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Ambient PM 2.5 pollution poses a major risk to public health in China, contributing to significant mortality and morbidity. While overall PM 2.5 concentrations have declined in recent years, the changes in PM 2.5 chemical constituents remain inadequately understood due to limited ground monitoring networks. We developed a Super Learner model that integrates MISR satellite data, chemistry transport model simulations, and land use information to predict daily OC concentrations across China from 2003 to 2019 at a 10-km spatial resolution. The model achieved high predictive accuracy with a cross-validation R 2 of 0.84 and an RMSE of 4.9 μg/m 3 . Our findings show elevated OC levels in Northern China, driven by industrial activities with concentrations exceeding 30 μg/m 3 during the heating season. In contrast, forest fires were the primary contributors in Yunnan, raising OC concentrations to 20-30 μg/m 3 during fire seasons. Over the 17-year period, the national OC trend declined by 1.3 % annually. Regionally, the Beijing-Tianjin-Hebei region and the Fenwei Plain experienced faster reductions at annual rates of 1.5 % and 2.0 %, respectively, while Yunnan exhibited no significant trends. To better understand pollution source contributions, we analyzed the OC/EC ratio, which indicated higher ratios in less populated rural areas, suggesting agricultural and biogenic emissions, while lower ratios in urban clusters pointed to primary sources such as traffic and industrial activities. Notably, since 2013, significant decreases in the OC/EC ratio have been observed in the North China Plain, likely reflecting the impact of stringent air pollution control policies on biomass burning. This study provides valuable exposure estimates for epidemiological research on the long-term health effects of OC in China, offering insights for evaluating air quality policies and guiding future management strategies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Epidemiological evidence on the impact of airborne organic pollutants on lung function among the elderly is limited, and their underlying biological mechanisms remain largely unexplored. Herein, a longitudinal panel study was conducted in Jinan, Shandong Province, China, involving 76 healthy older adults monitored over a span of five months repetitively. We systematically evaluated personal exposure to a diverse range of airborne organic pollutants using a wearable passive sampler and their effects on lung function. Participants' pulmonary function indicators were assessed, complemented by comprehensive multi-omics analyses of blood and urine samples. Leveraging the power of interaction analysis, causal inference test (CIT), and integrative pathway analysis (IPA), we explored intricate relationships between specific organic pollutants, biomolecules, and lung function deterioration, elucidating the biological mechanisms underpinning the adverse impacts of these pollutants. We observed that bis (2-chloro-1-methylethyl) ether (BCIE) was significantly associated with negative changes in the forced vital capacity (FVC), with glycerolipids mitigating this adverse effect. Additionally, 31 canonical pathways [e.g., high mobility group box 1 (HMGB1) signaling, phosphatidylinositol 3-kinase (PI3K)/AKT pathway, epithelial mesenchymal transition, and heme and nicotinamide adenine dinucleotide (NAD) biosynthesis] were identified as potential mechanisms. These findings may hold significant implications for developing effective strategies to prevent and mitigate respiratory health risks arising from exposure to such airborne pollutants. However, due to certain limitations of the study, our results should be interpreted with caution., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Evidence suggested that abiotic airborne exposures may be associated with changes in body composition. However, more evidence is needed to identify key pollutants linked to adverse health effects and their underlying biomolecular mechanisms, particularly in sensitive older adults., Objectives: Our research aimed to systematically assess the relationship between abiotic airborne exposures and changes in body composition among healthy older adults, as well as the potential mediating mechanisms through the serum lipidome., Methods: From September 2018 to January 2019, we conducted a monthly survey among 76 healthy adults (60-69 years old) in the China Biomarkers of Air Pollutant Exposure (BAPE) study, measuring their personal exposures to 632 abiotic airborne pollutions using MicroPEM and the Fresh Air wristband, 18 body composition indicators from the InBody 770 device, and lipidomics from venous blood samples. We used an exposome-wide association study (ExWAS) and deletion/substitution/addition (DSA) model to unravel complex associations between exposure to contaminant mixtures and body composition, a Bayesian kernel machine regression (BKMR) model to assess the overall effect of key exposures on body composition, and mediation analysis to identify lipid intermediators., Results: The ExWAS and DSA model identified that 2,4,5-T methyl ester (2,4,5-TME), 9,10-Anthracenedione (ATQ), 4b,8-dimethyl-2-isopropylphenanthrene, and 4b,5,6,7,8,8a,9,10-octahydro-(DMIP) were associated with increased body fat mass (BFM), fat mass indicators (FMI), percent body fat (PBF), and visceral fat area (VFA) in healthy older adults [Bonferroni-Hochberg false discovery rate ( FD R BH ) < 0.05 ]. The BKMR model demonstrated a positive correlation between contaminants (anthracene, ATQ, copaene, di-epi- α -cedrene, and DMIP) with VFA. Mediation analysis revealed that phosphatidylcholine [PC, PC(16:1e/18:1), PC(16:2e/18:0)] and sphingolipid [SM, SM(d18:2/24:1)] mediated a significant portion, ranging from 12.27% to 26.03% ( p -value < 0.05 ), of the observed increase in VFA., Discussion: Based on the evidence from multiple model results, ATQ and DMIP were statistically significantly associated with the increased VFA levels of healthy older adults, potentially regulated through lipid intermediators. These findings may have important implications for identifying potentially harmful environmental chemicals and developing targeted strategies for the control and prevention of chronic diseases in the future, particularly as the global population is rapidly aging. https://doi.org/10.1289/EHP13865.

Fine particulate matter (PM 2.5 ) has been linked to aging risk, and a lack of knowledge about the relationships between PM 2.5 components and aging risk impeded the development of healthy aging. Participants were recruited through a multicenter cross-sectional study in the Beijing-Tianjin-Hebei region in China. Middle-age and older males and menopausal women completed the collection of basic information, blood samples, and clinical examinations. The biological age was estimated by Klemera-Doubal method (KDM) algorithms based on clinical biomarkers. Multiple linear regression models were applied to quantify the associations and interactions while controlling for confounders, and a restricted cubic spline function estimated the corresponding dose-response curves of the relationships. Overall, KDM-biological age acceleration was associated with PM 2.5 component exposure over the preceding year in both males and females, with calcium [females: 0.795 (95% CI: 0.451, 1.138); males: 0.712 (95% CI: 0.389, 1.034)], arsenic [females: 0.770 (95% CI: 0.641, 0.899); males: 0.661 (95% CI: 0.532, 0.791)], and copper [females: 0.401 (95% CI: 0.158, 0.644); males: 0.379 (95% CI: 0.122, 0.636)] having greater estimates of the effect than total PM 2.5 mass. Additionally, we observed that the associations of specific PM 2.5 components with aging were lower in the higher sex hormone scenario. Maintaining high levels of sex hormones may be a crucial barrier against PM 2.5 component-related aging in the middle and older age groups.

Background: The association between fine particular matter (PM2.5) and frailty is less studied, and the national burden of PM2.5-related frailty in China is unknown., Objective: To explore the association between PM2.5 exposure and incident frailty in older adults, and estimate the corresponding disease burden., Design: Chinese Longitudinal Healthy Longevity Survey from 1998 to 2014., Setting: Twenty-three provinces in China., Subjects: A total of 25,047 participants aged ≥65-year-old., Methods: Cox proportional hazards models were performed to evaluate the association between PM2.5 and frailty in older adults. A method adapted from the Global Burden of Disease Study was used to calculate the PM2.5-related frailty disease burden., Results: A total of 5,733 incidents of frailty were observed during 107,814.8 person-years follow-up. A 10 μg/m3 increment of PM2.5 was associated with a 5.0% increase in the risk of frailty (Hazard Ratio = 1.05, 95% confidence interval = [1.03-1.07]). Monotonic, but non-linear exposure-response, relationships of PM2.5 with risk of frailty were observed, and slopes were steeper at concentrations >50 μg/m³. Considering the interaction between population ageing and mitigation of PM2.5, the PM2.5-related frailty cases were almost unchanged in 2010, 2020 and 2030, with estimations of 664,097, 730,858 and 665,169, respectively., Conclusions: This nation-wide prospective cohort study showed a positive association between long-term PM2.5 exposure and frailty incidence. The estimated disease burden indicated that implementing clean air actions may prevent frailty and substantially offset the burden of population ageing worldwide., (© The Author(s) 2023. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Ambient fine particulate matter (PM 2.5 ) pollution is a major environmental and public health challenge in China. In the recent decade, the PM 2.5 level has decreased mainly driven by reductions in particulate sulfate as a result of large-scale desulfurization efforts in coal-fired power plants and industrial facilities. Emerging evidence also points to the differential toxicity of particulate sulfate affecting human health. However, estimating the long-term spatiotemporal trend of sulfate is difficult because a ground monitoring network of PM 2.5 constituents has not been established in China. Spaceborne sensors such as the Multi-angle Imaging SpectroRadiometer (MISR) instrument can provide complementary information on aerosol size and type. With the help of state-of-the-art machine learning techniques, we developed a sulfate prediction model under support from available ground measurements, MISR-retrieved aerosol microphysical properties, and atmospheric reanalysis data at a spatial resolution of 0.1°. Our sulfate model performed well with an out-of-bag cross-validationR 2 of 0.68 at the daily level and 0.93 at the monthly level. We found that the national mean population-weighted sulfate concentration was relatively stable before the Air Pollution Prevention and Control Action Plan was enforced in 2013, ranging from 10.4 to 11.5 µg m -3 . But the sulfate level dramatically decreased to 7.7 µg m -3 in 2018, with a change rate of -28.7 % from 2013 to 2018. Correspondingly, the annual mean total non-accidental and cardiopulmonary deaths attributed to sulfate decreased by 40.7 % and 42.3 %, respectively. The long-term, full-coverage sulfate level estimates will support future studies on evaluating air quality policies and understanding the adverse health effect of particulate sulfate., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Ambient ozone pollution is steadily increasing and becoming a major environmental risk factor contributing to the global disease burden. Although the association between short-term ozone exposure and mortality has been widely studied, results are mostly reported on deaths from non-accidental or total cardiopulmonary disease rather than a spectrum of causes. In particular, a knowledge gap still exists for the potential thresholds in mortality risks., Methods: This nationwide time-series study in China included 323 counties totaling 230,266,168 residents. Daily maximum 8-hour average was calculated as the ozone exposure metric. A two-stage statistical approach was adopted to assess ozone effects on 21 cause-specific deaths for 2013-2018. The subset approach and threshold approach were utilized to explore potential thresholds, and stratification analysis was used to evaluate population susceptibility., Results: On average, the annual mean ozone concentration was 93.4 μg/m 3 across 323 counties. A 10-μg/m 3 increase in lag 0-1 day of ozone was associated with increases of 0.12 % in mortality risk from non-accidental disease, 0.11 % from circulatory disease, 0.09 % from respiratory disease, 0.29 % from urinary system disease, and 0.20 % from nervous system disease. There may be a "safe" threshold in the ozone-mortality association, which may be between 60 and 100 μg/m 3 , and vary by cause of death. Women and older adults (especially those over 75) are more affected by short-term ozone exposure. Populations in North China had a higher risk of ozone-related circulatory mortality, while populations in South China had a higher risk of ozone-related respiratory mortality., Conclusions: National findings link short-term ozone exposure to premature death from circulatory, respiratory, neurological, and urinary diseases, and provide evidence for a potential "safe" threshold in the association of ozone and mortality. These findings have important implications for helping policymakers tighten the relevant air quality standards and developing early warning systems for public health protection in China., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Epidemiological evidence of the effects of PM 2.5 elements on lung function and DNA methylation is limited. We conducted a longitudinal panel study of 76 healthy older adults aged 60-69 years in Jinan, China, from September 2018 to January 2019. We periodically measured individual 72 h PM 2.5 and element concentrations, lung function, and DNA methylation levels of eight inflammation-related genes. We used linear mixed-effect models to investigate the effects of exposure to personal PM 2.5 elements on the lung function and DNA methylation. Mediation analysis was used to investigate the underlying effect mechanism. Negative changes in the ratio of forced expiratory volume in 1 s to forced vital capacity, ranging from -1.23% [95% confidence interval (CI): -2.11%, -0.35%] to -0.77% (95% CI: -1.49%, -0.04%), were significantly associated with interquartile range (IQR) increases in personal PM 2.5 at different lag periods (7-12, 13-24, 25-48, 0-24, 0-48, and 0-72 h). Arsenic (As), nickel, rubidium (Rb), selenium, and vanadium were significantly associated with at least three lung function parameters, and IQR increases in these elements led to 0.12-5.66% reductions in these parameters. PM 2.5 elements were significantly associated with DNA methylation levels. DNA methylation mediated 7.28-13.02% of the As- and Rb-related reduced lung function. The findings indicate that exposure to elements in personal PM 2.5 contributes to reduced lung function through DNA methylation.

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 ) exposure and sleep disturbance have been significantly associated with adverse cardiovascular outcomes, however, the combined effects of these two factors are still unclear. We conducted a multi-center cross-sectional study from November 2018 to May 2019 in the Beijing-Tianjin-Hebei region in China to investigate the potential modifying effects of sleep disturbance on associations between cardiac conduction abnormalities and PM 2.5 exposure, as well as the combined effects of sleep disturbance and heavy pollution episodes, which were defined based on the PM 2.5 mass concentration (≥75 μg/m 3 , falling in the 75th/90th percentile) and duration (1 day and ≥2 days). The sleep quality and sleep duration of all participants were evaluated using the Pittsburgh Sleep Quality Index. Standard 12-lead electrocardiogram (ECG) test was performed to measure the heart rate (HR), QRS duration (time taken for ventricular depolarization), HR corrected QT interval (time for ventricular depolarization and repolarization) and PR interval (time for atrioventricular conduction). Multivariable linear regression models were performed to evaluate the associations of PM 2.5 and heavy pollution events on ECG parameters and the joint effects with sleep disturbance. We found PM 2.5 exposure was independently associated with prolonged QRS and QTc intervals. Association between PM 2.5 and the QTc interval was significantly stronger in participants with poor sleep quality. For each 10-μg/m 3 increase in PM 2.5 concentration, the QTc interval in the participants with poor sleep quality increased by 0.41 % (95 % confidence interval: 0.19, 0.64). In addition, heavy PM 2.5 pollution episodes, especially extremely heavy pollution of long duration, were found to have synergistic effects with sleep disturbance on ECG parameters. Our findings provide evidence that PM 2.5 exposure, especially heavy pollution episodes, may increase abnormal cardiac conduction and have a synergistic effect with sleep disturbance. Improving sleep hygiene is crucial to protect the heart health of the general population., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Background: Exposure to fine particulate matter (PM 2.5 ) is a prominent risk factor for cardiovascular aging in older adults and causes mild syndromes or other comorbidities in otherwise healthy older adults. Accordingly, a precise tool for PM 2.5 exposure risk stratification is urgently needed. We aimed to address this need by comparing the performances of seven types of epigenetic age and chronological age to classify the effects of short-term PM 2.5 exposure on blood pressure (BP), a typical clinical surrogate marker of cardiovascular aging., Methods: We conducted a panel study of the Chinese healthy adults aged 60-69 years through five monthly visits. Personal PM 2.5 exposures were measured using wearable monitoring devices for three consecutive days, and DNA methylation was determined by the Illumina MethylationEPIC BeadChip using blood samples collected at each visit. Systolic BP, diastolic BP, mean arterial pressure and pulse pressure were measured by the electronic BP monitor. Linear mixed models with interaction terms between PM 2.5 and different ages were used to assess their potential usefulness for stratification., Results: DNAmPhenoAge, Skin & blood clock, DNAmGrimAge acceleration, and DunedinPoAm had significant modifying effects on the relationship between PM 2.5 and BP. For instance, a 10-μg/m 3 increase in the 72-h moving mean PM 2.5 was significantly associated with 0.30% (95% CI: 0.10%, 0.51%) and -0.07% (95% CI: -0.32%, 0.18%) increases in systolic BP at higher and lower DNAmPhenoAge acceleration, respectively. Joint models further revealed that using a combination of epigenetic ages could more precisely stratify the effect of PM 2.5 on BP., Conclusions: Our research indicates that epigenetic age may be a useful tool for evaluating the effect of short-term PM 2.5 exposure on cardiovascular aging status., (Copyright © 2022 Elsevier Inc. All rights reserved.)

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.

Ambient PM 2.5 (fine particulate matter with aerodynamic diameters ≤ 2.5 μm) is thought to be associated with the development of diabetes, but few studies traced the effects of PM 2.5 components and pollution sources on the change in the fasting blood glucose (FBG). In the present study, we assessed the associations of PM 2.5 constituents and their sources with the FBG in a general Chinese population aged over 40 years. Exposure to PM 2.5 was positively associated with the FBG level, and each interquartile range (IQR) increase in a lag period of 30 days (18.4 μg/m 3 ) showed the strongest association with an elevated FBG of 0.16 mmol/L (95% confidence interval: 0.04, 0.28). Among various constituents, increases in exposed elemental carbon, organic matter, arsenic, and heavy metals such as silver, cadmium, lead, and zinc were associated with higher FBG, whereas barium and chromium were associated with lower FBG levels. The elevated FBG level was closely associated with the PM 2.5 from coal combustion, industrial sources, and vehicle emissions, while the association with secondary sources was statistically insignificant. Improving air quality by tracing back to the pollution sources would help to develop well-directed policies to protect human health.

We explored the impact of heavy PM 2.5 pollution events on the health of residents in 250 counties in China. A time-series approach involving a two-stage analysis was applied to estimate the association between heavy PM 2.5 pollution events and mortality from 2013 to 2018. The associations between heavy (PM 2.5 ≥75 μg/m 3 and <150 μg/m 3 ) and extremely heavy (PM 2.5 ≥150 μg/m 3 ) PM 2.5 pollution days with mortality were explored. The added effects of the heavy PM 2.5 pollution events were evaluated by controlling PM 2.5 concentration in the model. From 2013 to 2018, there were 57,279 county days of heavy PM 2.5 pollution and 21,248 county days of extremely heavy PM 2.5 pollution. The risks of mortality during this period of heavy PM 2.5 pollution events increased by 1.22% (95% CI: 0.82-1.63%), 1.14% (95% CI: 0.74-1.53%), 1.09% (95% CI: 0.58-1.60%), and 1.30% (95% CI: 0.40-2.20%), for all-cause, nonaccidental, circulatory, and respiratory mortality, respectively. We also observed that heavy PM 2.5 pollution events had an added effect on mortality risk associated with all-cause, nonaccidental, circulatory, and respiratory mortality, evident from an observed increase by 0.77% (95% CI: 0.29-1.24%), 0.73% (95% CI: 0.27-1.19%), 0.96% (95% CI: 0.37-1.55%), and 0.55% (95% CI: -0.52-1.63%), respectively. Heavy PM 2.5 pollution events increased mortality risks and caused an independent added effect. The findings serve as a foundation for policymakers in developing early warning systems and policy interventions.

Existing studies mostly explored the association between urban environmental exposures and blood pressure (BP) in isolation, ignoring correlations across exposures. This study aimed to systematically evaluate the impact of a wide range of urban exposures on BP using an exposome-wide approach. A multicenter cross-sectional study was conducted in ten cities of China. For each enrolled participant, we estimated their urban exposures, including air pollution, built environment, surrounding natural space, and road traffic indicator. On the whole, this study comprised three statistical analysis steps, that is, single exposure analysis, multiple exposure analysis and a cluster analysis. We also used deletion-substitution-addition algorithm to conduct variable selection. After considering multiple exposures, for hypertension risk, most significant associations in single exposure model disappeared, with only neighborhood walkability remaining negatively statistically significant. Besides, it was observed that SBP (systolic BP) raised gradually with the increase in PM 2.5 , but such rising pattern slowed down when PM 2.5 concentration reached a relatively high level. For surrounding natural spaces, significant protective associations between green and blue spaces with BP were found. This study also found that high population density and public transport accessibility have beneficially significant association with BP. Additionally, with the increase in the distance to the nearest major road, DBP (diastolic BP) decreased rapidly. When the distance was beyond around 200 m, however, there was no obvious change to DBP anymore. By cluster analysis, six clusters of urban exposures were identified. These findings reinforce the importance of improving urban design, which help promote healthy urban environments to optimize human BP health.

Background: We hypothesize higher air pollution and fewer greenness exposures jointly contribute to metabolic syndrome (MetS), as mechanisms on cardiometabolic mortality., Methods: We studied the samples in the Chinese Longitudinal Healthy Longevity Survey. We included 1755 participants in 2012, among which 1073 were followed up in 2014 and 561 in 2017. We used cross-sectional analysis for baseline data and the generalized estimating equations (GEE) model in a longitudinal analysis. We examined the independent and interactive effects of fine particulate matter (PM 2.5 ) and Normalized Difference Vegetation Index (NDVI) on MetS. Adjustment covariates included biomarker measurement year, baseline age, sex, ethnicity, education, marriage, residence, exercise, smoking, alcohol drinking, and GDP per capita., Results: At baseline, the average age of participants was 85.6 (SD: 12.2; range: 65-112). Greenness was slightly higher in rural areas than urban areas (NDVI mean: 0.496 vs. 0.444; range: 0.151-0.698 vs. 0.133-0.644). Ambient air pollution was similar between rural and urban areas (PM 2.5 mean: 49.0 vs. 49.1; range: 16.2-65.3 vs. 18.3-64.2). Both the cross-sectional and longitudinal analysis showed positive associations of PM 2.5 with prevalent abdominal obesity (AO) and MetS, and a negative association of NDVI with prevalent AO. In the longitudinal data, the odds ratio (OR, 95% confidence interval-CI) of PM 2.5 (per 10 μg/m 3 increase) were 1.19 (1.12, 1.27), 1.16 (1.08, 1.24), and 1.14 (1.07, 1.21) for AO, MetS and reduced high-density lipoprotein cholesterol (HDL-C), respectively. NDVI (per 0.1 unit increase) was associated with lower AO prevalence [OR (95% CI): 0.79 (0.71, 0.88)], but not significantly associated with MetS [OR (95% CI): 0.93 (0.84, 1.04)]. PM 2.5 and NDVI had a statistically significant interaction on AO prevalence (p interaction : 0.025). The association between PM 2.5 and MetS, AO, elevated fasting glucose and reduced HDL-C were only significant in rural areas, not in urban areas. The association between NDVI and AO was only significant in areas with low PM 2.5 , not under high PM 2.5 ., Conclusions: We found air pollution and greenness had independent and interactive effect on MetS components, which may ultimately manifest in pre-mature mortality. These study findings call for green space planning in urban areas and air pollution mitigation in rural areas., (© 2022. The Author(s).)

Background: Insulin resistance (IR) affects the development of type 2 diabetes mellitus (T2DM), which is also influenced by accumulated fine particle air pollution [particulate matter (PM) with aerodynamic diameter of < 2.5 μ m ( PM 2.5 )] exposure. Previous experimental and epidemiological studies have proposed several potential mechanisms by which PM 2.5 contributes to IR/T2DM, including inflammation imbalance, oxidative stress, and endothelial dysfunction. Recent evidence suggests that the imbalance of the gut microbiota affects the metabolic process and may precede IR. However, the underlying mechanisms of PM 2.5 , gut microbiota, and metabolic diseases are unclear., Objectives: We investigated the associations between personal exposure to PM 2.5 and fasting blood glucose and insulin levels, the IR index, and other related biomarkers. We also explored the potential underlying mechanisms (systemic inflammation and sphingolipid metabolism) between PM 2.5 and insulin resistance and the mediating effects between PM 2.5 and sphingolipid metabolism., Methods: We recruited 76 healthy seniors to participate in a repeated-measures panel study and conducted clinical examinations every month from September 2018 to January 2019. Linear mixed-effects (LME) models were used to analyze the associations between PM 2.5 and health data (e.g., functional factors, the IR index, inflammation and other IR-related biomarkers, metabolites, and gut microbiota). We also performed mediation analyses to evaluate the effects of mediators (gut microbiota) on the associations between exposures ( PM 2.5 ) and featured metabolism outcomes., Results: Our prospective panel study illustrated that exposure to PM 2.5 was associated with an increased risk of higher IR index and functional biomarkers, and our study provided mechanistic evidence suggesting that PM 2.5 exposure may contribute to systemic inflammation and altered sphingolipid metabolism., Discussion: Our findings demonstrated that PM 2.5 was associated with the genera of the gut microbiota, which partially mediated the association between PM 2.5 and sphingolipid metabolism. These findings may extend our current understanding of the pathways of PM 2.5 and IR. https://doi.org/10.1289/EHP9688.

Exposure to fine particulate matter (PM 2.5 ) is proven to be associated with a decline in renal function. However, few studies have explored the acute renal damage from carbonaceous compounds and water-soluble inorganic ions (WSIIs), which constitute the bulk of total PM 2.5 mass. We examined the acute effect of these constituents of ambient PM 2.5 on renal function in older Chinese individuals. Seventy-one healthy people aged 60-69 years from Jinan, China, were enrolled and visited monthly and asked to complete survey questionnaires, undergo physical exams, and provide blood samples. The hourly concentrations of organic carbon, elemental carbon (EC), and WSIIs in ambient PM 2.5 were collected from a fixed-site monitoring station. The association between PM 2.5 constituents and estimated glomerular filtration rate (eGFR) was evaluated using linear mixed-effects models after controlling for a series of covariates. We observed that ambient carbonaceous compounds and WSIIs were associated with a significant decline in renal function. The interquartile range increased in the 24 h moving average of carbonaceous compounds, and WSIIs in ambient PM 2.5 were associated with -13.11% [95% confidence interval (95% CI): -19.49, -6.21%] to -0.81% (95% CI: -4.17, 2.67%) changes in eGFR. We found significant associations between EC, chlorine (Cl - ), sodium (Na + ), and magnesium (Mg 2+ ) and eGFR in single-pollutant, constituent-PM 2.5 , and residual-constituent models with a lag period of 0-24 h. This study demonstrated that carbonaceous compounds and WSIIs in PM 2.5 were inversely associated with renal function.

The exposome overhauls conventional environmental health impact research paradigms and provides a novel methodological framework that comprehensively addresses the complex, highly dynamic interplays of exogenous exposures, endogenous exposures, and modifiable factors in humans. Holistic assessments of the adverse health effects and systematic elucidation of the mechanisms underlying environmental exposures are major scientific challenges with widespread societal implications. However, to date, few studies have comprehensively and simultaneously measured airborne pollutant exposures and explored the associated biomarkers in susceptible healthy elderly subjects, potentially resulting in the suboptimal assessment and management of health risks. To demonstrate the exposome paradigm, we describe the rationale and design of a comprehensive biomarker and biomonitoring panel study to systematically explore the association between individual airborne exposure and adverse health outcomes. We used a combination of personal monitoring for airborne pollutants, extensive human biomonitoring, advanced omics analysis, confounding information, and statistical methods. We established an exploratory panel study of Biomarkers of Air Pollutant Exposure in Chinese people aged 60-69 years (China BAPE), which included 76 healthy residents from a representative community in Jinan City, Shandong Province. During the period between September 2018 and January 2019, we conducted prospective longitudinal monitoring with a 3-day assessment every month. This project: (1) leveraged advanced tools for personal airborne exposure monitoring (external exposures); (2) comprehensively characterized biological samples for exogenous and endogenous compounds (e.g., targeted and untargeted monitoring) and multi-omics scale measurements to explore potential biomarkers and putative toxicity pathways; and (3) systematically evaluated the relationships between personal exposure to air pollutants, and novel biomarkers of exposures and effects using exposome-wide association study approaches. These findings will contribute to our understanding of the mechanisms underlying the adverse health impacts of air pollution exposures and identify potential adverse clinical outcomes that can facilitate the development of effective prevention and targeted intervention techniques., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The health impact of airborne contaminants has been challenging to assess due to current limitations in measurement technologies. The emergence of wearable passive samplers coupled with high resolution mass spectrometry (HR-MS) chemical analysis has enabled comprehensive characterization of personal exposures. We conducted a repeated-measure study among 84 older adults in Jinan, China, as part of the Biomarkers for Air Pollutants Exposure (China BAPE) study. Study objectives were: 1) to characterize the occurrence, magnitude, and distribution of personal exposure to airborne contaminants; 2) to evaluate the temporal variation of chemical exposures across the study population; and 3) to identify behavioral and environmental factors that influence the observed variance in chemical exposures. The FreshAir wristband was worn by participants for three consecutive days each month from September 2018 to January 2019 and collected with paired time-activity logs. Passive air samplers were also deployed in parallel at a local outdoor air monitoring station. Spearman's Rho trend test and trajectory cluster analysis were used to identify exposure trends and variation patterns, respectively. Out of the 70 airborne compounds of potential concern screened, 26 compounds from 10 chemical classes were found to be above detection thresholds across >70% of the study population. Personal exposures were predominantly characterized by nine polycyclic aromatic hydrocarbons (PAHs), four phthalates, three nitroaromatics, and two volatile organic compounds (VOCs). Phthalate personal exposures were positively correlated with outdoor temperatures while the inverse relationship was observed for certain PAHs (p < 0.05). Specifically, dimethyl phthalate (r s  = 0.31) decreased as temperatures declined, while nitrobenzene (r s  = -0.35) and naphthalene (r s  = -0.40) increased as temperatures decreased. Compared to levels measured at the outdoor air monitoring site, personal exposure of phthalates was elevated (p < 0.05) and hexachlorobutadiene was lower across participants (p < 0.01). Personal exposure of these chemicals was further found to be weakly associated with daily duration participants spent outdoors. Individuals formed distinct clusters based on trajectories of chemical exposures across the sampling period (September to January), potentially suggestive of distinct emission sources. In conclusion, we demonstrate the feasibility of characterizing the occurrence and magnitude of personal exposure to airborne chemical contaminants using passive wristband samplers. The temporal variability of these personal exposure profiles was highlighted and with distinct trends identified across different groups of individuals. Future studies will integrate this data with other omics datasets collected from this population of Chinese older adults to investigate associations between exposure profiles and health relevant biomarkers, to provide evidence in feasibility of disease prevention through environmental improvements., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: 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., Objectives: 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., Methods: 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., Results: 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/m 3 ) 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- ., Conclusions: 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., Competing Interests: Declaration of competing interest The authors declared no conflicts of interests., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Environmental exposures are one of the greatest threats to human health, yet we lack tools to answer simple questions about our exposures: what are our personal exposure profiles and how do they change overtime (external exposome), how toxic are these chemicals, and what are the sources of these exposures? To capture variation in personal exposures to airborne chemicals in the gas and particulate phases and identify exposures which pose the greatest health risk, wearable exposure monitors can be deployed. In this study, we deployed passive air sampler wristbands with 84 healthy participants (aged 60-69 years) as part of the Biomarkers for Air Pollutants Exposure (China BAPE) study. Participants wore the wristband samplers for 3 days each month for five consecutive months. Passive samplers were analyzed using a novel gas chromatography high resolution mass spectrometry data-processing workflow to overcome the bottleneck of processing large datasets and improve confidence in the resulting identified features. The toxicity of chemicals observed frequently in personal exposures were predicted to identify exposures of potential concern via inhalation route or other routes of airborne contaminant exposure. Three exposures were highlighted based on elevated toxicity: dichlorvos from insecticides (mosquito/malaria control), naphthalene partly from mothballs, and 183 polyaromatic hydrocarbons from multiple sources. Other exposures explored in this study are linked to diet and personal care products, cigarette smoke, sunscreen, and antimicrobial soaps. We highlight the potential for this workflow employing wearable passive samplers for prioritizing chemicals of concern at both the community and individual level, and characterizing sources of exposures for follow up interventions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

The association between fine particulate matter (PM 2.5 ) exposure and mental disorders is attracting increasing attention, but the roles of specific PM 2.5 chemical constituents have yet to be explored. We conducted a multicenter cross-sectional study in nine cities located in the Beijing-Tianjin-Hebei region in China to assess the effects of PM 2.5 and chemical constituents on depression and anxiety. The Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder (GAD-7) scale were used to quantify the depression and anxiety status, atmospheric monitoring data from fixed stations was used to calculate exposure concentrations. We performed multiple logistic regression models to assess the associations of PM 2.5 chemical constituents exposure over the preceding 2 weeks with depression and anxiety. Overall, anxiety and depression were significantly associated with organic carbon (OC), elemental carbon (EC), copper (Cu), cadmium (Cd), nickel (Ni), and zinc (Zn). Subgroup analysis showed a stronger effect of PM 2.5 constituents on depression during the heating period. This study provide evidence for the possible link between PM 2.5 constituents and mental disorders among middle-aged and elderly Chinese adults, which requires further validation of the causal correlation. Our findings support the need for a stricter regulation on emissions of certain specific constituents, in addition to targeting control of total PM 2.5 emission concentration.

Long-term exposure to fine particulate matter (PM 2.5 ) is associated with kidney dysfunction. However, few studies have investigated acute effects of PM 2.5 elemental constituents on renal function. We evaluated associations between personal PM 2.5 and its elemental constituents and kidney function, assessed by an estimated glomerular filtration rate (eGFR) in Biomarkers of Air Pollutants Exposure in the Chinese aged 60-69 study. Seventy one older individuals were visited monthly between September 2018 and January 2019. Each participant wore a PM 2.5 monitor for 72 h, responded to a questionnaire, and underwent a physical examination with blood sampling. Linear mixed-effect models were used to estimate associations between personal PM 2.5 elemental constituents and eGFR. We found that significant changes in eGFR from -1.69% [95% confidence interval (CI): -3.34%, -0.01%] to -3.27% (95% CI: -5.04%, -1.47%) were associated with interquartile range (IQR) increases in individual PM 2.5 exposures at various lag periods (7-12, 13-24, 0-24, 25-48, and 49-72 h). An IQR increase in 72 h moving averages of copper, manganese, and titanium in personal PM 2.5 corresponded to -2.34% (95% CI: -3.67%, -0.99%) to -4.56% (95% CI: -7.04%, -2.00%) changes in eGFR. Personal PM 2.5 and some of its elemental constituents are inversely associated with eGFR in older individuals.

Both ozone exposure and extreme temperatures are found to be significantly associated with mortality; however, inconsistent results have been obtained on the modification effects of temperature on the ozone-mortality association. In the present study, we conducted a nationwide time-series analysis in 128 counties from 2013-2018 to examine whether temperature modifies the association between short-term ozone exposure with nonaccidental and cause-specific mortality in China. First, we analyzed the effects of ozone exposure on mortality at different temperature levels. Then, we calculated the pooled effects through a meta-analysis across China. We found that high-temperature conditions (>75th percentile in each county) significantly enhanced the effects of ozone on nonaccidental, cardiovascular, and respiratory mortality, with increases of 0.44% (95% confidence interval (CI): 0.36 and 0.51%), 0.42% (95% CI: 0.32 and 0.51%) and 0.50% (95% CI: 0.31 and 0.68%), respectively, for a 10 μg/m 3 increase in ozone at high temperatures. Stronger effects on nonaccidental and cardiovascular mortality were observed at high temperatures among elderly individuals aged 65 years and older compared with the younger people. Our findings provide evidence that health damage because of ozone may be influenced by the impacts of increasing temperatures, which point to the importance of mitigating ozone exposure in China under the context of climate change to further reduce the public health burden.

Abstract Studies worldwide have estimated the number of deaths attributable to long-term exposure to fine airborne particles (PM 2.5), but limited information is available on short-term exposure, particularly in China. In addition, most existing studies have assumed that short-term PM 2.5 -mortality associations were linear. For this reason, the use of linear exposure-response functions for calculating disease burden of short-term exposure to PM 2.5 in China may not be appropriate. There is an urgent need for a comprehensive, evidence-based assessment of the disease burden related to short-term PM 2.5 exposure in China. Here, we explored the non-linear association between short-term PM 2.5 exposure and all-cause mortality in 104 counties in China; estimated county-specific mortality burdens attributable to short-term PM 2.5 exposure for all counties in the country and analyzed spatial characteristics of the mortality burden due to short-term PM 2.5 exposure in China. The pooled PM 2.5 -mortality association was non-linear, with a reversed J-shape. We found an approximately linear increased risk of mortality from 0 to 62 μg/m3 and decreased risk from 62 to 250 μg/m3. We estimated a total of 169,862 additional deaths from short-term PM 2.5 exposure throughout China in 2015. Models using linear exposure-response functions for the PM 2.5 -mortality association estimated 32,186 deaths attributable to PM 2.5 exposure, which is 5.3 times lower than estimates from the non-linear effect model. Short-term PM 2.5 exposure contributed greatly to the death burden in China, approximately one seventh of the estimates from the chronic effect. It is essential and crucial to incorporate short-term PM 2.5 -related mortality estimations when considering the disease burden attributable to PM 2.5 in developing countries such as China. Traditional linear effect models likely underestimated the mortality burden due to short-term exposure to PM 2.5. Highlights • The first county-level assessment of short-term PM 2.5 related mortality in China. • The association between short-term PM 2.5 exposure and mortality was non-linear. • A total of 169,862 additional deaths from short-term PM 2.5 exposure in China in 2015. • Previous linear models might have largely underestimated the burden of mortality. [ABSTRACT FROM AUTHOR]

[Display omitted] • Limited evidence depicting effects of airborne chemicals on ageing biomarkers. • PAEs, NIs, and PAHs significantly accelerated epigenetic age in the healthy elderly. • Exposure to chemicals mixture significantly accelerated the phenotypic age. • The adverse effect of airborne chemicals was mainly contributed by PAEs exposure. Air pollution is associated with accelerated biological ages determined by DNA methylation (DNAm) patterns, imposing further risks of age-related adverse effects. However, little is known about the independent and joint effects of exposure to gaseous organic chemicals that may share a common source. We conducted a panel study with the 3-day exposure assessment monthly among 73 Chinese healthy elderly people aged 60 to 69 years in Jinan, Shandong province during September 2018 to January 2019. Exposure to 26 ambient organic chemical contaminants were measured by wearable passive samplers, including volatile organic compounds, polycyclic aromatic hydrocarbons (PAHs), phthalates (PAEs), nitroaromatics (NIs), polybrominated diphenyl ethers, chlorinated hydrocarbons, and organophosphate esters. The Illumina MethylationEPIC BeadChip was used to measure DNA methylation levels in blood samples, and based on which, epigenetic ageing biomarkers, including Hannum clock, Horvath clock, DNAm PhenoAge, DNAm GrimAge, and DNAm estimator of telomere length (DNAmTL) were calculated. Linear mixed effect models were used to estimate the linear associations between 3-day personal chemical exposure and the epigenetic biomarkers, Weighted quantile sum (WQS) regression and the Bayesian kernel machine regression (BKMR) model were further used to evaluate the effect of chemical mixtures. Multiple linear mixed effects regression models showed that DNAmPhenoAge acceleration was significantly and positively associated with exposure to PAEs, NIs, and PAHs in healthy elderly individuals. Both WQS regression and BKMR models showed a significant positive association with DNAmPhenoAge acceleration with chemical exposures, in which the effect of di- n -butyl phthalate exposure showed the greatest importance. These findings suggest that exposure to a mixture of airborne chemicals significantly increase the acceleration of the epigenetic biomarker of phenotypic age. These findings serve to identify toxic chemicals in the air and facilitate the evaluation of their potentially severe health effects. [ABSTRACT FROM AUTHOR]