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Background: Pregnancy loss, a major health issue that affects human sustainability, has been linked to short-term exposure to ground-surface ozone (O 3 ). However, the association is inconsistent, possibly because of the co-occurrence of O 3 and heat episodes, as increased temperature is a risk factor for pregnancy loss. To explain this inconsistency, the effect of O 3 on pregnancy loss needs to be examined jointly with that of high temperature., Methods: A total of 247,305 pregnancy losses during the warm season were extracted from fetal death certificates from the 386 counties in contiguous United States from 1989 to 2005. We assessed environmental exposure based on the daily maximum 8 h average of O 3 from Air Quality System monitors and the 24 h average temperature from the North American Regional Reanalysis product. We conducted a bidirectional, time-stratified case-crossover study of the association between pregnancy loss and exposures to O 3 and temperature and their multiplicative interaction. The main time window for the exposure assessment was the day of case occurrence and the preceding 3 days. To estimate the association, we used conditional logistic regression with adjustment for relative humidity, height of the planetary boundary layer, and holidays. Sensitivity analyses were performed on the lagged structure, nonlinearity, and between-subpopulation heterogeneity of the estimated joint effect., Results: The joint effect was first estimated by the regression against categorical exposure by tertile. Compared to the low-low exposure group (O 3  ≤ 78 μg/m 3 and temperature ≤ 18 °C), the odds of pregnancy loss was significantly higher by 6.0 % (95 % confidence interval [CI] 2.4-9.7 %), 9.8 % (6.1-13.8 %), and 7.5 % (4.7-10.3 %) in the high-low (>104 μg/m 3 and ≤18 °C), low-high (≤78 μg/m 3 and >23 °C), and high-high (>104 μg/m 3 and >23 °C) groups. The model of linear exposure and the multiplicative interaction yielded similar results. Each increment of 10 μg/m 3 in O 3 and 1 °C in temperature was associated with a 3.0 % (2.0 %-4.0 %) and 3.9 % (3.5 %-4.3 %), respectively, increase in the odds of pregnancy loss. A decrease in odds of 0.2 % (0.1 %-0.2 %) was associated with the temperature × O 3 interaction. The finding of an antagonistic interaction between temperature and O 3 was confirmed by models parametrizing the joint exposure as alternative nonlinear terms (i.e., a two-dimensional spline term or a varying-coefficient term) and was robust to a variety of exposure lags and stratifications. Therefore, the marginal effect of O 3 was estimated to vary by climate zone. A significant association between O 3 and pregnancy loss was observed in the northern, but not southern, United States., Conclusion: Joint exposure to O 3 and high temperature can increase the risk for pregnancy loss. The adverse effect of O 3 is potentially modified by ambient temperature. In high-latitude cities, controlling for O 3 pollution could protect maternal health., 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 B.V. All rights reserved.)

Background: Recently, professionals, such as those from the World Health Organization, have recommended a rigorous standard for nitrogen dioxide (NO 2 ), a typical urban air pollutant affected by regular traffic emissions, based on its short-term and long-term cardiorespiratory effects. However, the association between middle-term NO 2 exposure and cardiovascular disorders remains unknown., Objectives: This study was conducted to examine the relationship between NO 2 exposure and its middle-term cardiovascular risks indicated by electrocardiogram (ECG) abnormalities., Method: We included 61,094 subjects (132,249 visits) with repeated ECG observations based on longitudinal data from the China National Stroke Screening Survey (CNSSS). The NO 2 exposure concentration was derived from a predictive model, measured as the monthly average concentration in the 6 months of preceding the ECG measurement. We used the generalized estimation equation to assess the association between NO 2 exposure and ECG abnormalities., Result: For each 10 µg/m 3 increase in monthly average NO 2 concentration, the odds ratio of ECG abnormalities was 1.10 (95% confidence interval [CI] 1.09-1.12) after multiple adjustments. Stratified regression analyses of urban and rural residents showed associations between middle-term NO 2 exposure and ECG abnormalities in urban (OR 1.09 [95% CI 1.08-1.11]) and rural residents (OR 1.14 [95% CI 1.10-1.19]). The association was robust within different subpopulations. Associations generally remained statistically significant (OR 1.03 [95% CI 1.02-1.05]) after extra adjustment for PM 2.5 . Exposure-response relationship analysis revealed a nearly linear relationship between NO 2 exposure and the risk for ECG abnormalities., Conclusion: Using the variation in ECG signals as a potentially reversible indicator for subclinical risk in cardiovascular systems, our study provides additional evidence on the increased risk posed by middle-term NO 2 exposure. Our study showed that policies controlling for NO 2 concentrations are beneficial to prevent cardiovascular diseases among Chinese adults., 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 Inc. All rights reserved.)

Objective: We investigated associations between source-specific fine particulate matter (PM 2.5 ) exposure and hemoglobin levels among children in low- and middle-income countries (LMICs)., Method: 36,675 children aged < 5 years were collected in 11 LMICs during 2017. We associated child hemoglobin with 20 source-specific PM 2.5 , and calculated changes in hemoglobin that could be attributed to different PM 2.5 -mixture scenarios, established using real-world data from 88 Asian and African LMICs (AA-LMICs)., Results: Multiple-source analysis revealed PM 2.5 produced by solvents (change in hemoglobin for 1-μg/m 3 increment in PM 2.5 : -10.34 g/L, 95% CI -14.88 to -5.91), industrial coal combustion (-0.51 g/L, 95% CI -9.25 to -0.08), road transportation (-0.50 g/L, 95% CI -6.96 to -0.29), or waste handling and disposal (-0.34 g/L, 95% CI -4.38 to -0.23) was significantly associated with a decrease in hemoglobin level. Decreases in hemoglobin attributable to the PM 2.5 mixtures were co-determined by the concentrations and their source profiles. The largest PM 2.5 -related change in hemoglobin was -10.25 g/L (95% CI -15.54 to -5.27) for a mean exposure of 61.01 μg/m 3 in India., Conclusion: Association between PM 2.5 and a decrease in hemoglobin was affected by variations in PM 2.5 source profiles. Source-oriented interventions are warranted to protect children in LMICs from air pollution., 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 B.V. All rights reserved.)

Due to global warming, an increased number of open fires is becoming a major contributor to PM 2.5 pollution and thus a threat to public health. However, the burden of stillbirths attributable to fire-sourced PM 2.5 is unknown. In low- and middle-income countries (LMICs), there is a co-occurrence of high baseline stillbirth rates and frequent firestorms, which may lead to a geographic disparity. Across 54 LMICs, we conducted a self-matched case-control study, making stillbirths comparable to the corresponding livebirths in terms of time-invariant characteristics (e.g., genetics) and duration of gestational exposure. We established a joint-exposure-response function (JERF) by simultaneously associating stillbirth with fire- and non-fire-sourced PM 2.5 concentrations, which were estimated by fusing multi-source data, such as chemical transport model simulations and satellite observations. During 2000-2014, 35,590 pregnancies were selected from multiple Demographic and Health Surveys. In each mother, a case of stillbirth was compared to her livebirth(s) based on gestational exposure to fire-sourced PM 2.5 . We further applied the JERF to assess stillbirths attributable to fire-sourced PM 2.5 in 136 non-Western countries. The disparity was evaluated using the Gini index. The risk of stillbirth increased by 17.4% (95% confidence interval [CI]: 1.6-35.7%) per 10 μg/m 3 increase in fire-sourced PM 2.5 . In 2014, referring to a minimum-risk exposure level of 10 μg/m 3 , total and fire-sourced PM 2.5 contributed to 922,860 (95% CI: 578,451-1,183,720) and 49,951 (95% CI: 3,634-92,629) stillbirths, of which 10% were clustered within the 6.4% and 0.6% highest-exposure pregnancies, respectively. The Gini index of stillbirths attributable to fire-sourced PM 2.5 was 0.65, much higher than for total PM 2.5 (0.28). Protecting pregnant women against PM 2.5 exposure during wildfires is critical to avoid stillbirths, as the burden of fire-associated stillbirths leads to a geographic disparity in maternal health., 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 Elsevier Ltd. All rights reserved.)

Background: Electrocardiogram (ECG) abnormalities are known to have prognostic value for heart conditions, while evidence on the relationship between long-term exposure to PM 2.5 constituents and electrocardiographic (ECG) abnormalities is limited. This study aimed to quantify the association between long-term exposure to PM 2.5 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 PM 2.5 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 PM 2.5 constituents on ECG., Conclusion: Differential associations between various constituents of PM 2.5 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 PM 2.5 and cardiovascular conditions., 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: A large gap exists between the latest Global Air Quality Guidelines (AQG 2021) and Chinese air quality standards for NO 2 . Assessing whether and to what extent air quality standards for NO 2 should be tightened in China requires a comprehensive understanding of the spatiotemporal characteristics of population exposure to ambient NO 2 and related health risks, which have not been studied to date., Objective: We predicted ground NO 2 concentrations with high resolution in mainland China, explored exposure characteristics to NO 2 pollution, and assessed the mortality burden attributable to NO 2 exposure., Methods: Daily NO 2 concentrations in 2019 were predicted at 1-km spatial resolution in mainland China using random forest models incorporating multiple predictors. From these high-resolution predictions, we explored the spatiotemporal distribution of NO 2 , population and area percentages with NO 2 exposure exceeding criterion levels, and premature deaths attributable to long- and short-term NO 2 exposure in China., Results: The cross-validation R 2 and root mean squared error of the NO 2 predicting model were 0.80 and 7.78 μg/m 3 , respectively,at the daily level in 2019.The percentage of people (population number) with annual NO 2 exposure over 40 μg/m 3 in mainland China in 2019 was 10.40 % (145,605,200), and it reached 99.68 % (1,395,569,840) with the AQG guideline value of 10 μg/m 3 . NO 2 levels and population exposure risk were elevated in urban areas than in rural. Long- and short-term exposures to NO 2 were associated with 285,036 and 121,263 non-accidental deaths, respectively, in China in 2019. Tightening standards in steps gradually would increase the potential health benefit., Conclusion: In China, NO 2 pollution is associated with significant mortality burden. Spatial disparities exist in NO 2 pollution and exposure risks. China's current air quality standards may no longer objectively reflect the severity of NO 2 pollution and exposure risk. Tightening the national standards for NO 2 is needed and will lead to significant health benefits., 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 Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: The associations between short- and long-term exposure to ambient fine particulate matter with an aerodynamic diameter ≤ 2.5 µm (PM 2.5 ) and allergic symptoms in middle-aged and elderly populations remain unclear, particularly in China, where most cities have severe air pollution., Methods: Participants (n = 10,142; age = 40-75 years) were recruited from ten regions in China from 2018 to 2021 for the Predictive Value of Inflammatory Biomarkers and Forced Expiratory Volume in 1 s (FEV 1 ) for Chronic Obstructive Pulmonary Disease (PIFCOPD) study. Short-term (lag0 and lag0-7 day) and long-term (1-, 3- and 5-year) PM 2.5 concentrations at residences were extracted from the air pollutant database known as Tracking Air Pollution (TAP) in China. Multivariate logistic regression models were used to estimate associations for short- and long-term PM 2.5 exposure concentrations and long-term exposure models were additionally adjusted for short-term deviations., Results: A 10 µg/m 3 increase in PM 2.5 on the day the allergic symptoms questionnaire was administered (lag0 day) was associated with higher odds of allergic nasal (1.09, 95% CI 1.05, 1.12) and eye symptoms (1.08, 95% CI 1.05, 1.11), worsening dyspnea caused by allergens (1.06, 95% CI 1.02, 1.10), and ≥ 2 allergic symptoms (1.07, 95% CI 1.03, 1.11), which was similar in the lag0-7 day concentrations. A 10 µg/m 3 increase in the 1-year average PM 2.5 concentration was associated with an increase of 23% for allergic nasal symptoms, 22% for eye symptoms, 20% for worsening dyspnea caused by allergens, and 21% for ≥ 2 allergic symptoms, similar to the 3- and 5-year average PM 2.5 concentrations. These associations between long-term PM 2.5 concentration and allergic symptoms were generally unchanged after adjustment for short-term deviations., Conclusions: Short- and long-term exposure to ambient PM 2.5 was associated with an increased risk of allergic nasal and eye symptoms, worsening dyspnea caused by allergens, and ≥ 2 allergic symptoms., Trial Registration: Clinical trial ID: NCT03532893 (29 Mar 2018)., (© 2023. The Author(s).)

Background: Low birthweight attributable to fine particulate matter (PM 2.5 ) exposure is a global issue affecting infant health, especially in low- and middle-income countries (LMICs). However, large-population studies of multiple LMICs are lacking, and little is known about whether the source of PM 2.5 is a determinant of the toxic effect on birthweight., Objective: We examined the effect on birthweight of long-term exposure to PM 2.5 from different sources in LMICs., Methods: The birthweights of 53,449 infants born between September 16, 2017 and September 15, 2018 in 17 LMICs were collected from demographic and health surveys. Long-term exposure to PM 2.5 in 2017 produced by 20 different sources was estimated by combining chemical transport model simulations with satellite-based concentrations of total mass. Generalized linear regression models were used to investigate the associations between birthweight and each source-specific PM 2.5 exposure. A multiple-pollutant model with a ridge penalty on the coefficients of all 20-source-specific components was employed to develop a joint exposure-response function (JERF) of the PM 2.5 mixtures. The estimated JERF was then used to quantify the global burden of birthweight reduction attributable to PM 2.5 mixtures and to PM 2.5 from specific sources., Results: The fully adjusted single-pollutant model indicated that exposure to a 10 μg/m 3 increase in total PM 2.5 was significantly associated with a -6.6 g (95% CI -11.0 to -2.3) reduction in birthweight. In single- and multiple-pollutant models, significant birthweight changes were associated with exposure to PM 2.5 produced by international shipping (SHP), solvents (SLV), agricultural waste burning (GFEDagburn), road transportation (ROAD), waste handling and disposal (WST), and windblown dust (WDUST). Based on the global average exposure to PM 2.5 mixtures, the JERF showed that the overall change in birthweight could mostly be attributed to PM 2.5 produced by ROAD (-37.7 g [95% CI -49.2 to -24.4] for a global average exposure of 2.2 μg/m 3 ), followed by WST (-27.5 g [95% CI -42.6 to -10.7] for a 1.6-μg/m 3 exposure), WDUST (-19.5 g [95% CI -26.7 to -12.6] for a 8.6-μg/m 3 exposure), and SHP (-19.0 g [95% CI -32.3 to -5.7] for a 0.2-μg/m 3 exposure), which, with the exception of WDUST, are anthropogenic sources. The changes in birthweight varied geographically and were co-determined by the concentration as well as the source profile of the PM 2.5 mixture., Conclusion: PM 2.5 exposure is associated with a reduction in birthweight, but our study shows that the magnitude of the association differs depending on the PM 2.5 source. A source-targeted emission-control strategy that considers local features is therefore critical to maximize the health benefits of air quality improvement, especially with respect to promoting maternal and child health., 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 Inc. All rights reserved.)

Background: Fine particulate matter (PM2.5) is a risk factor for stroke, and patients with pre-existing diseases appear to be particularly susceptible. We conducted a case-crossover study to examine the association between short-term exposure to fine particulate matter (PM2.5) and hospital admission for stroke in individuals with atrial fibrillation (AF), hypertension, diabetes, or hyperlipidemia., Methods: Patients diagnosed with acute ischemic stroke (AIS) were recruited from 2015 to 2017 in Chinese Stroke Center Alliances. We estimated daily PM2.5 average exposures with a spatial resolution of 0.1° using a data assimilation approach combining satellite measurements, air model simulations, and monitoring values. Conditional logistic regression was used to assess PM2.5-related stroke risk in patients with pre-existing medical co-morbidities., Results: A total of 155,616 patients diagnosed with AIS were admitted. Patients with a history of AF ( n  = 15,430), hypertension ( n  = 138,220), diabetes ( n  = 43,737), or hyperlipidemia ( n  = 16,855) were assessed separately. A 10 µg/m 3 increase in daily PM2.5 was associated with a significant increase in AIS for individuals with AF at lag 4 (odds ratio (OR), 1.008; 95% confidence interval (CI), 1.002-1.014), and with hypertension (OR, 1.008; 95% CI, 1.006-1.010), diabetes (OR, 1.006; 95% CI, 1.003-1.010), and hyperlipidemia (OR, 1.007; 95% CI, 1.001-1.012) at lags 0-7. Elderly (⩾ 65 years old) and female patients with AF had significantly higher associations at lag 5 (OR, 1.009; 95% CI, 1.002-1.015) and lag 5 (OR, 1.010; 95% CI, 1.002-1.018), respectively., Conclusion: Short-term exposure to PM2.5 is significantly associated with hospital admission for stroke in individuals with pre-existing medical histories, especially in older or female patients with AF. Preventive measures to reduce PM2.5 concentrations are particularly important in individuals with other medical co-morbidities.

Introduction: Long-term exposure to ambient fine particulate matter (PM 2.5 ) has been linked to increases in the incidence of lung cancer. However, more evidence is needed to conclude its effects on lung cancer survival., Objectives: The study aimed to explore the relationship between long-term PM 2.5 exposure and lung cancer survival and evaluated the benefits of clean air actions in Beijing., Methods: A whole-population cohort study was conducted on lung cancer patients diagnosed between 2001 and 2017. An atmospheric chemical transport model was used to estimate exposure under a counterfactual scenario without the policy and then quantified the effect of the policy. Cox regression models were used with the seasonality-adjusted PM 2.5 as the main effect., Results: A 10 μg/m 3 increase in PM 2.5 was estimated to be with a 6.5 % (95 % CI: 4.8 %, 8.2 %) increase in the mortality rates. The association was heterogeneous and modified by individual-level characteristics. The clean air actions were estimated to have prevented 3548 (95 % CI: 3280, 3825) premature deaths and to have prolonged survival time by 4.29 months (95 % CI: 0.01, 25.11)., Conclusion: Our findings suggest that PM 2.5 exposure lowers the survival rate for lung cancer. The clean air actions implemented in Beijing can protect lung cancer patients by increasing their survival time., Synopsis: Long-term exposure to PM 2.5 can lower lung patients' survival rates whereas the clean air actions in Beijing have prolonged these patients' survival time by reducing PM 2.5 level., 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 Authors. Published by Elsevier B.V. All rights reserved.)

Background: Fine particulate matter (PM 2.5 ) from different source sectors might differ in toxicity. However, data from large-scale studies on vulnerable children in low- and middle-income countries (LMICs) are insufficient., Objective: To analyze the association of under-five death (U5D) with long-term exposure to PM 2.5 from different sources., Method: We evaluated demographic and health survey data for 79,995 babies born in 2017 in 16 Asian and African LMICs (AA-LMICs) and a Latin America low-income country (i.e., Haiti). Long-term exposure to PM 2.5 was assessed by a well-established product that attributed the annual concentration to 20 source sectors in 2017. The associations of survival during < 5-year periods with each source-specific concentration of PM 2.5 were analyzed by Cox regression with multiple adjustments. We derived a multiple-pollutant ridge regression model to estimate the joint exposure-response function (JERF) between U5D and PM 2.5 mixtures. To evaluate how sources affected PM 2.5 toxicity, we evaluated the number of U5Ds attributable to PM 2.5 based on the source profiles for 88 AA-LMICs., Results: According to the single-pollutant model, the risk of U5D increased by 7% (95% confidence interval [CI]: 5%, 9%) for each 10 μg/m 3 increment in total PM 2.5 concentration. The model performance was lower than that of the multiple-pollutant ridge regression model. For each 10 μg/m 3 increment in PM 2.5 , the excess risk of U5D ranged from 6% (95% CI: 4%, 9%) in Nepal to 10% (95% CI: 6%, 14%) in Mauritania. Based on the JERF, PM 2.5 contributed to 817,647 (95% CI: 585,729, 1,050,439), i.e., 28.0% (95% CI: 20.1%, 35.8%), of all U5Ds across the 88 AA-LMICs. The PM 2.5 -related U5Ds were mostly attributable to PM 2.5 produced by desert dust, followed by solid biofuel combustion and open fires., Conclusion: The average toxicity of PM 2.5 varied by source profile, which should be taken into consideration when planning public health interventions. For some AA LMICs, natural sources of PM 2.5 had the most significant health effects, and should not be ignored to ensure the protection of child health., 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 Author(s). Published by Elsevier Ltd.. All rights reserved.)

Objective: This study aimed to investigate the association of ambient PM 2.5 exposure with blood pressure (BP) at the population level in China., Methods: A total of 14,080 participants who had at least two valid blood pressure records were selected from the China Health and Retirement Longitudinal Survey during 2011-2015. Their long-term PM 2.5 exposure was assessed at the geographical level, on the basis of a regular 0.1° × 0.1° grid over China. A mixed-effects regression model was used to assess associations., Results: Each decrease of 10 μg/m 3 in the 1 year-mean PM 2.5 concentration (FPM 1Y ) was associated with a decrease of 1.24 [95% confidence interval ( CI ): 0.84-1.64] mmHg systolic BP (SBP) and 0.50 (95% CI : 0.25-0.75) mmHg diastolic BP (DBP), respectively. A robust association was observed between the long-term decrease in PM 2.5 and decreased BP in the middle-aged and older population. Using a generalized additive mixed model, we further found that SBP increased nonlinearly overall with FPM 1Y but in an approximately linear range when the FPM 1Y concentration was < 70 µg/m 3 ; In contrast, DBP increased approximately linearly without a clear threshold., Conclusion: Efficient control of PM 2.5 air pollution may promote vascular health in China. Our study provides robust scientific support for making the related air pollution control policies., (Copyright © 2023 The Editorial Board of Biomedical and Environmental Sciences. Published by China CDC. All rights reserved.)

Physical activity (PA) would increase the inhalation rate and thereby inhaled dose of air pollutants. However, it's still uncertain whether the effects of air pollutants on lung function are attenuated by PA, especially in the high-polluted areas. We aimed to disentangle the interaction between air pollution and PA on lung function among healthy adults. In this study, a real-world crossover study was conducted among 74 healthy adults. Each participant underwent both rest and 15-min intermittent moderate PA exposure scenarios (consisting of 15min stationary bike riding alternating with 15min of rest), which lasted for 2 h. On the same day, the participants among active and inactive group were exposed to the same air pollution. We have monitored the fine particulate matter (PM 2.5 ), particulate matter less than 10 μm (PM 10 ), particulate matter less than 1 μm (PM 1 ), black carbon (BC), nitrogen dioxide (NO 2 ), and ozone (O 3 ) continuously during 2-h exposure. Lung function were measured at five times points for each visit (before, immediately, 3 h, 5 h, and 24 h after the 2-h exposure scenario). Mixed-effects models were applied to explore the effects of air pollution, PA, and their interaction on lung function. The participants had a mean (standard deviation (SD)) age of 19.9 (0.9) years. The average concentration [mean ± SD] of PM 2.5 , PM 10 , PM 1 , BC, NO 2 , and O 3 were 59.4 ± 45.1 μg/m 3 , 122.8 ± 109.0 μg/m 3 , 38.8 ± 29.2 μg/m 3 , 1.94 ± 1.17 μg/m 3 , 59.5 ± 26.6 μg/m 3 , and 74.0 ± 30.3 μg/m 3 , respectively. Overall, greater increasement in lung function were observed among active group compared with inactive group at all timepoints. In fully adjusted models, we observed the benefits of PA and detrimental effects of air pollutants on lung function. Our results suggested that PA, compared to rest, alleviated the detrimental effects of air pollutants on lung function. We also stressed the importance of timing of measurements for capturing association. In conclusion, our observations suggested that PA might alleviate the associations between various pollutant exposures and lung function, which would drive further research towards potential pathway., 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 Ltd. All rights reserved.)

Background: Fine particulate matter (PM 2.5 ) produced by landscape fires is thought to be more toxic than that from non-fire sources. However, the effects of "fire-sourced" PM 2.5 on acute respiratory infection (ARI) are unknown., Methods: We combined Demographic and Health Survey (DHS) data from 48 countries with gridded global estimates of PM 2.5 concentrations from 2003 to 2014. The proportions of fire-sourced PM 2.5 were assessed by a chemical transport model using a variety of PM 2.5 source data. We tested for associations between ARI and short-term exposure to fire- and "non-fire-sourced" PM 2.5 using a bidirectional case-crossover analysis. The robustness and homogeneity of the associations were examined by sensitivity analyses. We also established a nonlinear exposure-response relationship between fire- and non-fire-sourced PM 2.5 and ARI using a two-dimensional spline function., Results: The study included 36,432 children under 5 years who reported ARI symptoms. Each 1 µg/m 3 increment of fire-sourced PM 2.5 was associated with a 3.2 % (95 % confidence interval [CI] 0.2, 6.2) increment in the risk of ARI. This effect was comparable to that of each ∼5 µg/m 3 increment in PM 2.5 from non-fire sources (3.1 %; 95 % CI 2.4, 3.7). The association between ARI and total PM 2.5 concentration was significantly mediated by the proportion of fire-sourced particles. Nonlinear analysis showed that the risk of ARI was increased by both fire- and non-fire-sourced PM 2.5 , but especially by the former., Conclusions: PM 2.5 produced by landscape fire was more strongly associated to ARI among children under 5 years than that from non-fire sources., 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.)

The independent associations of air pollution and Physical activity (PA) with metabolic syndrome (MetS) were inconsistent, while the joint associations between PA and air pollution with MetS were still unknown. We aimed to (1) further confirm the independent associations of PA and air pollution; (2) examine whether PA would attenuate the positive associations of air pollutants with MetS. We included 13,418 adults above 45 years old in this study. We defined MetS according to the Joint Interim Societies. The concentration of air pollutants (including fine particulate matter (PM 2.5 ), inhalable particles (PM 10 ), ozone (O 3 ), nitrogen dioxide (NO 2 ), sulfur dioxide (SO 2 ), and carbon monoxide (CO)) were estimated by ground-based measurements and satellite remote sensing products. We assessed the level of PA by metabolic equivalent (MET)-hour/week by summing the MET of all activities. We applied logistic regression models with sampling weight to explore the independent and joint associations of PA and air pollutants on MetS. Interaction plots were conducted to exhibit estimates of air pollutants on MetS as a function of PA. We found that all air pollutants were positively associated with the odds of MetS, while PA showed beneficial associations with MetS. The associations of air pollution on MetS decreased accompanied the increase of PA, while the detrimental effects between air pollutants and MetS did not be reversed by PA. In conclusion, PA may attenuate the associations of air pollutants with MetS, although in polluted areas, suggesting that keeping PA might be an effective way to reduce the adverse effects of air pollution with MetS., 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 Ltd. All rights reserved.)

Background: Gestational exposure to fine particulate matter (PM2.5) has been reported to be associated with an increased risk of fetal death in recent studies, but earlier studies in the past century have usually reported a non-significant association. As such, it remains unknown whether this adverse effect of PM2.5 exposure varies with time., Methods: Nearly 49.2 million eligible birth and fetal death records from 1989 to 2004 were selected from the United States (US) birth and fetal death certificate datasets. For each record, the level of prenatal exposure to PM2.5 was taken as the average concentration in the mother's residential county during the entire gestational period, according to well-established estimates of monthly levels across the contiguous US. We first stratified the dataset by the month of the last menstrual period (LMP) and then independently evaluated the nationwide association between PM2.5 exposure and fetal death within each stratum using five typical logit models: unadjusted, covariate-adjusted, propensity-score, double robust, and diagnostic-score models. Finally, we conducted a meta-analysis to pool estimated LMP-specific associations and explored how the overall association varied by LMP month., Results: Different models showed temporal heterogeneity in the estimated association between PM2.5 exposure and fetal death. According to the meta-analysis, double robust model estimates were more homogeneous than the rest, and thus the model outcome was recognized as the main result. For each 1-µg/m3 increase in prenatal exposure to PM2.5, the pooled odds ratio (OR) of fetal death was estimated to be 1.08 [95% confidence interval (CI): 1.05, 1.10]. The LMP-specific ORs exhibited a slightly increasing trend and a significant seasonal pattern. Compared with the pooled OR among samples with the LMP in spring, the estimates for summer, fall and winter were higher by 11.1% (95% CI: 6.2%, 16.3%), 27.8% (95% CI: 22.1%, 33.8%) and 28.8% (95% CI: 23.7%, 34.1%), respectively. We also found that temporal patterns in the association between PM2.5 exposure and fetal death could be explained by several population-level indicators or modifiers (i.e. ethnicity, maternal age, gestational weight gain, previous pregnancy of abnormal termination and diabetes)., Conclusions: Prenatal exposure to PM2.5 can increase the risk of fetal death. The effects of PM2.5 exposure may be modified by complex factors, which leads to a time-varying association., (© The Author(s) 2022; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: Studies show that fine particulate matter (PM 2.5 ) contributes to childhood obesity. However, evidence on the effects of its constituents on obesity has not been explored., Methods: Using multistage stratified cluster sampling, we enrolled 41,439 school-age children (aged 6-17 years) from a representative nationwide survey of 30 provinces in China (mean age ± standard deviation: 12.0 ± 3.3 years). Weight and height were measured using a physician beam scale with a height rod, and covariates were determined using a standard questionnaire. The concentration of PM 2.5 chemical constituents was estimated by a chemical transport (GEOS-Chem) model using input satellite data and ground-based observations. The constituents included black carbon, ammonium, nitrate, organic matter, sulfate, and soil dust. Generalized linear models were used to estimate the association between the chemical constituents of PM 2.5 and obesity., Results: A positive association between the constituents of PM 2.5 and obesity were observed. Children were more susceptible to black carbon than other species. A 1-μg/m 3 increase in black carbon led to a 0.079 (95 % confidence interval [CI]:0.028, 0.130)-kg/m 2 increase in body mass index (BMI). This also increased the odds of being obese and overweight to 1.174 (95 % CI: 1.111, 1.240) and 1.165 (95 % CI: 1.116, 1.216), respectively. Stratified analyses showed that the effects were stronger in girls and older children, as well as in urban and Northeast regions. The effect of the PM 2.5 constituents on obese and overweight children from urban areas significantly interacted with that of rural areas., Conclusions: The PM 2.5 constituents were associated with an increased BMI and childhood obesity. Further studies are warranted to validate these results and clarify their potential mechanisms. We suggest focusing on black carbon and Northeast regions., Competing Interests: Declaration of competing interest The authors declare no conflict of actual or potential financial interests., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Background: Despite cumulative evidence reports the interaction effects of physical activity (PA) and air pollution on lung function, the findings have been inconsistent. We aimed to identify the threshold values that reverse the beneficial effects of PA on lung function., Methods: This multistage probability sampling study examined 13,032 individuals aged ≥45 years across China from 2011 to 2015. City-level particulate matter 2.5 μm or less in diameter (PM 2.5 ) were estimated based on a two-stage machine learning model, with a spatial resolution of 0.1° × 0.1°. We assessed PA and a range of covariates using standardized self-reported questionnaires. The peak expiratory flow (PEF) was measured using a peak flow meter. We used mixed-effects linear regression models to examine the associations between PA and PM 2.5 , and their interactions with PEF., Results: Participants were 60.4 ± 9.4 years old [mean ± standard deviation (SD)]. The mean ± SD of PM 2.5 and PEF was 54.4 ± 23.0 μg/m 3 and 273 ± 116 L/min, respectively. Each 10 μg/m 3 increase in PM 2.5 was associated with a 1.27 L/min decrease in PEF. The PEF increased by 2.48 (95% confidence interval, CI: 0.40, 4.55) L/min, 0.74 (95% CI: -1.17, 2.66) L/min, and 1.99 (95% CI: 0.001, 3.99) L/min following a 10 h/week increment of walking, moderate intensity PA, and vigorous intensity PA, respectively. Detrimental associations between PM 2.5 and PEF outweighed PA benefits for approximate PM 2.5 concentrations >81 μg/m 3 (95% CI: 58.9, 111) and >77 μg/m 3 (95% CI: 39.7, 102) for walking and vigorous intensity PA, respectively., Conclusions: We identified the threshold of ambient PM 2.5 above which the beneficial association of PA with lung function may be reversed to an adverse one. Although the threshold may vary across populations and places, the findings suggested that reducing air pollution could enhance the benefits of PA on lung function., 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.)

Air pollution is a major trigger of chronic obstructive pulmonary disease (COPD). Dysregulation of the neuroendocrine hypothalamic-pituitary-adrenal (HPA) and sympathetic-adrenal medullary (SAM) axes is essential in progression of COPD. However, it is not clear whether air pollution exposure is associated with neuroendocrine responses in individuals with and without COPD. Based on a panel study of 51 stable COPD patients and 78 non-COPD participants with 384 clinical visits, we measured the morning serum levels of corticotropin-releasing hormone (CRH), adrenocorticotropic hormone (ACTH), cortisol, norepinephrine, and epinephrine as indicators of stress hormones released from the HPA and SAM axes. Ambient nitrogen dioxide (NO 2 ), fine particulate matter (PM 2.5 ), and meteorological conditions were continuously monitored at the station from 2 weeks before the start of clinical visits. Linear mixed-effects models were used to estimate associations between differences in stress hormones following an average of 1-14-day exposures to NO 2 and PM 2.5 . The average 1 day air pollutant levels prior to the clinical visits were 24.4 ± 14.0 ppb for NO 2 and 55.6 ± 41.5 μg/m 3 for PM 2.5 . We observed significant increases in CRH, ACTH, and norepinephrine, and decreases in cortisol and epinephrine with interquartile range increase in the average NO 2 and PM 2.5 concentrations in all participants. In the stratified analyses, we identified significant between-group difference in epinephrine following NO 2 exposure in individuals with and without COPD. These results may suggest the susceptibility of COPD patients to the neuroendocrine responses associated with short-term air pollution exposure., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Background: Exposure to landscape fire smoke (LFS) is linked to child mortality and birthweight. It is unknown whether gestational exposure to LFS affects child survival rate. We aimed to link under-five death (U5D) to gestational LFS exposure by performing a causal mediation analysis based on birthweight., Method: We conducted a sibling-matched case-control study of children under 5 years of age who were affiliated with the same mothers from Demographic and Health Surveys in 54 low- and middle-income countries, during the period from 2000 to 2014. LFS exposure was quantified as the surface concentration of fine particulate matter (PM 2.5 ) attributable to landscape fires, estimated using a global atmospheric model. Three pairwise associations between fire-sourced PM 2.5 , birthweight, and U5D were assessed using fixed-effects regressions. We used a bootstrap-based mediation test of regression coefficients to examine whether the LFS-birthweight-U5D pathway was statistically significant. We also conducted three pairwise exposure-response functions using nonlinear models and used them to estimate the pathway-specific disease burden from 2000 to 2014., Results: After adjustments for multiple confounders, each 1-µg/m 3 increase in gestational exposure to fire-sourced PM 2.5 was associated with a reduction of 2.179 (95% confidence interval [CI]: -3.777, -0.580) g in birthweight. Each 1-g birthweight reduction was associated with a 0.072% (95% CI: 0.065%, 0.078%) increase in U5D. Furthermore, each increase in exposure to fire-sourced PM 2.5 was associated with a 2.853% (95% CI: 0.835%, 4.911%) increase in U5D; 7.294% (95% CI: 0.710%, 24.254%) of the linkage was explained by LFS-attributable birthweight reduction. Based on the estimated exposure-response functions, from 2000 to 2014, global exposure to fire-sourced PM 2.5 contributed a mean birthweight reduction of 10.30 (95% CI: 2.93, 19.47) g, contributing to 60,350 (18,111, 106,619) premature U5Ds annually., Conclusion: In low- and middle-income countries, gestational exposure to LFS can increase mortality during infancy; appropriate interventions are needed to promote health in childhood., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: The pathophysiological mechanisms of air pollution-induced atherosclerosis are incompletely understood. Sphingolipids serve as biological intermediates during atherosclerosis development by facilitating production of proatherogenic apoB (apolipoprotein B)-containing lipoproteins. We explored whether sphingolipids mediate the proatherogenic effects of air pollution., Methods: This was a prospective panel study of 110 participants (mean age 56.5 years) followed from 2013 to 2015 in Beijing, China. Targeted lipidomic analyses were used to quantify 24 sphingolipids in 579 plasma samples. The mass concentrations of ambient particulate matter ≤2.5 μm in diameter (PM 2.5 ) were continuously monitored by a fixed station. We evaluated the associations between sphingolipid levels and average PM 2.5 concentrations 1-30 days before clinic visits using linear mixed-effects models and explored whether sphingolipids mediate PM 2.5 -associated changes in the levels of proatherogenic apoB-containing lipoproteins (LDL-C [low-density lipoprotein cholesterol] and non-HDL-C [nonhigh-density lipoprotein cholesterol]) using mediation analyses., Results: We observed significant increases in the levels of non-HDL-C and fourteen sphingolipids associated with PM 2.5 exposure, from short- (14 days) to medium-term (30 days) exposure time windows. The associations exhibited near-monotonic increases and peaked in 30-day time window. Increased levels of the sphingolipids, namely, sphinganine, ceramide C24:0, sphingomyelins C16:0/C18:0/C18:1/C20:0/C22:0/C24:0, and hexosylceramides C16:0/C18:0/C20:0/C22:0/C24:0/C24:1 significantly mediated 32%, 58%, 35% to 93%, and 23% to 86%, respectively, of the positive association between 14-day PM 2.5 average and the non-HDL-C level, but not the LDL-C level. Similar mediation effects (19%-91%) of the sphingolipids were also observed in 30-day time window., Conclusions: Our results suggest that sphingolipids may mediate the proatherogenic effects of short- and medium-term PM 2.5 exposure.

Background: Increasing evidence regards the role of ambient particles on morbidity and mortality caused by cardiovascular diseases (CVDs). However, there was no evidence about the association between ambient particles and CVD-associated disability. This study used large national representative data to investigate the relationship between long-term exposure to an aerodynamic diameter less than or equal to 2.5 µm (PM 2.5 ) and CVD-associated disability among Chinese adults aged 45 years old and above and estimated the burden of CVD-associated disability attributed to PM 2.5 ., Methods: Using data from the Second National Sample Survey on Disability, this study used a combination of self-reports or family members' reports and on-site medical diagnosis by experienced specialists to ascertain CVD-associated disability in 852,742 adults aged 45 years old and above. Logistic regression models and spline regression models were used to examine the association between PM 2.5 long-term exposure and CVD-associated disability, and the population attributable risk was calculated to assess the burden of CVD-associated disability contributed to PM 2.5 ., Results: Every increase of 10 μg/m 3 in PM 2.5 was associated with an 8% (OR = 1.08, 95% CI: 1.05, 1.10) increase the odds of CVD-associated disability. Stratified analyses by demographic factors suggested that this association was robust. There were 1.05 (0.74,1.35) million -3.53 (3.29,3.75) million CVD-associated disabilities attributed to high PM 2.5 concentration exposure (≥35 µg/m 3 ) among middle-aged and older adults in 2006. A reduction in PM 2.5 concentrations to 35 µg/m 3 corresponded to a decrease of 13.59% (9.55%, 17.46%)-23.98% (17.17%, 30.25%) in CVD-associated disability by age group, respectively, and this magnitude increased in areas with a high prevalence of CVD-related disability., Conclusions: This study suggests that reducing PM 2.5 concentrations may contribute to preventing CVD-associated disability and decreasing air pollution-related medical expenditures and rehabilitation fees., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright: © 2022 The Author(s).)

Based on the exposure data sets from the Tracking Air Pollution in China (TAP, http://tapdata.org.cn/ ), we characterized the spatiotemporal variations in PM 2.5 and O 3 exposures and quantified the long- and short-term exposure related premature deaths during 2013-2020 with respect to the two-stage clean air actions (2013-2017 and 2018-2020). We find a 48% decrease in national PM 2.5 exposure during 2013-2020, although the decrease rate has slowed after 2017. At the same time, O 3 pollution worsened, with the average April-September O 3 exposure increased by 17%. The improved air quality led to 308 thousand and 16 thousand avoided long- and short-term exposure related deaths, respectively, in 2020 compared to the 2013 level, which was majorly attributed to the reduction in ambient PM 2.5 concentration. It is also noticed that with smaller PM 2.5 reduction, the avoided long-term exposure associated deaths in 2017-2020 (13%) was greater than that in 2013-2017 (9%), because the exposure-response curve is nonlinear. As a result of the efforts in reducing PM 2.5 -polluted days with the daily average PM 2.5 higher than 75 μg/m 3 and the considerable increase in O 3 -polluted days with the daily maximum 8 h average O 3 higher than 160 μg/m 3 , deaths attributable to the short-term O 3 exposure were greater than those due to PM 2.5 exposure since 2018. Future air quality improvement strategies for the coordinated control of PM 2.5 and O 3 are urgently needed.

There is growing concern about the strong health effects of ultrafine particles (UFPs). However, less is known about the biological mechanisms. The objective of this study is to examine the association between short-term exposure to UFPs and fasting blood glucose (FBG) levels, and explore the potential physiological mechanisms at transcriptional levels. In a panel study of 135 participants, we measured FBG and the whole blood transcriptome repeatedly. The concentrations of ambient air pollutants were monitored continuously at a station. Linear mixed-effects models coupled with a mediating effect model were used to discriminate transcripts associated with air pollutant exposure and ln-transformed FBG levels. We found that FBG was significantly associated with interquartile range increase in the average UFPs concentrations 1-13 d prior to the clinical visits (ranging from 5.1% [95% CI 2.0-8.1%] in the 1-d time-window to 12.1% [95% CI 6.5-17.8%] in the 13-d time-window). Top 1000 transcripts associated with FBG increase following UFPs exposure were enriched into some biological pathways, such as pro-opiomelanocortin processing, negative regulation of hypoxia-inducible factor 1 A function, ubiquinone metabolism, and antigen presentation by major histocompatibility complex class I, classical pathway. These results suggest that elevated FBG associated with UFPs exposure may be related to regulation of metabolism, immune response, DNA damage, and apoptosis and survival., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Background: Exposure to air pollution is associated with several chronic diseases and subclinical processes that could subsequently contribute to physical disability. However, whether and to what extent air pollution exposure is associated with objective measures of physical functioning remains understudied., Methods: We used longitudinal data from the China Health and Retirement Longitudinal Study (CHARLS) and included 10 823 participants who were surveyed at least twice. Annual average exposure to fine particulate matter (PM2.5) was assessed using a state-of-the-art estimator. Physical functioning was assessed with 4 objective tests covering hand-grip strength, balance, repeated chair stands, and gait speed. Mixed-effects models with participants as a random term were used to estimate associations with multiple adjustments., Results: We found a significant and robust association between exposure to increased PM2.5 and the reduction in hand-grip strength and balance ability. Each 10 μg/m3 increase in annual averaged concentrations of PM2.5 was associated with a 220-g (95% confidence interval [CI]: 127, 312 g) reduction in hand-grip strength per 60 kg of body weight and a 5% risk (95% CI: 2, 7) of reduced balance ability. The estimated effect of each 10 μg/m3 increase in PM2.5 on hand-grip strength and balance ability was equivalent to the effect of aging (1.12 [95% CI: 0.76, 1.48] and 0.98 [95% CI: 0.50, 1.50] years, respectively)., Conclusions: PM2.5 may be differentially associated with various dimensions of physical functioning. Improving air quality can prevent physical disability., (© The Author(s) 2021. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Evaluating ozone levels at high resolutions and accuracy is crucial for understanding the spatiotemporal characteristics of ozone distribution and assessing ozone exposure levels in epidemiological studies. The national models with high spatiotemporal resolutions to predict ground ozone concentrations are limited in China so far. In this study, we aimed to develop a random forest model by combining ground ozone measurements from fixed stations, ozone simulations from the Community Multiscale Air Quality (CMAQ) modeling system, meteorological parameters, population density, road length, and elevation to predict ground maximum daily 8-h average (MDA8) ozone concentrations at a daily level and 1 km × 1 km spatial resolution. The model cross-validation R 2 and root mean squared error (RMSE) were 0.80 and 20.93 μg/m 3 at daily level in 2013-2019, respectively. CMAQ ozone simulations and near-surface temperature played vital roles in predicting ozone concentrations among all predictors. The population-weighted median concentrations of predicted MDA8 ozone were 89.34 μg/m 3 in mainland China in 2013, and reached 100.96 μg/m 3 in 2019. However, the long-term temporal variations among regions were heterogeneous. Central and Eastern China, as well as the Southeast Coastal Area, suffered higher ozone pollution and higher increased rates of ozone concentrations from 2013 to 2019. The seasonal pattern of ozone pollution varied spatially. The peak-season ozone pollution with the highest 6-month ozone concentrations occurred in different months among regions, with more than half domain in April-September. The predictions showed that not only the annual mean concentrations but also the percentages of grid-days with MDA8 ozone concentrations higher than 100/160 μg/m 3 have been increasing in the past few years in China; meanwhile, majority areas in mainland China suffered peak-season ozone concentrations higher than the air quality guidelines launched by the World Health Organization in September 2021. The proposed model and ozone predictions with high spatiotemporal resolution and full coverage could provide health studies with flexible choices to evaluate ozone exposure levels at multiple spatiotemporal scales in the future., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Allergic rhinitis (AR) is one of the most common allergic diseases in the world, and usually persists throughout the activity. Epidemiological studies have shown a positive association between air pollution and allergic rhinitis. However, we could not find any meta-analysis of the risk of air pollutants (PM 2.5 , PM 10 , NO 2 , SO 2 , O 3 and CO) on the prevalence of AR in people of all ages., Objectives: Carry out a meta-analysis on the results of recent studies (up to 2020) to present valid information about exposure to air pollution and risk of prevalence of AR., Methods: We systematically searched three databases for studies up to December 17, 2020, including air pollution and AR. Random effect models were conducted to estimate the pooled odds ratios (ORs) and 95% confidence intervals (95% CIs). Subgroup analysis, funnel plot, Egger's test, and the trim-and-fill method were also conducted., Results: Thirty-five studies across 12 countries, including a total of 453,470 participants, were included. The OR per 10 μg/m 3 increase of pollutants was 1.13 (1.04-1.22) for PM 10 and 1.12 (1.05-1.20) for PM 2.5 . The OR per 10 μg/m 3 increment of gaseous pollutants were 1.13 (1.07-1.20) for NO 2 , 1.13 (1.04-1.22) for SO 2 and 1.07 (1.01-1.12) for O 3 . No significant association was observed between CO and AR. Children or adolescents are more sensitive to air pollution than adults. The effects of PM 10 and SO 2 were significantly stronger in Europe than Asia. The effects of air pollutants were more significant and higher in developing countries than in developed countries, except for PM 10 . A significant difference of subgroup test was found between developed and developing countries of NO 2 ., Conclusion: This meta-analysis showed a positive association between air pollution and the prevalence of allergic rhinitis, and identified geographic area and economic level as the potential modifiers for the association., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background: Air pollution might accelerate cognitive ageing; it is unclear whether large-scale interventions, such as China's Clean Air Act (CCAA), can mitigate cognitive deterioration. We aimed to evaluate the effect of CCAA on changes in cognitive function in older adults., Methods: In this population-based, quasi-experimental study, we did a difference-in-differences analysis of the data collected during the 2014 and 2018 waves of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). The study design used a counterfactual analysis feature by dividing CLHLS participants into two groups. The intervention group included participants who lived in areas where the provincial government set a target of reducing particulate matter (PM) by at least 5% annually from 2014 onward, whereas the control group consisted of individuals who lived in areas without a PM reduction target. Global cognitive function was measured using the Mini-Mental State Examination (MMSE). We used fixed-effects models to examine the between-group differences in MMSE score changes before and after CCAA implementation. We associated longitudinal changes in MMSE scores with changes in concentrations of PM with a diameter of less than 2·5 μm (PM 2·5 ) concentration and other regulated pollutants. We used alternative models and sensitivity analyses to evaluate the robustness of the results from the main models., Findings: 2812 individuals participated in the 2014 and 2018 surveys (mean age 81·0 years [SD 9·3] in 2014; 1408 [50·1%] female and 1404 [49·9%] male). 2251 (80·0%) were included in the intervention group and 561 (20·0%) in the control group. After controlling for potential confounders, the intervention group had a significantly smaller decline in MMSE scores from 2014 to 2018 compared with the control group: the mean between-group difference was 2·45 points (95% CI 1·32-3·57). Interquartile increases in PM 2·5 were associated with a significant MMSE score decline of 0·83 points (95% CI 0·24-1·42); similarly, increases in SO 2 were also associated with a significant MMSE score decline of 0·80 points (0·32-1·29)., Interpretation: Implementing stringent clean air policies might mitigate the risk of air pollutant-associated cognitive ageing in older people., Funding: National Natural Sciences Foundation of China, National Key R&D Program of China, China Postdoctoral Science Foundation funded project, the Duke/Duke-National University of Singapore Collaboration Pilot Project, the National Institute on Aging and Peking University-Baidu Fund, Energy Foundation, and the Fundamental Research Funds for the Central Universities., Competing Interests: Declaration of interests We declare no competing interests.

Background: Over 3 million people die every year from diseases caused by exposure to outdoor PM 2·5 air pollution, and more than a quarter of these premature deaths occur in China. In addition to clean-air policies that target pollution emissions, climate policies aimed at reducing fossil-fuel CO 2 emissions (eg, to avoid 1·5°C of warming) might also greatly improve air quality and public health. However, no comprehensive accounting of public health outcomes has been done under different energy pathways and local clean-air management decisions in China. We aimed to develop an integrated method for quantifying the health co-benefits from different climate, energy, and clean-air policy scenarios and to assess the relationship between climate and clean-air policies and future health burdens in China, where an ageing population will further exacerbate the effects of air pollution., Methods: For this modelling study, we used a China-focused integrated assessment model and a dynamic emission projection model to project future Chinese air quality in scenarios spanning a range of global climate targets (1·5°C, 2°C, national determined contributions [NDC], unambitious, baseline, and 4·5°C) and national clean-air actions (termed 2015-pollution, current-pollution, and ambitious-pollution). We then evaluated the health effects of PM 2·5 air pollution in the scenario matrix using the air quality model and the latest epidemiological concentration-response functions from the 2019 Global Burden of Diseases, Injuries, and Risk Factors Study., Findings: We found that, without ambitious climate mitigation (eg, under current NDC pledge), Chinese deaths related to PM 2·5 air pollution might not always decrease-and might often grow-by 2050 compared with the base year of 2015, regardless of clean-air policies and air quality improvements. For example, in the scenario that tracks China's current NDC pledge and uses the best available pollution control technologies (the ambitious-pollution and NDC goals scenario), PM 2·5 -related deaths in China would decrease slightly by 2030 to 1·23 million per year (95% CI 0·95-1·51) from 1·25 million (1·04-1·46) in 2015, but would not decrease further by 2050 (1·21 million, 0·86-1·60) despite substantial and continuous improvements in population-weighted air quality (from 27·2 μg/m 3 in 2030 to 16·0 μg/m 3 in 2050). The contrary trends of improving air quality and increasing PM 2·5 -related deaths in many of our scenarios revealed the extent to which extra efforts are needed to compensate for the increasing age of China's population in the future. With the scenarios that included ambitious clean-air policies and met international climate goals to avoid 1·5°C and 2°C of warming (the ambitious-pollution-2°C goals scenario and the ambitious-pollution-1·5°C goals scenario), we observed substantial decreases in China's PM 2·5 -related deaths of 0·32-0·55 million deaths compared with NDC goals in 2050, and age-standardised death rates decreased by 10·2-14·2 deaths per 100 000 population per year., Interpretation: Our results show that ambitious climate policies (ie, limiting global average temperature rise to well below 2°C) and low-carbon energy transitions coupled with stringent clean-air policies are necessary to substantially reduce the human health effects from air pollution in China, regardless of socioeconomic assumptions. Our findings could help policy makers understand the crucial links between climate policy and public health., Funding: The National Natural Science Foundation of China., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Air pollution has become a major issue in China, especially for traffic-related pollutants such as nitrogen dioxide (NO 2 ). Current studies in China at the national scale were less focused on NO 2 exposure and consequent health effects than fine particulate exposure, mainly due to a lack of high-quality exposure models for accurate NO 2 predictions over a long period. We developed an advanced modeling framework that incorporated multisource, high-quality predictor data (e.g., satellite observations [Ozone Monitoring Instrument NO 2 , TROPOspheric Monitoring Instrument NO 2 , and Multi-Angle Implementation of Atmospheric Correction aerosol optical depth], chemical transport model simulations, high-resolution geographical variables) and three independent machine learning algorithms into an ensemble model. The model contains three stages: (1) filling missing satellite data; (2) building an ensemble model and predicting daily NO 2 concentrations from 2013 to 2019 across China at 1×1 km 2 resolution; (3) downscaling the predictions to finer resolution (100 m) at the urban scale. Our model achieves a high performance in terms of cross-validation to assess the agreement of the overall (R 2  = 0.72) and the spatial (R 2  = 0.85) variations of the NO 2 predictions over the observations. The model performance remains moderately good when the predictions are extrapolated to the previous years without any monitoring data (CV R 2  > 0.68) or regions far away from monitors (CV R 2  > 0.63). We identified a clear decreasing trend of NO 2 exposure from 2013 to 2019 across the country with the largest reduction in suburban and rural areas. Our downscaled model further improved the prediction ability by 4%-14% in some megacities and captured substantial NO 2 variations within 1-km grids in the urban areas, especially near major roads. Our model provides flexibility at both temporal and spatial scales and can be applied to exposure assessment and epidemiological studies with various study domains (e.g., national or citywide) and settings (e.g., long-term and short-term)., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

The Beijing-Tianjin-Hebei (BTH) region, which has a resource-dependent economy dominated by clusters of heavy industries, has long borne the highest PM 2.5 pollution levels in China, prompting serious concerns about the region's disease burden. Pollution-intensive industries in the BTH region not only meet local consumer demands but also those of other places via the supply chain. In the present study, we combined a multi-region input-output model with adjoint source sensitivity modeling technique at a high resolution (0.25° × 0.3125°) to apportion PM 2.5 -related mortality risks in the BTH to consuming areas and sectors. The model predicted that exposure to ambient PM 2.5 caused 0.12 million premature deaths (95% confidence interval: 0.08-0.15) in the BTH region in 2013. The adjoint source sensitivity results showed that only 46% of the total premature deaths were attributable to local consumption. The top contributors of local consumption were rural households and the agricultural sector in Hebei, and service sector in Beijing. Consumption of other domestic regions and international export accounted for 25% of the total premature deaths in the BTH, mainly to support consumption of manufacturing and construction products of these outer regions. Atmospheric transport of pollutants, mainly from the surrounding areas, accounted for the remaining 29% of total deaths in BTH. Our findings underline the consumption-based driven force of BTH's pollution and associated health impacts, which may facilitate the joint control actions among the BTH region and its surrounding areas from a comprehensive perspective., 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 © 2021 Elsevier B.V. All rights reserved.)

Severe episodic air pollution blankets entire cities and regions and have a profound impact on humans and their activities. We compiled daily fine particle (PM 2.5 ) data from 100 cities in five continents, investigated the trends of number, frequency, and duration of pollution episodes, and compared these with the baseline trend in air pollution. We showed that the factors contributing to these events are complex; however, long-term measures to abate emissions from all anthropogenic sources at all times is also the most efficient way to reduce the occurrence of severe air pollution events. In the short term, accurate forecasting systems of such events based on the meteorological conditions favouring their occurrence, together with effective emergency mitigation of anthropogenic sources, may lessen their magnitude and/or duration. However, there is no clear way of preventing events caused by natural sources affected by climate change, such as wildfires and desert dust outbreaks., (Copyright © 2021. Published by Elsevier Ltd.)

Air pollution has altered the Earth's radiation balance, disturbed the ecosystem, and increased human morbidity and mortality. Accordingly, a full-coverage high-resolution air pollutant data set with timely updates and historical long-term records is essential to support both research and environmental management. Here, for the first time, we develop a near real-time air pollutant database known as Tracking Air Pollution in China (TAP, http://tapdata.org.cn/) that combines information from multiple data sources, including ground observations, satellite aerosol optical depth (AOD), operational chemical transport model simulations, and other ancillary data such as meteorological fields, land use data, population, and elevation. Daily full-coverage PM 2.5 data at a spatial resolution of 10 km is our first near real-time product. The TAP PM 2.5 is estimated based on a two-stage machine learning model coupled with the synthetic minority oversampling technique and a tree-based gap-filling method. Our model has an averaged out-of-bag cross-validation R 2 of 0.83 for different years, which is comparable to those of other studies, but improves its performance at high pollution levels and fills the gaps in missing AOD on daily scale. The full coverage and near real-time updates of the daily PM 2.5 data allow us to track the day-to-day variations in PM 2.5 concentrations over China in a timely manner. The long-term records of PM 2.5 data since 2000 will also support policy assessments and health impact studies. The TAP PM 2.5 data are publicly available through our website for sharing with the research and policy communities.

Background: The prevalence of landscape fires has increased, particularly in low-income and middle-income countries (LMICs). We aimed to assess the impact of exposure to landscape fire smoke (LFS) on the health of children., Methods: We conducted a sibling-matched case-control study and selected 552 155 children (aged <18 years) from Demographic and Health Surveys in 55 LMICs from 2000 to 2014. Each deceased child was matched with their sibling(s). The exposure indicators were fire-sourced PM 2·5 and dry-matter emissions. We associated these exposure indicators with child mortality using conditional regressions, and derived an exposure-response function using a non-linear model. Based on the association, we quantified the global burden of fire-attributable child deaths in LMICs from 2000 to 2014., Findings: Each 1 μg/m 3 increment of fire-sourced PM 2·5 was associated with a 2·31% (95% CI 1·50-3·13) increased risk of child mortality. The association was robust to different models. The exposure-response function was superlinear and suggested per-unit exposure to larger fires was more toxic. Based on our non-linear exposure-response function, we estimated that between 2000 and 2014, the five countries with the largest number of child deaths associated with fire-sourced PM 2·5 were Nigeria (164 000 [126 000 to 209 000] annual deaths), Democratic Republic of the Congo (126 000 [95% CI 114 000 to 139 000] annual deaths), India (65 900 [-22 200 to 147 000] annual deaths), Uganda (30 200 [24 500 to 36 300] annual deaths), and Indonesia (28 900 [19 100 to 38 400])., Interpretation: Exposure to landscape fire smoke contributes substantially to the global burden of child mortality., Funding: National Natural Science Foundation of China, Ministry of Science and Technology of China, Peking University, UK National Institute for Health Research Health Protection Research Unit, Leverhulme Center for Wildfires, Environment and Society, and National Environment Research Council National Capability funding to National Centre for Earth Observation and Energy Foundation., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Ambient air pollution is a major risk factor for the prevalence and exacerbation of chronic obstructive pulmonary disease (COPD). Based on the COPDB (COPD in Beijing) panel study, whole-blood transcriptomes were repeatedly measured in 48 COPD patients and 62 healthy participants. Ambient mass concentrations of fine particulate matter (PM 2.5 ), temperature, and relative humidity were continuously monitored at a monitoring station. The linear mixed-effects models were applied to estimate the associations between logarithmically transformed transcript levels and 1-day (d), 7-d, and 14-d average concentrations of PM 2.5 before the start of follow-up visits. MetaCore™ was used to conduct the pathway enrichment analyses. Exposure to 1-, 7-, and 14-d average concentrations of PM 2.5 was significantly associated with the transcriptome responses in both groups. The top 10, top 100, and top 1000 PM 2.5 -associated transcripts differed greatly between the two groups. Among COPD patients, role of alpha-6/beta-4 integrins in carcinoma progression, Notch signaling in breast cancer, and ubiquinone metabolism were the most significantly enriched PM 2.5 -associated biological pathways in the three time windows, respectively. In healthy participants, pro-opiomelanocortin processing was the most significant PM 2.5 -associated biological pathway in all three time windows. Our findings provide novel insights into the adverse health effects of air pollution exposure., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Certain studies suggest that air pollution could be a risk factor for obesity, but the evidence on the association between air pollution exposure and obesity in adults is limited. This study aims to examine the association between long-term exposure to fine particulate matter (PM 2.5 ) and obesity-related traits in Chinese adults. Thus, a cross-sectional study was conducted based on a nationally representative sample of 91, 121 adults from 31 provinces in China. Integrated the data from satellites, chemical transport model, and ground observations, annual average concentrations of PM 2.5 was obtained at the township level using a machine learning method. The information on body weight, height, and waist circumference (WC) were obtained from a questionnaire survey. The general obesity and abdominal obesity status were classified based on body mass index (BMI) and WC, respectively. Logistic and multivariate linear regression models were used to examine the association between PM 2.5 and obesity-related traits, along with the examination of potential effect modifications. After adjustment for covariates, a 10 μg/m 3 increase in PM 2.5 concentration was associated with 8.0% [95% confidence interval (CI): 1.0%, 10.0%] and 10% (95% CI: 9.0%, 11.0%) increases in odds for general obesity and abdominal obesity, respectively. The odds ratios associated with per 10 μg/m 3 PM 2.5 increase were significantly greater in individuals of older age (≥60 years), of Han ethnicity, with lower socioeconomic status (SES), cooking without using a ventilation device, using unclean household fuels, having near-home pollution sources, and doing no physical exercise. These findings suggest that long-term exposure to ambient PM 2.5 increase obesity risk in Chinese adults. It has significant significance to reduce air pollution to reducing the burden of obesity, particularly for the susceptible populations., Competing Interests: Declaration of competing interest The views expressed in this manuscript are solely of the authors and do not necessarily reflect those of the funding agencies. Additionally, we declare that we have no financial and personal relationships with other organizations that can inappropriately influence our work., (Copyright © 2021. Published by Elsevier B.V.)

Background: Although epidemiological studies on the effect of chronic fine particulate matter (PM 2.5 ) exposure on lipid disorders have been conducted, it is unclear if improved air quality is associated with beneficial changes in the blood lipid profile. In China, clean air actions introduced in 2013 have rapidly reduced the concentration of ambient PM 2.5 ., Methods: We conducted a change-by-change study, based on two waves (2011 and 2015) of a national survey of the same 5111 Chinese adults before and after implementation of the clean air actions. Long-term PM 2.5 exposure was assessed using a state-of-the-art estimator at the city level. Based on the within-individual differences between the two waves, we associated PM 2.5 changes with the variations of four lipid biomarkers-triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C)-using a mixed-effects regression model. The robustness and homogeneity of the association were tested via sensitivity analyses., Results: For each 10 μg/m 3 reduction in PM 2.5 , LDL-C, and TC decreased by 2.71 (95% confidence interval [CI] 0.10-5.32) and 4.16 (95% CI 1.24-7.08)mg/dL, respectively. There was no significant association with HDL-C or TG. The results were robust among models adjusted for different covariates. PM 2.5 was a significant risk factor for dyslipidemia with an adjusted relative risk of 1.21 (95% CI 1.09-1.34). The association between PM 2.5 and LDL-C was stronger in the elderly or adults who did not take medications., Conclusions: The results suggest that PM 2.5 exert a cardiotoxic effect by increasing the risk of lipid disorders. Improvement of air quality could prevent dyslipidemia by reducing LDL-C and TC levels. Clean air policies should be implemented as public health measures in countries with aging societies, especially developing ones with a high air pollution burden., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Long-term exposure to ambient fine particles (PM 2.5 ) has been evidenced to be a leading contributor to premature mortality in China and many other countries. Previous studies assess the health risk using an exposure-response function, such as an exposure-mortality model (EMM) based on total concentration of PM 2.5 . However, the risk assessment method can be problematic as it ignores the unequal toxicity between the different chemical components of PM 2.5 . To derive a components-specific EMM (CS-EMM), we conducted a whole-population-based epidemiology study in China, using the Chinese Population Census data in 2000 and 2010. Concentrations of ambient PM 2.5 and its components were assessed by satellite-based concentrations of PM 2.5 and composition fractions simulated by a chemical transport model. We used a difference-in-difference approach to associate county-level changes of census-based total mortality with changes of PM 2.5 and its components between 2010 and 2000. The chemical components of PM 2.5 simulated by the model included sulfate (SO 4 2- ), nitrate (NO 3 - ), ammonium (NH 4 + ), organic carbon (OC), and black carbon (BC). We further compared CS-EMM with EMM based on a single pollutant of PM 2.5 (PM 2.5 -EMM) or black carbon (BC-EMM), by evaluating their performance in a risk assessment. Using census-based total mortality and cross validation we evaluated the performance of the mortality prediction of an EMM, and found that the CS-EMM outperformed PM 2.5 -EMM or BC-EMM. For instance, CS-EMM, PM 2.5 -EMM, and BC-EMM all overestimated the average number of county-level deaths by 117, 142, and 149, respectively; hence CS-EMM overestimated by the lowest amount. Moreover, CS-EMM had the advantage of interpreting the toxicity of PM 2.5 mixture in its entirety. From 2000 to 2010, CS-EMM attributed a 205 496 increase in PM 2.5 -associated mortality across China to the joint contribution of the growth of total concentration and the reduction of PM 2.5 toxicity. Among the components, BC contributed 6.4% of PM 2.5 , and should help policy-makers target the toxic sources of air pollution.2.5 -associated deaths. This study developed a framework to establish and validate an exposure-response function based on PM 2.5 components, and illustrated its advantages in terms of risk prediction and result interpretation in China. Our approach can be utilized to evaluate how chemical composition modified the health impact of PM 2.5 , and should help policy-makers target the toxic sources of air pollution.

The effects of ambient fine particulate matter (PM 2.5 ) exposure on blood pressure have been widely reported. However, there remains uncertainty regarding the underlying roles of particulate matter components. We aimed to investigate the association between ambient PM 2.5 exposure and blood pressure, as well as the potential effects of trace metal(loid)s, in a repeated-measurement study that enrolled women of childbearing age. Our study included 35 participants from Hebei Province, China, each of whom was visited for five times. During each visit, we conducted questionnaire surveys, measured blood pressure, and collected blood. The daily PM 2.5 exposure of participants was estimated according to their residential addresses using a spatiotemporal model that combined monitoring data with satellite measurements and chemical-transport model simulations. This model was used to calculate average PM 2.5 concentrations in 1, 3, 7, 15, 30, and 60 days prior to each visit. Serum concentrations of various trace metal(loid)s were measured. A linear mixed-effects model was used to investigate associations among study variables. Overall, the mean (standard deviation) 60 days PM 2.5 concentration over all five visits was 108.1(43.3) μg/m 3 . PM 2.5 concentration was positively associated with both systolic and diastolic blood pressures. Likewise, ambient PM 2.5 concentration was positively associated with serum concentrations of manganese and arsenic, and negatively associated with serum concentrations of nickel, tin, and chromium. Only the serum concentration of molybdenum was negatively associated with systolic blood pressure. We concluded that ambient PM 2.5 exposure may contribute to elevated blood pressure, potentially by interfering with internal intake of various metal(loid)s in the human body., 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.)

Exposure to fine particulate matter (PM 2.5 ) has become a major global health concern. Although modeling exposure to PM 2.5 has been examined in China, accurate long-term assessment of PM 2.5 exposure with high spatiotemporal resolution at the national scale is still challenging. We aimed to establish a hybrid spatiotemporal modeling framework for PM 2.5 in China that incorporated extensive predictor variables (satellite, chemical transport model, geographic, and meteorological data) and advanced machine learning methods to support long-term and short-term health studies. The modeling framework included three stages: (1) filling satellite aerosol optical depth (AOD) missing values; (2) modeling 1 km × 1 km daily PM 2.5 concentrations at a national scale using extensive covariates; and (3) downscaling daily PM 2.5 predictions to 100-m resolution at a city scale. We achieved good model performances with spatial cross-validation (CV) R 2 of 0.92 and temporal CV R 2 of 0.85 at the air quality sites across the country. We then estimated daily PM 2.5 concentrations in China from 2013 to 2019 at 1 km × 1 km grid cells. The downscaled predictions at 100 m resolution greatly improved the spatial variation of PM 2.5 concentrations at the city scale. The framework and data set generated in this study could be useful to PM 2.5 exposure assessment and epidemiological studies.

Rationale: Lung function impairment is reportedly associated with elevated exposure to ambient fine particles (particulate matter ≤2.5 μm in aerodynamic diameter [PM 2.5 ]). However, whether improvement of air quality prevents respiratory diseases is unclear. Objectives: To examine whether the policy-driven reduction in PM 2.5 concentration after 2013 was associated with improved lung function among Chinese adults. Methods: We compared the longitudinal measurements of peak expiratory flow (PEF) before (2011) and after (2013 and 2015) China's clean air actions. Long-term exposure to ambient pollution was assessed using a state-of-the-art estimator of historical PM 2.5 concentration, and its association with PEF was examined using a linear mixed-effects model. The robustness and homogeneity of the association were examined via sensitivity analyses. Results: We analyzed 35,055 repeated measurements from 13,959 adults. Mean of age at survey was 60.5 years (standard deviation = 9.7 yr). Compared with the reference in 2011, after the policy was implemented, the mean PEF was elevated by 9.19 (6.79-11.59) L/min and 36.64 (33.53-39.75) L/min in 2013 and 2015, respectively. According to the regression results, each 10-μg/m 3 reduction of PM 2.5 was associated with a 14.95 (12.62-17.28) L/min improvement of PEF. The significance of the association was not affected by adjustments for covariates, inclusion criteria, or the approach to control for the effects of age. Adults of lower socioeconomic status (e.g., those with an educational level of below middle school or rural residents) were more susceptible to the adverse effects of PM 2.5 on PEF. Conclusions: We found a robust association between a reduction in PM 2.5 and an increase in PEF among Chinese adults. The findings suggest that mitigation of air pollution can promote respiratory health.

Background: Exposure to air pollution, a leading contributor to the global burden of disease, can cause economic losses. Driven by clean air policies, the air quality in China, one of the most polluted countries, has improved rapidly since 2013. This has enabled a unique, quasi-experiment to assess the economic impact of air pollution empirically., Methods and Findings: Using a series of nation-scale longitudinal surveys in 2011, 2013, and 2015, we first examined the questionnaire-based medical expenditure changes before and after the policy intervention for air pollution. Using a state-of-the-art estimator of the historical concentration of particulate matters with diameter less than 2.5 μm (particulate matter (PM)2.5), we further quantified the association between household medical expenditure and PM2.5 using mixed-effect models of the repeated measurements from 26,511 households in 126 cities. Regression models suggest a robust linear association between reduced PM2.5 and saved medical expenditures, since the association did not vary significantly across models with different covariate adjustments, subregions, or subpopulations. Each 10 μg/m3 reduction in PM2.5 was associated with a saving of 251.6 (95% CI: 30.8, 472.3; p-value = 0.026) Yuan in per capita annual medical expenditure. However, due to limitations in data quality (e.g., self-reported expenditures), and imperfect control for unmeasured confounders or impact from concurrent healthcare reform in China, the causality underlying our findings should be further confirmed or refuted., Conclusion: In this study, we observed that compared with the PM2.5 reduction in 2013, the PM2.5 reduction in 2017 was associated with a saving of 552 (95% CI: 68, 1036) Yuan / (person × year), or approximately 736 billion Yuan (equivalent to 111 billion US dollar) per year nationally, which is equivalent to approximately 1% of the national gross domestic product of China., Competing Interests: The authors have declared that no competing interests exist.

Since 2013, clean-air actions in China have reduced ambient concentrations of PM 2.5 . However, recent studies suggest that ground surface O 3 concentrations increased over the same period. To understand the shift in air pollutants and to comprehensively evaluate their impacts on health, a spatiotemporal model for O 3 is required for exposure assessment. This study presents a data-fusion algorithm for O 3 estimation that combines in situ observations, satellite remote sensing measurements, and model results from the community multiscale air quality model. Performance of the algorithm for O 3 estimation was evaluated by five-fold cross-validation. The estimates are highly correlated with the in situ observations of the maximum daily 8 h averaged O 3 ( R 2 = 0.70). The mean modeling error (measured using the root-mean-squared error) is 26 μg/m 3 , which accounts for 29% of the mean level. We also found that satellite O 3 played a key role to improve model performance, particularly during warm months. The estimates were further used to illustrate spatiotemporal variation in O 3 during 2013-2017 for the whole country. In contrast to the reduced trend of PM 2.5 , we found that the population-weighted O 3 mean increased from 86 μg/m 3 in 2013 to 95 μg/m 3 in 2017, with a rate of 2.07 (95% CI: 1.65, 2.48) μg/m 3 per year at the national level. This increased trend in O 3 suggests that it is becoming an important contributor to the burden of diseases attributable to air pollutants in China. The developed method and the results generated from this study can be used to support future health-related studies in China.

The spatial distribution of the COVID-19 infection in China cannot be explained solely by geographical distance and regulatory stringency. In this research we investigate how meteorological conditions and air pollution, as concurring factors, impact COVID-19 transmission, using data on new confirmed cases from 219 prefecture cities from January 24 to February 29, 2020. Results revealed a kind of nonlinear dose-response relationship between temperature and coronavirus transmission. We also found that air pollution indicators are positively correlated with new confirmed cases, and the coronavirus further spreads by 5-7% as the AQI increases by 10 units. Further analysis based on regional divisions revealed that in northern China the negative effects of rising temperature on COVID-19 is counteracted by aggravated air pollution. In the southern cities, the ambient temperature and air pollution have a negative interactive effect on COVID-19 transmission, implying that rising temperature restrains the facilitating effects of air pollution and that they jointly lead to a decrease in new confirmed cases. These results provide implications for the control and prevention of this disease and for the anticipation of another possible pandemic., 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 B.V. All rights reserved.)

Background: Childhood obesity is a global health issue, and limited evidence suggests that air pollution may be a contributing factor. This study aims to examine whether exposure to fine particulate matter (PM 2.5 ) is associated with obesity status in a nationally representative sample of schoolchildren in China., Methods: The study population consisted of 41,439 schoolchildren of 6-17 years old, recruited from 30 provinces in China using a multi-stage stratified sampling method. Weights and heights were measured for all the participants, and sociodemographic information was collected using a questionnaire. The obesity status was classified following the Chinese national standards. The PM 2.5 exposure was estimated as the 5-year average concentration at the school location for each participant. The association between obesity status and PM 2.5 exposure was examined using weighted logistic regressions adjusted for potential confounders., Results: The prevalence of normal weight, overweight, and obesity were 78.5%, 12.4%, and 9.0%, respectively. PM 2.5 exposure averaged 59.8 ± 17.6 μg/m 3 with a range of 30.5-115.2 μg/m 3 among all the participants. The risk of obesity increased by 10.0% (95% confidence interval: 3.0-16.0%) per 10 μg/m 3 increase in PM 2.5 exposure. The PM 2.5 -associated risk was significantly elevated in older age groups and children living in urban areas (interaction p-values < 0.05)., Conclusions: This national survey revealed that approximately 1 in 5 Chinese schoolchildren were overweight or obese. Exposure to PM 2.5 in the ambient air was significantly associated with childhood obesity. The findings suggest the need for further research to uncover the roles of PM 2.5 exposure in childhood obesity development., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: The relationship between temperature and mental disorders is still unclear. This study aims to assess the short-term effect of apparent temperature (AT) on daily emergency visits of mental and behavioral disorders (MDs) in Beijing, China., Methods: Daily counts of emergency visits related to MDs in Beijing from 2016 to 2018 were obtained. A quasi-Poisson generalized additive model combined with a distributed lag non-linear model (DLNM) was applied to analyze the lag-exposure-response relationship between AT and emergency admissions related to MDs. Sunshine duration, precipitation, PM 2.5 , SO 2 , O 3 , time trend, day of week and holiday were adjusted in the model., Results: Total daily emergency visits for MDs during the study period were 16,606. With the reference of -2.4 °C (temperature with the minimum emergency visit risk), the single day effects of low AT (-8.6 °C, 10th percentile) and high AT (9.2 °C, 90th percentile) on MDs emergency visits reached a relative risk peak of 1.043 (95%CI: 1.017-1.069) on lag day 4 and 1.105 (95%CI: 1.006-1.215) on lag day 1, respectively. The greatest cumulative effect of high AT emerged on lag 0-5 days and reached a relative risk of 1.435 (95%CI: 1.048-1.965), while no significant cumulative effect of low AT was observed. There was a significant effect of high AT on emergency visits of MDs due to psychoactive substance use and male patients., Conclusions: Both low and high AT are demonstrated to be the significant risk factors of MDs, which highlights the need of strengthening the health interventions, patient medical services and early warning for patients., 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 The Authors. Published by Elsevier B.V. All rights reserved.)

Results from recent studies on associations between blood pressure (BP) and short-term exposure to fine particulate matter (PM 2.5 ) have been inconsistent. Most studies have been evaluations of small geographic areas, with no national study in China. This study aimed to examine the acute BP responses to ambient PM 2.5 among the general population of Chinese adults. During 2012-2015, systolic and diastolic BP levels were obtained from a large national representative sample, the China Hypertension Survey database (n = 479,842). Daily PM 2.5 average exposures with a spatial resolution of 0.1° were estimated using a data assimilation that combines satellite measurements, air model simulations, and monitoring values. Overall, a 10-μg/m 3 increase in daily PM 2.5 was associated with a 0.035 (95% confidence interval: 0.020, 0.049) mmHg change in systolic BP and 0.001 (-0.008, 0.011) mmHg in diastolic BP after adjustments. Stratified by geographic regions, the systolic and diastolic BP levels varied from -0.050 (-0.109, 0.010) to 0.242 (0.176, 0.307) mmHg, and from -0.026 (-0.053, 0.001) to 0.051 (0.020, 0.082) mmHg, respectively. Statistically significant positive BP-PM 2.5 associations were only found in South and North China for systolic levels and in Southwest China for diastolic levels. We further explored the regional study population characteristics and exposure-response curves, and found that the geographic variations in BP-PM 2.5 associations were probably due to different population compositions or different PM 2.5 exposure levels. Our study provided national-level evidence on the associations between ambient PM 2.5 exposure and elevated BP levels. The magnitude of the estimated associations varied substantially by geographic location in China. CLINICAL TRIAL REGISTRATION: The Clinical trial registration name was Survey on prevalence of hypertension in China; the registration number was ChiCTR-ECS-14004641. http://www.chictr.org.cn/showproj.aspx?proj=4932., 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 B.V. All rights reserved.)

Long-term exposure to ambient fine particulate matter (PM 2.5 ) has been identified as a major contributor to disease burden in many countries, including China. The effects of long-term PM 2.5 exposure have been evaluated by risk assessment studies, which are based on an exposure-response function (ERF) derived from a specific epidemiological study or multiple studies. To explore whether generalization from the pre-established ERFs (including the integrated exposure-response [IER] model and the global exposure mortality model [GEMM]) introduces biases into risk assessment of a specific local population, we conducted the first census-based epidemiological study of PM 2.5 , aimed at the entire population of mainland China. Using a difference-in-difference analysis at the county level, we associated mortality changes from 2000 to 2010 to corresponding PM 2.5 changes, with adjustments made for multiple socioeconomic factors. Based on the epidemiological linkage between PM 2.5 and total mortality, we calculated the change in PM 2.5 -attributed deaths and compared this value with the results derived from the pre-established models (IER and GEMM). According to the epidemiological model, a 10-μg/m 3 increment in PM 2.5 was associated with a 4.3% (95% confidence interval [CI]: 1.9%-6.7%) increment in total mortality, and the change in PM 2.5 -attributed deaths from 2000 to 2010 was estimated as 561,000 (95% CI: 539,000-581,000). The census-based estimation was in better agreement with the GEMM results (545,000-612,000) than was the IER result (354,000 [95% CI: 286,000-421,000]). In sensitivity analyses of the epidemiological model, the association between PM 2.5 exposure and mortality was stronger among younger adults, consistent with the pre-established models. Due to the potential limitations of our findings, we cannot conclusively state that GEMM is more reliable than IER in China. Future studies are warranted to confirm or refute our findings., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Recent studies suggest that people with diabetes or who are at risk of developing diabetes, i.e. prediabetic (preDM), are potentially susceptible to air pollution, but the underlying mechanisms remain unclear because the existing epidemiological studies did not include healthy control groups and only focused on limited health outcomes. We hypothesized that acute exposure to ambient fine particles (PM 2.5 ) will lead to enhanced pulmonary and cardiometabolic changes in preDM than healthy individuals., Methods: We recruited 60 preDM and 60 healthy individuals from a community of 22,343 adults in Beijing China, and arranged each subject to complete up to seven repeated clinical visits with measures of 6 cardiopulmonary biomarkers, 6 cytokines, 4 blood pressure and endothelial function outcomes and 4 glucose metabolism biomarkers.. Moving averaged daily ambient PM 2.5 in preceding 1-14 days was matched to each subject and the PM 2.5 associated effect on multiple biomarkers was estimated and compared between PreDM and healthy subjects based on linear mixed effect model., Results: All the subjects exhibited significant acute elevation of exhaled nitric oxide, white blood cells, neutrophils, interleukin-1α, and glycated haemoglobin with increased exposure to PM 2.5 . PreDM subjects had significant stronger adverse changes compared to healthy subjects in 6 cardiometabolic biomarkers, namely, interleukin-2, interleukin-8, systolic and diastolic blood pressure, augmentation pressure, and glucose. The maximum elevation of these 6 biomarkers in PreDM subjects were 8.6% [CI: 4.1-13.3%], 10.0% [CI: 3.9-16.4%], 1.9% [CI: 0.2-3.6%], 1.2% [CI: - 0.1-2.4%], 5.7% [CI: - 0.1-11.8%], 2.4% [CI: 0.7-4.2%], respectively, per an interquartile increase of ambient PM 2.5 (61.4 μg m - 3 ) throughout the exposure window of the preceding 1-14 days. No significant difference was observed for the changes in pulmonary biomarkers between the two groups., Conclusions: PreDM individuals are more susceptible to the acute cardiometabolic effect of air pollution than the healthy individuals. A considerable public health burden can be inferred, given the high prevalence of prediabetes and the ubiquity of air pollution in China and worldwide.