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Tan Q, Zhou M, You X, Ma J, Ye Z, Shi W, Cui X, Mu G, Yu L, Chen W. Association of ambient ozone exposure with early cardiovascular damage among general urban adults: A repeated-measures cohort study in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 957:177380. [PMID: 39505024 DOI: 10.1016/j.scitotenv.2024.177380] [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: 04/23/2024] [Revised: 10/21/2024] [Accepted: 11/02/2024] [Indexed: 11/08/2024]
Abstract
Longitudinal evidence of long-term ozone exposure on heart rate variability (HRV, an early indicator of cardiovascular damage) is lacking and the potential mechanism remains largely unclear. Our objectives were to evaluate the cross-sectional and longitudinal associations of ozone exposure with HRV alteration, and the potential roles of protein carbonyl (PC, biomarker of oxidative protein damage) and transforming growth factor (TGF)-β1 in this association. This repeated-measures prospective study included 4138 participants with 6617 observations from the Wuhan-Zhuhai cohort. Ozone concentrations were estimated using a high temporospatial resolution model for each participant. HRV indices, PC, and TGF-β1 were also repeatedly measured. Cross-sectional and longitudinal relationships of ozone exposure with HRV alteration were evaluated by linear mixed model. Cross-sectionally, the strongest lag effect of each 10 ppb increment in short-term ozone exposure showed a 12.40 %, 8.47 %, 4.31 %, 8.03 %, 3.69 %, and 2.41 % decrement on very low frequency (VLF, lag 3 weeks), LF (lag 2 weeks), high frequency (HF, lag 0-7 days), total power (TP, lag 2 weeks), standard deviation of all normal-to-normal intervals (SDNN, lag 3 weeks), and square root of the mean squared difference between adjacent normal-to-normal intervals (lag 2 weeks), respectively. Longitudinally, each 10 ppb increment of annual average ozone was related with an annual change rate of -0.024 ms2/year in VLF, -0.009 ms2/year in LF, -0.013 ms2/year in HF, -0.014 ms2/year in TP, and -0.004 ms/year in SDNN. Mediation analyses indicated that PC mediated 20.77 % and 12.18 % of ozone-associated VLF and TP decline, respectively; TGF-β1 mediated 16.87 % and 27.78 % of ozone-associated VLF and SDNN reduction, respectively. Our study demonstrated that ozone exposure was cross-sectionally and longitudinally related with HRV decline in general Chinese urban adults, and oxidative protein damage and increased TGF-β1 partly mediated ozone exposure-related HRV reduction.
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Affiliation(s)
- Qiyou Tan
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Institute of Occupational Health and Radiation Protection, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang 310051, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Min Zhou
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Xiaojie You
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Jixuan Ma
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Zi Ye
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Wendi Shi
- Lucy Cavendish College, University of Cambridge, Cambridge CB3 0BU, UK
| | - Xiuqing Cui
- Institute of Health Surveillance Analysis and Protection, Hubei Provincial Center for Disease Control and Prevention, Wuhan, Hubei 430079, China
| | - Ge Mu
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Data Center, Medical Affairs Department, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi 710068, China
| | - Linling Yu
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Weihong Chen
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China.
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Nan N, Liu Y, Yan Z, Zhang Y, Li S, Zhang J, Qin G, Sang N. Ozone induced multigenerational glucose and lipid metabolism disorders in Drosophila. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 951:175477. [PMID: 39151609 DOI: 10.1016/j.scitotenv.2024.175477] [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: 06/19/2024] [Revised: 08/10/2024] [Accepted: 08/10/2024] [Indexed: 08/19/2024]
Abstract
Ozone (O3), a persistent pollutant, poses a significant health threat. However, research on its multigenerational toxicity remains limited. Leveraging the Drosophila model with its short lifespan and advanced genetic tools, we explored the effects of O3 exposure across three generations of fruit flies. The findings revealed that O3 disrupted motility, body weight, stress resistance, and oxidative stress in three generations of flies, with varying effects observed among them. Transcriptome analysis highlighted the disruption of glucose metabolism-related pathways, encompassing gluconeogenesis/glycolysis, galactose metabolism, and carbon metabolism. Hub genes were identified, and RT-qPCR results indicated that O3 decreased their transcription levels. Comparative analysis of their human orthologs was conducted using Comparative Toxicogenomics Database (CTD) and DisGeNET databases. These genes are linked to various metabolic diseases, including diabetes, hypoglycemia, and obesity. The trehalose content was reduced in F0 generation flies but increased in F1-F2 generations after O3 exposure. While the trehalase and glucose levels were decreased across F0-F2 generations. TAG synthesis-related genes were significantly upregulated in F0 generation flies but downregulated in F1-F2 generations. The expression patterns of lipolysis-related genes varied among the three generations of flies. Food intake was increased in F0 generation flies but decreased in F1-F2 generations. Moreover, TAG content was significantly elevated in F0 generation flies by O3 exposure, while it was reduced in F2 generation flies. These differential effects of O3 across three generations of flies suggest a metabolic reprogramming aimed at mitigating the damage caused by O3 to flies. The study affirms the viability of employing the Drosophila model to investigate the mechanisms underlying O3-induced glucose and lipid metabolism disorders while emphasizing the importance of studying the long-term health effects of O3 exposure. Moreover, this research highlights the Drosophila model as a viable tool for investigating the multigenerational effects of pollutants, particularly atmospheric pollutants.
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Affiliation(s)
- Nan Nan
- College of Environment and Resource, Research Center of Environment and Health, Shanxi University, Shanxi 030006, PR China
| | - Yuntong Liu
- College of Environment and Resource, Research Center of Environment and Health, Shanxi University, Shanxi 030006, PR China
| | - Zhipeng Yan
- College of Environment and Resource, Research Center of Environment and Health, Shanxi University, Shanxi 030006, PR China
| | - Yaru Zhang
- College of Environment and Resource, Research Center of Environment and Health, Shanxi University, Shanxi 030006, PR China
| | - Shiya Li
- College of Environment and Resource, Research Center of Environment and Health, Shanxi University, Shanxi 030006, PR China
| | - Jianqin Zhang
- School of Life Science, Shanxi University, Shanxi 030006, PR China
| | - Guohua Qin
- College of Environment and Resource, Research Center of Environment and Health, Shanxi University, Shanxi 030006, PR China.
| | - Nan Sang
- College of Environment and Resource, Research Center of Environment and Health, Shanxi University, Shanxi 030006, PR China
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Chen X, Jiang Z, Shen Y, Wang S, Shindell D, Zhang Y. Ozone Mortality Burden Changes Driven by Population Aging and Regional Inequity in China in 2013-2050. GEOHEALTH 2024; 8:e2024GH001058. [PMID: 39086930 PMCID: PMC11286545 DOI: 10.1029/2024gh001058] [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: 03/31/2024] [Revised: 07/10/2024] [Accepted: 07/10/2024] [Indexed: 08/02/2024]
Abstract
Air pollution exposure is closely linked to population age and socioeconomic status. Population aging and imbalance in regional economy are thus anticipated to have important implications on ozone (O3)-related health impacts. Here we provide a driver analysis for O3 mortality burden due to respiratory disease in China over 2013-2050 driven by population aging and regional inequity. Unexpectedly, we find that population aging is estimated to result in dramatic rises in annual O3 mortality burden in China; by 56, 101-137, and 298-485 thousand over the periods 2013-2020, 2020-2030, and 2030-2050, respectively. This reflects the exponential rise in baseline mortality rates with increasing age. The aging-induced mortality burden rise in 2030-2050 is surprisingly large, as it is comparable to the net national mortality burden due to O3 exposure in 2030 (359-399 thousand yr-1). The health impacts of O3 pollution, shown as mortality burden per capita, are inequitably distributed, with more severe effects in less developed provinces than their developed counterparts by 23.1% and 21.5% in 2019 and 2030, respectively. However, the regional inequity in O3 mortality burden is expected to be mitigated in 2050. This temporal variation reflects evolving demographic dividend characterized by a larger proportion of younger individuals in developed regions. These findings are critical for targeted improvement of healthcare services to ensure the sustainability of social development.
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Affiliation(s)
- Xiaokang Chen
- School of Earth and Space SciencesUniversity of Science and Technology of ChinaHefeiChina
| | - Zhe Jiang
- School of Earth and Space SciencesUniversity of Science and Technology of ChinaHefeiChina
| | - Yanan Shen
- School of Earth and Space SciencesUniversity of Science and Technology of ChinaHefeiChina
| | - Shuxiao Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution ControlSchool of EnvironmentTsinghua UniversityBeijingChina
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution ComplexBeijingChina
| | - Drew Shindell
- Nicholas School of the EnvironmentDuke UniversityDurhamNCUSA
| | - Yuqiang Zhang
- Big Data Research Center for Ecology and EnvironmentShandong UniversityQingdaoChina
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Li S, Wang S, Wu Q, Zhao B, Jiang Y, Zheng H, Wen Y, Zhang S, Wu Y, Hao J. Integrated Benefits of Synergistically Reducing Air Pollutants and Carbon Dioxide in China. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024. [PMID: 39086301 DOI: 10.1021/acs.est.4c00599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/02/2024]
Abstract
China's advancements in addressing air pollution and reducing CO2 emissions offer valuable lessons for collaborative strategies to achieve diverse environmental objectives. Previous studies have assessed the mutual benefits of climate policies and air pollution control measures on one another, lacking an integrated assessment of the benefits of synergistic control attributed to refined measures. Here, we comprehensively used coupled emission inventory and response models to evaluate the integrated benefits and synergy degrees of various measures in reducing air pollutants and CO2 in China during 2013-2021. Results indicated that the implemented measures yielded integrated benefits value at 6.7 (2.4-12.6) trillion Chinese Yuan. The top five contributors, accounting for 55%, included promoting non-thermal power, implementing end-of-pipe control technologies in power plants and iron and steel industry, replacing residential scattered coal, and saving building energy. Measures demonstrating high synergies and integrated benefits per unit of reduction (e.g., green traffic promotion) yielded low benefits mainly due to their low application, which are expected to gain greater implementation and prioritization in the future. Our findings provide insights into the effectiveness and limitations of strategies aimed at joint control. By ranking these measures based on their benefits and synergy, we offer valuable guidance for policy development in China and other nations with similar needs.
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Affiliation(s)
- Shengyue Li
- School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Shuxiao Wang
- School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Qingru Wu
- School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Bin Zhao
- School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Yueqi Jiang
- School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Haotian Zheng
- School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Yifan Wen
- School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Shaojun Zhang
- School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Ye Wu
- School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Jiming Hao
- School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
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Liu M, Zeeshan M, Sun T, Hu X, Nie Z, Dong H, Dong G, Ou Y. Association of Air Quality Improvement and Frailty Progression: A National Study across China. TOXICS 2024; 12:464. [PMID: 39058116 PMCID: PMC11280498 DOI: 10.3390/toxics12070464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2024] [Revised: 06/22/2024] [Accepted: 06/23/2024] [Indexed: 07/28/2024]
Abstract
Accumulating evidence strongly suggests that exposure to ambient air pollution is linked with increased frailty. However, little is known about the effect of improved air quality on frailty progression. We aimed to investigate whether improvements in air quality (PM1, PM2.5, PM10, NO2, and O3) can alleviate frailty progression, particularly in the aftermath of implementation of the "Clean Air Action" policy in China. The study involved 12,891 participants with geocoded environmental data from the nationwide China Health and Retirement Longitudinal Study (CHARLS) during the period from May 2011 to August 2015. Multivariate logistic regression models were used to analyze the association of air pollution improvements and frailty progression. The protective effects were noted for PM1, PM2.5, PM10, and NO2 indices, with an aOR (adjusted odds ratio) ranging from 0.72 to 0.79. Air quality improvement in PM1, PM2.5, PM10, and NO2 could alleviate the progression of frailty. The study is the first to examine the association between the improvement of air quality and the progression of frailty, setting a precedent for the importance of a nationwide clean air policy and its impact on healthy ageing.
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Affiliation(s)
- Mingqin Liu
- Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China;
| | - Mohammed Zeeshan
- Department of Biochemistry and Structural Biology, University of Texas Health San Antonio, San Antonio, TX 78229, USA;
| | - Tiantian Sun
- Department of Hematology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen 518000, China;
| | - Xiangming Hu
- Department of Cardiology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou 510080, China; (X.H.); (Z.N.); (H.D.)
| | - Zhiqiang Nie
- Department of Cardiology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou 510080, China; (X.H.); (Z.N.); (H.D.)
| | - Haojian Dong
- Department of Cardiology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou 510080, China; (X.H.); (Z.N.); (H.D.)
| | - 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
| | - Yanqiu Ou
- Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China;
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Sun F, Gong X, Wei L, Zhang Y, Ge M, Xiong L. Assessing the impact of short-term ozone exposure on excess deaths from cardiovascular disease: a multi-pollutant model in Nanjing, China's Yangtze River Delta. Front Public Health 2024; 12:1353384. [PMID: 38939565 PMCID: PMC11208627 DOI: 10.3389/fpubh.2024.1353384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Accepted: 06/03/2024] [Indexed: 06/29/2024] Open
Abstract
Background Ozone pollution is associated with cardiovascular disease mortality, and there is a high correlation between different pollutants. This study aimed to assess the association between ozone and cardiovascular disease deaths and the resulting disease burden in Nanjing, China. Methods A total of 151,609 deaths from cardiovascular disease were included in Nanjing, China from 2013 to 2021. Daily data on meteorological and air pollution were collected to apply a generalized additional model with multiple pollutants to perform exposure-response analyses, stratification analysis, and evaluation of excess deaths using various standards. Results In the multi-pollutant model, an increase of 10 μg/m3 in O3 was significantly associated with a 0.81% (95%CI: 0.49, 1.12%) increase in cardiovascular disease deaths in lag05. The correlation weakened in both the single-pollutant model and two-pollutant models, but remained more pronounced in females, the older group, and during warm seasons. From 2013 to 2021, the number of excess deaths attributed to ozone exposure in cardiovascular disease continued to rise with an increase in ozone concentration in Nanjing. If the ozone concentration were to be reduced to the WHO standard and the minimum level, the number of deaths would decrease by 1,736 and 10,882, respectively. Conclusion The risk of death and excess deaths from cardiovascular disease due to ozone exposure increases with higher ozone concentration. Reducing ozone concentration to meet WHO standards or lower can provide greater cardiovascular disease health benefits.
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Affiliation(s)
| | | | | | | | | | - Liling Xiong
- Department of Environment Health, Nanjing Municipal Center for Disease Control and Prevention, Nanjing, China
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Guo LH, Zeeshan M, Huang GF, Chen DH, Xie M, Liu J, Dong GH. Influence of Air Pollution Exposures on Cardiometabolic Risk Factors: a Review. Curr Environ Health Rep 2023; 10:501-507. [PMID: 38030873 DOI: 10.1007/s40572-023-00423-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/20/2023] [Indexed: 12/01/2023]
Abstract
PURPOSE OF REVIEW The increasing prevalence of cardiometabolic risk factors (CRFs) contributes to the rise in cardiovascular disease. Previous research has established a connection between air pollution and both the development and severity of CRFs. Given the ongoing impact of air pollution on human health, this review aims to summarize the latest research findings and provide an overview of the relationship between different types of air pollutants and CRFs. RECENT FINDINGS CRFs include health conditions like diabetes, obesity, hypertension etc. Air pollution poses significant health risks and encompasses a wide range of pollutant types, air pollutants, such as particulate matter (PM), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O2). More and more population epidemiological studies have shown a positive correlation between air pollution and CRFs. Although various pollutants have diverse effects on specific cellular molecular pathways, their main influence is on oxidative stress, inflammation response, and impairment of endothelial function. More and more studies have proved that air pollution can promote the occurrence and development of cardiovascular and metabolic risk factors, and the research on the relationship between air pollution and CRFs has grown intensively. An increasing number of studies are using new biological monitoring indicators to assess the occurrence and development of CRFs resulting from exposure to air pollution. Abnormalities in some important biomarkers in the population (such as homocysteine, uric acid, and C-reactive protein) caused by air pollution deserve more attention. Further research is warranted to more fully understand the link between air pollution and novel CRF biomarkers and to investigate potential prevention and interventions that leverage the mechanistic link between air pollution and CRFs.
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Affiliation(s)
- Li-Hao Guo
- 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, 74 Zhongshan 2Nd Road, Yuexiu District, Guangzhou, 510080, China
| | - Mohammed Zeeshan
- 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, 74 Zhongshan 2Nd Road, Yuexiu District, Guangzhou, 510080, China
| | - Guo-Feng Huang
- Guangdong Ecological Environmental Monitoring Center, State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangdong Environmental Protection Key Laboratory of Atmospheric Secondary Pollution, Guangzhou, 510308, China
| | - Duo-Hong Chen
- Guangdong Ecological Environmental Monitoring Center, State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangdong Environmental Protection Key Laboratory of Atmospheric Secondary Pollution, Guangzhou, 510308, China
| | - Min Xie
- Guangdong Ecological Environmental Monitoring Center, State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangdong Environmental Protection Key Laboratory of Atmospheric Secondary Pollution, Guangzhou, 510308, China
| | - Jun Liu
- Guangdong Ecological Environmental Monitoring Center, State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangdong Environmental Protection Key Laboratory of Atmospheric Secondary Pollution, Guangzhou, 510308, China
| | - Guang-Hui 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, 74 Zhongshan 2Nd Road, Yuexiu District, Guangzhou, 510080, China.
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Ji JS, Xia Y, Liu L, Zhou W, Chen R, Dong G, Hu Q, Jiang J, Kan H, Li T, Li Y, Liu Q, Liu Y, Long Y, Lv Y, Ma J, Ma Y, Pelin K, Shi X, Tong S, Xie Y, Xu L, Yuan C, Zeng H, Zhao B, Zheng G, Liang W, Chan M, Huang C. China's public health initiatives for climate change adaptation. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2023; 40:100965. [PMID: 38116500 PMCID: PMC10730322 DOI: 10.1016/j.lanwpc.2023.100965] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 10/01/2023] [Accepted: 11/01/2023] [Indexed: 12/21/2023]
Abstract
China's health gains over the past decades face potential reversals if climate change adaptation is not prioritized. China's temperature rise surpasses the global average due to urban heat islands and ecological changes, and demands urgent actions to safeguard public health. Effective adaptation need to consider China's urbanization trends, underlying non-communicable diseases, an aging population, and future pandemic threats. Climate change adaptation initiatives and strategies include urban green space, healthy indoor environments, spatial planning for cities, advance location-specific early warning systems for extreme weather events, and a holistic approach for linking carbon neutrality to health co-benefits. Innovation and technology uptake is a crucial opportunity. China's successful climate adaptation can foster international collaboration regionally and beyond.
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Affiliation(s)
- John S. Ji
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Yanjie Xia
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Linxin Liu
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Weiju Zhou
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Renjie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and National School of Public Health, Health Commission Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Guanghui Dong
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, Guangzhou, China
| | - Qinghua Hu
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Jingkun Jiang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and National School of Public Health, Health Commission Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Tiantian Li
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yi Li
- Public Meteorological Service Centre, China Meteorological Administration, Beijing, China
| | - Qiyong Liu
- National Institute of Infectious Diseases at China, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yanxiang Liu
- Public Meteorological Service Centre, China Meteorological Administration, Beijing, China
| | - Ying Long
- School of Architecture, Tsinghua University, Beijing, China
| | - Yuebin Lv
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jian Ma
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Yue Ma
- School of Architecture, Tsinghua University, Beijing, China
| | - Kinay Pelin
- School of Climate Change and Adaptation, University of Prince Edward Island, Prince Edward Island, Canada
| | - Xiaoming Shi
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Shilu Tong
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Public Health, Queensland University of Technology, Brisbane, Australia
| | - Yang Xie
- School of Economics and Management, Beihang University, Beijing, China
| | - Lei Xu
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Changzheng Yuan
- School of Public Health, Zhejiang University, Hangzhou, China
| | - Huatang Zeng
- Shenzhen Health Development Research and Data Management Center, Shenzhen, China
| | - Bin Zhao
- Department of Building Science, School of Architecture, Tsinghua University, Beijing, China
| | - Guangjie Zheng
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
| | - Wannian Liang
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Margaret Chan
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Cunrui Huang
- Vanke School of Public Health, Tsinghua University, Beijing, China
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