Exposure to black carbon is associated with symptoms of depression: A retrospective cohort study in college students

Comparative assessment of acute neurotoxicity of real-world ultra-fine black carbon emitted from residential solid fuel combustion

Incomplete combustion of residential solid fuel is one of the main anthropogenic sources for black carbon (BC). Fresh BC, mainly enriched in ultra-fine fraction of particles, can directly cross blood-brain barrier and are reported to be associated with neurodegenerative diseases. Because of the difficulties in collection and purification of BC from ambient particles, there are still significant knowledge gaps in understanding neurotoxicity caused by real-world BC. The purpose of this study is to compare the neurotoxic effects caused by BCs emitted from combustion of six residential solid fuels, and try to reveal associated biological mechanisms in SH-SY5Y cells. Two straw BC (Wheat-BC and Corn-BC) showed highest neurotoxic effects followed by wood BC (Pine-BC and Aspen-BC) and coal BC (Xvzhou and Longkou Coal), as indicated by viability, lactic dehydrogenase, malondialdehyde, adenosine triphosphate and acetylcholine levels. Coal BC caused nearly no toxicity in human neuroblastoma (SH-SY5Y) cells within highest dose of 200 μg/mL. RNA sequence and bioinformatics analysis were applied to effectively identify differential genes and signaling pathways. Based on Gene Ontology (GO) annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, Protein Protein Interaction network (PPI network) construction, we found biomass BC affected mitochondrial function, interfered with cellular metabolic processes, disturbed redox homeostasis, and finally resulted in cellular damages. Coal-BC mainly caused cytokine/chemokine related inflammatory responses. Reverse transcription quantitative polymerase chain reaction (RT-qPCR) and Western blotting methods were further applied to find out related signaling pathways. Biomass BC activated IL6R/JAK3/STAT3 and JAK3/STAT6 pathways leading to oxidative stress and inflammatory responses. Coal BC activated JAK3/STAT3 pathway leading to chemokine related responses. This study revealed the heterogeneity in neurotoxicity of BCs from different combustion sources and provided important data for health risk assessment. BC-related neurotoxicity should be considered when making air pollution emission control strategies, with residential biomass receiving more policy attention.

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.

Airborne Exposure to Pollutants and Mental Health: A Review with Implications for United States Veterans

PURPOSE OF REVIEW

Inhalation of airborne pollutants in the natural and built environment is ubiquitous; yet, exposures are different across a lifespan and unique to individuals. Here, we reviewed the connections between mental health outcomes from airborne pollutant exposures, the biological inflammatory mechanisms, and provide future directions for researchers and policy makers. The current state of knowledge is discussed on associations between mental health outcomes and Clean Air Act criteria pollutants, traffic-related air pollutants, pesticides, heavy metals, jet fuel, and burn pits.

RECENT FINDINGS

Although associations between airborne pollutants and negative physical health outcomes have been a topic of previous investigations, work highlighting associations between exposures and psychological health is only starting to emerge. Research on criteria pollutants and mental health outcomes has the most robust results to date, followed by traffic-related air pollutants, and then pesticides. In contrast, scarce mental health research has been conducted on exposure to heavy metals, jet fuel, and burn pits. Specific cohorts of individuals, such as United States military members and in-turn, Veterans, often have unique histories of exposures, including service-related exposures to aircraft (e.g. jet fuels) and burn pits. Research focused on Veterans and other individuals with an increased likelihood of exposure and higher vulnerability to negative mental health outcomes is needed. Future research will facilitate knowledge aimed at both prevention and intervention to improve physical and mental health among military personnel, Veterans, and other at-risk individuals.

An association between PM2.5 components and respiratory infectious diseases: A China's mainland-based study

The particulate matter with diameter of less than 2.5 µm (PM2.5) is an important risk factor for respiratory infectious diseases, such as scarlet fever, tuberculosis, and similar diseases. However, it is not clear which component of PM2.5 is more important for respiratory infectious diseases. Based on data from 31 provinces in mainland China obtained between 2013 and 2019, this study investigated the effects of different PM2.5 components, i.e., sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and organic matter (OM), and black carbon (BC), on respiratory infectious diseases incidence [pulmonary tuberculosis (PTB), scarlet fever (SF), influenza, hand, foot, and mouth disease (HFMD), and mumps]. Geographical probes and the Bayesian kernel machine regression (BKMR) model were used to investigate correlations, single-component effects, joint effects, and interactions between components, and subgroup analysis was used to assess regional and temporal heterogeneity. The results of geographical probes showed that the chemical components of PM2.5 were associated with the incidence of respiratory infectious diseases. BKMR results showed that the five components of PM2.5 were the main factors affecting the incidence of respiratory infectious diseases (PIP>0.5). The joint effect of influenza and mumps by co-exposure to the components showed a significant positive correlation, and the exposure-response curve for a single component was approximately linear. And single-component modelling revealed that OM and BC may be the most important factors influencing the incidence of respiratory infections. Moreover, respiratory infectious diseases in southern and southwestern China may be less affected by the PM2.5 component. This study is the first to explore the relationship between different components of PM2.5 and the incidence of five common respiratory infectious diseases in 31 provinces of mainland China, which provides a certain theoretical basis for future research.

Short-Term Exposure to PM2.5 Chemical Components and Depression Outpatient Visits: A Case-Crossover Analysis in Three Chinese Cities

BACKGROUND

The association between specific chemical components of PM2.5 and depression remains largely unknown.

METHODS

We conducted a time-stratified case-crossover analysis with a distributed lag nonlinear model (DLNM) to evaluate the relationship of PM2.5 and its chemical components, including black carbon (BC), organic matter (OM), sulfate (SO42-), nitrate (NO3-), and ammonium (NH4+), with the depression incidence. Daily depression outpatients were enrolled from Huizhou, Shenzhen, and Zhaoqing.

RESULTS

Among 247,281 outpatients, we found the strongest cumulative effects of PM2.5 and its chemical components with the odd ratios (ORs) of 1.607 (95% CI: 1.321, 1.956) and 1.417 (95% CI: 1.245, 1.612) at the 50th percentile of PM2.5 and OM at lag 21, respectively. Furthermore, the ORs with SO42- and NH4+ at the 75th percentile on the same lag day were 1.418 (95% CI: 1.247, 1.613) and 1.025 (95% CI: 1.009, 1.140). Relatively stronger associations were observed among females and the elderly.

CONCLUSIONS

Our study suggests that PM2.5 and its chemical components might be important risk factors for depression. Reducing PM2.5 emissions, with a particular focus on the major sources of SO42- and OM, might potentially alleviate the burden of depression in South China.

Source apportionment of heavy metals in PM2.5 samples and effects of heavy metals on hypertension among schoolchildren in Tianjin

The prevalence of hypertension in children has increased significantly in recent years in China. The aim of this study was to provide scientific support to control ambient heavy metals (HMs) pollution and prevent childhood hypertension. In this study, ambient HMs in PM2.5 were collected, and 1339 students from Tianjin were randomly selected. Positive matrix factorization (PMF) was used to identify and determine the sources of HMs pollution. The generalized linear model, Bayesian kernel machine regression (BKMR) and the quantile g-computation method were used to analyze the relationships between exposure to HMs and the risk of childhood hypertension. The results showed that HMs in PM2.5 mainly came from four sources: soil dust, coal combustion, incineration of municipal waste and the metallurgical industry. The positive relationships between As, Se and Pb exposures and childhood hypertension risk were found. Coal combustion and incineration of municipal waste were important sources of HMs in the occurrence of childhood hypertension. Based on these accomplishments, this study could provide guidelines for the government and individuals to alleviate the damaging effects of HMs in PM2.5. The government must implement policies to control prime sources of HMs pollution.

Ambient temperatures associated with reduced cognitive function in older adults in China

The cognitive function status of older adults determines the social function and living quality of older adults, which is related to the healthy development and stability of the society. However, the impact of high or low ambient temperature on cognitive function in older adults remains unclear. Based on data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), we comprehensively assessed the impact of ambient temperature on the cognitive function of older adults in this study. The findings exhibited that for each 1 °C ascent in monthly temperature of high temperature, the examination score of global cognitive function of older adults decreased by 0.48 (95% CI 0.21-0.74), which was greater than that of 0.14 (95% CI 0.06-0.25) for each 1 °C reduction in low temperature. Overall, the detrimental effect of high temperature on cognitive function in older adults was more significant than that of low temperature, including on the five sub-cognitive functions involved. Our research provides vital technical guidance and reference for the health protection and prevention of cognitive function of older adults in specific external environmental conditions under the current climatic variation and temperature rise.

Longitudinal associations of neighbourhood environmental exposures with mental health problems during adolescence: Findings from the TRAILS study

BACKGROUND

Cross-sectional studies have found associations between neighbourhood environments and adolescent mental health, but the few longitudinal studies mainly focused on single exposure-based analyses and rarely assessed the mental health associations with environmental changes.

OBJECTIVES

We assessed longitudinal within- and between-person associations of multiple neighbourhood time-varying physical and social environmental exposures with externalising and internalising problems throughout adolescence.

METHODS

We used four waves of TRAILS (Tracking Adolescents' Individual Lives Survey) data on self-reported externalising and internalising problems at ages 11, 13, 16, and 19 among 2,135 adolescents in the Netherlands. We measured residence-based time-varying environmental exposures, including green space, air pollution (fine particulate matter (PM2.5)), noise, deprivation, and social fragmentation. We fitted random-effect within-between regression models to assess the environment-mental health associations.

RESULTS

At the within-person level, an interquartile range (IQR) increase in PM2.5 was associated with a 0.056 IQR (95% CI: 0.014, 0.099) increase in externalising problems, while an IQR social fragmentation increase was associated with a 0.010 IQR (95% CI: -0.020, -0.001) decrease in externalising problems. Stratification revealed that the association with PM2.5 was significant only for movers, whereas the association with social fragmentation remained only for non-movers. At the between-person level, an IQR higher noise was associated with a 0.100 IQR (95% CI: 0.031, 0.169) more externalising problems, while higher deprivation (β = 0.080; 95% CI: 0.022, 0.138) and lower fragmentation (β = -0.073; 95% CI: -0.128, -0.018) were associated with more internalising problems. We also observed positive between-person associations between PM2.5, noise, and internalising problems, but both associations were unstable due to the high PM2.5-noise correlation. Further, we observed a non-linear between-person PM2.5-externalising problems association turning positive when PM2.5 > 15 µg/m3. Null associations were found for green space.

CONCLUSION

Our findings suggested that air pollution, noise, and neighbourhood deprivation are risk factors for adolescent mental health. Not only exposure levels but also exposure changes matter for adolescent mental health.

Atopic dermatitis is associated with abnormal stool form: a population-based cross-sectional study in college students

BACKGROUND

Atopic dermatitis (AD) is a chronic inflammatory skin disorder. Bristol Stool Form Scale (BSFS) is a widely used stool scoring method that could indirectly reflect intestinal function.

OBJECTIVES

To evaluate the associations of AD with BSFS.

METHODS

This was a population-based cross-sectional study of freshmen in five universities of China. AD diagnosis was performed by dermatologists according to the guideline from the American Academy of Dermatology. BSFS and covariates were collected through an online questionnaire survey. Chronic itch scores were assessed by the numeric rating scales and grouped into quartiles (Q). Mixed logistic regression models were used. Subgroup analysis was conducted by covariates. P value < 0.05 was considered statistically significant.

RESULTS

The prevalence of hard stools and loose stools were 8.9% and 7.6%, respectively (20,049 participants). After adjusting covariates, AD was significantly associated with hard stools (OR = 1.38, P < 0.001) and loose stools (OR = 1.24, P = 0.037). In subgroup analysis of hard stool, a stronger effect was observed in intake of milk (> 3 days/week), yogurt (> 3 days/week), pork (< 1 day/week), and higher itch scores (Q4).

CONCLUSION

This study found the relationship between AD and abnormal stool forms, and the association with hard stools might be modified by dietary factor.

Association of joint exposure to various ambient air pollutants during adolescence with blood pressure in young adulthood

The association of various air pollutants exposure during adolescence with blood pressure (BP) in young adulthood is uncertain. We intended to evaluate the long-term association of individual and joint air pollutants exposure during adolescence with BP in young adulthood. This cross-sectional study of incoming students was conducted in five geographically disperse universities in China during September and October 2018. Mean concentrations of particulate matter with diameters ≤2.5 μm (PM2.5 ), ≤10 μm (PM10 ), nitrogen dioxides (NO2 ), carbon monoxide (CO), sulfur dioxide (SO2 ), and ozone (O3 ) at participants' residential addresses during 2013-2018 were collected from the Chinese Air Quality Reanalysis dataset. Generalized linear mixed models (GLM) and quantile g-computation (QgC) models were utilized to estimate the association between individual and joint air pollutants exposure and systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse pressure (PP). A total of 16,242 participants were included in the analysis. The GLM analyses showed that PM2.5 , PM10 , NO2 , CO, and SO2 were significantly positively associated with SBP and PP, while O3 was positively associated with DBP. The QgC analyses indicated that long-term exposure to a mixture of the six air pollutants had a significant positive joint association with SBP and PP. In conclusion, air pollutant co-exposure during adolescence may influence BP in young adulthood. The findings of this study emphasized the impacts of multiple air pollutants interactions on potential health and the need of minimizing pollution exposures in the environment.

Occupational characteristics and incident anxiety and depression: A prospective cohort study of 206,790 participants

BACKGROUND

This study aimed to analyze the impact of a wide spectrum of occupational characteristics on the incidence of anxiety and depression, and to determine the features affecting adaptation to specific characteristics.

METHODS

Participants in paid employment or self-employed at baseline in UKB were included, with occupational characteristics extracted from O*NET. Cox-proportional-hazard models were conducted in the main analyses and subgroup analyses.

RESULTS

Direct work with the public and exposure to disease/infections were first time demonstrated to be risk factors for both anxiety and depression, along with occupations involving more physical activities and dealing with unpleasant/physically aggressive people. Protective factors for both: time spent sitting, communication, decision making, creativity and reasoning, and responsibility in work. Protective factors for anxiety only: Coordinating/leading, fluency of ideas, originality, problem sensitivity, decision latitude, and time pressure. Risk factor for depression only: Exposure to contaminants. Females were found more sensitive to dealing with unpleasant/physically aggressive people. The impact of exposure to disease/infections was more significant among those with lower education levels. Those with BMI over 24 were more sensitive to the risk factors.

LIMITATIONS

The short-term effect of the above exposures remained unclear. The scores of occupational characteristics were based on self-reported questionnaires. There was the potential for undiagnosed anxiety or depression events. The participants included only those aged from 40 to 69. Participants included in this cohort were mainly White British.

CONCLUSIONS

Our findings advocate closer monitoring of the mental health of workers with risk work-related factors.

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.

Affective disorder and brain alterations in children and adolescents exposed to outdoor air pollution

BACKGROUND

Childhood and adolescence are critical periods for the development of the brain. However, a limited number of studies have explored how air pollution may associate with affective symptoms in youth.

METHODS

We performed a comprehensive review of the existing research on the associations between outdoor air pollution and affective disorders, suicidality, and the evidence for brain changes in youth. PRISMA guidelines were followed and PubMed, Embase, Web of Science, Cochrane Library, and PsychINFO databases were searched from their inception to June 2022.

RESULTS

From 2123 search records, 28 papers were identified as being relevant for studying the association between air pollution and affective disorders (n = 14), suicide (n = 5), and neuroimaging-based evidence of brain alterations (n = 9). The exposure levels and neuropsychological performance measures were highly heterogeneous and confounders including traffic-related noise, indoor air pollution, and social stressors were not consistently considered. Notwithstanding, 10 out of the 14 papers provide evidence that air pollution is associated with increased risk of depression symptoms, and 4 out of 5 papers provide evidence that air pollution might trigger suicidal attempts and behaviors. Besides, 5 neuroimaging studies revealed decreased gray-matter volume in the Cortico-Striato-Thalamo-Cortical neurocircuitry, and two found white matter hyperintensities in the prefrontal lobe.

CONCLUSIONS

Outdoor air pollution is associated with increased risks of affective disorders and suicide in youth, and there is evidence for associated structural and functional brain abnormalities. Future studies should determine the specific effects of each air pollutant, the critical exposure levels, and population susceptibility.

Association of air pollution and genetic risks with incidence of elderly-onset atopic dermatitis: A prospective cohort study

BACKGROUND

Elderly-onset atopic dermatitis (AD) is a remarkable subtype and has been put on the agenda owing to its difficulty to control. Understanding the influence of genetic and environmental exposures is crucial to preventing elderly-onset AD.

OBJECTIVES

To explore the association between genes and air pollution on incident elderly-onset AD.

MATERIAL AND METHODS

This study was based on UK Biobank that recruited over 500,000 participants. The genetic risks were categorized into low, intermediate, and high groups according to tertiles of polygenic risk scores. Mixed exposure to various air pollutants was assessed using the weighted quantile sum (WQS) and also categorized based on tertiles. Within each genetic risk group, whether air pollutant mixture was associated with incident elderly-onset AD was estimated.

RESULTS

337,910 participants were included in the final analysis, and the mean age was 57.1. The median years for follow-up were 12.0, and the incident cases of AD were 2545. The medium and high air pollution mixture was significantly associated with incident AD compared with the low pollution group, with HRs of 1.182 (P = 0.003) and 1.359 (P < 0.001), respectively. In contrast, HR for medium and high genetic susceptibility was only 1.065 (P = 0.249) and 1.153 (P = 0.008). The population-attributable fraction of air pollution and genetic risk was 15.5 % (P < 0.001) and 6.4 % (P = 0.004). Additionally, compared with low genetic risk and low air pollution, high genetic risk and high air pollution was significantly associated with the incidence of elderly-onset AD with a HR of up to 1.523 (P < 0.001). There were no interactive effects between each group of genetic risks and air pollution. When grouped by sex, females could observe a stronger effect by genetic and air pollutant mixture exposure.

CONCLUSION

Air pollution and genetics both independently enhance the risk of newly developed AD, and the effect of air pollutants is stronger than the investigated genes.

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.

Nitrogen dioxide and hospital length of stay and cost for systemic lupus erythematosus in Hunan, China

BACKGROUND

Evidence of both epidemiological and clinical studies exploring the impact of nitrogen dioxide (NO₂) on the systemic lupus erythematosus (SLE) disease activity have been contradictory.

OBJECTIVES

To evaluate the association between short-term NO₂ exposure and length of hospital stay (LOS) and hospital cost of SLE and estimate the burden of disease attributable to NO₂ exposure.

METHODS

We collected health data of SLE inpatients who were hospitalized at secondary and tertiary hospitals in Hunan province of China during 2017-2019. Daily ambient concentrations of air pollutants (O₃, CO, NO₂, SO₂, PM_2.5 and PM₁₀) and other environmental factors were obtained from public repositories by linking to individual addresses and date of hospitalization. Mixed effect models were employed to assess the associations between LOS and hospital cost for SLE inpatients and NO₂ exposures during the previous 1 to 21 days (lag₁-lag₂₁) before hospitalization. We further estimated excess LOS and hospital cost attributable to NO₂ exposure according to China's and World Health Organization's air quality guideline (AQG) respectively.

RESULTS

A total of 11,447 records from 221 hospitals were finally included in our study. After full adjustments, 1 μg/m³ increment of NO₂ was significantly associated with 0.038 day increase in LOS (95%CI: 0.0159-0.0601, P = 0.0008) and 0.0384 thousand yuan increase in hospital cost (95%CI: 0.0017-0.0679, P = 0.0395) with a lagged effect of 7 days prior to admission. Based on the adjusted effects of lag₇, controlling for short-term NO₂ exposure according to AQG could avoid up to 1.47 thousand days of hospitalization and 1.35 million yuan of cost for SLE in Hunan province during 2017 to 2019.

CONCLUSIONS

Excess LOS and substantial economic burden among SLE inpatients attributable to NO₂ could be avoid if policies were implemented to reduce the exposure.

Spatiotemporal Analysis of Black Carbon Sources: Case of Santiago, Chile, under SARS-CoV-2 Lockdowns

BACKGROUND

The SARS-CoV-2 pandemic has temporarily decreased black carbon emissions worldwide. The use of multi-wavelength aethalometers provides a quantitative apportionment of black carbon (BC) from fossil fuels (BCff) and wood-burning sources (BCwb). However, this apportionment is aggregated: local and non-local BC sources are lumped together in the aethalometer results.

METHODS

We propose a spatiotemporal analysis of BC results along with meteorological data, using a fuzzy clustering approach, to resolve local and non-local BC contributions. We apply this methodology to BC measurements taken at an urban site in Santiago, Chile, from March through December 2020, including lockdown periods of different intensities.

RESULTS

BCff accounts for 85% of total BC; there was up to an 80% reduction in total BC during the most restrictive lockdowns (April-June); the reduction was 40-50% in periods with less restrictive lockdowns. The new methodology can apportion BCff and BCwb into local and non-local contributions; local traffic (wood burning) sources account for 66% (86%) of BCff (BCwb).

CONCLUSIONS

The intensive lockdowns brought down ambient BC across the city. The proposed fuzzy clustering methodology can resolve local and non-local contributions to BC in urban zones.

The impact of black carbon (BC) on mode-specific galvanic skin response (GSR) as a measure of stress in urban environments

Previous research has shown that walking and cycling could help alleviate stress in cities, however there is poor knowledge on how specific microenvironmental conditions encountered during daily journeys may lead to varying degrees of stress experienced at that moment. We use objectively measured data and a robust causal inference framework to address this gap. Using a Bayesian Doubly Robust (BDR) approach, we find that black carbon exposure statistically significantly increases stress, as measured by Galvanic Skin Response (GSR), while cycling and while walking. Augmented Outcome Regression (AOR) models indicate that greenspace exposure and the presence of walking or cycling infrastructure could reduce stress. None of these effects are statistically significant for people in motorized transport. These findings add to a growing evidence-base on health benefits of policies aimed at decreasing air pollution, improving active travel infrastructure and increasing greenspace in cities.

Long-term exposure to ambient black carbon is associated with sleep disturbance in college students

BACKGROUND

Evidence suggests an association of air pollution with sleep quality. However, there is limited knowledge regarding the effect of black carbon, a key component of ambient particulate matter, on sleep.

OBJECTIVES

To investigate the association of long-term exposure to black carbon and sleep quality in a group of college students.

METHODS

A retrospective cohort study was conducted in five universities in different regions of China. The concentrations of black carbon and other environment factors were defined as the averages during the 6 years prior to the recruitment. Averagely daily dose of black carbon exposure was estimated according to the respiratory rate. Sleep quality was measured by the Pittsburgh Sleep Quality Index (PSQI) with a cutoff >5 indicating sleep disturbance. Linear regression and logistic regression models were used to estimate the association. The sensitivity analyses were conducted to estimate the effects of 1-month, 6-month and 1-year mean levels of exposure to black carbon on sleep quality.

RESULTS

A total of 20,053 incoming college students were included. 29.3% reported impaired sleep quality, with a mean PSQI score of 4.3 ± 2.2. The logistic regression showed that the risk of impaired sleep quality was positively associated with black carbon exposure, especially in the highest quantile (OR: 1.26, 95% CI: 1.11-1.43) compared with the lowest quartile after adjusting for potential confounders. Subgroup analysis showed that the effect of black carbon on sleep quality was stronger in participants with higher BMI, lower household income, and lower parental educational level. The results of sensitivity analyses were similar with main analyses.

CONCLUSION

Long-term exposure to black carbon is associated with sleep disturbance in college students. Improvement of air quality may help improve sleep quality.

Synergistic Effects between Ambient Air Pollution and Second-Hand Smoke on Inflammatory Skin Diseases in Chinese Adolescents

Atopic dermatitis (AD), chronic hand eczema (CHE), and urticaria are common inflammatory skin diseases among adolescents and associated with air quality. However, the synergistic effects of ambient air pollution and second-hand smoke (SHS) have been unclear. We conducted a cross-sectional study including 20,138 Chinese college students where dermatological examinations and a questionnaire survey were carried out. A generalized linear mixed model was applied for the association between individualized exposure of O3, CO, NO2, SO2, PM2.5, and PM10 and the prevalence of inflammatory skin diseases. Interactions between air pollutants and SHS were analyzed. As a result, CO, NO2, SO2, PM2.5, and PM10 were positively correlated with the prevalence of AD, CHE, and urticaria. Higher frequency of SHS exposure contributed to increased probabilities of AD (p = 0.042), CHE (p < 0.001), and urticaria (p = 0.002). Of note, CO (OR: 2.57 (1.16−5.69) in third quartile) and NO2 (OR: 2.38 (1.07−5.27) in third quartile) had positive interactions with SHS for AD, and PM2.5 synergized with SHS for CHE (OR: 2.25 (1.22−4.15) for second quartile). Subgroup analyses agreed with the synergistic results. In conclusion, SHS and ambient air pollution are both associated with inflammatory skin diseases, and they have a synergistic effect on the prevalence of AD and CHE.

Effect of time-activity patterns and microenvironments on the personal exposure of undergraduate students to black carbon

In this study, the personal exposure to and potential dose of black carbon (BC) of undergraduate students (22-27 years old, nonsmokers) were determined. BC was continuously measured by a portable device (microAeth^® AE51) for four consecutive days in Istanbul between April and May 2019. The time-activity diaries filled out by each volunteer were assessed to define the activities and microenvironments (home, school, transportation and entertainment) that contributed to daily BC exposure. The overall mean concentration of BC was 2.0 μg/m³, and the mean concentrations on weekdays and weekends were 3.0 μg/m³ and 1.1 μg/m³, respectively. Transportation made the highest contribution to mean BC exposure (42%) and dose (45.8%) on weekdays, while the contributions of home-based activities to BC exposure (66.1%) and dose (63.2%) were higher on weekends. Students had the most intense exposure to (2.8% and 4.6%) and dose (3.1% and 5.8%) of BC in transportation both on weekdays and on weekends, respectively. Between transportation modes, the mean BC concentration was the highest for minibuses (14.8 μg/m³), while walking made the largest contribution to BC exposure (16.8%) on weekdays. Students spent 12.8% of their weekdays at school, and the contributions of the school environment to BC exposure and dose were 8.5% and 7%, respectively. Exposure to BC increased during cooking and eating activities in microenvironments such as the kitchen, cafe and dining hall.

Analysis of PM2.5 Variations Based on Observed, Satellite-Derived, and Population-Weighted Concentrations

Fine particulate matter (PM2.5), which can cause adverse human health effects, has been proven as the first air pollutant in China. In situ observations with ground-level monitoring and satellite-based concentrations have been used to analyze the variations in PM2.5. However, variation analyses based on these two kinds of measurement have mainly focused on the concentration itself and ignored the effects on the population. Therefore, this study not only investigated these two kinds of measurements, but also performed weighted population analyses to study the variations in PM2.5. Firstly, daily models of timely structure adaptive modeling (TSAM) were constructed to simulate satellite-derived PM2.5 levels from January 2013 to December 2016. Secondly, population-weighted concentrations were calculated based on TSAM-derived PM2.5 surfaces. Finally, observed, TSAM-derived, and population-weighted concentrations were used to analyze the variations in PM2.5. The results showed the different importance of various input parameters; AOD had the highest rank. Additionally, TSAM models demonstrated good performance, fitting R ranging from 0.86 to 0.91, and validating R from 0.82 to 0.89. According to the air quality standard in China, TSAM-derived PM2.5 showed that the increase in area lower than Level II was 29.03% and the increase in population was only 14.81%. This indicates that the air quality exhibited an overall improvement in spatial perspective, but some areas with high population density showed a relatively low improvement due to uneven distributions in China. The population-weighted PM2.5 concentration could better represent the health threats of air pollutants compared with in situ observations.

Short-Term exposure to ambient air pollution and onset of work incapacity related to mental health conditions

The OECD estimates that greater work absenteeism is one of the main drivers behind the impact of air pollution on gross domestic product loss, but research linking air pollution with work absenteeism is scarce. With air pollution increasingly being linked to poor mental health, and poor mental health having become one of the main reasons for work absenteeism, we examined whether the onset of work incapacity related to mental health conditions is associated with short-term fluctuations in ambient black carbon (BC), nitrogen dioxide (NO₂), ozone (O₃), and particulate matter 2.5 (PM_2.5), estimating the contributions of these pollutants jointly, while accounting for relative humidity, total solar radiation and temperature. We conducted a bidirectional time-stratified case-crossover study with daily air pollution estimates by municipality linked with 12 270 events of work incapacity related to mental health conditions in 2019 in Belgium. We ran single- and multi-pollutant conditional logistic regression models for three different exposure windows (lag 0, 0-1 and 0-2), considering potential confounding by relative humidity and total solar radiation. We observed positive associations between work incapacity related to mental health conditions and BC, NO₂, and O₃ exposure, but findings for PM_2.5 were inconsistent. Results from multi-pollutant models showed a 12% higher risk of work incapacity for an IQR increase in NO₂ and O₃ at the day of the event (lag 0), with estimates increasing to about 26% for average concentrations up to two days before the event (lag 0-2). We found evidence for effect modification by age and season in the association with NO₂, with highest effect estimates in the age group 40-49 years and in spring and summer. For O₃, we observed effect modification by type of mental health problem. This country-wide study suggests that air pollution aggravates within 48 h a likely existing propensity to enter work incapacity because of mental health conditions.

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.

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.

Exposure to multiple trace elements and miscarriage during early pregnancy: A mixtures approach

BACKGROUND

Exposure to some conventional trace elements has been found to be associated with miscarriage; however, evidence for combined exposure is inconclusive. Therefore, it is important to explore the joint associations between toxic and essential trace elements and miscarriage.

METHODS

This cross-sectional study measured a wide range of element levels in the whole blood of pregnant women by using inductively coupled plasma mass spectrometry. The associations between individual elements and miscarriage were appraised using logistic regression model. Multi-exposure models, including Bayesian kernel machine regression (BKMR) and weighted quantile sum regression (WQS), were used to explore the mixed exposure to elements. Furthermore, grouped weighted quantile sum (GWQS) considered multiple elements with different magnitudes and directions of associations.

RESULTS

In logistic regression, the odds ratios (ORs) with a 95% confidence interval (CI) in the highest quartiles were 5.45 (2.00, 15.91) for barium, 0.28 (0.09, 0.76) for copper, and 0.32 (0.12, 0.83) for rubidium. These exposure-outcome associations were confirmed and supplemented by BKMR, which indicated a positive association for barium and negative associations for copper and rubidium. In WQS, a positive association was found between mixed elements and miscarriage (OR: 1.71; 95% CI: 1.07, 2.78), in which barium (75.7%) was the highest weighted element. The results of GWQS showed that the toxic trace element group dominated by barium was significantly associated with increased ORs (OR: 2.71; 95% CI: 1.74, 4.38). Additionally, a negative association was observed between the essential trace element group and miscarriage (OR: 0.32; 95% CI: 0.18, 0.54), with rubidium contributing the most to the result.

CONCLUSIONS

As a toxic trace element, barium was positively associated with miscarriage both by individual and multiple evaluations, while essential trace elements, particularly rubidium and copper, exhibited negative associations. Our findings provide significant evidence for exploring the effects of trace elements on miscarriage.

PM2.5 Concentration Exposure over the Belt and Road Region from 2000 to 2020

Ambient fine particulate matter (PM_2.5) can cause respiratory and heart diseases, which have a great negative impact on human health. While, as a fast-developing region, the Belt and Road (B&R) has suffered serious air pollution, more detailed information has not been revealed. This study aims to investigate the evolutionary relationships between PM_2.5 air pollution and its population-weighted exposure level (PWEL) over the B&R based on satellite-derived PM_2.5 concentration and to identify the key regions for exposure control in the future. For this, the study focused on the B&R region, covering 51 countries, ranging from developed to least developed levels, extensively evaluated the different development levels of PM_2.5 concentrations during 2000–2020 by spatial-temporal trend analysis and bivariate spatial correlation, then identified the key regions with high risk under different levels of Air Quality Guidelines (AQG). Results show that the overall PM_2.5 and PWEL of PM_2.5 concentration remained stable. Developing countries presented with the heaviest PM_2.5 pollution and highest value of PWEL of PM_2.5 concentration, while least developed countries presented with the fastest increase of both PM_2.5 and PWEL of PM_2.5 concentration. Areas with a high level and rapid increase PWEL of PM_2.5 concentration were mainly located in the developing countries of India, Bangladesh, Nepal, and Pakistan, the developed country of Saudi Arabia, and least developed countries of Yemen and Myanmar. The key regions at high risk were mainly on the Indian Peninsula, Arabian Peninsula, coastal area of the Persian Gulf, northwestern China, and North China Plain. The findings of this research would be beneficial to identify the spatial distributions of PM_2.5 concentration exposure and offer suggestions for formulating policies for the prevention and control PM_2.5 air pollution at regional scale by the governments.

Association of exposure to artificial light at night with atopic diseases: A cross-sectional study in college students

The impact of artificial light at night (ALAN) exposure on health has become increasingly prominent. However, little is known about the effect of ALAN exposure on atopic diseases. In this study, a cross-sectional analysis of incoming students was conducted in 5 geographically disperse universities which locate in Changsha (south), Wuhan (central), Xiamen (east), Urumchi (west), and Hohhot (north), respectively. All incoming students who consented to participate were recruited, followed by a health examination and a questionnaire survey. Prevalent atopic diseases were diagnosed by clinicians. Mean ALAN (nanoWatts/cm²/sr) during their adolescence was obtained from the remote sensing observed nighttime light data matching with their residence information, which was obtained from survey. Mixed generalized linear models (log-binomial) were used to estimate the associations, in terms of prevalence ratio (PR) with 95% confidence interval (CI). A total of 20106 participants were included in the analysis. Based on previous work, we chose factors including socioeconomic status, behavioural factors, major air pollutants, and air climatic parameters for adjustment. After full adjustment, the PR for atopic diseases was 1.35 (95% CI: 1.27-1.42; P < 0.001). The effect size of ALAN was the largest for asthma (PR = 1.80; 95% CI: 1.48-2.19; P < 0.001), followed by atopic rhinitis (PR = 1.42; 95% CI: 1.33-1.51; P < 0.001), and atopic dermatitis (PR = 1.20; 95% CI: 1.06-1.35; P = 0.003). Subgroup analyses by covariates showed consistent results. This study revealed that exposure to ALAN during adolescence may contribute to a higher risk of atopic diseases in young adulthood.