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Different aspects of the built and natural environment appear related to people's walking behavior. State-of-the-art transport studies typically incorporate built environmental measures (e.g., density, diversity, design). However, street view (SV) environments capturing how pedestrians perceived their surroundings on site are understudied. Therefore, this study examined possibly non-linear associations between multiple SV-derived environmental features and pedestrians’ walking duration in Amsterdam, the Netherlands. We used travel survey data (N = 1,886) between 2014 and 2017. SV-derived environmental measures (e.g., cars and people) were extracted from SV images through a fully convolutional neural network. Covariate-adjusted generalized additive mixed models were fitted to the data. Our results showed that walking-SV features associations differed between weekdays and weekends. On weekdays, pedestrians walked more in neighborhoods with fewer individual standing walls and lower address density. On weekends, pedestrians’ walking duration increased with more street greenery, fewer cars, higher address density, pronounced land-use diversity, and further distances to train stations. Non-linear associations were found only in the case of weekday SV-derived people, even after adjusting for other neighborhood characteristics (e.g., address density, land-use mix, and street connectivity). Our findings suggest that SV environmental features complement the typically used built environmental measures to explain pedestrians’ mobility. Policy-makers and urban planners are advised to incorporate characteristics of the street environments, also should not only rely on the conventional thinking “the more, the merrier”.

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.

This review aimed to assess the longitudinal associations between neighborhood social, natural, and built environments, and multiple mental health outcomes (i.e., depression, anxiety, common mental disorder, and pooled mental disorders). Of 6,785 records retrieved, 30 studies fulfilled the inclusion criteria. Meta-analytical results primarily obtained from developed country studies showed that composite neighborhood socioeconomic status was negatively associated with depression (p = 0.007) and pooled mental disorders (p = 0.002), while neighborhood urbanicity was positively associated with depression (p = 0.012) and pooled mental disorders (p = 0.005). Future longitudinal studies with similar designs and standardized exposure assessments are warranted.

BACKGROUND AND OBJECTIVES: Buses are the most common form of public transport for older adults in developing countries. With over 37% of total trips, buses are the principal mode of transport in Dhaka. The majority of older adults are dependent on buses because of their affordability relative to other modes such as auto-rickshaws, rideshares, and taxis. This study aims to investigate key barriers in accessing buses in Dhaka and the consequences of these barriers to the everyday mobility of older adults. RESEARCH DESIGN AND METHODS: Thirty participants aged 60 and older were recruited from 2 socioeconomically different neighborhoods in Dhaka. We employed a thematic analysis of visual surveys and in-depth interviews to understand older adults' spatial and cultural context and their experiences using buses in their everyday lives. RESULTS: Boarding and deboarding buses were common barriers for older adults due to overcrowding and traffic congestion. In addition, older adults faced challenges such as ageism, gender discrimination, and undesirable behavior by transport personnel and co-passengers. These barriers affected their independent mobility and influenced their access to work and social life, contributing to their social exclusion. DISCUSSION AND IMPLICATIONS: This study illustrates the challenges faced by older adults when accessing public transport and the need to improve access to work, health care, and social life. Inclusive transport policies are essential in low- and middle-income countries to improve the well-being of older adults.

Background Mobility, one of the basic daily activities, helps in carrying out routine work, which contributes to people’s well-being. A lack of friendly and accessible infrastructure may act as a barrier, which limits older adults’ contributions and participation in society. Hence, it is important to have an enabling environment for older adults to carry out their activities independently at ease. There is ample research evidence about effective interventions on urban mobility infrastructures, but there is a lack of evidence regarding what works, for whom, and in what circumstances. Hence, there is a need to identify the contextual factors for different regions to design region-specific interventions. The aim of this realist synthesis is to develop an evidence-informed framework for safe and accessible urban mobility infrastructures for older adults in low- and middle-income countries. Methods A realist review will be undertaken using the following process: (1) development of a program theory, (2) search strategy and information sources, (3) study selection and appraisal, (4) data extraction, and (5) data synthesis. In addition to searching grey literature and contacting authors, we will search (since inception) multiple electronic databases such as PubMed, EMBASE, Scopus, Web of Science, and Cochrane Library. Studies will be included based on their ability to provide data that evaluates some aspect of the program theory. Two independent reviewers will screen and extract data from all relevant sources. A realist logic of analysis will be used to identify all context-mechanism-outcome that explains how safe and accessible urban mobility infrastructures for older adults implemented in low- and middle-income countries translate to better health outcomes. The findings will be reported according to Realist and MEta-narrative Evidence Syntheses: Evolving Standards guidelines. Discussion This realist review will help to develop a framework for safe and accessible urban mobility infrastructures for older adults in low- and middle-income countries. The results of this study will support evidence-based decision-making on urban mobility systems and will be of interest to various stakeholders. Dissemination will be done through conference presentations, policy briefs, media, and peer-reviewed journals. Implications for future research will be discussed. Systematic review registration PROSPERO CRD42020168020

Extensive evidence from cross-sectional studies has revealed a positive link between greenspace access and walking behaviors. However, the inherent weaknesses of the cross-sectional research design have provided little causal inference. In this natural experimental study, we assessed the effects of a large-scale greenway intervention (i.e., the opening of East Lake greenway) on walking behaviors in Wuhan, China. Longitudinal survey data on 1,020 participants were collected before and after the intervention in 2016 and 2019, respectively. The results of the mixed-effect difference-in-difference (DID) models showed that the greenway intervention had a significantly positive effect on the walking time, especially for residents living within two kilometers from the greenway. Furthermore, women and socio-economically disadvantaged people benefited most from the greenway implementation regarding walking time. Our findings provided compelling evidence that public investment in transportation infrastructure (e.g., greenway) effectively promotes walking behaviors and mitigates social inequities in physical activity.

Transportation is among the key aspects that influence active ageing. This realist review intends to understand the mechanisms of urban mobility infrastructure interventions and policies in low- and middle-income countries for older adults and to identify factors, which influenced the success or failure of interventions. We followed the steps suggested by Pawson and colleagues for a realist review. Electronic databases were searched from inception until August 2020. Studies were screened based on titles, abstracts and full text. The quality of included studies was assessed based on rigour and relevance. The evidence was obtained from 36 articles with diverse study designs conducted in 36 low- and middle-income countries. Findings were validated through stakeholder consultations from three low- and middle-income countries. Of the various individual factors identified, behaviour change communication interventions were low-cost, had a long-term impact and were efficient in increasing awareness among users to improve safety, social inclusion and about transport schemes for older adults. Improved transport infrastructure resulted in a shift from private to public transportation. For a sustainable urban transport infrastructure, good governance and involvement of stakeholders for planning and implementing transport interventions were considered necessary. Lack of evaluation, experience of transport planners, and inter-sectoral coordination were key challenges to successful interventions. The review highlighted a lack of older adult-specific transportation policies, and gender-targeted interventions for older women, suggesting a need for interventions and policies based on the contextual factors existing in a region.

BackgroundBoth social and physical neighbourhood factors may affect residents' health, but few studies have considered the combination of several exposures in relation to individual health status.AimTo assess a range of different potentially relevant physical and social environmental characteristics in a sample of small neighbourhoods in the Netherlands, to study their mutual correlations and to explore associations with morbidity of residents using routinely collected general practitioners' (GPs') data.MethodsFor 135 neighbourhoods in 43 Dutch municipalities, we could assess area-level social cohesion and collective efficacy using external questionnaire data, urbanisation, amount of greenspace and water areas, land use diversity, air pollution (particulate matter (PM) with a diameter 10), PM 2.5) and nitrogen dioxide (NO2), and noise (from road traffic and from railways). Health data of the year 2013 from GPs were available for 4450 residents living in these 135 neighbourhoods, that were representative for the entire country. Morbidity of 10 relevant physical or mental health groupings was considered. Individual-level socio-economic information was obtained from Statistics Netherlands. Associations between neighbourhood exposures and individual morbidity were quantified using multilevel mixed effects logistic regression analyses, adjusted for sex, age (continuous), household income and socio-economic status (individual level) and municipality and neighbourhood (group level).ResultsMost physical exposures were strongly correlated with degree of urbanisation. Social cohesion and collective efficacy tended to be higher in less urbanised municipalities. Degree of urbanisation was associated with higher morbidity of all disease groupings. A higher social cohesion at the municipal level coincided with a lower prevalence of depression, migraine/severe headache and Medically Unexplained Physical Symptoms (MUPS). An increase in both natural and agricultural greenspace in the neighbourhood was weakly associated with less morbidity for all conditions. A high land use diversity was consistently associated with lower morbidities, in particular among non-occupationally active individuals.ConclusionA high diversity in land use of neighbourhoods may be beneficial for physical and mental health of the inhabitants. If confirmed, this may be incorporated into urban planning, in particular regarding the diversity of greenspace.

In this correspondence, we emphasize methodological caveats of ecological studies assessing associations between COVID-19 and its physical and social environmental determinants. First, we stress that inference is error-prone due to the modifiable areal unit problem and the modifiable temporal unit problem. The possibility of confounding from using aggregated data is substantial due to the neglect of person-level factors. Second, studying the viral transmission of COVID-19 solely on people's residential neighborhoods is problematic because people are also exposed to nonhome locations and environments en-route along their daily mobility path. We caution against an uncritical application of aggregated data and reiterate the importance of stronger research designs (e.g., case-control studies) on an individual level. To address environmental contextual uncertainties due to people's day-to-day mobility, we call for people-centered studies with mobile phone data., Highlights • Number of ecological studies of environmental determinants of COVID-19 is increasing. • Their results may be biased and confounded by spatiotemporal aggregation of data. • People's day-to-day mobility away from the home can further bias their results. • Stronger research designs on a person-level with day-to-day mobility are needed.

Background Walking is a good and simple way to increase people’s energy expenditure, but there is limited evidence whether the neighborhood environment correlates differently with recreational and transportation walking. Aim To investigate how recreational walking and transportation walking are associated with the natural and built environmental characteristics of the living environment in the Netherlands, and examine the differences in their associations between weekdays and weekends. Method and data We extracted the total duration of daily walking (in minutes per person) for recreation and transport from the Dutch National Travel Survey 2015-2017 (N=66,880) and analyzed it as an outcome variable. Objective measures of the natural (i.e., Normalized Difference Vegetation Index (NDVI) and meteorological conditions) and built environment (i.e., crossing density, land-use mix, and residential building density) around respondents’ home addresses were determined for buffers with 300, 600, and 1,000 m radii using a geographic information system. To assess associations between recreational and transport walking and the environmental exposures separately, we fitted Tobit regression models to the walking data, adjusted for multiple confounders. Results On weekdays, people living in areas with less NDVI, higher land-use mix, higher residential building density, and higher crossing density were more likely to engage in transportation walking. While recreational walking was negatively associated with NDVI, crossing density, precipitation, and daily average temperature, it was positively associated with residential building density. At weekends, land-use mix supports both recreational and transportation walking. A negative association appeared for NDVI and transportation walking. Daily average rainfall and temperature were inversely correlated with recreational walking. Sensitivity tests indicated that some associations depend on the buffer size. Conclusions Our findings suggest that the built and natural environments have different impacts on people’s recreational and transportation walking. We also found differences in the walking–environment associations between weekdays and weekends. Place-based policies to design walking-friendly neighborhoods may have different implications for different types of walking.

BackgroundUniversity students are increasingly recognized as a vulnerable population, suffering from higher levels of anxiety, depression, substance abuse, and disordered eating compared to the general population. Therefore, when the nature of their educational experience radically changes—such as sheltering in place during the COVID-19 pandemic—the burden on the mental health of this vulnerable population is amplified. The objectives of this study are to 1) identify the array of psychological impacts COVID-19 has on students, 2) develop profiles to characterize students' anticipated levels of psychological impact during the pandemic, and 3) evaluate potential sociodemographic, lifestyle-related, and awareness of people infected with COVID-19 risk factors that could make students more likely to experience these impacts.MethodsCross-sectional data were collected through web-based questionnaires from seven U.S. universities. Representative and convenience sampling was used to invite students to complete the questionnaires in mid-March to early-May 2020, when most coronavirus-related sheltering in place orders were in effect. We received 2,534 completed responses, of which 61% were from women, 79% from non-Hispanic Whites, and 20% from graduate students.ResultsExploratory factor analysis on close-ended responses resulted in two latent constructs, which we used to identify profiles of students with latent profile analysis, including high (45% of sample), moderate (40%), and low (14%) levels of psychological impact. Bivariate associations showed students who were women, were non-Hispanic Asian, in fair/poor health, of below-average relative family income, or who knew someone infected with COVID-19 experienced higher levels of psychological impact. Students who were non-Hispanic White, above-average social class, spent at least two hours outside, or less than eight hours on electronic screens were likely to experience lower levels of psychological impact. Multivariate modeling (mixed-effects logistic regression) showed that being a woman, having fair/poor general health status, being 18 to 24 years old, spending 8 or more hours on screens daily, and knowing someone infected predicted higher levels of psychological impact when risk factors were considered simultaneously.ConclusionInadequate efforts to recognize and address college students’ mental health challenges, especially during a pandemic, could have long-term consequences on their health and education.

Introduction The rising use of e-bikes (EBs) presents an opportunity to increase active transportation but may compromise road safety due to increased travel speed and weight compared to conventional bicycle (CBs). Evidence comparing the safety of EBs and CBs is limited while the influence of cyclists’ health status has been neglected. Methods This cross-sectional case-control study compared EB and CB users in the Netherlands. Data were gathered 1) through a survey among crash casualties treated at emergency departments aged >16 (N = 2383) and 2) control group data were collected among cyclists without any known crash experience, randomly drawn from a panel of the Dutch population (N = 1860). Using logistic regressions, we assessed the likelihood of crashes and crash severity while adjusting for bicycle use and health status. Results EB users had poorer health than CB users, but they were not more likely to be involved in a crash or to sustain more severe injuries. However, older female cyclists did have an elevated risk on EBs and sustained more severe injuries. Health-related factors such as the presence of morbid conditions, medication use, and the body mass index were neither associated with crash likelihood nor associated with injury severity and accordingly did not explain the findings for older females. However, balance and coordination problems, and the use of anti-epileptic drugs were associated with crashes. Conclusion Our findings provide support that EB users have a poorer health status than CB users, while general health status is unrelated to the likelihood and severity of bicycle crashes. EBs enable more vulnerable groups to cycle or keep cycling but, after controlling for bicycle use, EB users are not more likely to be involved in a crash or to sustain severe injuries. As older females run a higher risk on an EB and are more likely to fall while (dis)mounting, we recommend to promote EBs enabling safer (dis)mounting such as by reduced saddle height.

Opioid consumption, both legal and illicit, has risen precipitously in the U.S. over the past few decades, as has the number of deaths due to the use and misuse of opioids. Exposure to green spaces may help to alleviate the problematic levels of opioid use. Such exposure has been tied to health benefits relevant to opioid use. To explore the potential influence of green space on opioid-related health outcomes, we analyzed the association between tree canopy cover and mortality attributable to opioid use and abuse using 2008–2018 death rate data on a county level (n = 3087) across the contiguous U. S. We fitted spatial general additive model while controlling for socioeconomic factors, healthcare access measures, opioid prescription rates, and particulate air pollution. Contrary to expectations, canopy cover was positively associated with opioid mortality. A sensitivity analysis with forest land cover showed similar results while a sensitivity analysis with total greenness (NDVI) was nonsignificant. Stratified models by urbanicity level suggested suburban and rural counties drove the positive associations observed in the nationwide models. The findings for forest and canopy cover are unexpected, given the myriad health benefits of green spaces, yet might be explained by heavily forested areas (i.e., Appalachia) being home to injury-prone natural resource extraction employment sectors. The steady decline of these industries has created poor socioeconomic conditions that exacerbate the already elevated risk of opioid use and misuse. Alternatively, the magnitude of the protective effects of greenspace on pain reduction are insufficient to counter opioid demand. Further research is warranted, especially in studies with individual-level data. Entities with responsibility or interest in reducing the incidence of deaths from opioids are cautioned that green spaces might not be a viable option for reducing opioid mortality.

Suicide mortality is a major contributor to premature death, with geographic variation in suicide rates. Why suicide rates differ across urban and rural areas has not yet been fully established. We conducted a literature review describing the urban–rural disparities in suicide mortality. Articles were searched in five databases (EMBASE, PubMed, PsychINFO, Scopus, and Web of Science) from inception till 26 May 2021. Eligible studies were narratively analyzed in terms of the urban–rural disparities in suicides, different suicide methods, and suicide trends over time. In total, 24 articles were included in our review. Most studies were ecological and cross-sectional evidence tentatively suggests higher suicide rates in rural than in urban areas. Men were more at risk by rurality than women, but suicide is in general more prevalent among men. No obvious urban–rural pattern emerged regarding suicide means or urban–rural changes over time. Potential suicidogenic explanations include social isolation, easier access to lethal means, stigmatization toward people with mental health problems, and reduced supply of mental health services. For research progress, we urge, first, individual-level cohort and case-control studies in different sociocultural settings. Second, both rurality and urbanicity are multifaceted concepts that are inadequately captured by oversimplified typologies and require detailed assessments of the sociophysical residential environment.

Near-repeat crime refers to a pattern whereby one crime event is soon followed by a similar crime event at a nearby location. Existing research on near-repeat crime patterns is inconclusive about where near-repeat patterns emerge and which physical and social factors influence them. The present research addressed this gap by examining the relationship between initiator events (i.e., the first event in a near-repeat pattern) and environmental characteristics to estimate where near-repeat patterns are most likely to emerge. A two-step analysis was undertaken using data on street robberies reported in Malm&ouml, Sweden, for the years 2006&ndash, 15. After determining near-repeat patterns, we assessed the correlations between initiator events and criminogenic places and socioeconomic indicators using a negative binomial regression at a street segment level. Our results show that both criminogenic places and socioeconomic indicators have a significant influence on the spatial variation of initiator events, suggesting that environmental characteristics can be used to explain the emergence of near-repeat patterns. Law enforcement agencies can utilize the findings in efforts to prevent further street robberies from occurring.

This paper examines how outdoor advertising shapes the perception and meaning of commuting for cyclists in Amsterdam (The Netherlands), and how individualised constructions of place arise during the journey. New insights are developed for a sustainable urban policy, whilst challenging consumer research methodologies through an emphasis on urban rhythm. Interviews were enhanced through the use of video cameras, capturing the visual attention of advertisements and recording bodily engagement with the road. In contrast to much academic and industry research, it is found that the reception of advertising landscapes differs significantly between transportation types, with socio-cultural differences specific to Amsterdam also determining distinctions for cyclists. The use of data by advertisers to track the movement of cyclists is a contentious issue, with wider consequences for privacy and consent in urban daily life. This paper breaks new ground for sustainability in cycling, re-evaluating the daily-embodied experience of commercial landscapes for commuter-cyclists.

Malaria threatens the lives of many people throughout the world. To counteract its spread, knowledge of the prevalence of malaria and the effectiveness of intervention strategies is of great importance. The aim of this study was to assess (1) the spread of malaria by means of a spatial agent-based model (ABM) and (2) the effectiveness of several interventions in controlling the spread of malaria. We focused on Sarbaz county in Iran, a malaria-endemic area where the prevalence rate is high. Our ABM, which was carried out in two steps, considers humans and mosquitoes along with their attributes and behaviors as agents, while the environment is made up of diverse environmental factors, namely air temperature, relative humidity, vegetation, altitude, distance from rivers and reservoirs, and population density, the first three of which change over time. As control interventions, we included long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS). The simulation results showed that applying LLINs and IRS in combination, rather than separately, was most efficient in reducing the number of infected humans. In addition, LLINs and IRS with moderate or high and high coverage rates, respectively, had significant effects on reducing the number of infected humans when applied separately. Our results can assist health policymakers in selecting appropriate intervention strategies in Iran to reduce malaria transmission.

Residential environments are associated with people's walking behavior. Transit-related, non-transit-related, and recreational walking may be differently associated with residential environments on weekdays and weekends, but empirical evidence is scarce. We therefore examined 1) to which extent these types of walking correlated with natural and built environmental characteristics of residential neighborhoods, 2) how these correlations differ for walking on weekdays and weekends, and 3) what substitution and complementarity effects between different types of walking exist. Our sample comprised 92,298 people aged ≥18 years from the pooled Dutch National Travel Survey 2010–2014. Multivariate Tobit regression models were used to assess the associations between the natural and built environment and the three types of walking (in average minutes per day). Our models accounted for cross-correlations between the walking types. Our results showed that denser residential areas encouraged both longer transit-related and non-transit-related transport walking on weekdays and weekends, whereas lower density neighborhoods were positively associated with recreational walking on weekdays. Shorter distances to public transport were only significantly associated with transit-related transport walking on weekdays. Shorter distances to daily facilities were positively associated with non-transit-related transport on weekdays. No significant associations between built environment and recreational walking were found on weekends. Additionally, some compensation effects between different types of walking seem to be at play: during weekends, recreational walking was inversely correlated with transit-related transport walking. Residential environments seem to affect walking types in a different way, suggesting that one size fits all policies might be less effective. Intervention strategies should be tailored for each walking type separately.

Purpose The physical and social neighborhood environments are increasingly recognized as determinants for depression. There is little evidence on combined effects of multiple neighborhood characteristics and their importance. Our aim was (1) to examine associations between depression severity and multiple perceived neighborhood environments; and (2) to assess their relative importance. Methods Cross-sectional data were drawn from a population-representative sample (N = 9435) from the Netherlands. Depression severity was screened with the Patient Health Questionnaire (PHQ-9) and neighborhood perceptions were surveyed. Supervised machine learning models were employed to assess depression severity-perceived neighborhood environment associations. Results We found indications that neighborhood social cohesion, pleasantness, and safety inversely correlate with PHQ-9 scores, while increasing perceived distance to green space and traffic were correlated positively. Perceived distance to blue space and urbanicity seemed uncorrelated. Young adults, low-income earners, low-educated, unemployed, and divorced persons were more likely to have higher PHQ-9 scores. Neighborhood characteristics appeared to be less important than personal attributes (e.g., age, marital and employment status). Results were robust across different ML models. Conclusions This study suggested that the perceived social environment plays, independent of socio-demographics, a role in depression severity. Contrasted with person-level and social neighborhood characteristics, the prominence of the physical neighborhood environment should not be overstated.

Monitoring of air pollution is an important task in public health. Availability of data is often hindered by the paucity of the ground monitoring station network. We present here a new spatio-temporal dataset collected and processed from the Sentinel 5P remote sensing platform. As an example application, we applied the full workflow to process measurements of nitrogen dioxide (NO2) collected over the territory of mainland France from May 2018 to June 2019. The data stack generated is daily measurements at a 4 × 7 km spatial resolution. The supplementary Python code package used to collect and process the data is made publicly available. The dataset provided in this article is of value for policy-makers and health assessment.

Although migration trajectories over people's life courses seem to be associated with mental health outcomes, previous studies have considered migration at only one point in time when correlating migration with mental health. However, people can migrate multiple times during their life courses. The decision to migrate can be triggered by several life course development events, such as education, entry to the labour market, marriage, or retirement. The present study addressed this research gap by focusing on the trajectories of migration and their relationship to mental health among internal migrants in China. Data were collected from a cross‐sectional survey (N = 534) in Shenzhen, China, in 2017. People's migration trajectories were aligned into migration groups using sequence alignment method. Binary logistic regression models were estimated to assess the associations between each migration trajectory group and the prevalence of mental health problems, controlling for sociodemographics and self‐reported physical health. The results show that migration trajectories—namely, the sequence of multiple migrations between migrants' places of origin and their final destinations—are significantly related to mental health outcomes. Our findings suggest that treating migration as a one‐time transition could be problematic because many migrants undertake multiple migration trips.

Background Neighbourhood social fragmentation and socioeconomic deprivation seem to be associated with suicide mortality. However, results are inconclusive, which might be because dynamics in the social context are not well-represented by administratively bounded neighbourhoods at baseline. We used individualised neighbourhoods to examine associations between suicide mortality, social fragmentation, and deprivation for the total population as well as by sex and age group. Methods Using a nested case-control design, all suicides aged 18–64 years between 2007 and 2016 were selected from longitudinal Dutch register data and matched with 10 random controls. Indices for social fragmentation and deprivation were calculated annually for 300, 600 and 1000 metre circular buffers around each subject’s residential address. Results Suicide mortality was significantly higher in neighbourhoods with high deprivation and social fragmentation. Accounting for individual characteristics largely attenuated these associations. Suicide mortality remained significantly higher for women living in highly fragmented neighbourhoods in the fully adjusted model. Age-stratified analyses indicate associations with neighbourhood fragmentation among women in older age groups (40–64 years) only. Among men, suicide risk was lower in fragmented neighbourhoods for those aged 18–39 years and for short-term residents. In deprived neighbourhoods, suicide risk was lower for men aged 40–64 years and long-term residents. Associations between neighbourhood characteristics and suicide mortality were comparable across buffer sizes. Conclusion Our findings suggest that next to individual characteristics, the social and economic context within which people live may both enhance and buffer the risk of suicide.

Objectives Residential greenness may prevent overweight/obesity, but the matter has not been investigated among middle-aged and older adults in China. This study 1) assessed associations between residential greenness and markers of adiposity among middle-aged and older Chinese adults and 2) investigated physical activity, sedentary behaviours, particulate matter (PM) with a diameter of

Background: \ud Exposure to residential greenery accumulates over people’s lifetimes, and possibly has a protective association with suicide later in life.\ud \ud Objectives: \ud To examine the associations between suicide mortality and long-term residential greenery exposure in male and female adults.\ud \ud Methods: \ud Our population-based nested case-control study used longitudinally georeferenced Dutch register data. Suicide cases aged 18–64 years between 2007 and 2016 were matched by gender, age, and date of suicide to 10 random controls. We measured long-term greenery exposure along people’s 10-year residential address histories through longitudinal normalized difference vegetation indices (NDVI) from Landsat satellite imagery between 1997 and 2016. We assigned accumulated greenery exposures, weighted by people’s exposure duration, within 300, 600, and 1,000 m concentric buffers around home addresses. To assess associations between suicide and greenery, we estimated gender-specific conditional logistic regressions without and with adjustment for individual-level and area-level confounders. Stratified models were fitted for areas with a high/low level of urbanicity and movers/non-movers.\ud \ud Results: \ud Our study population consisted of 9,757 suicide cases and 95,641 controls. In our models adjusted for age, gender, and date of suicide, the odds ratios decreased significantly with higher quartiles of accumulated NDVI scores. NDVI associations were attenuated and did not remain significant after adjustment for socioeconomics, urbanicity, air pollution, social fragmentation, etc. for either males or females. For females, but not males, our model with 300 m buffers for areas with a low level of urbanicity showed a significant suicide risk reduction with increasing levels of NDVI. Individual risk factors (e.g., lack of labor market participation) outweighed the contribution of greenery.\ud \ud Conclusion: \ud We found limited evidence that long-term greenery exposure over people’s lifetimes contributes to resilience against suicide mortality. Ensuring exposure to greenery may contribute to suicide prevention for specific population groups, but the effectiveness of such exposure should not be overstated.

Background Emerging evidence suggests that exposure to residential green space is beneficial for people's mental health along multiple pathways. It remains unknown, however, whether the complex pathways found for the general population also apply to internal migrants in China. Aim To examine the mediators of green space–mental health associations among migrants in the metropolis of Shenzhen, China. Methods We conducted a cross-sectional survey among 591 migrants aged between 18 and 68 years in January–April 2017 in Shenzhen, a city facing a considerable inflow of rural-urban migration. Migrants' mental health was assessed using the 12-item General Health Questionnaire. Data on migrant's green space perception, migration characteristics, environmental disturbances, social cohesion, physical health, etc. were obtained through a questionnaire. Structural equation modeling was used to analyze the mechanisms underlying the green space–mental health association. Results No direct effect of perceived green space on migrants' mental health was found. We did find, however, that perceived green space is significantly and indirectly related to mental health through reducing perceived environmental disturbance and enhancing social cohesion. Migrants' residential mobility presented a significant potential risk to migrants’ physical health and might influence their mental health indirectly. A similar but only weakly significant health-threatening effect was found for migration frequency. Male and female respondents showed different patterns regarding their physical and mental health status. Migrants with higher personal incomes seemed to face a lower mental health risk. Conclusions Our findings suggest distinctive pathways through which residential green space could affect the mental health of internal migrants in China. Further studies in rapidly urbanizing areas are advised to evaluate green space–mental health relationships for specific population groups/subgroups with distinctive socioeconomic backgrounds.

Walking is a common form of physical activity and has a considerable impact on public health. Walking behavior may change over time due to life events, including residential relocation. Only a few studies based on longitudinal data have examined the impacts of life events on walking behavior. The present study investigated the extent to which life events lead to changes in transport-related and recreational walking duration, by analyzing longitudinal panel data from the Netherlands Mobility Panel (MPN) for the years 2013 and 2015. In total, 1185 respondents aged 18 or older who completed both survey waves were included in our sample. Multilevel mixed-effects Tobit regression models were fitted and showed that both childbirth and relocation to less urbanized areas were related to an increase in transport-related walking over time. No significant associations of life events with recreational walking were observed. Findings suggest that transport-related walking is more likely to be influenced by changes in the household composition and residential relocation than recreational walking. Further longitudinal research is needed to verify our findings and gain insight into the mechanisms underlying these relationships.

Sedentary behavior has negative health effects. It is assumed that the walkability of the living environment is related to the amount of time spent on sedentary behavior in the residential setting. However, evidence on such a relation is still scarce, and results are contradictory. Therefore, we examined to what extent residential neighborhood walkability is associated with a variety of sedentary behaviors that frequently occur in the residential setting among adults. We carried out a cross-sectional survey using the domain-specific sedentary behavior questionnaire among adults in Breda, the Netherlands. Respondents&rsquo, walkability of the living environment was assessed objectively by means of road network buffers. We employed gamma generalized linear regressions to assess correlations between multiple sedentary behaviors and neighborhood walkability. We found no significant associations between residential neighborhood walkability and sedentary behavior levels. The lack of correlations was consistent across buffer sizes. Our models showed that adults with a higher education, a job, and a driver&rsquo, s license spent significantly less time on sedentary behaviors. Our findings suggest that person-level characteristics should be targeted when developing intervention strategies to counteract sedentary time, rather than intervening in the walkability of the residential living environment.

Introduction Environmental exposures are intertwined with mental health outcomes. People are exposed to the environments in which they currently live, and to a multitude of environments along their daily movements and through their residential relocations. However, most research assumes that people are immobile, disregarding that such dynamic exposures also serve as stressors or buffers potentially associated with depression and suicide risk. The aim of the Dynamic Urban Environmental Exposures on Depression and Suicide (NEEDS) study is to examine how dynamic environmental exposures along people’s daily movements and over their residential histories affect depression and suicide mortality in the Netherlands. Methods and analysis The research design comprises two studies emphasising the temporality of exposures. First, a cross-sectional study is assessing how daily exposures correlate with depression. A nationally representative survey was administered to participants recruited through stratified random sampling of the population aged 18–65 years. Survey data were enriched with smartphone-based data (eg, Global Positioning System tracking, Bluetooth sensing, social media usage, communication patterns) and environmental exposures (eg, green and blue spaces, noise, air pollution). Second, a longitudinal population register study is addressing the extent to which past environmental exposures over people’s residential history affect suicide risk later in life. Statistical and machine learning-based models are being developed to quantify environment–health relations.

Impacts of global warming and local scale urbanization on precipitation are evident from observations; hence both must be considered in future projections of urban precipitation. Dynamic regional models at a fine spatial resolution can capture the signature of urbanization on precipitation, however simulations for multiple decades are computationally expensive. In contrast, statistical regional models are computationally inexpensive but incapable of assessing the impacts of urbanization due to the stationary relationship between predictors and predictand. This paper aims to develop a unique modelling framework with a demonstration for Mumbai, India, where future urbanization is projected using a Markov Chain Cellular Automata approach, long term projections with climate change impacts are performed using statistical downscaling and urban impacts are simulated with a dynamic regional model for limited number of years covering different precipitation characteristics. The evaluation of the statistical downscaling methodology over historical time period reveals large underestimation of the extreme rainfall, which is improved effectively by applying another regression model, for extreme days. The limited runs of dynamic downscaling models with different stages of urbanization for Mumbai, India, reveal spatially non uniform changes in precipitation, occurring primarily at the higher quantiles. The statistical and dynamical outputs are further integrated using quantile transformation for precipitation projection in Mumbai during 2050s. The projections show dominant impacts of urbanization compared to those from large scale changing patterns. The uniqueness of this computationally efficient framework lies in an integration of global and local factors for precipitation projections through a conjugal statistical–dynamical approach.

Background Depression has become a severe societal problem in China. Although many studies have analyzed how environmental characteristics within neighborhoods affect depression, only a few have dealt with developing countries, and even fewer have considered built, natural, and social environments concurrently. Methods Based on a sample of 20,533 Chinese residents assessed in 2016, the present study examined associations between depressive symptoms and respondents’ built, natural, and social environments. Depressive symptoms were measured using the Center for Epidemiologic Studies Depression Scale (CES-D), and multilevel regression models were fitted accounting for potential covariates. Results Results indicated that living in neighborhoods with more green spaces and a higher population density were negatively associated with CES-D scores. Living in neighborhoods with more social capital was protective against depression. Furthermore, results showed that the social environment moderated the association between the built environment and depression. Conclusions Social environments moderate the relationship between the built environment and depression. As environments seem to interact with each other, we advise against relying on a single environment when examining associations with depressive symptoms.

Advances in commercial wearable devices are increasingly facilitating the collection and analysis of everyday physiological data. This article discusses the theoretical and practical aspects of using such ambulatory devices for the detection of episodic changes in physiological signals as a marker for mental state in outdoor environments. A pilot study was conducted to evaluate the feasibility of using commercial wearables in combination with location tracking technologies. The study measured physiological signals for fifteen participants, including heart rate, heart rate variability, and skin conductance. Participants’ signals were recorded during an outdoor walk that was tracked using a Global Positioning System logger. The walk was designed to pass through various types of environments including green, blue, and urban spaces, as well as a more stressful road crossing. The data that were obtained were used to demonstrate how biosensor information can be contextualized and enriched using location information. Significant episodic changes in physiological signals under real-world conditions were detectable in the stressful road crossing but not in the other types of environments. The article concludes that despite challenges and limitations of current off-the-shelf wearables, the utilization of these devices offers novel opportunities for evaluating episodic changes in physiological signals as a marker for mental state during everyday activities including in outdoor environments. Key Words: electrodermal activity, GPS, mental state, stress, wearable.

This study introduces a novel framework for land change simulation that combines the traditional Land Transformation Model (LTM) with data clustering tools for the purposes of conducting land change simulations of large areas (e.g., continental scale) and over multiple time steps. This framework, called “LTM-cluster”, subsets massive land use datasets which are presented to the artificial neural network-based LTM. LTM-cluster uses the k-means clustering algorithm implemented within the Spark high-performance compute environment. To illustrate the framework, we use three case studies in the United States which vary in simulation extents, cell size, time intervals, number of inputs, and quantity of urban change. Findings indicate consistent and substantial improvements in accuracy performance for all three case studies compared to the traditional LTM model implemented without input clustering. Specifically, the percent correct match, the area under the operating characteristics curve, and the error rate improved on average of 9%, 11%, and 4%. These results confirm that LTM-cluster has high reliability when handling large datasets. Future studies should expand on the framework by exploring other clustering methods and algorithms.

Background Multiple mechanisms have been proposed to explain how greenery in the vicinity of people's homes enhances their mental health and wellbeing. Mediation studies, however, focus on a limited number of mechanisms and rely on remotely sensed greenery measures, which do not accurately capture how neighborhood greenery is perceived on the ground. Objective To examine: 1) how streetscape and remote sensing-based greenery affect people's mental wellbeing; 2) whether and, if so, to what extent the associations are mediated by physical activity, stress, air quality and noise, and social cohesion; and 3) whether differences in the mediation across the streetscape greenery and NDVI exposure metrics occurred. Methods We used a population sample of 1029 adult residents of the metropolis of Guangzhou, China, from 2016. Mental wellbeing was quantified by the World Health Organization Well-Being Index (WHO-5). Two objective greenery measures were extracted at the neighborhood level: 1) streetscape greenery from street view data via a convolutional neural network, and 2) the normalized difference vegetation index (NDVI) from Landsat 8 remote sensing images. Single and multiple mediation analyses with multilevel regressions were conducted. Results Streetscape and NDVI greenery were weakly and positively, but not significantly, correlated. Our regression results revealed that streetscape greenery and NDVI were, individually and jointly, positively associated with mental wellbeing. Significant partial mediators for the streetscape greenery were physical activity, stress, air quality and noise, and social cohesion; together, they explained 62% of the association. For NDVI, only physical activity and social cohesion were significant partial mediators, accounting for 22% of the association. Conclusions Mental health and wellbeing and both streetscape and satellite-derived greenery seem to be both directly correlated and indirectly mediated. Our findings signify that both greenery measures capture different aspects of natural environments and may contribute to people's wellbeing by means of different mechanisms.

Environmental health studies on green space may be affected by contextual uncertainties originating from the temporality of environmental exposures and by how the spatial context is delimitated. The Normalized Difference Vegetation Index (NDVI) is frequently used as an outdoor green space metric capturing the chlorophyll content in the vegetation canopy. This study assessed (1) whether residential NDVI exposures vary over time, and (2) how these time series of NDVI scores vary across spatial context delimitations. Multi-temporal NDVI data for the period 2006&ndash, 2017 for the Netherlands were obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite platform. Annual NDVI exposures were determined across multiple buffer sizes (i.e., 300, 600, and 1000 m) centered on a random sample of 10,000 Dutch residential addresses. Besides the descriptive statistics, pairwise Wilcoxon tests and Fligner&ndash, Killeen tests were used to determine mean and variance differences in annual NDVI scores across buffer widths. Heat maps visualized the correlation matrices. Significance levels were adjusted for multiple hypotheses testing. The results indicated that annual NDVI metrics were significantly correlated but their magnitude varied notably between 0.60 to 0.97. Numerous mean and variance differences in annual NDVI exposures were significant. It seems that the disparate buffers (i.e., 300 and 1000 m) were less strongly correlated, possibly because variance heterogeneity is reduced in larger buffers. These results have been largely consistent over the years and have passed Monte Carlo-based sensitivity tests. In conclusion, besides assessing green space exposures along different buffer sizes, our findings suggest that green space&ndash, health studies should employ NDVI data that are well-aligned with epidemiological data. Even an annual temporal incompatibility may obscure or distort green space&ndash, health associations. Both strategies may diminish contextual uncertainties in environmental exposure assessments.

This study examined whether interactions between travel mode attitudes, urbanization level, and socio-demographics were different for bicycle commuting and cycling for other purposes. Data were obtained from the 2014 wave of the Netherlands mobility panel (MPN). In total, 2673 respondents (18 + years) who had recorded at least one trip on the days covered by the survey were included in the sample. Four outcomes were constructed, two of which concerned commuting-related cycling: any commuting-related bicycle usage (yes vs. no) and average cycling duration (in hours per weekday). Likewise, two similar outcome variables concerning cycling for other proposes were constructed. These outcomes were analyzed by means of Tobit regression models (cycling duration) and binary logistic models (any bicycle usage). Attitudinal factors concerning different travel modes, namely bus, car, cycling, and train, were constructed by means of factor analysis. The results showed that a positive attitude toward cycling was positively related to bicycle commuting duration, but this association was less strong among those with a positive attitude toward bus use. Having a positive cycling attitude had a weaker association with both bicycle commuting usage and duration in those who do not always have a car available. Regarding cycling for other purposes, cycling attitude had a stronger positive association with cycling duration among residents of very highly urbanized area, compared to residents of less urbanized areas. The available evidence, though limited, suggests that targeting attitudes can have a measurable impact on bicycling, but not to the same extend among all people.

Massive rural&ndash, urban migration in China has drawn attention to the prevalence of mental health problems among migrants. Research on the mental health of Chinese migrants has a narrow focus on rural&ndash, urban migrants, emphasizing the institutional role of hukou in migrant mental health. We argue that the heterogeneity of migrants, including their place of origin and whether they are temporary or permanent migrants, should be taken into account when trying to understand the meaning of migration as an actual movement from one place to another. The data used for this study is from a cross-sectional survey (N = 855) conducted in Shenzhen to compare the differences in migrants&rsquo, mental health that arise when using the two definitions (e.g., hukou and birthplace). Binary logistic regression models were estimated to assess the associations between people&rsquo, s mental health and migration, while controlling for settlement experiences, self-reported physical health, and sociodemographics. The results reveal inconsistent findings across both definitions: general migrants by birthplace were found to be unlikely to have mental problems compared to non-migrants, whereas temporary migrants were at higher risk of mental problems. The study provides important evidence that different migrant groups have different mental health outcomes. The choice of the definition used influences both migrant group selection and the actual linkage between migration and mental health.

It is increasingly recognized that mental disorders are affected by both personal characteristics and environmental exposures. The built, natural, and social environments can either contribute to or buffer against metal disorders. Environmental exposure assessments related to mental health typically rely on neighborhoods within which people currently live. In this article, I call into question such neighborhood-based exposure assessments at one point in time, because human life unfolds over space and across time. To circumvent inappropriate exposure assessments and to better grasp the etiologies of mental disease, I argue that people are exposed to multiple health-supporting and harmful exposures not only during their daily lives, but also over the course of their lives. This article aims to lay a theoretical foundation elucidating the impact of dynamic environmental exposures on mental health outcomes. I examine, first, the possibilities and challenges for mental health research to integrate people's environmental exposures along their daily paths and, second, how exposures over people's residential history might affect mental health later in life. To push the borders of scientific inquiries, I stress that only such mobility-based approaches facilitate an exploration of exposure duration, exposure sequences, and exposure accumulation., Graphical abstract fx1, Highlights • The environmental context affects people's mental health. • Environmental exposure assessments are frequently restricted to the neighborhoods in which people currently live. • Dynamic exposures along people's daily paths may trigger mental disorders. • Exposures over people's residential history might affect mental health later in life. • Only dynamic exposure assessments enable the inclusion of the duration and sequence of exposures and risk accumulation over time.

The aim of our study was to investigate the association between health enhancing and threatening, and social and physical aspects of the neighbourhood environment and general practitioner (GP) assessed morbidity of the people living there, in order to find out whether the effects of environmental characteristics add up or modify each other. We combined GP electronic health records with environmental data on neighbourhoods in the Netherlands. Cross-classified logistic multilevel models show the importance of taking into account several environmental characteristics and confounders, as social capital effects on the prevalence of morbidity disappear when other area characteristics are taken into account. Stratification by area socio-economic status, shows that the association between environmental characteristics and the prevalence of morbidity is stronger for people living in low SES areas. In low SES areas, green space seems to alleviate effects of air pollution on the prevalence of high blood pressure and diabetes, while the effects of green space and social capital reinforce each other.

Mental health is reportedly influenced by the presence of green and blue space in residential areas, but scientific evidence of a relation to psychotic disorders is scant. We put two hypotheses to the test: first, compared to the general population, psychiatric patients live in neighborhoods with less green and blue space, second, the amount of green and blue space is negatively associated with the duration of hospital admission. The study population consisted of 623 patients with psychotic disorders who had been admitted to the psychiatric ward of an academic hospital in Utrecht, The Netherlands from 2008 to 2016. Recovery was measured by length of stay. Structured patient data was linked to socio-economic status and the amount of green and blue space in the residential area. Associations were assessed by means of regression models controlling for confounding factors. Compared to the general population, psychiatric patients had a significantly lower amount of green space in their neighborhood. This result was not confirmed for blue space. Furthermore, no significant associations were found between green and blue space and the duration of hospital stay. In conclusion, previous studies focusing on other mental disorders, like anxiety or depression, found positive mental health effects of green and blue space in the neighborhood. We were not able to confirm significant effects among our study population on duration of admission, however. Future research focusing on psychotic patients could investigate the influence of exposure to green and blue space on other influences and outcomes on mental health.

The discussion on urban metabolism has been long dominated by natural scientists focussing on natural forces shaping the energy and material flows in urban systems. However, in the anthropocene human forces such as industrialization and urbanization are mobilizing people, goods and information at an increasing pace and as such have a large impact on urban energy and material flows. In this white paper, we develop a combined natural and social science perspective on urban metabolism. More specifically, innovative conceptual and methodological interdisciplinary approaches are identified and discussed to enhance the understanding of the forces that shape urban metabolism, and how these forces affect urban living and the environment. A challenging research agenda on urban metabolism is also presented.

Massive rural–urban migration in China has drawn attention to the prevalence of mental health problems among migrants. Research on the mental health of Chinese migrants has a narrow focus on rural–urban migrants, emphasizing the institutional role of hukou in migrant mental health. We argue that the heterogeneity of migrants, including their place of origin and whether they are temporary or permanent migrants, should be taken into account when trying to understand the meaning of migration as an actual movement from one place to another. The data used for this study is from a cross-sectional survey (N = 855) conducted in Shenzhen to compare the differences in migrants’ mental health that arise when using the two definitions (e.g., hukou and birthplace). Binary logistic regression models were estimated to assess the associations between people’s mental health and migration, while controlling for settlement experiences, self-reported physical health, and sociodemographics. The results reveal inconsistent findings across both definitions: general migrants by birthplace were found to be unlikely to have mental problems compared to non-migrants, whereas temporary migrants were at higher risk of mental problems. The study provides important evidence that different migrant groups have different mental health outcomes. The choice of the definition used influences both migrant group selection and the actual linkage between migration and mental health. View Full-Text

Background: Urban-rural disparities in suicide mortality have received considerable attention. Varying conceptualizations of urbanity may contribute to the conflicting findings. This ecological study on Germany assessed how and to what extent urban-rural suicide associations are affected by 14 different urban-rural indicators. Methods: Indicators were based on continuous or k-means classified population data, land-use data, planning typologies, or represented population-based accessibility indicators. Agreements between indicators were tested with correlation analyses. Spatial Bayesian Poisson regressions were estimated to examine urban-rural suicide associations while adjusting for risk and protective factors. Results: Urban-rural differences in suicide rates per 100,000 persons were found irrespective of the indicator. Strong and significant correlation was observed between different urban-rural indicators. Although the effect sign consistently referred to a reduced risk in urban areas, statistical significance was not universally confirmed by all regressions. Goodness-of-fit statistics suggested that the population potential score performs best, and that population density is the second best indicator of urbanicity. Numerical indicators are favored over classified ones. Regional planning typologies are not supported. Conclusions: The strength of suicide urban-rural associations varies with respect to the applied indicator of urbanicity. Future studies that put urban-rural inequalities central are recommended to apply either unclassified population potentials or population density indicators, but sensitivity analyses are advised.

Introduction Pedestrian falls (PFs) – falls in public spaces without collisions with other road users – are a significant cause of serious transport-related injuries, amounting to three-quarters of all pedestrians admitted to hospital. Methods This scoping review examined peer-reviewed research on PFs published between 1995 and 2015. Electronic databases (Scopus, SafetyLit, and PubMed) were used to find studies identifying PFs or outdoor falls (the latter also including falls in gardens). Results We identified only 28 studies reporting relevant information on PFs (i.e., 15 prospective, 10 retrospective, and 3 intervention studies). The results show that more walking is related to a lower risk of PFs. Older people, especially older women, have a higher risk of (injurious) PFs. Outdoor fall victims have equally good or better health characteristics and scores on balance tests compared to those who have not experienced such falls. Road factors such as uneven surfaces, busy junctions, stairs, and slippery surfaces seem to play an important role in PFs, but much of the research on these factors is of a qualitative nature. Conclusions PF victims are generally in good health (apart from normal age-related problems) but at risk due to road factors. Practical applications We recommend to adopt a human factors approach. The road system should be adapted to human capabilities and limitations including those of pedestrians. Measures such as preventing uneven surfaces and good winter maintenance seem to be effective. However, we advise more quantitative research on road factors to inform design guidelines and standards for public space authorities given the qualitative nature of current research on road factors.