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Wu P, Guo Q, Zhao Y, Bian M, Cao S, Zhang J(J, Duan X. Emerging concern on air pollution and health: Trade-off between air pollution exposure and physical activity. ECO-ENVIRONMENT & HEALTH 2024; 3:202-207. [PMID: 38655004 PMCID: PMC11035044 DOI: 10.1016/j.eehl.2024.01.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/03/2023] [Revised: 12/31/2023] [Accepted: 01/25/2024] [Indexed: 04/26/2024]
Abstract
Air pollution is a major contributor to the global disease burden, especially affecting respiratory and cardiovascular health. However, physical activity is associated with improved lung function, a slower decline in lung function, and lower mortality. The public is more likely to be exposed to air pollution during outdoor physical activity. However, studies on how long-term and short-term exposure to air pollution interacts with physical activity yield inconsistent results, and the thresholds for air pollution and physical activity remain unclear. Thus, more studies are needed to provide sufficient evidence to guide the public to safely engage in outdoor physical activity when exposed to air pollution.
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Affiliation(s)
- Pengpeng Wu
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
| | - Qian Guo
- China North Artificial Intelligence & Innovation Research Institute, Beiing 100072, China
- Collective Intelligence & Collaboration Laboratory, Beijing 100072, China
| | - Yuchen Zhao
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
| | - Mengyao Bian
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
| | - Suzhen Cao
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
| | - Junfeng (Jim) Zhang
- Nicholas School of the Environment and Global Health Institute, Duke University, Durham, NC 27708, USA
- Duke Kunshan University, Kunshan 215316, China
| | - Xiaoli Duan
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
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Su D, Chen L, Wang J, Zhang H, Gao S, Sun Y, Zhang H, Yao J. Long- and short-term health benefits attributable to PM 2.5 constituents reductions from 2013 to 2021: A spatiotemporal analysis in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 907:168184. [PMID: 37907103 DOI: 10.1016/j.scitotenv.2023.168184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 10/26/2023] [Accepted: 10/27/2023] [Indexed: 11/02/2023]
Abstract
Long- and short-term exposure to constituents of fine particulate matter (PM2.5) substantially affects human health. However, assessments of the health and economic benefits of reducing PM2.5 constituents are scarce. This study estimates the number of premature deaths from all-cause, cardiovascular (CVD), and respiratory diseases avoided due to reductions in daily and annual average concentrations of PM2.5 constituents. The Environmental Benefits Mapping and Analysis Program was used for two scenarios: we used yearly concentrations of PM2.5 constituents from 2013 to 2020 as the baseline concentration surface (Scenario I), and 2021 as the baseline year (Scenario II). With reductions in daily and annual average concentrations of PM2.5 constituents, 309,099 (95 % confidence interval [CI]: 37,265-571,485) and 195,297 (95 % CI: 178,192-211,914) premature deaths were avoided in Scenario I, respectively; meanwhile, 347,296 (95 % CI: 79,258-604,758) and 201,567 (95 % CI: 185,038-217,530) premature deaths were avoided in Scenario II, respectively. Moreover, economic benefits associated with the prevention of premature deaths were estimated using the willingness to pay (WTP) and modified human capital (AHC) methods. The total estimated economic benefits amounted to 563.32 billion RMB (WTP) and 322.03 billion RMB (AHC) in Scenario I. In Scenario II, the associated economic benefits were 751.48 billion RMB (WTP) and 427.56 billion RMB (AHC), accounting for 0.657 and 0.374 % of China's gross domestic product in 2021, respectively. Additionally, we analyzed the sensitivity of CVD-related premature deaths to the concentrations of PM2.5 constituents, and found that CVD-related premature deaths were more sensitive to black carbon.
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Affiliation(s)
- Die Su
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China
| | - Li Chen
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China.
| | - Jing Wang
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China
| | - Hui Zhang
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China
| | - Shuang Gao
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China
| | - Yanling Sun
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China
| | - Hu Zhang
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China
| | - Jiaqi Yao
- Academy of Eco-civilization Development for Jing-Jin-Ji Megalopolis, China
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Liu S, Zhao J, Ye X, Fu M, Zhang K, Wang H, Zou Y, Yu K. Fine particulate matter and its constituent on ovarian reserve: Identifying susceptible windows of exposure. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 904:166744. [PMID: 37659528 DOI: 10.1016/j.scitotenv.2023.166744] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2023] [Revised: 08/12/2023] [Accepted: 08/30/2023] [Indexed: 09/04/2023]
Abstract
BACKGROUND Little is known about the associations of exposure to fine particulate matter (PM2.5) and its constituents with ovarian reserve, and the potential susceptible window of exposure remains unclear. METHODS We performed a retrospective cohort study of 5189 women who attended a fertility center in Hubei, China, during 2019-2022, and estimated concentrations of PM2.5 and its major constituents during the development of follicles (4th-6th month [W1], 0-4th month [W2], 0-6th month [W3]) and 1-year before measurement (W4) based on Tracking Air Pollution in China database. We used multivariable linear regression and logistic regression models to examine the associations of PM2.5 and its constituent exposures with anti-Müllerian hormone (AMH), the preferred indicator of ovarian reserve. RESULTS We observed significantly decreased AMH levels associated with increasing PM2.5 concentrations, with the percent changes (95 % confidence intervals [CIs]) of 1.99 % (0.24 %-3.71 %) during W1 and 3.99 % (0.74 %-7.15 %) during W4 for per 10 μg/m3 increases in PM2.5.When PM2.5 exposure levels were equal to 50th percentile (32.6-42.3 μg/m3) or more, monotonically decreased AMH levels and increased risks of low AMH were seen with increasing PM2.5 concentrations during W1 and W4 (P < 0.05). Black carbon (BC), ammonium (NH4+), nitrate (NO3-), and organic matter (OM) during W1, and NH4+, NO3-, as well as sulfate (SO42-) during W4 were significantly associated with decreased AMH. Moreover, PM2.5 and SO42- exposures during W4 were positively associated with low AMH. Additionally, the associations were stronger among women aged <35 years, lived in urban regions, or measured AMH in cold-season (P for interaction <0.05). CONCLUSION PM2.5 and specific chemical components (particularly NH4+, NO3-, and SO42-) exposure during the secondary to antral follicle stage and 1-year before measurement were associated with diminished ovarian reserve (DOR), indicating the adverse impact of PM2.5 and its constituent exposures on female reproductive potential.
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Affiliation(s)
- Shuangyan Liu
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Jing Zhao
- Reproductive Medicine Center, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Xin Ye
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Mingjian Fu
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Kexin Zhang
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Han Wang
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yujie Zou
- Reproductive Medicine Center, Renmin Hospital of Wuhan University, Wuhan 430060, China.
| | - Kuai Yu
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
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Liu J, You Y, Liu R, Shen L, Wang D, Li X, Min L, Yin J, Zhang D, Ma X, Di Q. The joint effect and hemodynamic mechanism of PA and PM 2.5 exposure on cognitive function: A randomized controlled trial study. JOURNAL OF HAZARDOUS MATERIALS 2023; 460:132415. [PMID: 37657321 DOI: 10.1016/j.jhazmat.2023.132415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 08/24/2023] [Accepted: 08/25/2023] [Indexed: 09/03/2023]
Abstract
BACKGROUND While PM2.5 has been shown to impair cognitive function, physical activity (PA) is known to enhance it. Nonetheless, considering the increased inhalation of PM2.5 during exercise, the potential of PA to counteract the detrimental effects of PM2.5, along with the underlying hemodynamic mechanisms, remains uncertain. METHODS We conducted a double-blinded, randomized controlled trial among healthy young adults in Beijing, China. Ninety-three participants were randomly allocated to groups experiencing different intensities of PA interventions, and either subjected to purified or unpurified air conditions. Cognitive function was measured by the Color-Word Matching Stroop task, and the hemodynamic response was measured using functional near-infrared spectroscopy during participants performed the Stroop task both before and after the intervention. Linear mixed-effect models were used to estimate the impact of PA and PM2.5 on cognitive function and hemodynamic response. RESULTS The reaction time for congruent and incongruent Stroop tasks improved by - 80.714 (95% CI: -136.733, -24.695) and - 105.843 (95% CI: -188.6, -23.085) milliseconds after high-intensity interval training (HIIT) intervention. PM2.5 and HIIT had interaction effects on cognition, such that every 1 μg/m3 increase in PM2.5 attenuated the benefits of HIIT on reaction time by 2.231 (95% CI: 0.523, 3.938) and 3.305 (95% CI: 0.791, 5.819) milliseconds for congruent and incongruent Stroop tasks. Moreover, we divided participants into high and low PM2.5 exposure groups based on average PM2.5 concentration (32.980 μg/m3), and found that HIIT intervention in high PM2.5 concentration led to 69.897 (95% CI: 9.317, 130.476) and 99.269 (95% CI: 10.054, 188.485) milliseconds increased in the reaction time of congruent and incongruent Stroop, compared with the control group among low PM2.5. Furthermore, we found a significant interaction effects of PM2.5 and moderate-intensity continuous training (MICT) on the middle frontal gyrus (MFG) and dorsolateral superior frontal gyrus (DLPFC). PM2.5 and HIIT had a significant interaction effect on the DLPFC. CONCLUSIONS HIIT improved cognitive function, but the cognitive benefits of HIIT were attenuated or even reversed under high PM2.5 exposure. The activation of the DLPFC and MFG could serve as hemodynamic mechanisms to explain the joint effect of PA and PM2.5.
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Affiliation(s)
- Jianxiu Liu
- Vanke School of Public Health, Tsinghua University, Beijing 100084, China; Division of Sports Science and Physical Education, Tsinghua University, Beijing 100084, China
| | - Yanwei You
- Division of Sports Science and Physical Education, Tsinghua University, Beijing 100084, China
| | - Ruidong Liu
- Sports Coaching College, Beijing Sport University, Beijing 100084, China
| | - Lijun Shen
- School of Medicine, Tsinghua University, Beijing 100084, China
| | - Dizhi Wang
- Division of Sports Science and Physical Education, Tsinghua University, Beijing 100084, China
| | - Xingtian Li
- Division of Sports Science and Physical Education, Tsinghua University, Beijing 100084, China
| | - Leizi Min
- Division of Sports Science and Physical Education, Tsinghua University, Beijing 100084, China
| | - Jie Yin
- College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
| | - Dan Zhang
- Department of Psychology, Tsinghua University, Beijing 100084, China
| | - Xindong Ma
- Division of Sports Science and Physical Education, Tsinghua University, Beijing 100084, China; IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China.
| | - Qian Di
- Vanke School of Public Health, Tsinghua University, Beijing 100084, China; Institute for Healthy China, Tsinghua University, Beijing 100084, China.
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Liu J, Liu R, Zhang Y, Lao X, Mandeville KL, Ma X, Di Q. Leisure-time physical activity mitigated the cognitive effect of PM 2.5 and PM 2.5 components exposure: Evidence from a nationwide longitudinal study. ENVIRONMENT INTERNATIONAL 2023; 179:108143. [PMID: 37598596 DOI: 10.1016/j.envint.2023.108143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 06/30/2023] [Accepted: 08/10/2023] [Indexed: 08/22/2023]
Abstract
BACKGROUND Exposure to fine particulate matter (PM2.5) impairs cognition, while physical activity (PA) improves cognitive function. However, whether taking PA with PM2.5 exposure is still beneficial to cognition remains unknown. METHODS We utilized national representative longitudinal data from the China Family Panel Study (CFPS), comprising a total sample of 108,099 from 2010 to 2018 in three waves. Cognitive performance and leisure-time PA were measured using the standard cognitive module and Godin-Shephard Leisure-Time Physical Activity Questionnaire. Gridded overall PM2.5 and major chemical components of PM2.5 were estimated using a two-stage machine learning model and matched to each participant based on their residential location. Mixed-effect models and difference-in-difference models were employed to investigate the individual and joint effects of total PM2.5, PM2.5 components, and leisure-time PA on cognition. RESULTS Every 1 μg/m3 increase in PM2.5 was associated with a -0.035 (95% confidence interval [CI] = -0.052, -0.018) point change in cognitive score. All PM2.5 components exhibited negative associations with cognitive change, with black carbon (BC) contributing the most significant cognitive decline (β = -1.025, 95% CI = -1.367, -0.683). Every one-time (or one-hour) increase in leisure-time PA frequency (or PA time) per week was associated with an increase in cognitive score by 0.576 (0.270) points (PA frequency: 95% CI = 0.544, 0.608, PA time: 95% CI = 0.248, 0.293). PA frequency (β = -0.005, 95% CI = -0.006, -0.003) and PA time (β = -0.002, 95% CI = -0.003, -0.001) exhibited interactive effects with PM2.5. Increased PA frequency and time were more beneficial to cognitive function in the low PM2.5 exposure group compared to those exposed to high PM2.5 levels. Moreover, relative to lower PM2.5 exposure, the cognitive benefits of physically active individuals with higher PM2.5 exposure were attenuated but still improved cognition when compared to those with no PA. CONCLUSION Engaging in leisure-time PA provides cognitive benefits even under PM2.5 exposure, although PM2.5 exposure attenuates these benefits. Among all PM2.5 components, BC demonstrated the most significant cognitive hazard and interaction with leisure-time PA. Promoting PA as a preventive measure may offer a cost-effective and convenient strategy to mitigate the negative impact of PM2.5 exposure on cognition. There is no excuse to avoid PA under PM2.5 exposure, as its cognitive benefits persist even in polluted environments.
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Affiliation(s)
- Jianxiu Liu
- Vanke School of Public Health, Tsinghua University, Beijing 100084, China; Division of Sports Science and Physical Education, Tsinghua University, Beijing 100084, China.
| | - Ruidong Liu
- China Athletics College, Beijing Sport University, 100084, China.
| | - Yao Zhang
- Soochow College, Soochow University, Suzhou 215006, China.
| | - Xiangqian Lao
- Department of Biomedical Sciences, City University of Hong Kong, 999077, Hong Kong, China.
| | - Kate L Mandeville
- Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, United Kingdom.
| | - Xindong Ma
- Division of Sports Science and Physical Education, Tsinghua University, Beijing 100084, China; IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China.
| | - Qian Di
- Vanke School of Public Health, Tsinghua University, Beijing 100084, China; Institute for Healthy China, Tsinghua University, Beijing 100084, China.
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Cao M, Zheng C, Zhou H, Wang X, Chen Z, Zhang L, Cao X, Tian Y, Han X, Liu H, Liu Y, Xue T, Wang Z, Guan T. Air pollution attenuated the benefits of physical activity on blood pressure: Evidence from a nationwide cross-sectional study. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 262:115345. [PMID: 37572623 DOI: 10.1016/j.ecoenv.2023.115345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 08/04/2023] [Accepted: 08/06/2023] [Indexed: 08/14/2023]
Abstract
INTRODUCTION Although physical activity (PA) has multiple health benefits, the inhaled dose of fine particulate matter (PM2.5) during PA may increase. The trade-off between harmful effects of PM2.5 exposure and protective effects of PA remain unclear. Our study aims to examine the joint effects of PA and PM2.5 exposure on blood pressure (BP) in Chinese adults. METHODS A total of 203,108 adults aged ≥ 18 years from the China Hypertension Survey study (2012-2015) were included. Individual-level PA was assessed as minutes of metabolic equivalent tasks per week (MET-min/week). The average weekly PM2.5 exposures were estimated by using a spatial resolution of 10 km, integrating multiple data sources, including monitoring values, satellite measurements and model simulations. BP was measured with a professional portable BP monitor. Generalized linear regressions were used to estimate joint associations and to further explore two-dimensional nonlinear associations. RESULTS The median PA and 4-week PM2.5 average exposures were 3213.0 MET-min/week and 47.8 μg/m3, respectively. PA was negatively associated with BP, while PM2.5 exposure was positively with BP. The associations between PA and systolic BP were significantly modified by PM2.5 exposure (Pinteraction < 0.001). Compared with inactive participants under low PM2.5 exposure, those with highest level of PA under low PM2.5 exposure had a 0.90 (95 % CI: 0.53, 1.26) mmHg decrease in systolic BP, whereas they had a 0.48 (95 % CI: 0.07, 0.89) mmHg increase under high PM2.5 exposure. When PM2.5 exposure was approximately > 25 μg/m3, the joint exposure to total PA and PM2.5 was associated with an increase in systolic BP. CONCLUSIONS The benefits of PA on BP were counteracted by high PM2.5 levels.
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Affiliation(s)
- Man Cao
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Congyi Zheng
- Division of Prevention and Community Health, National Center for Cardiovascular Disease, National Clinical Research Center of Cardiovascular Disease, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Haoqi Zhou
- Division of Prevention and Community Health, National Center for Cardiovascular Disease, National Clinical Research Center of Cardiovascular Disease, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Xin Wang
- Division of Prevention and Community Health, National Center for Cardiovascular Disease, National Clinical Research Center of Cardiovascular Disease, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Zuo Chen
- Division of Prevention and Community Health, National Center for Cardiovascular Disease, National Clinical Research Center of Cardiovascular Disease, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Linfeng Zhang
- Division of Prevention and Community Health, National Center for Cardiovascular Disease, National Clinical Research Center of Cardiovascular Disease, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Xue Cao
- Division of Prevention and Community Health, National Center for Cardiovascular Disease, National Clinical Research Center of Cardiovascular Disease, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Yixin Tian
- Division of Prevention and Community Health, National Center for Cardiovascular Disease, National Clinical Research Center of Cardiovascular Disease, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Xueyan Han
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Hengyi Liu
- Institute of Reproductive and Child Health/National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Yuanli Liu
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Tao Xue
- Institute of Reproductive and Child Health/National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Zengwu Wang
- Division of Prevention and Community Health, National Center for Cardiovascular Disease, National Clinical Research Center of Cardiovascular Disease, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
| | - Tianjia Guan
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
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Huang W, Zhou Y, Chen X, Zeng X, Knibbs LD, Zhang Y, Jalaludin B, Dharmage SC, Morawska L, Guo Y, Yang X, Zhang L, Shan A, Chen J, Wang T, Heinrich J, Gao M, Lin L, Xiao X, Zhou P, Yu Y, Tang N, Dong G. Individual and joint associations of long-term exposure to air pollutants and cardiopulmonary mortality: a 22-year cohort study in Northern China. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2023; 36:100776. [PMID: 37547049 PMCID: PMC10398602 DOI: 10.1016/j.lanwpc.2023.100776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 04/11/2023] [Accepted: 04/14/2023] [Indexed: 08/08/2023]
Abstract
Background Evidence on the associations between long-term exposure to multiple air pollutants and cardiopulmonary mortality is limited, especially for developing regions with higher pollutant levels. We aimed to characterise the individual and joint (multi-pollutant) associations of long-term exposure to air pollutants with cardiopulmonary mortality, and to identify air pollutant that primarily contributes to the mortality risk. Methods We followed 37,442 participants with a mean age of 43.5 years in four cities in northern China (Tianjin, Shenyang, Taiyuan, and Rizhao) from January 1998 to December 2019. Annual particulate matter (PM) with diameters ≤2.5 μm (PM2.5), ≤10 μm (PM10), sulfur dioxide (SO2) and nitrogen dioxide (NO2) were estimated using daily average values from satellite-derived machine learning models and monitoring stations. Time-varying Cox proportional hazards model was used to evaluate the individual association between air pollutants and mortality from non-accidental causes, cardiovascular diseases (CVDs), non-malignant respiratory diseases (RDs) and lung cancer, accounting for demographic and socioeconomic factors. Effect modifications by age, sex, income and education level were also examined. Quantile-based g-Computation integrated with time-to-event data was additionally applied to evaluate the co-effects and the relative weight of contributions for air pollutants. Findings During 785,807 person-years of follow-up, 5812 (15.5%) died from non-accidental causes, among which 2932 (7.8%) were from all CVDs, 479 (1.3%) from non-malignant RDs, and 552 (1.4%) from lung cancer. Long-term exposure to PM10 (mean [baseline]: 136.5 μg/m3), PM2.5 (mean [baseline]: 70.2 μg/m3), SO2 (mean [baseline]: 113.0 μg/m3) and NO2 (mean [baseline]: 39.2 μg/m3) were adversely and consistently associated with all mortality outcomes. A 10 μg/m3 increase in PM2.5 was associated with higher mortality from non-accidental causes (hazard ratio 1.20; 95% confidence interval 1.17-1.23), CVDs (1.23; 1.19-1.28), non-malignant RDs (1.37; 1.25-1.49) and lung cancer (1.14; 1.05-1.23). A monotonically increasing curve with linear or supra-linear shape with no evidence of a threshold was observed for the exposure-response relationship of mortality with individual or joint exposure to air pollutants. PM2.5 consistently contributed most to the elevated mortality risks related to air pollutant mixture, followed by SO2 or PM10. Interpretation There was a strong and positive association of long-term individual and joint exposure to PM10, PM2.5, SO2, and NO2 with mortalities from non-accidental causes, CVDs, non-malignant RDs and lung cancer in high-exposure settings, with PM2.5 potentially being the main contributor. The shapes of associations were consistent with a linear or supra-linear exposure-response relationship, with no lower threshold observed within the range of concentrations in this study. Funding National Key Research and Development Program of China, the China Scholarship Council, the National Natural Science Foundation of China, Natural Science Foundation of Guangdong Province.
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Affiliation(s)
- Wenzhong Huang
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yang Zhou
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Environmental Protection, Guangzhou 510655, China
| | - Xi Chen
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Tianjin 300070, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin 300070, China
| | - Xiaowen Zeng
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Luke D. Knibbs
- Faculty of Medicine and Health, School of Public Health, The University of Sydney, NSW 2006, Australia
- Public Health Research Analytics and Methods for Evidence, Public Health Unit, Sydney Local Health District, Camperdown, NSW 2050, Australia
| | - Yunting Zhang
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Bin Jalaludin
- Centre for Air Quality and Health Research and Evaluation, Glebe, NSW 2037, Australia
- Ingham Institute for Applied Medial Research, Liverpool, NSW 2170, Australia
- School of Public Health and Community Medicine, The University of New South Wales, Kensington, NSW 2052, Australia
| | - Shyamali C. Dharmage
- Allergy and Lung Health Unit, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC 3052, Australia
| | - Lidia Morawska
- International Laboratory for Air Quality and Health, Queensland University of Technology, Brisbane, QLD 4001, Australia
| | - Yuming Guo
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Xueli Yang
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Tianjin 300070, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin 300070, China
| | - Liwen Zhang
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Tianjin 300070, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin 300070, China
| | - Anqi Shan
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Tianjin 300070, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin 300070, China
| | - Jie Chen
- Department of Occupational and Environmental Health, School of Public Health, China Medical University, Shenyang 110122, China
| | - Tong Wang
- School of Public Health, Shanxi Medical University, Taiyuan 030001, China
| | - Joachim Heinrich
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, Munich 80336, Germany
| | - Meng Gao
- Department of Geography, Hong Kong Baptist University, Hong Kong SAR, China
| | - Lizi Lin
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Xiang Xiao
- Department of Geography, Hong Kong Baptist University, Hong Kong SAR, China
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Peien Zhou
- Department of Public Health & Primary Care, University of Cambridge, Cambridge CB2 1TN, United Kingdom
| | - Yunjiang Yu
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Environmental Protection, Guangzhou 510655, China
| | - Naijun Tang
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China
| | - Guanghui Dong
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
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8
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Jiang H, Zhang S, Yao X, Meng L, Lin Y, Guo F, Yang D, Jin M, Wang J, Tang M, Chen K. Does physical activity attenuate the association between ambient PM 2.5 and physical function? THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 874:162501. [PMID: 36863583 DOI: 10.1016/j.scitotenv.2023.162501] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 02/21/2023] [Accepted: 02/23/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Physical function (PF), such as muscle strength, performing daily activities, has gradually declined with the increase of age, causing the occurrence of disability and diseases burden. Air pollution exposure and physical activity (PA) were both linked to PF. We aimed to explore the individual and joint effects of particulate matter <2.5 μm (PM2.5) and PA on PF. METHODS A total of 4537 participants and 12,011 observations aged ≥45 years old from the China Health and Retirement Longitudinal Study (CHARLS) cohort from 2011 to 2015 were included into the study. PF was assessed by a combined score of four tests, including grip strength, walking speed, sense of balance, and chair standing tests. Air pollution exposure data was from The ChinaHighAirPollutants (CHAP) dataset. The annual PM2.5 exposure for each individual was estimated based on county-level resident addresses. We estimated the volume of moderate-to-vigorous physical activity (MVPA) by quoting metabolic equivalent (MET). Multivariate linear model was conducted for baseline analysis, and linear mixed model with random participant intercepts was constructed for cohort longitudinal analysis. RESULTS PM2.5 was negatively associated with PF, while PA was positively associated with PF in baseline analysis. In cohort longitudinal analysis, a 10 μg/m3 increase in PM2.5 was associated to a 0.025 point (95 % CI: -0.047, -0.003) decrease in PF score, and a 10-MET-h/week increase in PA was related to a 0.004 point (95 % CI: 0.001, 0.008) increase in PF score. The association between PM2.5 and PF decreased by increased PA intensity, and PA reversed the detrimental effects between PM2.5 and PF. CONCLUSION PA attenuated the association of air pollution with PF at both high and low levels of air pollution, implying that PA may be an effective behavior to reduce the adverse effects of poor air quality on PF.
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Affiliation(s)
- Haiyan Jiang
- Department of Public Health, Fourth Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Simei Zhang
- Department of Public Health, Fourth Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Xuecheng Yao
- Department of Public Health, Fourth Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Lin Meng
- Department of Public Health, Fourth Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Yaoyao Lin
- Department of Public Health, Fourth Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Fanjia Guo
- Department of Public Health, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Dandan Yang
- Department of Public Health, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Mingjuan Jin
- Department of Public Health, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Jianbing Wang
- Department of Public Health, National Clinical Research Center for Child Health of Children's Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Mengling Tang
- Department of Public Health, Fourth Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China.
| | - Kun Chen
- Department of Public Health, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China.
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9
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Guo Q, Zhao Y, Xue T, Zhang J, Duan X. Association of PM 2.5 and Its Chemical Compositions with Metabolic Syndrome: A Nationwide Study in Middle-Aged and Older Chinese Adults. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph192214671. [PMID: 36429390 PMCID: PMC9690751 DOI: 10.3390/ijerph192214671] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 10/30/2022] [Accepted: 11/05/2022] [Indexed: 05/28/2023]
Abstract
Studies on the association of PM2.5 and its compositions with metabolic syndrome (MetS) were limited, and it was unclear which was the most hazardous composition. In this study, we aimed to investigate the association between PM2.5 and its compositions with MetS and identified the most hazardous composition. In this study, we included 13,418 adults over 45 years across 446 communities from 150 counties of 28 provinces in nationwide China in 2015. MetS was defined based on the five indicators of the Joint Interim Societies, including: blood pressure (SBP (systolic blood pressure) and DBP (diastolic blood pressure)); fasting blood glucose (FBG); fasting triglyceride (FTG); high density lipoprotein cholesterol (HDL-C); and waist circumference (WC). We used chemical transport models to estimate the concentration of PM2.5 and its compositions, including black carbon, ammonium, nitrate, organic matter, and sulfate. We used a generalized linear regression model to examine the association of PM2.5 and its compositions with MetS. In this study, we observed that the average age was 61.40 (standard deviation (SD): 9.59). Each IQR (29.76 μg/m3) increase in PM2.5 was associated with a 1.27 (95% CI: 1.17, 1.37) increase in the odds for MetS. We indicated that black carbon showed stronger associations than other compositions. The higher associations were observed among women, participants aged less than 60 years, who lived in urban areas and in the Northeast, smokers, drinkers, and the obese populations. In conclusion, our findings identified the most harmful composition and sensitive populations and regions that required attention, which would be helpful for policymakers.
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Affiliation(s)
- Qian Guo
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
| | - Yuchen Zhao
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
| | - Tao Xue
- Institute of Reproductive and Child Health/Ministry of Health Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100083, China
| | - Junfeng Zhang
- Nicholas School of the Environment and Global Health Institute, Duke University, Durham, NC 27708, USA
- Duke Kunshan University, Kunshan 215316, China
| | - Xiaoli Duan
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
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