Search

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.

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]

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. 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. 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. 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. [Display omitted] • Chemical components of PM2.5 and 10-year ASCVD risk were positively associated. • Organic matter made the most contribution to the PM-ASCVD relationship. • Participants who were female were more significantly adversely affected. [ABSTRACT FROM AUTHOR]

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.

Current evidence demonstrated that ambient fine particulate matter with an aerodynamic diameter ≤2.5 μm (PM 2.5) and its constituents may be obesogenic in children, but evidence from adults is lacking. Our aim was to characterize the association between PM 2.5 and its constituents and obesity in adults. We included 68,914 participants from the China Multi-Ethnic Cohort (CMEC) baseline survey. Three-year average concentrations of PM 2.5 and its constituents were evaluated by linking pollutant estimates to the geocoded residential addresses. Obesity was defined as body mass index (BMI) ≥ 28 kg/m2. Logistic regression was used to examine the relationship between PM 2.5 and its constituents and obesity. We performed weighed quantile sum (WQS) regression to get the overall effect of PM 2.5 and its constituents and the relative contribution of each constituent. Per-SD increase in PM 2.5 (odds ratio [OR] = 1.43, 95% confidence interval [CI]: 1.37–1.49), black carbon (BC) (1.42, 1.36–1.48), ammonium (1.43, 1.37–1.49), nitrate (1.44, 1.38–1.50), organic matter (OM) (1.45, 1.39–1.51), sulfate (1.42, 1.35–1.48), and soil particles (SOIL) (1.31, 1.27–1.36) were positively associated with obesity, and SS (0.60, 0.55–0.65) was negatively associated with obesity. The overall effect (OR = 1.34, 95% CI: 1.29–1.41) of the PM 2.5 and its constituents was positively associated with obesity, and ammonium made the most contribution to this relationship. Participants who were older, female, never smoked, lived in urban areas, had lower income or higher levels of physical activity were more significantly adversely affected by PM 2.5 , BC, ammonium, nitrate, OM, sulfate and SOIL compared to other individuals. Our study revealed that PM 2.5 constituents except SS were positively associated with obesity, and ammonium played the most important role. These findings provided new evidence for public health interventions, especially the precise prevention and control of obesity. [Display omitted] • Chemical constituents of PM 2.5 were positively related to obesity. • Ammonium played the most important role. • Effects were modified by age, sex, smoking, income, and physical activity. • Participants living in urban areas were more susceptible. [ABSTRACT FROM AUTHOR]

Previous research has implicated PM 2.5 as a potential environmental risk factor for CKD, but little is known about the associations between its components and CKD. We conducted a nationwide cross-sectional study using the updated air pollution data in the nationwide population (N = 2,938,653). Using generalized additive models, we assessed the association between long-term exposure to PM 2.5 and its components (i.e., black carbon [BC], organic matter [OM], nitrate [NO 3 −], ammonium [NH 4 +], sulfate [SO 4 2−]), and CKD prevalence. The air pollution data was estimated using high-resolution and high-quality spatiotemporal datasets of ground-level air pollutants in China. Besides, we adopted a novel quantile-based g-computation approach to assess the effect of a mixture of PM 2.5 constituents on CKD prevalence. The average concentration of PM 2.5 was 78.67 ± 22.5 μg/m3, which far exceeded WHO AQG. In the fully adjusted generalized additive model, at a 10 km × 10 km spatial resolution, the ORs per IQR increase in previous 1-year average PM 2.5 exposures was 1.380 (95%CI: 1.345–1.415), for NH 4 + was 1.094 (95%CI: 1.062–1.126), for BC was 1.604 (95%CI: 1.563–1.646), for NO 3 − was 1.094 (95%CI: 1.060–1.130), for SO 4 2− was 1.239 (95%CI: 1.208–1.272), and for the OM was 1.387 (95%CI: 1.354–1.421), respectively. Subgroup analysis showed females, younger, and healthier were more vulnerable to this effect. In the further exploration of the joint effect of PM 2.5 compositions (OR 1.234 [95%CI 1.222–1.246]) per quartile increase in all 5 PM 2.5 components, we found that PM 2.5 SO 4 2− contributed the most. These findings provide important evidence for the positive relationship between long-term exposure to PM 2.5 and its chemical constituents and CKD prevalence in a Chinese health check-up population, and identified PM 2.5 SO 4 2− has the highest contribution to this relationship. This study provides clinical and public health guidance for reducing specific air particle exposure for those at risk of CKD. • Long-term exposure to PM 2.5 and its components is significantly associated with CKD prevalence. • Sulfate is the strongest contributor to the CKD prevalence among PM 2.5 components. • Our research provids updated evidence for clinical and public health guidance. [ABSTRACT FROM AUTHOR]

Metabolic syndrome (MetS) is considered a main public health issue as it remarkably adds the risk of cardiovascular disease, leading to a heavy burden of disease. There is growing evidence linking fine particulate matter (PM 2.5) exposure to MetS. However, the influences of PM 2.5 constituents, especially in children and adolescents, remain unclear. Our study was according to a national analysis among Chinese children and adolescents to examine the associations between long-term exposure to PM 2.5 main constituents and MetS. A total of 10,066 children and adolescents aged 10–18 years were recruited in 7 provinces in China, with blood tests, health exams, and questionnaire surveys. We estimated long-term exposures to PM 2.5 mass and its five constituents, containing black carbon (BC), organic matter (OM), inorganic nitrate (NO 3 −), sulfate (SO 4 2−), and soil particles (SOIL) from multi-source data fusion models. Mixed-effects logistic regression models were used with the adjustment of a variety of covariates. In the surveyed populations, 2.9% were classified as MetS. From the single-pollutant models, we discovered that long-term exposures to PM 2.5 mass, BC, OM, NO 3 −, as well as SO 4 2−, were significantly associated with the prevalence of MetS, with odds ratios (ORs) per 1 μg/m3 that were 1.02 (95% confidence interval (CI): 1.01, 1.03) for PM 2.5 mass, 1.24 (95% CI: 1.14, 1.35) for BC, 1.07 (95% CI: 1.04, 1.11) for OM, 1.09 (95% CI: 1.04, 1.13) for NO 3 −, and 1.14 (95% CI:1.04, 1.24) for SO 4 2−. The influence of BC on the prevalence of MetS was robust in both the multi-pollutant model and the PM 2.5 -constituent joint model. The paper indicates long-term exposure to PM 2.5 mass and specific PM 2.5 constituents, particularly for BC, was significantly associated with a higher MetS prevalence among children and adolescents in China. Our results highlight the significance of establishing further regulations on PM 2.5 constituents. • 10,066 children and adolescents from 7 province with blood tests were involved. • Long-term exposure to PM 2.5 mass was significantly associated with the childhood MetS. • Black carbon exposure has a robust positive association with childhood MetS. [ABSTRACT FROM AUTHOR]

• Tailpipe tracers of PM 2.5 (EC and OC) were associated with ASD in single pollutant models. • Non-tailpipe tracers of PM 2.5 (Cu, Fe and Mn) were associated with ASD in single pollutant models. • Associations of Cu, Fe, and Mn were largely unchanged by adjusting for EC or OC. • However, EC and OC associations were markedly attenuated by adjustment for non-tailpipe sources. • Reducing tailpipe emissions may not eliminate ASD associations with traffic-related air pollution. 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 (PM 2.5) 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. 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 PM 2.5 and PM 2.5 constituents EC, OC, Cu, Fe, and Mn with 4 km spatial resolution were obtained from a source-oriented chemical transport model. These exposures and NO 2 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 PM 2.5 and NO 2 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. 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 PM 2.5 , NO 2 , EC or OC. In contrast, ASD associations with EC and OC were markedly attenuated by adjustment for non-tailpipe sources. 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. [ABSTRACT FROM AUTHOR]

PM 2.5 is a well-known airborne hazard to cause various diseases. Evidence suggests that air pollution exposure contributes to the occurrence of pulmonary nodules. Pulmonary nodules detected on the computed tomography scans can be malignant or progress to malignant during follow-up. But the evidence of the association between PM 2.5 exposure and pulmonary nodules was limited. To examine potential associations of exposures to PM 2.5 and its major chemical constituents with the prevalence of pulmonary nodules. A total of 16 865 participants were investigated from eight physical examination centers in China from 2014 to 2017. The daily concentrations of PM 2.5 and its five components were estimated by high-resolution and high-quality spatiotemporal datasets of ground-level air pollutants in China. The logistic regression and the quantile-based g-computation models were used to assess the single and mixture impact of air pollutant PM 2.5 and its components on the risk of pulmonary nodules, respectively. Each 1 mg m -3 increase in PM 2.5 (OR 1.011 (95% CI: 1.007-1.014)) was positively associated with pulmonary nodules. Among five PM 2.5 components, in single-pollutant effect models, every 1 μ g m -3 increase in organic matter (OM), black carbon (BC), and NO 3 - elevated the risk of pulmonary nodule prevalence by 1.040 (95% CI: 1.025-1.055), 1.314 (95% CI: 1.209-1.407) and 1.021 (95% CI: 1.007-1.035) fold, respectively. In mixture-pollutant effect models, the joint effect of every quintile increase in PM 2.5 components was 1.076 (95% CI: 1.023-1.133) fold. Notably, NO 3 - BC and OM contributed higher risks of pulmonary nodules than other PM 2.5 components. And the NO 3 - particles were identified to have the highest contribution. The impacts of PM 2.5 components on pulmonary nodules were consistent across gender and age.These findings provide important evidence for the positive correlation between exposure to PM 2.5 and pulmonary nodules in China and identify that NO 3 - particles have the highest contribution to the risk., (© 2023 IOP Publishing Ltd.)

Fine particulate matter (PM 2.5) has been linked to gestational diabetes mellitus (GDM). However, PM 2.5 is a complex mixture with large spatiotemporal heterogeneities, and women with early-onset GDM (i.e., diagnosed before 24th gestation week) have distinct maternal characteristics and a higher risk of worse health outcomes compared with those with late-onset GDM (i.e., diagnosed in or after 24th gestation week). We aimed to examine differential impacts of PM 2.5 and its constituents on early-vs. late-onset GDM, and to identify corresponding susceptible exposure windows. We leveraged statewide linked electronic health records and birth records data in Florida in 2012–2017. Exposures to PM 2.5 and its constituents (i.e., sulfate [SO 4 2−], ammonium [NH 4 +], nitrate [NO 3 −], organic matter [OM], black carbon [BC], mineral dust [DUST], and sea-salt [SS]) were spatiotemporally linked to pregnant women based on their residential histories. Cox proportional hazards models and multinomial logistic regression were used to examine the associations of PM 2.5 and its constituents with GDM and its onsets. Distributed non-linear lag models were implemented to identify susceptible exposure windows. Exposures to PM 2.5 , SO 4 2−, NH 4 +, and BC were statistically significantly associated with higher hazards of GDM. Exposures to PM 2.5 during weeks 1–12 of gestation were positively associated with GDM. Associations of early-onset GDM with PM 2.5 in the 1st and 2nd trimesters, SO 4 2− in the 1st and 2nd trimesters, and NO 3 − in the preconception and 1st trimester were considerably stronger than observations for late-onset GDM. Our findings suggest there are differential associations of PM 2.5 and its constituents with early-vs. late-onset GDM, with different susceptible exposure windows. This study helps better understand the impacts of air pollution on GDM accounting for its physiological heterogeneity. [Display omitted] • Associations of PM 2.5 components with GDM onset were examined. • Differential associations with early-vs. late-onset GDM were found. • Susceptible exposure windows are different for early-vs. late-onset GDM. [ABSTRACT FROM AUTHOR]

[Display omitted] • PM 2.5 components, particularly those from combustion-related sources, are associated with cognitive decline. • Sleep quality plays a mediation role in the association between PM 2.5 and its chemical composition and cognitive decline. • Higher greenspace is associated with lower risk of cognitive decline associated with PM 2.5 components. Although exposure to fine particulate matter (PM 2.5) has been associated with cognitive decline, little is known about which PM 2.5 constituents are more harmful. Recent study on the association between PM 2.5 and sleep quality prompted us to propose that sleep quality may mediate the adverse effects of PM 2.5 components on cognitive decline. Understanding the association between PM 2.5 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 PM 2.5 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 PM 2.5 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 PM 2.5 [−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 PM 2.5. 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 PM 2.5 components. Our study suggests that the adverse effect of suffering from PM 2.5 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. [ABSTRACT FROM AUTHOR]

Factor analysis is a commonly used method of modelling correlated multivariate exposure data. Typically, the measurement model is assumed to have constant factor loadings. However, from our preliminary analyses of the Environmental Protection Agency's (EPA's) PM2.5 fine speciation data, we have observed that the factor loadings for four constituents change considerably in stratified analyses. Since invariance of factor loadings is a prerequisite for valid comparison of the underlying latent variables, we propose a factor model that includes non-constant factor loadings that change over time and space using P-spline penalized with the generalized cross-validation (GCV) criterion. The model is implemented using the Expectation-Maximization (EM) algorithm and we select the multiple spline smoothing parameters by minimizing the GCV criterion with Newton's method during each iteration of the EM algorithm. The algorithm is applied to a one-factor model that includes four constituents. Through bootstrap confidence bands, we find that the factor loading for total nitrate changes across seasons and geographic regions. [ABSTRACT FROM AUTHOR]

Previous studies have indicated the associations between fine particulate matter (PM 2.5) exposure and diabetes or glucose levels. However, evidence linking PM 2.5 constituents and diabetes or glucose levels was extensively scarce, particularly in developing countries. This study aimed to investigate the associations of exposure to PM 2.5 and its five constituents (black carbon [BC], organic matter [OM], nitrate [NO 3 -], sulfate [SO 4 2-], and ammonium [NH 4 +]) with diabetes and glucose levels among the middle-aged and elderly Chinese populations. 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 HbA 1c ≥6.5 or fasting glucose ≥7 mmol/L or random glucose ≥11.1 mmol/L. Monthly exposure to PM 2.5 mass and its five constituents (BC, OM, NO 3 -, SO 4 2-, and NH 4 +) 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 PM 2.5 and its constituents on diabetes or glucose levels, respectively. Stratification analyses were done by sex and age. We included a total of 17,326 adults over 45 years in this study. The 3-year mean (interquartile range [IQR]) concentrations of PM 2.5 , BC, OM, NO 3 -, SO 4 2-, and NH 4 + 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 PM 2.5 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]), NO 3 - (0.145 mmol/L [0.039−0.251]), SO 4 2- (0.111 mmol/L [0.026−0.196]), and NH 4 + (0.135 mmol/L [0.041−0.230]). Under different diabetes definitions, PM 2.5 mass and selected constituents with the exception of SO 4 2- 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 PM 2.5 , 1.154 (1.079−1.235) for BC, 1.170 (1.079−1.270) for OM, 1.200 (1.098−1.312) for NO 3 -, and 1.123 (1.037−1.215) for NH 4 +. 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 PM 2.5. Participants under 65 years were generally more vulnerable to diabetes hazards related to PM 2.5 constituents exposure. Exposures to PM 2.5 and its constituents (i.e., BC, OM, NO 3 -, and NH 4 +) were positively associated with increased risks of prevalent diabetes and elevated glucose levels in middle-aged and older adults. [Display omitted] • Nationwide study investigating long-term associations of PM 2.5 constituents' exposure with diabetes and glucose. • Positive associations between PM 2.5 constituents and diabetes were robust to analysis using multiple definitions. • PM 2.5 constituents were associated with elevated glucose levels among nondiabetics only. • Mixture effects and the relative importance of each PM 2.5 constituent were investigated. [ABSTRACT FROM AUTHOR]

Growing evidence suggests that fine particulate matter (PM 2.5 ) 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 PM 2.5 major chemical composition, including black carbon (BC), organic matter (OM), nitrate (NO 3 - ), sulfate (SO 4 2- ), ammonium (NH 4 + ), and soil dust (DUST). To investigate the impact of long-term exposure to PM 2.5 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 PM 2.5 and its major constituents. An interquartile range increase in PM 2.5 mass was associated with a 6 to 7% increase in dementia incidence and a 9% increase in AD incidence. For different PM 2.5 constituents, associations remained significant for BC, OM, SO 4 2- , and NH 4 + for both end points (even after adjustments of other constituents), among which BC and SO 4 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 PM 2.5 is significantly associated with higher rates of incident dementia and AD and that SO 4 2- , BC, and OM related to traffic and fossil fuel combustion might drive the observed associations.

The general toxicity of fine particulate matter (PM 2.5 ) has been intensively studied, but its pulmonary toxicities are still not fully understood. To investigate the changes of lung tissue after PM 2.5 exposure and identify the potential mechanisms of pulmonary toxicity, PM 2.5 samples were firstly collected and analyzed. Next, different doses of PM 2.5 samples (5 mg/kg, 10 mg/kg, 20 mg/kg) were intratracheally instilled into rats to simulate lung inhalation of polluted air. After instillation for eight weeks, morphological alterations of the lung were examined, and the levels of oxidative stress were detected. The data indicated that the major contributors to PM 2.5 mass were organic carbon, elemental carbon, sulfate, nitrate, and ammonium. Different concentrations of PM 2.5 could trigger oxidative stress through increasing reactive oxygen species (ROS) and 8-hydroxy-2'-deoxyguanosine (8-OHdG) levels, and decreasing expression of antioxidant-related proteins (nuclear factor erythroid 2-related factor 2 (Nrf2), superoxide dismutase 1 (SOD1) and catalase). Histochemical staining and transmission electron microscopy displayed pulmonary inflammation, collagen deposition, mitochondrial swelling, and a decreasing number of multilamellar bodies in alveolar type II cells after PM 2.5 exposure, which was related to PM 2.5 -induced oxidative stress. These results provide a basis for a better understanding of pulmonary impairment in response to PM 2.5 .

Dyslipidemia may be a potential mechanism linking fine particulate matter (PM 2.5 ) to adverse cardiovascular outcomes. However, inconsistent associations between PM 2.5 and blood lipids have resulted from the existing research, and the joint effect of PM 2.5 elemental constituents on blood lipid profiles remains unclear. We aimed to explore the overall associations between PM 2.5 elemental constituents and blood lipid profiles and to identify the significant PM 2.5 elemental constituents in this association. Sixty-nine elderly people were recruited between September 2018 and January 2019. Each participant completed a survey questionnaire, 3 days of individual exposure monitoring, health examination, and biological sample collection at each follow-up visit. Bayesian kernel machine regression (BKMR) models were used to identify the joint effects of the 17 elemental constituents on blood lipid profiles. Total cholesterol, low-density lipoprotein cholesterol (LDL-C), and non-high-density lipoprotein cholesterol (non-HDL-C) levels were significantly increased in older adults when exposed to the mixture of PM 2.5 elemental constituents. Copper and titanium had higher posterior inclusion probabilities than other constituents, ranging from 0.76 to 0.90 (Cu) and 0.74 to 0.94 (Ti). Copper and titanium in the PM 2.5 elemental constituent mixture played an essential role in changes to blood lipid levels. This study highlights the importance of identifying critical hazardous PM 2.5 constituents that may cause adverse cardiovascular outcomes in the future.

Fine particulate matter (PM 2.5 ) was reported to be associated with metabolic syndrome (MetS), but how PM 2.5 constituents affect MetS and the underlying mediators remains unclear. We aimed to investigate the associations of long-term exposure to 24 kinds of PM 2.5 constituents with MetS (defined by five indicators) in middle-aged and elderly adults and to further explore the potential mediating role of apolipoprotein B (ApoB). A multicenter study was conducted by recruiting subjects ( n = 2045) in the Beijing-Tianjin-Hebei region from the cohort of Sub-Clinical Outcomes of Polluted Air in China (SCOPA-China Cohort). Relationships among PM 2.5 constituents, serum ApoB levels, and MetS were estimated by multiple logistic/linear regression models. Mediation analysis quantified the role of ApoB in "PM 2.5 constituents-MetS" associations. Results indicated PM 2.5 was significantly related to elevated MetS prevalence. The MetS odds increased after exposure to sulfate (SO 4 2- ), calcium ion (Ca 2+ ), magnesium ion (Mg 2+ ), Si, Zn, Ca, Mn, Ba, Cu, As, Cr, Ni, or Se (odds ratios ranged from 1.103 to 3.025 per interquartile range increase in each constituent). PM 2.5 and some constituents (SO 4 2- , Ca 2+ , Mg 2+ , Ca, and As) were positively related to serum ApoB levels. ApoB mediated 22.10% of the association between PM 2.5 and MetS. Besides, ApoB mediated 24.59%, 50.17%, 12.70%, and 9.63% of the associations of SO 4 2- , Ca 2+ , Ca, and As with MetS, respectively. Our findings suggest that ApoB partially mediates relationships between PM 2.5 constituents and MetS risk in China.

As the major constituents of PM 2.5 , carbonaceous constituents and inorganic ions have attracted emerging attentions on their health risks, particularly on cardiorespiratory diseases. However, evidences on the risks of PM 2.5 constituents on other diseases (eg. nervous disease, genitourinary disease, neoplasms and endocrine disease) remain scarce. In our study, we firstly calculated residuals of PM 2.5 constituents regressed on PM 2.5 to remove the confounding effect of PM 2.5. Then, generalized additive model (GAM) was used to assess impacts of residuals of PM 2.5 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 NO 3 - 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 NO 3 - with endocrine disease and neoplasm. For more specific causes, the highest effect estimates of EC and NO 3 - 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. The association between PM 2.5 and its constituents and cause-specific mortality. [Display omitted] • We explored independent effects of PM 2.5 constituents on mortality from 36 diseases. • EC, OC and NO 3 - were significantly associated with cardiovascular mortality. • EC was significantly associated with respiratory mortality. • NO 3 - was significantly associated with deaths of endocrine disease and neoplasm. [ABSTRACT FROM AUTHOR]

Ambient fine particulate matter (PM 2.5) has been linked to various cardiovascular disease (CVD) endpoints. However, little is known regarding the health effects of PM 2.5 constituents. This study aimed to assess the associations of CVD incidence with long-term exposures to PM 2.5 constituents in China, including black carbon (BC), organic matter (OM), sulfate (SO 4 2−), nitrate (NO 3 −) and ammonium (NH 4 +). A nationwide cohort of 14,331 adults were drawn from the China Family Panel Study, a high-quality longitudinal survey initiated from 2010 over 25 provincial regions in China. We used the baseline survey and the ensuing three waves of follow-up data during 2010–2017 to conceive our study cohort. Annual county-level exposures of PM 2.5 and its constituents for each participant were assessed by aggregating satellite-derived estimates at a monthly time-scale and 1 km-resolution. A directed acyclic graph (DAG) was developed to identify confounding variables. Cox proportional hazards models with time-varying exposures and province-level random intercepts were employed to quantify associations of CVD incidence with long-term exposures to PM 2.5 and its constituents. During 84,162.4 person-years' follow-up, a total of 1575 CVD, 953 hypertension and 342 stroke incidents occurred. DAG-based Cox model estimated an hazard ratio (HR) of 1.291 (95% confidence interval: 1.147–1.454) for total CVD and 1.326 (1.151–1.528) for hypertension, associated with per interquartile range (IQR=27.9 μg/m3) increase in exposure to PM 2.5 mass. Elevated CVD risks were also significantly related to several PM 2.5 constituents, with the largest HRs observed in SO 4 2− (1.721 [1.517–1.951], IQR = 5.67 μg/m3), followed by NH 4 + (1.537 [1.341–1.762], IQR = 4.44 μg/m3), NO 3 − (1.311 [1.128–1.523], IQR = 8.92 μg/m3) and BC (1.294 [1.158–1.446], IQR = 2.28 μg/m3). No associations were identified between long-term exposures to particulate constituents and incidence of stroke. Associations with PM 2.5 and constituents (BC, NO 3 −, NH 4 + and SO 4 2−) were more pronounced among adults aged over 50 years, and residents in southern region. Long-term exposures to PM 2.5 mass and specific constituents (i.e., BC, NO 3 −, NH 4 + and SO 4 2−) were associated with increased risks of total CVD and hypertension incidence in Chinese adults. Findings may have implications for in-depth understandings of biological mechanisms in chronic impacts of ambient PM 2.5 on cardiovascular health. [Display omitted] • First cohort study to assess chronic effects of PM 2.5 constituents on CVD incidence in China. • Long-term exposures to PM 2.5 and specific constituents (BC, NO 3 −, NH 4 + and SO 4 2−) may elevate risk of CVD incidence. • Constituents-CVD associations were stronger in the elderly and southern region of China. [ABSTRACT FROM AUTHOR]

Background: Although ambient fine particulate matter (PM2.5) has been associated with adverse respiratory outcomes in children, few studies have examined PM2.5 constituents with respiratory diseases in children in China.Objectives: To investigate the associations of short-term exposure to PM2.5 and its constituents with pediatric emergency room visits (ERVs) for respiratory diseases in Shanghai, China.Methods: We collected daily concentrations of PM2.5 and its constituents in urban Shanghai from January 1, 2016, to December 31, 2018. Daily pediatric ERVs for four major respiratory diseases, including upper respiratory tract infection, bronchitis, pneumonia, and asthma, were obtained from 66 hospitals in Shanghai during the same period. Associations of exposure to daily PM2.5 and constituents with respiratory ERVs were estimated using the over-dispersed generalized additive models.Result: Short-term exposure to PM2.5 and its constituents were associated with increased pediatric ERVs for respiratory diseases. Specifically, an interquartile range increase in the 3-day average PM2.5 level (31 μg/m3) was associated with 1.86% (95%CI: 0.52, 3.22), 1.53% (95%CI: 0.01, 3.08), 1.90% (95%CI: 0.30, 3.52), and 2.67% (95%CI: 0.70, 4.68) increase of upper respiratory tract infection, bronchitis, pneumonia, and asthma ERVs, respectively. As for PM2.5 constituents, we found organic carbon, ammonium, nitrate, selenium, and zinc were associated with higher risk of respiratory ERVs in the single constituent and the constituent-PM2.5 models.Conclusion: Short-term exposure to PM2.5 was associated with increased pediatric ERVs for respiratory diseases. Constituents related to anthropogenic combustion and traffic might be the dominant contributors of the observed associations. [ABSTRACT FROM AUTHOR]

Limited evidence is available on the associations of long-term exposure to various fine particulate matter (PM 2.5) constituents with sub-clinical outcomes of cardiovascular disease (CVD) in China. We aimed to explore the associations of PM 2.5 and its constituents with blood pressure (BP), fasting glucose, and cardiac electrophysiological (ECG) properties based on a national survey of 5852 Chinese adults, who participated in the Sub-Clinical Outcome of Polluted Air study, from July 2017 to March 2019. Annual residential exposure to PM 2.5 and its constituents of each subject was predicted by a satellite-based mode. We assessed the associations between five main constituents [organic matter (OM), black carbon (BC), sulfate (SO 4 2−), nitrate (NO 3 −), ammonium (NH 4 +)] of PM 2.5 and systolic BP (SBP), diastolic BP (DBP), fasting glucose, and ECG measurements (PR, QRS, QT, and QTc interval) using multivariable linear regression models. Long-term PM 2.5 exposure was significantly associated with increased levels of fasting glucose, DBP, and ECG measurements. An IQR increase in OM (8.2 μg/m3) showed considerably stronger associations with an elevated fasting glucose of 0.39 mmol/L (95%CI confidence interval: 0.28, 0.49) compared with other PM 2.5 constituents. Meanwhile, an IQR increase in NO 3 −, NH 4 + and OM had stronger associations with DBP and ECG parameters compared with BC and SO 4 2−. This nationwide multi-center study in China indicated that some constituents (i.e., OM, NO 3 −, and NH 4 +) might be mainly responsible for the association of PM 2.5 with sub-clinical outcomes of CVD including BP, fasting glucose, and ECG measurements. Unlabelled Image • Few studies explore the associations of PM 2.5 constituents with sub-clinical outcomes. • PM 2.5 constituents were significantly associated with sub-clinical outcomes. • Some constituents may dominate the association of PM 2.5 with sub-clinical outcomes. [ABSTRACT FROM AUTHOR]

• This is the largest evaluation on the effects of PM 2.5 constituents on cause-specific mortality in China. • PM 2.5 constituents were significantly associated with mortality risk in China, with largest effect for OC. • Those with cardiovascular disease, females, the elderly, and illiterates were more vulnerable to PM 2.5 constituents. • Higher mortality risks of PM 2.5 constituents were generally observed in residents in the South and urban communities. Fine particulate matter (with aerodynamic diameter ≤2.5 µm, PM 2.5) causes huge disease burden worldwide. However, evidence is still inadequate and inconsistent on the relationships between PM 2.5 constituents and mortality, especially in low resource settings. To evaluate the impact of PM 2.5 constituents on cause-specific mortality in China. We obtained daily mortality data for 161 communities in 2011–2013 from the Disease Surveillance Point system in China. Daily concentrations of major PM 2.5 constituents, including organic carbon (OC), elemental carbon (EC), sulphate (SO 4 2-), nitrate (NO 3 -) and ammonium (NH 4 +), 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 PM 2.5 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. Each interquartile range change of EC, OC, SO 4 2- , NO 3 - and NH 4 + 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. Our findings suggest positive associations between PM 2.5 constituents and cause-specific mortality, particularly for myocardial infarction. [ABSTRACT FROM AUTHOR]

Understanding the heterogeneity between ambient concentration and personal exposure is crucial in studies regarding the health risks of air pollution exposure. We performed a panel study with 4–19 (average = 10) repeated personal monitoring in 16 adult subjects (ages 18–30) for three consecutive weeks during the winter and summer of 2011–2012 in the Chinese megacity of Guangzhou. Also, we conducted simultaneous ambient measurements at eight districts (including five urban sites, two suburban locations, and one rural site) of Guangzhou. Significant seasonal variations were shown in personal PM 2.5 exposure for most of the analyzed components (p < 0.05), with higher levels in winter than in summer. Average personal exposures exhibited a pattern of central urban > suburban > rural areas for PM 2.5 mass and most of the constituents (e.g., carbonaceous aerosols, ions). We applied mixed-effects models to estimate within- and between-subject variance components and determinants of personal PM 2.5 exposure after adjusting for potential confounders. The within-subject variance component dominated the total variability (63.7–95.6%) for most of the investigated PM 2.5 components. Ambient PM 2.5 mass and its components were the dominant predictors and contributors of the corresponding personal exposures (0.11 < R c 2 < 0.97; p < 0.05). The results indicate that season and district type affect personal PM 2.5 exposure and its components, contributing to 4.9–51.6% and 8.0–77.8% of the variability. Time indoors and outdoors were also factors affecting personal exposure. The study findings revealed ambient concentrations at a fixed monitoring station underestimated residents' true exposure levels. In conclusion, the current study emphasizes the need for incorporating spatio-temporal activity patterns complementing evenly-distributed air quality monitoring networks to increase the estimation power in epidemiological analysis linking true personal exposure to health effects. • Repeated personal monitoring is required in epidemiological study design for assessing the health effects of PM 2.5 exposure. • Within-subject variance dominated the total variability of most exposure data. • Average ambient concentrations from multiple monitoring sites serve as better surrogates for young adults exposures. • Ambient concentrations, season, district type, and time indoors were factors influencing personal exposures. [ABSTRACT FROM AUTHOR]

Factor analysis is a commonly used method of modelling correlated multivariate exposure data. Typically, the measurement model is assumed to have constant factor loadings. However, from our preliminary analyses of the Environmental Protection Agency's (EPA's) PM 2.5 fine speciation data, we have observed that the factor loadings for four constituents change considerably in stratified analyses. Since invariance of factor loadings is a prerequisite for valid comparison of the underlying latent variables, we propose a factor model that includes non-constant factor loadings that change over time and space using P-spline penalized with the generalized cross-validation (GCV) criterion. The model is implemented using the Expectation-Maximization (EM) algorithm and we select the multiple spline smoothing parameters by minimizing the GCV criterion with Newton's method during each iteration of the EM algorithm. The algorithm is applied to a one-factor model that includes four constituents. Through bootstrap confidence bands, we find that the factor loading for total nitrate changes across seasons and geographic regions.