Validity of Mobility-Based Exposure Assessment of Air Pollution: A Comparative Analysis with Home-Based Exposure Assessment.

Air pollution exposure is typically assessed at the front door where people live in large-scale epidemiological studies, overlooking individuals' daily mobility out-of-home. However, there is limited evidence that incorporating mobility data into personal air pollution assessment improves exposure assessment compared to home-based assessments. This study aimed to compare the agreement between mobility-based and home-based assessments with personal exposure measurements. We measured repeatedly particulate matter (PM2.5) and black carbon (BC) using a sample of 41 older adults in the Netherlands. In total, 104 valid 24 h average personal measurements were collected. Home-based exposures were estimated by combining participants' home locations and temporal-adjusted air pollution maps. Mobility-based estimates of air pollution were computed based on smartphone-based tracking data, temporal-adjusted air pollution maps, indoor-outdoor penetration, and travel mode adjustment. Intraclass correlation coefficients (ICC) revealed that mobility-based estimates significantly improved agreement with personal measurements compared to home-based assessments. For PM2.5, agreement increased by 64% (ICC: 0.39-0.64), and for BC, it increased by 21% (ICC: 0.43-0.52). Our findings suggest that adjusting for indoor-outdoor pollutant ratios in mobility-based assessments can provide more valid estimates of air pollution than the commonly used home-based assessments, with no added value observed from travel mode adjustments.

Environmental noise is positively associated with socioeconomically less privileged neighborhoods in the Netherlands.

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.

Global positioning system-based food environment exposures, diet-related, and cardiometabolic health outcomes: a systematic review and research agenda.

BACKGROUND: Geographic access to food may affect dietary choices and health outcomes, but the strength and direction of associations may depend on the operationalization of exposure measures. We aimed to systematically review the literature on up-to-date evidence on the association between food environment exposures based on Global Positioning System (GPS) and diet-related and cardiometabolic health outcomes. METHODS: The databases PubMed, Embase.com, APA PsycInfo (via Ebsco), Cinahl (via Ebsco), the Web of Science Core Collection, Scopus, and the International Bibliography of the Social Sciences (via ProQuest) were searched from inception to October 31, 2022. We included studies that measured the activity space through GPS tracking data to identify exposure to food outlets and assessed associations with either diet-related or cardiometabolic health outcomes. Quality assessment was evaluated using the criteria from a modified version of the Newcastle-Ottawa Scale (NOS) for cross-sectional studies. We additionally used four items from a quality assessment tool to specifically assess the quality of GPS measurements. RESULTS: Of 2949 studies retrieved, 14 studies fulfilled our inclusion criteria. They were heterogeneous and represent inconsistent evidence. Yet, three studies found associations between food outlets and food purchases, for example, more exposure to junk food outlets was associated with higher odds of junk food purchases. Two studies found associations between greater exposure to fast food outlets and higher fast food consumption and out of three studies that investigated food environment in relation to metabolic outcomes, two studies found that higher exposure to an unhealthy food environment was associated with higher odds of being overweight. CONCLUSIONS: The current and limited evidence base does not provide strong evidence for consistent associations of GPS-based exposures of the food environment with diet-related and cardiometabolic health outcomes.

Assessing runners' exposure to natural and built environments in the Netherlands: A descriptive assessment based on GPS tracking.

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.

Short-term exposure sequences and anxiety symptoms: a time series clustering of smartphone-based mobility trajectories.

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.

Socioeconomic and environmental determinants of asthma prevalence: a cross-sectional study at the U.S. County level using geographically weighted random forests.

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-physical environments play a role in explaining asthma prevalence, but their relevance seems to vary geographically. The results are vital for implementing future asthma prevention programs that should be tailor-made for specific areas.

Development of an objectively measured walkability index for the Netherlands.

BACKGROUND: Walkability indices have been developed and linked to behavioural and health outcomes elsewhere in the world, but not comprehensively for Europe. We aimed to 1) develop a theory-based and evidence-informed Dutch walkability index, 2) examine its cross-sectional associations with total and purpose-specific walking behaviours of adults across socioeconomic (SES) and urbanisation strata, 3) explore which walkability components drive these associations. METHODS: Components of the index included: population density, retail and service density, land use mix, street connectivity, green space, sidewalk density and public transport density. Each of the seven components was calculated for three Euclidean buffers: 150 m, 500 m and 1000 m around every 6-digit postal code location and for every administrative neighbourhood in GIS. Componential z-scores were averaged, and final indices normalized between 0 and 100. Data on self-reported demographic characteristics and walking behaviours of 16,055 adult respondents (aged 18-65) were extracted from the Dutch National Travel Survey 2017. Using Tobit regression modelling adjusted for individual- and household-level confounders, we assessed the associations between walkability and minutes walking in total, for non-discretionary and discretionary purposes. By assessing the attenuation in associations between partial indices and walking outcomes, we identified which of the seven components drive these associations. We also tested for effect modification by urbanization degree, SES, age and sex. RESULTS: In fully adjusted models, a 10% increase in walkability was associated with a maximum increase of 8.5 min of total walking per day (95%CI: 7.1-9.9). This association was consistent across buffer sizes and purposes of walking. Public transport density was driving the index's association with walking outcomes. Stratified results showed that associations with minutes of non-discretionary walking were stronger in rural compared to very urban areas, in neighbourhoods with low SES compared to high SES, and in middle-aged (36-49 years) compared to young (18-35 years old) and older adults (50-65 years old). CONCLUSIONS: The walkability index was cross-sectionally associated with Dutch adult's walking behaviours, indicating its validity for further use in research.

Greenspace and park use associated with less emotional distress among college students in the United States during the COVID-19 pandemic.

The COVID-19 pandemic has negatively affected many people's psychological health. Impacts may be particularly severe among socially vulnerable populations such as college students, a group predisposed to mental health problems. Outdoor recreation and visits to greenspaces such as parks offer promising pathways for addressing the mental health challenges associated with COVID-19. During the early stages of the pandemic (March-May 2020), we surveyed 1280 college students at four large public universities across the United States (U.S.) to assess how, and why, outdoor recreation and park use changed since the emergence of COVID-19. We also measured students' self-reported levels of emotional distress (a proxy for psychological health) and assessed potential demographic and contextual correlates of distress, including county-level per capita park area and greenness, using generalized linear models. We found that 67% of students reported limiting outdoor activities and 54% reported reducing park use during the pandemic. Students who reduced their use of outdoor spaces cited structural reasons (e.g., lockdowns), concerns about viral transmission, and negative emotions that obstructed active lifestyles. Students who maintained pre-pandemic park use levels expressed a desire to be outdoors in nature, often with the explicit goal of improving mental and physical health. Emotional distress among students was widespread. Models showed higher levels of emotional distress were associated with reducing park use during the pandemic and residing in counties with a smaller area of parks per capita. This study of U.S. college students supports the value of park-based recreation as a health promotion strategy for diverse populations of young adults during a time of crisis.

Contextual factors influencing the urban mobility infrastructure interventions and policies for older adults in low- and middle-income countries: a realist review.

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.

Objective environmental exposures correlate differently with recreational and transportation walking: A cross-sectional national study in the Netherlands.

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. AimTo 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 transportation of adults aged 18 years and above from the Dutch National Travel Survey 2015-2017 (N = 65,785) and analyzed it as an outcome variable. Objective measures of the natural (i.e., normalized difference vegetation index (NDVI), blue space 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 1000 m radii using a geographic information system. To assess associations between recreational and transportation walking and the environmental exposures separately, we fitted Tobit regression models to the walking data, adjusted for multiple confounders. ResultsOn weekdays, people living in areas with less NDVI, higher land-use mix, and higher crossing density were more likely to engage in transportation walking. Recreational walking was negatively associated with NDVI, blue space, crossing density, precipitation and daily average temperature. 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. ConclusionsOur findings suggest that the built and natural environments are differently associated with 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.

Assessing the perceived changes in neighborhood physical and social environments and how they are associated with Chinese internal migrants' mental health.

BACKGROUND: Migrants experience substantial changes in their neighborhood physical and social environments along their migration journeys, but little is known about how perceived changes in their neighborhood environment pre- and post-migration correlate with their mental health. Our aim was to examine the associations between recalled changes in the perceived neighborhood physical and social environments and migrants' mental health in the host city. METHODS: We used cross-sectional data on 591 migrants in Shenzhen, China. We assessed their risk of mental illness using the General Health Questionnaire (GHQ). Neighborhood perceptions were collected retrospectively pre- and post-migration. We used random forests to analyze possibly non-linear associations between GHQ scores and changes in the neighborhood environment, variable importance, and for exploratory analysis of variable interactions. RESULTS: Perceived changes in neighborhood aesthetics, safety, and green space were non-linearly associated with migrants' mental health: A decline in these characteristics was associated with poor mental health, while improvements in them were unrelated to mental health benefits. Variable importance showed that change in safety was the most influential neighborhood characteristic, although individual-level characteristics-such as self-reported physical health, personal income, and hukou (i.e., the Chinese household registration system)-appeared to be more important to explain GHQ scores and also strongly interacted with other variables. For physical health, we found different associations between changes in the neighborhood provoked by migration and mental health. CONCLUSION: Our findings suggest that perceived degradations in the physical environment are related to poorer post-migration mental health. In addition, it seems that perceived changes in the neighborhood environment play a minor role compared to individual-level characteristics, in particular migrants' physical health condition. Replication of our findings in longitudinal settings is needed to exclude reverse causality.

Transportation noise exposure and anxiety: A systematic review and meta-analysis.

BACKGROUND: Exposure to transportation noise is hypothesized to contribute to anxiety, but consistent associations have not been established. OBJECTIVE: To provide a comprehensive synthesis of the literature by examining associations between traffic-related noise (i.e., road traffic noise, railway noise, aircraft noise and mixed traffic noise) and anxiety. METHODS: We systematically searched Web of Science, Scopus, Embase, PubMed, and PsycINFO for English-language observational studies published up to February 2020 reporting on the traffic noise-anxiety association. We appraised the risk of bias using an assessment tool and the quality of evidence following established guidelines. A random-effects meta-analysis was performed for pooled and separated traffic-related noise sources. RESULTS: Of the 3575 studies identified, 11 fulfilled the inclusion criteria and 9 studies were appropriate for meta-analysis. For the pooled overall effect size between transport noise and anxiety, we found 9% higher odds of anxiety associated with a 10 dB(A) increase in day-evening-night noise level (Lden), with moderate heterogeneity (OR = 1.09, 95% CI: [0.97; 1.23], I2 = 70%). The association was more likely to be significant with more severe anxiety (OR = 1.08, 95% CI: [1.01; 1.15], I2 = 48%). Sub-group analysis revealed that the effects of different noise sources on anxiety were inconsistent and insignificant. The quality of evidence was rated as very low to low. CONCLUSIONS: Our findings support the hypothesis of an association between traffic noise and more severe anxiety. More high-quality studies are needed to confirm associations between different noise types and anxiety, as well as to better understand underlying mechanisms.

Using structural equation modeling to examine pathways between perceived residential green space and mental health among internal migrants in China.

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.

Relative importance of perceived physical and social neighborhood characteristics for depression: a machine learning approach.

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.

The effect of short-term exposure to the natural environment on depressive mood: A systematic review and meta-analysis.

BACKGROUND: Research suggests that exposure to the natural environment can improve mood, however, current reviews are limited in scope and there is little understanding of moderators. OBJECTIVE: To conduct a comprehensive systematic review and meta-analysis of the evidence for the effect of short-term exposure to the natural environment on depressive mood. METHODS: Five databases were systematically searched for relevant studies published up to March 2018. Risk of bias was evaluated using the Cochrane Risk of Bias (ROB) tool 1.0 and the Risk of Bias in Non-Randomised Studies of Interventions (ROBINS-I) tool where appropriate. The Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) approach was used to assess the quality of evidence overall. A random-effects meta-analysis was performed. 20 potential moderators of the effect size were coded and the machine learning-based MetaForest algorithm was used to identify relevant moderators. These were then entered into a meta-regression. RESULTS: 33 studies met the inclusion criteria. Effect sizes ranged from -2.30 to 0.84, with an unweighted mean effect size of Mg=-0.29,SD=0.60. However, there was significant residual heterogeneity between studies and risk of bias was high. Type of natural environment, type of built environment, gender mix of the sample, and region of study origin, among others, were identified as relevant moderators but were not significant when entered in a meta-regression. The quality of evidence was rated very low to low. An assessment of publication bias was inconclusive. CONCLUSIONS: A small effect was found for reduction in depressive mood following exposure to the natural environment. However, the high risk of bias and low quality of studies limits confidence in the results. The variation in effect size also remains largely unexplained. It is recommended that future studies make use of reporting guidelines and aim to reduce the potential for bias where possible.

Urban greenery and mental wellbeing in adults: Cross-sectional mediation analyses on multiple pathways across different greenery measures.

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.

Depressive symptoms among Chinese residents: how are the natural, built, and social environments correlated?

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.

The role of the natural and built environment in cycling duration in the Netherlands.

BACKGROUND: Cycling for transportation has the potential to contribute to an increase in people's physical activity levels. A growing body of evidence links the natural and the built environment to cycling. Whereas previous studies were mostly done within one city or one region, the present study covers the whole of the Netherlands, allowing an investigation of whether associations between environmental characteristics and cycling are context-specific. The study examines the extent to which objectively measured natural and built environment characteristics contribute to cycling duration in the Netherlands, as well as the differential effect of environmental characteristics on cycling duration by municipality size. METHODS: Our sample from the Dutch National Travel Survey 2010-2014 comprised 110,027 people aged 20-89 years, residing in 3163 four-digit postal code areas, nested within 387 municipalities across the whole of the Netherlands. Multilevel Tobit regression models were fitted to assess the associations between the natural and the built environment with average daily cycling duration (in minutes), while adjusting for individual and household characteristics. Interaction effects of natural and built environment characteristics and municipality size on cycling duration were also investigated. RESULTS: Higher address density, more bus stops, and shorter distance from home to the nearest train station were positively related to cycling duration. Respondents were more likely to cycle on days with higher temperatures, less wind, and less precipitation. Interaction tests showed that increased street density and address density were less cycling-promotive in small urban areas compared to medium or large cities. On the other hand, the positive association between number of bus stops and cycling duration was weaker in the largest and medium-sized cities compared to small urban and rural areas. CONCLUSIONS: Interactions suggest that relations between environmental characteristics and cycling duration are context-specific (i.e., dependent on circumstances that differ between highly urbanized and less urbanized areas). Our findings need to be replicated in other countries to gain more insight into the interplay between environmental factors and municipality size.

Toward dynamic urban environmental exposure assessments in mental health research.

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.

More green space is related to less antidepressant prescription rates in the Netherlands: A Bayesian geoadditive quantile regression approach.

BACKGROUND: Exposure to green space seems to be beneficial for self-reported mental health. In this study we used an objective health indicator, namely antidepressant prescription rates. Current studies rely exclusively upon mean regression models assuming linear associations. It is, however, plausible that the presence of green space is non-linearly related with different quantiles of the outcome antidepressant prescription rates. These restrictions may contribute to inconsistent findings. OBJECTIVE: Our aim was: a) to assess antidepressant prescription rates in relation to green space, and b) to analyze how the relationship varies non-linearly across different quantiles of antidepressant prescription rates. METHODS: We used cross-sectional data for the year 2014 at a municipality level in the Netherlands. Ecological Bayesian geoadditive quantile regressions were fitted for the 15%, 50%, and 85% quantiles to estimate green space-prescription rate correlations, controlling for physical activity levels, socio-demographics, urbanicity, etc. RESULTS: The results suggested that green space was overall inversely and non-linearly associated with antidepressant prescription rates. More important, the associations differed across the quantiles, although the variation was modest. Significant non-linearities were apparent: The associations were slightly positive in the lower quantile and strongly negative in the upper one. CONCLUSION: Our findings imply that an increased availability of green space within a municipality may contribute to a reduction in the number of antidepressant prescriptions dispensed. Green space is thus a central health and community asset, whilst a minimum level of 28% needs to be established for health gains. The highest effectiveness occurred at a municipality surface percentage higher than 79%. This inverse dose-dependent relation has important implications for setting future community-level health and planning policies.