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

Challenges of Air Pollution and Health in East Asia

PURPOSE OF REVIEW

Air pollution has been a serious environmental and public health issue worldwide, particularly in Asian countries. There have been significant increases in epidemiological studies on fine particulate matter (PM2.5) and ozone pollution in East Asia, and an in-depth review of epidemiological evidence is urgent. Thus, we carried out a systematic review of the epidemiological research on PM2.5 and ozone pollution in East Asia released in recent years.

RECENT FINDINGS

Recent studies have indicated that PM2.5 and ozone are the most detrimental air pollutants to human health, resulting in substantial disease burdens for Asian populations. Many epidemiological studies of PM2.5 and ozone have been mainly performed in three East Asian countries (China, Japan, and South Korea). We derived the following summary findings: (1) both short-term and long-term exposure to PM2.5 and ozone could raise the risks of mortality and morbidity, emphasizing the need for continuing improvements in air quality in East Asia; (2) the long-term associations between PM2.5 and mortality in East Asia are comparable to those observed in Europe and North America, whereas the short-term associations are relatively smaller in magnitude; and (3) further cohort and intervention studies are required to yield robust and precise evidence that can promote evidence-based policymaking in East Asia. This updated review presented an outline of the health impacts of PM2.5 and ozone in East Asia, which may be beneficial for the development of future regulatory policies and standards, as well as for designing subsequent investigations.

Differential effects of size-specific particulate matter on frailty transitions among middle-aged and older adults in China: findings from the China Health and Retirement Longitudinal Study (CHARLS), 2015-2018

BACKGROUND

This study aimed to assess the long-term effects of size-specific particulate matter (PM) on frailty transitions in middle-aged and older Chinese adults.

METHODS

We included 13 910 participants ≥45 y of age from the China Health and Retirement Longitudinal Study (CHARLS) for 2015 and 2018 who were classified into three categories in 2015 according to their frailty states: robust, prefrail and frail. Air quality data were obtained from the National Urban Air Quality Real-time Publishing Platform. A two-level logistic regression model was used to examine the association between concentrations of PM and frailty transitions.

RESULTS

At baseline, the total number of robust, prefrail and frail participants were 7516 (54.0%), 4324 (31.1%) and 2070 (14.9%), respectively. Significant associations were found between PM concentrations and frailty transitions. For each 10 μg/m3 increase in the 3-y averaged 2.5-μm PM (PM2.5) concentrations, the risk of worsening in frailty increased in robust (odds ratio [OR] 1.06 [95% confidence interval {CI} 1.01 to 1.12]) and prefrail (OR 1.07 [95% CI 1.01 to 1.13]) participants, while the probability of improvement in frailty in prefrail (OR 0.91 [95% CI 0.84 to 0.98]) participants decreased. In addition, the associations of PM10 and coarse fraction of PM with frailty transitions showed similar patterns.

CONCLUSIONS

Long-term exposure to PM was associated with higher risks of worsening and lower risks of improvement in frailty among middle-aged and older adults in China.

Health benefits from the rapid reduction in ambient exposure to air pollutants after China's clean air actions: progress in efficacy and geographic equality

Clean air actions (CAAs) in China have been linked to considerable benefits in public health. However, whether the beneficial effects of CAAs are equally distributed geographically is unknown. Using high-resolution maps of the distributions of major air pollutants (fine particulate matter [PM2.5] and ozone [O3]) and population, we aimed to track spatiotemporal changes in health impacts from, and geographic inequality embedded in, the reduced exposures to PM2.5 and O3 from 2013 to 2020. We used a method established by the Global Burden of Diseases Study. By analyzing the changes in loss of life expectancy (LLE) attributable to PM2.5 and O3, we calculated the gain of life expectancy (GLE) to quantify the health benefits of the air-quality improvement. Finally, we assessed the geographic inequality embedded in the GLE using the Gini index (GI). Based on risk assessments of PM2.5 and O3, during the first stage of CAAs (2013 to 2017), the mean GLE was 1.87 months. Half of the sum of the GLE was disproportionally distributed in about one quarter of the population exposed (GI 0.44). During the second stage of CAAs (2017 to 2020), the mean GLE increased to 3.94 months and geographic inequality decreased (GI 0.18). According to our assessments, CAAs were enhanced, from the first to second stages, in terms of not only preventing premature mortality but also ameliorating health inequalities. The enhancements were related to increased sensitivity to the health effects of air pollution and synergic control of PM2.5 and O3 levels. Our findings will contribute to optimizing future CAAs.

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.

Ultra-high-resolution mapping of ambient fine particulate matter to estimate human exposure in Beijing

With the decreasing regional-transported levels, the health risk assessment derived from fine particulate matter (PM2.5) has become insufficient to reflect the contribution of local source heterogeneity to the exposure differences. Here, we combined the both ultra-high-resolution PM2.5 concentration with population distribution to provide the personal daily PM2.5 internal dose considering the indoor/outdoor exposure difference. A 30-m PM2.5 assimilating method was developed fusing multiple auxiliary predictors, achieving higher accuracy (R2 = 0.78-0.82) than the chemical transport model outputs without any post-simulation data-oriented enhancement (R2 = 0.31-0.64). Weekly difference was identified from hourly mobile signaling data in 30-m resolution population distribution. The population-weighted ambient PM2.5 concentrations range among districts but fail to reflect exposure differences. Derived from the indoor/outdoor ratio, the average indoor PM2.5 concentration was 26.5 μg/m3. The internal dose based on the assimilated indoor/outdoor PM2.5 concentration shows high exposure diversity among sub-groups, and the attributed mortality increased by 24.0% than the coarser unassimilated model.

Long-Term PM2.5 Exposure, Lung Function, and Cognitive Function Among Middle-Aged and Older Adults in China

BACKGROUND

Long-term exposure to PM2.5 is related to poor lung function and cognitive impairment, but less is known about the pathway involved in this association. We aimed to explore whether the effect of PM2.5 on cognitive function was mediated by lung function.

METHODS

A total of 7 915 adults older than 45 years old were derived from the China Health and Retirement Longitudinal Study (CHARLS) collected in 2011 and 2015. PM2.5 exposure was estimated using a geographically weighted regression model. Lung function was measured by peak expiratory flow (PEF). Cognitive function was evaluated through a structured questionnaire with 4 dimensions: episodic memory, attention, orientation, and visuoconstruction. Under the counterfactual framework, causal mediation analysis was applied to examine direct and indirect associations.

RESULTS

An interquartile range (IQR) increase in PM2.5 change was significantly related to an 8.480 (95% confidence interval [CI]: 3.116, 13.845) decrease in PEF change and a 0.301 (95% CI: 0.100, 0.575) decrease in global cognitive score change. The direct and indirect effects of PM2.5 exposure on global cognitive performance were -0.279 (95% CI: -0.551, -0.060) and -0.023 (95% CI: -0.041, -0.010), respectively. The proportion of the indirect effect was 7.48% (p = .010). The same significant association appeared in only 2 dimensions, episodic memory and attention, which were both mediated by PEF.

CONCLUSIONS

Lung function played a partially mediating role in the association between long-term PM2.5 exposure and cognition. More clean air actions should be undertaken to improve lung function and cognitive function in older adults.

Spatial analysis of overweight prevalence in China: exploring the association with air pollution

BACKGROUND

Overweight is a known risk factor for various chronic diseases and poses a significant threat to middle-aged and elderly adults. Previous studies have reported a strong association between overweight and air pollution. However, the spatial relationship between the two remains unclear due to the confounding effects of spatial heterogeneity.

METHODS

We gathered height and weight data from the 2015 China Health and Retirement Long-term Survey (CHARLS), comprising 16,171 middle-aged and elderly individuals. We also collected regional air pollution data. We then analyzed the spatial pattern of overweight prevalence using Moran's I and Getis-Ord Gi* statistics. To quantify the explanatory power of distinct air pollutants for spatial differences in overweight prevalence across Southern and Northern China, as well as across different age groups, we utilized Geodetector's q-statistic.

RESULTS

The average prevalence of overweight among middle-aged and elderly individuals in each city was 67.27% and 57.39%, respectively. In general, the q-statistic in southern China was higher than that in northern China. In the north, the prevalence was significantly higher at 54.86% compared to the prevalence of 38.75% in the south. SO2 exhibited a relatively higher q-statistic in middle-aged individuals in both the north and south, while for the elderly in the south, NO2 was the most crucial factor (q = 0.24, p < 0.01). Moreover, fine particulate matter (PM2.5 and PM10) also demonstrated an important effect on overweight. Furthermore, we found that the pairwise interaction between various risk factors improved the explanatory power of the prevalence of overweight, with different effects for different age groups and regions. In northern China, the strongest interaction was found between NO2 and SO2 (q = 0.55) for middle-aged individuals and PM2.5 and SO2 (q = 0.27) for the elderly. Conversely, in southern China, middle-aged individuals demonstrated the strongest interaction between SO2 and PM10 (q = 0.60), while the elderly showed the highest interaction between NO2 and O3 (q = 0.42).

CONCLUSION

Significant spatial heterogeneity was observed in the effects of air pollution on overweight. Specifically, air pollution in southern China was found to have a greater impact on overweight than that in northern China. And, the impact of air pollution on middle-aged individuals was more pronounced than on the elderly, with distinct pollutants demonstrating significant variation in their impact. Moreover, we found that SO2 had a greater impact on overweight prevalence among middle-aged individuals, while NO2 had a greater impact on the elderly. Additionally, we identified significant statistically interactions between O3 and other pollutants.

Perchlorate, nitrate, and thiocyanate and depression: the potential mediating role of sleep

Perchlorate, nitrate, and thiocyanate are common thyroid disruptors, but it is not clear whether they are related to depression. In this study, we aimed to investigate the association between perchlorate, nitrate, and thiocyanate and depression, and to explore the potential role of sleep in this process. We used data from the National Health and Nutrition Examination Survey (NHANES). From 2005 to 2016, 6 cycles cross-sectional data were combined. Urinary perchlorate, nitrate, and thiocyanate came from laboratory test; depression was diagnosed by the Nine-item Patient Health Questionnaire (PHQ-9). Weighted generalized liner models, restricted cubic splines, and mediation analysis were used in this study. Totally, 16,715 participants were involved in this study, of which 8295 (49.63%) were male and 8420 (50.37%) were female, with an average age of 46.19 ± 0.32 years. We found that urinary thiocyanate concentration was positively associated with depression (Odds ratios [ORs]: 1.49; 95% confidence intervals [95% CIs]: 1.16, 1.91), but not perchlorate (ORs: 0.71; 95% CIs: 0.52, 0.97) or nitrate (ORs: 0.89, 95% CIs: 0.66, 1.19). Sleep may play a potential mediating role between thiocyanate and depression (9.55%). In conclusion, higher concentrations of thiocyanate exposure may be associated with a higher risk of depression, and the sleep duration may be an important mediating factor.

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

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

Causal effects of air pollution on mental health among Adults--An exploration of susceptible populations and the role of physical activity based on a longitudinal nationwide cohort in China

Long-term exposure to air pollutants is likely to be associated with mental disorders, but relevant studies remain limited and inconsistent, and evidence to assess causality is particularly lacking, especially in developing countries. In addition, there are few studies on the role of physical activity in this relationship. We investigated the causal relationship between air pollutant exposure and mental health among Chinese adults and whether physical activity could play a positive role in this relationship. Using the balanced panel data for 2014 and 2016 from the China Family Panel Study, a representative Chinese national cohort study, we selected and validated appropriate instrumental variable to explore the causal relationship between air pollution and mental health and explored the moderating effect of physical activity using an instrumental variable fixed effects model (IVFE) in a counterfactual causal inference framework. PM_2.5 and ground surface ozone were selected as proxies for different types of air pollutants and extended the interpretability by studying them for populations with different characteristics. A total of 21,944 participants were included in this study. In the IVFE model, we found that both PM_2.5 and ground surface ozone significantly negatively affected mental health, and that habitual physical activity counteracted this negative effect regardless of different types of air pollution. We also found that the findings held for adults with different characteristics. The findings suggest that habitual physical activity may offset the deterioration of mental health in adults in developing countries due to air pollution, regardless of age, gender, income, and the presence of chronic diseases.

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 path to healthy ageing in China: a Peking University-Lancet Commission

Around the world, populations are ageing at a faster pace than in the past and this demographic transition will have impacts on all aspects of societies. In May 2020, the UN General Assembly declared 2021–2030 the Decade of Healthy Ageing, highlighting the importance for policymakers across the world to focus policy on improving the lives of older people, both today and in the future. While rapid population ageing poses challenges, China’s rapid economic growth over the last forty years has created space for policy to assist older persons and families in their efforts to improve health and well-being at older ages. As China is home to 1/5 of the world’s older people, China is often held up as an example for other middle-income countries. This Commission Report aims to help readers to understand the process of healthy ageing in China as a means of drawing lessons from the China experience. In addition, with the purpose of informing the ongoing policy dialogue within China, the Commission Report highlights the policy challenges on the horizon and draws lessons from international experience.

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.

Overview of particulate air pollution and human health in China: Evidence, challenges, and opportunities

Ambient particulate matter (PM) pollution in China continues to be a major public health challenge. With the release of the new WHO air quality guidelines in 2021, there is an urgent need for China to contemplate a revision of air quality standards (AQS). In the recent decade, there has been an increase in epidemiological studies on PM in China. A comprehensive evaluation of such epidemiological evidence among the Chinese population is central for revision of the AQS in China and in other developing countries with similar air pollution problems. We thus conducted a systematic review on the epidemiological literature of PM published in the recent decade. In summary, we identified the following: (1) short-term and long-term PM exposure increase mortality and morbidity risk without a discernible threshold, suggesting the necessity for continuous improvement in air quality; (2) the magnitude of long-term associations with mortality observed in China are comparable with those in developed countries, whereas the magnitude of short-term associations are appreciably smaller; (3) governmental clean air policies and personalized mitigation measures are potentially effective in protecting public and individual health, but need to be validated using mortality or morbidity outcomes; (4) particles of smaller size range and those originating from fossil fuel combustion appear to show larger relative health risks; and (5) molecular epidemiological studies provide evidence for the biological plausibility and mechanisms underlying the hazardous effects of PM. This updated review may serve as an epidemiological basis for China’s AQS revision and proposes several perspectives in designing future health studies.

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Acute effects of PM are smaller in China compared with developed countries

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Health effects caused by PM depend on particle composition, source, and size

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There are no thresholds for the health effects of PM

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Mechanistic studies support the biological plausibility of PM’s health effects

Trimester-specific association of perceived indoor air quality with antenatal depression: China Medical University Birth Cohort Study

Antenatal depression is associated with adverse birth and long-term outcomes for mothers and children. Pregnant women spend 90% of time indoors; however, the association between indoor air quality and risk of antenatal depression has not been established. In this study, we aim to determine the total and trimester-specific association of perceived indoor air quality (PIAQ) with antenatal depression. A total of 2166 pregnant women were enrolled during the first trimester and evaluated during the second and third trimesters in the China Medical University Birth Cohort Study, a prospective pre-birth cohort study in northeastern China. PIAQ scores were obtained during each of three trimesters, which a higher score indicated a worse indoor air quality. Antenatal depression was screened using an Edinburgh Postnatal Depression Scale (EPDS) and defined as an EPDS score ≥ 9. Prevalence of antenatal depression was 26.7%, 20.6%, and 20.9% during the first, second, and third trimesters, respectively. A higher PIAQ score was positively associated with a depression score throughout pregnancy (β = 0.27, 95% CI = 0.15-0.39). Trimester-specific adverse PIAQ exposure was associated with a higher depression score in the same trimester, but not with a higher score in a subsequent trimester. A dose-response pattern and incremental increases in risk of depression were observed with calculated adverse PIAQ exposures across all three trimesters, with the highest risk (OR = 3.24; 95% CI = 2.28-4.78) among women with adverse PIAQ across all three trimesters. The hazardous association between adverse PIAQ exposure and risk of depression were less pronounced among women with higher physical activity levels (P for interaction < 0.001). The results of present study provided important evidence that pregnant women's mental health was linked to indoor air quality during pregnancy. These findings could be helpful in the development of guidelines to prevent antenatal depression by improving indoor air quality.

Associations of PM2.5 and road traffic noise with mental health: Evidence from UK Biobank

BACKGROUND

The associations of atmospheric particulate matter with diameters of 2.5 μm or less (PM2.5) and road traffic noise with mental disorders in men and women are not well studied.

OBJECTIVES

We aim to examine the cross-sectional associations of PM2.5 and road traffic noise with mental disorders in men and women.

METHODS

The baseline data of the UK Biobank study (2006-2010) were used. Mental disorders including symptoms of nerves, anxiety, tension or depression (NATD), major depression, and bipolar disorder were assessed by validated questions. Verified models were used to estimate PM2.5 and road traffic noise.

RESULTS

A total of 334,986 participants with measurements of NATD and 90,706 participants with measurements of major depression and bipolar disorder were included in the analysis. After adjusting for covariates, the odds for the risk of NATD symptoms increased by 2.31 (95% CI: 2.15-2.50) times per 10 μg/m³ increase in PM2.5. The odds for the risk of major depression and bipolar disorder increased by 2.26 and 4.99 times per 10 μg/m³ increase in PM2.5. On the other hand, higher road traffic noise exposure was significantly associated with a higher risk of NATD symptoms (Decile 6-8 (54.9-57.8 dB), OR: 1.03, 95% CI: 1.01-1.06; Decile 9-10 (≥57.8 dB), OR: 1.04, 95% CI: 1.01-1.07) and bipolar disorder (Decile 2-5 (52.1-54.9 dB), OR: 1.26, 95% CI: 1.00-1.59; Decile 6-8 (54.9-57.8 dB), OR: 1.30, 95% CI: 1.02-1.65; Decile 9-10 (≥57.8 dB), OR: 1.54, 95% CI: 1.21-1.97). Interestingly, a negative association was observed between moderate road traffic noise and major depression (Decile 2-5 (52.1-54.9 dB), OR: 0.95, 95% CI: 0.90-1.00). Interactions between PM2.5 exposure with age, gender, and sleeplessness for NATD symptoms were observed (P < 0.05), while interactions between road traffic noise exposure with age and gender were observed (P < 0.05).

CONCLUSIONS

We found a positive association between PM2.5 and mental disorders. Meanwhile, we found a positive association of road traffic noise with NATD symptoms and bipolar disorder and a negative association of moderate road traffic noise with major depression. Also, the effect modifications of these associations by age, gender, or sleeplessness may exist.

Air pollution and mental health: associations, mechanisms and methods

PURPOSE OF REVIEW

There is increasing interest in the links between exposure to air pollution and a range of health outcomes. The association with mental health however is much less established. This article reviews developments in the field over the past 12 months, highlighting the evidence for causation, associations between multiple air pollutants and mental health outcomes, and assesses the challenges of researching this topic.

RECENT FINDINGS

Increasingly rigorous methods are being applied to the investigation of a broader range of mental health outcomes. These methods include basic science, neuroimaging, and observational studies representing diverse geographical locations. Cohort studies with linked high-resolution air pollutant exposure data are common, facilitating advanced analytic methods. To date, meta-analyses have demonstrated small and significant positive associations between long-term exposure to fine particulate matter and depressive symptoms and cognitive decline. Methodological complexities in measuring exposure and outcome pose ongoing difficulties for the field.

SUMMARY

Literature on this topic has recently seen an appreciable expansion. Work that better estimates daily exposure, controls for complex confounders, and is driven by hypotheses founded in candidate causal mechanisms would help clarify associations, and inform targeted interventions and policymakers.

Impacts of air pollution on COVID-19 case fatality rate: a global analysis

The coronavirus disease 2019 (COVID-19) pandemic is still rapidly spreading globally. To probe high-risk cities and the impacts of air pollution on public health, this study explores the relationship between the long-term average concentration of air pollution and the city-level case fatality rate (CFR) of COVID-19 globally. Then, geographically weighted regression (GWR) is applied to examine the spatial variability of the relationships. Six air pollution factors, including nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃), PM_2.5 (particles with diameter ≤2.5 μm), PM₁₀ (particles with diameter ≤10 μm), and air quality index (AQI), are positively associated with the city-level COVID-19 CFR. Our results indicate that a 1-unit increase in NO₂ (part per billion, PPB), SO₂ (PPB), O₃ (PPB), PM_2.5 (microgram per cubic meter, μg/m³), PM₁₀ (μg/m³), AQI (score), is related to a 1.450%, 1.005%, 0.992%, 0.860%, 0.568%, and 0.776% increase in the city-level COVID-19 CFR, respectively. Additionally, the effects of NO₂, O₃, PM_2.5, AQI, and probability of living with poor AQI on COVID-19 spatially vary in view of the estimation of the GWR. In other words, the adverse impacts of air pollution on health are different among the cities. In summary, long-term exposure to air pollution is negatively related to the COVID-19 health outcome, and the relationship is spatially non-stationary. Our research sheds light on the impacts of slashing air pollution on public health in the COVID-19 pandemic to help governments formulate air pollution policies in light of the local situations.

ORIGINAL ARTICLE: Associations of antidepressant medication with its various predictors including particulate matter: Machine learning analysis using national health insurance data

This study uses machine learning and population-based data to analyze major determinants of antidepressant medication including the concentration of particulate matter under 2.5 μm (PM_2.5). Retrospective cohort data came from Korea National Health Insurance Service claims data for 43,251 participants, who were aged 15-79 years, lived in the same districts of Seoul and had no history of antidepressant medication during 2002-2012. The dependent variable was antidepressant-free months during 2013-2015 and the 30 independent variables for 2012 were included (demographic/socioeconomic information, health information, district-level information including PM_2.5). Random forest variable importance, the contribution of a variable for the performance of the model, was used for identifying major predictors of antidepressant-free months. Based on random forest variable importance, the top 15 determinants of antidepressant medication during 2013-2015 included cardiovascular disease (0.0054), age (0.0047), household income (0.0037), gender (0.0027), the district-level proportion of recipients of national basic living security program benefits (0.0019), district-level social satisfaction (0.0013), diabetes mellitus (0.0012), January 2012 PM_2.5 (0.0011), district-level street ratio (0.0010), drinker (0.0009), chronic obstructive pulmonary disease (0.0008), district-level economic satisfaction (0.0006), exercise (0.0005), March 2012 PM_2.5 (0.0005) and November 2012 PM_2.5 (0.0004). Besides these predictors, smoker and district-level deprivation index are found to be influential most widely, given that they ranked within the top 10 most often in sub-group analysis. In conclusion, antidepressant medication has strong associations with neighborhood conditions including socioeconomic satisfaction and the seasonality of particulate matter. Strong interventions for these factors are really needed for the effective management of major depressive disorder.

Association of PM 2.5 Reduction with Improved Kidney Function: A Nationwide Quasiexperiment among Chinese Adults

Background. Increasing evidence from human studies has revealed the adverse impact of ambient fine particles (PM 2.5) on health outcomes related to metabolic disorders and distant organs. Whether exposure to ambient PM 2.5 leads to kidney impairment remains unclear. The rapid air quality improvement driven by the clean air actions in China since 2013 provides an opportunity for a quasiexperiment to investigate the beneficial effect of PM 2.5 reduction on kidney function.Methods. Based on two repeated nationwide surveys of the same population of 5115 adults in 2011 and 2015, we conducted a difference-in-difference study. Variations in long-term exposure to ambient PM 2.5 were associated with changes in kidney function biomarkers, including estimated glomerular filtration rate by serum creatinine (GFR scr) or cystatin C (GFR cys), blood urea nitrogen (BUN), and uric acid (UA).Results. For a 10  μg/m 3 reduction in PM 2.5, a significant improvement was observed for multiple kidney functional biomarkers, including GFR scr, BUN and UA, with a change of 0.42 (95% confidence interval [CI]: 0.06, 0.78) mL/min/1.73m 2, -0.38 (-0.64, -0.12) mg/dL, and -0.06 (-0.12, -0.00) mg/dL, respectively. A lower socioeconomic status, indicated by rural residence or low educational level, enhanced the adverse effect of PM 2.5 on kidney function.Conclusions. These results support a significant nephrotoxicity of PM 2.5 based on multiple serum biomarkers and indicate a beneficial effect of improved air quality on kidney function.

Exploring the Potential Relationship Between Global Greenness and DALY Loss Due to Depressive Disorders

OBJECTIVE

Prior studies have shown that greenness can reduce the burden of depressive disorders. However, most were focused on local-scale analyses while limited evaluated globally. We aimed to investigate the association between greenness and the burden of depressive disorders using data from 183 countries worldwide.

METHODS

We used the normalized difference vegetation index (NDVI) to estimate greenness. Country-level disability-adjusted life year (DALY) loss due to depressive disorders was used to represent depressive disorder burdens. A generalized linear mixed model was applied to assess the relationship between greenness and depressive disorders after controlling for covariates. Stratified analyses were conducted to determine the effects of greenness across several socio-demographic levels.

RESULTS

The findings showed a significant negative association between greenness and the health burden of depressive disorders with a coefficient of -0.196 (95% CI: -0.356, -0.035) in the DALY changes per interquartile unit increment of NDVI. The stratified analyses suggested beneficial effects of greenness on depressive disorders across sex, various age groups especially for those aged <49 years, with low-income and/or those living in highly urbanized countries.

CONCLUSIONS

Our study noted that greenness exposure was significant negative association with the burden of depressive disorders. The findings should be viewed as recommendations for relevant authorities in supporting environmental greenness enhancement to reduce the mental burdens.

Association between Ambient Fine Particulate Matter and Physical Functioning in Middle-aged and Older Chinese Adults: A Nationwide Longitudinal Study

BACKGROUND

Exposure to air pollution is associated with several chronic diseases and subclinical processes that could subsequently contribute to physical disability. However, whether and to what extent air pollution exposure is associated with objective measures of physical functioning remains understudied.

METHODS

We used longitudinal data from the China Health and Retirement Longitudinal Study (CHARLS) and included 10,823 participants who were surveyed at least twice. Annual average exposure to fine particulate matter (PM2.5) was assessed using a state-of-the-art estimator. Physical functioning was assessed with four objective tests covering hand-grip strength, balance, repeated chair stands, and gait speed. Mixed-effects models with participants as a random term were used to estimate associations with multiple adjustments.

RESULTS

We found a significant and robust association between exposure to increased PM2.5 and the reduction in hand-grip strength and balance ability. Each 10-μg/m 3 increase in annual averaged concentrations of PM2.5 was associated with a 220-g (95% confidence interval [CI]: 127, 312 g) reduction in hand-grip strength per 60 kg of body weight and a 5% risk (95% CI: 2, 7) of reduced balance ability. The estimated effect of each 10-μg/m 3 increase in PM2.5 on hand-grip strength and balance ability was equivalent to the effect of aging [1.12 (95% CI: 0.76, 1.48) and 0.98 (95% CI: 0.50, 1.50) years, respectively].

CONCLUSIONS

PM2.5 may be differentially associated with various dimensions of physical functioning. Improving air quality can prevent physical disability.