Long-term effect of fine particulate matter constituents on reproductive hormones homeostasis in women attending assisted reproductive technologies: A population-based longitudinal study.

Fine particulate matter (PM2.5) may disrupt women's reproductive hormones, posing potential reproductive risks. However, the exact compositions of PM2.5 responsible for these effects remain unclear. Our investigation explored the long-term impacts of PM2.5 constituents on reproductive hormones, based on a large longitudinal assisted reproductive cohort study in Anhui, China. We included 24,396 reproductive hormone samples from 19,845 women attending assisted reproductive technologies (ART) between 2014 and 2020. Using high-resolution gridded data (1-km resolution), we calculated the residence-specified PM2.5 constituents during the year before the month of hormone testing. Relationships between PM2.5 constituents [organic matter (OM), chloride (Cl-), sulfate (SO42-), ammonium (NH4+), black carbon, and nitrate] and reproductive hormones were investigated using the linear mixed model with subject-specific intercepts. The constituent-proportion model and the constituent-residual model were also constructed. Additionally, cubic spline analysis was used to examine the potential non-linear exposure-response relationship. We found that per interquartile range (IQR) increment in OM was associated with a 5.31 % (3.74 %, 6.89 %) increase in estradiol, and per IQR increment in Cl- and NH4+ were associated with 13.56 % (7.63 %, 19.82 %) and 9.07 % (4.35 %, 14.01 %) increases in luteinizing hormone. Conversely, per IQR increment in OM and Cl- were associated with -7.27 % (-9.34 %, -5.16 %) and -8.52 % (-10.99 %, -5.98 %) decreases in progesterone, and per IQR increment in SO42- was associated with a -9.15 % (-10.31 %, -7.98 %) decrease in testosterone. These associations were held in both proportional and residual models. Moreover, exposure-response curves for estradiol and progesterone with PM2.5 constituents exhibited approximately U-shaped. These results suggested that specific PM2.5 constituents might disrupt reproductive hormone homeostasis in women attending ART, providing new evidence for formulating PM2.5 pollution reduction strategies that could benefit women's reproductive health.

Particulate matter constituents trigger the formation of extracellular amyloid ß and Tau -containing plaques and neurite shortening in vitro.

Air pollution is an environmental factor associated with an increased risk of neurodegenerative diseases, such as Alzheimer's and Parkinson's, characterized by decreased cognitive abilities and memory. The limited models of sporadic Alzheimer's disease fail to replicate all pathological hallmarks of the disease, making it challenging to uncover potential environmental causes. Environmentally driven models of Alzheimer's disease are thus timely and necessary. We used live-cell confocal fluorescent imaging combined with high-resolution stimulated emission depletion (STED) microscopy to follow the response of retinoic acid-differentiated human neuroblastoma SH-SY5Y cells to nanomaterial exposure. Here, we report that exposure of the cells to some particulate matter constituents reproduces a neurodegenerative phenotype, including extracellular amyloid beta-containing plaques and decreased neurite length. Consistent with the existing in vivo research, we observed detrimental effects, specifically a substantial reduction in neurite length and formation of amyloid beta plaques, after exposure to iron oxide and diesel exhaust particles. Conversely, after exposure to engineered cerium oxide nanoparticles, the lengths of neurites were maintained, and almost no extracellular amyloid beta plaques were formed. Although the exact mechanism behind this effect remains to be explained, the retinoic acid differentiated SH-SY5Y cell in vitro model could serve as an alternative, environmentally driven model of neurodegenerative diseases, including Alzheimer's disease.

Associations of Long-Term Exposure to Fine Particulate Constituents With Cardiovascular Diseases and Underlying Metabolic Mediations: A Prospective Population-Based Cohort in Southwest China.

BACKGROUND: The health effects of particulate matter with an aerodynamic diameter ≤2.5 µm (PM2.5) might differ depending on compositional variations. Little is known about the joint effect of PM2.5 constituents on metabolic syndrome and cardiovascular disease (CVD). This study aims to evaluate the combined associations of PM2.5 components with CVD, identify the most detrimental constituent, and further quantify the mediation effect of metabolic syndrome. METHODS AND RESULTS: A total of 14 427 adults were included in a cohort study in Sichuan, China, and were followed to obtain the diagnosis of CVD until 2021. Metabolic syndrome was defined by the simultaneous occurrence of multiple metabolic disorders measured at baseline. The concentrations of PM2.5 chemical constituents within a 1-km2 grid were derived based on satellite- and ground-based detection methods. Cox proportional hazard models showed that black carbon, organic matter (OM), nitrate, ammonium, chloride, and sulfate were positively associated with CVD risks, with hazard ratios (HRs) ranging from 1.24 to 2.11 (all P<0.05). Quantile g-computation showed positive associations with 4 types of CVD risks (HRs ranging from 1.48 to 2.25, all P<0.05). OM and chloride had maximum weights for CVD risks. Causal mediation analysis showed that the positive association of OM with total CVD was mediated by metabolic syndrome, with a mediation proportion of 1.3% (all P<0.05). CONCLUSIONS: Long-term exposure to PM2.5 chemical constituents is positively associated with CVD risks. OM and chloride appear to play the most responsible role in the positive associations between PM2.5 and CVD. OM is probably associated with CVD through metabolic-related pathways.

Long-term exposure to air pollution and chronic kidney disease-associated mortality-Results from the pooled cohort of the European multicentre ELAPSE-study.

Despite the known link between air pollution and cause-specific mortality, its relation to chronic kidney disease (CKD)-associated mortality is understudied. Therefore, we investigated the association between long-term exposure to air pollution and CKD-related mortality in a large multicentre population-based European cohort. Cohort data were linked to local mortality registry data. CKD-death was defined as ICD10 codes N18-N19 or corresponding ICD9 codes. Mean annual exposure at participant's home address was determined with fine spatial resolution exposure models for nitrogen dioxide (NO2), black carbon (BC), ozone (O3), particulate matter ≤2.5 µm (PM2.5) and several elemental constituents of PM2.5. Cox regression models were adjusted for age, sex, cohort, calendar year of recruitment, smoking status, marital status, employment status and neighbourhood mean income. Over a mean follow-up time of 20.4 years, 313 of 289,564 persons died from CKD. Associations were positive for PM2.5 (hazard ratio (HR) with 95% confidence interval (CI) of 1.31 (1.03-1.66) per 5 µg/m3, BC (1.26 (1.03-1.53) per 0.5 × 10- 5/m), NO2 (1.13 (0.93-1.38) per 10 µg/m3) and inverse for O3 (0.71 (0.54-0.93) per 10 µg/m3). Results were robust to further covariate adjustment. Exclusion of the largest sub-cohort contributing 226 cases, led to null associations. Among the elemental constituents, Cu, Fe, K, Ni, S and Zn, representing different sources including traffic, biomass and oil burning and secondary pollutants, were associated with CKD-related mortality. In conclusion, our results suggest an association between air pollution from different sources and CKD-related mortality.

Long-term exposure to ambient PM2.5 and its constituents is associated with MAFLD.

Background & Aims: Existing evidence suggests that long-term exposure to ambient fine particulate pollution (PM2.5) may increase metabolic dysfunction-associated fatty liver disease (MAFLD) risk. However, there is still limited evidence on the association of PM2.5 constituents with MAFLD. Therefore, this study explores the associations between the five main chemical constituents of PM2.5 and MAFLD to provide more explicit information on the liver exposome. Methods: A total of 76,727 participants derived from the China Multi-Ethnic Cohort, a large-scale epidemic survey in southwest China, were included in this study. Multiple linear regression models were used to estimate the pollutant-specific association with MAFLD. Weighted quantile sum regression was used to evaluate the joint effect of the pollutant-mixture on MAFLD and identify which constituents contribute most to it. Results: Three-year exposure to PM2.5 constituents was associated with a higher MAFLD risk and more severe liver fibrosis. Odds ratios for MAFLD were 1.480, 1.426, 1.294, 1.561, 1.618, and 1.368 per standard deviation increase in PM2.5, black carbon, organic matter, ammonium, sulfate, and nitrate, respectively. Joint exposure to the five major chemical constituents was also positively associated with MAFLD (odds ratio 1.490, 95% CI 1.360-1.632). Nitrate contributed most to the joint effect of the pollutant-mixture. Further stratified analyses indicate that males, current smokers, and individuals with a high-fat diet might be more susceptible to ambient PM2.5 exposure than others. Conclusions: Long-term exposure to PM2.5 and its five major chemical constituents may increase the risk of MAFLD. Nitrate might contribute most to MAFLD, which may provide new clues for liver health. Males, current smokers, and participants with high-fat diets were more susceptible to these associations. Impact and implications: This large-scale epidemiologic study explored the associations between constituents of fine particulate pollution (PM2.5) and metabolic dysfunction-associated fatty liver disease (MAFLD), and further revealed which constituents play a more important role in increasing the risk of MAFLD. In contrast to previous studies that examined the effects of PM2.5 as a whole substance, this study carefully explored the health effects of the individual constituents of PM2.5. These findings could (1) help researchers to identify the specific particles responsible for hepatotoxicity, and (2) indicate possible directions for policymakers to efficiently control ambient air pollution, such as targeting the sources of nitrate pollution.

Association between long-term exposure to PM2.5 constituents and electrocardiographic abnormality: A nationwide longitudinal study in China.

BACKGROUND: Electrocardiogram (ECG) abnormalities are known to have prognostic value for heart conditions, while evidence on the relationship between long-term exposure to PM2.5 constituents and electrocardiographic (ECG) abnormalities is limited. This study aimed to quantify the association between long-term exposure to PM2.5 constituents and changes in ECG diagnoses. METHODS: We designed a longitudinal study among participants with repeated records of ECG examination based on the China National Stroke Screening Survey 2013-2018. Logistic regressions with multiple adjustment, estimated by the generalized estimating equation to incorporate repeated measurements, were used to assess the associations between the occurrence of any physician-diagnosed ECG abnormalities and long-term exposure to PM2.5 constituents. RESULTS: We included 61,094 participants with 132,249 visits. All five constituents (sulfate, nitrate, ammonium, organic matter, and black carbon) were significantly associated with an increased risk of ECG abnormalities. The excess risk of ECG abnormalities per interquartile-range increase in exposure was the highest for sulfate (26%, 95% confidence interval [CI] 23-29%), followed by ammonium (22%, 19-26%), nitrate (21%, 17-24%), black carbon (16%, 13-10%) and organic matter (9%,6%-11%). We also found that atrial fibrillation patients might be susceptible to the adverse effects of PM2.5 constituents on ECG. CONCLUSION: Differential associations between various constituents of PM2.5 and ECG abnormalities were found. The unequal toxicities for different chemical constituents of ambient particles on cardiovascular electrophysiological endpoints should be taken into consideration when considering the biological pathways linking PM2.5 and cardiovascular conditions.

Beyond the mean: Quantile regression to differentiate the distributional effects of ambient PM2.5 constituents on sperm quality among men.

Ambient PM2.5 (particulate matter ≤ 2.5 µm in aerodynamic diameter) constituents have been related to mean changes in semen quality, but focusing on the mean response may not well capture distributional and heterogeneous effects of PM2.5 constituents on semen quality. In this study, 2314 semen samples of 622 men between Jan 1, 2019 and Dec 31, 2019 from Guangdong Human Sperm Bank were subjected to semen quality analysis. Daily average concentrations of PM2.5 constituents including 4 water-soluble ions and 15 metals/metalloid were measured for 7 days per month at 3 fixed atmospheric pollutant monitoring stations. We used quantile regression for longitudinal data to examine whether the associations between PM2.5 constituents and quality indicators of semen varied across quantiles of outcome distribution. Heterogeneous associations were found between PM2.5 constituents and sperm quality across different quantiles. An interquartile range (14.0 µg/m3) increase in PM2.5 mass was negatively associated with lower tails of sperm concentration and upper tails of sperm count distribution. PM2.5 vanadium exposure was significantly related to the 90th percentile of sperm count distribution, but not to the lower quantiles. In addition, those subjects with relatively high sperm motility were more susceptible to sulfate, chromium, and manganese constituents in PM2.5. Our results indicate that PM2.5 and certain constituents were associated with sperm quality, especially sperm motility, and the associations are more pronounced in men with relatively high or low sperm motility.

Acute effects of fine particulate matter constituents on cardiopulmonary function in a panel of COPD patients.

BACKGROUND: Exposure to fine particulate matter (PM2.5) has been linked with adverse cardiorespiratory health conditions. However, evidence for PM2.5 constituents is still scarce, especially among patients with chronic obstructive pulmonary disease (COPD). OBJECTIVE: To investigate the associations of short-term exposure to different chemical constituents of PM2.5 with measures of cardiac and lung function in COPD patients. METHODS: We conducted a retrospective panel study among 100 COPD patients who received repeated measures of left ventricular ejection fraction (LVEF), forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) and peak expiratory flow (PEF) in Shanghai, China from August 2014 to September 2019. Daily PM2.5 and PM2.5 constituents were obtained from fixed-site monitoring station. Linear mixed-effects models were used to estimate the associations of PM2.5. RESULTS: We found water-soluble ions of PM2.5, mainly NO3-, SO42-, and NH4+ were robustly associated with reduced LVEF, and the reductions in LVEF associated with an IQR increase of them ranged from 1.8% to 2.0% (lag 1 d). Metal constituents such as Cu and As were associated with FEV1, FVC and PEF. The corresponding reductions in lung function parameters for an IQR increase of them ranged from 1.4% to 2.3% (lag 0 or 1 d). These associations remained relatively robust after adjusting for total PM2.5 mass and gaseous pollutants. CONCLUSIONS: Our results suggest that water-soluble ions and several metal/metalloid elements might be important constituents in PM2.5 that were associated with reduced cardiorespiratory function among COPD patients.

Associations of maternal exposure to fine particulate matter constituents during pregnancy with Apgar score and duration of labor: A retrospective study in Guangzhou, China, 2012-2017.

BACKGROUND: Limited evidence is available for demonstrating effects of prenatal PM2.5 and its components exposure on Apgar score and duration of labor. OBJECTIVE: We sought to investigate the associations between PM2.5 constituents, Apgar score and duration of labor, and evaluated the potential mediating role of duration of labor. METHODS: This study included 5396 participants. The V4·CH.02 was applied to assessing exposure to PM2.5 constituents. The associations between PM2.5 constituents Apgar score and duration of labor were examined by multivariate linear regression. Mediation analysis was conducted to estimate the potential mediation effect of duration of labor. RESULTS: Trimester-specific exposure to soil dust was significantly associated with 1-min Apgar score (1st trimester: OR: 1.03, 95% CI:0.97, 1.10; 2nd trimester: OR: 1.07, 95% CI: 1.01, 1.14; 3rd trimester: OR: 1.07, 95% CI: 1.01, 1.13), duration of first stage of labor (1st trimester: ß: 0.32, 95% CI: 0.07, 0.58; 2nd trimester: ß: 0.27, 95% CI: 0.04, 0.51; 3rd trimester: ß: 0.37, 95% CI: 0.13, 0.61) and duration of second stage of labor (1st trimester: ß: 0.04, 95% CI: -0.00, 0.09; 2nd trimester: ß: 0.05, 95% CI: 0.01, 0.10; 3rd trimester: ß: 0.05, 95% CI: 0.00, 0.09). The duration of labor mediated the relationship between soil dust and 1-min Apgar score. CONCLUSION: This study demonstrated that prenatal exposure to soil dust was significantly associated with the risk of abnormal 1-min Apgar score and extended stage of labor.

Acute effects of fine particulate matter constituents on mortality: A systematic review and meta-regression analysis.

BACKGROUND: The link between PM2.5 exposure and adverse health outcomes is well documented from studies across the world. However, the reported effect estimates vary across studies, locations and constituents. We aimed to conduct a meta-analysis on associations between short-term exposure to PM2.5 constituents and mortality using city-specific estimates, and explore factors that may explain some of the observed heterogeneity. METHODS: We systematically reviewed epidemiological studies on particle constituents and mortality using PubMed and Web of Science databases up to July 2015.We included studies that examined the association between short-term exposure to PM2.5 constituents and all-cause, cardiovascular, and respiratory mortality, in the general adult population. Each study was summarized based on pre-specified study key parameters (e.g., location, time period, population, diagnostic classification standard), and we evaluated the risk of bias using the Office of Health Assessment and Translation (OHAT) Method for each included study. We extracted city-specific mortality risk estimates for each constituent and cause of mortality. For multi-city studies, we requested the city-specific risk estimates from the authors unless reported in the article. We performed random effects meta-analyses using city-specific estimates, and examined whether the effects vary across regions and city characteristics (PM2.5 concentration levels, air temperature, elevation, vegetation, size of elderly population, population density, and baseline mortality). RESULTS: We found a 0.89% (95% CI: 0.68, 1.10%) increase in all-cause, a 0.80% (95% CI: 0.41, 1.20%) increase in cardiovascular, and a 1.10% (95% CI: 0.59, 1.62%) increase in respiratory mortality per 10µg/m3 increase in PM2.5. Accounting for the downward bias induced by studies of single days, the all-cause mortality estimate increased to 1.01% (95% CI: 0.81, 1.20%). We found significant associations between mortality and several PM2.5 constituents. The most consistent and stronger associations were observed for elemental carbon (EC) and potassium (K). For most of the constituents, we observed high variability of effect estimates across cities. CONCLUSIONS: Our meta-analysis suggests that (a) combustion elements such as EC and K have a stronger association with mortality, (b) single lag studies underestimate effects, and (c) estimates of PM2.5 and constituents differ across regions. Accounting for PM mass in constituent's health models may lead to more stable and comparable effect estimates across different studies. SYSTEMATIC REVIEW REGISTRATION: PROSPERO: CRD42017055765.

Current Methods and Challenges for Epidemiological Studies of the Associations Between Chemical Constituents of Particulate Matter and Health.

Epidemiological studies have been critical for estimating associations between exposure to ambient particulate matter (PM) air pollution and adverse health outcomes. Because total PM mass is a temporally and spatially varying mixture of constituents with different physical and chemical properties, recent epidemiological studies have focused on PM constituents. Most studies have estimated associations between PM constituents and health using the same statistical methods as in studies of PM mass. However, these approaches may not be sufficient to address challenges specific to studies of PM constituents, namely assigning exposure, disentangling health effects, and handling measurement error. We reviewed large, population-based epidemiological studies of PM constituents and health and describe the statistical methods typically applied to address these challenges. Development of statistical methods that simultaneously address multiple challenges, for example, both disentangling health effects and handling measurement error, could improve estimation of associations between PM constituents and adverse health outcomes.