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Although studies have estimated the associations of PM 2.5 with total mortality or cardiopulmonary mortality, few have comprehensively examined cause-specific mortality risk and burden caused by ambient PM 2.5 . Thus, this study investigated the association of short-term exposure to PM 2.5 with cause-specific mortality using a death-spectrum wide association study (DWAS). Individual information of 5,450,764 deaths during 2013-2018 were collected from six provinces in China. Daily PM 2.5 concentration in the case and control days were estimated by a random forest model. A time-stratified case-crossover study design was applied to estimate the associations (access risk, ER) of PM 2.5 with cause-specific mortality, which was then used to calculate the population-attributable fraction (PAF) of mortality and the corresponding mortality burden caused by PM 2.5 . Each 10 μg/m 3 increase in PM 2.5 concentration (lag03) was associated with a 0.80 % [95 % confidence interval (CI): 0.73 %, 0.86 %] rise in total mortality. We found greater mortality effect at PM 2.5 concentrations < 50 μg/m 3 . Stratified analyses showed greater ERs in females (1.01 %, 95 %CI: 0.91 %, 1.11 %), children ≤ 5 years (2.17 %, 95 %CI: 0.85 %, 3.51 %), and old people ≥ 70 years. We identified 33 specific causes (level 2) of death which had significant associations with PM 2.5 , including 16 circulatory diseases, 9 respiratory diseases, and 8 other causes. The PAF estimated based on the overall association between PM 2.5 and total mortality was 3.16 % (95 %CI: 2.89 %, 3.40 %). However, the PAF was reduced to 2.88 % (95 %CI: 1.88 %, 3.81 %) using the associations of PM 2.5 with 33 level 2 causes of death, based on which 250.15 (95 %CI: 163.29, 330.93) thousand deaths were attributable to short-term PM 2.5 exposure across China in 2019. Overall, this study provided a comprehensive picture on the death-spectrum wide association between PM 2.5 and morality in China. We observed robust positive cause-specific associations of PM 2.5 with mortality risk, which may provide more precise basis in assessing the mortality burden of 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 Inc. All rights reserved.)

Background: Particulate matter (PM) pollution is a well-known risk factor of stroke. However, little is known about the association between PM 1 (aerodynamic diameter ≤ 1.0 μm) and stroke. We estimated the associations of short-term exposure to PM 1 with hospital admission and recurrence of stoke in China., Methods: Stroke data were derived from the Chinese Stroke Center Alliance (CASA) program conducted in 1458 hospitals in 292 Chinese cities from 2015 to 2019. Daily air pollution and meteorological data were collected in the cities where studied hospitals were located. Daily PM 1 concentration was estimated by a generalized additive model (GAM) using PM 2.5 and meteorological variables. A time-stratified case-crossover design was applied to estimate the associations of short-term exposure to PM 1 with hospital admission of stroke. A GAM model was used to estimate the association between average PM 1 exposure during hospitalization and the recurrence of stroke., Results: A total of 989,591 stroke cases were included in the study. Each 10 μg/m 3 increase in PM 1 (lag06-day) was associated with a 0.53% (95%CI, 0.39%, 0.67%) increment in hospital admission for stroke. The adverse effects of PM 1 on ischemic stroke was stronger than on intracerebral hemorrhage. We found the associations were significant in Northeast (0.94%, 95%CI, 0.51%, 1.38%), North (0.47%, 95%CI, 0.20%, 0.75%), Central (0.57%, 95%CI, 0.30%, 0.85%), and East China (0.63%, 95%CI, 0.27%, 0.99%). Of all stroke cases, 62,988 (6.4%) had recurrent stoke attack during their hospitalization. Each 10 μg/m 3 increase in PM 1 was associated with a 1.64% (95%CI, 1.28%, 2.01%) increment in recurrence of stroke during hospitalization., Conclusions: Short-term exposure to PM 1 may increase the risk of incidence and recurrence of stroke in China, and the effects varied across different types of stroke and regions. Geographically targeted strategies and measures are needed to control air pollution for reducing the burden of stroke from PM 1 ., 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. Published by Elsevier B.V.)

Although strict lockdown measurements implemented during the COVID-19 pandemic have dramatically reduced the anthropogenic-based emissions, changes in air quality and its health impacts remain unclear in China. We comprehensively described air pollution during and after the lockdown periods in 2020 compared with 2018-2019, and estimated the mortality burden indicated by the number of deaths and years of life lost (YLL) related to the air pollution changes. The mean air quality index (AQI), PM 10 , PM 2.5 , NO 2 , SO 2 and CO concentrations during the lockdown across China declined by 18.2 (21.2%), 27.0 μg/m 3 (28.9%), 10.5 μg/m 3 (18.3%), 8.4 μg/m 3 (44.2%), 13.1 μg/m 3 (38.8%), and 0.3 mg/m 3 (27.3%) respectively, when compared to the same periods during 2018-2019. We observed an increase in O 3 concentration during the lockdown by 5.5 μg/m 3 (10.4%), and a slight decrease after the lockdown by 3.4 μg/m 3 (4.4%). As a result, there were 51.3 (95%CI: 32.2, 70.1) thousand fewer premature deaths (16.2 thousand during and 35.1 thousand after the lockdown), and 1066.8 (95%CI: 668.7, 1456.8) thousand fewer YLLs (343.3 thousand during and 723.5 thousand after the lockdown) than these in 2018-2019. Our findings suggest that the COVID-19 lockdown has caused substantial decreases in air pollutants except for O 3 , and that substantial human health benefits can be achieved when strict control measures for air pollution are taken to reduce emissions from vehicles and industries. Stricter tailored policy solutions of air pollution are urgently needed in China and other countries, especially in well-developed industrial regions, such as upgrading industry structure and promoting green transportation., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background: Previous studies have demonstrated the embryotoxicity and fetotoxicity of thallium (Tl). However, the effects of prenatal exposure to Tl on birth weight and placental weight and the mediating role of placental weight in the association of Tl with birth weight remain unclear. Methods: We recruited 2,748 participants from the ongoing Prenatal Environment and Offspring Health Cohort (PEOH Cohort) study, which was initiated in 2016 in Guangzhou, China. The Tl concentrations in maternal urine samples collected during the first and third trimester were determined by inductively coupled plasma mass spectrometry. Birth weight and placental weight were extracted from maternal medical records. Results: Pregnant women exposed to the highest tertile of Tl in the first trimester (β = -42.7 g, 95% CI: -82.3, -3.1 g) and third trimester (β = -50.6 g, 95% CI: -99.0, -2.3 g) had babies with lower birth weights than those exposed to the lowest tertile. We also found significant negative associations of exposure to Tl concentrations in the first and third trimester with placental weight. Mediation analyses showed that 50.3% (95% CI: 15.9, 79.2%) and 33.5% (95% CI: 1.3, 80.3%) of the effects of Tl exposure in the first and third trimester on birth weight were mediated by decreased placental weight. Conclusion: Our results suggest that prenatal exposure to Tl is negatively associated with birth weight and that this association may be mediated by decreased placental weight., 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 © 2021 Zhou, Sun, Wang, Ye, Chen, Chen, He, Wang, Liu, Dong, Chen, Chen, Yuan, Xiao, Hu, Zeng, Rong, Zhang, Zhou, Guo, Lv, Fan, Pu, Ma, Zhang and Liu.)