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

Sociodemographic inequalities in residential nighttime light pollution in urban Bulgaria: An environmental justice analysis

INTRODUCTION

Outdoor nighttime light (NTL) is a potential anthropogenic stressor in urban settings. While ecological studies have identified outdoor NTL exposure disparities, uncertainties remain about disparities in individual exposure levels, particularly in Europe.

AIM

To assess whether some populations are disproportionately affected by outdoor NTL at their residences in urban Bulgaria.

METHODS

We analyzed 2023 data from a representative cross-sectional survey of 4,270 adults from the five largest Bulgarian cities. Respondents' annual exposures to outdoor artificial nighttime luminance were measured using satellite imagery and assigned at their places of residence. We calculated the Gini coefficient as a descriptive NTL inequality measure. Associations between respondents' NTL exposure levels and sociodemographic characteristics were assessed by estimating quantile mixed regression models. Stratified regressions were fitted by gender and for each city.

RESULTS

We found moderate distributive NTL inequalities, as indicated by a 0.214 Gini coefficient. Regression analyses found associations between greater NTL exposure and higher educational attainment. Respondents with incomes perceived as moderate experienced less NTL exposure at the 0.5 and 0.8 quantiles, while unemployed respondents experienced lower exposure at the 0.2 and 0.5 quantiles. We observed null associations for the elderly and non-Bulgarian ethnicities. Regardless of the quantile, greater population density was associated with higher NTL levels. Stratification by sex did not yield substantial differences in the associations. We observed notable city-specific heterogeneities in the associations, with differences in the magnitudes and directions of the associations and the NTL quantiles.

CONCLUSIONS

NTL exposures appeared to embody an environmental injustice dimension in Bulgaria. Our findings suggest that some sociodemographic populations experience higher exposure levels to NTL; however, those are not necessarily the underprivileged or marginalized. Identifying populations with high exposure levels is critical to influencing lighting policies to ease related health implications.

Is Having Urban Green Space in the Neighborhood Enough to Make a Difference? Insights for Healthier City Design

Background: Prior research indicates that engagement with nature is associated with mental well-being; however, the impact of accessibility to urban green spaces (UGS) with suitable infrastructure for visitation and physical activities, like leisure or recreation, remains underexplored, particularly in developing countries. Purpose: This study delves into whether merely having green space in the neighborhood is sufficient to impact residents' mental health in Brazilian metropolitan regions. Method: Utilizing a cross-sectional survey, data were collected from 2136 participants. The analyzed variables included the intensity, duration, and frequency of nature engagement, suitability of UGS for visitation and physical activities, and mental well-being indicators measured by the DASS-21 scale. Multivariate statistical analyses and multiple regression models were employed to verify hypothetical relationships. Results and conclusions: Higher intensity, duration, and frequency of nature engagement in UGS were significantly associated with lower depression, anxiety, and stress scores. Notably, having urban UGS in the neighborhood alone was not enough to reduce mental health issues. Practical implications: The findings point out the need for urban planning policies that prioritize the development of high-quality, accessible green spaces to maximize mental well-being benefits. These insights could inform city designs that foster healthier urban environments. Future directions: Longitudinal studies are needed to establish causality between nature engagement and mental health improvements. Further research should incorporate objective measures of nature engagement and explore more aspects of green space quality, such as biodiversity and amenities.

The economics of nature's healing touch: A systematic review and conceptual framework of green space, pharmaceutical prescriptions, and healthcare expenditure associations

Green spaces play a crucial role in promoting sustainable and healthy lives. Recent evidence shows that green space also may reduce the need for healthcare, prescription medications, and associated costs. This systematic review provides the first comprehensive assessment of the available literature examining green space exposure and its associations with healthcare prescriptions and expenditures. We applied Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines to search MEDLINE, Scopus, and Web of Science for observational studies published in English through May 6, 2023. A quality assessment of the included studies was conducted using the Office of Health Assessment and Translation (OHAT) tool, and the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) assessment was used to evaluate the overall quality of evidence. Our search retrieved 26 studies that met the inclusion criteria and were included in our review. Among these, 20 studies (77 % of the total) showed beneficial associations of green space exposure with healthcare prescriptions or expenditures. However, most studies had risks of bias, and the overall strength of evidence for both outcomes was limited. Based on our findings and related bodies of literature, we present a conceptual framework to explain the possible associations and complex mechanisms underlying green space and healthcare outcomes. The framework differs from existing green space and health models by including upstream factors related to healthcare access (i.e., rurality and socioeconomic status), which may flip the direction of associations. Additional research with lower risks of bias is necessary to validate this framework and better understand the potential for green space to reduce healthcare prescriptions and expenditures.

Show me the money! Associations between tree canopy and hospital costs in cities for cardiovascular disease events in a longitudinal cohort study of 110,134 participants

Health benefits from urban greening are assumed to translate into reduced healthcare expenditure, yet few studies have tested this. A total of 110,134 participants in the Sax Institute's 45 and Up Study in the Australian cities of Sydney, Newcastle, or Wollongong were linked with hospital cost data for cardiovascular disease (CVD) events (e.g., acute myocardial infarctions) up to 30 June 2018. Associations between percentages of total green space, tree canopy, and open grass within 1.6 km of participants homes and annual per person measured CVD-related hospital costs were analysed using generalised linear model (GLM) with gamma density as a component of a two-part mixture model, adjusting for confounders. Overall, 26,243 participants experienced a CVD-related hospitalisation. Incidence was lower among participants with 10 % more tree canopy (OR 0.98, 95 %CI 0.96, 0.99), but not with higher total green space or open grass percentages. Total costs of hospitalisations per year were lower with 10 % more tree canopy (means ratio 0.96, 95 %CI 0.95, 0.98), but also higher with 10 % more open grass (means ratio 1.04, 95 %CI 1.02, 1.06). It was estimated that raising tree canopy cover to 30 % or more for individuals with currently less than 10 % could lead to a within-sample annual saving per person of AU$ 193 overall and AU$ 569 for those who experienced one or more CVD-related hospital admissions. This projects to an estimated annual health sector cost reduction of AU$ 19.3 million per 100,000 individuals for whom local tree canopy cover is increased from less than 10 % to 30 % or higher. In conclusion, this longitudinal study is among the first to analyse measured healthcare cost data in relation to urban green space in general, and with differentiation between major types of greenery relevant to urban planning policies in cities around the world. In sum, this study advances an increasingly important and international focus of research by reporting on the lower burden of CVD and fewer associated hospitalisations stemming from upstream investments that protect and restore urban tree canopy, which not only translates into substantial reduced costs for the health sector, but also helps to create regenerative cities and flourishing communities.

The use of Enhanced Vegetation Index for assessing access to different types of green space in epidemiological studies

BACKGROUND

Exposure to green space can protect against poor health through a variety of mechanisms. However, there is heterogeneity in methodological approaches to exposure assessments which makes creating effective policy recommendations challenging.

OBJECTIVE

Critically evaluate the use of a satellite-derived exposure metric, the Enhanced Vegetation Index (EVI), for assessing access to different types of green space in epidemiological studies.

METHODS

We used Landsat 5-8 (30 m resolution) to calculate average EVI for a 300 m radius surrounding 1.4 million households in Wales, UK for 2018. We calculated two additional measures using topographic vector data to represent access to green spaces within 300 m of household locations. The two topographic vector-based measures were total green space area stratified by type and average private garden size. We used linear regression models to test whether EVI could discriminate between publicly accessible and private green space and Pearson correlation to test associations between EVI and green space types.

RESULTS

Mean EVI for a 300 m radius surrounding households in Wales was 0.28 (IQR = 0.12). Total green space area and average private garden size were significantly positively associated with corresponding EVI measures (β = < 0.0001, 95% CI: 0.0000, 0.0000; β = 0.0001, 95% CI: 0.0001, 0.0001 respectively). In urban areas, as average garden size increases by 1 m2, EVI increases by 0.0002. Therefore, in urban areas, to see a 0.1 unit increase in EVI index score, garden size would need to increase by 500 m2. The very small β values represent no 'measurable real-world' associations. When stratified by type, we observed no strong associations between greenspace and EVI.

IMPACT

It is a widely implemented assumption in epidiological studies that an increase in EVI is equivalent to an increase in greenness and/or green space. We used linear regression models to test associations between EVI and potential sources of green reflectance at a neighbourhood level using satellite imagery from 2018. We compared EVI measures with a 'gold standard' vector-based dataset that defines publicly accessible and private green spaces. We found that EVI should be interpreted with care as a greater EVI score does not necessarily mean greater access to publicly available green spaces in the hyperlocal environment.

Greenspace and Land Cover Diversity During Pregnancy in a Rural Region, and Associations With Birth Outcomes

Beneficial effects on health outcomes have been observed from exposure to spaces with substantial green vegetation ("greenspace"). This includes studies of greenspace exposure on birth outcomes; however, these have been conducted largely in urban regions. We characterized residential exposure to greenspace and land cover diversity during pregnancy in rural northern New England, USA, investigating whether variation in greenspace or diversity related to newborn outcomes. Five landscape variables (greenspace land cover, land cover diversity, impervious surface area, tree canopy cover, and the Normalized Difference Vegetation Index) were aggregated within six circular zones of radii from 100 to 3,000 m around residential addresses, and distance to conservation land was measured, providing a total of 31 greenspace and diversity metrics. Four birth outcomes along with potentially confounding variables were obtained from 1,440 participants in the New Hampshire Birth Cohort Study. Higher greenspace land cover up to 3,000 m was associated with larger newborn head circumference, while impervious surface area (non-greenspace) had the opposite association. Further, birth length was positively associated with land cover diversity. These findings support beneficial health impacts of greenspace exposure observed in urban regions for certain health outcomes, such as newborn head circumference and length but not others such as birthweight and gestational age. Further our results indicate that larger radius buffer zones may be needed to characterize the rural landscape. Vegetation indices may not be interchangeable with other greenspace metrics such as land cover and impervious surface area in rural landscapes.

Critical factors influencing visitor emotions: analysis of "restorativeness" in urban park visits in Fuzhou, China

Objective

To date, a comprehensive analysis of urban green space (UGS) visitors' emotional remains largely unexplored. In this study, we focus on how UGS environmental preferences, restorativeness, other physical factors (sound, air, and thermal environments), and individual characteristics affecting visitor emotions. Such a comprehensive analysis would allow relevant practitioners to check the environmental quality of UGSs and improve certain conditions to promote visitor emotions.

Methods

A total of 904 questionnaire responses with concurrently monitored physical factors were analyzed by independent sample t-tests, one-way ANOVA and path analysis.

Results

The thermal evaluation had the largest impact on positive emotions (β = 0.474), followed by perceived restorativeness (β = 0.297), which had β values of -0.120 and -0.158, respectively, on negative emotions. Air evaluation was more effective for increasing positive emotions (β = 0.293) than reducing negative emotions (β = -0.115). Sound evaluation also had similar results (β = 0.330 vs. β = -0.080). Environmental preference significantly influenced only positive emotions (β = 0.181) but could still indirectly impact negative emotions. Moreover, objective physical factors can indirectly affect visitors' emotions by enhancing their evaluations..

Conclusion

The influence of different UGS environmental factors on visitors' emotions vary, as does their impacts on positive versus negative emotions. Positive emotions were generally more affected than negative emotions by UGS. Visitor emotions were mainly influenced by physical and psychological factors. Corresponding suggestions are proposed for UGS design and management in this study.

Perceptions of and interactions with green neighbourhood environment - A qualitative study

BACKGROUND

Green environments have been shown to be important for health, although less is known about what, in the environment and the individual, leads to interaction and promotes engagement in activities.

AIM

To explore some individuals' perceptions of their green neighbourhood environment and how the interaction with it promotes engagement in activities.

MATERIAL AND METHODS

A qualitative approach was used comprising eight semi-structured interviews and directed content analysis based on the Model of Human Occupation.

RESULTS

The green neigbourhood environment (GNE) offered opportunities to challenge the participants' performance capacity, develop habits and engage in activities. The GNE also gave stress relief and helped the participants experience balance. Experiences of interacting with green environments earlier in life and the cultural context seemed to be the main reason why the participants interacted with the GNE.Conclusions and significance: Norms and values from the childhood, previous experiences and interests were of particular importance for interaction with the GNE. Green environments gave perspective, a sense of being part of something larger and helped individuals achieve balance. Based on this knowledge, occupational therapists can enable individuals to interact with the green environment.

Examining neighborhood effects on mental health utilizing a novel two-stage modeling approach

PURPOSE

Neighborhood conditions may affect health, but health may also determine a preference for where to live. This study estimates the effect of neighborhood characteristics on mental health while aiming to adjust for this residential self-selection.

METHODS

A two-step method was implemented using register data from Statistics Netherlands from all residents of the city of Rotterdam relocating within the city in 2013 (N = 12,456). First, using a conditional logit model, we estimated for each individual the probability of relocating to a neighborhood over all other neighborhoods in Rotterdam, based on personal and neighborhood characteristics in 2013. Second, we corrected this selection process in a model investigating the effects of neighborhood characteristics in 2014 on reimbursed anti-depressant or anti-psychotic medication in 2016.

RESULTS

Personal and neighborhood characteristics predicted neighborhood choice, indicating strong patterns of selection into neighborhoods. Unadjusted for selection log neighborhood income was associated with reimbursed medication (β = -0.040, 95% CI = -0.060, -0.020), but the association strongly attenuated after controlling for self-selection into neighborhoods (β = -0.010, 95% CI = -0.030, 0.011). The opposite was observed for contact with neighbors; unadjusted for self-selection there was no association (β = -0.020, 95% CI = -0.073, 0.033), but after adjustment increased neighborhood contact was associated with an 8.5% relative reduction in reimbursed medication (β = -0.075, 95% CI = -0.126, -0.025).

CONCLUSIONS

The method illustrated in this study offers new opportunities to disentangle selection from causation in neighborhood health research.

Association between urban green space and postpartum depression, and the role of physical activity: a retrospective cohort study in Southern California

Background

Little research exists regarding the relationships between green space and postpartum depression (PPD). We aimed to investigate the relationships between PPD and green space exposure, and the mediating role of physical activity (PA).

Methods

Clinical data were obtained from Kaiser Permanente Southern California electronic health records in 2008-2018. PPD ascertainment was based on both diagnostic codes and prescription medications. Maternal residential green space exposures were assessed using street view-based measures and vegetation types (i.e., street tree, low-lying vegetation, and grass), satellite-based measures [i.e., Normalized Difference Vegetation Index (NDVI), land-cover green space, and tree canopy cover], and proximity to the nearest park. Multilevel logistic regression was applied to estimate the association between green space and PPD. A causal mediation analysis was performed to estimate the proportion mediated by PA during pregnancy in the total effects of green space on PPD.

Findings

In total, we included 415,020 participants (30.2 ± 5.8 years) with 43,399 (10.5%) PPD cases. Hispanic mothers accounted for about half of the total population. A reduced risk for PPD was associated with total green space exposure based on street-view measure [500 m buffer, adjusted odds ratio (OR) per interquartile range: 0.98, 95% CI: 0.97-0.99], but not NDVI, land-cover greenness, or proximity to a park. Compared to other types of green space, tree coverage showed stronger protective effects (500 m buffer, OR = 0.98, 95% CI: 0.97-0.99). The proportions of mediation effects attributable to PA during pregnancy ranged from 2.7% to 7.2% across green space indicators.

Interpretation

Street view-based green space and tree coverage were associated with a decreased risk of PPD. The observed association was primarily due to increased tree coverage, rather than low-lying vegetation or grass. Increased PA was a plausible pathway linking green space to lower risk for PPD.

Funding

National Institute of Environmental Health Sciences (NIEHS; R01ES030353).

Are actual and perceived environmental conditions associated with variation in mental health?

OBJECTIVE

Empirical evidence on the relationship between environmental factors and mental health remains inconclusive. One reason is that there is only scant evidence on the association between mental health and subjective exposure to environmental stressors, relative to objective pollution. We thus focus on how the perceived and actual presence of noise, air pollution, and green spaces relates to mental health.

METHODS AND RESULTS

Our cross-sectional study is based on a large representative sample of the adult population in Switzerland (n = 5729). Using individual-level geocodes of subjects' residence, we combined data from a survey of these individuals with data on objectively measured longer-term environmental conditions (noise, air pollution, green spaces). Subclinical mental health was assessed with the 12-item General Health Questionnaire (GHQ-12). When fitting multiple regressions and mediation models, we find that perceptions of environmental stressors are a better predictor of mental distress than objectively measured stressors. In addition, the predictive power of actual nature visits is stronger than the predictive power of mere proximity to green spaces at the place of residence. We found no direct link between actual environmental stressors and mental health, but mediation via perceived environmental stressors. Further, the association between the frequency of nature visits and mental health is mediated by perceived, but not actual pollution.

CONCLUSION

Since actual environmental stressors are not perceived as equally burdensome by all people, their subjective perception is crucial when evaluating policy interventions aimed at improving mental health. Even a relatively low level of environmental stressors, classified as non-harmful to human health in a physical or biological sense, may thus contribute to negative mental health outcomes. The main policy implication is that attractive and accessible green spaces may provide individuals with an enhanced sense of control over their exposure to environmental stressors and thereby reduce negative impacts.

Green place rather than green space as a health determinant: A 20-year scoping review

Numerous scientific studies, applying different approaches, have provided evidence of the links between the environment and people's health. Green spaces have been the subject of research aimed at exploring their benefits as components of the urban environment. We investigated possible causal relationships between green spaces and health, with the aim of addressing the following question. Does the mere material presence of green spaces contribute to the health of people who live in its vicinity, or are the health-promoting qualities of green spaces attributed to the ability of people to actually see, access, and enjoy them? The latter view highlights the relational dimension of places, and it entails personal relationships with places which are imbued with psychological meaning and significance for those who visit and experience them. We reviewed relevant literature, comprising a total of 189 papers on this topic that have been published over the first two decades of this century. Our findings showed that the material aspects of green spaces, such as their abundance and proximity to residences, received much more attention in studies than their quality and characteristics. However, relational rather than material measures of green spaces demonstrated statistically greater positive impacts of green spaces on health. These findings indicate that both sensory stimuli and activities and feelings attached to green spaces are essential for better health outcomes. Incorporating a relational perspective of green place-thinking into the existing literature on green spaces and health could contribute to optimizing the positive effects of green spaces and thus to the creation of healthy and livable cities.

The ‘Rippling’ Waves of Wellbeing: A Mixed Methods Evaluation of a Surf-Therapy Intervention on Patients with Acquired Brain Injury

Dominant psychological models of wellbeing neglect the role that nature connection and other key factors, such as positive health behaviours and behaviour change, play in determining wellbeing. The present mixed-methods evaluation explores the impact of ”Surf-Ability”, an adapted surf therapy intervention delivered in collaboration with a UK neurorehabilitation service, on individuals with acquired brain injury (ABI) as part of an effort to design interventions based on advances in wellbeing science. Following five surf-therapy sessions, within-subjects analysis (n= 15) revealed significant improvements on the Warwick–Edinburgh mental wellbeing scale (t (15) = −2.164, p = 0.048), as well as in anxiety and happiness as measured via a brief visual analogue. No significant changes occurred in the Hospital Anxiety and Depression Scale (HADS) or resting heart rate variability (HRV). A ripple effects mapping (REM) session at 6–10 months follow-up (n = 6) revealed that the physical and psychological experience of a nature-based challenge initiated a mindset shift in participants, which ultimately led to them adopting wellbeing-promoting long-term behaviour changes. These changes occurred at the scale of (1) individual wellbeing—increased mindfulness and physical activity; (2) collective wellbeing—improved relationships, community participation and contribution to organisations; and (3) planetary wellbeing—connection to nature. These findings align with the GENIAL theoretical framework, which defines wellbeing from a biopsychosocial ecological perspective across multiple levels of scale. The findings support the need for healthcare providers—including neurorehabilitation services—to enhance interventions for patients by incorporating novel factors that improve wellbeing, such as nature-connection.

Residential green space and mental health-related prescription medication sales: An ecological study in Belgium

BACKGROUND

Residential green space has been associated with mental health benefits, but how such associations vary with green space types is insufficiently known.

OBJECTIVE

We aimed to investigate associations between types and quantities of green space and sales of mood disorder medication in Belgium.

METHODS

We used aggregated sales data of psycholeptics and psychoanaleptics prescribed to adults from 2006 to 2014. Generalized mixed effects models were used to investigate associations between relative covers of woodland, low-green, grassland, and garden, and average annual medication sales. Models were adjusted for socio-economic background variables, urban-rural differences, and administrative region, and included random effects of latitude and longitude.

RESULTS

Urban census tracts were associated with 9-10% higher medication sales. In nationwide models, a 10% increase in relative cover of woodland, garden, and grass was associated with a 1-2% decrease in medication sales. The same association was found for low green but only for men. In stratified models, a 10% increase in relative cover of any green space type in urban census tracts was associated with a decrease of medication sales by 1-3%. In rural census tracts, no protective associations between green space and mood disorder medication sales were observed, with the exception of relative woodland cover for women (-1%), and low green was associated with higher medication sales (+6-7%).

CONCLUSIONS

Taken together, these results suggest that living in green environments may be beneficial for adult mental health. Woodland exposure seemed the most beneficial, but the amount of green space was more important than the type. Results underline the importance of conserving green space in our living environment, for the conservation of biodiversity and for human health.

The effects of greenness exposure on hypertension incidence among Chinese oldest-old: a prospective cohort study

BACKGROUND

Although the oldest-old (those aged over 80 years) are vulnerable to environmental factors and have the highest prevalence of hypertension, studies focusing on greenness exposure and the development of hypertension among them are insufficient. The aim of this study was to explore the association between residential greenness and hypertension in the oldest-old population.

METHODS

This cohort study included data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). The oldest-old were free of hypertension at baseline (2008), and hypertension events were assessed by follow-up surveys in 2011, 2014, and 2018. The one-year averages of the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) at 500-m buffer before the interview year of incident hypertension or last censoring interview were collected at the level of 652 residential units (district or county). The linear or nonlinear association between greenness and hypertension incidence was analyzed using the Cox proportional hazards model with penalized splines. The linear links between greenness and hypertension incidence were determined using the Cox proportional hazards model included a random effect term.

RESULTS

Among 5253 participants, the incidence rate of hypertension was 7.25 (95% confidence interval [CI]: 6.83-7.67) per 100 person-years. We found a nonlinear association between greenness exposure and hypertension risk, and the exposure-response curve showed that 1 change point existed. We examined the linear effect of greenness on hypertension by categorizing the NDVI/EVI into low and high-level exposure areas according to the change point. We found more notable protective effects of each 0.1-unit increase in greenness on hypertension incidence for participants living in the high-level greenness areas (hazard ratio (HR) = 0.60; 95% CI: 0.53-0.70 for NDVI; HR = 0.46; 95% CI: 0.37-0.57 for EVI). In contrast, no significant influence of greenness exposure on hypertension risk was found for participants living in the low-level greenness areas (HR = 0.77; 95% CI: 0.38-1.55 for NDVI; HR = 0.73; 95% CI: 0.33-1.63 for EVI).

CONCLUSIONS

Greenness exposure is nonlinearly associated with hypertension risk among the oldest-old, presenting its relationship in an inverse "U-shaped" curve. Greenness is a protective factor that decreases the risk of hypertension.

Urban greenspace and mental health in Chinese older adults: Associations across different greenspace measures and mediating effects of environmental perceptions

This study aimed to contrast the associations of street view-, land use- and satellite-derived greenspace measures with older adults' mental health and to examine the mediating effects of neighborhood environmental perceptions (i.e., noise, aesthetics and satisfaction with recreational opportunities) to explain potential heterogeneity in the associations. Data of 879 respondents aged 60 or older in Dalian, China were used, and multilevel regression models were conducted in Stata. Results indicated that the Normalized Difference Vegetation Index (NDVI), vegetation coverage, park coverage and streetscape grasses were positively correlated with older adults' mental health. The associations of exposure metrics measured by overhead view were stronger than those measured by the street view. Streetscape grasses had a stronger association with older adults' mental health than streetscape trees. Noise, aesthetics and satisfaction with recreational opportunities mediated these associations, but the strength of the mediating effects differed across the greenspace measures. Our findings confirm the necessity of multi-measures assessment for greenspace to examine associations with older adults' mental health in Chinese settings and can contribute to the realization of health benefits of urban greenspace.

Perceived green space quality, child biomarkers and health-related outcomes: A longitudinal study

Accumulating exposure to quality green space over time is posited to influence child health, yet longitudinal studies are scarce. This study aimed to examine the associations between trajectories of perceived green space quality and child health-related outcomes. We used data from 1874 childrenin the B-cohort of the Longitudinal Study of Australian Children who participated in the Child Health Checkpoint module at 11-12 years. Data on caregiver perceived green space quality measured biennially was assessed using discrete trajectory mixture models to group children by contrasting distributions in green space quality over time. Examination of associations between trajectory groups of perceived green space quality and child biomarkers (i.e., albumin-to-creatinine ratio, total, cholesterol, total triglycerides, and glucose), physical health and behavioural assessments (i.e., anthropometric measurements, blood pressure, sedentary behaviour, physical activity, sleep, aerobic work capacity, and general wellbeing), and health care use were assessed using multilevel models, adjusted for sociodemographic variables. Four perceived green space quality trajectories were identified: "decreasing quality from high to moderate"; "increasing quality from low to high"; "consistently high quality"; "consistently low quality". Compared with consistently low levels of quality green space, adjusted models indicated consistently high-quality green space was associated with lower total triglycerides (β -0.13; 95%CI -0.25, -0.01). Lower odds of hospital admission was observed among children who accumulated quality green space over time (OR 0.45; 95%CI 0.23, 0.87). These associations were observed in boys only in sex-stratified analyses. Moreover, boys accumulating quality green space through time tended to have lower diastolic blood pressure (β -2.76; 95%CI -5.17, -0.35) and girls who experienced loss in quality green space tended to have a higher percentage of body fat (β 2.81; 95%CI 0.43, 5.20). Accumulating quality green space over time is important for various aspects of child health, with contrasting benefits by sex.

Increased Wellbeing following Engagement in a Group Nature-Based Programme: The Green Gym Programme Delivered by the Conservation Volunteers

The wellbeing benefits of engaging in a nature-based programme, delivered by the Voluntary, Community and Social Enterprise sector, were examined in this study. Prior to attending The Conservation Volunteers' Green Gym™, attendees (n = 892) completed demographics, health characteristics and the Warwick Edinburgh Mental Wellbeing Short-Form Scale. Attendees (n = 253, 28.4%) provided a measure on average 4.5 months later. There were significant increases in wellbeing after engaging in Green Gym, with the greatest increases in those who had the lowest starting levels of wellbeing. Wellbeing increases were sustained on average 8.5 months and 13 months later in those providing a follow up measure (n = 92, n = 40, respectively). Attendees who continued to engage in Green Gym but not provide follow up data (n = 318, 35.7%) tended to be more deprived, female and self-report a health condition. Attendees who did not continue to engage in Green Gym (n = 321, 36.0%) tended to be less deprived and younger. These findings provide evidence of the wellbeing benefits of community nature-based activities and social ('green') prescribing initiatives and indicate that Green Gym targets some groups most in need.

PrAna: an R package to calculate and visualize England NHS primary care prescribing data

Background

The objective of this work to calculate prescribed quantity of an active pharmaceutical ingredient (API) in prescription medications for human use, to facilitate research on the prediction of amount of API released to the environment and create an open-data tool to facilitate spatiotemporal and long-term prescription trends for wider usage.

Design

We have developed an R package, PrAna to calculate the prescribed quantity (in kg) of an APIs by postcode using England’s national level prescription data provided by National Health Service, for the years 2015–2018. Datasets generated using PrAna can be visualized in a real-time interactive web-based tool, PrAnaViz to explore spatiotemporal and long-term trends. The visualisations can be customised by selecting month, year, API, and region.

Results

PrAnaViz’s targeted API approach is demonstrated with the visualisation of prescribed quantities of 14 APIs in the Bath and North East Somerset (BANES) region during 2018. Once the APIs list is loaded, the back end retrieves relevant data and populates the graphs based on user-defined data features in real-time. These plots include the prescribed quantity of APIs over a year, by month, and individual API by month, general practice, postcode, and medicinal form. The non-targeted API approach is demonstrated with the visualisation of clarithromycin prescribed quantities at different postcodes in the BANES region.

Conclusion

PrAna and PrAnaViz enables the analysis of spatio-temporal and long-term trends with prescribed quantities of different APIs by postcode. This can be used as a support tool for policymakers, academics and researchers in public healthcare, and environmental scientist to monitor different group of pharmaceuticals emitted to the environment and for prospective risk assessment of pharmaceuticals in the environment.

Assessing the role of urban green spaces for human well-being: a systematic review

Human has been evolving in a natural environment over a long time; thus, he is habitual to adapt it. Green spaces are obligatory landscapes in an urban structure that provide a natural environment and accelerate other life events. In contrast, unplanned urbanization, and conversion from green to grey structures have damaged natural environmental resources. Studies through different angles have highlighted the importance of urban green spaces for human well-being but now need to identify their role according to the potential. The demands of urban green spaces may differ with the change of population size, types of grey structure, urban expansion, the altitude of the place, and geographical location. Therefore, this systematic review aims to analyse the significance of urban green spaces for human well-being. The study opted for a systematic process during the selection and organization of studies for this review. After analysing, 46 studies were finalized with the consensus of three review authors. Accordingly, literature was analysed under the central theme of "Urban Green Spaces for Human Well-being." Human Well-being was assessed under six sub-themes; physical, psychological, mental, social, subjective, and environmental well-being. The review concluded that urban green spaces are the primary pillar for a sustainable urban place and human well-being due to highly positive and positive correlations. Moreover, the study did not find any demarcation line between green spaces and grey structures according to any specific need. Therefore, the study suggested that the role of urban green spaces for human well-being should be analysed according to their potential and required optimal ratio under different communities' urban specific environments and social behaviour.

The Influence of Covid-19 on Perceived Health Effects of Wetland Parks in China

Wetland parks are designed to support urban ecological protection, flood control and human well-being. Existing research mainly focuses on their influence on ecology and economy. However, their influence on human well-being and health is rarely studied. In China, during the peak of the COVID-19 pandemic (Peak), people were very concerned about health, while at the same time wetland parks which are generally considered beneficial to health were closed. Thus, this study explores the public's perception of the health effects of visiting wetland parks and the impact of the pandemic on the perception. From March 5th to 8th, 2020, before the Peak in China was over, 1,400 respondents participated in a nationwide online survey. It was found that the perceived benefits from visiting wetland parks were higher in terms of mental health than in physical health. Also, the perceived health benefits of wetland parks after the Peak were slightly higher than before the pandemic. The results highlight that wildlife habitat services were considered to be the most important ecosystem services that promote the perceived health benefits. Interestingly, the perceived health benefits of wetland parks by health experts appear to be lower than in other groups, indicating that the health benefits of visiting wetland parks may be overestimated by lay-people or underestimated by health experts. The results provide empirical evidence for managing ecosystem services as delivered by these urban wetlands, in the context of COVID-19 or potential future pandemics, for promoting public health.

Is urban green space associated with lower mental healthcare expenditure?

INTRODUCTION

While the evidence of mental health benefits from investing in green space accumulates, claims of reduced healthcare expenditure are rarely supported by evidence from analyses of actual healthcare data. Additionally, the question of 'who pays?' has been ignored. We addressed these gaps using person-level data in three Australian cities.

METHODS

55,339 participants with a mean follow-up time of 4.97 years in the Sax Institute's 45 and Up Study (wave 2, collected 2012-2015) were linked to fee-for-service records of antidepressant prescriptions and talking therapy subsidised by the Australian Government (including data on per unit fee, state subsidy, and individual co-payment). Total green space, tree canopy and open grass within 1.6 km road network distances were linked to each participant. Multilevel logistic, negative binomial, and generalised linear models with gamma distribution adjusted for demographic and socioeconomic confounders were used to assess association between each green space variable and prescribing/referral and costs of antidepressants and talking therapy.

RESULTS

Prescription of at least one course of antidepressants occurred for 20.01% (n = 11,071). Referral for at least one session of talking therapy occurred in 8.95% (n = 4954). 13,482 participants (24.4%) had either a prescription or a referral. A 10% increase in green space was associated with higher levels of antidepressant prescribing (e.g. incident rate ratio (IRR) = 1.06, 95%CI = 1.04-1.08). Tree canopy was not associated with antidepressant prescribing or referrals for talking therapy. Open grass was associated with higher odds (OR = 1.17, 95%CI = 1.13-1.20) and counts (IRR = 1.05, 95%CI = 1.02-1.08) of antidepressant prescriptions. Open grass was also associated with lower odds (OR = 0.87, 95%CI = 0.82-0.92) and counts (IRR = 0.93, 95%CI = 0.90-0.96) of talking therapy referrals. Open grass was associated with higher total and mean per-person levels of expenditure on antidepressant prescriptions.

CONCLUSION

Although green space supports mental health, these unexpected results provide pause for reflection on whether greening strategies will always result in purported reductions in mental healthcare expenditure.

Using machine learning to examine street green space types at a high spatial resolution: Application in Los Angeles County on socioeconomic disparities in exposure

BACKGROUND

Compared to commonly-used green space indicators from downward-facing satellite imagery, street view-based green space may capture different types of green space and represent how environments are perceived and experienced by people on the ground, which is important to elucidate the underlying mechanisms linking green space and health.

OBJECTIVES

This study aimed to evaluate machine learning models that can classify the type of vegetation (i.e., tree, low-lying vegetation, grass) from street view images; and to investigate the associations between street green space and socioeconomic (SES) factors, in Los Angeles County, California.

METHODS

SES variables were obtained from the CalEnviroScreen3.0 dataset. Microsoft Bing Maps images in conjunction with deep learning were used to measure total and types of street view green space, which were compared to normalized difference vegetation index (NDVI) as commonly-used satellite-based green space measure. Generalized linear mixed model was used to examine associations between green space and census tract SES, adjusting for population density and rural/urban status.

RESULTS

The accuracy of the deep learning model was high with 92.5% mean intersection over union. NDVI were moderately correlated with total street view-based green space and tree, and weakly correlated with low-lying vegetation and grass. Total and three types of green space showed significant negative associations with neighborhood SES. The percentage of total green space decreased by 2.62 [95% confidence interval (CI): -3.02, -2.21, p < 0.001] with each interquartile range increase in CalEnviroScreen3.0 score. Disadvantaged communities contained approximately 5% less average street green space than other communities.

CONCLUSION

Street view imagery coupled with deep learning approach can accurately and efficiently measure eye-level street green space and distinguish vegetation types. In Los Angeles County, disadvantaged communities had substantively less street green space. Governments and urban planners need to consider the type and visibility of street green space from pedestrian's perspective.

Using machine learning to examine street green space types at a high spatial resolution: Application in Los Angeles County on socioeconomic disparities in exposure

BACKGROUND

Compared to commonly-used green space indicators from downward-facing satellite imagery, street view-based green space may capture different types of green space and represent how environments are perceived and experienced by people on the ground, which is important to elucidate the underlying mechanisms linking green space and health.

OBJECTIVES

This study aimed to evaluate machine learning models that can classify the type of vegetation (i.e., tree, low-lying vegetation, grass) from street view images; and to investigate the associations between street green space and socioeconomic (SES) factors, in Los Angeles County, California.

METHODS

SES variables were obtained from the CalEnviroScreen3.0 dataset. Microsoft Bing Maps images in conjunction with deep learning were used to measure total and types of street view green space, which were compared to normalized difference vegetation index (NDVI) as commonly-used satellite-based green space measure. Generalized linear mixed model was used to examine associations between green space and census tract SES, adjusting for population density and rural/urban status.

RESULTS

The accuracy of the deep learning model was high with 92.5% mean intersection over union. NDVI were moderately correlated with total street view-based green space and tree, and weakly correlated with low-lying vegetation and grass. Total and three types of green space showed significant negative associations with neighborhood SES. The percentage of total green space decreased by 2.62 [95% confidence interval (CI): -3.02, -2.21, p < 0.001] with each interquartile range increase in CalEnviroScreen3.0 score. Disadvantaged communities contained approximately 5% less average street green space than other communities.

CONCLUSION

Street view imagery coupled with deep learning approach can accurately and efficiently measure eye-level street green space and distinguish vegetation types. In Los Angeles County, disadvantaged communities had substantively less street green space. Governments and urban planners need to consider the type and visibility of street green space from pedestrian's perspective.

Urban Nature and Public Health: How Nature Exposure and Sociocultural Background Relate to Depression Risk

As the world’s population becomes more urbanized, there is an associated decrease in nature exposure and a rise in noncommunicable diseases, including depression. Previous cross-sectional studies examining urban nature exposure and depression have reported favorable associations. However, many of these studies rely primarily on nature exposure metrics that measure the intensity of nature exposure, while other dimensions of urban nature exposure remain understudied. Therefore, in a cross-sectional, questionnaire-based case study targeting a general urban population (n = 282), we examined the relationship between two less commonly studied urban nature exposure variables (i.e., gardening behavior and greenspace visit frequency) and depression risk while also considering sociocultural background (multivariate logistic regression model). Results indicated that being a gardener was significantly associated with a reduced odds of being at risk of depression and that having a family migration history, but not a self-migration history, was associated with increased odds of being at risk of depression. In the examination of neighborhood socialization frequency and depression risk, we did not determine any significant association. The results of this study, therefore, highlight the importance of considering both people’s sociocultural backgrounds and urban nature exposure in more detail to help plan for and support healthier cities in the future.

A multilevel scenario based predictive analytics framework to model the community mental health and built environment nexus

The built environment affects mental health outcomes, but this relationship is less studied and understood. This article proposes a novel multi-level scenario-based predictive analytics framework (MSPAF) to explore the complex relationships between community mental health outcomes and the built environment conditions. The MSPAF combines rigorously validated interpretable machine learning algorithms and scenario-based sensitivity analysis to test various hypotheses on how the built environment impacts community mental health outcomes across the largest metropolitan areas in the US. Among other findings, our results suggest that declining socio-economic conditions of the built environment (e.g., poverty, low income, unemployment, decreased access to public health insurance) are significantly associated with increased reported mental health disorders. Similarly, physical conditions of the built environment (e.g., increased housing vacancies and increased travel costs) are significantly associated with increased reported mental health disorders. However, this positive relationship between the physical conditions of the built environment and mental health outcomes does not hold across all the metropolitan areas, suggesting a mixed effect of the built environment's physical conditions on community mental health. We conclude by highlighting future opportunities of incorporating other variables and datasets into the MSPAF framework to test additional hypotheses on how the built environment impacts community mental health.

Moving Beyond Disciplinary Silos Towards a Transdisciplinary Model of Wellbeing: An Invited Review

The construct of wellbeing has been criticised as a neoliberal construction of western individualism that ignores wider systemic issues such as inequality and anthropogenic climate change. Accordingly, there have been increasing calls for a broader conceptualisation of wellbeing. Here we impose an interpretative framework on previously published literature and theory, and present a theoretical framework that brings into focus the multifaceted determinants of wellbeing and their interactions across multiple domains and levels of scale. We define wellbeing as positive psychological experience, promoted by connections to self, community and environment, supported by healthy vagal function, all of which are impacted by socio-contextual factors that lie beyond the control of the individual. By emphasising the factors within and beyond the control of the individual and highlighting how vagal function both affects and are impacted by key domains, the biopsychosocial underpinnings of wellbeing are explicitly linked to a broader context that is consistent with, yet complementary to, multi-levelled ecological systems theory. Reflecting on the reciprocal relationships between multiple domains, levels of scale and related social contextual factors known to impact on wellbeing, our GENIAL framework may provide a foundation for a transdisciplinary science of wellbeing that has the potential to promote the wellbeing of individuals while also playing a key role in tackling major societal challenges.

Associations between green/blue spaces and mental health across 18 countries

Living near, recreating in, and feeling psychologically connected to, the natural world are all associated with better mental health, but many exposure-related questions remain. Using data from an 18-country survey (n = 16,307) we explored associations between multiple measures of mental health (positive well-being, mental distress, depression/anxiety medication use) and: (a) exposures (residential/recreational visits) to different natural settings (green/inland-blue/coastal-blue spaces); and (b) nature connectedness, across season and country. People who lived in greener/coastal neighbourhoods reported higher positive well-being, but this association largely disappeared when recreational visits were controlled for. Frequency of recreational visits to green, inland-blue, and coastal-blue spaces in the last 4 weeks were all positively associated with positive well-being and negatively associated with mental distress. Associations with green space visits were relatively consistent across seasons and countries but associations with blue space visits showed greater heterogeneity. Nature connectedness was also positively associated with positive well-being and negatively associated with mental distress and was, along with green space visits, associated with a lower likelihood of using medication for depression. By contrast inland-blue space visits were associated with a greater likelihood of using anxiety medication. Results highlight the benefits of multi-exposure, multi-response, multi-country studies in exploring complexity in nature-health associations.

Deciphering the Link Between Mental Health and Green Space in Shenzhen, China: The Mediating Impact of Residents' Satisfaction

Rapid urbanization and increasing urban density in China threaten residents' mental health. As a vital component of built environments, green space plays a key role in individuals' psychological well-being; however, the mediating effect of residents' satisfaction with the green space environment on the relationship between urban greening and residents' mental health in Chinese contexts has yet to be thoroughly explored. To fill this knowledge gap, this paper attempts to reveal the internal logic and mechanism underlying the linkages between green space, residents' mental health, and their satisfaction with green space in Shenzhen, China. Specifically, this paper explores the mediating role of residents' satisfaction with a green space environment using questionnaire survey data, “Quick Bird-2” high-resolution remote sensing image data, and a multilevel regression model. Our empirical findings indicate that the relative range of neighboring green spaces can directly improve residents' mental health. More importantly, the relationship between the relative scope of green space and residents' mental health is mediated by residents' satisfaction with the green space environment rather than its direct health effects. Given the influence of green space on residents' satisfaction with the environment, green space indirectly affects mental health. These findings should provide the government useful guidance for considering the spatial distribution and quantity of green space. Our results should also help residents improve their actual experiences and subjective satisfaction with the green space environment.

Green spaces, subjective health and depressed affect in middle-aged and older adults: a cross-country comparison of four European cohorts

Background

Studies on associations between urban green space and mental health have yielded mixed results. This study examines associations of green space exposures with subjective health and depressed affect of middle-aged and older adults in four European cohorts.

Methods

Data came from four Western-European and Central-European ageing cohorts harmonised as part of the Mindmap project, comprising 16 189 adults with an average age of 50–71 years. Green space exposure was based on the distance to the nearest green space and the amount of green space within 800 m buffers around residential addresses. Cohort-specific and one-step individual participant data (IPD) meta-analyses were used to examine associations of green space exposures with subjective health and depressed affect.

Results

The amount of green spaces within 800 m buffers was lowest for Residential Environment and CORonary heart Disease (Paris, 15.0 hectares) and highest for Health, Alcohol and Psychosocial factors In Eastern Europe (Czech Republic, 35.9 hectares). IPD analyses indicated no evidence of an association between the distance to the nearest green space and depressed affect (OR 0.98, 95% CI 0.96 to 1.00) or good self-rated health (OR 1.01, 95% CI 0.99 to 1.02). Likewise, the amount of green space within 800 m buffers did not predict depressed affect (OR 0.98, 95% CI 0.96 to 1.00) or good self-rated health (OR 1.01, 95% CI 0.99 to 1.02). Findings were consistent across all cohorts.

Conclusions

Data from four European ageing cohorts provide no support for the hypothesis that green space exposure is associated with subjective health or depressed affect. While longitudinal evidence is required, these findings suggest that green space may be less important for older urban residents.

Urban street tree biodiversity and antidepressant prescriptions

Growing urbanisation is a threat to both mental health and biodiversity. Street trees are an important biodiversity component of urban greenspace, but little is known about their effects on mental health. Here, we analysed the association of street tree density and species richness with antidepressant prescribing for 9751 inhabitants of Leipzig, Germany. We examined spatial scale effects of street trees at different distances around participant’s homes, using Euclidean buffers of 100, 300, 500, and 1000 m. Employing generalised additive models, we found a lower rate of antidepressant prescriptions for people living within 100 m of higher density of street trees—although this relationship was marginally significant (p = 0.057) when confounding factors were considered. Density of street trees at further spatial distances, and species richness of street trees at any distance, were not associated with antidepressant prescriptions. However, for individuals with low socio-economic status, high density of street trees at 100 m around the home significantly reduced the probability of being prescribed antidepressants. The study suggests that unintentional daily contact to nature through street trees close to the home may reduce the risk of depression, especially for individuals in deprived groups. This has important implications for urban planning and nature-based health interventions in cities.

Results from an 18 country cross-sectional study examining experiences of nature for people with common mental health disorders

Exposure to natural environments is associated with a lower risk of common mental health disorders (CMDs), such as depression and anxiety, but we know little about nature-related motivations, practices and experiences of those already experiencing CMDs. We used data from an 18-country survey to explore these issues (n = 18,838), taking self-reported doctor-prescribed medication for depression and/or anxiety as an indicator of a CMD (n = 2698, 14%). Intrinsic motivation for visiting nature was high for all, though slightly lower for those with CMDs. Most individuals with a CMD reported visiting nature ≥ once a week. Although perceived social pressure to visit nature was associated with higher visit likelihood, it was also associated with lower intrinsic motivation, lower visit happiness and higher visit anxiety. Individuals with CMDs seem to be using nature for self-management, but ‘green prescription’ programmes need to be sensitive, and avoid undermining intrinsic motivation and nature-based experiences.

Lifestyle behaviors, psychological distress, and well-being: A daily diary study

RATIONALE

Many lifestyle behaviors such as diet, exercise, social interaction, and substance use are related to physical and mental health. Less understood are the day-to-day associations of these behaviors with both psychological distress, well-being, and with each other.

OBJECTIVE

This study investigated how a number of common lifestyle behaviors were associated with psychological distress and well-being using a daily diary study with multilevel modeling. Associations among behaviors were analyzed with multilevel mediation and network models.

METHODS

An online participant pool consisting of seventy-six adults (age range: 19-64; mean age: 40.29; 58% female) completed daily diary surveys over 14 days and reported their engagement in lifestyle behaviors, psychological distress, hedonic well-being, and eudaimonic well-being.

RESULTS

Time spent in social interaction was the most consistent within-person correlate of psychological distress and well-being. The association between daily time in nature and well-being was mediated by social interaction and exercise. Network models found within-person associations among the lifestyle behaviors.

CONCLUSION

The results indicate that social interaction may be an especially important lifestyle behavior to consider when promoting well-being. Future research should recognize that daily fluctuations in many lifestyle behaviors cluster together.

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.

Greenness, mortality and mental health prescription rates in urban Scotland - a population level, observational study

BACKGROUND: Recent studies have shown an association between vegetation around dwellings and mortality, with mental health as a possible mediator.

OBJECTIVES: Examine whether there is an association between greenness and mortality or greenness and the proportion of the population being prescribed drugs for anxiety, depression or psychosis in urban areas of Scotland.

METHODS: Two greenness maps were prepared based on Landsat 8 Normalised Difference Vegetation Index data from 2013 to 2016, one for summer and one for winter. Greenness was sampled from these maps around each of 91,357 urban postcodes. The greenness data was averaged by 4,883 urban Data Zones covering 71% of the Scottish population and compared with mortality and prescription rate data from the Scottish Index of Multiple Deprivation.

RESULTS: The areas least green in the summer were found to have higher mortality rates but no association was found between mortality and winter-greenness. The largest relative differences of mortality were around 9%. High levels of summer-greenness were associated with an increase in mental health prescription rates but areas with the highest differences between summer and winter-greenness had lower prescription rates than other areas. The largest relative difference in prescription rate was 17%. All models controlled for overall deprivation. It is hypothesised that the year round greenness of mown grass is associated with increased mental health prescriptions and obscures the benefits of other kinds of vegetation on both mortality and mental health.

DISCUSSION: There is an association between greenness and mortality and greenness and mental health. The association is both statistically significant and large enough to be of importance for policy making. Higher levels of non mown grass vegetation may be preferable for human wellbeing but more detailed understanding of the diversity of plant life in urban areas and how people related to it is required to make more specific recommendations.

Road Traffic Noise Exposure and Depression/Anxiety: An Updated Systematic Review and Meta-Analysis

Unlike other World Health Organization evidence reviews, the systematic review on mental disorders could not provide a quantitative estimate of the effect of environmental noise. With that in mind, we aimed to update it with additional studies published through to 18 August 2019 in order to allow for a formal meta-analysis of the association of residential road traffic noise with anxiety and depression. The quality effects and random effects estimators were used for meta-analysis and the robustness of findings was tested in several sensitivity analyses. Ten studies were included in the qualitative synthesis, from which we extracted 15 estimates for depression (n = 1,201,168) and five for anxiety (n = 372,079). Almost all studies were cross-sectional and the risk of bias in them was generally high. We found 4% (95% CI: -3%, 11%) higher odds of depression and 12% (95% CI: -4%, 30%) of anxiety associated with a 10 dB(A) increase in day-evening-night noise level (Lden). Both models suffered from moderate heterogeneity (55% and 54%), but there was evidence of publication bias only in the depression model. These findings were robust with no evidence of study-level moderators. A sensitivity analysis on an alternative set of categorically-reported estimates supported a linear relationship between Lden and depression. Taking into account an overall quality assessment for the included studies, we conclude that there is evidence of "very low" quality that increasing exposure to road traffic noise may be associated with depression and anxiety.

Effect of changes in green spaces on mental health in older adults: a fixed effects analysis

Background

Urban green spaces have been linked to different health benefits, but longitudinal studies on the effect of green spaces on mental health are sparse and evidence often inconclusive. Our objective was to study the effect of changes in green spaces in the residential environment on changes in mental health using data with 10 years of follow-up (2004–2014).

Methods

Data from 3175 Dutch adults were linked to accessibility and availability measures of green spaces at three time points (2004/2011/2014). Mental health was measured with the Mental Health Inventory-5. Fixed effects analyses were performed to assess the effect of changes in green spaces on mental health.

Results

Cross-sectional analysis of baseline data showed significant associations between Euclidean distances to the nearest green space and mental health, with an increase of 100 m correlating with a lower mental health score of approximately 0.5 (95% CI −0.87 to −0.12) on a 0–100 scale. Fixed effects models showed no evidence for associations between changes in green spaces and changes in mental health both for the entire sample as well as for those that did not relocate during follow-up.

Conclusions

Despite observed cross-sectional correlations between the accessibility of green space in the residential environment and mental health, no evidence was found for an association between changes in green spaces and changes in mental health. If mental health and green spaces are indeed causally linked, then changes in green spaces in the Eindhoven area between 2004 and 2014 are not enough to produce a significant effect.

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.

Dynamic Urban Environmental Exposures on Depression and Suicide (NEEDS) in the Netherlands: a protocol for a cross-sectional smartphone tracking study and a longitudinal population register study

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.

ETHICS AND DISSEMINATION

Ethical approval (FETC17-060) was granted by the Ethics Review Board of Utrecht University, The Netherlands. Project-related findings will be disseminated at conferences and in peer-reviewed journal papers. Other project outcomes will be made available through the project's web page, http://www.needs.sites.uu.nl.

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.

Using deep learning to examine street view green and blue spaces and their associations with geriatric depression in Beijing, China

BACKGROUND

Residential green and blue spaces may be therapeutic for the mental health. However, solid evidence on the linkage between exposure to green and blue spaces and mental health among the elderly in non-Western countries is scarce and limited to exposure metrics based on remote sensing images (i.e., land cover and vegetation indices). Such overhead-view measures may fail to capture how people perceive the environment on the site.

OBJECTIVE

This study aimed to compare streetscape metrics derived from street view images with satellite-derived ones for the assessment of green and blue space; and to examine associations between exposure to green and blue spaces as well as geriatric depression in Beijing, China.

METHODS

Questionnaire data on 1190 participants aged 60 or above were analyzed cross-sectionally. Depressive symptoms were assessed through the shortened Geriatric Depression Scale (GDS-15). Streetscape green and blue spaces were extracted from Tencent Street View data by a fully convolutional neural network. Indicators derived from street view images were compared with a satellite-based normalized difference vegetation index (NDVI), a normalized difference water index (NDWI), and those derived from GlobeLand30 land cover data on a neighborhood level. Multilevel regressions with neighborhood-level random effects were fitted to assess correlations between GDS-15 scores and these green and blue spaces exposure metrics.

RESULTS

The average cumulative GDS-15 score was 3.4 (i.e., no depressive symptoms). Metrics of green and blue space derived from street view images were not correlated with satellite-based ones. While NDVI was highly correlated with GlobeLand30 green space, NDWI was moderately correlated with GlobeLand30 blue space. Multilevel regressions showed that both street view green and blue spaces were inversely associated with GDS-15 scores and achieved the highest model goodness-of-fit. No significant associations were found with NDVI, NDWI, and GlobeLand30 green and blue space. Our results passed robustness tests.

CONCLUSION

Our findings provide support that street view green and blue spaces are protective against depression for the elderly in China, yet longitudinal confirmation to infer causality is necessary. Street view and satellite-derived green and blue space measures represent different aspects of natural environments. Both street view data and deep learning are valuable tools for automated environmental exposure assessments for health-related studies.

Cross-sectional associations between long-term exposure to particulate matter and depression in China: The mediating effects of sunlight, physical activity, and neighborly reciprocity

BACKGROUND

Although numerous studies have speculated about the direct and indirect linkage between long-term air pollution (i.e., PM_2.5) concentrations and mental health in developed countries, evidence for developing countries is limited. Our aim was to examine the mediation effects of sunlight, physical activity, and neighborly reciprocity on the association between air pollution and depression.

METHODS

In a sample of 20,861 individuals in China in 2016, depression was measured using the Center for Epidemiological Studies Depression screener (CES-D) and linked to annual city-wide PM_2.5 data. We used multilevel regression models to assess the associations between depressive symptoms and PM_2.5 and tested the mediation of sunlight, physical activity, and neighborly reciprocity in this association. Propensity score matching was used to evaluate whether selection bias may affect the association between CES-D scores and PM_2.5.

RESULTS

PM_2.5 concentration was positively associated with depression symptoms. All mediators were significantly and negatively associated with PM_2.5. Our mediation analyses indicated that physical activity, neighborly reciprocity, and exposure to sunlight are important mechanisms through which PM_2.5 affects depressive symptoms.

LIMITATIONS

The limitations of the present study were the cross-sectional nature of the data and modifiable areal unit problem.

CONCLUSIONS

Our findings suggest not only that PM_2.5 is directly associated with depression, but also that this association seems to be partially mediated by physical activity, neighborly reciprocity, and sunlight.

Spatiotemporal Contextual Uncertainties in Green Space Exposure Measures: Exploring a Time Series of the Normalized Difference Vegetation Indices

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 2006–2017 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–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–health studies should employ NDVI data that are well-aligned with epidemiological data. Even an annual temporal incompatibility may obscure or distort green space–health associations. Both strategies may diminish contextual uncertainties in environmental exposure assessments.

Associations between Urban Green Spaces and Health are Dependent on the Analytical Scale and How Urban Green Spaces are Measured

Although the benefits from exposure to urban green spaces (UGS) are increasingly reported, there are important knowledge gaps in the nature of UGS-health relationships. One such unknown area is the dependence of UGS-health associations on the types of UGS studied, the way they are quantified, and the spatial scale used in the analysis. These knowledge gaps have important ramifications on our ability to develop generalizations to promote implementation and facilitate comparative studies across different socio-cultural and socio-economic contexts. We conducted a study in Singapore to examine the dependence of UGS-health associations on the metrics for quantifying UGS (vegetation cover, canopy cover and park area) in different types of buffer area (circular, nested and network) at different spatial scales. A population-based household survey (n = 1000) was used to collect information on self-reported health and perception and usage pattern of UGS. The results showed that although all three UGS metrics were positively related to mental health at certain scales, overall, canopy cover showed the strongest associations with mental health at most scales. There also appears to be minimum and maximum threshold levels of spatial scale at which UGS and health have significant associations, with the strongest associations consistently shown between 400 m to 1600 m in different buffer types. We discuss the significance of these results for UGS-health studies and applications in UGS planning for improved health of urban dwellers.

Green space associations with mental health and cognitive function: Results from the Quebec CARTaGENE cohort

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Urban green space may be important to mental health, but the association between long-term green space exposures and depression, anxiety, and cognitive function in adults remains unknown.

Association between Urban Greenness and Depressive Symptoms: Evaluation of Greenness Using Various Indicators

An increasing number of studies have suggested benefits of greenness exposure on mental health. We examined the association between urban greenness and depressive symptoms in adults in the general population living in the seven major cities in Korea (N = 65,128). Using data from the Korean Community Health Survey 2009, depressive symptoms were measured on the Center for Epidemiological Studies Depression Scale (CES-D). Greenness was assessed using Normalized Difference Vegetation Index (NDVI) and land-use data (forest area and forest volume). Logistic regression models were fitted to adjust for potential confounders. Individuals in regions with the highest NDVI (quartile 4) had the lowest odds for depressive symptoms compared to quartile 1, after adjusting for potential confounders (OR = 0.813; 95% CI: 0.747, 0.884). For all greenness indicators except for forest area per district area (%), the highest rate of depressive symptoms was found for the individuals in the lowest quartile of greenness (quartile 1) and the lowest rate of depressive symptoms for those in the highest quartile of greenness (quartile 4). We found an inverse association between urban greenness and depressive symptoms, which was consistent across a variety of greenness indicators. Our study suggests health benefits of greenness and could provide a scientific basis for policy making and urban planning.

Does Residential Green and Blue Space Promote Recovery in Psychotic Disorders? A Cross-Sectional Study in the Province of Utrecht, The Netherlands

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.