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Zhou X, Wei C, Chen Z, Xia X, Wang L, Li X. Potential mechanisms of ischemic stroke induced by heat exposure. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 952:175815. [PMID: 39197783 DOI: 10.1016/j.scitotenv.2024.175815] [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: 04/08/2024] [Revised: 08/04/2024] [Accepted: 08/24/2024] [Indexed: 09/01/2024]
Abstract
Recent decades of epidemiological and clinical research have suggested that heat exposure could be a potential risk factor for ischemic stroke. Despite climate factors having a minor impact on individuals compared with established risk factors such as smoking, their widespread and persistent effects significantly affect public health. The mechanisms by which heat exposure triggers ischemic stroke are currently unclear. However, several potential mechanisms, such as the impact of temperature variability on stroke risk factors, inflammation, oxidative stress, and coagulation system changes, have been proposed. This article details the potential mechanisms by which heat exposure may induce ischemic stroke, aiming to guide the prevention and treatment of high-risk groups in hot climates and support public health policy development.
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Affiliation(s)
- Xiao Zhou
- Department of Neurology, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Chanjuan Wei
- Department of Neurology, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Zhuangzhuang Chen
- Department of Neurology, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Xiaoshuang Xia
- Department of Neurology, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Lin Wang
- Department of Geriatrics, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Xin Li
- Department of Neurology, The Second Hospital of Tianjin Medical University, Tianjin, China; Department of Geriatrics, The Second Hospital of Tianjin Medical University, Tianjin, China.
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Zhang M, Bai Y, Hu J, Ni Y, Zeng Q. An Improved Air Health Index Based on Short-Term Cardiovascular Effects in Tianjin, China. Int J Public Health 2024; 69:1607214. [PMID: 39351212 PMCID: PMC11440067 DOI: 10.3389/ijph.2024.1607214] [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: 02/28/2024] [Accepted: 08/20/2024] [Indexed: 10/04/2024] Open
Abstract
Objectives To construct an improved air health index (AHI) based on cardiovascular years of life lost (YLL) in Tianjin and assess its utility. Methods We derived the exposure-response coefficients from time-series models and calculated the excess YLL (EYLL) for simultaneous exposure to air pollution and non-optimum temperature. The AHI was developed using the EYLL at the WHO 2021 Air Quality Guideline annual mean values and optimum temperature as a reference. We assessed the validity of AHI by comparing the correlations and model fit between the AHI, air quality health index (AQHI), and air quality index (AQI) with cause-specific YLLs. Results Each inter quartile range (IQR) increase in AHI was associated with 256.31 (95%CI: 183.05, 329.57), 150.34 (95%CI: 108.23, 192.46), 90.41 (95%CI: 64.80, 116.02) and 60.80 (95%CI:33.41, 88.18) person-year increments for non-accidental, cardiovascular, ischaemic, and cerebrovascular YLL, respectively. The AHI, in contrast to the AQHI and AQI, showed the strongest correlations with the risks of cause-specific YLLs, both in the total population and subpopulations. Conclusion The AHI based on cardiovascular YLL has a greater predictive ability for health risks.
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Affiliation(s)
- Mengnan Zhang
- Tianjin Centers for Disease Control and Prevention, Tianjin, China
- Huaian Center for Disease Control and Prevention, Huaian, China
| | - Yu Bai
- Tianjin Centers for Disease Control and Prevention, Tianjin, China
| | - Junyi Hu
- Tianjin Centers for Disease Control and Prevention, Tianjin, China
| | - Yang Ni
- Tianjin Centers for Disease Control and Prevention, Tianjin, China
| | - Qiang Zeng
- Tianjin Centers for Disease Control and Prevention, Tianjin, China
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He G, Lin Y, Hu J, Chen Y, Guo Y, Yu M, Zeng F, Duan H, Meng R, Zhou C, Xiao Y, Huang B, Gong W, Liu J, Liu T, Zhou M, Ma W. The trends of non-accidental mortality burden attributed to compound hot-dry events in China and its provinces in a global warming world. ENVIRONMENT INTERNATIONAL 2024; 191:108977. [PMID: 39216332 DOI: 10.1016/j.envint.2024.108977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2024] [Revised: 07/22/2024] [Accepted: 08/21/2024] [Indexed: 09/04/2024]
Abstract
BACKGROUND Global warming has provoked more co-occurrence of hot extreme and dry extreme, namely compound hot-dry events (CHDEs). However, their health impacts have seldom been investigated. This study aimed to characterize CHDEs and assess its mortality burden in China from 1990 to 2100. METHODS CHDEs were defined as a day when daily maximum temperature > its 90th percentile and Standardized Precipitation Index < its 50th percentile. A two-stage approach, including a distributed lag nonlinear model (DLNM) and a multivariate meta-analysis, was used to estimate exposure-response associations of CHDEs with mortality in 358 counties/districts during 2006-2017 in China, which was then applied to assess the national mortality burden attributable to CHDEs from 1990 to 2100. FINDINGS We observed a significant increasing trend of CHDEs in China until mid-21st century, and then flatted, while the duration and intensity of CHDEs continuously increased across the 21st century. CHDEs were much riskier (ER=17.82 %, 95 %CI: 14.17 %-21.60 %) than independent hot events (ER=5.86 %,95 %CI: -0.04 %,12.45 %) or dry events (ER=0.07 %,95 %CI: -1.22 %, 1.38 %), and there was significantly additive interaction between hot events and dry events (AP=0.10,95 %CI: 0.04, 0.16). Females (ER=24.28 %, 95 %CI: 19.21 %-29.56 %), the elderly (ER=23.28 %, 95 %CI: 18.23 %-28.55 %), and people living in humid area (ER=18.98 %, 95 %CI: 15.08 %-23.02 %) had higher mortality risks than their counterparts. Mortality burden attributed to CHDEs significantly increased during historical observation and became stable since mid-21st century in China. INTERPRETATION CHDEs would significantly increase mortality with higher risk for females, the elderly and people living in humid areas. Mortality burden has significantly increased during historical observation and will keep relatively steady since mid-21st century.
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Affiliation(s)
- Guanhao He
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Yi Lin
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Jianxiong Hu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Yang Chen
- State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Yanfang Guo
- Bao'an Chronic Diseases Prevent and Cure Hospital, Shenzhen 518100, China
| | - Min Yu
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310009, China
| | - Fangfang Zeng
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Hailai Duan
- Climate Center of Guangdong Province, Guangzhou 510640, China
| | - Ruilin Meng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Chunliang Zhou
- Hunan Provincial Center for Disease Control and Prevention, Changsha 410005, China
| | - Yize Xiao
- Yunnan Provincial Center for Disease Control and Prevention, Kunming 650034, China
| | - Biao Huang
- Jilin Provincial Center for Disease Control and Prevention, Changchun 130062, China
| | - Weiwei Gong
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310009, China
| | - Jiangmei Liu
- The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing 100050, China
| | - Tao Liu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Maigeng Zhou
- The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing 100050, China
| | - Wenjun Ma
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China.
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Hao T, Wang X, Han S, Yao Q, Ding J. Investigating the impact of weather on stroke in summer. INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 2024:10.1007/s00484-024-02724-3. [PMID: 38913080 DOI: 10.1007/s00484-024-02724-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 05/15/2024] [Accepted: 06/10/2024] [Indexed: 06/25/2024]
Abstract
The objective of this study is to explore how changes in weather contribute to an increase in hospital admissions for stroke in summer. We collected 96,509 cases of stroke hospitalization data in Tianjin from 2016 to 2022 summer, along with corresponding meteorological data. The generalized additive model and distributed lag nonlinear model were used to analyze the lag and cumulative effects of temperature on stroke hospitalization. The research results show both the cold effect and the heat effect in summer would increase the risk of hospitalization. The effect of daily maximum temperature on stroke hospitalization was immediate when the temperature was higher, and delayed when the temperature was lower. However, the risk of stroke hospitalization increased more significantly with increasing temperature than with decreasing temperature. In the presence of one or more of the following three weather changes: sharp temperature increase, sharp temperature decrease, continuous high temperature, the daily number of stroke inpatients were higher than the average in the same period. 83% of the Inpatient-heavy events within the study period were caused by a combination of dramatic temperature changes and continuous high temperatures. In 48% of Inpatient-heavy events, continuous high temperature weather above 30℃ for at least 4 consecutive days were observed. And 55% of high temperature weather was accompanied by high humidity. When the daily relative humidity was greater than 70% and the daily maximum temperature was between 26 and 28℃ or more than 34℃, or the daily maximum temperature changes over 10℃ within 48 h, the number of daily inpatients was more than 1.2 times of the average daily inpatients. More attention should be paid to the combined effects of continuous high temperature and sudden temperature changes in summer stroke prevention.
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Affiliation(s)
- Tianyi Hao
- Tianjin Environmental Meteorological Center, Tianjin, 300074, China
- CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin, 300074, China
- Tianjin Interdisciplinary Innovation Centre for Health and Meteorology, Tianjin, 300074, China
| | - Xiaojia Wang
- Tianjin Environmental Meteorological Center, Tianjin, 300074, China
- CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin, 300074, China
- Tianjin Interdisciplinary Innovation Centre for Health and Meteorology, Tianjin, 300074, China
| | - Suqin Han
- Tianjin Environmental Meteorological Center, Tianjin, 300074, China.
- CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin, 300074, China.
- Tianjin Interdisciplinary Innovation Centre for Health and Meteorology, Tianjin, 300074, China.
| | - Qing Yao
- Tianjin Environmental Meteorological Center, Tianjin, 300074, China
- CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin, 300074, China
- Tianjin Interdisciplinary Innovation Centre for Health and Meteorology, Tianjin, 300074, China
| | - Jing Ding
- Tianjin Environmental Meteorological Center, Tianjin, 300074, China
- CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin, 300074, China
- Tianjin Interdisciplinary Innovation Centre for Health and Meteorology, Tianjin, 300074, China
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Hansson E, Jakobsson K, Glaser J, Wesseling C, Chavarria D, Lucas RAI, Prince H, Wegman DH. Impact of heat and a rest-shade-hydration intervention program on productivity of piece-paid industrial agricultural workers at risk of chronic kidney disease of nontraditional origin. Ann Work Expo Health 2024; 68:366-375. [PMID: 38367206 PMCID: PMC11033565 DOI: 10.1093/annweh/wxae007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 02/06/2024] [Indexed: 02/19/2024] Open
Abstract
OBJECTIVES Assess the impact of environmental heat and a rest-shade-hydration (RSH) intervention against heat stress on productivity of piece-paid Mesoamerican sugarcane cutters. These workers are at a high risk of chronic kidney disease of non-traditional origin (CKDnt), from the severe heat stress they experience due to heavy work under hot conditions. RSH interventions in these populations improve kidney health outcomes, but their impact on productivity has yet to be examined. METHODS We accessed routine productivity data from seed (SC, N = 749) and burned (BCC, N = 535) sugarcane cutters observed over five harvest seasons with increasing RSH intervention at a large Nicaraguan sugarcane mill. Hourly field-site wet-bulb globe temperature (WBGT) was recorded by mill staff and summarized as a daily mean. Mixed linear regression was used to model daily productivity, adjusting for age (18-29, 30-44, and >45 years), sex, WBGT (<28, 28-29, 29-30, 30-31, and >31 °C) on the same and preceding day, harvest season (2017-18 to 2021-22), month, and acclimatization status (<1, 1-2, and >2 weeks). RESULTS There was an inverse dose-response relationship between SC productivity and WBGT on the same and preceding days, decreasing by approximately 3%/°C WBGT. Productivity increased during the study period, i.e. coinciding with RSH scale-up, by approximately 19% in SC and 9% in BCC. CONCLUSION Agricultural worker productivity was expected lower on hotter days, strengthening the interest in all stakeholders to mitigate increasing global temperatures and their impact. Despite decreasing the total time allocated for work each day, an RSH intervention appears to result in increased productivity and no apparent loss in productivity.
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Affiliation(s)
- Erik Hansson
- La Isla Network, 2219 California NW Unit 52, 20008 Washington, District of Columbia, United States
- Occupational and Environmental Medicine, School of Public Health and Community Medicine, Sahlgrenska Academy, University of Gothenburg, Box 414, 413 90 Gothenburg, Sweden
| | - Kristina Jakobsson
- La Isla Network, 2219 California NW Unit 52, 20008 Washington, District of Columbia, United States
- Occupational and Environmental Medicine, School of Public Health and Community Medicine, Sahlgrenska Academy, University of Gothenburg, Box 414, 413 90 Gothenburg, Sweden
- Occupational and Environmental Medicine, Sahlgrenska University Hospital, Box 414, 413 90 Gothenburg, Sweden
| | - Jason Glaser
- La Isla Network, 2219 California NW Unit 52, 20008 Washington, District of Columbia, United States
| | - Catharina Wesseling
- La Isla Network, 2219 California NW Unit 52, 20008 Washington, District of Columbia, United States
- Unit of Occupational Medicine, Institute of Environmental Medicine, Karolinska Institute, Box 210, 171 77 Stockholm, Sweden
| | - Denis Chavarria
- Occupational Health Management, Ingenio San Antonio/Nicaragua Sugar Estates Limited, Km. 119 Carretera León-Chinandega, Chichigalpa, Nicaragua
| | - Rebekah A I Lucas
- La Isla Network, 2219 California NW Unit 52, 20008 Washington, District of Columbia, United States
- School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Birmingham B15 2TT, United Kingdom
| | - Heath Prince
- La Isla Network, 2219 California NW Unit 52, 20008 Washington, District of Columbia, United States
- LBJ School of Public Affairs, University of Texas at Austin, 2315 Red River St, Austin, TX 78712,United States
| | - David H Wegman
- La Isla Network, 2219 California NW Unit 52, 20008 Washington, District of Columbia, United States
- University of Massachusetts Lowell, 1 University Avenue, Lowell, 01854 MA, United States
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Jiang Z, Lin Z, Li Z, Yu M, He G, Hu J, Meng R, Hou Z, Zhu S, Zhou C, Xiao Y, Huang B, Xu X, Jin D, Qin M, Xu Y, Liu T, Ma W. Joint effects of heat-humidity compound events on drowning mortality in Southern China. Inj Prev 2024:ip-2023-045036. [PMID: 38443161 DOI: 10.1136/ip-2023-045036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Accepted: 02/17/2024] [Indexed: 03/07/2024]
Abstract
BACKGROUND Several previous studies have examined the association of ambient temperature with drowning. However, no study has investigated the effects of heat-humidity compound events on drowning mortality. METHODS The drowning mortality data and meteorological data during the five hottest months (May to September) were collected from 46 cities in Southern China (2013-2018 in Guangdong, Hunan and Zhejiang provinces). Distributed lag non-linear model was first conducted to examine the association between heat-humidity compound events and drowning mortality at city level. Then, meta-analysis was employed to pool the city-specific exposure-response associations. Finally, we analysed the additive interaction of heat and humidity on drowning mortality. RESULTS Compared with wet-non-hot days, dry-hot days had greater effects (excess rate (ER)=32.34%, 95% CI: 24.64 to 40.50) on drowning mortality than wet-hot days (ER=14.38%, 95%CI: 6.80 to 22.50). During dry-hot days, males (ER=42.40%, 95% CI: 31.92 to 53.72), adolescents aged 0-14 years (ER=45.00%, 95% CI: 21.98 to 72.35) and urban city (ER=36.91%, 95% CI: 23.87 to 51.32) showed higher drowning mortality risk than their counterparts. For wet-hot days, males, adolescents and urban city had higher ERs than their counterparts. Attributable fraction (AF) of drowning attributed to dry-hot days was 23.83% (95% CI: 21.67 to 26.99) which was significantly higher than that for wet-hot days (11.32%, 95% CI: 9.64 to 13.48%). We also observed that high temperature and low humidity had an additive interaction on drowning mortality. CONCLUSION We found that dry-hot days had greater drowning mortality risk and burden than wet-hot days, and high temperature and low humidity might have synergy on drowning mortality.
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Affiliation(s)
- Zhiying Jiang
- Department of Public Health and Preventive Medicine, Jinan University, Guangzhou, China
| | - Ziqiang Lin
- Department of Public Health and Preventive Medicine, Jinan University, Guangzhou, China
| | - Zhixing Li
- Department of Public Health, Jinan University, Guangzhou, China
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Min Yu
- Division of NCD Control, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Guanhao He
- Department of Public Health and Preventive Medicine, Jinan University, Guangzhou, China
| | - Jianxiong Hu
- Department of Public Health and Preventive Medicine, Jinan University, Guangzhou, China
| | - Ruilin Meng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Zhulin Hou
- Jilin Provincial Center for Disease Control and Prevention, Changchun, China
| | - Sui Zhu
- Department of Public Health and Preventive Medicine, Jinan University, Guangzhou, China
| | - Chunliang Zhou
- Hunan Provincial Center for Disease Control and Prevention, Changsha, China
| | - Yize Xiao
- Yunnan Provincial Center for Disease Control and Prevention, Kunming, China
| | - Biao Huang
- Jilin Provincial Center for Disease Control and Prevention, Changchun, China
| | - Xiaojun Xu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Donghui Jin
- Hunan Provincial Center for Disease Control and Prevention, Changsha, China
| | - Mingfang Qin
- Yunnan Provincial Center for Disease Control and Prevention, Kunming, China
| | - Yiqing Xu
- Hunan Provincial Center for Disease Control and Prevention, Changsha, China
| | - Tao Liu
- Department of Public Health and Preventive Medicine, Jinan University, Guangzhou, China
| | - Wenjun Ma
- Department of Public Health and Preventive Medicine, Jinan University, Guangzhou, China
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Zhai G, Qi J, Chai G, Zhou W, Wang J. Effects of large temperature change lasting for several days on cardiovascular disease hospital admissions among farmers in China's Western villages. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2024; 34:443-454. [PMID: 36469800 DOI: 10.1080/09603123.2022.2153807] [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: 05/28/2022] [Accepted: 11/27/2022] [Indexed: 06/17/2023]
Abstract
Global climate change has resulted in an increase in the frequency, intensity, and duration of extreme events. However, we know very little about the associations between large temperature changes lasting for several days (LTCD) and CVD, particularly in less-developed, rural areas. We collected daily data on cardiovascular-related diseases and weather conditions from 119 villages in seven counties between 2010 and 2016. A distributed lag non-linear model was used to investigate the association between LTCD and relative risk (RR) of hospital admissions for CVD. Analyses were stratified by the duration and intensity of LTCD, age, and sex. The RR of CVD increases with the intensity and duration of LTCD. Men and young people were more vulnerable to LTCD of longer duration and higher intensity than women and old. Our findings may help local public health authorities develop adaptive preventive strategies targeting inhabitants of villages.
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Affiliation(s)
- Guangyu Zhai
- School of Economics and Management, Lanzhou University of Technology, Lanzhou, China
| | - Jintao Qi
- School of Economics and Management, Lanzhou University of Technology, Lanzhou, China
| | - Guorong Chai
- School of Management, Lanzhou University, Lanzhou, China
| | - Wenjuan Zhou
- Network Center, Gansu Provincial Hospital, Lanzhou, China
| | - Jiancheng Wang
- Network Center, Gansu Provincial Hospital, Lanzhou, China
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Zhao C, Pan Y, Wu H, Zhu Y. Quantifying the contribution of industrial zones to urban heat islands: Relevance and direct impact. ENVIRONMENTAL RESEARCH 2024; 240:117594. [PMID: 37926229 DOI: 10.1016/j.envres.2023.117594] [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: 08/27/2023] [Revised: 11/01/2023] [Accepted: 11/02/2023] [Indexed: 11/07/2023]
Abstract
Industrial production activities are an important source of urban heat emissions. Quantifying the contribution of industrial zones to urban heat islands (UHIs) is crucial for urban planning and management. However, few studies have explored the quantitative relationship between land surface temperature (LST) and urban industrial zones (UIZs) at the urban scale, especially the direct impact of industrial expansion or contraction on LST. Linyi City, the largest city in Shandong Province, was selected as the study area. This study aims to analyze the spatial-temporal variation in the UIZs in Linyi City from 2013 to 2022, focusing on the quantitative relationship between LST and UIZs. Using remote sensing images, a novel spectral index (called the BCCSI) was constructed to identify factory buildings. The performance of the BCCSI was validated using five existing indices and Google Earth images. Over the past 10 years, the UIZ area of Linyi has increased by 137.16 km2. The UIZs in Linyi are mainly distributed in counties near the urban center, and counties with large UIZ areas are also hotspots for UIZ changes. Moreover, we found that the contraction or expansion of UIZs has obvious effects on LST. After the contraction (or expansion) of UIZs, the LST decreased (or increased) by 0.48 °C (0.39 °C). In addition, we found that there is an exponential relationship between LST and the industrial unit area (P value less than 0.01). This research is valuable for environmental assessment and fine management of industrial cities.
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Affiliation(s)
- Chuanwu Zhao
- State Key Laboratory of Remote Sensing, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China; Key Laboratory of Environmental Change and Natural Disasters of Chinese Ministry of Education, Beijing Normal University, Beijing, 100875, China; Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China.
| | - Yaozhong Pan
- State Key Laboratory of Remote Sensing, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China; Key Laboratory of Environmental Change and Natural Disasters of Chinese Ministry of Education, Beijing Normal University, Beijing, 100875, China; Academy of Plateau Science and Sustainability, Qinghai Normal University, Xining, 810016, China.
| | - Hanyi Wu
- State Key Laboratory of Remote Sensing, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China; Key Laboratory of Environmental Change and Natural Disasters of Chinese Ministry of Education, Beijing Normal University, Beijing, 100875, China
| | - Yu Zhu
- State Key Laboratory of Remote Sensing, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China; Key Laboratory of Environmental Change and Natural Disasters of Chinese Ministry of Education, Beijing Normal University, Beijing, 100875, China
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9
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Zhu S, Zhang J, Liu C, Li D, Hong Y, Zhang F. Global burden of non-optimal temperature attributable stroke: The long-term trends, population growth and aging effects. Prev Med 2024; 178:107813. [PMID: 38092330 DOI: 10.1016/j.ypmed.2023.107813] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 12/05/2023] [Accepted: 12/06/2023] [Indexed: 12/17/2023]
Abstract
Since the 20th century, the world has undergone climate change, population growth and population aging, which may result in alterations in the epidemiology of non-optimal temperature-associated strokes. We employed multiple methodologies and data from the global burden of disease 2019 to unveil the long-term curvilinear trends in strokes attributed to non-optimal temperature and the impact of aging and population growth on its changing epidemiology. From 1990 to 2019, the age-standardized DALYs rate (ASDR) of strokes attributable to low temperature had been decreasing, but from 2016, the continued downward trend in ASDR disappeared and began to remain stable. On the contrary, the ASDR of strokes attributable to high temperature continued to increase. The high socio-demographic index (SDI) region experienced the fastest decreased trend. The disease burden of stroke attributable to low temperature is increased by aging in 178 countries (87.25%), compared with 130 (63.73%) for high temperature. After excluding aging and population growth, the DALY rate for strokes attributed to high temperature was increasing in 87 countries and territories (42.64%). The disease burden of strokes attributed to low temperature is far greater than that of high temperature in absolute figures. However, globally, there is a significant trend toward an increase in strokes attributed to high temperature. Social development has largely offset the burden of strokes attributed to low temperature, but most regions of the world are equally affected by strokes attributed to high temperature. Simultaneously, in the framework of climate change, aging is also largely hindering stroke prevention efforts.
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Affiliation(s)
- Shijie Zhu
- Department of Occupational and Environmental Health, School of Public Health, Wuhan University, Wuhan 430071, China
| | - Jian Zhang
- Department of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang 110004, China; Department of Neurosurgery, the Seventh Clinical College of China Medical University, Fushun 113000, China
| | - Chunlong Liu
- Department of Hepatobiliary and Pancreatic Surgery, Fuyang People's Hospital, Anhui Medical University, Fuyang 236000, China
| | - Dejia Li
- Department of Occupational and Environmental Health, School of Public Health, Wuhan University, Wuhan 430071, China
| | - Yang Hong
- Department of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang 110004, China.
| | - Faxue Zhang
- Department of Occupational and Environmental Health, School of Public Health, Wuhan University, Wuhan 430071, China.
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Fu G, Cheng H, Lu Q, Liu H, Zhang X, Zhang X. The synergistic effect of high temperature and ozone on the number of deaths from circulatory system diseases in Shijiazhuang, China. Front Public Health 2023; 11:1266643. [PMID: 37854243 PMCID: PMC10581204 DOI: 10.3389/fpubh.2023.1266643] [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: 07/25/2023] [Accepted: 08/29/2023] [Indexed: 10/20/2023] Open
Abstract
Introduction Urban ozone pollution in China is becoming increasingly serious. Climate warming, high temperatures, and ozone pollution all have significant impacts on human health. However, the synergistic effects of high temperatures and ozone pollution in summer on human health are rarely studied. China is at a critical stage of environmental pollution control. Assessing the health impact of high temperatures and ozone exposure on the number of deaths from circulatory diseases is of great significance for formulating ozone-related prevention and control policies. Methods This study uses daily data on deaths from circulatory system diseases in Shijiazhuang from June to August during the summer of 2013-2016, as well as concurrent meteorological data and concentration of O3 and PM2.5 pollution data. The generalized additive model (GAM) with Poisson distribution, smooth curve threshold effect, and saturation effect method is used to control for confounding effects. Results The study evaluates the impact of short-term exposure to temperature and ozone on deaths from circulatory system diseases and the synergistic effect after controlling for confounding factors. The results show that the impact of temperature and ozone on deaths from circulatory system diseases in Shijiazhuang is nonlinear, with a temperature threshold of 27.5°C and an ozone concentration threshold of 100 μg/m3. With an increase of temperature by 1°C, the risk of deaths for total population, men and women are 6.8%, 4.6% and 9.3%, respectively. The increase in temperature and ozone concentration has a greater impact on women; in men, the increase has a lag effect of 2 to 3 days, but the lag did not affect women. Discussion In conclusion, high temperatures and high ozone concentration have synergistic enhancement effects on circulatory system diseases. Prevention and scientific management strategies of circulatory system diseases in high temperatures and high ozone environments should be strengthened.
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Affiliation(s)
- Guiqin Fu
- China Meteorological Administration Xiong’an Atmospheric Boundary Layer Laboratory, Xiong’anChina
- Key Laboratory of Meteorology and Ecological Environment of Hebei Province, Shijiazhuang, China
- Hebei Meteorological Service Center, Shijiazhuang, China
| | - Haimin Cheng
- Key Laboratory of Meteorology and Ecological Environment of Hebei Province, Shijiazhuang, China
- Hebei Meteorological Service Center, Shijiazhuang, China
| | - Qian Lu
- China Meteorological Administration Xiong’an Atmospheric Boundary Layer Laboratory, Xiong’anChina
- Key Laboratory of Meteorology and Ecological Environment of Hebei Province, Shijiazhuang, China
- Chengde Meteorological Service of Hebei Province, Chengde, China
| | - Huayue Liu
- China Meteorological Administration Xiong’an Atmospheric Boundary Layer Laboratory, Xiong’anChina
- Hebei Meteorological Service Center, Shijiazhuang, China
| | - Xiaohui Zhang
- Chengde Meteorological Service of Hebei Province, Chengde, China
| | - Xingshan Zhang
- Handan Meteorological Service of Hebei Province, Handan, China
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11
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Hu J, He G, Meng R, Gong W, Ren Z, Shi H, Lin Z, Liu T, Zeng F, Yin P, Bai G, Qin M, Hou Z, Dong X, Zhou C, Pingcuo Z, Xiao Y, Yu M, Huang B, Xu X, Lin L, Xiao J, Zhong J, Jin D, Zhao Q, Li Y, Gama C, Xu Y, Lv L, Zeng W, Li X, Luo L, Zhou M, Huang C, Ma W. Temperature-related mortality in China from specific injury. Nat Commun 2023; 14:37. [PMID: 36596791 PMCID: PMC9810693 DOI: 10.1038/s41467-022-35462-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 12/05/2022] [Indexed: 01/04/2023] Open
Abstract
Injury poses heavy burden on public health, accounting for nearly 8% of all deaths globally, but little evidence on the role of climate change on injury exists. We collect data during 2013-2019 in six provinces of China to examine the effects of temperature on injury mortality, and to project future mortality burden attributable to temperature change driven by climate change based on the assumption of constant injury mortality and population scenario. The results show that a 0.50% (95% confident interval (CI): 0.13%-0.88%) increase of injury mortality risk for each 1 °C rise in daily temperature, with higher risk for intentional injury (1.13%, 0.55%-1.71%) than that for unintentional injury (0.40%, 0.04%-0.77%). Compared to the 2010s, total injury deaths attributable to temperature change in China would increase 156,586 (37,654-272,316) in the 2090 s under representative concentration pathways 8.5 scenario with the highest for transport injury (64,764, 8,517-115,743). Populations living in Western China, people aged 15-69 years, and male may suffer more injury mortality burden from increased temperature caused by climate change. Our findings may be informative for public health policy development to effectively adapt to climate change.
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Affiliation(s)
- Jianxiong Hu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Guanhao He
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, 511443, China
| | - Ruilin Meng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Weiwei Gong
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, 310009, China
| | - Zhoupeng Ren
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
| | - Heng Shi
- Tibet Autonomous Region Center for Disease Control and Prevention, Lhasa, 850002, China
| | - Ziqiang Lin
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, 511443, China
| | - Tao Liu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, 511443, China
| | - Fangfang Zeng
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, 511443, China
| | - Peng Yin
- The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing, 100050, China
| | - Guoxia Bai
- Tibet Autonomous Region Center for Disease Control and Prevention, Lhasa, 850002, China
| | - Mingfang Qin
- Yunnan Provincial Center for Disease Control and Prevention, Kunming, 650034, China
| | - Zhulin Hou
- Jilin Provincial Center for Disease Control and Prevention, Changchun, 130062, China
| | - Xiaomei Dong
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, 511443, China
| | - Chunliang Zhou
- Hunan Provincial Center for Disease Control and Prevention, Changsha, 410005, China
| | - Zhuoma Pingcuo
- Tibet Autonomous Region Center for Disease Control and Prevention, Lhasa, 850002, China
| | - Yize Xiao
- Yunnan Provincial Center for Disease Control and Prevention, Kunming, 650034, China
| | - Min Yu
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, 310009, China
| | - Biao Huang
- Jilin Provincial Center for Disease Control and Prevention, Changchun, 130062, China
| | - Xiaojun Xu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Lifeng Lin
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Jianpeng Xiao
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Jieming Zhong
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, 310009, China
| | - Donghui Jin
- Hunan Provincial Center for Disease Control and Prevention, Changsha, 410005, China
| | - Qinglong Zhao
- Jilin Provincial Center for Disease Control and Prevention, Changchun, 130062, China
| | - Yajie Li
- Tibet Autonomous Region Center for Disease Control and Prevention, Lhasa, 850002, China
| | - Cangjue Gama
- Tibet Autonomous Region Center for Disease Control and Prevention, Lhasa, 850002, China
| | - Yiqing Xu
- Hunan Provincial Center for Disease Control and Prevention, Changsha, 410005, China
| | - Lingshuang Lv
- Hunan Provincial Center for Disease Control and Prevention, Changsha, 410005, China
| | - Weilin Zeng
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Xing Li
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Liying Luo
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Maigeng Zhou
- The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing, 100050, China
| | - Cunrui Huang
- Vanke School of Public Health, Tsinghua University, Beijing, 100084, China
| | - Wenjun Ma
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, 511443, China.
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12
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Gong W, Li X, Zhou M, Zhou C, Xiao Y, Huang B, Lin L, Hu J, Xiao J, Zeng W, He G, Huang C, Liu T, Du Q, Ma W. Mortality burden attributable to temperature variability in China. JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2023; 33:118-124. [PMID: 35332279 PMCID: PMC8944404 DOI: 10.1038/s41370-022-00424-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 02/24/2022] [Accepted: 03/03/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND Several studies have investigated the associations between temperature variability (TV) and death counts. However, evidence of TV-attributable years of life lost (YLL) is scarce. OBJECTIVES To investigate the associations between TV and YLL rates (/100,000 population), and quantify average life loss per death (LLD) caused by TV in China. METHODS We calculated daily YLL rates (/100,000 population) of non-accidental causes and cardiorespiratory diseases by using death data from 364 counties of China during 2006-2017, and collected meteorological data during the same period. A distributed lag non-linear model (DLNM) and multivariate meta-analysis were used to estimate the effects of TV at national or regional levels. Then, we calculated the LLD to quantify the mortality burden of TV. RESULTS U-shaped curves were observed in the associations of YLL rates with TV in China. The minimum YLL TV (MYTV) was 2.5 °C nationwide. An average of 0.89 LLD was attributable to TV in total, most of which was from high TV (0.86, 95% CI: 0.56, 1.16). However, TV caused more LLD in the young (<65 years old) (1.87, 95% CI: 1.03, 2.71) than 65-74 years old (0.85, 95% CI: 0.40-1.31) and ≥75 years old (0.40, 95% CI: 0.21-0.59), cerebrovascular disease (0.74, 95% CI: 0.36, 1.11) than respiratory disease (0.54, 95% CI: 0.21, 0.87), South (1.23, 95% CI: 0.77, 1.68) than North (0.41, 95% CI: -0.7, 1.52) and Central China (0.40, 95% CI: -0.02, 0.81). TV-attributed LLD was modified by annual mean temperature, annual mean relative humidity, altitude, latitude, longitude, and education attainment. SIGNIFICANCE Our findings indicate that high and low TVs are both associated with increases in premature death, however the majority of LLD was attributable to high TV. TV-related LLD was modified by county level characteristics. TV should be considered in planning adaptation to climate change or variability. IMPACT (1) We estimated the associations of TV with YLL rates, and quantified the life loss per death (LLD) caused by TV. (2) An average of 0.89 years of LLD were attributable to TV, most of which were from high TVs. (3) TV caused more LLD in the young, cerebrovascular disease, and southern China. (4) The mortality burdens were modified by county level characteristics.
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Affiliation(s)
- Weiwei Gong
- Zhejiang Center for Disease Control and Prevention, Hangzhou, 310051, Zhejiang, China
| | - Xing Li
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Maigeng Zhou
- The National Center for Chronic and Noncommunicable Disease Control and Prevention, 100050, Beijing, China
| | - Chunliang Zhou
- Department of Environment and Health, Hunan Provincial Center for Disease Control and Prevention, Changsha, 450001, China
| | - Yize Xiao
- Yunnan Center for Disease Control and Prevention, Kunming, 650022, China
| | - Biao Huang
- Jilin Provincial Center for Disease Control and Prevention, Changchun, 130062, China
| | - Lifeng Lin
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Jianxiong Hu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Jianpeng Xiao
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Weilin Zeng
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Guanhao He
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Cunrui Huang
- School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Tao Liu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, 510632, China.
- Disease Control and Prevention Institute of Jinan University, Guangzhou, 510632, China.
| | - Qingfeng Du
- General Practice Center, The Seventh Affiliated Hospital, Southern Medical University, Foshan, 528200, China.
| | - Wenjun Ma
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, 510632, China
- Disease Control and Prevention Institute of Jinan University, Guangzhou, 510632, China
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13
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Liu C, Luo B, Wang B, He L, Wu H, Hou L, Zhang K. Global spatiotemporal trends of cardiovascular diseases due to temperature in different climates and socio-demographic index regions from 1990 to 2019. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:3282-3292. [PMID: 35945317 DOI: 10.1007/s11356-022-22407-z] [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: 05/31/2022] [Accepted: 08/01/2022] [Indexed: 06/15/2023]
Abstract
With the rapidly changing climate, assessing the global trends of cardiovascular diseases (CVDs) attributed to high and low temperatures in different climate zones and under varying socio-demographic levels is crucial for regulations, preparation, intervention, and clinical practice for CVD. Our study included 204 countries with global CVD data ranging from 1990 to 2019. We obtained the age-standardized mortality rate (ASMR); disability-adjusted life rate of CVD attributed to high, low, and non-optimal temperatures; and socio-demographic index (SDI) data from the Global Health Data Exchange. We also downloaded the temperature data from the Climatic Research Unit. These 204 countries were divided into five climate zones and five SDI levels according to the annual average temperature data and SDI in 2019. The temporal trends of CVD burden attributed to high, low, and non-optimal temperatures were estimated by using the cubic regression spline and the generalized additive mixed model (GAMM). The total burden of temperature-related CVD has been declining in the last 30 years. However, the burden of CVD attributed to high temperature showed an increasing trend. Among different climate regions, the ASMRs of CVD attributed to high temperature were the highest in the tropical regions, followed by subtropical regions, and the lowest in the boreal regions. In the past 30 years, the burden of CVD attributed to high temperatures has shown a significant increasing trend, while declining trends are observed for non-optimal and low temperatures. The CVD burden attributed to high temperatures is particularly pronounced in warmer and low-SDI regions with an increasing trend of CVD burden due to high temperature.
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Affiliation(s)
- Ce Liu
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, 119 Donggang West Road, Lanzhou, Gansu, People's Republic of China
| | - Bin Luo
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, 119 Donggang West Road, Lanzhou, Gansu, People's Republic of China.
| | - Bo Wang
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, 119 Donggang West Road, Lanzhou, Gansu, People's Republic of China
| | - Li He
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, 119 Donggang West Road, Lanzhou, Gansu, People's Republic of China
| | - Huanmei Wu
- Department of Health Services Administration and Policy, College of Public Health, Temple University, Philadelphia, PA, 19034, USA
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA
| | - Kai Zhang
- Department of Environmental Health Sciences, School of Public Health, University at Albany, State University of New York, One University Place, Rensselaer, NY, 12144, USA
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14
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He F, Wei J, Dong Y, Liu C, Zhao K, Peng W, Lu Z, Zhang B, Xue F, Guo X, Jia X. Associations of ambient temperature with mortality for ischemic and hemorrhagic stroke and the modification effects of greenness in Shandong Province, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 851:158046. [PMID: 35987239 DOI: 10.1016/j.scitotenv.2022.158046] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 07/28/2022] [Accepted: 08/11/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Evidence is scant on the relative and attributable contributions of ambient temperature on stroke subtypes mortality. Few studies have examined modification effects of multiple greenness indicators on such contributions, especially in China. We quantified the associations between ambient temperature and overall, ischemic, and hemorrhagic stroke mortality; further examined whether the associations were modified by greenness. METHODS We conducted a multicenter time-series analysis from January 1, 2013 to December 31, 2019. we adopted a distributed lag non-linear model to evaluate county-specific temperature-stroke mortality associations. We then applied a random-effects meta-analysis to pool county-specific effects. Attributable mortality was calculated for cold and heat, defined as temperatures below and above the minimum mortality temperature (MMT). Finally, We conducted a multivariate meta-regression to determine associations between greenness and stroke mortality risks for cold and heat, using normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), and enhanced vegetation index (EVI) as quantitative indicators of greenness exposure. RESULTS In the study period, 138,749 deaths from total stroke were reported: 86,873 ischemic and 51,876 hemorrhagic stroke. We observed significant W-shaped relationships between temperature and stroke mortality, with substantial differences among counties and regions. With MMT as the temperature threshold, 17.16 % (95 % empirical CI, 13.38 %-19.75 %) of overall, 20.05 % (95 % eCI, 16.46 %-22.70 %) of ischemic, and 12.55 % (95 % eCI, 5.59 %-16.24 %) of hemorrhagic stroke mortality were attributable to non-optimum temperature (combining cold and heat), more mortality was caused by cold (14.94 %; 95 % eCI, 11.57 %-17.34 %) than by heat (2.22 %; 95 % eCI, 1.54 %-2.72 %). Higher levels of NDVI, SAVI and EVI were related to mitigated effects of non-optimum temperatures-especially heat. CONCLUSIONS Exposure to non-optimum temperatures aggravated stroke mortality risks; increasing greenness could alleviate that risks. This evidence has important implications for local communities in developing adaptive strategies to minimize the health consequences of adverse temperatures.
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Affiliation(s)
- Fenfen He
- Department of Epidemiology and Statistics, Bengbu Medical College, Bengbu, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA
| | - Yilin Dong
- Department of Epidemiology and Statistics, Bengbu Medical College, Bengbu, China
| | - Chao Liu
- Department of Epidemiology and Statistics, Bengbu Medical College, Bengbu, China
| | - Ke Zhao
- Department of Epidemiology and Statistics, Bengbu Medical College, Bengbu, China
| | - Wenjia Peng
- School of Public Health, Fudan University, Shanghai, China
| | - Zilong Lu
- Shandong Center for Disease Control and Prevention, Jinan, China
| | - Bingyin Zhang
- Shandong Center for Disease Control and Prevention, Jinan, China
| | - Fuzhong Xue
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China; Healthcare Big Data Research Institute, Cheeloo College of Medicine, Shandong University, Jinan, China.
| | - Xiaolei Guo
- Shandong Center for Disease Control and Prevention, Jinan, China.
| | - Xianjie Jia
- Department of Epidemiology and Statistics, Bengbu Medical College, Bengbu, China.
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15
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Li C, Managi S. Global malaria infection risk from climate change. ENVIRONMENTAL RESEARCH 2022; 214:114028. [PMID: 35940231 DOI: 10.1016/j.envres.2022.114028] [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: 05/22/2022] [Revised: 07/19/2022] [Accepted: 07/30/2022] [Indexed: 06/15/2023]
Abstract
As a long-standing public health issue, malaria still severely affects many parts of the world, especially Africa. With greenhouse gas emissions, temperatures continue to rise. Based on diverse shared socioeconomic pathways (SSPs), future temperatures can be estimated. However, the impacts of climate change on malaria infection rates in all epidemic regions are unknown. Here, we estimate the differences in global malaria infection rates predicted under different SSPs during several periods as well as malaria infection case changes (MICCs) resulting from those differences. Our results indicate that the global MICCs resulting from the conversion from SSP1-2.6 to SSP2-4.5, to SSP3-7.0, and to SSP5-8.5 are 6.506 (with a 95% uncertainty interval [UI] of 6.150-6.861) million, 3.655 (3.416-3.894) million, and 2.823 (2.635-3.012) million, respectively, from 2021 to 2040; these values represent increases of 2.699%, 1.517%, and 1.171%, respectively, compared to the 241 million infection cases reported in 2020. Temperatures increases will adversely affect malaria the most in Africa during the 2021-2040 period. From 2081 to 2100, the MICCs obtained for the three scenario shifts listed above are -79.109 (-83.626 to -74.591) million, -238.337 (-251.920 to -0.141) million, and -162.692 (-174.628 to -150.757) million, corresponding to increases of -32.825%, -98.895%, and -67.507%, respectively. Climate change will increase the danger and risks associated with malaria in the most vulnerable regions in the near term, thus aggravating the difficulty of eliminating malaria. Reducing GHG emissions is a potential pathway to protecting people from malaria.
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Affiliation(s)
- Chao Li
- Urban Institute, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka, 819-0395, Japan
| | - Shunsuke Managi
- Urban Institute, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka, 819-0395, Japan.
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16
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Luo L, Zeng F, Bai G, Gong W, Ren Z, Hu J, He G, Shi H, Lin Z, Liu T, Yin P, Qin M, Hou Z, Meng R, Zhou C, Dong X, Pingcuo Z, Xiao Y, Yu M, Huang B, Xu X, Lin L, Xiao J, Zhong J, Jin D, Li Y, Gama C, Xiong P, Xu Y, Lv L, Zeng W, Li X, Zhou M, Huang C, Ma W. Future injury mortality burden attributable to compound hot extremes will significantly increase in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 845:157019. [PMID: 35798110 DOI: 10.1016/j.scitotenv.2022.157019] [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: 02/22/2022] [Revised: 06/23/2022] [Accepted: 06/24/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND As climate change, compound hot extremes (CHEs), daytime and nighttime persistent hot extremes, are projected to become much more frequent and intense, which may pose a serious threat to human health. However, evidence on the impact of CHEs on injury is rare. METHODS We collected injury death data and daily meteorological data from six Chinese provinces during 2013-2018. A time-stratified case-crossover design with two-stage analytic approach was applied to assess the associations of CHEs with injury mortality by intention, mechanism, age and gender. Using the projected daily temperatures of five General Circulation Models (GCMs), we projected the frequency of CHEs and CHEs-attributable mortality burden of injury under three Representative Concentration Pathway (RCP) scenarios. RESULTS CHEs were significantly associated with increased injury mortality risk (RR = 1.14, 95%CI: 1.09-1.19), with strong effects on unintentional injuries (RR = 1.16, 95%CI:1.11,1.22) and intentional injuries (RR = 1.11, 95%CI:0.99,1.25). Female (RR = 1.21,95%CI: 1.13-1.29) and the elderly (RR = 1.30, 95%CI: 1.22-1.39) were more susceptible to CHEs. Both the frequency and injury mortality burden of CHEs showed a steep rising trend under RCP8.5 scenario, with a 7.37-fold and 8.22-fold increase respectively, by the end of the century, especially in southern, eastern, central and northwestern China. CONCLUSION CHEs were associated with increased injury mortality risk, and the CHEs-attributable injury mortality burden was projected to aggravate substantially in the future as global warming. It is urgent to develop targeted adaptation policies to alleviate the health burden of CHEs.
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Affiliation(s)
- Liying Luo
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Fangfang Zeng
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 511443, China
| | - Guoxia Bai
- Tibet Autonomous Region Center for Disease Control and Prevention, Lhasa 850002, China
| | - Weiwei Gong
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, 310009, China
| | - Zhoupeng Ren
- State Key Laboratory of Resources and Environmental Information System (LREIS), Institute of Geographic Science and Natural Resource Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Jianxiong Hu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Guanhao He
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Heng Shi
- Tibet Autonomous Region Center for Disease Control and Prevention, Lhasa 850002, China
| | - Ziqiang Lin
- Department of Psychiatry, New York University School of Medicine, One Park Ave, New York, NY 10016, United States
| | - Tao Liu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 511443, China
| | - Peng Yin
- The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing 100050, China
| | - Mingfang Qin
- Yunnan Provincial Center for Disease Control and Prevention, Kunming 650034, China
| | - Zhulin Hou
- Jilin Provincial Center for Disease Control and Prevention, Changchun 130062, China
| | - Ruilin Meng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Chunliang Zhou
- Hunan Provincial Center for Disease Control and Prevention, Changsha 410005, China
| | - Xiaomei Dong
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 511443, China
| | - Zhuoma Pingcuo
- Tibet Autonomous Region Center for Disease Control and Prevention, Lhasa 850002, China
| | - Yize Xiao
- Yunnan Provincial Center for Disease Control and Prevention, Kunming 650034, China
| | - Min Yu
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, 310009, China
| | - Biao Huang
- Jilin Provincial Center for Disease Control and Prevention, Changchun 130062, China
| | - Xiaojun Xu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Lifeng Lin
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Jianpeng Xiao
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Jieming Zhong
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, 310009, China
| | - Donghui Jin
- Hunan Provincial Center for Disease Control and Prevention, Changsha 410005, China
| | - Yajie Li
- Tibet Autonomous Region Center for Disease Control and Prevention, Lhasa 850002, China
| | - Cangjue Gama
- Tibet Autonomous Region Center for Disease Control and Prevention, Lhasa 850002, China
| | - Peng Xiong
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 511443, China
| | - Yiqing Xu
- Hunan Provincial Center for Disease Control and Prevention, Changsha 410005, China
| | - Lingshuang Lv
- Hunan Provincial Center for Disease Control and Prevention, Changsha 410005, China
| | - Weilin Zeng
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Xing Li
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Maigeng Zhou
- The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing 100050, China
| | - Cunrui Huang
- Vanke School of Public Health, Tsinghua University, Beijing 100084, China
| | - Wenjun Ma
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 511443, China.
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17
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Chen Z, Liu P, Xia X, Wang L, Li X. The underlying mechanisms of cold exposure-induced ischemic stroke. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 834:155514. [PMID: 35472344 DOI: 10.1016/j.scitotenv.2022.155514] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 04/13/2022] [Accepted: 04/21/2022] [Indexed: 06/14/2023]
Abstract
Growing evidence suggests that cold exposure is to some extent a potential risk factor for ischemic stroke. At present, although the mechanism by which cold exposure induces ischemic stroke is not fully understood, some potential mechanisms have been mentioned. First, the seasonal and temperature variability of cerebrovascular risk factors (hypertension, hyperglycemia, hyperlipidemia, atrial fibrillation) may be involved. Moreover, the activation of sympathetic nervous system and renin-angiotensin system and their downstream signaling pathways (pro-inflammatory AngII, activated platelets, and dysfunctional immune cells) are also major contributors. Finally, the influenza epidemics induced by cold weather are also influencing factors that cannot be ignored. This article is the first to systematically and comprehensively describe the underlying mechanism of cold-induced ischemic stroke, aiming to provide more preventive measures and medication guidance for stroke-susceptible individuals in cold season, and also provide support for the formulation of public health policies.
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Affiliation(s)
- Zhuangzhuang Chen
- Department of Neurology, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Peilin Liu
- Department of Neurology, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Xiaoshuang Xia
- Department of Neurology, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Lin Wang
- Department of Geriatrics, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Xin Li
- Department of Neurology, The Second Hospital of Tianjin Medical University, Tianjin, China.
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18
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Pan R, Zheng H, Ding Z, Xu Z, Ho HC, Hossain MZ, Huang C, Yi W, Song J, Cheng J, Su H. Attributing hypertensive life expectancy loss to ambient heat exposure: A multicenter study in eastern China. ENVIRONMENTAL RESEARCH 2022; 208:112726. [PMID: 35033548 DOI: 10.1016/j.envres.2022.112726] [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: 11/08/2021] [Revised: 01/03/2022] [Accepted: 01/10/2022] [Indexed: 06/14/2023]
Abstract
Ambient high temperature is a worldwide trigger for hypertension events. However, the effects of heat exposure on hypertension and years of life lost (YLL) due to heat remain largely unknown. We conducted a multicenter study in 13 cities in Jiangsu Province, China, to investigate 9727 individuals who died from hypertension during the summer months (May to September) between 2016 and 2017. Meteorological observation data (temperature and rainfall) and air pollutants (fine particulate matter and ozone) were obtained for each decedent by geocoding the residential addresses. A time-stratified case-crossover design was used to quantify the association between heat and different types of hypertension and further explore the modification effect of individual and hospital characteristics. Meanwhile, the YLL associated with heat exposure was estimated. Our results show that summer heat exposure shortens the YLL of hypertensive patients by a total of 14,74 years per month. Of these, 77.9% of YLL was mainly due to hypertensive heart disease. YLL due to heat was pronounced for essential hypertension (5.1 years (95% empirical confidence intervals (eCI): 4.1-5.8)), hypertensive heart and renal disease with heart failure (4.4 years (95% eCI: 0.9-5.9)), and hypertensive heart and renal disease (unspecified, 3.5 years (95% eCI: 1.8-4.5)). Moderate heat was associated with a larger YLL than extreme heat. The distance between hospitals and patients and the number of local first-class hospitals can significantly mitigate the adverse effect of heat exposure on longevity. Besides, unmarried people and those under 65 years of age were potentially susceptible groups, with average reduced YLL of 3.5 and 3.9 years, respectively. Our study reveals that heat exposure increases the mortality risk from many types of hypertension and YLL. In the context of climate change, if effective measures are not taken, hot weather may bring a greater burden of disease to hypertension due to premature death.
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Affiliation(s)
- Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Hao Zheng
- Department of Environmental Health, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu, 210009, China
| | - Zhen Ding
- Department of Environmental Health, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu, 210009, China
| | - Zhiwei Xu
- School of Public Health, Faculty of Medicine, University of Queensland, 288 Herston Road, Herston, QLD, 4006, Australia
| | - Hung Chak Ho
- Department of Urban Planning and Design, The University of Hong Kong, Hong Kong, China
| | - Mohammad Zahid Hossain
- International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh
| | - Cunrui Huang
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China.
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China.
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19
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Relationship between Depressive Symptoms and Weather Conditions. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19095069. [PMID: 35564464 PMCID: PMC9101342 DOI: 10.3390/ijerph19095069] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 03/31/2022] [Accepted: 04/20/2022] [Indexed: 12/10/2022]
Abstract
Background: Weather is a well-known factor worldwide in psychiatric problems such as depression, with the elderly and females being particularly susceptible. The aim of this study was to detect associations between the risk of depressive symptoms (DS) and weather variables. Methods: 6937 participants were assessed in the baseline survey of the Health Alcohol Psychosocial Factors in Eastern Europe (HAPIEE) study during 2006−2008. To assess the risk of DS, a multivariate logistic model was created with predictors such as socio-demographic factors, health behaviors, and weather variables. Results: DS were found in 23.4% of the respondents, in 15.6% of males and in 29.9% in females. A higher risk of DS (by 25%) was associated with November−December, a rising wind speed, and relative humidity (RH) < 94% and snowfall during the cold period occurring 2 days before the survey. A higher air temperature (>14.2 °C) predominant during May−September had a protective impact. A higher risk of DS in males was associated with lower atmospheric pressure (<1009 hPa) 2 days before. Females were more sensitive to the monthly variation, snowfall, and RH. Conclusions: The findings of our study suggest that some levels of weather variables have a statistically significant effect on DS.
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20
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He G, Cai M, Meng R, Hu J, Peng K, Hou Z, Zhou C, Xu X, Xiao Y, Yu M, Huang B, Lin L, Liu T, Xiao J, Gong W, Hu R, Li J, Jin D, Qin M, Zhao Q, Xu Y, Zeng W, Li X, Huang C, Si L, Yang X, Ma W. The Spring Festival Is Associated With Increased Mortality Risk in China: A Study Based on 285 Chinese Locations. Front Med (Lausanne) 2022; 9:761060. [PMID: 35308488 PMCID: PMC8924482 DOI: 10.3389/fmed.2022.761060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 01/18/2022] [Indexed: 11/21/2022] Open
Abstract
Background The Spring Festival is one of the most important traditional festivals in China. This study aimed to estimate the mortality risk attributable to the Spring Festival. Methods Between 2013 and 2017, daily meteorological, air pollution, and mortality data were collected from 285 locations in China. The Spring Festival was divided into three periods: pre-Spring Festival (16 days before Lunar New Year's Eve), mid-Spring Festival (16 days from Lunar New Year's Eve to Lantern Festival), and post-Spring Festival (16 days after Lantern Festival). The mortality risk attributed to the Spring Festival in each location was first evaluated using a distributed lag nonlinear model (DLNM), and then it was pooled using a meta-analysis model. Results We observed a dip/rise mortality pattern during the Spring Festival. Pre-Spring Festival was significantly associated with decreased mortality risk (ER: −1.58%, 95%CI: −3.09% to −0.05%), and mid-Spring Festival was unrelated to mortality risks, while post-Spring Festival was significantly associated with increased mortality risk (ER: 3.63%, 95%CI: 2.15–5.12%). Overall, a 48-day Spring Festival period was associated with a 2.11% (95%CI: 0.91–3.33%) increased mortality. We also found that the elderly aged over 64 years old, women, people with cardiovascular disease (CVD), and people living in urban areas were more vulnerable to the Spring Festival. Conclusion Our study found that the Spring Festival significantly increased the mortality risk in China. These findings suggest that it is necessary to develop clinical and public health policies to alleviate the mortality burden associated with the Spring Festival.
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Affiliation(s)
- Guanhao He
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.,School of Public Health, Southern Medical University, Guangzhou, China
| | - Min Cai
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Ruilin Meng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Jianxiong Hu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Ke Peng
- National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen, China
| | - Zhulin Hou
- Jilin Provincial Center for Disease Control and Prevention, Changchun, China
| | - Chunliang Zhou
- Hunan Provincial Center for Disease Control and Prevention, Changsha, China
| | - Xiaojun Xu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Yize Xiao
- Yunnan Provincial Center for Disease Control and Prevention, Kunming, China
| | - Min Yu
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Biao Huang
- Jilin Provincial Center for Disease Control and Prevention, Changchun, China
| | - Lifeng Lin
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Tao Liu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.,Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Jianpeng Xiao
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Weiwei Gong
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Ruying Hu
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Junhua Li
- Hunan Provincial Center for Disease Control and Prevention, Changsha, China
| | - Donghui Jin
- Hunan Provincial Center for Disease Control and Prevention, Changsha, China
| | - Mingfang Qin
- Yunnan Provincial Center for Disease Control and Prevention, Kunming, China
| | - Qinglong Zhao
- Jilin Provincial Center for Disease Control and Prevention, Changchun, China
| | - Yiqing Xu
- Hunan Provincial Center for Disease Control and Prevention, Changsha, China
| | - Weilin Zeng
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Xing Li
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Cunrui Huang
- School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Lei Si
- Faculty of Medicine, The George Institute for Global Health, University of New South Wales, Sydney, NSW, Australia
| | - Xingfen Yang
- School of Public Health, Southern Medical University, Guangzhou, China
| | - Wenjun Ma
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.,Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
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21
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Lv LS, Zhou CL, Jin DH, Ma WJ, Liu T, Xie YJ, Xu YQ, Zhang XE. Impact of ambient temperature on life loss per death from cardiovascular diseases: a multicenter study in central China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:15791-15799. [PMID: 34633619 PMCID: PMC8827384 DOI: 10.1007/s11356-021-16888-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 09/30/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND In the context of global climate change, studies have focused on the ambient temperature and mortality of cardiovascular diseases (CVDs). However, little is known about the effect of ambient temperature on year of life lost (YLL), especially the life loss per death caused by ambient temperature. In this study, we aimed to assess the relationship between ambient temperature and life loss and estimate the impact of ambient temperature on life loss per death. METHODS We collected daily time series of mortality and meteorological data from 70 locations in Hunan province, central China, in periods ranging from Jan. 1, 2013, to Dec. 31, 2017. Crude rates of YLL were calculated per 100,000 people per year (YLL/100,000 population) for each location. A distributed lag nonlinear model and multivariate meta-regression were used to estimate the associations between ambient temperature and YLL rates. Then, the average life loss per death attributable to ambient temperature was calculated. RESULTS There were 711,484 CVD deaths recorded within the study period. The exposure-response curve between ambient temperature and YLL rates was inverted J or U-shaped. Relative to the minimum YLL rate temperature, the life loss risk of extreme cold temperature lasted for 10 to 12 days, whereas the risk of extreme hot temperature appeared immediately and lasted for 3 days. On average, the life loss per death attributable to non-optimum ambient temperatures was 1.89 (95% CI, 1.21-2.56) years. Life loss was mainly caused by cold temperature (1.13, 95% CI, 0.89‑1.37), particularly moderate cold (1.00, 95% CI, 0.78‑1.23). For demographic characteristics, the mean life loss per death was relatively higher for males (2.07, 95% CI, 1.44‑2.68) and younger populations (3.72, 95% CI, 2.06‑5.46) than for females (1.88, 95% CI, 1.21-2.57) and elderly people (1.69, 95% CI, 1.28-2.10), respectively. CONCLUSIONS We found that both cold and hot temperatures significantly aggravated premature death from CVDs. Our results indicated that the whole range of effects of ambient temperature on CVDs should be given attention.
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Affiliation(s)
- Ling-Shuang Lv
- Hunan Provincial Center for Disease Control and Prevention, Changsha, 410005, China
| | - Chun-Liang Zhou
- Hunan Provincial Center for Disease Control and Prevention, Changsha, 410005, China.
| | - Dong-Hui Jin
- Hunan Provincial Center for Disease Control and Prevention, Changsha, 410005, China
| | - Wen-Jun Ma
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Tao Liu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Yi-Jun Xie
- Hunan Provincial Climate Center, Changsha, 410007, China
| | - Yi-Qing Xu
- Hunan Provincial Center for Disease Control and Prevention, Changsha, 410005, China
| | - Xing-E Zhang
- Hunan Provincial Center for Disease Control and Prevention, Changsha, 410005, China
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22
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Zeng W, Yu M, Mai W, Zhou M, Zhou C, Xiao Y, Hou Z, Xu Y, Liu T, Hu J, Xu X, Lin L, Hu R, Li J, Jin D, Qin M, Gong W, Yin P, Xu Y, Xiao J, Li X, He G, Chen S, Zhang Y, Huang C, Rutherford S, Wu X, Huang B, Ma W. Age-specific disparity in life loss per death attributable to ambient temperature: A nationwide time-series study in China. ENVIRONMENTAL RESEARCH 2022; 203:111834. [PMID: 34358501 DOI: 10.1016/j.envres.2021.111834] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Revised: 07/30/2021] [Accepted: 08/01/2021] [Indexed: 06/13/2023]
Abstract
Age-specific discrepancy of mortality burden attributed to temperature, measured as years of life lost (YLL), has been rarely investigated. We investigated age-specific temperature-YLL rates (per 100,000) relationships and quantified YLL per death caused by non-optimal temperature in China. We collected daily meteorological data, population data and daily death counts from 364 locations in China during 2006-2017. YLL was divided into three age groups (0-64 years, 65-74 years, and ≥75 years). A distributed lag non-linear model was first employed to estimate the associations of temperature with age-specific YLL rates in each location. Then we pooled the associations using a multivariate meta-analysis. Finally, we calculated age-specific average YLL per death caused by temperature by cause of death and region. We observed greater effects of cold and hot temperature on YLL rates for the elderly compared with the young population by region or cause of death. However, YLL per death due to non-optimal temperature for different regions or causes of death decreased with age, with 2.0 (95 % CI:1.5, 2.5), 1.2 (1.1, 1.4) and 1.0 years (0.9, 1.2) life loss per death for populations aged 0-64 years, 65-74 years and over 75 years, respectively. Most life loss per death results from moderate temperature, especially moderate cold for all age groups. The effect of non-optimal temperature on YLL rates is smaller for younger populations than older ones, while the temperature-related life loss per death was more prominent for younger populations.
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Affiliation(s)
- Weilin Zeng
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
| | - Min Yu
- Zhejiang Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
| | - Weizhen Mai
- School of Public Health, Southern Medical University, Guangzhou, China.
| | - Maigeng Zhou
- The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing, China.
| | - Chunliang Zhou
- Department of Environment and Health, Hunan Provincial Center for Disease Control and Prevention, Changsha, China.
| | - Yize Xiao
- Yunnan Center for Disease Control and Prevention, Kunming, China.
| | - Zhulin Hou
- Jilin Provincial Center for Disease Control and Prevention, Changchun, China.
| | - Yanjun Xu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
| | - Tao Liu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
| | - Jianxiong Hu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
| | - Xiaojun Xu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
| | - Lifeng Lin
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
| | - Ruying Hu
- Zhejiang Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
| | - Junhua Li
- Department of Environment and Health, Hunan Provincial Center for Disease Control and Prevention, Changsha, China.
| | - Donghui Jin
- Department of Environment and Health, Hunan Provincial Center for Disease Control and Prevention, Changsha, China.
| | - Mingfang Qin
- Yunnan Center for Disease Control and Prevention, Kunming, China.
| | - Weiwei Gong
- Zhejiang Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
| | - Peng Yin
- The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing, China.
| | - Yiqing Xu
- Department of Environment and Health, Hunan Provincial Center for Disease Control and Prevention, Changsha, China.
| | - Jianpeng Xiao
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
| | - Xing Li
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
| | - Guanhao He
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
| | - Siqi Chen
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
| | - Yonghui Zhang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
| | - Cunrui Huang
- School of Public Health, Sun Yat-sen University, Guangzhou, China.
| | | | - Xianbo Wu
- School of Public Health, Southern Medical University, Guangzhou, China.
| | - Biao Huang
- Jilin Provincial Center for Disease Control and Prevention, Changchun, China.
| | - Wenjun Ma
- School of Public Health, Southern Medical University, Guangzhou, China.
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23
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Cheng J, Ho HC, Su H, Huang C, Pan R, Hossain MZ, Zheng H, Xu Z. Low ambient temperature shortened life expectancy in Hong Kong: A time-series analysis of 1.4 million years of life lost from cardiorespiratory diseases. ENVIRONMENTAL RESEARCH 2021; 201:111652. [PMID: 34246637 DOI: 10.1016/j.envres.2021.111652] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 06/26/2021] [Accepted: 07/02/2021] [Indexed: 06/13/2023]
Abstract
Ambient temperature is an important contributor to mortality burden worldwide, most of which is from cold exposure. However, little is known about the cold impact on life expectancy loss. This paper aimed to estimate cold-related life expectancy loss from cause-, age-, and gender-specific cardiovascular and respiratory diseases. Daily deaths from cardiovascular and respiratory diseases and weather records were acquired for Hong Kong, China during 2000-2016. Years of life lost (YLL) that considers life expectancy at the time of death was calculated by matching each death by age and sex to annual life tables. Using a generalized additive model that fits temperature-YLL association, we estimated loss of years in life expectancy from cold. Cold was estimated to cause life expectancy loss of 0.9 years in total cardiovascular disease, with more years of loss in males than in females and in people aged 65 years and older than in people aged up to 64 years. Cold-related life expectancy loss in total respiratory diseases was 1.2 years, with more years of loss in females than in males and comparable years of loss in people aged up to 64 years and in people aged 65 years and older. Among cause-specific diseases, we observed the greatest life expectancy loss in pneumonia (1.5 years), followed by ischaemic heart disease (1.2 years), COPD (1.1 years), and stroke (0.3 years). Between two periods of 2000-2007 and 2008-2016, cold-related life expectancy loss due to cardiovascular disease did not decrease and cold-related life expectancy loss due to respiratory disease even increased by five times. Our findings suggest an urgent need to develop prevention measures against adverse cold effects on cardiorespiratory disease in Hong Kong.
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Affiliation(s)
- Jian Cheng
- School of Public Health, Department of Epidemiology and Biostatistics, Anhui Medical University, 81 Meishan Road, 230022, Hefei, China; Anhui Province Key Laboratory of Major Autoimmune Disease, 81 Meishan Road, 230022, Hefei, China
| | - Hung Chak Ho
- Department of Urban Planning and Design, The University of Hong Kong, Hong Kong, China; School of Geography and Remote Sensing, Guangzhou University, Guangzhou, China
| | - Hong Su
- School of Public Health, Department of Epidemiology and Biostatistics, Anhui Medical University, 81 Meishan Road, 230022, Hefei, China; Anhui Province Key Laboratory of Major Autoimmune Disease, 81 Meishan Road, 230022, Hefei, China
| | - Cunrui Huang
- School of Public Health, Sun Yat-sen University, 74 Zhongshan 2nd Rd., Guangzhou, 510080, China
| | - Rubing Pan
- School of Public Health, Department of Epidemiology and Biostatistics, Anhui Medical University, 81 Meishan Road, 230022, Hefei, China; Anhui Province Key Laboratory of Major Autoimmune Disease, 81 Meishan Road, 230022, Hefei, China
| | - Mohammad Zahid Hossain
- International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh
| | - Hao Zheng
- Department of Environmental Health, Jiangsu Provincial Center for Disease Control and Prevention, 172 Jiangsu Road, 210009, Nanjing, China
| | - Zhiwei Xu
- School of Public Health, Faculty of Medicine, University of Queensland, 288 Herston Road, Herston, Brisbane, Queensland, 4006, Australia.
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