The impact of social capital, land use, air pollution and noise on individual morbidity in Dutch neighbourhoods

The Environment and Headache: a Narrative Review

PURPOSE OF REVIEW

In this narrative review, we summarize the peer-reviewed literature published between 2017 and 2022 that evaluated ambient environmental risk factors for primary headache disorders, which affect more than half of the population globally. Primary headache disorders include migraine, tension-type headache (TTH), and trigeminal and autonomic cephalalgias (TAC).

RECENT FINDINGS

We identified 17 articles that met the inclusion criteria via PubMed or Google Scholar. Seven studies (41%) relied on data from US populations. The remaining studies were conducted in China, Taiwan, Germany, Ghana, Japan, the Netherlands, South Korea, and Turkey. Air pollution was the most frequently assessed environmental risk factor. Most studies were cross-sectional and focused on all-cause or migraine headaches; one study included TTH, and none included TAC. Short-term exposure to fine particulate matter (PM2.5) was not consistently associated with headache endpoints, but long-term exposure to PM2.5 was associated with migraine headache prevalence and severity across multiple studies. Elevated ambient temperature, changes in weather, oil and gas well exposure, and less natural greenspace, but not noise pollution, were also associated with headache. No studies considered water pollution, metal exposure, ultrafine particulate matter, or wildfire smoke exposure. There is a need for ongoing research focused on headache and the environment. Study designs with the greatest explanatory power may include longitudinal studies that capture the episodic nature of headache and case-crossover analysis, which control for time-invariant individual-level confounders by design. There is also a clear need for research that considers comorbid psychiatric illness and socioeconomic position as powerful modifiers of the effect of the environment on headache.

Longitudinal study of changes in greenness exposure, physical activity and sedentary behavior in the ORISCAV-LUX cohort study

BACKGROUND

Greenness exposure has been associated with many health benefits, for example through the pathway of providing opportunities for physical activity (PA). Beside the limited body of longitudinal research, most studies overlook to what extent different types of greenness exposures may be associated with varying levels of PA and sedentary behavior (SB). In this study, we investigated associations of greenness characterized by density, diversity and vegetation type with self-reported PA and SB over a 9-year period, using data from the ORISCAV-LUX study (2007-2017, n = 628).

METHODS

The International Physical Activity Questionnaire (IPAQ) short form was used to collect PA and SB outcomes. PA was expressed as MET-minutes/week and log-transformed, and SB was expressed as sitting time in minutes/day. Geographic Information Systems (ArcGIS Pro, ArcMap) were used to collect the following exposure variables: Tree Cover Density (TCD), Soil-adjusted Vegetation Index (SAVI), and Green Land Use Mix (GLUM). The exposure variables were derived from publicly available sources using remote sensing and cartographic resources. Greenness exposure was calculated within 1000m street network buffers around participants' exact residential address.

RESULTS

Using Random Effects Within-Between (REWB) models, we found evidence of negative within-individual associations of TCD with PA (β = - 2.60, 95% CI - 4.75; - 0.44), and negative between-individual associations of GLUM and PA (β = - 2.02, 95% CI - 3.73; - 0.32). There was no evidence for significant associations between greenness exposure and SB. Significant interaction effects by sex were present for the associations between TCD and both PA and SB. Neighborhood socioeconomic status (NSES) did not modify the effect of greenness exposure on PA and SB in the 1000 m buffer.

DISCUSSION

Our results showed that the relationship between greenness exposure and PA depended on the type of greenness measure used, which stresses the need for the use of more diverse and complementary greenness measures in future research. Tree vegetation and greenness diversity, and changes therein, appeared to relate to PA, with distinct effects among men and women. Replication studies are needed to confirm the relevance of using different greenness measures to understand its' different associations with PA and SB.

Greenspaces And Cardiovascular Health

Accumulating evidence suggests that living in areas of high surrounding greenness or even brief exposures to areas of high greenery is conducive to cardiovascular health, which may be related to the environmental, social, psychological, and physiological benefits of greenspaces. Recent data from multiple cross-sectional, longitudinal, and cohort studies suggest that living in areas of high surrounding greenness is associated with a lower risk of all-cause and cardiovascular mortality. High levels of neighborhood greenery have been linked also to a decrease in the burden of cardiovascular disease risk factors as reflected by lower rates of hypertension, dyslipidemia, and diabetes. Those who live in greener environments report better mental health and more frequent social interactions, which can benefit cardiovascular health as well. In this narrative review, we discuss evidence linking greenspaces to cardiovascular health as well as the potential mechanisms underlying the beneficial effects of greenspaces, including the impact of vegetation on air, noise and light pollution, ambient temperature, physical activity, mental health, and biodiversity. We review literature on the beneficial effects of acute and chronic exposure to nature on cardiovascular disease risk factors, inflammation and immune function, and we highlight the potential cardiovascular effects of biogenic volatile organic compounds that are emitted by trees and shrubs. We identify current knowledge gaps in this area and underscore the need for additional population studies to understand more clearly and precisely the link between greenness and health. Such understanding is urgently needed to fully redeem the promise of greenspaces in preventing adverse environmental exposures, mitigating the effects of climate change, and creating healthier living environments.

Trajectories of depressive symptom and its association with air pollution: evidence from the Mr. OS and Ms. OS Hong Kong cohort study

BACKGROUND

Depression is a global health priority. Maintaining and delaying depressive symptoms in older adults is a key to healthy aging. This study aimed to identify depressive symptom trajectories, predictors and mortality, while also exploring the relationship between air quality and depressive symptoms in older adults in the Hong Kong community over 14 years.

METHODS

This study is a longitudinal study in Hong Kong. The target population was community-dwelling older adults over age 65. Depressive symptoms were measured by the Geriatric Depression Scale (GDS-15). Group-based trajectory model was used to identify heterogeneity in longitudinal changes over 14 years and examine the associations between baseline variables and trajectories for different cohort members using multinomial logistic regression. The Kaplan-Meier method was employed to conduct survival analysis and explore the variations in survival probabilities over time among different trajectory group. Linear mixed model was used to explore the relationship between air quality and depressive symptoms.

RESULTS

A total of 2828 older adults were included. Three different trajectories of depressive symptoms in older people were identified: relatively stable (15.4%), late increase (67.1%) and increase (17.5%). Female, more number of chronic diseases, poor cognitive function, and poor health-related quality of life (HRQOL) were significantly associated with other less favorable trajectories compared with participants with stable levels of depressive symptoms. The late increase group had a lower mortality rate than the relatively stable and increased groups. Lower baseline ambient air pollutant exposure to NO2 over 14 years was significantly associated with fewer depressive symptoms.

CONCLUSIONS

In this study, we found that a late increase in depressive symptoms was the predominant trend in older Chinese people in Hong Kong. Poorer HRQOL was predictive of less favorable trajectories of depressive symptoms. Ambient air pollution was associated with depressive symptoms. This novel observation strengthens the epidemiological evidence of longitudinal changes in depressive symptoms and associations with late-life exposure to air pollution.

Contributions of residential traffic noise to depression and mental wellbeing in Hong Kong: A prospective cohort study

Prior studies on the association between traffic noise and mental health have been mostly conducted in settings with lower population densities. However, evidence is lacking in high population-density settings where traffic noise is more pervasive and varies by topography and the vertical elevation of the residential unit. This study aimed to assess the mental health impact of residential traffic noise in one of the world's most urbanised populations. Data were analysed from 13,401 participants aged ≥15 years in a prospective cohort in Hong Kong from 2009 to 2014. Residential traffic noise level was estimated using 3D-geocoding and validated models that accounted for sound propagation in a highly vertical landscape. The 24-h day-night exposure to traffic noise, denoted as Ldn, was estimated with a 10-dB(A) penalty for night hours. Probable depression and mental wellbeing were assessed using the Patient Health Questionnaire-9 and the Short Form Health Questionnaire SF-12v2, respectively. Mixed effect regressions with random intercepts were used to examine the association between traffic noise and mental health outcomes. Residential road traffic noise (for each increment of 10 A-weighted decibels [dB(A)] 24-h average exposure) was associated with probable depression (odds ratio (OR) = 1.17, 95% CI: 1.05, 1.31), and poorer mental wellbeing (mean difference = -0.19, 95% CI: 0.31, -0.06), adjusting for sociodemographics, smoking, body mass index, self-reported health, proximity to green space, and neighbourhood characteristics (average household income, population density, and Gini coefficient). The results were robust to further adjustment for air pollution. In stratified analyses, residential traffic noise was associated with probable depression and poorer mental wellbeing among students and individuals aged 15-34 years. Residential traffic noise was associated with probable depression and poorer mental wellbeing in a highly urbanised setting. As traffic noise is increasing in urban settings, the public health impact of noise pollution could be substantial.

Advancing application of satellite remote sensing technologies for linking atmospheric and built environment to health

Background

The intricate interplay between human well-being and the surrounding environment underscores contemporary discourse. Within this paradigm, comprehensive environmental monitoring holds the key to unraveling the intricate connections linking population health to environmental exposures. The advent of satellite remote sensing monitoring (SRSM) has revolutionized traditional monitoring constraints, particularly limited spatial coverage and resolution. This innovation finds profound utility in quantifying land covers and air pollution data, casting new light on epidemiological and geographical investigations. This dynamic application reveals the intricate web connecting public health, environmental pollution, and the built environment.

Objective

This comprehensive review navigates the evolving trajectory of SRSM technology, casting light on its role in addressing environmental and geographic health issues. The discussion hones in on how SRSM has recently magnified our understanding of the relationship between air pollutant exposure and population health. Additionally, this discourse delves into public health challenges stemming from shifts in urban morphology.

Methods

Utilizing the strategic keywords "SRSM," "air pollutant health risk," and "built environment," an exhaustive search unfolded across prestigious databases including the China National Knowledge Network (CNKI), PubMed and Web of Science. The Citespace tool further unveiled interconnections among resultant articles and research trends.

Results

Synthesizing insights from a myriad of articles spanning 1988 to 2023, our findings unveil how SRMS bridges gaps in ground-based monitoring through continuous spatial observations, empowering global air quality surveillance. High-resolution SRSM advances data precision, capturing multiple built environment impact factors. Its application to epidemiological health exposure holds promise as a pioneering tool for contemporary health research.

Conclusion

This review underscores SRSM's pivotal role in enriching geographic health studies, particularly in atmospheric pollution domains. The study illuminates how SRSM overcomes spatial resolution and data loss hurdles, enriching environmental monitoring tools and datasets. The path forward envisions the integration of cutting-edge remote sensing technologies, novel explorations of urban-public health associations, and an enriched assessment of built environment characteristics on public well-being.

Migraine and air pollution: A systematic review

OBJECTIVE

To systematically synthesize evidence from a broad range of studies on the association between air pollution and migraine.

BACKGROUND

Air pollution is a ubiquitous exposure that may trigger migraine attacks. There has been no systematic review of this possible association.

METHODS

We searched for empirical studies assessing outdoor air pollution and any quantified migraine outcomes. We included short- and long-term studies with quantified air pollution exposures. We excluded studies of indoor air pollution, perfume, or tobacco smoke. We assessed the risk of bias with the World Health Organization's bias assessment instrument for air quality guidelines.

RESULTS

The final review included 12 studies with over 4,000,000 participants. Designs included case-crossover, case-control, time series, and non-randomized pre-post intervention. Outcomes included migraine-related diagnoses, diary records, medical visits, and prescriptions. Rather than pooling the wide variety of exposures and outcomes into a meta-analysis, we tabulated the results. Point estimates above 1.00 reflected associations of increased risk. In single-pollutant models, the percent of point estimates above 1.00 were carbon monoxide 5/5 (100%), nitrogen dioxide 10/13 (78%), ozone 7/8 (88%), PM2.5 13/15 (87%), PM10 2/2 (100%), black carbon 0/1 (0%), methane 4/6 (75%), sulfur dioxide 3/5 (60%), industrial toxic waste 1/1 (100%), and proximity to oil and gas wells 6/13 (46%). In two-pollutant models, 16/17 (94%) of associations with nitrogen dioxide were above 1.00; however, more than 75% of the confidence intervals included the null value. Most studies had low to moderate risks of bias. Where differences were observed, stronger quality articles generally reported weaker associations.

CONCLUSIONS

Balancing the generally strong methodologies with the small number of studies, point estimates were mainly above 1.00 for associations of carbon monoxide, nitrogen dioxide, ozone, and particulate matter with migraine. These results were most consistent for nitrogen dioxide.

The Influence of Greenspace Exposure on Affect in People With and Those Without Schizophrenia: Exploratory Study

BACKGROUND

Exposure to natural vegetation (ie, "greenspace") is related to beneficial outcomes, including higher positive and lower negative affect, in individuals with and those without mental health concerns. Researchers have yet to examine dynamic associations between greenspace exposure and affect within individuals over time. Smartphone-based ecological momentary assessment (EMA) and passive sensors (eg, GPS, microphone) allow for frequent sampling of data that may reveal potential moment-to-moment mechanisms through which greenspace exposure impacts mental health.

OBJECTIVE

In this study, we examined associations between greenspace exposure and affect (both self-reported and inferred through speech) in people with and those without schizophrenia spectrum disorder (SSD) at the daily level using smartphones.

METHODS

Twenty people with SSD and 14 healthy controls reported on their current affect 3 times per day over 7 days using smartphone-based EMA. Affect expressed through speech was labeled from ambient audio data collected via the phone's microphone using Linguistic Inquiry and Word Count (LIWC). Greenspace exposure, defined as the normalized difference vegetation index (NDVI), was quantified based on continuous geo-location data collected from the phone's GPS.

RESULTS

Overall, people with SSD used significantly more positive affect words (P=.04) and fewer anger words (P=.04) than controls. Groups did not significantly differ in mean EMA-reported positive or negative affect, LIWC total word count, or NDVI exposure. Greater greenspace exposure showed small to moderate associations with lower EMA-reported negative affect across groups. In controls, greenspace exposure on a given day was associated with significantly lower EMA-reported anxiety on that day (b=-0.40, P=.03, 95% CI -0.76 to -0.04) but significantly higher use of negative affect words (b=0.66, P<.001, 95% CI 0.29-1.04). There were no significant associations between greenspace exposure and affect at the daily level among participants with SSD.

CONCLUSIONS

Our findings speak to the utility of passive and active smartphone assessments for identifying potential mechanisms through which greenspace exposure influences mental health. We identified preliminary evidence that greenspace exposure could be associated with improved mental health by reducing experiences of negative affect. Future directions will focus on furthering our understanding of the relationship between greenspace exposure and affect on individuals with and those without SSD.

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).

Long-term exposure of PM2.5 components on the adults' depressive symptoms in China - Evidence from a representative longitudinal nationwide cohort

In recent years, there is growing evidence that long-term exposure to fine particulate matter (PM_2.5) is associated with depressive symptoms. However, little is known about the individual effects of PM_2.5 components, particularly in low-income and middle-income countries. We investigated the association between long-term exposure to major components of PM_2.5 and worsening depressive symptoms in Chinese adults based on a large, long-term, nationally representative, population-based prospective cohort. Our data were derived from China Family Panel Study (CFPS) wave 2012, 2016 and 2018 and a long-term (2010-2019) high-resolution PM_2.5 components dataset covering the whole China. We assessed respondents' depressive symptoms using standardized scales and applied advanced Fixed-effect ordered logit model (FE-ologit) to capture the ordinal nature of respondents' depressive symptoms and control for individual-specific and time-invariant effects to investigate their associations with PM_2.5 components. We included 9503 respondents and the FE-ologit model results indicated that the odds ratio of increase per standard unit was 1.118 (95 % CI: 1.020, 1.225) for black carbon, 1.134 (95 % CI: 1.028, 1.252) for organic matter, 1.127 for ammonium (95 % CI: 1.011, 1.255), 1.107 for nitrate (95 % CI: 0.981, 1.248), and 1.117 for sulfate (95 % CI: 1.020, 1.224). Our study suggests that long-term exposure to PM_2.5 components is significantly associated with worsening of depressive symptoms, and that different components may have different toxicity. Reducing PM_2.5 emissions, especially the major sources of organic matter and ammonium, may reduce the burden of depressive symptoms in Chinese adults.

The role of residential greenness levels, green land cover types and diversity in overweight/obesity among older adults: A cohort study

BACKGROUND

Few studies have investigated the effects of greenness exposure, green land cover types and diversity and their interaction with particulate matter (PM) to adiposity.

METHOD

Cohort data were collected from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Baseline data on greenness levels, green land cover types and diversity were assessed by the Normalized Difference Vegetation Index (NDVI), three greenery types (trees, shrublands and grassland) and Shannon's diversity index, respectively. Body mass index (BMI) and waist circumference (WC) were separately used as dependent variables and represented for peripheral overweight/obesity and central obesity, respectively. The mixed Cox model with random intercept was used to estimate the effects of greenness levels, types and diversity on overweight/obesity using single and multiple exposure models. We also examined the interaction of PM and the aforementioned indicators on overweight/obesity on both additive and multiplicative scales.

RESULTS

Single exposure models showed that higher levels of residential greenness, tree coverage and ratio of trees to shrublands/grassland were inversely associated with peripheral overweight/obesity and central obesity. An increase in shrublands, grassland and diversity of green was related to lower odds of peripheral overweight/obesity. Multiple exposure models confirmed the association between greenness levels and peripheral overweight/obesity. Males, educated participants and elderly who lived in southern regions and areas with cleaner air environments acquired more benefits from greenspace exposure. Single and multiple exposure models indicated that an antagonistic effect of increasing PM and decreasing greenness levels on peripheral overweight/obesity and central obesity. Single exposure models showed the potential interaction of tree coverage, ratio of trees to grassland and PM_2.5 exposures on the risk of peripheral overweight/obesity.

CONCLUSION

Increasing residential greenness and diversity of green were associated with healthy weight status. The relationship between greenery and overweight/obesity varied, and the effects of greenspace exposure on overweight/obesity were associated with air pollution.

Air pollution, depressive and anxiety disorders, and brain effects: A systematic review

Accumulating data suggest that air pollution increases the risk of internalizing psychopathology, including anxiety and depressive disorders. Moreover, the link between air pollution and poor mental health may relate to neurostructural and neurofunctional changes. We systematically reviewed the MEDLINE database in September 2021 for original articles reporting effects of air pollution on 1) internalizing symptoms and behaviors (anxiety or depression) and 2) frontolimbic brain regions (i.e., hippocampus, amygdala, prefrontal cortex). One hundred and eleven articles on mental health (76% human, 24% animals) and 92 on brain structure and function (11% human, 86% animals) were identified. For literature search 1, the most common pollutants examined were PM2.5 (64.9%), NO2 (37.8%), and PM10 (33.3%). For literature search 2, the most common pollutants examined were PM2.5 (32.6%), O3 (26.1%) and Diesel Exhaust Particles (DEP) (26.1%). The majority of studies (73%) reported higher internalizing symptoms and behaviors with higher air pollution exposure. Air pollution was consistently associated (95% of articles reported significant findings) with neurostructural and neurofunctional effects (e.g., increased inflammation and oxidative stress, changes to neurotransmitters and neuromodulators and their metabolites) within multiple brain regions (24% of articles), or within the hippocampus (66%), PFC (7%), and amygdala (1%). For both literature searches, the most studied exposure time frames were adulthood (48% and 59% for literature searches 1 and 2, respectively) and the prenatal period (26% and 27% for literature searches 1 and 2, respectively). Forty-three percent and 29% of studies assessed more than one exposure window in literature search 1 and 2, respectively. The extant literature suggests that air pollution is associated with increased depressive and anxiety symptoms and behaviors, and alterations in brain regions implicated in risk of psychopathology. However, there are several gaps in the literature, including: limited studies examining the neural consequences of air pollution in humans. Further, a comprehensive developmental approach is needed to examine windows of susceptibility to exposure and track the emergence of psychopathology following air pollution exposure.

The Weight of Place: Built Environment Correlates of Obesity and Diabetes

In recent decades, the prevalence of obesity and diabetes has risen substantially in North America and worldwide. To address these dual epidemics, researchers and policymakers alike have been searching for effective means to promote healthy lifestyles at a population level. As a consequence, there has been a proliferation of research examining how the "built" environment in which we live influences physical activity levels, by promoting active forms of transportation, such as walking and cycling, over passive ones, such as car use. Shifting the transportation choices of local residents may mean that more members of the population can participate in physical activity during their daily routine without structured exercise programs. Increasingly, this line of research has considered the downstream metabolic consequences of the environment in which we live, raising the possibility that "healthier" community designs could help mitigate the rise in obesity and diabetes prevalence. This review discusses the evidence examining the relationship between the built environment, physical activity, and obesity-related diseases. We also consider how other environmental factors may interact with the built environment to influence metabolic health, highlighting challenges in understanding causal relationships in this area of research.

Living near coasts is associated with higher suicide rates among females but not males: A register-based linkage study in the Netherlands

Exposure to blue spaces may promote psychological wellbeing and reduce mental distress. Whether these effects extend to suicide is unknown. We used register data from 14 million Dutch adults aged 18-64-years between 2007 and 2016 in a nested case-control study to estimate associations between blue space exposures and suicide risk. Each suicide case was matched to ten randomly selected controls. Two blue space exposures were assigned over a ten-year residential address history: distance to the closest inland blue space and distance to the coast. We fitted (gender-stratified) conditional logistic regressions to the data. Possible effect modifications by income were also examined. In total, our analyses included 9757 cases and 95,641 controls. Effect estimates for distance to the closest inland blue space in the total population showed that people living farthest away from inland blue space were at-risk. Suicide risk was lower among women who lived farther away from the coast; no significant effect was observed for men. No evidence was observed that income modified these associations. Our findings provide suggestive evidence that living close to the coast is associated with greater suicide risk for women, while living closer to inland blue spaces may add to the resilience against suicide in the total population. Past research shows that coastal proximity protects against milder forms of mental illness, but these protective effects do not appear to hold for suicide. Blue space interventions for women with severe mental illness or propensities to engage in self-harm should be approached with caution.

New determinants of mental health: the role of noise pollution. A narrative review

Urbanisation processes and anthropogenic actions led to a significant increase in pollution levels, with relevant consequences on global health. In particular, noise pollution demonstrated an association with cardiovascular, metabolic, and respiratory diseases. Furthermore, increasing evidence underlined the possible role of air and noise pollution in the development of psychiatric disorders. In this narrative review, evidence concerning the relationship between noise pollution and the emergence of psychiatric symptoms or psychiatric disorders is summarised. After the literature search process was completed, 40 papers were included in the present review. The exposure to road-, rail-, and air- traffic represented a risk factor for the emergence of affective disorders. This could also be mediated by the occurrence of circadian rhythms disturbances or by noise annoyance and noise sensitivity, both influencing psychological well-being and health-related quality of life. Fewer studies concentrated on special populations, particularly pregnant women and children, for whom noise pollution was confirmed as a risk factor for psychopathology. The better clarification of the complex interaction between noise pollution and mental health may help to identify subjects at risk and targeting specific prevention and intervention strategies in the urban environment.

The built environment and mental health among older adults in Dalian: The mediating role of perceived environmental attributes

The basic attributes of the urban built environment are an important factor affecting mental health. However, research has rarely distinguished objective and perceived built environment characteristics to explore the associations with older adults' mental health. Based on data of 879 respondents aged 60 or older in Dalian, China, we explored the mediating roles of perceived built environmental attributes in the relationship between objective built environmental characteristics and mental wellbeing by structural equation modelling. Furthermore, to control for residential self-selection, the model was further tested by excluding the participants who self-selected their residences. The results showed that accessibility to daily living service facilities was positively associated with older adults' mental wellbeing through an indirect role of perceived built environmental attributes. The positive direct effect of aggregation of daily living service facilities on mental wellbeing was offset by the negative indirect effects of perceived built environmental attributes. In addition, the street interface density was negatively related to mental wellbeing through indirect effects. The diverse leisure, exercise and landscape facilities, underground parking and presence of elevators within neighborhoods were all positively associated with older adults' mental wellbeing through direct and/or indirect effects. The results were verified after excluding residential self-selection samples. These findings are helpful for evidence-based planning strategies and can provide guidelines on designing neighborhood landscapes and facilities which can further contribute to aging in place policies.

Association between outdoor artificial light at night and sleep duration among older adults in China: A cross-sectional study

BACKGROUND

Light after dusk disrupts the circadian rhythms and shifts the timing of sleep later; but it is unknown whether outdoor artificial light at night (ALAN) affects sleep quality. This study aimed to explore the association between residential outdoor ALAN and sleep duration in a nationally representative sample of Chinese older adults.

METHODS

We examined the cross-sectional associations of outdoor ALAN with self-reported sleep duration in 13,474 older adults participating in the 2017-2018 wave of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Outdoor ALAN exposure was estimated at the residence level using satellite images. We applied generalized linear mixed models to investigate the association between ALAN exposure and sleep duration. We performed stratified analyses by age, sex, education, and household income levels. Moreover, we used multi-level logistic regression models to investigate the effects of ALAN on the short sleep duration (≤6 h) and the long sleep duration (>8 h), respectively, in reference to sleep for >6-8 h per day.

RESULTS

We found a significant association between outdoor ALAN intensity and sleep duration. The highest quartile of ALAN was associated with 17.04 (95% CI: 9.42-24.78) fewer minutes of sleep as compared to the lowest quartile. The reductions in sleep duration per quartile change in ALAN were greater in the young old (≥65-85 years) and in those with higher levels of education, and those with higher household income, respectively. We did not detect a sex difference. In addition, those in the highest quartile of ALAN were more likely to report a 25% (95% CI: 10%-42%) increase in short sleep (<6 h), and a 21% (95% CI: 9%-31%) decrease in long sleep (>8 h).

CONCLUSIONS

Increasing outdoor nighttime light intensity surrounding residences was associated with shorter sleep duration in older residents in China. This finding implies the importance of urban outdoor artificial light management as a potential means to lower the public health burden of sleep disorders.

Proximity to livestock farms and COVID-19 in the Netherlands, 2020-2021

Objectives

In the Netherlands, during the first phase of the COVID-19 epidemic, the hotspot of COVID-19 overlapped with the country's main livestock area, while in subsequent phases this distinct spatial pattern disappeared. Previous studies show that living near livestock farms influence human respiratory health and immunological responses. This study aimed to explore whether proximity to livestock was associated with SARS-CoV-2 infection.

Methods

The study population was the population of the Netherlands excluding the very strongly urbanised areas and border areas, on January 1, 2019 (12, 628, 244 individuals). The cases are the individuals reported with a laboratory-confirmed positive SARS-CoV-2 test with onset before January 1, 2022 (2, 223, 692 individuals). For each individual, we calculated distance to nearest livestock farm (cattle, goat, sheep, pig, poultry, horse, rabbit, mink). The associations between residential (6-digit postal-code) distance to the nearest livestock farm and individuals' SARS-CoV-2 status was studied with multilevel logistic regression models. Models were adjusted for individuals' age categories, the social status of the postal code area, particulate matter (PM₁₀)- and nitrogen dioxide (NO₂)-concentrations. We analysed data for the entire period and population as well as separately for eight time periods (Jan–Mar, Apr–Jun, Jul–Sep and Oct–Dec in 2020 and 2021), four geographic areas of the Netherlands (north, east, west and south), and for five age categories (0–14, 15–24, 25–44, 45–64 and > 65 years).

Results

Over the period 2020–2021, individuals' SARS-CoV-2 status was associated with living closer to livestock farms. This association increased from an Odds Ratio (OR) of 1.01 (95% Confidence Interval [CI] 1.01–1.02) for patients living at a distance of 751–1000 m to a farm to an OR of 1.04 (95% CI 1.04–1.04), 1.07 (95% CI 1.06–1.07) and 1.11 (95% CI 1.10–1.12) for patients living in the more proximate 501–750 m, 251–500m and 0–250 m zones around farms, all relative to patients living further than 1000 m around farms. This association was observed in three out of four quarters of the year in both 2020 and 2021, and in all studied geographic areas and age groups.

Conclusions

In this exploratory study with individual SARS-CoV-2 notification data and high-resolution spatial data associations were found between living near livestock farms and individuals' SARS-CoV-2 status in the Netherlands. Verification of the results in other countries is warranted, as well as investigations into possible underlying exposures and mechanisms.

Daily space-time activities, multiple environmental exposures, and anxiety symptoms: A cross-sectional mobile phone-based sensing study

BACKGROUND

Few mobility-based studies have investigated the associations between multiple environmental exposures, including social exposures, and mental health.

OBJECTIVE

To assess how exposure to green space, blue space, noise, air pollution, and crowdedness along people's daily mobility paths are associated with anxiety symptoms.

METHODS

358 participants were cross-sectionally tracked with Global Positioning System (GPS)-enabled mobile phones. Anxiety symptoms were measured at baseline using the Generalized Anxiety Disorder-7 (GAD-7) questionnaire. Green space, blue space, noise, and air pollution were assessed based on concentric buffers of 50 m and 100 m around each GPS point. Crowdedness was measured by the number of nearby Bluetooth-enabled devices detected along the mobility paths. Multiple linear regressions with full covariate adjustment were fitted to examine anxiety-environmental exposures associations. Random forest models were applied to explore possible nonlinear associations and exposure interactions.

RESULTS

Regression results showed null linear associations between GAD-7 scores and environmental exposures. Random forest models indicated that GAD-7-environment associations varied nonlinearly with exposure levels. We found a negative association between green space and GAD-7 scores only for participants with moderate green space exposure. We observed a positive association between GAD-7 scores and noise levels above 60 dB and air pollution concentrations above 17.2 μg m^-3. Crowdedness was positively associated with GAD-7 scores, but exposure-response functions flattened out with pronounced crowdedness of >7.5. Blue space tended to be positively associated with GAD-7 scores. Random forest models ranked environmental exposures as more important to explain GAD-7 scores than linear models.

CONCLUSIONS

Our findings indicate possible nonlinear associations between mobility-based environmental exposures and anxiety symptoms. More studies are needed to obtain an in-depth understanding of underlying anxiety-environment mechanisms during daily life.

Environmentally related gender health risks: findings from citizen science cross-sectional study

Background

Public engagement in the research of environmental epidemiological problems is becoming an important measure to empower citizens to identify the local environmental and health problems and to explain different environmental exposures affect estimates for males and females. This HORIZON2020 CitieS-Health Kaunas Pilot study examines the relationship between urban built and social environment, health behaviors, and health in men and women.

Methods

This cross-sectional study included 1086 18–74-year-old participants residing in 11 districts of Kaunas city, Lithuania. Using GIS, we measured traffic flow, noise, NO2, PM2.5, PM10, and greenness NDVI for the participants’ home addresses, determined participants’ perceptions of environmental quality, linked this information with personal sociodemographic data, and used multivariate logistic regression to assess the associations with health issues (physician-diagnosed chronic disease and self-rated general health) in men and women.

Results

Men and women similar rated the quality of the neighborhood environment, except for air pollution and satisfaction with the public transport in the district. The traffic-related health associations were stronger for women than for men. The prevalence of poor health increased with the increasing age of men and women, yet no significant differences between gender health risks were found in the total sample. Perceived air pollution, irregular visits to green space, and chronic diseases were consistently associated with poor health risks in men and women, yet part-time jobs and low income had a higher impact on women’s poor health.

Conclusions

Quality of the built neighborhood, air pollution, irregular visits to the green space, and chronic disease had a joint effect on the magnitude of the prevalence of poor health in men and women. Our results suggest that decreasing air pollution and improving the urban built neighborhood supporting citizens’ physical activity in green spaces, might reduce health risks for all.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13824-3.

Exposure to urban greenspace and pathways to respiratory health: An exploratory systematic review

BACKGROUND/OBJECTIVE

Urban greenspace may have a beneficial or adverse effect on respiratory health. Our objective was to perform an exploratory systematic review to synthesise the evidence and identify the potential causal pathways relating urban greenspace and respiratory health.

METHODS

We followed PRISMA guidelines on systematic reviews and searched five databases for eligible studies during 2000-2021. We incorporated a broad range of urban greenspace and respiratory health search terms, including both observational and experimental studies. Screening, data extraction, and risk of bias, assessed using the Navigation Guide criteria, were performed independently by two authors. We performed a narrative synthesis and discuss suggested pathways to respiratory health.

RESULTS

We identified 108 eligible papers (n = 104 observational, n = 4 experimental). The most common greenspace indicators were the overall greenery or vegetation (also known as greenness), green land use/land cover of physical area classes (e.g., parks, forests), and tree canopy cover. A wide range of respiratory health indicators were studied, with asthma prevalence being the most common. Two thirds (n = 195) of the associations in these studies were positive (i.e., beneficial) with health, with 31% (n = 91) statistically significant; only 9% (n = 25) of reported associations were negative (i.e., adverse) with health and statistically significant. The most consistent positive evidence was apparent for respiratory mortality. There were n = 35 (32%) 'probably low' and n = 73 (68%) 'probably high' overall ratings of bias. Hypothesised causal pathways for health benefits included lower air pollution, more physically active populations, and exposure to microbial diversity; suggested mechanisms with poorer health included exposure to pollen and other aeroallergens.

CONCLUSION

Many studies showed positive association between urban greenspace and respiratory health, especially lower respiratory mortality; this is suggestive, but not conclusive, of causal effects. Results underscore the importance of contextual factors, greenspace metric employed, and the potential bias of subtle selection factors, which should be explored further.

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.

An Evaluation of Risk Ratios on Physical and Mental Health Correlations due to Increases in Ambient Nitrogen Oxide (NOx) Concentrations

Nitrogen oxides (NOx) are gaseous pollutants contributing to pollution in their primary form and are also involved in reactions forming ground-level ozone and fine particulate matter. Thus, NOx is of great interest for targeted pollution reduction because of this cascade effect. Primary emissions originate from fossil fuel combustion making NOx a common outdoor and indoor air pollutant. Numerous studies documenting the observed physical health impacts of NOx were reviewed and, where available, were summarized using risk ratios. More recently, the literature has shifted to focus on the mental health implications of NOx exposure, and a review of the current literature found five main categories of mental health-related conditions with respect to NOx exposure: common mental health disorders, sleep, anxiety, depression, and suicide. All the physical and mental health effects with available risk ratios were organized in order of increasing risk. Mental health concerns emerged as those most influenced by NOx exposure, with physical health impacts, such as asthma, only beginning to surface as the fourth highest risk. Mental health conditions occupied seven of the top ten highest risk health ailments. The results summarized in this narrative review show that there are clear positive correlations between NOx and negative physical and mental health manifestations, thus strengthening the argument in support of the reduction in ambient NOx levels.

Association between Land Use Mix and Respiratory Symptoms and Asthma in Children from the Generation XXI Birth Cohort

Land use mix (LUM) in the neighbourhoods has been associated with healthier lifestyles. However, less is known about the association between LUM and health outcomes, namely during childhood. The objective of this study was to evaluate the association between different LUM indexes for Porto Metropolitan Area and asthma and respiratory symptoms in children. A cross-sectional analysis was performed involving 6260 children enrolled in Generation XXI. Land use around the child's residence was assessed with the Portuguese official map of land cover using a GIS. Generalized linear mixed-effects models were fitted to estimate the association between LUM and respiratory symptoms and asthma at 7 years of age. Adjusted associations were quantified using odds ratio (OR) and 95% confidence interval (95% CI). After adjustment, LUM was associated with a lower odds of wheezing in the last 12 months [OR (95% CI) = 0.37 (0.15; 0.93) using Shannon's Evenness Index within 500 m; and OR = 0.93 (0.89; 0.98) using the number of different land use types within 250 m]. Living in neighbourhoods with high LUM has a protective effect on current wheezing symptoms. Our results highlight the association between LUM and respiratory symptoms among children, suggesting that public health considerations should be incorporated in land use decision-making.

The challenges of measuring social cohesion in public health research: A systematic review and ecometric meta-analysis

The relationship between social cohesion and health has been studied for decades. Yet, due to the contextual nature of this concept, measuring social cohesion remains challenging. Using a meta-analytical framework, this review's goal was to study the ecometric measurement properties of social cohesion in order to describe dissimilarities in its measurement as well as bring a new perspective on the empirical usefulness of the concept itself. To this end, we analysed if, and to what extent, contextual-level reliability and intersubjective agreement of 78 social cohesion measurements varied under different measurement conditions like measurement instrument, spatial unit, ecometric model specification, or region. We found consistent evidence for the contextual nature of social cohesion, however, most variation existed between individuals, not contexts. While contextual dependence in response behaviour was fairly insensitive to item choices, population size within chosen spatial units of social cohesion measurements mattered. Somewhat counterintuitively, using spatial units with, on average, fewer residents did not yield systematically superior ecometric properties. Instead, our results underline that precise theory about the relevant contextual units of causal relationships between social cohesion and health is vital and cannot be replaced by empirical analysis. Although adjustment for respondent's characteristics had only small effects on ecometric properties, potential pitfalls of this analytic strategy are discussed in this paper. Finally, acknowledging the sensitivity of measuring social cohesion, we derived recommendations for future studies investigating the effects of contextual-level social characteristics on health.

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Social cohesion aims to describe aspects of the social environment we live in but its measurement remains challenging.

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We meta-analysed the ecometric properties of 78 social cohesion measurements.

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There is modest but consistent evidence for the contextual nature of social cohesion.

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Contextual dependence in individual response behaviour is sensitive to the chosen spatial unit.

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Meta-ecometrics studies the empirical usefulness of theoretical concepts aiming to describe social environments.

Associations of greenness surrounding schools with blood pressure and hypertension: A nationwide cross-sectional study of 61,229 children and adolescents in China

BACKGROUND

Greenness exposure may lower blood pressure. However, few studies of this relationship have been conducted with children and adolescents, especially in low and middle-income countries.

OBJECTIVES

To evaluate associations between greenness around schools and blood pressure among children and adolescents across China.

METHODS

We recruited 61,229 Chinese citizens aged 6-18 years from 94 schools in a nationwide cross-sectional study in seven Chinese provinces/province-level municipalities. Participants' blood pressures and hypertension were assessed with standardized protocols. Greenness levels within 500 m and 1,000 m of each school were estimated with three satellite-based indices: vegetation continuous fields (VCF), normalized difference vegetation index (NDVI), and soil adjusted vegetation index (SAVI). Generalized linear mixed models were used to evaluate associations between greenness and blood pressure, greenness and prevalent hypertension, using coefficient and odds ratio respectively. Stratified analyses and mediation analyses were also performed.

RESULTS

One interquartile range increase in greenness was associated with a 17%-20% reduced prevalence of hypertension for all measures of greenness (odds ratios for VCF_500m = 20% (95% CI:18%, 23%); for NDVI_500m = 17% (95% CI:13%, 21%); and for SAVI_500m = 17% (95% CI: 13%, 20%). Increases in greenness were also associated with reductions in systolic blood pressure (0.48-0.58 mmHg) and diastolic blood pressure (0.26-0.52 mmHg). Older participants, boys, and urban dwellers showed stronger associations than their counterparts. No evidence of mediation was observed for air pollution (i.e., NO₂ and PM_2.5) and body mass index.

CONCLUSION

Higher greenness around schools may lower blood pressure levels and prevalent hypertension among Chinese children and adolescents, particularly in older subjects, boys, and those living in urban districts. Further studies, preferably longitudinal, are needed to examine causality.

Investigating the association between regeneration of urban blue spaces and risk of incident chronic health conditions stratified by neighbourhood deprivation: A population-based retrospective study, 2000-2018

Chronic non-communicable diseases are leading causes of poor health and mortality worldwide, disproportionately affecting people in highly deprived areas. We undertook a population-based, retrospective study of 137,032 residents in Glasgow, Scotland, to investigate the association between proximity to urban blue spaces and incident chronic health conditions during a canal regeneration programme. Hazard ratios (HRs) were estimated using Cox proportional hazards models adjusted for age and sex, with the incidence of a given health condition as the dependent variable. The analyses were stratified by socioeconomic deprivation tertiles. We found that, in areas in the highest deprivation tertile, proximity to blue space was associated with a lower risk of incident cardiovascular disease (HR 0.85, 95% Confidence Interval (CI) 0.76-0.95), hypertension (HR 0.85, 95% CI 0.79-0.92), diabetes (HR 0.88, 95% CI 0.83-0.94), stroke (HR 0.85, 95% CI 0.77-0.94) and obesity (HR 0.90, 95% CI 0.86-0.94), but not chronic pulmonary disease, after adjusting for age and sex covariates. In middle and low deprivation tertiles, living closer to the canal was associated with a higher risk of incident chronic pulmonary disease (middle: HR 1.56, 95% CI 1.24-1.97, low: HR 1.34, 95% CI 1.05-1.73). Moreover, in the middle deprivation tertile, a higher risk of stroke (HR 1.36, 95% CI 1.02-1.81) and obesity (HR 1.14, 95% CI 1.01-1.29) was observed. We conclude that exposure to blue infrastructure could be leveraged to mitigate some of the health inequalities in cities.

The relationship between greenspace exposure and psychopathology symptoms: A systematic review

Greenspace exposure is associated with psychological benefits. In this systematic review, we summarized and critically evaluated the literature on the relationship between greenspace exposure (i.e., objective and subjective assessments of interactions with nature) and psychopathology incidence and symptom severity in those with and without a clinical diagnosis. A secondary aim of our review was to examine potential interactions between greenspace exposure and urban environmental features (e.g., pollution, population density) associated with poorer mental health. We identified 40 studies published between January 1, 1981, and July 31, 2020, from PubMed and PsycINFO electronic database search. Although heterogeneous in assessments of greenspace exposure and psychopathology symptom domain, the majority of cross-sectional and longitudinal evidence found that objectively assessed greenspace exposure (e.g., satellite measures of greenery) was related to less severe symptoms and lower incidence of psychopathology in children (e.g., attention-deficit/hyperactivity disorder symptoms) and adults (e.g., depression symptoms). In addition, five studies that assessed urban environmental features suggest that greenspace exposure may show a net positive relationship with psychopathology over and above the absence of urban features. We discuss limitations of the literature and future directions, including more mechanistic work to delineate the potential cognitive, affective, and behavioral factors that may contribute to the beneficial relationship between greenspace exposure and psychological health.

Air pollution exposure and depression: A comprehensive updated systematic review and meta-analysis

We provide a comprehensive and updated systematic review and meta-analysis of the association between air pollution exposure and depression, searching PubMed, Embase, and Web of Sciences for relevant articles published up to May 2021, and eventually including 39 studies. Meta-analyses were performed separately according to pollutant type [particulate matter with diameter ≤10 μm (PM₁₀) and ≤2.5 μm (PM_2.5), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃), and carbon monoxide (CO)] and exposure duration [short- (<30 days) and long-term (≥30 days)]. Test for homogeneity based on Cochran's Q and I² statistics were calculated and the restricted maximum likelihood (REML) random effect model was applied. We assessed overall quality of pooled estimates, influence of single studies on the meta-analytic estimates, sources of between-study heterogeneity, and publication bias. We observed an increased risk of depression associated with long-term exposure to PM_2.5 (relative risk: 1.074, 95% confidence interval: 1.021-1.129) and NO₂ (1.037, 1.011-1.064), and with short-term exposure to PM₁₀ (1.009, 1.006-1.012), PM_2.5 (1.009, 1.007-1.011), NO₂ (1.022, 1.012-1.033), SO₂ (1.024, 1.010-1.037), O₃ (1.011, 0.997-1.026), and CO (1.062, 1.020-1.105). The publication bias affecting half of the investigated associations and the high heterogeneity characterizing most of the meta-analytic estimates partly prevent to draw very firm conclusions. On the other hand, the coherence of all the estimates after excluding single studies in the sensitivity analysis supports the soundness of our results. This especially applies to the association between PM_2.5 and depression, strengthened by the absence of heterogeneity and of relevant publication bias in both long- and short-term exposure studies. Should further investigations be designed, they should involve large sample sizes, well-defined diagnostic criteria for depression, and thorough control of potential confounding factors. Finally, studies dedicated to the comprehension of the mechanisms underlying the association between air pollution and depression remain necessary.

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.

The Burden of Disease Due to Road Traffic Noise in Hesse, Germany

Road-traffic-noise exposition is widespread in Germany and can have harmful health effects. As guidance for informed decision-making, we estimated the environmental burden of disease attributable to road-traffic noise in Hesse, Germany as disability-adjusted life-years (DALYs). Using detailed road-traffic-noise exposure data provided by the Hessian Agency for Nature Conservation, Environment, and Geology (HLNUG), we calculated the DALYs due to road-traffic noise > 40 dB(A) L_24h (unweighted average 24 h noise level) and other noise metrics for endpoints with known dose-response functions and evidence in the literature (NORAH-study on disease risks and WHO reviews): cardiovascular disease, depressive disorders, road-traffic annoyance, and sleep disturbance. We calculated the population-attributable fractions (PAF) for road-noise-related cardiovascular disease (hypertensive heart disease, ischemic heart disease, and stroke) and depressive disorders in the population using published relative risk estimates. We multiplied the PAFs with the Hessian proportion of the 2015 WHO DALY estimates for Germany in people aged ≥ 40 years. For high annoyance and high sleep disturbance, we used published dose-response functions to determine the burden for residents of all ages. For Hesse, we found a total of 26,501 DALYs attributable to road-traffic noise or 435 DALY per 100,000 persons for the reference year, 2015. Further, we estimated that a hypothetic uniform road-traffic-noise reduction of 3 dB would prevent 23% of this burden of disease.

Urban Environment and Health: A Cross-Sectional Study of the Influence of Environmental Quality and Physical Activity on Blood Pressure

Few studies have examined the relation between urban built environment and the prevalence of hypertension. This cross-sectional study aimed at assessing the relationship between the environmental quality, physical activity, and stress on hypertension among citizens of Kaunas city, Lithuania. We conducted a survey of 1086 citizens residing in 11 districts to determine their perceptions of environmental quality, health behavior, and health indices. The independent variables included residential traffic flows, access to public transportation and green spaces. Dependent variables included physician-diagnosed hypertension, systolic and diastolic blood pressure, and stress level. We used multivariable logistic regression to assess the associations as odds ratios (OR). The environmental factors beneficially associated with meeting the physical activity recommendations were opportunities for walking to reach the city's green spaces and available relaxation areas. Residents of high noise level districts aged 45-64 years had a significantly higher OR of stress and a higher prevalence of hypertension when age, sex, education status, family status, and smoking were accounted for. However, meeting the physical activity recommendations had a beneficial effect on the risk of hypertension. This study provided evidence that improvement of the district-level built environment supporting citizens' physical activity might reduce the risk of hypertension.

Long-term exposure to ambient fine particulate matter originating from traffic and residential wood combustion and the prevalence of depression

Introduction

Air pollution has been suggested to be associated with depression. However, current evidence is conflicting, and no study has considered different sources of ambient particulate matter with an aerodynamic diameter below 2.5 µm (PM_2.5). We evaluated the associations of long-term exposure to PM_2.5 from road traffic and residential wood combustion with the prevalence of depression in the Helsinki region, Finland.

Methods

We conducted a cross-sectional analysis based on the Helsinki Capital Region Environmental Health Survey 2015–2016 (N=5895). Modelled long-term outdoor concentrations of PM_2.5 were evaluated using high-resolution emission and dispersion modelling on an urban scale and linked to the home addresses of study participants. The outcome was self-reported doctor-diagnosed or treated depression. We applied logistic regression and calculated the OR for 1 μg/m³ increase in PM_2.5, with 95% CI. Models were adjusted for potential confounders, including traffic noise and urban green space.

Results

Of the participants, 377 reported to have been diagnosed or treated for depression by a doctor. Long-term exposure to PM_2.5 from road traffic (OR=1.23, 95% CI 0.86 to 1.73; n=5895) or residential wood combustion (OR=0.78, 95% CI 0.43 to 1.41; n=5895) was not associated with the prevalence of depression. The estimates for PM_2.5 from road traffic were elevated, but statistically non-significant, for non-smokers (OR=1.38, 95% CI 0.94 to 2.01; n=4716).

Conclusions

We found no convincing evidence of an effect of long-term exposure to PM_2.5 from road traffic or residential wood combustion on depression.

Associations of co-exposures to air pollution and noise with psychological stress in space and time: A case study in Beijing, China

Air pollution and noise are both ubiquitous environmental stressors that pose great threats to public health. Emerging evidence has noticed the combined health risks caused by the coexistence of traffic-related air pollutants and noise in the residential context. However, less is known about how mobile individuals are simultaneously exposed to multiple sources of air pollution and noise, and thus respond with more acute psychological responses beyond the residence. This study examines the co-exposures to fine particles (PM_2.5) and noise across spatiotemporal contexts where the concurrent exposures are jointly associated with momentary psychological stress. An innovative research protocol, including GPS-equipped activity-travel diaries, air pollutant and noise sensors, and ecological momentary assessment, was adopted to collect real-time data from a sample of residents in Beijing, China. The results showed a minor correlation between PM_2.5 and noise exposures after accounting for individual mobility and the spatiotemporal dynamics of these two environmental pollutants. Further, exposure to PM_2.5 was more associated with momentary psychological stress given the insignificant independent effect and the weak moderating effect of noise exposure. Three specific spatiotemporal contexts involving the health risks of co-exposures were delineated, including morning rush hours and traveling by public transits with intensified stress risks caused by combined exposures to air pollution and noise, workplaces with counteracting stress effect of both exposures, and evening time at home with stress-induced air pollution and stress-relieving social noise. In conclusion, the mobility-based and context-aware analysis provides a more nuanced understanding of the associations of co-exposures to environmental pollution and synchronous psychological stress in space and time.

A Multilevel Perspective on the Health Effect of Social Capital: Evidence for the Relative Importance of Individual Social Capital over Neighborhood Social Capital

Employing a multilevel perspective on the health effects of social capital, this study analyzes how individual and neighborhood differences in self-rated health in Ghent (Belgium), relate to individual and collective social mechanisms, when taking demographic and socioeconomic characteristics of individuals into account. This study estimates the health effects of social trust, informal social control and disorder at the neighborhood level and social support and network size at the individual level, using indicators indebted to both the normative and resource-based approaches to social capital. Instead of the mere aggregation of individual indicators of social capital, this study uses the key informant technique as a methodologically superior measurement of neighborhood social capital, which combined with a multilevel analysis strategy, allows to disentangle the health effects of individual and neighborhood social capital. The analysis highlights the health benefits of individual social capital, i.e., individual social support and network size. The study indicates that controlling for individual demographic and socioeconomic characteristics reduces the effect of the neighborhood-level counterparts and the neighborhood characteristics social trust and neighborhood disorder have significant, but small health effects. In its effects on self-rated health, social capital operates on the individual level, rather than the neighborhood level.

Association between particulate matter air pollution and risk of depression and suicide: a systematic review and meta-analysis

An increasing number of studies examined the potential effects of ambient particulate matter (PM: PM2.5 and PM10-PMs with diameters not greater than 2.5 and 10 μm, respectively) pollution on the risk of depression and suicide; however, the results have been inconclusive. This study aimed to determine the overall relationship between PM exposure and depression/suicide based on current evidence. We conducted a systematic review and meta-analysis of current available studies. Thirty articles (20 for depression and 10 for suicide) with data from 1,447,313 participants were included in the meta-analysis. For a 10 μg/m3 increase in short-term exposure to PM2.5, we found a 2% (p < 0.001) increased the risk of depression and a 2% (p = 0.001) increased risk of suicide. A 10 μg/m3 increase in long-term exposure to PM2.5 was associated with a more apparent increase of 18% (p = 0.005) in depression risk. In addition, a 10 μg/m3 increase in short-term exposure to PM10 was associated with a 2% (p = 0.003) increase in depression risk and a 1% (p = 0.002) increase in suicide risk. Subgroup analyses showed that associations between PM and depression were more apparent in people over 65 years and from developed regions. Besides, the study design and study quality might also have an impact on their associations. The meta-analysis found that an increase in ambient PM concentration was strongly associated with an increased risk of depression and suicide, and the associations for depression appeared stronger for smaller particles (PM2.5) and at a long-term time pattern.

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 (L_den), 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.

Outdoor light at night, air pollution and depressive symptoms: A cross-sectional study in the Netherlands

BACKGROUND

Artificial light at night (ALAN) may be an anthropogenic stressor for mental health disturbing humans' natural day-night cycle. However, the few existing studies used satellite-based measures of radiances for outdoor ALAN exposure assessments, which were possibly confounded by traffic-related air pollutants.

OBJECTIVES

To assess 1) whether living in areas with increased exposure to outdoor ALAN is associated with depressive symptoms; and 2) to assess the potential confounding effects of air pollution.

METHODS

We used cross-sectional data from people (N = 10,482) aged 18-65 years in the Netherlands. Depressive symptoms were assessed with the Patient Health Questionnaire (PHQ-9). Satellite-measured annual ALAN were taken from the Visible Infrared Imaging Radiometer Suite. ALAN exposures were assessed at people's home address within 100 and 600 m buffers. We used generalized (geo)additive models to quantify associations between PHQ-9 scores and quintiles of ALAN adjusting for several potential confounders including PM_2.5 and NO₂.

RESULTS

Unadjusted estimates for the 100 m buffers showed that people in the 2^nd to 5^th ALAN quintile showed significantly higher PHQ-9 scores than those in the lowest ALAN quintile (β_Q2 = 0.503 [95% confidence intervals (CI): 0.207-0.798], β_Q3 = 0.587 [95% CI: 0.291-0.884], β_Q4 = 0.921 [95% CI: 0.623-1.218], β_Q5 = 1.322 [95% CI: 1.023-1.620]). ALAN risk estimates adjusted for individual and area-level confounders (i.e., PM_2.5, urbanicity, noise, land-use diversity, greenness, deprivation, and social fragmentation) were attenuated but remained significant for the 100 m buffer (β_Q2 = 0.420 [95% CI: 0.125-0.715], β_Q3 = 0.383 [95% CI: 0.071-0.696], β_Q4 = 0.513 [95% CI: 0.177-0.850], β_Q5 = 0.541 [95% CI: 0.141-0.941]). When adjusting for NO₂ per 100 m buffers, the air pollutant was associated with PHQ-9 scores, but ALAN did not display an exposure-response relationship. ALAN associations were insignificant for 600 m buffers.

CONCLUSION

Accounting for NO₂ exposure suggested that air pollution rather than outdoor ALAN correlated with depressive symptoms. Future evaluations of health effects from ALAN should consider potential confounding by traffic-related exposures (i.e., NO₂).

Neighborhood greenness associated with chronic obstructive pulmonary disease: A nationwide cross-sectional study in China

Differential findings have been reported on the association between neighborhood greenness and chronic obstructive pulmonary disease (COPD). The underlying reasons might be the different types of vegetation and the diagnosis methods used in different studies. In this nationwide cross-sectional study in China, we examined the linkage between neighborhood greenness and COPD prevalence among 66,752 adults aged 40 years and above. Neighborhood greenness was estimated using the normalized difference vegetation index (NDVI) based on satellite imagery within buffers of 100, 300, 500, 1000, 2000, 3000 and 5000 m of residential community of the participants. COPD was defined according to the 2017 Global Initiative for Chronic Obstructive Lung Disease lung function criteria. A two-level logistic regression model was applied to estimate the associations. Finally, 9134 adults were classified as COPD. We observed significant positive associations between neighborhood greenness and COPD prevalence. The odds ratio for each interquartile range increase in NDVI within 100 m buffer was 1.08 (95% CI: 1.01, 1.15) after adjustment for potential confounders. Consistent associations were observed across all other NDVI buffer sizes. Stratified analyses revealed that younger adults (40-65 years) and urban residents might be the vulnerable subpopulations. Further regional analyses found that residents from the Northeastern and Northern China were more likely to have this association. Our results indicated that neighborhood greenness might be one risk factor of COPD prevalence. Our study have important public health implications for allocating the surrounding green spaces among living areas, especially for those with respiratory illness; however, the findings and the underlying mechanisms warrant further examinations in longitudinal settings.

Prevalence of non-specific health symptoms in livestock dense areas: Looking beyond respiratory conditions

The aim of this study was to gain more insight in the association between prevalence of diverse acute non-specific symptoms (NSS) and livestock density as a possible risk factor among residents of livestock-dense and non-dense regions, taking into account socio-demographic factors and psychological morbidity. Prevalence of NSS and psychological morbidity were assessed for the year 2017, based on electronic health records from 39 general practices in the Netherlands. The study group consisted of people who lived in rural areas with high numbers of livestock (n = 74093), while the control group included people in rural areas with low numbers of livestock (n = 50139). For a large portion of the study group, exposure estimates (to livestock) were calculated. Multiple logistic multilevel regression analyses were performed. Two methods were used: 1) area comparisons between study and control areas in relation to health problems, and 2) estimates of livestock exposure (to goats, poultry, pigs, and cattle) within the study area. It was found that prevalence of diarrhea, headache, sleep disturbance, respiratory symptoms, and skin problems were higher in the study group. The data suggest that there may be a protective effect of livestock exposure: in general, there was a lower risk of NSS closer to livestock (within the exposure analyses). The study suggests that the previously identified higher risk of respiratory health problems in livestock dense areas might also apply to the prevalence of various other NSS. Longitudinal research taking into account different or more individual and contextual characteristics could possibly elucidate why prevalence of NSS in closer proximity to livestock is lower compared to people who live further away, whilst a more overarching analysis indicated that living in livestock dense areas was associated with more NSS.

Traffic Noise and Mental Health: A Systematic Review and Meta-Analysis

Recent evidence suggests that traffic noise may negatively impact mental health. However, existing systematic reviews provide an incomplete overview of the effects of all traffic noise sources on mental health. We conducted a systematic literature search and summarized the evidence for road, railway, or aircraft noise-related risks of depression, anxiety, cognitive decline, and dementia among adults. We included 31 studies (26 on depression and/or anxiety disorders, 5 on dementia). The meta-analysis of five aircraft noise studies found that depression risk increased significantly by 12% per 10 dB L_DEN (Effect Size = 1.12, 95% CI 1.02–1.23). The meta-analyses of road (11 studies) and railway traffic noise (3 studies) indicated 2–3% (not statistically significant) increases in depression risk per 10 dB L_DEN. Results for road traffic noise related anxiety were similar. We did not find enough studies to meta-analyze anxiety and railway or aircraft noise, and dementia/ cognitive impairment and any traffic noise. In conclusion, aircraft noise exposure increases the risk for depression. Otherwise, we did not detect statistically significant risk increases due to road and railway traffic noise or for anxiety. More research on the association of cognitive disorders and traffic noise is required. Public policies to reduce environmental traffic noise might not only increase wellness (by reducing noise-induced annoyance), but might contribute to the prevention of depression and anxiety disorders.

The association between natural outdoor environments and common somatic symptoms

There is growing evidence that urban natural outdoor environments (NOE) may positively impact health by reducing stress and stress-related symptoms. However, there is limited research investigating this link across a range of NOE indicators. This cross-sectional study investigated the association between neighbourhood NOE (availability, use, and satisfaction with NOE) and common somatic symptoms and the role of potential mediators. Data were analysed from 3481 adults from Barcelona (Spain), Doetinchem (Netherlands), Kaunas (Lithuania) and Stoke-on-Trent (United Kingdom). NOE data were obtained through self-reported data and environmental measurements. Common somatic symptom data were self-reported. Mixed effects regression models were used for analysis, with models adjusted for potential sociodemographic confounders. Higher satisfaction with neighbourhood NOE was associated with lower prevalence of common somatic symptoms (exp(β) 0.97; 95% CI 0.96, 0.98); an association partially mediated by mental health, social cohesion and air quality concern. A longer time spent in NOE was associated with lower prevalence of common somatic symptoms in low socioeconomic status neighbourhoods (exp(β) 0.98; 95% CI 0.96, 1.00). A higher number of neighbourhood green spaces (300m buffer) was associated with higher prevalence of common somatic symptoms (exp(β) 1.03; 95% CI 1.00, 1.05). No statistically significant associations were found for other NOE indicators. Study findings suggest that higher satisfaction with NOE may be associated with lower prevalence of common somatic symptoms, with mental health, social cohesion and concern about air quality playing partial mediating roles. Little evidence was found of an association between objective NOE measurements and common somatic symptoms, underlining the importance of perceptions of NOE for conferring health benefits.

The spatial relationship between traffic-related air pollution and noise in two Danish cities: Implications for health-related studies

Air pollution and noise originating from urban road traffic have been linked to the adverse health effects e.g. cardiovascular disease (CVD), although their generation and propagation mechanisms vary. We aimed to (i) develop a tool to model exposures to air pollution and noise using harmonized inputs based on similar geographical structure (ii) explore the relationship (using Spearman's rank correlation) of both pollutions at residential exposure level (iii) investigate the influence of traffic speed and Annual Average Daily Traffic (AADT) on air-noise relationship. The annual average (2005) air pollution (NO_x, NO₂, PM₁₀, PM_2.5) and noise levels (L_day, L_eve, L_night, L_den, L_Aeq,24h) are modelled at address locations in Copenhagen and Roskilde (N = 11,000 and 1500). The new AirGIS system together with the Operational Street Pollution Model (OSPM®) is used to produce air pollution estimates. Whereas, noise is estimated using Common Noise Assessment Methods in the EU (CNOSSOS-EU, hereafter CNOSSOS) with relatively coarser inputs (100 m CORINE land cover, simplified vehicle composition). In addition, noise estimates (L_day, L_eve, L_night) from CNOSSOS are also compared with noise estimates from Road Traffic Noise 1996 (RTN-96, one of the Nordic noise prediction standards). The overall air-noise correlation structure varied significantly in the range |r_S| = 0.01-0.42, which was mainly affected by the background concentrations of air pollution as well as non-traffic emission sources. Moreover, neither AADT nor traffic speed showed substantial influence on the air-noise relationship. The noise levels estimated by CNOSSOS were substantially lower, and showed much lower variation than levels obtained by RTN-96. CNOSSOS, therefore, needs to be further evaluated using more detailed inputs (e.g. 10 m land cover polygons) to assess its feasibility for epidemiological noise exposure studies in Denmark. Lower to moderate air-noise correlations point towards significant potential to determine the independent health effects of air pollution and noise.

Different types of urban natural environments influence various dimensions of self-reported health

BACKGROUND

Growing evidence suggests health benefits of natural environments. Yet, the effects of different types of natural environments (vegetation and water features) and forms of human-nature contact (access versus exposure) remain relatively unexplored.

METHODS

A cross-sectional observational survey was used to analyse the relationship between both access and exposure to different types of urban natural environments and health outcomes in Metro Vancouver, Canada. Data for health outcomes (self-reported general health, mental health, and common mental disorders) and key confounders were obtained from the 2013-2014 Canadian Community Health Survey. Natural environments were quantified using local land use and land cover data, and linked to survey respondents by six-digit postal code. Access was defined as living within 300 m of a public greenspace (≥ 1 hectare) and exposure as the percentage of different land cover types within multiple buffer distances of postal code centroids. Separate logistic regression models were used to estimate the associations of the access and exposure metrics with the three health outcomes.

RESULTS

Exposure to water within 1,000 m buffers was associated with a reduced odds of reporting poor general health (OR = 0.982, 95% CI = 0.965, 0.999). A similar association was found for exposure to shrub and grass-herb vegetation types for reported mental health and common mental disorder, respectively (OR = 0.741, 95% CI = 0.576, 0.953 for shrubs in 250 m; OR = 0.737, 95% CI = 0.577, 0.942 for shrubs in 500 m; OR = 0.731, 95% CI = 0.570, 0.938 for shrubs in 1,000 m; OR = 0.980, 95% CI = 0.965, 0.995 for grass-herbs in 250 m). Neither access to public greenspace nor aggregated greenspace exposure were associated with self-reported health. Results from stratified analyses suggest that observed associations between human-nature contact and self-reported health differ according to gender.

CONCLUSIONS

Results suggest that type of natural environment should be considered in future research studying the health-promoting aspects of natural environments, and that positive health effects may be more consistent for daily life exposure than for access to public greenspace.

The longitudinal relationship between exposure to air pollution and depression in older adults

BACKGROUND

Air pollution, especially PM_2.5 (particulate matter with a diameter of below 2.5 μm), has been recognized as a key environmental factor that affects mental health, but few studies have focused on its influence on older adults, who are a vulnerable group.

OBJECTIVE

This study focused on the influence of PM_2.5 on health-related behaviors, such as physical activities and social contact, to assess their role as mediators of depression among older adults in China.

METHODS

We used data (N = 24 623) from the CHARLS (China Health and Retirement Longitudinal Study) of 2011-2015. CES-D 10 (Center for Epidemiology Studies of Depression scale) was used to measure depression. Using multilevel linear models, we examined the relationships between the variables, with different times nested within the same individual and individuals nested within the cities.

RESULTS

Before mediators were added, depression symptoms among older adults increased with annual concentration of PM_2.5 (Coeff = 0.57, SE = 0.11). However, after the mediators were added, the coefficient of the annual concentration of PM_2.5 decreased (Coeff = 0.37, SE = 0.10). While both physical activities (Sobel test Z score = 2.37, P value = .02) and social contact (Z score = 7.33, P value = .00) mediated the relationship between PM_2.5 and depression, the mediating effects decreased with increasing PM_2.5 .

CONCLUSIONS

Exposure to PM_2.5 , therefore, increases depressive symptoms in older Chinese adults by decreasing their physical activities and social contact. Also, the positive effects of physical activities and social contact on depression decreased with increasing PM_2.5 concentrations.

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.

Evidence Relating to Environmental Noise Exposure and Annoyance, Sleep Disturbance, Cardio-Vascular and Metabolic Health Outcomes in the Context of IGCB (N): A Scoping Review of New Evidence

WHO published the Environmental Noise Guidelines for the European Region in 2018, based on seven systematic reviews including studies published between 2000 and 2014. Since then, new studies were published. At the request of the UK Department for Environment, Food and Rural Affairs (DEFRA), a review on annoyance, sleep disturbance, cardiovascular and metabolic effects in relation to environmental noise was prepared. The aim was to advise the Interdepartmental Group on Costs and Benefits Noise Subject Group (IGCB(N)) whether this new evidence warrants an update of their recommendations. Four databases for observational studies were screened and data were extracted on design, type and measurements of exposures and outcomes and confounders and their associations. The quality of the studies was indirectly assessed for cardiovascular and metabolic effects by only including studies with a case control or cohort design. For studies on annoyance and sleep disturbance, the risk of bias was expressed in exposure misclassification, selective participation and confounding. The update yielded 87 papers, pertaining to 108 new studies of which 40 new studies were on annoyance, 42 on sleep disturbance and 26 concerning cardiovascular and metabolic effects. The number, size and quality of the new studies suggest new meta-analyses could be undertaken over the sources and effects included in the WHO reviews.

Ambient air pollution and depression: A systematic review with meta-analysis up to 2019

Although epidemiological studies have evaluated the associations of ambient air pollution with depression, the results remained mixed. To clarify the nature of the association, we performed a comprehensive systematic review and meta-analysis with the Inverse Variance Heterogeneity (IVhet) model to estimate the effect of ambient air pollution on depression. Three English and four Chinese databases were searched for epidemiologic studies investigating associations of ambient particulate (diameter ≤ 2.5 μm (PM_2.5), ≤10 μm (PM₁₀)) and gaseous (nitric oxide (NO), nitrogen dioxide (NO₂), carbon monoxide (CO), sulfur dioxide (SO₂) and ozone (O₃)) air pollutants with depression. Odds ratios (OR) and corresponding 95% confidence intervals (CI) were calculated to evaluate the strength of the associations. We identified 22 eligible studies from 10 countries of the world. Under the IVhet model, per 10 µg/m³ increase in long-term exposure to PM_2.5 (OR: 1.12, 95% CI: 0.97-1.29, I²: 51.6), PM₁₀ (OR: 1.04, 95% CI: 0.88-1.25, I²: 85.7), and NO₂ (OR: 1.05, 95% CI: 0.83-1.34, I²: 83.6), as well as short-term exposure to PM_2.5 (OR: 1.01, 95% CI: 0.99-1.04, I²: 51.6), PM₁₀ (OR: 1.01, 95% CI: 0.98-1.04, I²: 86.7), SO₂ (OR: 1.03, 95% CI: 0.99-1.07, I²: 71.2), and O₃ (OR: 1.01, 95% CI: 0.99-1.03, I²: 82.2) was not significantly associated with depression. However, we observed significant association between short-term NO₂ exposure (per 10 µg/m³ increase) and depression (OR: 1.02, 95% CI: 1.00-1.04, I²: 65.4). However, the heterogeneity was high for all of the pooled estimates, which reduced credibility of the cumulative evidence. Additionally, publication bias was detected for six of eight meta-estimates. In conclusion, short-term exposure to NO₂, but not other air pollutants, was significantly associated with depression. Given the limitations, a larger meta-analysis incorporating future well-designed longitudinal studies, and investigations into potential biologic mechanisms, will be necessary for a more definitive result.

Evidence for Environmental Noise Effects on Health for the United Kingdom Policy Context: A Systematic Review of the Effects of Environmental Noise on Mental Health, Wellbeing, Quality of Life, Cancer, Dementia, Birth, Reproductive Outcomes, and Cognition

This systematic review commissioned by the UK Department for the Environment, Food and Rural Affairs (Defra), considers how the evidence base for noise effects on health has changed following the recent reviews undertaken for the WHO Environmental Noise Guidelines. This systematic review assesses the quality of the evidence for environmental noise effects on mental health, wellbeing, and quality of life; birth and reproductive outcomes; and cognition for papers published since the WHO reviews (mid-2015 to March 2019), as well as for cancer and dementia (January 2014 to March 2019). Using the GRADE methodology (Grading of Recommendations Assessment, Development and Evaluation) most evidence was rated as low quality as opposed to very low quality in the previous reviews. There is now low-quality evidence for a harmful effect of road traffic noise on medication use and interview measures of depression and anxiety and low quality evidence for a harmful effect of road traffic noise, aircraft noise, and railway noise on some cancer outcomes. Many other conclusions from the WHO evidence reviews remain unchanged. The conclusions remain limited by the low number of studies for many outcomes. The quantification of health effects for other noise sources including wind turbine, neighbour, industrial, and combined noise remains a research priority.