integrating the facilities with employment densification and open-space creation and planning.

A pathway linking smart growth neighborhoods to home-based pedestrian travel

Land development patterns, urban design, and transportation system features are inextricably linked to pedestrian travel. Accordingly, planners and decision-makers have turned to integrated transportation-land use policies and investments to address the pressing need for improvements in physical activity levels via the creation of walkable communities. However, policy questions regarding the identification of smart growth indicators and their connection to walking remain unanswered, because most studies of the built environment determinants of pedestrian travel: (a) represent the built environment with isolated metrics instead of as a multidimensional construct and (b) model this transportation-land use relationship outside of a multidirectional analytic framework. Using structural equation modeling, this Portland, Oregon study identifies a second-order latent construct of the built environment indicated by land use mix, employment concentration, and pedestrian-oriented design features. Study findings suggest this construct has a strong positive effect on the household-level decision to walk for transportation and discretionary trip purposes.

The built environment determinants of activity participation and walking near the workplace

Investigating the built environment determinants of commuting behaviors to and from the workplace has long been of interest to travel behavior researchers. Specific attention has centered on examination of how smart growth policies encourage both trip-chaining and active travel. Yet, limited research has investigated the impact of the built environment on activity participation and pedestrian travel once the worker has arrived at his/her workplace. A research omission that exists despite the prospect that built environment densification and diversification within employment districts may encounter less opposition from the local community and commuter. Our study investigates these identified gaps by analyzing how the built environment near an individual’s workplace as well as personal, household, and tour-related attributes relate to work-based sub-tour activity participation and walking for activity fulfillment. A bivariate selection model estimated the workplace built environment determinants of work-based sub-tour participation and the likelihood to initiate travel for these sub-tour activities on foot. Findings from this Portland, Oregon study revealed that design and diversity features predicted work-based sub-tour participation; while, the decision to walk to start a sub-tour was strongly associated with a workplace built environment characterized by a traditional neighborhood design and increased residential density.

Healthy Canada by Design CLASP: Lessons learned from the first phase of an intersectoral, cross-provincial, built environment initiative.

The Healthy Canada by Design (HCBD) CLASP (Coalitions Linking Action and Science for Prevention) Initiative promotes the building of communities that support health by 1) facilitating the integration of health evidence into built environment decision-making; 2) developing new, cross-sector collaboration models and tools; and 3) fostering a national community of practice. A coalition of public health professionals, researchers, professional planners and non-governmental organization (NGO) staff from across Canada developed, implemented and participated in the Initiative. In the first phase, HCBD interventions took place for the most part in large urban and suburban settings in Quebec, Ontario and British Columbia. National knowledge transfer and exchange (KTE) activities were delivered both locally and nationally. Project participants developed tools or processes for collaboration between the health and the community planning sectors. These were designed to increase the capacity of the health sector to influence decisions about land use and transportation planning. Tool or process development was accompanied by pilot testing, evaluation, and dissemination of findings and lessons learned. On a parallel track, NGOs involved with HCBD led national KTE interventions. The first phase of HCBD demonstrated the potential for public health organizations to influence the built environment determinants of cancer and chronic diseases. Public health authorities forged relationships with several organizations with a stake in built environment decisions, including municipal and regional planning departments, provincial governments, federal government agencies, researchers, community groups and NGOs. The Initiative accomplished the following: 1) created new relationships across sectors and across health authorities; 2) improved the knowledge and skills for influencing land use planning processes among public health professionals; 3) increased awareness of health evidence and intent to change practice among built environment decision-makers; and 4) facilitated inclusion of health considerations in local plans, policies and decisions. The first phase of HCBD engaged built environment stakeholders, including public health professionals, planners, researchers, community groups and NGOs, in ways that would be expected to influence health risk factors and population health outcomes in the long term.