Fine Particulate Matter Constituents Research Articles

Long-term exposure to major constituents of fine particulate matter and neurodegenerative diseases: A population-based survey in the Pearl River Delta Region, China

BackgroundExposure to PM2.5 has been linked to neurodegenerative diseases, with limited understanding of constituent-specific contributions. ObjectivesTo explore the associations between long-term exposure to PM2.5 constituents and neurodegenerative diseases. MethodsWe recruited 148,274 individuals aged ≥ 60 from four cities in the Pearl River Delta region, China (2020 to 2021). We calculated twenty-year average air pollutant concentrations (PM2.5 mass, black carbon (BC), organic matter (OM), ammonium (NH4+), nitrate (NO3-) and sulfate (SO42-)) at the individuals' home addresses. Neurodegenerative diseases were determined by self-reported doctor-diagnosed Alzheimer’s disease (AD) and Parkinson’s disease (PD). Generalized linear mixed models were employed to explore associations between pollutants and neurodegenerative disease prevalence. ResultsPM2.5 and all five constituents were significantly associated with a higher prevalence of AD and PD. The observed associations generally exhibited a non-linear pattern. For example, compared with the lowest quartile, higher quartiles of BC were associated with greater odds for AD prevalence (i.e., the adjusted odds ratios were 1.81; 95% CI, 1.45–2.27; 1.78; 95% CI, 1.37–2.32; and 1.99; 95% CI, 1.54–2.57 for the second, third, and fourth quartiles, respectively). ConclusionsLong-term exposure to PM2.5 and its constituents, particularly combustion-related BC, OM, and SO42-, was significantly associated with higher prevalence of AD and PD in Chinese individuals. Environmental implicationPM2.5 is a routinely regulated mixture of multiple hazardous constituents that can lead to diverse adverse health outcomes. However, current evidence on the specific contributions of PM2.5 constituents to health effects is scarce. This study firstly investigated the association between PM2.5 constituents and neurodegenerative diseases in the moderately to highly polluted Pearl River Delta region in China, and identified hazardous constituents within PM2.5 that have significant impacts. This study provides important implications for the development of targeted PM2.5 prevention and control policies to reduce specific hazardous PM2.5 constituents.

The joint effects of prenatal exposure to PM2.5 constituents and reduced fetal growth on children's accelerated growth in the first 3 years: a birth cohort study.

Prenatal fine particulate matter (PM2.5) constituents exposure and reduced fetal growth may be risk factors for accelerated growth in early childhood, an important indicator for lifelong health. The study investigated whether the joint effects are present between PM2.5 constituents and reduced fetal growth. The study was embedded in a birth cohort in China, including 5424 mother-child pairs. Prenatal PM2.5 and its constituents' [organic carbon (OC), elementary carbon (EC), ammonium (NH4+), nitrate (NO3-), and sulfate (SO42-)] concentrations were estimated based on maternal residential addresses. Fetal growth was evaluated by fetal growth trajectory in utero and preterm birth (PTB), low birth weight (LBW), and small for gestational age (SGA). Children's accelerated growth was defined as body mass index (BMI) Z-score change of >0.67 between birth and 3 years. Generalized logistic regression was used to analyze the effects of prenatal PM2.5 constituents exposure and fetal growth on children's accelerated growth. Joint effect was tested on multiplicative scale and additive scale with the relative excess risk due to interaction (RERI). Children with lower fetal growth trajectory, PTB, LBW, and SGA had increased odds of children's accelerated growth, with odds ratios (ORs) ranging from 1.704 to 11.605. Compared with lower exposure (≤median), higher exposure (>median) of PM2.5, OC, and SO42- were significantly associated with increased odds of children's accelerated growth, varying in ORs from 1.163 to 1.478. Prenatal exposure to OC had joint effects with lower fetal growth on children's accelerated growth. We observed that the interaction was statistically significant on an additive scale in OC and lower fetal growth trajectory (RERI: 0.497, 95% CI: 0.033,0.962). Fine particulate matter (PM2.5) is a huge threat to human health worldwide, causing 6.7 million death globally in 2019. According to the theory of DOHaD, prenatal PM2.5 exposure could influence early childhood growth, which is important for lifelong health. We found that prenatal exposure to PM2.5, OC, and SO42- was associated with higher risk of accelerated childhood growth in the first 3 years. More importantly, reduced fetal growth moderated these associations. Our findings highlight the need for policies and interventions on PM2.5 constituents to improve lifelong health, especially for those vulnerable populations with reduced fetal growth.

Associations between brake and tire wear-related PM2.5 metal components, particulate oxidative stress potential, and autism spectrum disorder in Southern California

BackgroundAir pollution is a global health concern, with fine particulate matter (PM2.5) constituents posing potential risks to human health, including children's neurodevelopment. Here we investigated associations between exposure during pregnancy and infancy to specific traffic-related PM2.5 components with Autism Spectrum Disorder (ASD) diagnosis. MethodsFor exposure assessment, we estimated PM2.5 components related to traffic exposure (Barium [Ba] as a marker of brake dust and Zinc [Zn] as a tire wear marker, Black Carbon [BC]) and oxidative stress potential (OSP) markers (Hydroxyl Radical [OPOH] formation, Dithiothreitol activity [OPDTT], reactive oxygen species [ROS]) modeled with land use regression with co-kriging based on an intensive air monitoring campaign. We assigned exposures to a cohort of 444,651 children born in Southern California between 2016 and 2019, among whom 11,466 ASD cases were diagnosed between 2018 and 2022, Odds ratios (ORs) and 95% confidence intervals (CIs) were obtained with logistic regression for single pollutant and PM2.5 mass co-adjusted models, also adjusting for sociodemographic characteristics. ResultsAmong PM2.5 components, we found the strongest positive association with ASD for our brake wear marker Ba (ORper IQR = 1.29, 95 % CI: 1.24, 1.34). This was followed by an increased risk for all PM2.5 oxidative stress potential markers; the strongest association was with ROS formation (ORper IQR = 1.22, 95 % CI: 1.18, 1.25). PM2.5 mass was linked to ASD in Hispanic and Black children, but not White children, while traffic-related PM2.5 and OSP markers increased ASD risk across all groups. In neighborhoods with the lowest socioeconomic status (SES), associations with ASD were stronger for all examined pollutants compared to higher SES areas. ConclusionsOur findings suggest that brake wear-related PM2.5 and PM2.5 OSP are associated with ASD diagnosis in Southern California. These results suggest that strategies aimed at reducing the public health impacts of PM2.5 need to consider specific sources.

Associations of exposure to ambient fine particulate matter constituents from different pollution sources with semen quality: Evidence from a prospective cohort

The association between ambient fine particulate matter (PM2.5) exposure and semen quality remains inconclusive, possibly due to variations in pollution sources and PM2.5 compositions. Studies investigating the constituents of PM2.5 have been hindered by small sample sizes, and research exploring the relationships between PM2.5 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 PM2.5. This study included 9013 semen samples from 4417 males in the urban districts of Hefei. The median concentrations of PM2.5 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 PM2.5 with semen quality. The results showed that exposure to PM2.5-bound metals (antimony, arsenic, cadmium, lead, and thallium) and WSIs (sulphate and chloride) were negatively associated with semen quality parameters. Moreover, mixtures of PM2.5-bound metals and WSIs were negatively associated with semen quality. Additionally, PM2.5 derived from traffic emissions was negatively associated with semen quality. In summary, our study revealed that ambient PM2.5 and its constituents, especially metals, were negatively associated with semen quality. Antimony, lead, and thallium emerged as the primary contributors to toxicity, and PM2.5 from traffic emissions was associated with decreased semen quality. These findings have important public health implications for the management of PM2.5 pollution in the context of male reproductive health.

Ambient fine particulate matter constituents and semen quality among adult men in China

Exposure to ambient fine particulate matter (PM2.5) was associated with decreased semen quality, but the relationship between PM2.5 constituents and semen quality was unclear. We recruited 27,824 adult men attending an infertility clinic in Wuhan, China, between 2014 and 2020. We used a four-dimensional spatiotemporal deep forest model to estimate concentrations of PM2.5 mass and its chemical constituents, including organic matter (OM), black carbon (BC), sulfate (SO42−), nitrate (NO3–), ammonium (NH4+), and chloride (Cl−). We employed linear regression models to estimate the association between PM2.5 mass and its constituents with various sperm parameters. Exposure to PM2.5 was associated with a reduction in sperm quality, with a percent change of − 5.69% (95% confidence interval [CI]: −8.53%, −2.85%) for sperm density, − 15.09% (95% CI: −22.24%, −7.94%) for sperm total count, − 1.63% (95% CI: −2.36%, −0.91%) for sperm progressive motility, and − 2.30% (95% CI: −3.04%, −1.55%) for sperm total motility. Among specific constituents, exposure to OM, BC, Cl−, or NO3– was associated with a reduction in these four semen quality parameters. The association was more pronounced among older men or individuals with lower levels of education. Our findings suggest that PM2.5 mass and each constituent were associated with decreased semen quality in adult men.

Long-term exposure to ambient fine particulate matter constituents and mortality from total and site-specific gastrointestinal cancer

BackgroundAmbient fine particulate matter (PM2.5) exposure has been associated with an increased risk of gastrointestinal cancer mortality, but the attributable constituents remain unclear. ObjectivesTo investigate the association of long-term exposure to PM2.5 constituents with total and site-specific gastrointestinal cancer mortality using a difference-in-differences approach in Jiangsu province, China during 2015–2020. MethodsWe split Jiangsu into 53 spatial units and computed their yearly death number of total gastrointestinal, esophagus, stomach, colorectum, liver, and pancreas cancer. Utilizing a high-quality grid dataset on PM2.5 constituents, we estimated 10-year population-weighted exposure to black carbon (BC), organic carbon (OC), sulfate, nitrate, ammonium, and chloride in each spatial unit. The effect of constituents on gastrointestinal cancer mortality was assessed by controlling time trends, spatial differences, gross domestic product (GDP), and seasonal temperatures. ResultsOverall, 524,019 gastrointestinal cancer deaths were ascertained in 84.77 million population. Each interquartile range increment of BC (0.46 μg/m3), OC (4.56 μg/m3), and nitrate (1.41 μg/m3) was significantly associated with a 27%, 26%, and 34% increased risk of total gastrointestinal cancer mortality, respectively, and these associations remained significant in PM2.5-adjusted models and constituent-residual models. We also identified robust associations of BC, OC, and nitrate exposures with site-specific gastrointestinal cancer mortality. The mortality risk generally displayed increased trends across the total exposure range and rose steeper at higher levels. We did not identify robust associations for sulfate, ammonium, or chlorine exposure. Higher mortality risk ascribed to constituent exposures was identified in total gastrointestinal and liver cancer among women, stomach cancer among men, and total gastrointestinal and stomach cancer among low-GDP regions. ConclusionsThis study offers consistent evidence that long-term exposure to PM2.5-bound BC, OC, and nitrate is associated with total and site-specific gastrointestinal cancer mortality, indicating that these constituents need to be controlled to mitigate the adverse effect of PM2.5 on gastrointestinal cancer mortality.

Associations of long-term exposure to PM2.5 constituents with serum uric acid and hyperuricemia in Chinese adults

ObjectiveLittle 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.MethodsThis 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.ResultsSignificant 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).ConclusionsOur 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

Long- and short-term health benefits attributable to PM2.5 constituents reductions from 2013 to 2021: A spatiotemporal analysis in China

Long- and short-term exposure to constituents of fine particulate matter (PM2.5) substantially affects human health. However, assessments of the health and economic benefits of reducing PM2.5 constituents are scarce. This study estimates the number of premature deaths from all-cause, cardiovascular (CVD), and respiratory diseases avoided due to reductions in daily and annual average concentrations of PM2.5 constituents. The Environmental Benefits Mapping and Analysis Program was used for two scenarios: we used yearly concentrations of PM2.5 constituents from 2013 to 2020 as the baseline concentration surface (Scenario I), and 2021 as the baseline year (Scenario II). With reductions in daily and annual average concentrations of PM2.5 constituents, 309,099 (95 % confidence interval [CI]: 37,265–571,485) and 195,297 (95 % CI: 178,192–211,914) premature deaths were avoided in Scenario I, respectively; meanwhile, 347,296 (95 % CI: 79,258–604,758) and 201,567 (95 % CI: 185,038–217,530) premature deaths were avoided in Scenario II, respectively. Moreover, economic benefits associated with the prevention of premature deaths were estimated using the willingness to pay (WTP) and modified human capital (AHC) methods. The total estimated economic benefits amounted to 563.32 billion RMB (WTP) and 322.03 billion RMB (AHC) in Scenario I. In Scenario II, the associated economic benefits were 751.48 billion RMB (WTP) and 427.56 billion RMB (AHC), accounting for 0.657 and 0.374 % of China's gross domestic product in 2021, respectively. Additionally, we analyzed the sensitivity of CVD-related premature deaths to the concentrations of PM2.5 constituents, and found that CVD-related premature deaths were more sensitive to black carbon.

Association of Fine Particulate Matter Constituents with the Predicted 10-Year Atherosclerotic Cardiovascular Disease Risk: Evidence from a Large-Scale Cross-Sectional Study.

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.

Association of fine particulate matter constituents and ozone with immunotherapy outcomes among Non-small cell lung cancer patients

Association of fine particulate matter constituents and ozone with immunotherapy outcomes among Non-small cell lung cancer patients

An interrupted time series analysis of the cardiovascular health benefits of a coal coking operation closure

With the widespread implementation of air pollution mitigation strategies for health and climate policy, there is an emerging interest in accountability studies to validate whether a reduction of air pollution exposure, in fact, produces the human health benefits estimated from past air pollution epidemiology. The closure of a coal coking plant provides an ideal ‘natural’ experiment opportunity to rigorously evaluate the health benefits of air pollution emissions reductions. In this study, we applied an interrupted time series model to test the hypothesis that the substantial reduction in air pollution induced by the closure of the Shenango, Inc. coke plant in Pittsburgh, PA during January, 2016 was followed by immediate and/or longer-term cumulative local cardiovascular health benefits. We observed a 90% decrease in nearby SO2 levels, as well as significant reductions in coal-related fine particulate matter constituents (sulfate and arsenic), after the closure. Statistically significant cardiovascular health benefits were documented in the local population, including a 42% immediate drop (95% CI: 33%, 51%) in cardiovascular emergency department (ED) visits from the pre-closure mean. A longer-term downward trend was also observed for overall emergency visits at −0.14 (95% CI: −0.17, −0.11) visits per week rate of decrease after the closure, vs. a rise of 0.17 (95% CI: 0.14, 0.20) visits per week before. Similarly, inpatient cardiovascular hospitalizations per year showed a decrease after closure (−27.97 [95% CI: −46.90, −9.04], as compared with a 5.09 [95% CI: −13.84, 24.02] average increase in cases/year over the prior three years). Our study provides clear evidence that this intervention lowering fossil fuel-associated air pollution benefited public health in both the short and longer term, while also providing validation of the past use of observational air pollution epidemiology effect estimates in policy analyses.

Association Between Long-Term Exposure to Fine Particulate Matter Constituents and Progression of Cerebral Blood Flow Velocity in Beijing: Modifying Effect of Greenness.

Few studies have explored the effects of fine particulate matter (PM2.5) and its constituents on the progression of cerebral blood flow velocity (BFV) and the potential modifying role of greenness. In this study, we investigated the association of PM2.5 and its constituents, including sulfate (SO4 2-), nitrate (NO3 -), ammonium (NH4 +), organic matter (OM), and black carbon (BC), with the progression of BFV in the middle cerebral artery. Participants from the Beijing Health Management Cohort who underwent at least two transcranial Doppler sonography examinations during 2015-2020 were recruited. BFV change and BFV change rate were used to define the progression of cerebral BFV. Linear mixed effects models were employed to analyze the data, and the weighted quantile sum regression assessed the contribution of PM2.5 constituents. Additionally, greenness was examined as a modifier. Among the examined constituents, OM exhibited the strongest association with BFV progression. An interquartile range increase in PM2.5 and OM exposure concentrations was associated with a decrease of -16.519cm/s (95% CI: -17.837, -15.201) and -15.403cm/s (95% CI: -16.681, -14.126) in BFV change, and -10.369cm/s/year (95% CI: -11.387, -9.352) and -9.615cm/s/year (95% CI: -10.599, -8.632) in BFV change rate, respectively. Furthermore, stronger associations between PM2.5 and BFV progression were observed in individuals working in areas with lower greenness, those aged under 45years, and females. In conclusion, reducing PM2.5 levels in the air, particularly the OM constituent, and enhancing greenness could potentially contribute to the protection of cerebrovascular health.

Short-term effects of fine particulate matter constituents on mortality considering the mortality displacement in Zhejiang province, China

BackgroundEvidence linking mortality and short-term exposure to particulate matter (PM2.5) constituents was sparse. The mortality displacement was often unconsidered and may induce incorrect risk estimation. ObjectivesTo assess the short-term effects of PM2.5 constituents on all-cause mortality considering the mortality displacement. MethodsDaily data on all-cause mortality and PM2.5 constituents, including sulfate (SO42−), nitrate (NO3−), ammonium (NH4+), organic matters (OM), and black carbon (BC), were collected from 2009 to 2020. The mortality effect of PM2.5 and its constituents was estimated using a distributed lag non-linear model. Stratified analyses were performed by age, sex, and season. ResultsPer interquartile range increases in SO42−, NO3−, NH4+, OM, and BC were associated with the 1.42% (95%CI: 0.98, 1.87), 3.76% (3.34, 4.16), 2.26% (1.70, 2.83), 2.36% (2.02, 2.70), and 1.26% (0.91, 1.61) increases in all-cause mortality, respectively. Mortality displacements were observed for PM2.5, SO42−, NH4+, OM, and BC, with their overall effects lasting for 7–15 days. Stratified analyses revealed a higher risk for old adults (>65 years) and females, with stronger effects in the cold season. ConclusionsShort-term exposures to PM2.5 constituents were positively associated with increased risks of mortality. The mortality displacement should be considered in future epidemiological studies on PM constituents. Data availabilityData will be made available on request.

The association between chemical constituents of ambient fine particulate matter and obesity in adults: A large population-based cohort study

ObjectivesCurrent evidence demonstrated that ambient fine particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5) and its constituents may be obesogenic in children, but evidence from adults is lacking. Our aim was to characterize the association between PM2.5 and its constituents and obesity in adults. MethodsWe included 68,914 participants from the China Multi-Ethnic Cohort (CMEC) baseline survey. Three-year average concentrations of PM2.5 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 PM2.5 and its constituents and obesity. We performed weighed quantile sum (WQS) regression to get the overall effect of PM2.5 and its constituents and the relative contribution of each constituent. ResultsPer-SD increase in PM2.5 (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 PM2.5 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 PM2.5, BC, ammonium, nitrate, OM, sulfate and SOIL compared to other individuals. ConclusionOur study revealed that PM2.5 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.

Prenatal exposure to ambient PM2.5 and its chemical constituents and child intelligence quotient at 6 years of age

There are limited studies on the associations between prenatal exposure to constituents of fine particulate matter (PM2.5) and children’s intelligence quotient (IQ). Our study aimed to explore the associations between prenatal PM2.5 and its six constituents and the IQ levels of 6-year-old children. We included 512 mother-child pairs. We used a satellite-based modelling framework to estimate prenatal PM2.5 and its six constituents (ammonium, sulfate, nitrate, organic carbon, soil dust, and black carbon). We assessed the children’s IQ using the short form of the Wechsler Intelligence Scale. Perceptual Reasoning Index (PRI), Verbal Comprehension Index (VCI), and Full Scale IQ (FSIQ) scores were computed. The multiple informant model (MIM) was applied to explore the trimester specific effects of PM2.5 and its six constituents’ exposure on children’s PRI, VCI, and FSIQ. To examine whether the duration of breastfeeding and physical activity (PA) could modify the effects of PM2.5 on children’s IQ, we stratified the analyses according to the duration of breastfeeding (≤6 and >6 months) and time of outdoor activities after school (≤2 and >2 h/week). The first trimester PM2.5 and its five constituents’ exposures were inversely associated with FSIQ [β = −1.34, 95 % confidence interval [CI] (−2.71, 0.04) for PM2.5] and PRI [β = −2.18, 95 %CI (−3.80, −0.57) for PM2.5] in children. The associations were magnified among boys and those with less outdoor activities or shorter breastfeeding duration. Our results indicate that prenatal PM2.5 and several of its main constituents’ exposure may disrupt cognitive development in children aged 6 years. More PA and longer breastfeeding duration may alleviate the detrimental effects of prenatal PM2.5 exposure on children’s cognitive function.

Feature extraction and prediction of fine particulate matter (PM2.5) chemical constituents using four machine learning models

The concentrations of fine particulate matter (PM2.5) constituents, which are very important and essential information for the identification of air pollution sources, were predicted at three sites (Seoul, Ulsan, Baengnyeong) in South Korea between 2016 and 2018 using four machine learning (ML) models: generative adversarial imputation network (GAIN), fully connected deep neural network (FCDNN), random forest (RF), and k-nearest neighbor (kNN). 3 PM2.5 constituent groups, namely 8 ions, 2 carbons, and 15 trace elements, were targeted for prediction. The latest hyperparameter optimization techniques were used to learn air pollution characteristics from ambient PM2.5-related information, such as time, meteorology, and air pollutant concentrations. We compared the feature extraction abilities of the four models. The prediction accuracy identified by the coefficient of determination (R2) between prediction and observation was highest in GAIN, followed by FCDNN and RF or kNN. On availability of data on the time, air pollutant concentrations, and/or meteorology, simultaneously missed 20 % data of all PM2.5 constituent groups were predicted, with R2 = 0.897, 0.861, 0.785, and 0.801 by the GAIN, FCDNN, RF, and kNN, respectively. As missing ratios (20 %, 40 %, 60 %, 80 %) of input data increased, prediction accuracy decreased in the four models and was predominantly more noticeable in GAIN and kNN. As the available period of data increased, prediction accuracy increased in GAIN and FCDNN. Trace elements were predicted with the lowest R2 in all models among the target constituent groups. Study sites with more emission sources showed lower prediction accuracy, resulting in the highest R2 in Baengnyeong island and the lowest in Ulsan. According to the current findings, ML models can be used to evaluate various air pollution issues for which data is missing.

Association of long-term exposure to PM2.5 constituents with glucose metabolism in Chinese rural population

BackgroundEvidence on the associations of fine particulate matter (PM2.5) constituents and glucose metabolism is limited in resource-limited areas. This study aimed to explore the associations of PM2.5 constituents with glucose metabolism in rural areas, and to further specify the most responsible constituent. MethodsA total of 38,442 adults were recruited from the Henan Rural Cohort Study during 2015–2017. Three-year averaged concentrations of PM2.5 mass and its constituents (black carbon (BC), ammonium (NH4+), nitrate (NO3−), organic matter (OM), inorganic sulfate (SO42−), soil particles (SOIL) and sea salt (SS)) were estimated by a hybrid satellite-based model. Generalized linear model was applied to explore the associations of PM2.5 mass and its constituents with type 2 diabetes mellitus (T2DM), fasting blood glucose (FBG), insulin, and HOMA-β. Proportion and residual analyses were employed to specify the most responsible constituent. ResultsThe adjusted odds ratio (OR) for T2DM associated with 1 μg/m3 increase was 1.02 for PM2.5 mass, 1.28 for BC, 1.15 for NH4+, 1.08 for NO3−, 1.10 for OM, 1.11 for SO42−, and 1.12 for SOIL. Significant associations of PM2.5 mass and its constituents with elevated FBG, decreased insulin and HOMA-β were also observed. Proportion and residual analyses indicated that BC was the most responsible constituent, in which 1 percentage increment in the proportion of BC in PM2.5 corresponded with 1.51-fold risk for T2DM, 0.17 mmol/L increase in FBG, 2.18 μU/mL decrease in insulin, and 38.26 % decrease in HOMA-β; and 1 μg/m3 increment in the PM2.5-adjusted BC corresponded with 1.59-fold risk for T2DM, 0.53 mmol/L increase in FBG, 4.79 μU/mL decrease in insulin, and 91.32 % decrease in HOMA-β. ConclusionsPM2.5 mass and its constituents (BC, NH4+, NO3−, OM, SO42−, SOIL) were associated with T2DM, increased FBG, decreased insulin and HOMA-β, of which BC was most responsible for these associations. Trial registrationThe Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). Date of registration: 06 July 2015. http://www.chictr.org.cn/showproj.aspx?proj=11375.

Metal Constituents of Fine Particulate Matter Mass and Incident Depression: A Community-based Cohort Study in China

BACKGROUND AND AIM: Little is known about the effects of chemical constituents of fine particulate matter (particles with aerodynamic diameter &amp;#x2264; 2.5 &amp;#x3bc;m, PM2.5). This study aims to estimate the associations between constituents of PM2.5 and incident depression. METHODS: This large cohort study recruited the local adults in Ningbo, a southeastern coastal city in China. Depression cases were ascertained from local Health Information System. Daily PM2.5 samples were collected at seven monitoring sites for the 10th-16th seven consecutive days and further measured for ten PM2.5-bound metals. Land-use regression models were conducted to predict the residential PM2.5-bound metals exposure. We conducted three cox proportional hazards models which respectively employed single constituent, constituent adjusting for PM2.5 and constituent residual calculated by PM2.5 as exposures to estimate the effect of constituents on incident depression. Environmental Risk Score (ERS) and Weighted Quintile Score (WQS) were utilized to estimate the overall effect of all metals. RESULTS: In fully adjusted constituent models, the higher concentrations of ambient Lead(Pb), Nickel(Ni), Mercury(Hg), Chromium(Cd) and Beryllium(Be) were significantly associated with higher risk of incident depression. In ERS analyses, one main effect (Tl), three squared terms (Hg, Cd and Al) and twelve pairwise interactions (Tl &amp;#x26; Pb, Tl &amp;#x26; Be, et al) were selected by adaptive elastic-net (AENET) for construction of ERS of incident depression-related ambient metal mixtures. The ERS index was positively and significantly associated with depression incidence. And similar results were found for WQS index which suggesting that Al, Sb, Hg, Tl, Mn and Be contributed the most to the association. CONCLUISIONS: These findings highlighted the associations of exposure to PM2.5-bound metals with incident depression. Further studies are needed to confirm the findings and examine the underlying mechanisms. KEYWORDS: PM2.5-bound Metal, depression, Cox Proportional Hazardous Regression, ERS, WQS.

Short-term effects of fine particulate matter constituents on pulmonary function among adolescents

Short-term effects of fine particulate matter constituents on pulmonary function among adolescents

Research progress on adverse health effects of fine particulate matter constituents in China

Research progress on adverse health effects of fine particulate matter constituents in China