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Background: Habitual commutes through green space may be associated with health promotion, including stress alleviation. However, few studies have assessed green space exposure during commuting with stress levels, and none have tracked commuters’ actual routes. Aim: To assess 1) the association between commuting through green space and people's self-perceived stress, 2) whether the association is moderated by the transport mode, and 3) whether the association depends on differing green space operationalizations and buffer sizes. Methods: This cross-sectional study used questionnaires and global positioning system data from Dutch adults aged 18–65 (N = 275). The Perceived Stress Scale was used to measure people's stress levels. Green space was measured by calculating the green space percentage from land use data (GREENLU), and by using normalized difference vegetation index (NDVI) obtained from Sentinel-2 (NDVISE) and Landsat-8 (NDVILS) satellite imagery. Buffers of 50, 100, and 250 m along commuting routes were applied to assess subjects’ environmental exposures. Associations were estimated using ordinary least squares regression models. Results: Covariate-adjusted regressions showed that GREENLU was significantly but positively associated with stress levels, regardless of the buffer size. By contrast, the NDVI measures consistently showed null associations. We observed a positive association between GREENLU and stress levels among active commuters within the 250 m buffer in stratified analyses; however, associations were null for passive commuters across all green space measures and buffer sizes. Conclusions: Our findings suggest a counterintuitive positive association between increased exposure to green space during daily commutes and people's stress levels. These associations possibly may depend on the selected green space metric, the buffer sizes, and the commuting mode considered. The behavioral aspects

Computer vision-based analysis of street view imagery has transformative impacts on environmental assessments. Interactive web services, particularly Google Street View, play an ever-important role in making imagery data ubiquitous. Despite the technical ease of harnessing millions of Google Street View images, this article questions the current practices in using this proprietary data source from a European viewpoint. Our concern lies with Google's terms of service, which restrict bulk image downloads and the generation of street view image-based indices. To reconcile the challenge of advancing society through groundbreaking research while maintaining data license agreements and legal integrity, we believe it is crucial to 1) include an author's statement on using proprietary street view data and the directives it entails, 2) negotiate academic-specific license to democratize Google Street View data access, and 3) adhere to open data principles and utilize open image sources for future research.

Background: Environmental noise has detrimental effects on various health outcomes. Although disparities in some environmental exposures (e.g., air pollution) are well-documented, there is still a limited and uncertain understanding of the extent to which specific populations are disproportionately burdened by noise. Aim: To assess whether environmental noise levels are associated with demographic and socioeconomic neighborhood compositions. Methods: We cross-sectionally examined long-term noise levels for 9,372 neighborhoods in the Netherlands. We linked these noise levels with administrative data on neighborhood characteristics for the year 2021. Linear and non-linear spatial regression models were fitted to explore the associations between noise, demographic, and socioeconomic neighborhood characteristics. Results: Our results showed that 46 % of the neighborhoods exhibited noise levels surpassing the recommended threshold of 53 dB to prevent adverse health effects. The regressions uncovered positive and partially non-linear neighborhood-level associations between noise and non-Western migrants, employment rates, low-incomers, and address density. Conversely, we found negative associations with higher-educated neighborhoods and those with a greater proportion of younger residents. Neighborhoods with older populations displayed a U-shaped association. Conclusions: This national study showed an inequality in the noise burden, adversely affecting vulnerable, marginalized, and less privileged neighborhoods. Addressing the uneven distribution of noise and its root causes is an urgent policy imperative for sustainable Dutch cities.

The 3-30-300 rule offers benchmarks for cities to promote equitable nature access. It dictates that individuals should see three trees from their dwelling, have 30 % tree canopy in their neighborhood, and live within 300 m of a high-quality green space. Implementing this demands thorough measurement, monitoring, and evaluation methods, yet little guidance is currently available to pursue these actions. To overcome this gap, we employed an expert-based consensus approach to review the available ways to measure 3-30-300 as well as each measure's strengths and weaknesses. We described seven relevant data and processes: vegetation indices, street level analyses, tree inventories, questionnaires, window view analyses, land cover maps, and green space maps. Based on the reviewed strengths and weaknesses of each measure, we presented a suitability matrix to link recommended measures with each component of the rule. These recommendations included surveys and window-view analyses for the ‘3 component’, high-resolution land cover maps for the ‘30 component’, and green space maps with network analyses for the ‘300 component’. These methods, responsive to local situations and resources, not only implement the 3-30-300 rule but foster broader dialogue on local desires and requirements. Consequently, these techniques can guide strategic investments in urban greening for health, equity, biodiversity, and climate adaptation.

Air pollution is a major environmental urban issue, particularly in fast-growing cities in developing countries. Reducing air pollution is thus a challenge while evaluating the economic value of air quality is crucial for environmental policies made. However, few studies accurately estimate this value as they neglect the possible endogeneity issues, as well as the dynamic and heterogeneous effects of air pollution. Under the hedonic framework, we therefore assess the economic effect of fine particulate matter (PM2.5) on housing prices in Beijing, China. We construct a panel based on resale apartment transactions matched with average quarterly PM2.5 data between 2013 and 2019. To reduce the risk of an estimation bias, we apply an instrumental variable (IV) approach. Our results show that PM2.5 is negatively associated with housing prices. Households were willing to pay an extra 0.0852% per housing unit price for an average quarterly reduction in PM2.5 of 1 µg/m3. Furthermore, we argue that high-income dwellers tend to pay more for clean air. The negative effects of PM2.5 across regions are significant and different. Compared with that in the basic year 2013, the negative effect increases in the first 3 years and then decreases in the last 3 years. Our findings enhance our comprehension of the economic impact of air quality and make a valuable contribution to the nuanced understanding of willingness to pay for air quality, which is beneficial in assessing and optimizing environmental regulations.

Running is a convenient physical activity that has gained popularity. However, little is known about runners’ running environments and how they differ from their residential environments. To fill this gap, this study examines runners’ exposure to natural and built environments along their running routes and assesses the difference between running and residential environments. We collected running track data from Endmondo, a fitness data platform, and used it to determine runners’ residency. Moreover, we used open geographical data to calculate a range of environmental variables within their residential areas and along their running trajectories. We applied t-tests to assess differences across objectively measured environmental variables between urban and rural runners, considering geographic, temporal and track-specific strata. We found that the running environments of urban and rural runners were diverse and had distinct characteristics. The results suggest policies to promote running acknowledging these differences between running environments in urban and rural areas.

Introduction Outdoor nighttime light (NTL) is a potential anthropogenic stressor in urban settings. While ecological studies have identified outdoor NTL exposure disparities, uncertainties remain about disparities in individual exposure levels, particularly in Europe. Aim To assess whether some populations are disproportionately affected by outdoor NTL at their residences in urban Bulgaria. Methods We analyzed 2023 data from a representative cross-sectional survey of 4,270 adults from the five largest Bulgarian cities. Respondents' annual exposures to outdoor artificial nighttime luminance were measured using satellite imagery and assigned at their places of residence. We calculated the Gini coefficient as a descriptive NTL inequality measure. Associations between respondents’ NTL exposure levels and sociodemographic characteristics were assessed by estimating quantile mixed regression models. Stratified regressions were fitted by gender and for each city. Results We found moderate distributive NTL inequalities, as indicated by a Gini coefficient of 0.214. Regression analyses showed associations between greater NTL exposure and higher educational attainment. Respondents with incomes perceived as moderate experienced less NTL exposure at the 0.5 and 0.8 quantiles, while unemployed respondents experienced lower exposure at the 0.2 and 0.5 quantiles. We observed null associations for the elderly and non-Bulgarian ethnicities. Regardless of the quantile, greater population density was associated with higher NTL levels. Stratification by sex did not yield substantial differences in the associations. We observed notable city-specific heterogeneities in the associations, with differences in the magnitudes and directions of the associations and the NTL quantiles. Conclusions NTL exposures appeared to embody an environmental injustice dimension in Bulgaria. Our findings suggest that some sociodemographic populations exp

Heart health is important for the quality of life, especially for older adults. Awareness is mounting that green space possibly matters for promoting heart health. While most studies mainly focused on the relationship between green space and cardiovascular diseases among older adults, scant attention has been paid to general heart heat measures through electrocardiography (ECG). This study aims to systematically assess the association between community green space exposure and heart health for Chinese older adults using street view and ECG. This observational, cross-sectional study was based on data from the 33 Chinese Community Health Study (33 CCHS). The heart health was measured by the presence of electrocardiographic abnormalities. We used street view data to calculate exposure to community street view green space (SVG) and further distinguished between street view trees (SVG-tree) and grass (SVG-grass). As a green space reference, we also incorporated the Normalized Difference Vegetation Index (NDVI). The results showed that SVG-grass was negatively associated with older adults’ odds of reporting electrocardiographic abnormalities, but there is no evidence that SVG-tree or NDVI was related to that. Also, the stratified analyses indicated that the results vary across demographic and socioeconomic groups. Heart health for males and older adults with lower income or educational attainment were significantly associated with SVG exposure, while such findings were not found for their counterparts. Our findings suggest ECG and street view data are promising in understanding green space-heart health associations. Hence, it is essential to promote the provision and visibility of community green space especially for older adults in disadvantaged groups.

Increasing anthropogenic global warming has emerged as a significant challenge to human health in China, as extreme heat hazards increasingly threaten outdoor-exposed populations. Differences in thermal comfort, outdoor activity duration, and social vulnerability between females and males may exacerbate gender inequalities in heat-related health risks, which have been overlooked by previous studies. Here, we combine three heat hazards and outdoor activity duration to identify the spatiotemporal variation in gender-specific heat risk in China during 1991–2020. We found that females' heat risk tends to be higher than that of males. Gender disparities in heat risk decrease in southern regions, while those in northern regions remain severe. Males are prone to overheating in highly urbanized areas, while females in low urbanized areas. Males' overheating risk is mainly attributed to population clustering associated with prolonged outdoor activity time and skewed social resource allocation. In contrast, females' overheating risk is primarily affected by social inequalities. Our findings suggest that China needs to further diminish gender disparities and accelerate climate adaptation planning.

Anthropogenic warming and rapid urbanization have exacerbated the deterioration of urban thermal environments, increasing interest in the ability of parks to regulate local climates. However, their potential to mitigate local thermal discomfort and spatial mismatch in supply and demand is poorly understood. We 1) examined the cooling effects of Shanghai's parks via a thermal comfort index, 2) identified the role of parks in improving local thermal environments by comparing thermal discomfort and park cooling capacity, and 3) explored the spatial mismatch between the demand for thermal discomfort mitigation and the supply of park cooling based on multiple park accessibility. The extent of park cooling is inversely related to the level of urbanization, while cooling intensity is positively associated with urbanization. Only 20.65% of the parks effectively mitigate local thermal discomfort, highlighting the need for improvements. Cooling accessibility increases from the city center to the periphery, with 22.70% of areas lacking access to park cooling services within a 15-min radius. Further improvements can enhance the thermal comfort of accessible parks by 49.55%. Priority adaptation is required in old urban areas and key development zones in peripheral urban areas to meet the needs of their large populations. Our study contributes to the study of urban thermal discomfort mitigation via parks in the context of climate adaptation planning.

We investigated trends in associations between physical and social neighbourhood and school characteristics and adolescent mental health problems between 2005 and 2017. Nationally representative, repeated cross-sectional data collected in the Netherlands among primary (N = 5,871) and secondary school students (N = 20,778) were analysed through cross-classified multilevel models. Hardly any evidence was found for over-time changes in associations between neighbourhood and school characteristics and adolescent mental health problems. Findings showed that for both groups of students, only social characteristics within the two contexts were associated with adolescent mental health problems. For secondary school students, school effects were larger than neighbourhood effects, while the opposite was true for primary school students. Specifically, primary school students residing in more socially fragmented or lower socioeconomic status (SES) neighbourhoods, and lower SES schools, reported more conduct problems and peer relationship problems. For secondary school students, only the SES of the neighbourhood and the school was associated with all four aspects of mental health problems. Remarkably, the direction of the associations between neighbourhood/ school SES and adolescent mental health problems varied across the different mental health outcomes. More research is warranted to replicate our findings.

Background Short-term environmental exposures, including green space, air pollution, and noise, have been suggested to affect health. However, the evidence is limited to aggregated exposure estimates which do not allow the capture of daily spatiotemporal exposure sequences. We aimed to (1) determine individuals’ sequential exposure patterns along their daily mobility paths and (2) examine whether and to what extent these exposure patterns were associated with anxiety symptoms. Methods We cross-sectionally tracked 141 participants aged 18–65 using their global positioning system (GPS) enabled smartphones for up to 7 days in the Netherlands. We estimated their location-dependent exposures for green space, fine particulate matter, and noise along their moving trajectories at 10-min intervals. The resulting time-resolved exposure sequences were then partitioned using multivariate time series clustering with dynamic time warping as the similarity measure. Respondents’ anxiety symptoms were assessed with the Generalized Anxiety Disorders-7 questionnaire. We fitted linear regressions to assess the associations between sequential exposure patterns and anxiety symptoms. Results We found four distinctive daily sequential exposure patterns across the participants. Exposure patterns differed in terms of exposure levels and daily variations. Regression results revealed that participants with a “moderately health-threatening” exposure pattern were significantly associated with fewer anxiety symptoms than participants with a “strongly health-threatening” exposure pattern. Conclusions Our findings support that environmental exposures’ daily sequence and short-term magnitudes may be associated with mental health. We urge more time-resolved mobility-based assessments in future analyses of environmental health effects in daily life.

Numerous neighborhood environments have been recognized to affect mental health, but only a few longitudinal studies investigated these associations jointly and whether different population groups are affected differently. We used three-wave panel data of 2699 adults between 2010 and 2016 in the Netherlands to assess the associations between changes in neighborhood physical and social environments and mental health changes. Further, we assessed possible effect modification of gender and income. Mental health was measured using the Mental Health Inventory. Time-varying exposure to green space, blue space, population density, air pollution, socioeconomic deprivation, and social fragmentation were assigned based on individuals' neighborhood histories. Fixed-effect regressions were conducted to assess within-person associations between single and multiple exposures on mental health for the entire sample and stratified by gender and income. Our single-exposure models showed that increases in blue space were significantly associated with mental health improvements, while increases in fine particulate matter (PM2.5) resulted in declines in mental health. These associations were not attenuated in the multi-exposure model. We observed no significant associations for the remaining environments. Stratification analyses showed that females’ mental health further declined as PM2.5 concentrations increased compared to males. Increasing levels of socioeconomic deprivation were associated with further declines in mental health among the less well-off compared with higher-income earners. Our longitudinal findings suggested that neighborhood physical and social environment changes were associated with mental health changes. Future research is required to establish the underlying pathways.

Background: Some studies have established associations between the prevalence of new-onset asthma and asthma exacerbation and socioeconomic and environmental determinants. However, research remains limited concerning the shape of these associations, the importance of the risk factors, and how these factors vary geographically. Objective: We aimed (1) to examine ecological associations between asthma prevalence and multiple socio-physical determinants in the United States; and (2) to assess geographic variations in their relative importance. Methods: Our study design is cross sectional based on county-level data for 2020 across the United States. We obtained self-reported asthma prevalence data of adults aged 18 years or older for each county. We applied conventional and geographically weighted random forest (GWRF) to investigate the associations between asthma prevalence and socioeconomic (e.g., poverty) and environmental determinants (e.g., air pollution and green space). To enhance the interpretability of the GWRF, we (1) assessed the shape of the associations through partial dependence plots, (2) ranked the determinants according to their global importance scores, and (3) mapped the local variable importance spatially. Results: Of the 3059 counties, the average asthma prevalence was 9.9 (standard deviation ± 0.99). The GWRF outperformed the conventional random forest. We found an indication, for example, that temperature was inversely associated with asthma prevalence, while poverty showed positive associations. The partial dependence plots showed that these associations had a non-linear shape. Ranking the socio-physical environmental factors concerning their global importance showed that smoking prevalence and depression prevalence were most relevant, while green space and limited language were of minor relevance. The local variable importance measures showed striking geographical differences. Conclusion: Our findings strengthen the evidence that socio-physic

Streets comprise over 80% of all urban public space, while previous studies associated street network attributes with traffic and transport model choice, they did not examine network design in conjunction with symptoms of depression. This paper developed a path analysis model to examine the direct and indirect effects of street network designs on symptoms of depression among undergraduates. Road network density, road intersection density and public transit density were measured within 1 km buffers centered on university campuses. A survey that included the 9-item patient health questionnaire (PHQ9) addressed these effects and measured the incidence of symptoms of depression among a random sample of 22,060 Chinese undergraduates. After controlling for individual- and campus-level covariates, the results revealed that exposure to PM2.5, poor sleep quality and unhealthy dietary pattern (excluding transport-related physical activity) mediated the relationship between specific street network attributes and symptoms of depression. Higher road density was found to alleviate symptoms of depression by increasing exposure to PM2.5. Greater road connectivity tended to alleviate symptoms of depression by reducing exposure to PM2.5 but to exacerbate symptoms of depression by worsening sleep quality and increasing the incidence of unhealthy dietary patterns. Better access to public transit inclined to ameliorate symptoms of depression by improving sleep quality but to exacerbate symptoms by increasing PM2.5 exposure. These findings emphasize the need for strategies aimed at improving street network designs to include assessments of the aggregate effects on campus environs and the associated impacts on undergraduate mental health.

The evidence of selective daily mobility bias distorting exposure-health associations is limited. Using 7-day smartphone-based global positioning system (GPS) tracking data for 67 Dutch adults aged 25–45, we conducted paired Wilcoxon tests to compare the absolute and relative exposure to food outlets along actual and modelled commuting routes. We fitted Tobit regressions to examine their associations with three daily snack and soft drink intake outcomes. We found significant differences in absolute food outlet exposure between two types of routes. Adjusted regression analyses yielded unexpected associations between dietary intakes and food outlet exposures. Our results suggested no evidence of a selective daily mobility bias in the association between the food environment along commuting routes and adults’ snacks and soft drink consumption in this sample.

Background: Adolescents' daily active travel (AT) has positive health effects. However, previous studies had paid little attention on the differences between the streetscape characteristics-AT relationship on the weekdays and weekends, and most of them only focused on the environmental exposure around home and schools. Methods: This study used data from a survey (N = 476) in Guangzhou, China between April and September 2018 and streetscape images from the Tencent Map. By using the Hurdle models and the Tobit models, we examined the associations between the streetscape characteristics and AT patterns (i.e., frequency and duration) among adolescents on weekdays and weekend days. Results: Streetscape greenery was negatively associated with odds of AT and positively associated with the number of AT trips on weekdays, while it was negatively related to AT duration on weekends. Pavement ratio and traffic volume were negatively associated with odds of AT and AT duration on weekdays. Safety facilities and street vitality were positively associated with the AT frequency and AT duration on weekends and weekdays. Our stratified analyses indicated that gender is an effect modifier of the built environment-AT patterns associations. Conclusion: The results showed that the relationships between streetscape characteristics and AT patterns differed between weekdays and weekends. Streetscape characteristics related to the odds of AT were not necessarily the same as those associated with AT intensity. These findings offer practical guidance for creating sustainable cities in China through AT promotion.

Obesity is a global public health threat. Although studies have suggested that the built environment is related to obesity, scholars have paid less attention to the pathways from the built environment to young adults' obesity. To bridge this gap, we employed path analysis to examine whether food intake, exercise, and active travel mediate the association between the campus-based built environment and body mass index (BMI), based on a nationwide sample of 15,503 Chinese undergraduates mostly aged 18–23 years old. Our results showed that unhealthy food intake mediated the association. A higher number of points of interest, more green space, and fewer restaurants were negatively related to body mass index by inhibiting unhealthy food intake. Neither the duration of exercise nor active travel distance mediated the built environment-BMI association, although both were directly associated with the campus-based built environment. These findings suggest that improving the campus-based environment could contribute to a reduction in obesity risk among undergraduates by improving their diets.

Despite increasing interest in how travel behavior changes over time, few studies have investigated how life events alter travel behavior, especially from a household perspective. This study examined the extent to which life events influenced changes in travel mode frequencies at the household level. We applied structural equation modeling based on the Netherlands Mobility Panel data for 2014 and 2016. For both partners, acquiring a household car significantly increased car use, and disposing of household cars decreased car use frequency. The number of household cars was inversely related to men's train use. Childbirth in the household decreased both partners’ cycling frequency. Men's job changes increased train use. These findings emphasize that life events can influence changes in travel behavior within household partners.

Promoting adolescents’ active school travel may support their health and wellbeing. Based on survey data of 473 adolescents in Guangzhou, China, and street view images, we employed generalized structural equation models to examine 1) the relationships between objective and perceived streetscape characteristics and adolescents’ active school travel and 2) the mediating roles of perceived safety, walkability, and air pollution. Results showed that street safety, vitality, greenery, and vehicle volume were positively related to odds of active school travel, while higher pavement ratio was associated with lower odds of active school travel. Street safety, pavement ratio, and vehicle volume were related to active school travel through perceived walkability, while street vitality and vehicle volume were associated with active school travel through the perceived safety-walkability path and perceived air pollution-walkability path. Our findings provide practical insights that could help city planners to make urban street environments more child-friendly for adolescents’ active travelling.

There is increasing evidence that people’s walking behavior is linked to the physical environment to which they are exposed. However, whether this association is moderated through local weather conditions is largely unclear. Based on Dutch National Travel Survey data, we applied latent class analysis to determine co-occurring weather conditions and used Tobit regression model to examine whether and, if so, to what extent weather conditions moderated the associations between the physical environment and different walking patterns on weekdays and weekends. We found that in warm and dry weather conditions on weekdays, people living nearby bus stops were more likely to walk to public transit. However, the same correlation was not found on weekends. In inclement weather (i.e., warm, very windy, rainy), people were less likely to walk to public transit. In warm, windy, and slightly rainy conditions, address density was negatively related to recreational walking. On weekends, people were more likely to walk for leisure outside the residential neighborhood (e.g., large open spaces, parks) in warm and dry conditions. Our results indicate that the combined impact of weather and the physical environment needs to be taken into account in walking infrastructure planning.

A hedonic approach is typically performed to identify housing rental or sales price determinants. However, standard hedonic regression models disregard spatial autocorrelation of prices and heterogeneity of housing preferences across space and over price segments. We developed a spatial autoregressive geographically weighted quantile regression (GWQR-SAR) to address these shortcomings. Using data on the determinants of residential rental prices in Warsaw (Poland) and Amsterdam (The Netherlands) as case studies, we applied GWQR-SAR and rigorously compared its performance with alternative mean and quantile hedonic regressions. The results revealed that GWQR-SAR outperforms other models in terms of fitting accuracy. Compared with mean regressions, GWQR-SAR performs better, especially at the tails of the dependent variable distribution, where non-quantile models overestimate low rent values and underestimate high ones. Policy recommendations for the development of private residential rental markets are provided based on our results, which incorporate spatial effects and price segment requirements.

Previous research has largely ignored the neighborhood’s vitality in creating a relaxing and safe environment for the prevalence of physical activity. Neighborhood vitality is critical for a healthy urban environment, and outdoor safety can only be ensured by reducing crime and repurposing underutilized spaces. A global regression and two local regressions are used to model the cross-sectional, ecological relationships between physical inactivity and multiple environmental variables in Chicago, United States. Multiscale geographically weighted regression showed the best model fit (R2 = 0.92). According to the findings, the factors influencing physical inactivity in Chicago neighborhoods are crime, green space, and vacant properties. Physical inactivity is rising in neighborhoods with a high share of 17 aged and younger and children living in poverty. Besides that, the relationships between neighborhood covariates and physical inactivity are spatially heterogeneous. Our study advocates for multiscale and multidisciplinary policies and institutions to create comfortable outdoor spaces for controlling and reducing physical inactivity prevalence.