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

Long-term effects of fine particulate matter components on depression among middle-aged and elderly adults in China: A nationwide cohort study

BACKGROUND

Fine particulate matter (PM2.5) has been implicated in various health concerns. However, a comprehensive understanding of the specific PM2.5 components affecting depression remains limited.

METHODS

This study conducted a Cox proportional-hazards model to assess the effect of PM2.5 components on the incidence of depression based on the China Health and Retirement Longitudinal Study (CHARLS). Participants with 10-item Center for Epidemiologic Studies Depression Scale (CESD-10) score of 10 or higher were classified as exhibiting depression.

RESULTS

Our findings demonstrated a significant positive correlation between long-term exposure to black carbon (BC), sulfate (SO42-), and organic matter (OM) components of PM2.5 and the prevalence of depression. Per 1 Interquartile Range (IQR) increment in 3-year average concentrations of BC, OM, and SO42- were associated with the hazard ratio (HR) of 1.54 (95 % confidence intervals (CI): 1.44, 1.64), 1.24 (95%CI: 1.16, 1.34) and 1.25 (95%CI: 1.16, 1.35). Notably, females, younger individuals, those with lower educational levels, urban residents, individuals who were single, widowed, or divorced, and those living in multi-story houses exhibited heightened vulnerability to the adverse effects of PM2.5 components on depression.

LIMITATIONS

Firstly, pollutant data is confined to subjects' fixed addresses, overlooking travel and international residence history. Secondly, the analysis only incorporates five fine particulate components, leaving room for further investigation into the remaining fine particulate components in future studies.

CONCLUSIONS

This study provides robust evidence supporting the detrimental impact of PM2.5 components on depression. The identification of specific vulnerable populations contributes to a deeper understanding of the underlying mechanisms involved in the relationship between PM2.5 components and depression.

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.

Objectively measured the impact of ambient air pollution on physical activity for older adults

BACKGROUND

Air pollution poses a significant health risk to the human population, especially for vulnerable groups such as the elderly, potentially discouraging their engagement in physical activity. However, there is a lack of sufficient objective and longitudinal data in current research on how air pollution affects physical activity among older adults. With these gaps, we aimed to explore the relationship between air pollution and objective measurement-based physical activity among older adults by engaging in a longitudinal study design.

METHODS

A total of 184 older adults were recruited from three cities with varying levels of air quality. Mean daily minutes of physical activity were measured with 7 consecutive days of accelerometer monitoring (ActiGraph GT3X-BT). Corresponding air pollution data including daily PM2.5 (µg/m3), PM10 (µg/m3) and air quality index (AQI) were sourced from the China National Environmental Monitoring Centre at monitor locations close to older adults' addresses. Associations between air quality and physical activity were estimated using a fixed effect model, adjusting for average daytime temperature, rain, age and weight.

RESULTS

AQI and PM2.5 were observed to exhibit significant, inverse, and linear associations with mean daily walk steps, minutes of light physical activity (LPA), moderate physical activity (MPA) and moderate-to-vigorous physical activity (MVPA) in the single variable models. A one-level increase in AQI corresponded to a decline in 550.04 steps (95% [CI] = -858.97, -241.10; p < 0.001), 10.43 min (95% [CI] = -17.07, -3.79; p < 0.001), 4.03 min (95% [CI] = -7.48, -0.59; p < 0.001) and 4.16 min (95% [CI] = -7.77, -0.56; p < 0.001) in daily walking steps, LPA, MPA, and MVPA, respectively. A one-level increase in PM2.5 correlated with a decline in daily walk steps, LPA, MPA and MVPA by 361.85 steps (95% [CI] = -516.53, -207.16; p < 0.001), 8.97 min (95% [CI] = -12.28, -5.66; p < 0.001), 3.73 min (95% [CI] = -5.46, -2.01; p < 0.001,) and 3.79 min (95% [CI] = -5.59, -1.98; p < 0.001), respectively. However, PM10 displayed a significant negative association exclusively with LPA, with one-level increase in PM10 resulting in a 3.7-minute reduction in LPA (95% [CI] = -6.81, -0.59, p < 0.05).

CONCLUSION

Air pollution demonstrates an inverse association with physical activity levels among older adults, potentially discouraging their engagement in physical activity. Different air quality indicators may exert varying impacts on physical activity. Future studies are warranted to enhance policy interventions aimed at reducing air pollution and promoting physical activity.

Mental health impacts of environmental exposures: A scoping review of evaluative instruments

To date, much of the health focus of environmental policy has been on preventing physical health impacts of environmental exposures. Recent research has however highlighted increasingly concurrent mental health effects and its consideration is an emerging requirement for many governments and their agencies, yet there are limited universal mental health assessment tools for environmental exposures. This paper details the findings of a scoping review that evaluated assessment tools used to measure psychological impacts from environmental exposures and pollution, as reported in recent peer-reviewed literature (2000-2022). Across the 126 papers identified in our review, a wide range of tools to assess mental health impact were identified. We document a clear recent upswing of research interest in the mental and psychological impacts of environmental exposures, and an overarching concern for air pollution from industry, traffic, and fires. A majority of studies utilised standardised assessment instruments, but there was little consistency in the way that these were combined or deployed. The dominant mental health outcomes of interest in these studies were depression, anxiety, and mental and psychiatric health. The findings of the review identify a need and opportunity to develop a best-practice approach to consistently assess the mental health impacts arising from environmental exposures. Future work is needed to define the most appropriate choice and application of assessment tools to evaluate adverse mental health impacts from environmental exposures. This will support a more universal, coordinated and cross-jurisdiction approach for the assessment, quantification and targeted response to addressing mental health impacts arising from environmental exposures.

Particulate matters (PM2.5, PM10) and the risk of depression among middle-aged and older population: analysis of the Korean Longitudinal Study of Aging (KLoSA), 2016-2020 in South Korea

BACKGROUND

There is a growing concern that particulate matter (PM) such as PM2.5 and PM10 has contributed to exacerbating psychological disorders, particularly depression. However, little is known about the roles of these air pollutants on depression in elderly. Therefore, this study aimed to examine the association between PM2.5 and PM10, and depression in the elderly population in South Korea.

METHODS

We used panel survey data, the Korean Longitudinal Study of Aging (KLoSA), administered by the Labor Institute during the study period of 2016, 2018, and 2020 covering 217 districts in South Korea (n = 7674). Annual district-specific PM2.5 and PM10 concentrations were calculated for the study period from the monthly prediction concentrations produced by a machine-learning-based ensemble model (cross-validated R2: 0.87), then linked to the people matching with year and their residential district. We constructed a generalized estimating equation (GEE) model with a logit link to identify the associations between each of the long-term PM2.5 and PM10 exposures and depression (CES-D 10) after adjusting for individual and regional factors as confounders.

RESULTS

In single-pollutant models, we found that long-term 10 [Formula: see text] increments in PM2.5 (OR 1.36, 95% CI 1.20-1.56) and PM10 (OR 1.19, 95% CI 1.10-1.29) were associated with an increased risk of depression in the elderly. Associations were consistent after adjusting for other air pollutants (NO2 and O3) in two-pollutant models. In addition, the impacts substantially differed by regions grouped by the tertile of the population density, for which the risks of particulate matters on depression were substantial in the middle- or high-population-density areas in contrast to the low-population-density areas.

CONCLUSIONS

Long-term exposure to PM2.5 and PM10 was associated with a higher risk of developing depression in elderly people. The impact was modified by the population density level of the region where they reside.

Meteorological factors, ambient air pollution, and daily hospital admissions for depressive disorder in Harbin: A time-series study

BACKGROUND

The literature has discussed the relationship between environmental factors and depressive disorders; however, the results are inconsistent in different studies and regions, as are the interaction effects between environmental factors. We hypothesized that meteorological factors and ambient air pollution individually affect and interact to affect depressive disorder morbidity.

AIM

To investigate the effects of meteorological factors and air pollution on depressive disorders, including their lagged effects and interactions.

METHODS

The samples were obtained from a class 3 hospital in Harbin, China. Daily hospital admission data for depressive disorders from January 1, 2015 to December 31, 2022 were obtained. Meteorological and air pollution data were also collected during the same period. Generalized additive models with quasi-Poisson regression were used for time-series modeling to measure the non-linear and delayed effects of environmental factors. We further incorporated each pair of environmental factors into a bivariate response surface model to examine the interaction effects on hospital admissions for depressive disorders.

RESULTS

Data for 2922 d were included in the study, with no missing values. The total number of depressive admissions was 83905. Medium to high correlations existed between environmental factors. Air temperature (AT) and wind speed (WS) significantly affected the number of admissions for depression. An extremely low temperature (-29.0 ℃) at lag 0 caused a 53% [relative risk (RR)= 1.53, 95% confidence interval (CI): 1.23-1.89] increase in daily hospital admissions relative to the median temperature. Extremely low WSs (0.4 m/s) at lag 7 increased the number of admissions by 58% (RR = 1.58, 95%CI: 1.07-2.31). In contrast, atmospheric pressure and relative humidity had smaller effects. Among the six air pollutants considered in the time-series model, nitrogen dioxide (NO2) was the only pollutant that showed significant effects over non-cumulative, cumulative, immediate, and lagged conditions. The cumulative effect of NO2 at lag 7 was 0.47% (RR = 1.0047, 95%CI: 1.0024-1.0071). Interaction effects were found between AT and the five air pollutants, atmospheric temperature and the four air pollutants, WS and sulfur dioxide.

CONCLUSION

Meteorological factors and the air pollutant NO2 affect daily hospital admissions for depressive disorders, and interactions exist between meteorological factors and ambient air pollution.

A study on longitudinal relationship between ultrafine dust and the prevalence of depression

BACKGROUND

Recently, the fine dust problem caused by rapid industrialization and science and technological development has emerged as a severe social issue worldwide. This also increases the interest in its effect on human life. In particular, there is a growing concern about the harm of fine dust in Korea.

METHODS

This study is based on the PM 2.5 data from 2017 to 2021 provided by Air Korea to estimate changes in ultrafine dust. In addition, the data from the Community Health Survey provided by the Korea Centers for Disease Control and Prevention (KCDC) from 2017 to 2021 were used to examine the effect between the change in ultra-fine dust and the prevalence of depression. A total of 229 local governments were included in the analysis. The Latent Growth Modeling was carried out to estimate the change in ultra-fine dust and the prevalence of depressions and verify the relationship between ultra-fine dust and the prevalence of depression.

RESULTS

The analysis result revealed that the ultra-fine dust concentration continued to decrease from 2017 to 2021. However, the depression prevalence increased from an average of 2.60% in 2017 to an average of 3.12% in 2021, suggesting the need for adequate and sufficient welfare policies for depression treatment. As a result of estimating the initial value and change rate of ultra-fine dust and depression prevalence, the higher the initial value of ultra-fine dust, the greater the decrease in ultra-fine dust. In terms of depression, the lower the initial value of the prevalence of depression, the larger the increase in depression prevalence.

CONCLUSIONS

This study is significant in that it revealed the strong association of the longitudinal relationship between ultra-fine dust and depression, one of the biggest issues in Korea, by utilizing large-scale longitudinal data.

Association Between Sunlight Exposure and Mental Health: Evidence from a Special Population Without Sunlight in Work

Purpose

In recent years, mental health problems have become the most serious social problems worldwide. Past studies have proposed that some links exist between sunlight and mental health; however, relevant studies examining low-dose sunlight exposure populations are lacking. We conducted a study among a group of operating room nurses (ORNs) who work long hours in operating rooms and have limited sunlight exposure. We aim to add to and refine previous researches on the association between mental health and sunlight exposure in community population.

Patients and Methods

A total of 787 ORNs were interviewed and analyzed. Mental health, sunlight exposure duration, sociodemographic and work-related variables, and chronic diseases were evaluated. The Kessler 10 scale (K10) was used to assess participants' mental health status, and their sunlight exposure duration was assessed using their self-reports. Multiple linear regression analysis was adopted to examine the association between sunlight exposure and mental health.

Results

The average K10 score of ORNs was 25.41. ORNs exhibit poorer mental health than other populations. Poor mental health was negatively associated with greater sunlight exposure hours per day (β=-0.378) and sleep regularity (β=-3.341). Poor mental health was positively associated with chronic disease (β=3.514).

Conclusion

This study indicated that the positive association between sunlight exposure and mental health existed. Appropriate enhancement of sunlight exposure will be beneficial to mental health. Hospitals, related organizations and individuals should pay greater attention to ORNs' mental health and sunlight exposure conditions. More policy recommendations as well as building structure recommendations should be proposed.

Joint associations and pathways from greenspace, traffic-related air pollution, and noise to poor self-rated general health: A population-based study in Sofia, Bulgaria

BACKGROUND

Little is still known of how multiple urban exposures interact as health determinants. This study investigated various ways in which greenspace, traffic-related air pollution, and noise could operate together, influencing general health status.

METHODS

In 2022, a cross-sectional population-based survey was conducted in Sofia, Bulgaria. Included were 917 long-term adult residents who completed questionnaires on poor self-rated health (PSRH), total time spent in physical activity (PA), home garden presence, time spent in urban greenspace and nature, and sociodemographics. Residential greenspace was operationalized using the normalized difference vegetation index (NDVI), tree cover density, number of trees, and access to local greenspace and parks. Nitrogen dioxide (NO₂) was modeled for the study area. Road traffic, railway, and aircraft day-evening-night sound levels (L_den) were extracted from EU noise maps. Area-level income and urbanicity were considered. Analyses included multivariate ordinal regressions, interactions, and structural equation modeling (SEM).

RESULTS

Associations with PSRH were per 0.10 NDVI _300 m: OR = 0.65 (0.42-1.01), home garden: OR = 0.72 (0.49-1.07), per 5 μg/m³ NO₂: OR = 1.57 (1.00-2.48), per 5 dB(A) L_den road traffic: OR = 1.06 (0.91-1.23), railway: OR = 1.11 (1.03-1.20), and aircraft: OR = 1.22 (1.11-1.34). Spending >30 min/week in nature related to better health. In multi-exposure models, only associations with aircraft and railway L_den persisted. People with lower education and financial difficulties or living in poorer districts experienced some exposures stronger. In SEM, time spent in nature and PA mediated the effect of greenspace.

CONCLUSIONS

Greenspace was associated with better general health, with time spent in nature and PA emerging as intermediate pathways. NO₂, railway, and aircraft noise were associated with poorer general health. These results could inform decision-makers, urban planners, and civil society organizations facing urban development problems. Mitigation and abatement policies and measures should target socioeconomically disadvantaged citizens.

Long-term exposure to elemental components of fine particulate matter and all-natural and cause-specific mortality in a Danish nationwide administrative cohort study

BACKGROUND

Fine particulate matter (PM_2.5) is a well-recognized risk factor for premature death. However, evidence on which PM_2.5 components are most relevant is unclear.

METHODS

We evaluated the associations between mortality and long-term exposure to eight PM_2.5 elemental components [copper (Cu), iron (Fe), zinc (Zn), sulfur (S), nickel (Ni), vanadium (V), silicon (Si), and potassium (K)]. Studied outcomes included death from diabetes, chronic kidney disease (CKD), dementia, and psychiatric disorders as well as all-natural causes, cardiovascular disease (CVD), respiratory diseases (RD), and lung cancer. We followed all residents in Denmark (aged ≥30 years) from January 1, 2000 to December 31, 2017. We used European-wide land-use regression models at a 100 × 100 m scale to estimate the residential annual mean levels of exposure to PM_2.5 components. The models were developed with supervised linear regression (SLR) and random forest (RF). The associations were evaluated by Cox proportional hazard models adjusting for individual- and area-level socioeconomic factors and total PM_2.5 mass.

RESULTS

Of 3,081,244 individuals, we observed 803,373 death from natural causes during follow-up. We found significant positive associations between all-natural mortality with Si and K from both exposure modeling approaches (hazard ratios; 95% confidence intervals per interquartile range increase): SLR-Si (1.04; 1.03-1.05), RF-Si (1.01; 1.00-1.02), SLR-K (1.03; 1.02-1.04), and RF-K (1.06; 1.05-1.07). Strong associations of K and Si were detected with most causes of mortality except CKD and K, and diabetes and Si (the strongest associations for psychiatric disorders mortality). In addition, Fe was relevant for mortality from RD, lung cancer, CKD, and psychiatric disorders; Zn with mortality from CKD, RD, and lung cancer, and; Ni and V with lung cancer mortality.

CONCLUSIONS

We present novel results of the relevance of different PM_2.5 components for different causes of death, with K and Si seeming to be most consistently associated with mortality in Denmark.

Sunshine duration and risks of schizophrenia hospitalizations in main urban area: Do built environments modify the association?

BACKGROUND

Although studies have explored the relationship between sunshine duration and schizophrenia, the evidence was ambiguous. Different built environments may alter the effect of sunlight on schizophrenia, thus the purpose of this study was to investigate the effects of built environments on the sunshine duration-schizophrenia association.

MATERIALS AND METHODS

Daily schizophrenia hospitalizations data during 2017-2020 in Hefei's main urban area, China, and corresponding meteorological factors as well as ambient pollutants were collected. The impact of sunshine duration on schizophrenia admissions in urban areas was investigated using a generalized additive model combined with a distributed lagged nonlinear model. Additionally, the various modifying effects of different Building Density, Building Height, Normalized Vegetation Index, and Nighttime Light were also explored between sunshine duration and schizophrenia.

RESULTS

We observed that inadequate sunshine duration (<5.3 h) was associated with an increase in schizophrenia hospital admissions, with a maximum relative risk of 1.382 (95 % confidence interval (CI): 1.069-1.786) at 2.9 h. In turn, adequate sunshine duration reduced the risk of schizophrenia hospitalizations. Subgroup analyses indicated females and old patients were particularly vulnerable. In the case of insufficient sunshine duration, significant positive effects were noticed on schizophrenia risk at High-Building Density and High-Nighttime Light. Higher NDVI as well as Building Height were found to be associated with lower risks of schizophrenia.

CONCLUSIONS

Given that sunshine duration in various built environments might lead to distinct effects on schizophrenia hospitalizations. Our findings assist in identifying vulnerable populations that reside in particular areas, thus suggesting policymakers provide advice to mitigate the onset of schizophrenia by allocating healthcare resources rationally and avoiding adverse exposures to vulnerable populations timely.

The prevalence of depression and suicidal ideation among cancer patients in mainland China and its provinces, 1994-2021: A systematic review and meta-analysis of 201 cross-sectional studies

To evaluate the national prevalence depression of Chinese cancer patients and clarify its potential associated factors. Twelve databases were searched from database inception through October 31, 2022 for relevant studies published in English (PubMed MEDLINE, Ovid MEDLINE, Embase, Scopus, PsycINFO, and Cochrane and Web of Science) and Chinese (China National Knowledge Infrastructure, Wanfang, Weipu, Chinese Biomedical Literature Service System, Duxiu) that estimated point or period prevalence of depression, depressive disorder, or suicidal ideation as assessed by self-report scale or structured interview. 201 studies were eligible for inclusion in our meta-analyses. We found the national pooled prevalence rates of depression and suicidal ideation were 44.63 % (95 % CI 42.24 %-47.01 %) and 24.95 % (95 % CI 10.96 %-38.95 %), respectively. The pooled prevalence of depression was associated with study location, cancer type, comorbid chronic disease, and female sex (all P < 0.05). The distribution of the depression prevalence among cancer patients in mainland China was characterized by significant geographical variation and clustering. The highest pooled prevalence of depression was among gynecologic oncology patients. We recommend that more attention and resources be given to mental health problems such as depression and suicidal ideation among Chinese cancer patients, and that prevention programs be developed, especially in areas with a high prevalence of depression.

Air pollution, climate conditions and risk of hospital admissions for psychotic disorders in U.S. residents

BACKGROUND

The physical environmental risk factors for psychotic disorders are poorly understood. This study aimed to examine the associations between exposure to ambient air pollution, climate measures and risk of hospitalization for psychotic disorders and uncover potential disparities by demographic, community factors.

METHODS

Using Health Cost and Utilization Project (HCUP) State Inpatient Databases (SIDs), we applied zero-inflated negative binomial regression to obtain relative risks of hospitalization due to psychotic disorders associated with increases in residential exposure to ambient air pollution (fine particulate matter, PM_2.5; nitrogen dioxide, NO₂), temperature and cumulative precipitation. The analysis covered all-age residents in eight U.S. states over the period of 2002-2016. We additionally investigated modification by age, sex and area-level poverty, percent of blacks and Hispanics.

RESULTS

Over the study period and among the covered areas, we identified 1,211,100 admissions due to psychotic disorders. For each interquartile (IQR) increase in exposure to PM_2.5 and NO₂, we observed a relative risk (RR) of 1.11 (95% confidence interval (CI) = 1.09, 1.13) and 1.27 (95% CI = 1.24, 1.31), respectively. For each 1 °C increase of temperature, the RR was 1.03 (95% CI = 1.03, 1.04). Males were more affected by NO₂. Older age residents (≥30 yrs) were more sensitive to PM_2.5 and temperature. Population living in economically disadvantaged areas were more affected by air pollution.

CONCLUSIONS

The study suggests that living in areas with higher levels of air pollutants and ambient temperature could contribute to additional risk of inpatient care for individuals with psychotic disorders.

The temporality of geographic contexts: Individual environmental exposure has time-related effects on mood

Research on environmental exposure and its impacts on people's mood has attracted increasing attention. Most studies focus on the spatiality of geographic contexts, but they neglect the influence of temporality in the relationships between environments and mood. To this end, a survey was conducted in January 2019 in Guangzhou, China, and measured data (micro-environments, built environments, EMA records, GPS trajectories, and activity logs) covering a weekday were collected from 125 participants. Then, multiple linear regression models are employed to examine and compare the associations between environments and mood based on three possible types of temporal responses (cumulative response, momentary response, and time-lagged response). The results indicate that there are great differences in environmental mood effects based on different types of temporal responses. Specifically, (i) for three types of temporal responses, exposure to PM_2.5 and noise have mood-blunting effects, whereas exposure to green spaces has mood-augmenting effects. (ii) For two types of temporal responses, higher temperature (in winter) may positively influence individual mood based on cumulative and time-lagged response, and higher POI density can positively affect mood based on cumulative and momentary response. (iii) Relative humidity may not have time-related effects on mood. Although all three types of temporal responses are observed in this study, the most significant manifestation is momentary response. These findings not only enrich theoretical research on environmental mood effects and temporality, but also inform the practice of more refined and humanistic urban planning, environmental governance, and public services.

Effects of sunshine duration on daily outpatient visits for depression in Suzhou, Anhui Province, China

Previous epidemiological studies have reported seasonal variation patterns of depression symptoms, which may be influenced by bad weather conditions, such as a lack of sunlight. However, evidence on the acute effects of sunshine duration on outpatient visits for depression is limited, especially in developing countries, and the results are inconsistent. We collected daily outpatient visits for depression from the local mental health centre in Suzhou, Anhui Province, China, during 2017-2019. We defined the 5th and 95th sunshine percentiles as short and long sunshine durations, respectively. A quasi-Poisson generalized linear regression model combined with a distributed lag nonlinear model was used to quantitatively assess the effects of short and long sunshine durations on outpatient visits for depression. Stratified analyses were further performed by gender, age and number of visits to identify vulnerable populations. A total of 26,343 depression cases were collected during the study period. An approximate U-shaped exposure-response association was observed between sunshine duration and depression outpatient visits. The cumulative estimated relative risks (RRs) for short and long sunshine durations at lag 0-21 days were 1.53 [95% confidence intervals (CI): 1.14, 2.06] and 1.13 (95% CI: 0.88, 1.44), respectively. Moreover, a short sunshine duration was associated with a greater disease burden than a long sunshine duration, with attributable fractions (AFs) of 16.64% (95% CI: 7.8%, 23.89%) and 2.24% (95% CI: -2.65%, 5.74%), respectively. Subgroup analysis showed that males, people aged less than 45 years and first-visit cases may be more susceptible to a lack of sunlight. For a long sunshine duration, no statistically significant associations were found in any population groups. Our study found that a short sunshine duration was associated with an increased risk of depression. The government, medical institutions, family members and patients themselves should fully recognize the important role of sunlight and take active measures to prevent depression.

The mental health and well-being effects of wildfire smoke: a scoping review

BACKGROUND

Smoke from wildfires is a growing public health risk due to the enormous amount of smoke-related pollution that is produced and can travel thousands of kilometers from its source. While many studies have documented the physical health harms of wildfire smoke, less is known about the effects on mental health and well-being. Understanding the effects of wildfire smoke on mental health and well-being is crucial as the world enters a time in which wildfire smoke events become more frequent and severe. We conducted a scoping review of the existing information on wildfire smoke's impact on mental health and well-being and developed a model for understanding the pathways in which wildfire smoke may contribute to mental health distress.

METHODS

We conducted searches using PubMed, Medline, Embase, Google, Scopus, and ProQuest for 1990-2022. These searches yielded 200 articles. Sixteen publications met inclusion criteria following screening and eligibility assessment. Three more publications from the bibliographies of these articles were included for a total of 19 publications.

RESULTS

Our review suggests that exposure to wildfire smoke may have mental health impacts, particularly in episodes of chronic and persistent smoke events, but the evidence is inconsistent and limited. Qualitative studies disclose a wider range of impacts across multiple mental health and well-being domains. The potential pathways connecting wildfire smoke with mental health and well-being operate at multiple interacting levels including individual, social and community networks, living and working conditions, and ecological levels.

CONCLUSIONS

Priorities for future research include: 1) applying more rigorous methods; 2) differentiating between mental illness and emotional well-being; 3) studying chronic, persistent or repeated smoke events; 4) identifying the contextual factors that set the stage for mental health and well-being effects, and 5) identifying the causal processes that link wildfire smoke to mental health and well-being effects. The pathways model can serve as a basis for further research and knowledge synthesis on this topic. Also, it helps public health, community mental health, and emergency management practitioners mitigate the mental health and well-being harms of wildfire smoke.

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.

Fine particle components and risk of psychiatric hospitalization in the U.S

BACKGROUND

There is a lack of evidence for the associations between atmospheric particle components exposure and psychiatric health. We aimed to identify the most toxic particle component(s) and source(s) related with psychiatric illness.

METHODS

Using Health Cost and Utilization Project (HCUP) State Inpatient Databases (SIDs), we analyzed the relative risk (RR) of psychiatric hospitalization associated with increased residential exposure to 14 particle components (Zn, V, Si, Pb, Ni, K, Fe, Cu, Ca, Br, sulfate (SO42-), nitrate (NO3-), organic carbon (OC), and elemental carbon (EC)). We covered the residents of eight U.S. states, who contributed to 5,012,041 psychiatric admissions over 2002-2018. Single component models were conducted via fitting zero-inflated negative binomial regression for each component with aggregated counts of total psychiatric hospitalizations per ZIP code per year as dependent variable. We used Nonnegative Matrix Factorization (NMF) to identify particle source factors and obtained the source-specific estimates. Generalized Weighted Quantile Sum (gWQS) Regression was applied to obtain an overall mixture effect. Separate but similar models were fitted for different age groups (<30 yrs. vs. ≥ 30 yrs) and psychiatric illness sub-categories to assess effect heterogeneity.

RESULTS

Sulfate, Fe, Pb and Zn were associated with the largest risk increases in single-component models. The biggest harmful associations were observed for metal industry source (high loadings of Pb and sulfate). For one quartile increase in components mixture score, we observed an adjusted RR of 1.24 (95 % CI, 1.21-1.26). Older population were more affected. We also observed higher increase in bipolar and psychotic admission risk for increased components source and mixture level.

CONCLUSION

Living in areas with higher levels of particle components was associated with increased risk of psychiatric hospitalization among the residents in eight U.S. states. Certain components (i.e. Pb, sulfate) and sources (metal industry) were the most related.

Ecological Sustainability and Households' Wellbeing: Linking Households' Non-Traditional Fuel Choices with Reduced Depression in Rural China

A sustainable and pleasant environment is deemed to offer various positive externalities such as scenic, visual and behavioral archetypes and patterns exhibiting in various forms. Such a scenario can significantly relieve households from many psychological and personal complications such as depression. Depression has aroused great concerns in recent years due to its personal and social burdens and unforeseeable damage. Many studies have explored the effects of air pollution caused by traditional fuel consumption on depression. However, limited evidence is available on how household non-traditional fuel choices affect depression. Based on a nationally representative dataset collected from China Family Panel Studies (CFPS) in 2012, this paper employs an endogenous switching regression (ESR) model and an endogenous switching probit (ESP) model to address the endogenous issue and to estimate the treatment effects of non-traditional fuel choices on depression in rural China. The empirical results show that non-traditional fuel users have significantly lower Epidemiologic Studies Depression Scale (CES-D) scores, indicating non-traditional fuel users face a lower risk of depression. Compared to solid fuels, employing non-traditional fuels will lead to a 3.659 reduction in depression score or decrease the probability of depression by 8.2%. In addition, the results of the mechanism analysis show that household non-traditional fuel choices affect depression by reducing the probability of physical discomfort and chronic disease. This study provides new insight into understanding the impact of air pollution in the house on depression and how to avoid the risk of depression in rural China effectively.

Assessing myocardial infarction severity from the urban environment perspective in Wuhan, China

Health inequalities are globally widespread due to the regional socioeconomic inequalities. Myocardial infarction (MI) is a leading health problem causing deaths worldwide. Yet medical services for it are often inequitably distributed by region. Moreover, studies concerning MI's potential spatial risk factors generally suffer from difficulties in focusing on too few factors, inappropriate models, and coarse spatial grain of data. To address these issues, this paper integrates registered 1098 MI cases and urban multi-source spatio-temporal big data, and spatially analyses the risk factors for MI severity by applying an advanced interpretable model, the random forest algorithm (RFA)-based SHapley Additive exPlanations (SHAP) model. In addition, a community-scale model between spatio-temporal risk factors and MI cases is constructed to predict the MI severity of all communities in Wuhan, China. The results suggest that those risk factors (i.e., age of patients, medical quality, temperature changes, air pollution and urban habitat) affect the MI severity at the community scale. We found that Wuhan residents in the downtown area are at risk for high MI severity, and the surrounding suburb areas show a donut-shape pattern of risk for medium-to-high MI severity. These patterns draw our attention to the impact of spatial environmental risk factors on MI severity. Thus, this paper provides three recommendations for urban planning to reduce the risk and mortality from severe MI in the aspect of policy implication.

Long-term exposure to air pollution and mortality in a Danish nationwide administrative cohort study: Beyond mortality from cardiopulmonary disease and lung cancer

BACKGROUND

The association between long-term exposure to air pollution and mortality from cardiorespiratory diseases is well established, yet the evidence for other diseases remains limited.

OBJECTIVES

To examine the associations of long-term exposure to air pollution with mortality from diabetes, dementia, psychiatric disorders, chronic kidney disease (CKD), asthma, acute lower respiratory infection (ALRI), as well as mortality from all-natural and cardiorespiratory causes in the Danish nationwide administrative cohort.

METHODS

We followed all residents aged ≥ 30 years (3,083,227) in Denmark from 1 January 2000 until 31 December 2017. Annual mean concentrations of fine particulate matter (PM_2.5), nitrogen dioxide (NO₂), black carbon (BC), and ozone (warm season) were estimated using European-wide hybrid land-use regression models (100 m × 100 m) and assigned to baseline residential addresses. We used Cox proportional hazard models to evaluate the association between air pollution and mortality, accounting for demographic and socioeconomic factors. We additionally applied indirect adjustment for smoking and body mass index (BMI).

RESULTS

During 47,023,454 person-years of follow-up, 803,881 people died from natural causes. Long-term exposure to PM_2.5 (mean: 12.4 µg/m³), NO₂ (20.3 µg/m³), and/or BC (1.0 × 10^-5/m) was statistically significantly associated with all studied mortality outcomes except CKD. A 5 µg/m³ increase in PM_2.5 was associated with higher mortality from all-natural causes (hazard ratio 1.11; 95% confidence interval 1.09-1.13), cardiovascular disease (1.09; 1.07-1.12), respiratory disease (1.11; 1.07-1.15), lung cancer (1.19; 1.15-1.24), diabetes (1.10; 1.04-1.16), dementia (1.05; 1.00-1.10), psychiatric disorders (1.38; 1.27-1.50), asthma (1.13; 0.94-1.36), and ALRI (1.14; 1.09-1.20). Associations with long-term exposure to ozone (mean: 80.2 µg/m³) were generally negative but became significantly positive for several endpoints in two-pollutant models. Generally, associations were attenuated but remained significant after indirect adjustment for smoking and BMI.

CONCLUSION

Long-term exposure to PM_2.5, NO₂, and/or BC in Denmark were associated with mortality beyond cardiorespiratory diseases, including diabetes, dementia, psychiatric disorders, asthma, and ALRI.

Comparison of moderate and vigorous walking exercise on reducing depression in middle-aged and older adults: A pilot randomized controlled trial

The optimal intensity of physical activity for alleviating depression in middle-aged and older adults remains unclear. The comparative effects of moderate and vigorous physical activity on reducing depression have not been directly examined. The World Health Organization (WHO) physical activity guidelines recommend adults and older adults to accumulate at least 150-300 minutes of moderate or 75-150 minutes of vigorous aerobic-type physical activity weekly or an equivalent combination of both for health benefits including reduced risk of depression. This parallel, assessor-blinded, pilot randomized controlled trial preliminarily compared the effectiveness of the minimal volume of aerobic-type physical activity at different intensities as recommended by WHO (150 minutes of moderate walking exercise and 75 minutes of vigorous walking exercise weekly) on alleviating depression in middle-aged and older adults. Middle-aged and older adults diagnosed with depression were randomized to the control group (CON), moderate walking exercise group (MOD), or vigorous walking exercise group (VIG). The exercise frequency of the moderate and vigorous walking exercise were three times a week and the intervention duration were 12 weeks. The primary outcome was the severity of depression assessed by Beck Depression Inventory. Secondary outcomes included severity of anxiety, sleep quality, quality of life, and cardiorespiratory fitness. Thirty participants completed the study (CON: n = 10, MOD: n = 10, VIG: n = 10). Participants in both MOD and VIG had significantly decreased depression severity after the intervention compared to CON (both p < 0.001). There was no significant difference between MOD and VIG (p = 0.92). Both MOD and VIG interventions also mitigated anxiety severity, improved quality of life and cardiorespiratory fitness. The minimum volume of walking exercise at either moderate or vigorous intensity was found to alleviate depression in middle-aged and older adults.Trial registration: ClinicalTrials.gov identifier: NCT04403373..

Air pollution in association with mental and self-rated health and the mediating effect of physical activity

BACKGROUND

Recent studies showed that air pollution might play a role in the etiology of mental disorders. In this study we evaluated the association between air pollution and mental and self-rated health and the possible mediating effect of physical activity in this association.

METHODS

In 2008, 2013 and 2018 the Belgian Health Interview Survey (BHIS) enrolled 16,455 participants who completed following mental health dimensions: psychological distress, suboptimal vitality, suicidal ideation, and depressive and generalized anxiety disorder and self-rated health. Annual exposure to nitrogen dioxide (NO₂), particulate matter ≤ 2.5 µm (PM_2.5) and black carbon (BC) were estimated at the participants' residence by a high resolution spatiotemporal model. Multivariate logistic regressions were carried out taking into account a priori selected covariates.

RESULTS

Long-term exposure to PM_2.5, BC and NO₂ averaged 14.5, 1.4, and 21.8 µg/m³, respectively. An interquartile range (IQR) increment in PM_2.5 exposure was associated with higher odds of suboptimal vitality (OR = 1.27; 95% CI: 1.13, 1.42), poor self-rated health (OR = 1.20; 95% CI: 1.09, 1.32) and depressive disorder (OR = 1.19; 95% CI: 1.00, 1.41). Secondly, an association was found between BC exposure and higher odds of poor self-rated health and depressive and generalized anxiety disorder and between NO₂ exposure and higher odds of psychological distress, suboptimal vitality and poor self-rated health. No association was found between long-term ambient air pollution and suicidal ideation or severe psychological distress. The mediation analysis suggested that between 15.2% (PM_2.5-generalized anxiety disorder) and 40.1% (NO₂-poor self-rated health) of the association may be mediated by a difference in physical activity.

CONCLUSIONS

Long-term exposure to PM_2.5, BC or NO₂ was adversely associated with multiple mental health dimensions and self-rated health and part of the association was mediated by physical activity. Our results suggest that policies aiming to reduce air pollution levels could also reduce the burden of mental health disorders in Belgium.

Influence of External Natural Environment Including Sunshine Exposure on Public Mental Health: A Systematic Review

The COVID-19 pandemic has been raging around the world and public health measures such as lockdowns have forced people to go out less often, reducing sunlight exposure time, green space use, and physical activity. It is well known that exercise has a positive impact on mental health, but the impact of external environmental factors such as sunlight exposure and green space use on mental health has not been systematically reviewed. In this review, we categorized the major factors that may affect people’s mental health into (1) external environmental factors such as exposure to sunlight and green spaces, (2) internal life factors such as physical activity and lifestyle, and (3) mixed external and internal factors, and systematically examined the relationship between each factor and people’s mental health. The results showed that exposure to sunlight, spending leisure time in green spaces, and physical activity each had a positive impact on people’s mental health, including depression, anxiety, and stress states. Specifically, moderate physical activity in an external environment with sunlight exposure or green space was found to be an important factor. The study found that exposure to the natural environment through sunbathing and exercise is important for people’s mental health.

Long-term exposure to ambient air pollution and incidence of depression: A population-based cohort study in China

BACKGROUND

Long-term exposure to ambient air pollution was linked to depression incidence, although the results were limited and inconsistent.

OBJECTIVES

To investigate the effects of long-term air pollution exposure on depression risk prospectively in China.

METHODS

The present study used data from Yinzhou Cohort on adults without depression at baseline, and followed up until April 2020. Two-year moving average concentrations of particulate matter with a diameter ≤ 2.5 μm (PM_2.5), ≤10 μm (PM₁₀) and nitrogen dioxide (NO₂) were measured using land-use regression (LUR) models for each participant. Depression cases were ascertained using the Health Information System (HIS) of the local health administration by linking the unique identifiers. We conducted Cox regression models with time-varying exposures to estimate the hazard ratios (HRs) and 95% confidence intervals (95% CIs) of depression with each pollutant, after adjusting for a sequence of individual covariates as demographic characteristics, lifestyles, and comorbidity. Besides, physical activity, baseline potential depressive symptoms, cancer status, COVID-19 pandemic, different outcome definitions and air pollution exposure windows were considered in sensitivity analyses.

RESULTS

Among the 30,712 adults with a mean age of 62.22 ± 11.25, 1024 incident depression cases were identified over totaling 98,619 person-years of observation. Interquartile range increments of the air pollutants were associated with increased risks of depression, and the corresponding HRs were 1.59 (95%CI: 1.46, 1.72) for PM_2.5, 1.49 (95%CI: 1.35, 1.64) for PM₁₀ and 1.58 (95%CI: 1.42, 1.77) for NO₂. Subgroup analyses suggested that participants without taking any protective measures towards air pollution were more susceptible. The results remained robust in all sensitivity analyses.

CONCLUSIONS

Long-term exposure to ambient air pollution was identified as a risk factor for depression onset. Strategies to reduce air pollution are necessary to decrease the disease burden of depression.

Biological, Psychological, and Social Determinants of Depression: A Review of Recent Literature

Depression is one of the leading causes of disability, and, if left unmanaged, it can increase the risk for suicide. The evidence base on the determinants of depression is fragmented, which makes the interpretation of the results across studies difficult. The objective of this study is to conduct a thorough synthesis of the literature assessing the biological, psychological, and social determinants of depression in order to piece together the puzzle of the key factors that are related to this condition. Titles and abstracts published between 2017 and 2020 were identified in PubMed, as well as Medline, Scopus, and PsycInfo. Key words relating to biological, social, and psychological determinants as well as depression were applied to the databases, and the screening and data charting of the documents took place. We included 470 documents in this literature review. The findings showed that there are a plethora of risk and protective factors (relating to biological, psychological, and social determinants) that are related to depression; these determinants are interlinked and influence depression outcomes through a web of causation. In this paper, we describe and present the vast, fragmented, and complex literature related to this topic. This review may be used to guide practice, public health efforts, policy, and research related to mental health and, specifically, depression.

Air Pollution and Adolescent Development: Evidence from a 3-Year Longitudinal Study in China

This study aimed to investigate the impact of air pollution on the development of adolescents and the mediating role of students’ emotional disorders. Participants came from a longitudinal sample group of adolescents (n = 1301) in Southern China from the years 2016 to 2018. They were assessed for the Positive Youth Development and emotional disorders, and air pollution was measured by the Air Quality Index. The results show that students’ higher degree of exposure to air pollution was negatively associated with their positive development. Three out of four emotional disorders (i.e., anxiety, neuroticism, and withdrawal) mediate this association. The results suggest that the physical environment can have a paramount influence on the emotional status and overall development of adolescents, calling for intervention programs by policymakers.

Ambient air pollution and movement behaviours: A scoping review

This scoping review summarizes the literature about how ambient (outdoor) air pollution impacts movement behaviours (i.e., physical activity, sedentary behaviour, and sleep), or beliefs about movement behaviours. Of 6552 potential documents, 58 documents and 218 findings were included in the final synthesis. Most studies were from the United States and China, involved cross-sectional designs, and included mixed age groups. Overall, unfavourable changes/associations (i.e., decreased/lower physical activity, increased/higher sedentary-related behaviour, and decreased/lower sleep duration and quality) or no change/association in movement behaviours in relation to ambient air pollution were identified. Our findings suggest that more attention should be given to understanding the impact of ambient air pollution on movement behaviours in general and in diverse countries and vulnerable populations such as children or older adults.

PM2.5 Pollutant Concentrations in Greenspaces of Nanjing Are High but Can Be Lowered with Environmental Planning

Small-scale greenspaces in high-density central urban districts serve as important outdoor activity spaces for the surrounding residents, especially the elderly. This study selects six small-scale, popular greenspaces with distinct characteristics that are jointly situated along the same main urban artery in a high-density central urban district. Field investigations and questionnaires are conducted and combined with statistical analyses, to explore the spatial-temporal distribution and influencing factors of PM2.5 concentrations in these greenspaces. The study finds that the air quality conditions in the sites are non-ideal, and this has potential negative impacts on the health of the elderly visitors. Moreover, the difference values of PM2.5 concentrations' spatial-temporal distributions are significantly affected by vehicle-related emissions, which have significant temporal characteristics. PM2.5 concentration is strongly correlated with percentage of green coverage (R = 0.82, p < 0.05), degree of airflow (R = -0.83, p < 0.05), humidity and comfort level (R = 0.54, p < 0.01 and R = -0.40, p < 0.01 respectively). Meanwhile, the sites' "sky view factor" is strongly correlated with degree of airflow (R = 0.82, p < 0.05), and the comfort level plays an indirect role in the process of PM2.5 affecting crowd activities. Based on this analysis, an optimal set of index ranges for greenspace elements which are correlated with the best reduction in PM2.5 concentrations is derived. As such, this research reveals the technical methods to best reduce their concentrations and provides a basis and reference for improving the quality of small-scale greenspaces in high-density urban districts for the benefit of healthy aging.

Effects of short- and long-term exposure to air pollution and meteorological factors on Meniere's disease

The association between air pollutants and Meniere’s disease has not been explored. The present study investigated the relationship between meteorological factors and air pollutants on Meniere’s disease. Participants, aged ≥ 40 years, of the Korean National Health Insurance Service-Health Screening Cohort were included in this study. The 7725 patients with Meniere’s disease were matched with 30,900 control participants. The moving average meteorological and air pollution data of the previous 7 days, 1 month, 3 months, and 6 months before the onset of Meniere’s disease were compared between the Meniere’s disease and control groups using conditional logistic regression analyses. Additional analyses were conducted according to age, sex, income, and residential area. Temperature range; ambient atmospheric pressure; sunshine duration; and levels of SO₂, NO₂, O₃, CO, and PM₁₀ for 1 month and 6 months were associated with Meniere’s disease. Adjusted ORs (odds ratios with 95% confidence interval [CI]) for 1 and 6 months of O₃ concentration were 1.29 (95% CI 1.23–1.35) and 1.31 (95% CI 1.22–1.42), respectively; that for the 1 and 6 months of CO concentration were 3.34 (95% CI 2.39–4.68) and 4.19 (95% CI 2.79–6.30), respectively. Subgroup analyses indicated a steady relationship of O₃ and CO concentrations with Meniere’s disease. Meteorological factors and air pollutants were associated with the rate of Meniere’s disease. In particular, CO and O₃ concentrations were positively related to the occurrence of Meniere’s disease.

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

BACKGROUND

Migrants experience substantial changes in their neighborhood physical and social environments along their migration journeys, but little is known about how perceived changes in their neighborhood environment pre- and post-migration correlate with their mental health. Our aim was to examine the associations between recalled changes in the perceived neighborhood physical and social environments and migrants' mental health in the host city.

METHODS

We used cross-sectional data on 591 migrants in Shenzhen, China. We assessed their risk of mental illness using the General Health Questionnaire (GHQ). Neighborhood perceptions were collected retrospectively pre- and post-migration. We used random forests to analyze possibly non-linear associations between GHQ scores and changes in the neighborhood environment, variable importance, and for exploratory analysis of variable interactions.

RESULTS

Perceived changes in neighborhood aesthetics, safety, and green space were non-linearly associated with migrants' mental health: A decline in these characteristics was associated with poor mental health, while improvements in them were unrelated to mental health benefits. Variable importance showed that change in safety was the most influential neighborhood characteristic, although individual-level characteristics-such as self-reported physical health, personal income, and hukou (i.e., the Chinese household registration system)-appeared to be more important to explain GHQ scores and also strongly interacted with other variables. For physical health, we found different associations between changes in the neighborhood provoked by migration and mental health.

CONCLUSION

Our findings suggest that perceived degradations in the physical environment are related to poorer post-migration mental health. In addition, it seems that perceived changes in the neighborhood environment play a minor role compared to individual-level characteristics, in particular migrants' physical health condition. Replication of our findings in longitudinal settings is needed to exclude reverse causality.

Which Risk Factors Matter More for Psychological Distress during the COVID-19 Pandemic? An Application Approach of Gradient Boosting Decision Trees

BACKGROUND

A growing body of scientific literature indicates that risk factors for COVID-19 contribute to a high level of psychological distress. However, there is no consensus on which factors contribute more to predicting psychological health.

OBJECTIVES

The present study quantifies the importance of related risk factors on the level of psychological distress and further explores the threshold effect of each rick factor on the level of psychological distress. Both subjective and objective measures of risk factors are considered in the model.

METHODS

We sampled 937 individual items of data obtained from an online questionnaire between 20 January and 13 February 2020 in China. Objective risk factors were measured in terms of direct distance from respondents' housing to the nearest COVID-19 hospital, direct distance from respondents' housing to the nearest park, and the air quality index (AQI). Perceived risk factors were measured in regard to perceived distance to the nearest COVID-19 hospital, perceived air quality, and perceived environmental quality. Psychological distress was measured with the Kessler psychological distress scale K6 score. The following health risk factors and sociodemographic factors were considered: self-rated health level, physical health status, physical activity, current smoker or drinker, age, gender, marital status, educational attainment level, residence location, and household income level. A gradient boosting decision tree (GBDT) was used to analyse the data.

RESULTS

Health risk factors were the greatest contributors to predicting the level of psychological distress, with a relative importance of 42.32% among all influential factors. Objective risk factors had a stronger predictive power than perceived risk factors (23.49% vs. 16.26%). Furthermore, it was found that there was a dramatic rise in the moderate level of psychological distress regarding the threshold of AQI between 40 and 50, and 110 and 130, respectively. Gender-sensitive analysis revealed that women and men responded differently to psychological distress based on different risk factors.

CONCLUSION

We found evidence that perceived indoor air quality played a more important role in predicting psychological distress compared to ambient air pollution during the COVID-19 pandemic.

Clinical Ecopsychology: The Mental Health Impacts and Underlying Pathways of the Climate and Environmental Crisis

Humankind is confronted with progressing climate change, pollution, environmental degradation, and/or destruction of the air, soil, water, and ecosystems. The climate and environmental crisis is probably one of the greatest challenges in the history of humankind. It not only poses a serious current and continuing threat to physical health, but is also an existing and growing hazard to the mental health of millions of people worldwide. This synergy of literature provides a current summary of the adverse mental health impacts of the climate and environmental crisis from the perspective of Clinical Psychology. Furthermore, it presents potential underlying processes, including biological, emotional, cognitive, behavioral, and social pathways. The existing data suggest that the climate and environmental crisis not only acts as a direct stressor, but can also exert a detrimental impact on the various pathways, with the potential to amplify an individual's biopsychosocial vulnerability to develop mental ill-health. This is a call for an increased investigation into this emerging research field of Clinical Ecopsychology by clinical psychologists and other researchers.

Short- and long-term exposure to air pollution and lack of sunlight are associated with an increased risk of depression: A nested case-control study using meteorological data and national sample cohort data

Previous studies have suggested an increased risk of depression related to air pollutants. This study investigated the relationship of air pollutant exposure and meteorological factors with depression. The Korean National Health Insurance Service-Health Screening Cohort from 2002 to 2013 was analyzed. In total, 25,589 depression participants were 1:4 matched with 102,356 control participants for age, sex, income, and region of residence. Depression was defined based on a diagnosis (ICD-10: F31-33) by a psychiatric physician. Meteorological factors and air pollutants including sulfur dioxide (SO₂) (ppm), nitrogen dioxide (NO₂) (ppm), ozone (O₃) (ppm), carbon monoxide (CO) (ppm), and particulate matter with an aerodynamic diameter <10 μm (PM₁₀) (μg/m³) during the 30 days and 365 days before the index date were analyzed for associations with depression using conditional logistic regression. Subgroup analyses were performed according to age, sex, income, and region of residence. The odds ratios (ORs) for depression were 1.05 (95% CI = 1.02-1.08) at 365 days for 1 h less of sunshine. The ORs for depression were 1.02 (95% CI = 1.01-1.03) and 1.03 (95% CI = 1.00-1.05) at 30 days and 365 days for PM₁₀ (10 μg/m³), respectively. The ORs for depression were 1.18 (95% CI = 1.04-1.35) and 1.25 (95% CI = 1.07-1.47) at 30 days and 365 days for CO (ppm), respectively. In the subgroup analyses, the overall results were consistent. However, statistical significance diminished in the younger, high-income, and urban resident subgroups. Both short- and long-term exposure to PM₁₀ and CO and a reduced duration of sunshine were related to an increased risk of depression.

"Shedding Light on Light": A Review on the Effects on Mental Health of Exposure to Optical Radiation

In relation to human health and functioning, light, or more specifically optical radiation, plays many roles, beyond allowing vision. These may be summarized as: regulation of circadian rhythms; consequences of direct exposure to the skin; and more indirect effects on well-being and functioning, also related to lifestyle and contact with natural and urban environments. Impact on mental health is relevant for any of these specifications and supports a clinical use of this knowledge for the treatment of psychiatric conditions, such as depression or anxiety, somatic symptom disorder, and others, with reference to light therapy in particular. The scope of this narrative review is to provide a summary of recent findings and evidence on the regulating functions of light on human beings’ biology, with a specific focus on mental health, its prevention and care.

Particulate matter pollution and risk of outpatient visits for psychological diseases in Nanjing, China

Exposure to air pollution has been associated with increased risk for a range of adverse mental health conditions. Less is known about whether air pollution is also associated with increases in the utilization of mental health services, especially outpatient mental health service utilization. This study aimed to examine the association between the number of daily outpatient visits at the psychological disease departments of two major hospitals (PSYC) and daily average concentrations of PM_2.5 and PM₁₀ in a heavily polluted city in China, Nanjing, from 2013/7/1 to 2019/2/28, using generalized additive models with a quasi-Poisson regression. Results showed that each 10 μg/m³ increase in PM_2.5 concentration on lag0 day was associated with a 0.40% increase (95% CI: 0.07-0.72) in PSYC visits, and each 10 μg/m³ increase in PM₁₀ concentration on the same day a 0.31% increase (95% CI: 0.09-0.54) in PSYC visits. Exposure-response curves suggested linear relationships between PM concentration and daily PSYC outpatient visits, without evidence of a threshold. Associations remained positive, but were non-significant, with adjustment for co-pollutants, SO₂, NO₂ and CO. Significantly larger effects were found for older and male participants, vs. their counterparts. These findings add to the growing literature linking air pollution to mental health service utilization, demonstrating the critical need for both air pollution mitigation measures and increased capacity of the mental health system in China.

Long-term PM2.5 exposure and depressive symptoms in China: A quasi-experimental study

Background

Air pollutants, particularly fine particulate matters (PM_2.5) have been associated with mental disorder such as depression. Clean air policy (CAP, i.e., a series of emission-control actions) has been shown to reduce the public health burden of air pollutions. There were few studies on the health effects of CAP on mental health, particularly, in low-income and middle-income countries (LMICs). We investigated the association between a stringent CAP and depressive symptoms among general adults in China.

Methods

We used three waves (2011, 2013 and 2015) of the China Health and Retirement Longitudinal Study (CHARLS), a prospective nationwide cohort of the middle-aged and older population in China. We assessed exposure to PM_2.5 through a satellite-retrieved dataset. We implemented a difference-in-differences (DID) approach, under the quasi-experimental framework of the temporal contrast between 2011 (before the CAP) and 2015 (after the CAP), to evaluate the effect of CAP on depressive symptoms. The association was further explored using a mixed-effects model of the three waves. To increase the interpretability, the estimated impact of PM_2.5 was compared to that of aging, an established risk factor for depression.

Findings

Our analysis included 15,954 participants. In the DID model, we found a 10-µg/m³ reduction of PM_2.5 concentration was associated with a 4.14% (95% CI: 0.41–8.00%) decrement in the depressive score. The estimate was similar to that from the mixed-effects model (3.63% [95% CI, 2.00–5.27%]). We also found improved air quality during 2011–2015 offset the negative impact from 5-years’ aging.

Interpretation

The findings suggest that implementing CAP may improve mental wellbeing of adults in China and other LMICs.

Association Pathways Between Neighborhood Greenspaces and the Physical and Mental Health of Older Adults-A Cross-Sectional Study in Guangzhou, China

According to the United Nations, the proportion of the older population is increasing at a faster rate than all other age groups. Hence, the well-being of older adults is a mounting concern worldwide in the current century. Using a single greenery metric, previous studies linked greenness to residents' well-being. This study aims to extend this field by focusing on the mental and physical well-being of older adults by using remote sensing and streetscape metrics in evaluating neighborhood greenness. We selected 20 residential neighborhoods in Guangzhou City, China as the cross-sectional case study areas. We investigated neighborhood normalized difference vegetation index (NDVI) collected using remote sensing images, streetscape greenery, and PM2.5 via field surveys. We assessed the health condition of 972 senior residents selected by multi-stage stratified probability proportionate to population size sampling technique (PPS) using a questionnaire survey. We adopted the structural equation model (SEM) in analyzing the pathways that link neighborhood greenness and the mental and physical health of older adults. We found that neighborhood greenness has a positive association with the physical activity by older adults that is positively linked to their physical health. Moreover, neighborhood greenness is positively related to regular social interactions among older adults that is positively linked to their mental health. These findings are consistent with those of previous studies. However, we obtained new results that were unique to China. We found that neighborhood greenness has no significant direct relationship with the physical and mental health of older adults and that social interactions of low-income senior groups are more substantially related to neighborhood greenness than the other groups. Therefore, community planning should emphasize the development of neighborhood greenness, such as parks and street trees, to provide natural spaces for social interactions and places for physical activities among older residents.

Health and economic impacts of particulate matter pollution on hospital admissions for mental disorders in Chengdu, Southwestern China

The evidence for adverse effects of ambient particulate matter (PM) pollution on mental disorders (MDs) is limited, especially in developing countries. This study aimed to quantify both PM related health impacts and corresponding economic loses for overall and specific MDs in southwestern China. Data regarding 134,292 hospital admissions for MDs were collected from local Compulsory Medical Insurance Database in 2013-2017. A generalized additive model (GAM) was applied to estimate the exposure-response effects of PM pollution on hospital admissions for MDs. And the cost of illness method (COI) was adopted to further assess corresponding hospitalization costs and productivity loses. It was showed that PM pollution was significantly related to hospital admissions for overall and specific MDs. Each 10 μg/m³ increase in concentrations of PM₁₀ (particles with an aerodynamic diameters ≤10 μm), PM_2.5 (≤ 2.5 μm) and PMc (2.5 μm < c < 10 μm) at the cumulative lag03 day would be responsible for 3.25% (95%CI: 2.34-4.16%), 6.38% (95%CI: 4.79-7.97%), and 3.81% (95%CI: 2.13-5.50%) increments in daily hospital admissions for MDs, respectively. Stronger associations were observed in males, cool season and people over 45 years. During the study period, PM pollution brought 1453.18 million Yuan economic losses for overall MDs, accounting for 0.026% of local GDP. This study suggested that short-term exposure to PM pollution, especially to PM_2.5, was associated with increased hospital admissions for MDs in southwestern China. In addition, potential benefits of lowering PM concentrations are considerable.

Urban-rural disparity in the relationship between ambient air pollution and preterm birth

BACKGROUND

Some studies have reported that air pollution exposure can have adverse effects on pregnancy outcomes. However, the disparity between urban and rural areas in the risk of preterm birth (PTB) has yet to be elucidated. Considering geographic contexts as homogeneous or ignoring urban-rural differences cannot accurately reveal the disparities in the health effects of air pollution under different geographic contexts. The aims of this study were to examine the disparities in the risks of PTB in three different regions and five urban-rural types and to investigate the extent to which fine particulate matter (PM2.5) exposure during the entire pregnancy can explain the variations.

METHODS

We collected data on 429,865 singleton newborns born in 2014 in Hubei Province, China, and divided Hubei Province into three regions. Spatial correlation methods were employed to measure the associations between the rate of PTB and air pollution using average annual indexes for the entire province and regions. A series of multilevel logistic models were conducted to examine disparities in the risks of PTB with decreases in urbanity and the effects of air pollution exposure on the occurrence of preterm births.

RESULTS

The PM2.5 concentration was significantly different across the regions. The eastern region had the most wide-ranged and serious level of pollution, whereas the levels in the middle and western regions weakened. The odds of PTB and air pollution exhibited a positive spatial correlation for the entire province and in the east (BiMoran's I = 0.106 and 0.697, respectively). Significant urban-rural disparities in the risks of PTB were noted in the east and middle regions, and the mean PM2.5 exposure during the entire pregnancy was positively associated with PTB risk. However, in the west, the results showed weak differences in the risks of PTB among the five urban-rural types and an insignificant effect of PM2.5 exposure. The direction of the effect of district/county-level income on PTB varied by region.

CONCLUSIONS

This study finds that air pollution exposure and PTB have significant and positive spatial relationships in areas with a serious air pollution burden. The risks of PTB in three regions of Hubei Province follow the same W-shaped pattern as urbanity decreases and rurality increases. High levels of air pollution exposure may be an important disadvantage for urban pregnant women in this setting.

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.

Residential greenness, air pollution and psychological well-being among urban residents in Guangzhou, China

China's rapid urbanization has led to an increasing level of exposure to air pollution and a decreasing level of exposure to vegetation among urban populations. Both trends may pose threats to psychological well-being. Previous studies on the interrelationships among greenness, air pollution and psychological well-being rely on exposure measures from remote sensing data, which may fail to accurately capture how people perceive vegetation on the ground. To address this research gap, this study aimed to explore relationships among neighbourhood greenness, air pollution exposure and psychological well-being, using survey data on 1029 adults residing in 35 neighbourhoods in Guangzhou, China. We used the Normalized Difference Vegetation Index (NDVI) and streetscape greenery (SVG) to assess greenery exposure at the neighbourhood level, and we distinguished between trees (SVG-tree) and grasses (SVG-grass) when generating streetscape greenery exposure metrics. We used two objective (PM_2.5 and NO₂ concentrations) measures and one subjective (perceived air pollution) measure to quantify air pollution exposure. We quantified psychological well-being using the World Health Organization Well-Being Index (WHO-5). Results from multilevel structural equation models (SEM) showed that, for parallel mediation models, while the association between SVG-grass and psychological well-being was completely mediated by perceived air pollution and NO₂, the relationship between SVG-tree and psychological well-being was completely mediated by ambient PM_2.5, NO₂ and perceived air pollution. None of three air pollution indicators mediated the association between psychological well-being and NDVI. For serial mediation models, measures of air pollution did not mediate the relationship between NDVI and psychological well-being. While the linkage between SVG-grass and psychological well-being scores was partially mediated by NO₂-perceived air pollution, SVG-tree was partially mediated by both ambient PM_2.5-perceived air pollution and NO₂-perceived air pollution. Our results suggest that street trees may be more related to lower air pollution levels and better mental health than grasses are.

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

BACKGROUND

Emerging evidence suggests that exposure to residential green space is beneficial for people's mental health along multiple pathways. It remains unknown, however, whether the complex pathways found for the general population also apply to internal migrants in China.

AIM

To examine the mediators of green space-mental health associations among migrants in the metropolis of Shenzhen, China.

METHODS

We conducted a cross-sectional survey among 591 migrants aged between 18 and 68 years in January-April 2017 in Shenzhen, a city facing a considerable inflow of rural-urban migration. Migrants' mental health was assessed using the 12-item General Health Questionnaire. Data on migrant's green space perception, migration characteristics, environmental disturbances, social cohesion, physical health, etc. were obtained through a questionnaire. Structural equation modeling was used to analyze the mechanisms underlying the green space-mental health association.

RESULTS

No direct effect of perceived green space on migrants' mental health was found. We did find, however, that perceived green space is significantly and indirectly related to mental health through reducing perceived environmental disturbance and enhancing social cohesion. Migrants' residential mobility presented a significant potential risk to migrants' physical health and might influence their mental health indirectly. A similar but only weakly significant health-threatening effect was found for migration frequency. Male and female respondents showed different patterns regarding their physical and mental health status. Migrants with higher personal incomes seemed to face a lower mental health risk.

CONCLUSIONS

Our findings suggest distinctive pathways through which residential green space could affect the mental health of internal migrants in China. Further studies in rapidly urbanizing areas are advised to evaluate green space-mental health relationships for specific population groups/subgroups with distinctive socioeconomic backgrounds.

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.

Relationship between neighbourhood social participation and depression among older adults: A longitudinal study in China

Previous research has found a negative linkage between neighbourhood social participation and depressive symptoms in Western countries, but the cross-sectional design of these studies limits the ability to infer causality. Little attention has been paid to socio-psychological pathways linking neighbourhood social participation to depressive symptoms among older adults in China. This study aimed to examine the impact of neighbourhood social participation on depressive symptoms among older adults in China. It also further explored the mediating roles of physical activity, social contact among neighbours, and contact with own children in the relationship between social participation and depressive symptoms. Data obtained through three waves (2011, 2013, and 2015) of the China Health and Retirement Longitudinal Study were used. The sample consisted of 10,105 individuals aged 60 and above and 24,623 person-year records captured during these three waves. Depressive symptoms were assessed using the Center for Epidemiology Studies of Depression scale. Results showed that respondents' depression decreased with an increasing level of neighbourhood social participation, more time spent on physical activities, and a higher frequency of contact with neighbours and with own children. These factors were found to partly mediate the relationship between neighbourhood social participation and depression. The negative relationships between social contact and depression and contact with own children and depression were both strengthened by neighbourhood social participation. In conclusion, physical activity, social contact among neighbours and contact with own children are mechanisms through which neighbourhood social participation lowers the risk of depression among older adults in China.

Air pollution and self-perceived stress and mood: A one-year panel study of healthy elderly persons

BACKGROUND AND OBJECTIVES

Previous studies have suggested that air pollution is associated with depression and anxiety symptoms. Here, we investigate the association between personal exposure to NO₂ and perceived stress and mood in a panel of healthy elderly persons.

METHODS

In a one-year panel study, we included 20 healthy volunteers (10 male-female couples aged 58-76 years) with air pollution and health parameters measured every two months (120 observations). We measured personal exposure to NO₂ in the previous 5 days, perceived stress using the Perceived Stress Scale (PSS) and positive and negative affect with the Positive and Negative Affect Schedule (PANAS). We used linear and Poisson mixed models to evaluate the associations between the health outcomes and NO₂ adjusted for age, sex, temperature in the previous 5 days, sunlight in the previous day and physical activity (daily average number of steps on the previous week). Also, the interaction terms between NO₂ and physical activity were tested. We report % changes for PSS scores and unit changes (β) for positive and negative affect, and their 95% confidence intervals (CI), for changes in 10 μg/m³ of NO₂.

RESULTS

After adjustment, an increase by 10 μg/m³ in NO₂ concentrations was associated with a decrease of 1.3 points in the positive affect (95% CI -2.49 to -0.17) and an increase of 0.11 points in the negative affect (95% CI 0.02 to 0.20). The association with positive affect was stronger when physical activity was below median value of 9,362 steps per day (β = -2.68; CI: 4.87 to -0.49); p-value for interaction was 0.08. No statistically significant associations were observed with perceived stress.

CONCLUSION

Short-term exposure to air pollution may produce non-pathological alterations in mood in healthy elderly population.

Identifying the Factors Related to Depressive Symptoms Amongst Community-Dwelling Older Adults with Mild Cognitive Impairment

High-level depressive symptoms have been reported in individuals with mild cognitive impairment (MCI), resulting in increased risk of progression to dementia. However, studies investigating the correlates of depressive symptoms among this population are scarce. This study aimed to investigate the significant socio-demographic, lifestyle-related and disease-related correlates of depressive symptoms among this cohort. Cross-sectional data were obtained from a sample of 154 Chinese community-dwelling older adults with MCI. MCI subjects were screened by the Montreal Cognitive Assessment. Depressive symptoms were measured by the Geriatric Depression Scale. Possible correlates of depressive symptoms in individuals with MCI were explored by multiple linear regressions. The prevalence of depressive symptoms among Chinese older adults with MCI was 31.8%. In multiple regression analysis, poor perceived positive social interaction, small social network, low level of physical activity, poor functional status, subjective memory complaint, and poor health perception were correlated with depressive symptoms. The findings highlight that depressive symptoms are sufficient to warrant evaluation and management in older adults with MCI. Addressing social isolation, assisting this vulnerable group in functional and physical activities, and cultivating a positive perception towards cognitive and physical health are highly prioritized treatment targets among individuals with MCI.

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

INTRODUCTION

Environmental exposures are intertwined with mental health outcomes. People are exposed to the environments in which they currently live, and to a multitude of environments along their daily movements and through their residential relocations. However, most research assumes that people are immobile, disregarding that such dynamic exposures also serve as stressors or buffers potentially associated with depression and suicide risk. The aim of the Dynamic Urban Environmental Exposures on Depression and Suicide (NEEDS) study is to examine how dynamic environmental exposures along people's daily movements and over their residential histories affect depression and suicide mortality in the Netherlands.

METHODS AND ANALYSIS

The research design comprises two studies emphasising the temporality of exposures. First, a cross-sectional study is assessing how daily exposures correlate with depression. A nationally representative survey was administered to participants recruited through stratified random sampling of the population aged 18-65 years. Survey data were enriched with smartphone-based data (eg, Global Positioning System tracking, Bluetooth sensing, social media usage, communication patterns) and environmental exposures (eg, green and blue spaces, noise, air pollution). Second, a longitudinal population register study is addressing the extent to which past environmental exposures over people's residential history affect suicide risk later in life. Statistical and machine learning-based models are being developed to quantify environment-health relations.

ETHICS AND DISSEMINATION

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

Neighborhood social reciprocity and mental health among older adults in China: the mediating effects of physical activity, social interaction, and volunteering

BACKGROUND

This study aims to investigate the mechanisms through which neighborhood social reciprocity influences older adults' mental health in China.

METHODS

This study used data from the 2011-2015 waves of the China Health and Retirement Longitudinal Study. It estimated the effects of neighborhood social reciprocity on older adults' mental health and tested the mediating effects of the frequencies of physical activity, social interaction with neighbors, and volunteering experience.

RESULTS

The results indicated that more neighborhood social reciprocity related to better mental health. The effects of the three mediators were statistically significant and enhanced mental health. In addition, the effects of the mediators were strengthened by neighborhood social reciprocity, and vice versa.

CONCLUSIONS

In China, neighborhood social reciprocity influenced older adults' mental health directly and through the mechanisms of the frequencies of physical activity, social interaction with neighbors, and volunteering experience.

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

Background

Depression has become a severe societal problem in China. Although many studies have analyzed how environmental characteristics within neighborhoods affect depression, only a few have dealt with developing countries, and even fewer have considered built, natural, and social environments concurrently.

Methods

Based on a sample of 20,533 Chinese residents assessed in 2016, the present study examined associations between depressive symptoms and respondents’ built, natural, and social environments. Depressive symptoms were measured using the Center for Epidemiologic Studies Depression Scale (CES-D), and multilevel regression models were fitted accounting for potential covariates.

Results

Results indicated that living in neighborhoods with more green spaces and a higher population density were negatively associated with CES-D scores. Living in neighborhoods with more social capital was protective against depression. Furthermore, results showed that the social environment moderated the association between the built environment and depression.

Conclusions

Social environments moderate the relationship between the built environment and depression. As environments seem to interact with each other, we advise against relying on a single environment when examining associations with depressive symptoms.