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Nationwide longitudinal evidence linking cognitive decline with exposure to fine particulate matter (PM2.5) constituents remains scarce in China. By constructing a dynamic cohort based on the China Health and Retirement Longitudinal Study, we aimed to assess individual and joint associations of PM2.5 constituents with cognitive function among middle-aged and older adults in China. Linear mixed-effects models incorporated with quantile-based g-computation were applied to investigate individual and joint associations of long-term exposures to PM2.5 constituents with cognitive function. Among 13,507 respondents, we evaluated 38,950 follow-up records of cognitive function tests. Declines in global cognitive score associated with an interquartile range (IQR) increase in exposure were −1.477 (95% CI: −1.722, −1.232) for nitrate, followed by −1.331 (−1.529, −1.133) for ammonium, −1.033 (−1.184, −0.883) for sulfate, −0.988 (−1.144, −0.832) for organic matter and −0.822 (−0.946, −0.699) for black carbon. An IQR-equivalent increase in joint exposure to these PM2.5 constituents was associated with a decline of −1.353 (−1.659, −1.048) in global cognitive score. Female, younger, and well-educated individuals were at greater vulnerability to cognitive impairment related to individual and joint exposure to PM2.5 constituents. This study suggested that later-life exposures to PM2.5 constituents were associated with cognitive decline in middle-aged and older adults in China. [ABSTRACT FROM AUTHOR]

The effects of long-term exposure to fine particulate matter (PM2.5) constituents on chronic kidney disease (CKD) are not fully known. This study sought to examine the association between long-term exposure to major PM2.5 constituents and CKD and look for potential constituents contributing substantially to CKD. This study included 81,137 adults from the 2018 to 2019 baseline survey of China Multi-Ethnic Cohort. CKD was defined by the estimated glomerular filtration rate. Exposure concentration data of 7 major PM2.5 constituents were assessed by satellite remote sensing. Logistic regression models were used to estimate the effect of each PM2.5 constituent exposure on CKD. The weighted quantile sum regression was used to estimate the effect of mixed exposure to all constituents. PM2.5 constituents had positive correlations with CKD (per standard deviation increase), with ORs (95% CIs) of 1.20 (1.02–1.41) for black carbon, 1.27 (1.07–1.51) for ammonium, 1.29 (1.08–1.55) for nitrate, 1.20 (1.01–1.43) for organic matter, 1.25 (1.06–1.46) for sulfate, 1.30 (1.11–1.54) for soil particles, and 1.63 (1.39–1.91) for sea salt. Mixed exposure to all constituents was positively associated with CKD (1.68, 1.32–2.11). Sea salt was the constituent with the largest weight (0.36), which suggested its importance in the PM2.5-CKD association, followed by nitrate (0.32), organic matter (0.18), soil particles (0.10), ammonium (0.03), BC (0.01). Sulfate had the least weight (< 0.01). Long-term exposure to PM2.5 sea salt and nitrate may contribute more than other constituents in increasing CKD risk, providing new evidence and insights for PM2.5-CKD mechanism research and air pollution control strategy. [ABSTRACT FROM AUTHOR]

Studies have demonstrated that fine particulate matter (PM2.5) is an underlying risk factor for type 2 diabetes mellitus (T2DM), but evidence exploring the relationship between PM2.5 chemical components and T2DM was extremely limited, to investigate the effects of long-term exposure to PM2.5 and its five constituents (sulfate [SO42−], nitrate [NO3−], ammonium [NH4+]), organic matter [OM] and black carbon [BC]) on incidence of T2DM. Based on the "Jinchang Cohort" platform, a total of 19,884 participants were selected for analysis. Daily average concentrations of pollutants were gained from Tracking Air Pollution in China (TAP). Cox proportional hazards regression models were utilized to estimate the hazard ratios (HR) and 95% confidence interval (CI) in single-pollutant models, restricted cubic splines functions were used to examine the dose–response relationships, and quantile g-computation (QgC) was applied to evaluate the combined effect of PM2.5 compositions on T2DM. Stratification analysis was also considered. A total of 791 developed new cases of T2DM were observed during a follow-up period of 45254.16 person-years. The concentrations of PM2.5, NO3−, NH4+, OM and BC were significantly associated with incidence of T2DM (P-trend < 0.05), with the HRs in the highest quartiles of 2.16 (95% CI 1.79, 2.62), 1.43 (95% CI 1.16, 1.75), 1.75 (95% CI 1.45, 2.11), 1.31 (95% CI 1.08, 1.59) and 1.79 (95% CI 1.46, 2.21), respectively. Findings of QgC model showed a noticeably positive joint effect of one quartile increase in PM2.5 constituents on increased T2DM morbidity (HR 1.27, 95% CI 1.09, 1.49), and BC (32.7%) contributed the most to the overall effect. The drinkers, workers and subjects with hypertension, obesity, higher physical activity, and lower education and income were generally more susceptible to PM2.5 components hazards. Long-term exposure to PM2.5 and its components (i.e., NO3−, NH4+, OM, BC) was positively correlated with T2DM incidence. Moreover, BC may be the most responsible for the association between PM2.5 constituents and T2DM. In the future, more epidemiological and experimental studies are needed to identify the link and potential biological mechanisms. [ABSTRACT FROM AUTHOR]

Background: While evidence suggests that PM2.5 is associated with overall prevalence of Metabolic (dysfunction)-Associated Fatty Liver Disease (MAFLD), effects of comprehensive air pollutant mixture on MAFLD and its subtypes remain unclear. Objective: To investigate individual and joint effects of long-term exposure to comprehensive air pollutant mixture on MAFLD and its subtypes. Methods: Data of 27,699 participants of the Chinese Cohort of Working Adults were analyzed. MAFLD and subtypes, including overweight/obesity, lean, and diabetes MAFLD, were diagnosed according to clinical guidelines. Concentrations of NO3–, SO42−, NH4+, organic matter (OM), black carbon (BC), PM2.5, SO2, NO2, O3 and CO were estimated as a weighted average over participants’ residential and work addresses for the three years preceding outcome assessment. Logistic regression and weighted quantile sum regression were used to estimate individual and joint effects of air pollutant mixture on presence of MAFLD. Results: Overall prevalence of MAFLD was 26.6 % with overweight/obesity, lean, and diabetes MAFLD accounting for 92.0 %, 6.4 %, and 1.6 %, respectively. Exposure to SO42−, NO3–, NH4+, BC, PM2.5, NO2, O3and CO was significantly associated with overall MAFLD, overweight/obesity MAFLD, or lean MAFLD in single pollutant models. Joint effects of air pollutant mixture were observed for overall MAFLD (OR = 1.10 [95 % CI: 1.03, 1.17]), overweight/obesity (1.09 [1.02, 1.15]), and lean MAFLD (1.63 [1.28, 2.07]). Contributions of individual air pollutants to joint effects were dominated by CO in overall and overweight/obesity MAFLD (Weights were 42.31 % and 45.87 %, respectively), while SO42− (36.34 %), SO2 (21.00 %) and BC (12.38 %) were more important in lean MAFLD. Being male, aged above 45 years and smoking increased joint effects of air pollutant mixture on overall MAFLD. Conclusions: Air pollutant mixture was associated with MAFLD, particularly the lean MAFLD subtype. CO played a pivotal role in both overall and overweight/obesity MAFLD, whereas SO42− were associated with lean MAFLD.

Abstract Objective Little is known about the magnitude of the relation of ambient fine particulate matter (PM2.5) constituents with hyperuricemia and serum uric acid (SUA) levels. Therefore, we aimed to assess the associations and to identify the most hazardous constituent. Methods This study included 72,840 participants from the China Multi-Ethnic Cohort. Annual average concentrations of PM2.5 mass and its major 7 constituents were matched to individuals by residential address. SUA levels exceeding 7.0 mg/dL (417 μmol/L) for men and 6.0 mg/dL (357 μmol/L) for women were considered to be hyperuricemia. Multiple logistic and linear regressions were performed on the association of single exposure to PM2.5 constituents with hyperuricemia and SUA, separately. The weighted quantile sum method was applied to examine the joint effect of PM2.5 constituents on hyperuricemia/SUA. Results Significant positive associations were discovered between PM2.5 constituents and SUA/hyperuricemia. For example, the odds ratio (95% confidence interval) of hyperuricemia for per standard deviation increase of PM2.5 mass, black carbon, organic matter, ammonium, and nitrate concentrations were 1.22 (1.12–1.32), 1.17 (1.08–1.27), 1.20 (1.10–1.31), 1.21 (1.11–1.31), and 1.28 (1.18–1.40), respectively. The joint exposure to PM2.5 constituents was significantly positively correlated with hyperuricemia (1.09, 1.05–1.14) and SUA (1.05, 1.03–1.06). And the weight of nitrate was the largest (0.668 for hyperuricemia, 0.586 for SUA). Conclusions Our findings suggest that long-term exposure to PM2.5 constituents is associated with increased SUA levels and a higher risk of hyperuricemia. In particular, nitrate seems to be the main contributor. This study may help prevent hyperuricemia by promoting the introduction of precise preventive measures. Graphical Abstract

Objective: Little is known about the magnitude of the relation of ambient fine particulate matter (PM2.5) constituents with hyperuricemia and serum uric acid (SUA) levels. Therefore, we aimed to assess the associations and to identify the most hazardous constituent. Methods: This study included 72,840 participants from the China Multi-Ethnic Cohort. Annual average concentrations of PM2.5 mass and its major 7 constituents were matched to individuals by residential address. SUA levels exceeding 7.0 mg/dL (417 μmol/L) for men and 6.0 mg/dL (357 μmol/L) for women were considered to be hyperuricemia. Multiple logistic and linear regressions were performed on the association of single exposure to PM2.5 constituents with hyperuricemia and SUA, separately. The weighted quantile sum method was applied to examine the joint effect of PM2.5 constituents on hyperuricemia/SUA. Results: Significant positive associations were discovered between PM2.5 constituents and SUA/hyperuricemia. For example, the odds ratio (95% confidence interval) of hyperuricemia for per standard deviation increase of PM2.5 mass, black carbon, organic matter, ammonium, and nitrate concentrations were 1.22 (1.12–1.32), 1.17 (1.08–1.27), 1.20 (1.10–1.31), 1.21 (1.11–1.31), and 1.28 (1.18–1.40), respectively. The joint exposure to PM2.5 constituents was significantly positively correlated with hyperuricemia (1.09, 1.05–1.14) and SUA (1.05, 1.03–1.06). And the weight of nitrate was the largest (0.668 for hyperuricemia, 0.586 for SUA). Conclusions: Our findings suggest that long-term exposure to PM2.5 constituents is associated with increased SUA levels and a higher risk of hyperuricemia. In particular, nitrate seems to be the main contributor. This study may help prevent hyperuricemia by promoting the introduction of precise preventive measures. Highlights: Considering the constituents of PM2.5 in assessing its toxicity and health effects. Exposure to PM2.5 constituents was related with serum uric acid and hyperuricemia. Nitrate contributed most to serum uric acid levels and hyperuricemia. The results of joint effects were verified by two different statistical methods. A large-scale sample of nearly 100,000 subjects from diverse ethnic backgrounds. [ABSTRACT FROM AUTHOR]

Little is known concerning the associations of fine particulate matter (PM2.5) and its constituents with atherosclerotic cardiovascular disease (ASCVD). A total of 31,162 participants enrolled from the Henan Rural Cohort were used to specify associations of PM2.5 and its constituents with ASCVD. Hybrid machine learning was utilized to estimate the 3-year average concentration of PM2.5 and its constituents (black carbon [BC], nitrate [NO3−], ammonium [NH4+], inorganic sulfate [SO42−], organic matter [OM], and soil particles [SOIL]). Constituent concentration, proportion, and residual models were utilized to examine the associations of PM2.5 constituents with 10-year ASCVD risk and to identify the most hazardous constituent. The isochronous substitution model (ISM) was employed to analyze the substitution effect between PM2.5 constituents. We found that each 1 μg/m3 increase in PM2.5, BC, NH4+, NO3−, OM, SO42−, and SOIL was associated with a 3.5%, 49.3%, 19.4%, 10.5%, 21.4%, 14%, and 28.5% higher 10-year ASCVD risk, respectively (all p < 0.05). Comparable results were observed in proportion and residual models. The ISM found that replacing BC with other constituents will generate the greatest health benefits. The results indicated that long-term exposure to PM2.5 and its constituents were associated with increased risks of ASCVD, with BC being the most attributable constituent. [ABSTRACT FROM AUTHOR]

Background: The association of specific PM2.5 chemical constituents with childhood overweight or obesity (OWOB) remain unclear. Furthermore, the long-term impacts of PM2.5 exposure on the trajectory of children's body mass index (BMI) have not been explored. Methods: We conducted a longitudinal study among 1,450,830 Chinese children aged 6–19 years from Beijing and Zhongshan in China during 2005–2018 to examine the associations of PM2.5 and its chemical constituents with incident OWOB risk. We extracted PM2.5 mass and five main component exposure from Tracking Air Pollution in China (TAP) dataset. Cox proportional hazards models were applied to quantify exposure–response associations. We further performed principal component analysis (PCA) to handle the multi-collinearity and used quantile g-computation (QGC) approach to analyze the impacts of exposure mixtures. Additionally, we selected 125,863 children with at least 8 physical examination measurements and combined group-based trajectory models (GBTM) with multinomial logistic regression models to explore the impacts of exposure to PM2.5 mass and five constituents on BMI and BMI Z-score trajectories during 6–19 years. Results: We observed each interquartile range increment in PM2.5 exposure was significantly associated with a 5.1 % increase in the risk of incident OWOB (95 % confidence Interval [CI]: 1.036–1.066). We also found black carbon, sulfate, organic matter, often linked to fossil combustion, had comparable or larger estimates of the effect (HR = 1.139–1.153) than PM2.5. Furthermore, Exposure to PM2.5 mass, sulfate, nitrate, ammonium, organic matter and black carbon was significantly associated with an increased odds of being in a larger BMI trajectory and being assigned to persistent OWOB trajectory. Conclusions: Our findings provide evidence that the constituents mainly from fossil fuel combustion may have a perceptible influence on increased OWOB risk associated with PM2.5 exposure in China. Moreover, long-term exposure to PM2.5 contributes to an increased odds of being in a lager BMI and a persistent OWOB trajectories.

BackgroundEpidemiological findings are inconsistent regarding the associations between air pollution exposure during pregnancy and gestational diabetes mellitus (GDM). Several limitations exist in previous studies, including potential outcome and exposure misclassification, unassessed confounding, and lack of simultaneous consideration of air pollution mixtures and particulate matter (PM) constituents.ObjectivesTo assess the association between GDM and maternal residential exposure to air pollution, and the joint effect of the mixture of air pollutants and PM constituents.MethodsDetailed clinical data were obtained for 395,927 pregnancies in southern California (2008-2018) from Kaiser Permanente Southern California (KPSC) electronic health records. GDM diagnosis was based on KPSC laboratory tests. Monthly average concentrations of fine particulate matter

Background: Short-term exposure to fine particulate matter (PM2.5) and its specific constituents might exacerbate allergic rhinitis (AR) conditions. However, the evidence is still inconclusive. Method: We conducted a panel study of 49 patients diagnosed with AR > 1 year prior to the study in Taiyuan, China, to investigate associations of individual exposure to PM2.5 and its constituents with oxidative parameters, symptoms, and quality of life among AR patients. All participants underwent repeated assessments of health and PM exposure at 4 time points in both the heating and nonheating seasons from June 2017 to January 2018. AR patients’ oxidative parameters were assessed using nasal lavage, and their subjective symptoms and quality of life were determined through in-person interviews using a structured questionnaire. Short-term personal exposure to PM2.5 and its constituents was estimated using the time-microenvironment-activity pattern and data from the nearest air sampler, respectively. We applied mixed-effects regression models to estimate the short-term effects of PM2.5 and its constituents. Results: The results showed that exposure to PM2.5 and its constituents, including BaP, PAHs, SO42−, NH4+, V, Cr, Cu, As, Se, Cd, and Pb, was significantly associated with increased oxidative stress, as indicated by an increase in the malondialdehyde (MDA) index. Exposure to PM2.5 and its components (V, Mn, Fe, Zn, As, and Se) was associated with decreased antioxidant activity, as indicated by a decrease in the superoxide dismutase (SOD) index. Additionally, increased visual analog scale (VAS) and rhinoconjunctivitis quality of life questionnaire (RQLQ) scores indicated that exposure to PM2.5 and its constituents exacerbated inflammatory symptoms and affected quality of life in AR patients. Conclusion: Exposure to PM2.5 and specific constituents, could exacerbate AR patients' inflammatory symptoms and adversely affect their quality of life in the heavily industrialized city of Taiyuan, China. These findings may have potential biological and policy implications.

Mounting studies explored associations between fine particulate matter (PM2.5) and preterm birth (PTB); however, individual and combined impacts of PM2.5 constituents on PTB were less known. PM2.5 and its seven constituents were assessed by V4.CH.02 product of the Dalhousie University Atmospheric Composition Analysis Group, a dataset containing combined geophysical-statistical estimates of PM2.5 across China. Effects of PM2.5 and its constituents on PTB and gestational age were firstly explored. Furthermore, weighted quantile sum (WQS) regression was conducted to reveal the impacts of total PM2.5 mass and identify contributing constituents. An interquartile range (IQR) increase in PM2.5 was associated with increased odds ratio (OR) of PTB. PM2.5 constituents were widely associated with PTB and reduced gestational age, with different time window. The total mass of PM2.5 (per IQR increment) in the first and the second trimester was positively associated with PTB by WQS regression (Trimester 1: OR = 1.38, 95%CI: 1.15, 1.65; Trimester 2: OR = 1.47, 95%CI: 1.21, 1.79). The most contributing factors were black carbon in the first trimester and sulphate ion in the second trimester, respectively. Especially, sea salt was identified as contributing constituent during the first trimester. The study indicated that prenatal exposure to PM2.5 and its constituents was individually and jointly associated with PTB and reduced gestational age. Sea salt was firstly identified as a risk factor of PTB in the seaside city, which needs further exploration. [ABSTRACT FROM AUTHOR]

Background: Exposure to particulate matter with aerodynamic diameters less than 2.5 µm (PM2.5) may increase the risk of 10-year atherosclerotic cardiovascular disease (ASCVD) risk. While PM2.5 is comprised of various components, the evidence on the correlation of its components with 10-year ASCVD risk and which component contributes most remains limited. Methods: Data were derived from the baseline assessments of China Multi-Ethnic Cohort (CMEC). In total, 69,722 individuals aged 35–74 years were included into this study. The annual average concentration of PM2.5 and its components (black carbon, ammonium, nitrate, sulfate, organic matter, soil particles, and sea salt) were estimated by satellite remote sensing and chemical transport models. The ASCVD risk of individuals was calculated by the equations from the China-PAR Project (prediction for ASCVD risk in China). The relationship between single exposure to PM2.5 and its components and predicted 10-year ASCVD risk was assessed using the logistic regression model. The effect of joint exposure was estimated, and the most significant contributor was identified using the weighted quantile sum approach. Results: Totally 69,722 participants were included, of which 95.8 % and 4.2 % had low and high 10-year ASCVD risk, respectively. Per standard deviation increases in the 3-year average concentration of PM2.5 mass (odds ratio [OR] 1.23, 95 % confidence interval [CI]: 1.12–1.35), black carbon (1.21, 1.11–1.33), ammonium (1.21, 1.10–1.32), nitrate (1.25, 1.14–1.38), organic matter (1.29, 1.18–1.42), sulfate (1.17, 1.07–1.28), and soil particles (1.15, 1.04–1.26) were related to high 10-year ASCVD risk. The overall effect (1.19, 1.11–1.28) of the PM2.5 components was positively associated with 10-year ASCVD risk, and organic matter had the most contribution to this relationship. Female participants were more significantly impacted by PM2.5, black carbon, ammonium, nitrate, organic matter, sulfate, and soil particles compared to others. Conclusion: Long-term exposure to PM2.5 mass, black carbon, ammonium, nitrate, organic matter, sulfate, and soil particles were positively associated with high 10-year ASCVD risk, while sea salt exhibited a protective effect. Moreover, the organic matter might take primary responsibility for the relationship between PM2.5 and 10-year ASCVD risk. Females were more susceptible to the adverse effect.

Background: Ambient particulate matter with aerodynamic diameter ≤ 2.5 µm (PM2.5) consists of various toxic constituents. However, the health effect of PM2.5 may differ depending on its constituents, but the joint effect of PM2.5 constituents remains incompletely understood. Objective: Our goal was to evaluate the joint effect of long-term PM2.5 constituent exposures on dyslipidemia and identify the most hazardous chemical constituent. Methods: This study included 67,015 participants from the China Multi-Ethnic Cohort study. The average yearly levels of PM2.5 constituents for all individuals at their residences were assessed through satellite remote sensing and chemical transport modeling. Dyslipidemia was defined as one or more following abnormal blood lipid concentrations: total cholesterol (TC) ≥ 6.22 mmol/L, triglycerides (TG) ≥ 2.26 mmol/L, high-density lipoprotein cholesterol (HDL-C)

Growing evidence suggests that fine particulate matter (PM2.5) likely increases the risks of dementia, yet little is known about the relative contributions of different constituents. Here, we conducted a nationwide population-based cohort study (2000 to 2017) by integrating the Medicare Chronic Conditions Warehouse database and two independently sourced datasets of high-resolution PM2.5 major chemical composition, including black carbon (BC), organic matter (OM), nitrate (NO3 -), sulfate (SO4 2-), ammonium (NH4 +), and soil dust (DUST). To investigate the impact of long-term exposure to PM2.5 constituents on incident all-cause dementia and Alzheimer's disease (AD), hazard ratios for dementia and AD were estimated using Cox proportional hazards models, and penalized splines were used to evaluate potential nonlinear concentration-response (C-R) relationships. Results using two exposure datasets consistently indicated higher rates of incident dementia and AD for an increased exposure to PM2.5 and its major constituents. An interquartile range increase in PM2.5 mass was associated with a 6 to 7% increase in dementia incidence and a 9% increase in AD incidence. For different PM2.5 constituents, associations remained significant for BC, OM, SO4 2-, and NH4 + for both end points (even after adjustments of other constituents), among which BC and SO4 2-showed the strongest associations. All constituents had largely linear C-R relationships in the low exposure range, but most tailed off at higher exposure concentrations. Our findings suggest that long-term exposure to PM2.5 is significantly associated with higher rates of incident dementia and AD and that SO4 2-, BC, and OM related to traffic and fossil fuel combustion might drive the observed associations. [ABSTRACT FROM AUTHOR]

Background: Traffic-related air pollution exposure is associated with increased risk of autism spectrum disorder (ASD). It is unknown whether carbonaceous material from vehicular tailpipe emissions or redox-active non-tailpipe metals, eg. from tire and brake wear, are responsible. We assessed ASD associations with fine particulate matter (PM2.5) tracers of tailpipe (elemental carbon [EC] and organic carbon [OC]) and non-tailpipe (copper [Cu]; iron [Fe] and manganese [Mn]) sources during pregnancy in a large cohort. Methods: This retrospective cohort study included 318,750 children born in Kaiser Permanente Southern California (KPSC) hospitals during 2001–2014, followed until age 5. ASD cases were identified by ICD codes. Monthly estimates of PM2.5 and PM2.5 constituents EC, OC, Cu, Fe, and Mn with 4 km spatial resolution were obtained from a source-oriented chemical transport model. These exposures and NO2 were assigned to each maternal address during pregnancy, and associations with ASD were assessed using Cox regression models adjusted for covariates. PM constituent effect estimates were adjusted for PM2.5 and NO2 to assess independent effects. To distinguish ASD risk associated with non-tailpipe from tailpipe sources, the associations with Cu, Fe, and Mn were adjusted for EC and OC, and vice versa. Results: There were 4559 children diagnosed with ASD. In single-pollutant models, increased ASD risk was associated with gestational exposures to tracers of both tailpipe and non-tailpipe emissions. The ASD hazard ratios (HRs) per inter-quartile increment of exposure) for EC, OC, Cu, Fe, and Mn were 1.11 (95% CI: 1.06–1.16), 1.09 (95% CI: 1.04–1.15), 1.09 (95% CI: 1.04–1.13), 1.14 (95% CI: 1.09–1.20), and 1.17 (95% CI: 1.12–1.22), respectively. Estimated effects of Cu, Fe, and Mn (reflecting non-tailpipe sources) were largely unchanged in two-pollutant models adjusting for PM2.5, NO2, EC or OC. In contrast, ASD associations with EC and OC were markedly attenuated by adjustment for non-tailpipe sources. Conclusion: Results suggest that non-tailpipe emissions may contribute to ASD. Implications are that reducing tailpipe emissions, especially from vehicles with internal combustion engines, may not eliminate ASD associations with traffic-related air pollution.

A growing number of studies associated increased mortality with exposures to specific fine particulate (PM2.5) constituents, while great heterogeneity exists between locations. In China, evidence linking PM2.5 constituents and mortality was extensively sparse. This study primarily aimed to quantify short-term associations between PM2.5 constituents and non-accidental mortality among the Chinese population. We collected daily mortality records from 32 counties in China between January 1, 2011, and December 31, 2013. Daily concentrations of main PM2.5 constituents (organic carbon (OC), elemental carbon (EC), nitrate (NO3−), sulfate (SO42−), and ammonium (NH4+)) were estimated using the modified Community Multiscale Air Quality model. Time-stratified case-crossover design with conditional logistic regression models was adopted to estimate mortality risks associated with short-term exposures to PM2.5 mass and its constituents. Stratification analyses were done by sex, age, and season. A total of 116,959 non-accidental deaths were investigated. PM2.5 concentrations on the day of death were averaged at 75.7 µg m−3 (control day: 75.6 µg m−3), with an interquartile range (IQR) of 65.2 µg m−3. Per IQR rise in PM2.5, EC, OC, NO3−, SO42−, and NH4+ at lag-04 day was associated with an increase in non-accidental mortality of 2.4% (95% confidence interval, (1.0–3.7), 1.7% (0.8–2.7), 2.9% (1.6–4.3), 2.1% (0.4–3.9), 1.0% (0.2–1.9), and 1.6% (0.3–2.9), respectively. Both PM2.5 mass and its constituents were strongly associated with elevated cardiovascular mortality risks, but only PM2.5, EC, and OC were positively associated with respiratory mortality at lag-3 day. PM2.5 mass and its constituents associated effects on mortality varied among sex- and age-specific subpopulations. Differences in the seasonal pattern of associations exist among PM2.5 constituents, with stronger effects related to EC and NO3− in warm months but SO42− and NH4+ in cold months. Short-term exposures to PM2.5 compositions were positively associated with increased risks of mortality, particularly those constituents from combustion-related sources. [ABSTRACT FROM AUTHOR]

East Asian countries have been conducting source apportionment of fine particulate matter (PM 2.5) by applying positive matrix factorization (PMF) to hourly constituent concentrations. However, some of the constituent data from the supersites in South Korea was missing due to instrument maintenance and calibration. Conventional preprocessing of missing values, such as exclusion or median replacement, causes biases in the estimated source contributions by changing the PMF input. Machine learning (ML) can estimate the missing values by training on constituent data, meteorological data, and gaseous pollutants. Complete data from the Seoul Supersite in 2018 was taken, and a random 20% was set as missing. PMF was performed by replacing missing values with estimates. Percent errors of the source contributions were calculated compared to those estimated from complete data. Missing values were estimated using a random forest analysis. Estimation accuracy (r2) was as high as 0.874 for missing carbon species and low at 0.631 when ionic species and trace elements were missing. For the seven highest contributing sources, replacing the missing values of carbon species with estimates minimized the percent errors to 2.0% on average. However, replacing the missing values of the other chemical species with estimates increased the percent errors to more than 9.7% on average. Percent errors were maximal at 37% on average when missing values of ionic species and trace elements were replaced with estimates. Missing values, except for carbon species, need to be excluded. This approach reduced the percent errors to 7.4% on average, which was lower than those due to median replacement. Our results show that reducing the biases in source apportionment is possible by replacing the missing values of carbon species with estimates. To improve the biases due to missing values of the other chemical species, the estimation accuracy of the ML needs to be improved. [Display omitted] • Missing values of hourly PM 2.5 constituents were estimated using a random forest. • Estimation accuracy (r2) was 0.631–0.874, highest for carbon species. • PMF was performed by replacing missing values in the input data with estimates. • Source contributions were compared to the complete PMF result with percent errors. • Replacing the missing carbon species minimized the percent errors to 2.0%. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the association between long-term exposure to fine particulate matter (PM 2.5) and its constituents (black carbon (BC), ammonium (NH 4 +), nitrate (NO 3 −), organic matter (OM), inorganic sulfate (SO 4 2−)) and incident female breast cancer in Beijing, China. Data from a prospective cohort comprising 85,504 women enrolled in the National Urban Cancer Screening Program in Beijing (2013–2019) and the Tracking Air Pollution in China dataset are used. Monthly exposures were aggregated to calculate 5-year average concentrations to indicate long-term exposure. Cox models and mixture exposure models (weighted quantile sum, quantile-based g-computation, and explanatory machine learning model) were employed to analyze the associations. Findings indicated increased levels of PM 2.5 and its constituents were associated with higher breast cancer risk, with hazard ratios per 1-μg/m3 increase of 1.02 (95% confidence interval (CI): 1.01, 1.03), 1.39 (95% CI: 1.16, 1.65), 1.28 (95% CI: 1.12, 1.46), 1.15 (95% CI: 1.05, 1.24), 1.05 (95% CI: 1.02, 1.08), and 1.15 (95% CI: 1.07, 1.23) for PM 2.5 , BC, NH 4 +, NO 3 −, OM, and SO 4 2−, respectively. Exposure-response curves demonstrated a monotonic risk increase without an evident threshold. Mixture exposure models highlighted BC and SO 4 2− as key factors, underscoring the importance of reducing emissions of these pollutants. [Display omitted] • Long-term exposure to PM 2.5 and its constituents was linked to higher female breast cancer risk in Beijing. • Key pollutants black carbon (BC) and sulfate (SO 4 2−) were identified as significant contributors to breast cancer risk. • Effective control measures are crucial in mitigating pollutants to reduce the risk of female breast cancer. [ABSTRACT FROM AUTHOR]

The individual and combined effects of PM 2.5 constituents on cardiometabolic risk factors are sparsely investigated. Besides, the key cardiometabolic risk factor that PM 2.5 constituents targeted and the biological mechanisms remain unclear. A multistage, stratified cluster sampling survey was conducted in two typically air-polluted Chinese cities. The PM 2.5 and its constituents including sulfate, nitrate, ammonium, organic matter, and black carbon were predicted using a machine learning model. Twenty biomarkers in three category were simultaneously adopted as cardiometabolic risk factors. We explored the individual and mixture association of long-term PM 2.5 constituents with these markers using generalized additive model and quantile-based g-computation, respectively. To minimize potential confounding effects, we accounted for covariates including demographic, lifestyle, meteorological, temporal trends, and disease-related information. We further used ROC curve and mediation analysis to identify the key subclinical indicators and explore whether inflammatory mediators mediate such association, respectively. PM 2.5 constituents was positively correlated with HOMA-B, TC, TG, LDL-C and LCI, and negatively correlated with PP and RC. Further, PM 2.5 constituent mixture was positive associated with DBP, MAP, HbA1c, HOMA-B, AC, CRI-1 and CRI-2, and negative associated with PP and HDL-C. The ROC analysis further reveals that multiple cardiometabolic risk factors can collectively discriminate exposure to PM 2.5 constituents (AUC>0.9), among which PP and CRI-2 as individual indicators exhibit better identifiable performance for nitrate and ammonium (AUC>0.75). We also found that multiple blood lipid indicators may be affected by PM 2.5 and its constituents, possibly mediated through complement C3 or hsCRP. Our study suggested associations of individual and combined PM 2.5 constituents exposure with cardiometabolic risk factors. PP and CRI-2 were the targeted markers of long-term exposure to nitrate and ammonium. Inflammation may serve as a mediating factor between PM 2.5 constituents and dyslipidemia, which enhance current understanding of potential pathways for PM 2.5 -induced preclinical cardiovascular responses. [Display omitted] • Long-term exposure to PM 2.5 constituents was positively correlated with HOMA-B, TC, TG, LDL-C and LCI, and negatively correlated with PP and RC. • PM 2.5 component mixture was positive associated with DBP, MAP, HbA1c, HOMA-B, AC, CRI-1 and CRI-2, and negative associated with PP and HDL-C. • The ROC analysis reveals that multiple cardiometabolic risk factors can collectively discriminate exposure to PM 2.5 constituents (AUC>0.9), among which PP and CRI-2 as individual indicators exhibit better predictive performance for nitrate and ammonium (AUC>0.75). • In medication analysis, we found that multiple blood lipid indicators such as TC, TG, and LDL-C may be affected by PM 2.5 and its constituents, possibly mediated through complement C3 or hsCRP. [ABSTRACT FROM AUTHOR]

Little is known concerning the associations of fine particulate matter (PM2.5) and its constituents with atherosclerotic cardiovascular disease (ASCVD). A total of 31,162 participants enrolled from the Henan Rural Cohort were used to specify associations of PM2.5 and its constituents with ASCVD. Hybrid machine learning was utilized to estimate the 3-year average concentration of PM2.5 and its constituents (black carbon [BC], nitrate [NO3−], ammonium [NH4+], inorganic sulfate [SO42−], organic matter [OM], and soil particles [SOIL]). Constituent concentration, proportion, and residual models were utilized to examine the associations of PM2.5 constituents with 10-year ASCVD risk and to identify the most hazardous constituent. The isochronous substitution model (ISM) was employed to analyze the substitution effect between PM2.5 constituents. We found that each 1 μg/m3 increase in PM2.5, BC, NH4+, NO3−, OM, SO42−, and SOIL was associated with a 3.5%, 49.3%, 19.4%, 10.5%, 21.4%, 14%, and 28.5% higher 10-year ASCVD risk, respectively (all p < 0.05). Comparable results were observed in proportion and residual models. The ISM found that replacing BC with other constituents will generate the greatest health benefits. The results indicated that long-term exposure to PM2.5 and its constituents were associated with increased risks of ASCVD, with BC being the most attributable constituent.

Although exposure to fine particulate matter (PM2.5) has been associated with cognitive decline, little is known about which PM2.5 constituents are more harmful. Recent study on the association between PM2.5 and sleep quality prompted us to propose that sleep quality may mediate the adverse effects of PM2.5 components on cognitive decline. Understanding the association between PM2.5 constituents and cognitive function, as well as the mediating role of sleep quality provides a future intervention target for improving cognitive function. Using data involving 1834 participants from a multicenter cross-sectional study in nine cities of the Beijing-Tianjin-Hebei (BTH) region in China, we undertook multivariable linear regression analyses to quantify the association of annual moving-average PM2.5 and its chemical constituents with cognitive function and to assess the modifying role of exposure characteristic in this association. Besides, we examined the extent to which this association of PM2.5 constituents with cognitive function was mediated via sleep quality by a mediation analysis. We observed significantly negative associations between an increase of one interquartile range increase in PM2.5 [−0.876 (95 % CI: −1.205, −0.548)], organic carbon [−0.481 (95 % CI: −0.744, −0.219)], potassium [−0.344 (95 % CI: −0.530, −0.157)], iron [−0.468 (95 % CI: −0.646, −0.291)], and ammonium ion [−0.125 (95 % CI: −0.197, −0.052)] and cognitive decline. However, we didn’t find any individual components more harmful than PM2.5. Poor sleep quality partially mediated the estimated associations, which were explained ranging from 2.28 % to 11.99 %. Stratification analyses showed that people living in areas with lower greenspace were more susceptible to specific PM2.5 components. Our study suggests that the adverse effect of suffering from PM2.5 components is more pronounced among individuals with poor sleep quality, amplifying environmental inequalities in health. Besides reducing environmental pollution, improving sleep quality may be another measure worth considering to improve cognition if our research is confirmed in the future.

Background: Previous studies have indicated the associations between fine particulate matter (PM2.5) exposure and diabetes or glucose levels. However, evidence linking PM2.5 constituents and diabetes or glucose levels was extensively scarce, particularly in developing countries. This study aimed to investigate the associations of exposure to PM2.5 and its five constituents (black carbon [BC], organic matter [OM], nitrate [NO3-], sulfate [SO42-], and ammonium [NH4+]) with diabetes and glucose levels among the middle-aged and elderly Chinese populations. Methods: A national cross-sectional sample of participants aged 45+ years was enrolled from 28 provinces across China’s mainland. Health examination and questionnaire survey for each respondent were performed during 2011−2012. Diabetes was determined by alternative definitions, and the main definition (MD) was self-report diabetes or antidiabetic medicine use or HbA1c ≥6.5 or fasting glucose ≥7 mmol/L or random glucose ≥11.1 mmol/L. Monthly exposure to PM2.5 mass and its five constituents (BC, OM, NO3-, SO42-, and NH4+) for each participant at residence were estimated using satellite-based spatiotemporal prediction models. Generalized linear models and linear mixed-effects models were used to assess the effects of exposure to PM2.5 and its constituents on diabetes or glucose levels, respectively. Stratification analyses were done by sex and age. Results: We included a total of 17,326 adults over 45 years in this study. The 3-year mean (interquartile range [IQR]) concentrations of PM2.5, BC, OM, NO3-, SO42-, and NH4+ were 47.9 (27.4) µg/m3, 2.9 (2.2) µg/m3, 9.2 (6.6) µg/m3, 10.2 (9.4) µg/m3, 11.0 (5.2) µg/m3, and 7.1 (4.4) µg/m3, respectively. Per IQR rise in exposure to PM2.5 was significantly associated with an increase of 0.133 mmol/L (95% confidence interval, 0.048−0.219) in glucose concentrations. Similar positive associations were observed for BC (0.097 mmol/L [0.012−0.181]), OM (0.160 mmol/L [0.065−0.256]), NO3- (0.145 mmol/L [0.039−0.251]), SO42- (0.111 mmol/L [0.026−0.196]), and NH4+ (0.135 mmol/L [0.041−0.230]). Under different diabetes definitions, PM2.5 mass and selected constituents with the exception of SO42- were all associated with a higher risk of prevalent diabetes. In MD-based analysis, similar positive associations were observed for four constituents, with corresponding odds ratios of 1.180 (1.097−1.270) for PM2.5, 1.154 (1.079−1.235) for BC, 1.170 (1.079−1.270) for OM, 1.200 (1.098−1.312) for NO3-, and 1.123 (1.037−1.215) for NH4+. Stratified analyses showed a significantly higher risk of diabetes in males (1.225 [1.064−1.411]) than females (1.024 [0.923−1.136]) when exposed to PM2.5. Participants under 65 years were generally more vulnerable to diabetes hazards related to PM2.5 constituents exposure. Conclusions: Exposures to PM2.5 and its constituents (i.e., BC, OM, NO3-, and NH4+) were positively associated with increased risks of prevalent diabetes and elevated glucose levels in middle-aged and older adults.

Background: Emerging evidence suggests that early-life (in-utero and first-year since birth) exposure to ambient PM2.5 is a risk factor for asthma onset and exacerbation among children, while the hazards caused by PM2.5 compositions remain largely unknown. Objective: To examine potential associations of early-life exposures to PM2.5 mass and its major chemical constituents with childhood asthma and wheezing. Methods: By conducting the Phase II of the China, Children, Homes, Health study, we investigated 30,325 preschool children aged 3–6 years during 2019–2020 in mainland China. Early-life exposure to PM2.5 mass and its constituents (i.e., black carbon [BC], organic matter [OM], nitrate, ammonium, sulfate) were calculated based on monthly estimates at a 1 km × 1 km resolution from satellite-based models. We adopted a novel quantile-based g-computation approach to assess the effect of a mixture of PM2.5 constituents on childhood asthma/wheezing. Results: The average PM2.5 concentrations during in-utero and the first year since birth were 64.7 ± 10.6 and 61.8 ± 10.5 µg/m3, respectively. Early-life exposures to a mixture of major PM2.5 constituents were significantly associated with increased risks of asthma and wheezing, while no evident compositions-wheezing associations were found in the first year. Each quintile increases in all five PM2.5 components exposures in utero was accordingly associated with an odds ratio of 1.18 [95% confidence interval: 1.07–1.29] for asthma and 1.08 [1.01–1.16] for wheezing. BC, OM and SO42− contributed more to risks of asthma and wheezing than the other PM2.5 constituents during early life, wherein the effects of BC were only observed during pregnancy. Sex subgroup analyses suggested stronger associations among girls of first-year exposures to PM2.5 components with childhood asthma. Conclusion: Early-life exposures to ambient PM2.5, particularly compositions of BC, OM and SO42−, are associated with an increased risk of childhood asthma.

[Display omitted] While evidence suggests that PM 2.5 is associated with overall prevalence of Metabolic (dysfunction)-Associated Fatty Liver Disease (MAFLD), effects of comprehensive air pollutant mixture on MAFLD and its subtypes remain unclear. To investigate individual and joint effects of long-term exposure to comprehensive air pollutant mixture on MAFLD and its subtypes. Data of 27,699 participants of the Chinese Cohort of Working Adults were analyzed. MAFLD and subtypes, including overweight/obesity, lean, and diabetes MAFLD, were diagnosed according to clinical guidelines. Concentrations of NO 3 –, SO 4 2−, NH 4 +, organic matter (OM), black carbon (BC), PM 2.5 , SO 2 , NO 2 , O 3 and CO were estimated as a weighted average over participants' residential and work addresses for the three years preceding outcome assessment. Logistic regression and weighted quantile sum regression were used to estimate individual and joint effects of air pollutant mixture on presence of MAFLD. Overall prevalence of MAFLD was 26.6 % with overweight/obesity, lean, and diabetes MAFLD accounting for 92.0 %, 6.4 %, and 1.6 %, respectively. Exposure to SO 4 2−, NO 3 –, NH 4 +, BC, PM 2.5 , NO 2 , O 3 and CO was significantly associated with overall MAFLD, overweight/obesity MAFLD, or lean MAFLD in single pollutant models. Joint effects of air pollutant mixture were observed for overall MAFLD (OR = 1.10 [95 % CI: 1.03, 1.17]), overweight/obesity (1.09 [1.02, 1.15]), and lean MAFLD (1.63 [1.28, 2.07]). Contributions of individual air pollutants to joint effects were dominated by CO in overall and overweight/obesity MAFLD (Weights were 42.31 % and 45.87 %, respectively), while SO 4 2− (36.34 %), SO 2 (21.00 %) and BC (12.38 %) were more important in lean MAFLD. Being male, aged above 45 years and smoking increased joint effects of air pollutant mixture on overall MAFLD. Air pollutant mixture was associated with MAFLD, particularly the lean MAFLD subtype. CO played a pivotal role in both overall and overweight/obesity MAFLD, whereas SO 4 2− were associated with lean MAFLD. [ABSTRACT FROM AUTHOR]

Ambient fine particulate matter (PM 2.5) has attracted considerable attention due to its crucial role in the rising global disease burden. Evidence of health risks associated with exposure to PM 2.5 and its major constituents is important for advancing hazard assessments and air pollution emission policies. We investigated the relationship between exposure to major constituents of PM 2.5 and outpatient visits as well as hospitalizations in Guangdong Province, China, where 127 million residents live in a severe PM 2.5 pollution environment. An approach that integrates the generalized weighted quantile sum (gWQS) regression with the difference-in-differences (DID) approach was used to assess the overall mixture effects and relative contributions of each constituent. We observed significant associations between long-term exposure to the mixture of PM 2.5 constituents (WQS index) and outpatient visits (IR %, percentage increases in risk per unit WQS index increase:1.73, 95% CI : 1.72, 1.74) as well as hospitalizations (IR %:5.15, 95% CI : 5.11, 5.20). Black carbon (weight: 0.34) and nitrate (weight: 0.60) respectively exhibited the highest contributions to outpatient visits and hospitalizations. The overall mixture effects on outpatient visits and hospitalizations were higher with increased summer air temperatures (IR %: 7.54, 95% CI : 7.33, 7.74 and IR %: 9.55, 95% CI : 8.36, 10.75, respectively) or decreased winter air temperatures (IR %: 1.88, 95% CI : 1.68, 2.08 and IR %: 4.87, 95% CI : 3.73, 6.02, respectively). Furthermore, the overall mixture effects on outpatient visits and hospitalizations were significantly higher in populations with higher socioeconomic status (P < 0.01). It's crucial to address the primary sources of nitrate precursor substances and black carbon (mainly traffic-related and industrial-related air pollutants) and consider the complex interaction effects between air temperature and PM 2.5 in the context of climate change. Of particular concern is the need to prioritize healthcare demands in economically disadvantaged regions and to address the health inequalities stemming from the uneven distribution of healthcare resources and PM 2.5 pollution. [Display omitted] • PM 2.5 constituent exposure was associated with outpatient visits and hospitalizations. • Black carbon was the most influential constituent in increased outpatient visits. • Nitrate was the most influential constituent in increased hospitalizations. • The overall mixture effect was modified by air temperature and socioeconomic factors. [ABSTRACT FROM AUTHOR]

Although growing evidence has shown independent links of long-term exposure to fine particulate matter (PM 2.5) with cognitive impairment, the effects of its constituents remain unclear. This study aims to explore the associations of long-term exposure to ambient PM 2.5 constituents' mixture with cognitive impairment in Chinese older adults, and to further identify the main contributor. 15,274 adults ≥ 65 years old were recruited by the Chinese Longitudinal Healthy Longevity Study (CLHLS) and followed up through 7 waves during 2000–2018. Concentrations of ambient PM 2.5 and its constituents (i.e., black carbon [BC], organic matter [OM], ammonium [NH 4 +], sulfate [SO 4 2-], and nitrate [NO 3 -]) were estimated by satellite retrievals and machine learning models. Quantile-based g-computation model was employed to assess the joint effects of a mixture of 5 PM 2.5 constituents and their relative contributions to cognitive impairment. Analyses stratified by age group, sex, residence (urban vs. rural), and region (north vs. south) were performed to identify vulnerable populations. During the average 3.03 follow-up visits (89,296.9 person-years), 4294 (28.1%) participants had developed cognitive impairment. The adjusted hazard ratio [HR] (95% confidence interval [CI]) for cognitive impairment for every quartile increase in mixture exposure to 5 PM 2.5 constituents was 1.08 (1.05–1.11). BC held the largest index weight (0.69) in the positive direction in the qg-computation model, followed by OM (0.31). Subgroup analyses suggested stronger associations in younger old adults and rural residents. Long-term exposure to ambient PM 2.5 , particularly its constituents BC and OM, is associated with an elevated risk of cognitive impairment onset among Chinese older adults. [Display omitted] • Exposure to PM 2.5 and its constituents has an adverse effect on cognitive impairment. • A qg-computation model assessed the joint effect and relative importance of PM 2.5 constituents. • BC and OM are the main PM 2.5 constituents contributing to cognitive impairment. • A roughly linear concentration-response association was found for PM 2.5. • Younger old adults and rural residents are more vulnerable. [ABSTRACT FROM AUTHOR]

Previous studies have reported that atmospheric elemental carbon (EC) may pose potentially elevated toxicity when compared to total ambient fine particulate matter (PM _2.5 ). However, most research on EC has been conducted in the US and Europe, whereas China experiences significantly higher EC pollution levels. Investigating the health impact of EC exposure in China presents considerable challenges due to the absence of a monitoring network to document long-term EC levels. Despite extensive studies on total PM _2.5 in China over the past decade and a significant decrease in its concentration, changes in EC levels and the associated mortality burden remain largely unknown. In our study, we employed a combination of satellite remote sensing, available ground observations, machine learning techniques, and atmospheric big data to predict ground EC concentrations across China for the period 2005–2018, achieving a spatial resolution of 10 km. Our findings reveal that the national average annual mean EC concentration has remained relatively stable since 2005, even as total PM _2.5 levels have substantially decreased. Furthermore, we calculated the all-cause non-accidental deaths attributed to long-term EC exposure in China using baseline mortality data and pooled mortality risk from a cohort study. This analysis unveiled significant regional disparities in the mortality burden resulting from long-term EC exposure in China. These variations can be attributed to varying levels of effectiveness in EC regulations across different regions. Specifically, our study highlights that these regulations have been effective in mitigating EC-related health risks in first-tier cities. However, in regions characterized by a highconcentration of coal-power plants and industrial facilities, additional efforts are necessary to control emissions. This observation underscores the importance of tailoring environmental policies and interventions to address the specific challenges posed by varying emission sources and regional contexts.

Background: Epidemiological findings are inconsistent regarding the associations between air pollution exposure during pregnancy and gestational diabetes mellitus (GDM). Several limitations exist in previous studies, including potential outcome and exposure misclassification, unassessed confounding, and lack of simultaneous consideration of air pollution mixtures and particulate matter (PM) constituents. Objectives: To assess the association between GDM and maternal residential exposure to air pollution, and the joint effect of the mixture of air pollutants and PM constituents. Methods: Detailed clinical data were obtained for 395,927 pregnancies in southern California (2008–2018) from Kaiser Permanente Southern California (KPSC) electronic health records. GDM diagnosis was based on KPSC laboratory tests. Monthly average concentrations of fine particulate matter

As the major constituents of PM2.5, carbonaceous constituents and inorganic ions have attracted emerging attentions on their health risks, particularly on cardiorespiratory diseases. However, evidences on the risks of PM2.5 constituents on other diseases (eg. nervous disease, genitourinary disease, neoplasms and endocrine disease) remain scarce. In our study, we firstly calculated residuals of PM2.5 constituents regressed on PM2.5 to remove the confounding effect of PM2.5. Then, generalized additive model (GAM) was used to assess impacts of residuals of PM2.5 constituents on mortality from 36 diseases (10 broad categories and 26 subcategories) during 2011–2015 in Guangzhou, China. Results of constituent-residual models showed that only EC, OC and NO3- were significantly associated with all-cause mortality, with per IQR change in corresponding constituent residuals related to percentage changes of 1.69% (95% CI: 0.42, 2.97), 1.94% (95% CI: 0.37, 3.54) and 2.59% (95% CI: 1.02, 4.18) at lag 03 days. All these pollutants were significantly associated with elevated mortality risk of cardiovascular disease, but only EC was significantly associated with respiratory mortality, and NO3- with endocrine disease and neoplasm. For more specific causes, the highest effect estimates of EC and NO3-were both observed on mortality from other form of heart disease, and OC on intentional self-harm, with estimates of 11.45% (95% CI: 2.74, 20.91), 12.59% (95% CI: 1.41, 25.02) and 18.01% (95% CI: 2.14, 36.36), respectively. Our findings highlighted that stricter emission control measures are still warranted to reduce air pollution level and protect the public health.

Exposure to fine particulate matter (PM 2.5 ) during pregnancy has been inversely associated with neonatal neurological development. However, the associations of exposure to specific PM 2.5 constituents with neonatal neurological development remain unclear. We investigated these associations and examined the mediating role of meconium metabolites in a Chinese birth cohort consisting of 294 mother-infant pairs. Our results revealed that exposure to PM 2.5 and its specific constituents (i.e., organic matter, black carbon, sulfate, nitrate, and ammonium) in the second trimester, but not in the first or third trimester, was inversely associated with the total neonatal behavioral neurological assessment (NBNA) scores. The PM 2.5 constituent mixture in the second trimester was also inversely associated with NBNA scores, and sulfate was identified as the largest contributor. Furthermore, meconium metabolome analysis identified four metabolites, namely, threonine, lysine, leucine, and saccharopine, that were associated with both PM 2.5 constituents and NBNA scores. Threonine was identified as an important mediator, accounting for a considerable proportion (14.53-15.33%) of the observed inverse associations. Our findings suggest that maternal exposure to PM 2.5 and specific constituents may adversely affect neonatal behavioral development, in which meconium metabolites may play a mediating role.

Recent studies found the intrusion and retention of exogenous fine particles into joints, but epidemiological data for long- and intermediate-term exposure associations are scare. Here, all urban working, retired employee, and rural residents (16.78 million) in Beijing from January 1, 2011 to December 31, 2019 were included to investigate the effects of long- and intermediate-term ambient particulate exposure on development of osteoarthritis. We identified 1,742,067 participants as first-visit patients with osteoarthritis. For each interquartile range increase in annual PM 2.5 (23.32 μg/m 3 ) and PM 10 (23.92 μg/m 3 ) exposure concentration, the pooled hazard ratios were respectively 1.238 (95% CI: 1.228, 1.249) and 1.178 (95% CI: 1.168, 1.189) for first osteoarthritis outpatient visits. Moreover, age at first osteoarthritis outpatient visits significantly decreased by 4.52 (95% CI: 3.45 to 5.40) days per μg/m 3 for annual PM 2.5 exposure at below 67.85 μg/m 3 . Finally, among the six constituents analyzed, black carbon appears to be the most important component associated with the association between PM 2.5 exposure and the three osteoarthritis-related outcomes.

The association between ambient fine particulate matter (PM 2.5) exposure and semen quality remains inconclusive, possibly due to variations in pollution sources and PM 2.5 compositions. Studies investigating the constituents of PM 2.5 have been hindered by small sample sizes, and research exploring the relationships between PM 2.5 pollution sources and semen quality is lacking. To address this gap, we conducted a comprehensive study based on the Anhui prospective assisted reproduction cohort to evaluate the associations between semen quality and the constituents and pollution sources of PM 2.5. This study included 9013 semen samples from 4417 males in the urban districts of Hefei. The median concentrations of PM 2.5 constituents, including eight metals and four water-soluble ions (WSIs), were measured for seven days per month at two monitoring stations during the 0–90-day exposure window. A linear mixed-effects model, weighted quantile sum regression, and positive matrix factorisation were used to evaluate the associations of the constituents and pollution sources of PM 2.5 with semen quality. The results showed that exposure to PM 2.5 -bound metals (antimony, arsenic, cadmium, lead, and thallium) and WSIs (sulphate and chloride) were negatively associated with semen quality parameters. Moreover, mixtures of PM 2.5 -bound metals and WSIs were negatively associated with semen quality. Additionally, PM 2.5 derived from traffic emissions was negatively associated with semen quality. In summary, our study revealed that ambient PM 2.5 and its constituents, especially metals, were negatively associated with semen quality. Antimony, lead, and thallium emerged as the primary contributors to toxicity, and PM 2.5 from traffic emissions was associated with decreased semen quality. These findings have important public health implications for the management of PM 2.5 pollution in the context of male reproductive health. [Display omitted] • PM 2.5 -bound metals and water soluble ions were negatively associated with semen quality. • Cd, Sb and Tl were the leading causes of the toxicity of PM 2.5 on semen quality. • PM 2.5 from traffic emissions was negatively associated with semen quality. [ABSTRACT FROM AUTHOR]

Evidence on the association of fine particulate matter (PM 2.5) exposure with stillbirth is limited and inconsistent, which is largely attributed to differences in PM 2.5 constituents. Studies have found that the hazards of certain PM 2.5 constituents to the fetus are comparable to or even higher than total PM 2.5 mass. However, few studies have linked PM 2.5 constituents to stillbirth. Moreover, the mediating role of pregnancy complications in PM 2.5 -related stillbirth remains unclear. To our knowledge, this study was the first to explore the individual and mixed associations of PM 2.5 and its constituents with stillbirth in China. After matching the concentrations of PM 2.5 and its constituents (sulfate [SO 4 2−], nitrate [NO 3 −], ammonium [NH 4 +], organic matter [OM], and black carbon [BC]) for participants according to their geographical location, there were 170,507 participants included in this study. We found that stillbirth was associated with exposure to PM 2.5 and its constituents in the year before pregnancy and during the entire pregnancy, and the associations in trimester 1 were strongest. The risk of stillbirth increased sharply when PM 2.5 and its constituents during pregnancy exceeded the median concentrations. Moreover, stillbirth was associated with exposure to the mixtures of SO 4 2−, NO 3 −, NH 4 +, OM, and BC before and during pregnancy (trimesters 1 and 2). Meanwhile, two-pollutant models also suggested stillbirth was associated with PM 2.5 and its constituents in the year before and during pregnancy. The associations of PM 2.5 and its constituents with stillbirth were stronger in mothers with advanced age and without cesarean delivery history. Additionally, hypertensive disorders in pregnancy, gestational diabetes, and placental abruption mediated the association of PM 2.5 with stillbirth. Therefore, enhanced protection against PM 2.5 for pregnant women before and during pregnancy and targeted interventions for pregnancy complications and anthropogenic sources of PM 2.5 constituents are important to reduce stillbirth risk. [Display omitted] • The first study to reveal the association between PM 2.5 constituents and stillbirth in China. • The first trimester is the susceptibility window for stillbirths caused by PM 2.5. • Targeted control for the anthropogenic sources of SO 4 2− and BC is important. • Pregnancy complications mediated the risk of stillbirth related to PM 2.5. [ABSTRACT FROM AUTHOR]

Exposure to particulate matter with aerodynamic diameter ≤2.5 μm (PM 2.5) was associated with the risk for metabolic syndrome (MetS) in the general population, but the contributions of individual PM 2.5 constituents to this association and the potential pathway between PM 2.5 constituents and MetS risk are not well elaborated. This study aimed to investigate associations between PM 2.5 constituents and MetS in general populations, relative importance of PM 2.5 constituents to and mediation effects of serum uric acid (SUA) on those associations. The 48,148 participants from a provincially representative cohort established in southwest China were included. The 3-year average concentrations of PM 2.5 and its constituents (nitrate [NO 3 −], sulfate [SO 4 2−], ammonium [NH 4 +], organic matter [OM], and black carbon [BC]) were estimated using a series of machine-learning models. Multivariate logistic regression and weighted quantile sum regression were used to estimate effects of independent PM 2.5 constituents on MetS and their contributions to the joint effect. Mediation analysis examined the potential mediation effects of SUA on the associations between PM 2.5 constituents and MetS. Each interquartile range (IQR) increase in the concentration of PM 2.5 constituents was all positively associated with the increased MetS odds, including SO 4 2− (OR = 1.15 [1.11, 1.19]]), NO 3 − (OR = 1.12 [1.08, 1.16]), NH 4 + (OR = 1.13 [1.09, 1.17]), OM (OR = 1.09 [1.06, 1.13]), and BC (OR = 1.09 [1.06, 1.13]). Their joint associations on MetS were mainly attributed to SO 4 2− (weight=46.1%) and NH 4 + (44.0%). The associations of PM 2.5 constituents with abnormal MetS components were mainly attributed to NH 4 + for elevated BP (51.6%) and reduced HDL-C (97.0%), SO 4 2− for elevated FG (68.9%), NO 3 - for elevated TG (51.0%), and OM for elevated WC (63.0%). Percentages mediated by SUA for the associations of PM 2.5, SO 4 2−, NO 3 −, and BC with MetS were 13.6%, 13.1%, 10.6%, and 11.1%, respectively. Long-term exposure to PM 2.5 constituents, mainly NH 4 + and SO 4 2−, was positively associated with MetS odds, partially mediated by SUA. [Display omitted] • Exposure to PM 2.5 and its constituents was associated with MetS odds. • SO 4 2− and NH 4 + played a dominant role in the joint effects of PM 2.5 on MetS odds. • SUA partially mediated relationships between PM 2.5 constituents and MetS odds. • The largest percentages mediated by SUA was the association of SO 4 2− with MetS. [ABSTRACT FROM AUTHOR]

[Display omitted] • PM 2.5 was associated with higher risk of incident OWOB. • PM 2.5 was associated with increased odds of being in larger BMI growth trajectories. • PM 2.5 was associated with increased odds of being in persistent OWOB trajectory. • Constituents including SO 4 2−, BC and OM are particularly relevant for these effects. The association of specific PM 2.5 chemical constituents with childhood overweight or obesity (OWOB) remain unclear. Furthermore, the long-term impacts of PM 2.5 exposure on the trajectory of children's body mass index (BMI) have not been explored. We conducted a longitudinal study among 1,450,830 Chinese children aged 6–19 years from Beijing and Zhongshan in China during 2005–2018 to examine the associations of PM 2.5 and its chemical constituents with incident OWOB risk. We extracted PM 2.5 mass and five main component exposure from Tracking Air Pollution in China (TAP) dataset. Cox proportional hazards models were applied to quantify exposure–response associations. We further performed principal component analysis (PCA) to handle the multi-collinearity and used quantile g-computation (QGC) approach to analyze the impacts of exposure mixtures. Additionally, we selected 125,863 children with at least 8 physical examination measurements and combined group-based trajectory models (GBTM) with multinomial logistic regression models to explore the impacts of exposure to PM 2.5 mass and five constituents on BMI and BMI Z-score trajectories during 6–19 years. We observed each interquartile range increment in PM 2.5 exposure was significantly associated with a 5.1 % increase in the risk of incident OWOB (95 % confidence Interval [CI]: 1.036–1.066). We also found black carbon, sulfate, organic matter, often linked to fossil combustion, had comparable or larger estimates of the effect (HR = 1.139–1.153) than PM 2.5. Furthermore, Exposure to PM 2.5 mass, sulfate, nitrate, ammonium, organic matter and black carbon was significantly associated with an increased odds of being in a larger BMI trajectory and being assigned to persistent OWOB trajectory. Our findings provide evidence that the constituents mainly from fossil fuel combustion may have a perceptible influence on increased OWOB risk associated with PM 2.5 exposure in China. Moreover, long-term exposure to PM 2.5 contributes to an increased odds of being in a lager BMI and a persistent OWOB trajectories. [ABSTRACT FROM AUTHOR]

Background: Fine particulate matter (with aerodynamic diameter ≤2.5 µm, PM2.5) causes huge disease burden worldwide. However, evidence is still inadequate and inconsistent on the relationships between PM2.5 constituents and mortality, especially in low resource settings. Objectives: To evaluate the impact of PM2.5 constituents on cause-specific mortality in China. Methods: We obtained daily mortality data for 161 communities in 2011–2013 from the Disease Surveillance Point system in China. Daily concentrations of major PM2.5 constituents, including organic carbon (OC), elemental carbon (EC), sulphate (SO42-), nitrate (NO3-) and ammonium (NH4+), were estimated by using the modified Community Multiscale Air Quality model. For each community, we applied quasi-Poisson regression and polynomial distributed lag models to estimate the effects of PM2.5 constituents on cause-specific mortality. Then, the pooled effect estimates were calculated by a random-effect meta-analysis based on the restricted maximum likelihood estimation. Stratification analyses were performed by region, gender, age group and education level to identify the vulnerable populations. Results: Each interquartile range change of EC, OC, SO42-, NO3- and NH4+ at lag 0–3 day was associated with increments in non-accidental mortality of 0.45% (95%CI: 0.21, 0.69), 1.43% (0.97, 1.89), 0.71% (0.28, 1.15), 0.70% (0.10, 1.30) and 0.95% (0.39, 1.51), respectively. The associations were stronger for the deaths from cardiovascular disease and myocardial infarction, the elderly, illiterates, and people living in the South region. Conclusions: Our findings suggest positive associations between PM2.5 constituents and cause-specific mortality, particularly for myocardial infarction.

[Display omitted] • PM 2.5 and its constituents of BaP, PAHs, SO 4 2− , Se were linked to increased oxidative stress in AR patients. • PM 2.5 and its constituents of Cl-, Fe, Ni, Zn, and Se were found to worsen the severity of AR patients' symptoms. • PM 2.5 constituents including Cl-, Mn, Fe, Ni, Zn, and Se were associated with a reduced quality of life in AR patients. Short-term exposure to fine particulate matter (PM 2.5) and its specific constituents might exacerbate allergic rhinitis (AR) conditions. However, the evidence is still inconclusive. We conducted a panel study of 49 patients diagnosed with AR > 1 year prior to the study in Taiyuan, China, to investigate associations of individual exposure to PM 2.5 and its constituents with oxidative parameters, symptoms, and quality of life among AR patients. All participants underwent repeated assessments of health and PM exposure at 4 time points in both the heating and nonheating seasons from June 2017 to January 2018. AR patients' oxidative parameters were assessed using nasal lavage, and their subjective symptoms and quality of life were determined through in-person interviews using a structured questionnaire. Short-term personal exposure to PM 2.5 and its constituents was estimated using the time-microenvironment-activity pattern and data from the nearest air sampler, respectively. We applied mixed-effects regression models to estimate the short-term effects of PM 2.5 and its constituents. The results showed that exposure to PM 2.5 and its constituents, including BaP, PAHs, SO 4 2− , NH 4 + , V, Cr, Cu, As, Se, Cd, and Pb, was significantly associated with increased oxidative stress, as indicated by an increase in the malondialdehyde (MDA) index. Exposure to PM 2.5 and its components (V, Mn, Fe, Zn, As, and Se) was associated with decreased antioxidant activity, as indicated by a decrease in the superoxide dismutase (SOD) index. Additionally, increased visual analog scale (VAS) and rhinoconjunctivitis quality of life questionnaire (RQLQ) scores indicated that exposure to PM 2.5 and its constituents exacerbated inflammatory symptoms and affected quality of life in AR patients. Exposure to PM 2.5 and specific constituents, could exacerbate AR patients' inflammatory symptoms and adversely affect their quality of life in the heavily industrialized city of Taiyuan, China. These findings may have potential biological and policy implications. [ABSTRACT FROM AUTHOR]

Previous studies have reported that atmospheric elemental carbon (EC) may pose potentially elevated toxicity when compared to total ambient fine particulate matter (PM 2.5 ). However, most research on EC has been conducted in the US and Europe, whereas China experiences significantly higher EC pollution levels. Investigating the health impact of EC exposure in China presents considerable challenges due to the absence of a monitoring network to document long-term EC levels. Despite extensive studies on total PM 2.5 in China over the past decade and a significant decrease in its concentration, changes in EC levels and the associated mortality burden remain largely unknown. In our study, we employed a combination of satellite remote sensing, available ground observations, machine learning techniques, and atmospheric big data to predict ground EC concentrations across China for the period 2005-2018, achieving a spatial resolution of 10 km. Our findings reveal that the national average annual mean EC concentration has remained relatively stable since 2005, even as total PM 2.5 levels have substantially decreased. Furthermore, we calculated the all-cause non-accidental deaths attributed to long-term EC exposure in China using baseline mortality data and pooled mortality risk from a cohort study. This analysis unveiled significant regional disparities in the mortality burden resulting from long-term EC exposure in China. These variations can be attributed to varying levels of effectiveness in EC regulations across different regions. Specifically, our study highlights that these regulations have been effective in mitigating EC-related health risks in first-tier cities. However, in regions characterized by a high concentration of coal-power plants and industrial facilities, additional efforts are necessary to control emissions. This observation underscores the importance of tailoring environmental policies and interventions to address the specific challenges posed by varying emission sources and regional contexts., Competing Interests: Conflict of interests The authors declare no competing interests.

Aim: To date, PM 2.5 -associated vascular damage in metabolic abnormalities has remained controversial. We knew little about the vascular damage of PM 2.5 constituents. Thus, this study aimed to investigate the relationship between long-term exposure to PM 2.5 and its constituents and vascular damage in metabolic abnormalities., Methods: A total of 124,387 participants with metabolic abnormalities (defined as at least one metabolic disorder, such as obesity, elevated blood pressure, elevated triglyceride level, elevated fasting glucose level, or low HDL cholesterol level) were recruited in this study from 11 representative centers in China between January 2011 and December 2017. PM 2.5 and its constituents (black carbon [BC], organic matter [OM], sulfate [SO 4 2- ], nitrate [NO 3 - ], and ammonium salts [NH 4 ＋ ]) were extracted. Elevated brachial-ankle pulse wave velocity (baPWV) (≥ 1,400 cm/s) and declined ankle-brachial index (ABI) (＜0.9) indicated vascular damage. Multivariable logistic regression and Quantile g-Computation models were utilized to explore the impact on outcomes., Results: Of the 124,387 participants (median age, 49 years), 87,870 (70.64%) were men. One-year lag exposure to PM 2.5 and its constituents was significantly associated with vascular damage in single pollutant models. The adjusted odds ratios (OR) for each 1-µg/m 3 increase in PM 2.5 was 1.013 (95% CI, 1.012-1.015) and 1.031 (95% CI, 1.025-1.037) for elevated baPWV and decreased ABI, respectively. PM 2.5 constituents were also associated with vascular damage in multi-pollutant models. Among the PM 2.5 constituents, BC (47.17%), SO 4 2- (33.59%), and NH 4 ＋ (19.23%) have the highest contribution to elevated baPWV and NO 3 - (47.89%) and BC (23.50%) to declined ABI., Conclusion: Chronic exposure to PM 2.5 and PM 2.5 constituents was related to vascular damage in the abnormal metabolic population in China. The heterogeneous contribution of different PM 2.5 constituents to vessel bed damage is worthy of attention when developing targeted strategies.

Epidemiological studies have demonstrated association between the total mass of fine particulate matter (PM 2.5) exposures and inflammation. There are few studies exploring the associations between PM 2.5 constituents and the biomarkers of inflammation in older adults and the underlying biological mechanisms are not exact. In this study, we examined the associations between PM 2.5 and its constituents (organic carbon (OC), elemental carbon (EC), total carbon (TC), polycyclic aromatic hydrocarbons (PAHs) and complement three factor (C3), an important biomarker of inflammation in a repeated panel of 175 older adults in Beijing, China. We have constructed three different linear mixed effect models (single-pollutant model, constituent-PM 2.5 joint model, and constituent-residual model) to evaluate the association of PM 2.5 and its constituents and complement C3, controlling for concentration of high sensitive C-reactive protein (hs-CRP), day of week, mean temperature, relative humidity, location and potential individual confounders. We found robust positive associations of OC, EC, TC, PAHs and PM 2.5 mass concentration with complement C3 at different lag patterns. The cumulative effects of pollutants increased across average of 2–5 days. Individuals aged 65 and above, or with diabetes, or BMI ≥30, or with no-cardiopathy, or with hypertension also exhibited positive associations between PM 2.5 and complement C3. The results revealed that short-term exposure to PM 2.5 and its constituents could result in a significant increase in serum level of complement C3. These findings suggested a possible involvement of complement C3 in the effect of PM 2.5 on inflammatory reaction. Image 1 • Highlights. • Short-term exposure to PM 2.5 and its constituents could result in a significant increase in complement C3. • The first study examining complement C3's role in the effect of PM 2.5 on inflammatory reaction. • Complement C3 may mediate the effect of PM 2.5 on inflammatory reaction. Short-term exposure to PM 2.5 and its constituents could result in a significant increase in complement C3, which may mediate the effect of PM 2.5 on inflammatory reaction. [ABSTRACT FROM AUTHOR]

Ambient particulate matter with aerodynamic diameter ≤ 2.5 µm (PM 2.5) consists of various toxic constituents. However, the health effect of PM 2.5 may differ depending on its constituents, but the joint effect of PM 2.5 constituents remains incompletely understood. Our goal was to evaluate the joint effect of long-term PM 2.5 constituent exposures on dyslipidemia and identify the most hazardous chemical constituent. This study included 67,015 participants from the China Multi-Ethnic Cohort study. The average yearly levels of PM 2.5 constituents for all individuals at their residences were assessed through satellite remote sensing and chemical transport modeling. Dyslipidemia was defined as one or more following abnormal blood lipid concentrations: total cholesterol (TC) ≥ 6.22 mmol/L, triglycerides (TG) ≥ 2.26 mmol/L, high-density lipoprotein cholesterol (HDL-C) < 1.04 mmol/L, and low-density lipoprotein cholesterol (LDL-C) ≥ 4.14 mmol/L. The logistic regression model was utilized to examine the single effect of PM2.5 constituents on dyslipidemia, while the weighted quantile sum regression model for the joint effect. The odds ratio with a 95 % confidence interval for dyslipidemia positively related to per-SD increase in the three-year average was 1.29 (1.20–1.38) for PM 2.5 mass, 1.25 (1.17–1.34) for black carbon, 1.24 (1.16–1.33) for ammonium, 1.33 (1.24–1.43) for nitrate, 1.34 (1.25–1.44) for organic matter, 1.15 (1.08–1.23) for sulfate, 1.30 (1.22–1.38) for soil particles, and 1.12 (1.05–1.92) for sea salt. Stronger associations were observed in individuals < 65 years of age, males, and those with low physical activity. Joint exposure to PM 2.5 constituents was positively related to dyslipidemia (OR: 1.09, 95 %CI: 1.05–1.14). Nitrate was identified as the constituent with the largest weight (weighted at 0.387). Long-term exposure to PM 2.5 constituents poses a significant risk to dyslipidemia and nitrate might be the most responsible for the risk. These findings indicate that reducing PM 2.5 constituent exposures, especially nitrate, could be beneficial to alleviate the burden of disease attributed to PM 2.5 -related dyslipidemia. • Epidemiologic evidence on the effects of PM 2.5 constituents on dyslipidemia is limited. • Exposure to ambient PM 2.5 constituents was positively associated with dyslipidemia. • Nitrate was found to be the most crucial constituent for increased risk of dyslipidemia. • Young people, males, and those with low physical activity were vulnerable to PM 2.5 constituents. [ABSTRACT FROM AUTHOR]