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The influence of meteorological factors and total malignant tumor health risk in Wuhu city in the context of climate change. BMC Public Health 2023; 23:346. [PMID: 36797719 PMCID: PMC9933274 DOI: 10.1186/s12889-023-15200-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 02/02/2023] [Indexed: 02/18/2023] Open
Abstract
With the increasing severity of the malignant tumors situation worldwide, the impacts of climate on them are receiving increasing attention. In this study, for the first time, all-malignant tumors were used as the dependent variable and absolute humidity (AH) was innovatively introduced into the independent variable to investigate the relationship between all-malignant tumors and meteorological factors. A total of 42,188 cases of malignant tumor deaths and meteorological factors in Wuhu City were collected over a 7-year (2014-2020) period. The analysis method combines distributed lagged nonlinear modeling (DLNM) as well as generalized additive modeling (GAM), with prior pre-analysis using structural equation modeling (SEM). The results showed that AH, temperature mean (T mean) and diurnal temperature range (DTR) all increased the malignant tumors mortality risk. Exposure to low and exceedingly low AH increases the malignant tumors mortality risk with maximum RR values of 1.008 (95% CI: 1.001, 1.015, lag 3) and 1.016 (95% CI: 1.001, 1.032, lag 1), respectively. In addition, low and exceedingly low T mean exposures also increased the risk of malignant tumors mortality, the maximum RR was 1.020 (95% CI: 1.006, 1.034) for low T mean and 1.035 (95% CI: 1.014, 1.058) for exceedingly low T mean. As for DTR, all four levels (exceedingly low, low, high, exceedingly high, from low to high) of exposure increased the risk of death from malignant tumors, from exceedingly low to exceedingly high maximum RR values of 1.018 (95% CI: 1.004, 1.032), 1.011 (95% CI: 1.005, 1.017), 1.006 (95% CI: 1.001, 1.012) and 1.019 (95% CI: 1.007, 1.031), respectively. The results of the stratified analysis suggested that female appear to be more sensitive to humidity, while male require additional attention to reduce exposure to high level of DTR.
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Liu J, Liu T, Burkart KG, Wang H, He G, Hu J, Xiao J, Yin P, Wang L, Liang X, Zeng F, Stanaway JD, Brauer M, Ma W, Zhou M. Mortality burden attributable to high and low ambient temperatures in China and its provinces: Results from the Global Burden of Disease Study 2019. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2022; 24:100493. [PMID: 35756888 PMCID: PMC9213765 DOI: 10.1016/j.lanwpc.2022.100493] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
BACKGROUND Non-optimal temperatures are associated with mortality risk, yet the heterogeneity of temperature-attributable mortality burden across subnational regions in a country was rarely investigated. We estimated the mortality burden related to non-optimal temperatures across all provinces in China in 2019. METHODS The global daily temperature data were obtained from the ERA5 reanalysis dataset. The daily mortality data and exposure-response curves between daily temperature and mortality for 176 individual causes of death were obtained from the Global Burden of Disease Study 2019 (GBD 2019). We estimated the population attributable fraction (PAF) based on the exposure-response curves, daily gridded temperature, and population. We calculated the cause- and province-specific mortality burden based on PAF and disease burden data from the GBD 2019. FINDINGS We estimated that 593·9 (95% UI:498·8, 704·6) thousand deaths were attributable to non-optimal temperatures in China in 2019 (PAF=5·58% [4·93%, 6·28%]), with 580·8 (485·7, 690·1) thousand cold-related deaths and 13·9 (7·7, 23·2) thousand heat-related deaths. The majority of temperature-related deaths were from cardiovascular diseases (399·7 [322·8, 490·4] thousand) and chronic respiratory diseases (177·4 [141·4, 222·3] thousand). The mortality burdens were observed significantly spatial heterogeneity for both high and low temperatures. For instance, the age-standardized death rates (per 100 000) attributable to low temperature were higher in Western China, with the highest in Tibet (113·7 [82·0, 155·5]), while for high temperature, they were greater in Xinjiang (1·8 [0·7, 3·3]) and Central-Southern China such as Hainan (2·5 [0·9, 5·4]). We also observed considerable geographical variation in the temperature-related mortality burden by causes of death at provincial level. INTERPRETATION A substantial mortality burden was attributable to non-optimal temperatures across China, and cold effects dominated the total mortality burden in all provinces. Both cold- and heat-related mortality burden showed significantly spatial variations across China. FUNDING National Key Research and Development Program.
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Affiliation(s)
- Jiangmei Liu
- The National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention
| | - Tao Liu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Katrin G. Burkart
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - Haidong Wang
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - Guanhao He
- Guangdong Provincial Institute of Public Health, 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
| | - Peng Yin
- The National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention
| | - Lijun Wang
- The National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention
| | - Xiaofeng Liang
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Fangfang Zeng
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Jeffrey D. Stanaway
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - Michael Brauer
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
- School of Population and Public Health, The University of British Columbia, Vancouver, BC, Canada
| | - Wenjun Ma
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
- Prof Wenjun Ma, Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, No.601 West, Huangpu Road, Tianhe District, Guangzhou 510632, China.
| | - Maigeng Zhou
- The National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention
- Correspondence to: Prof Maigeng Zhou, The National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention 27 Nanwei Road, Xicheng District, Beijing, 100050, China.
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Burkart KG, Brauer M, Aravkin AY, Godwin WW, Hay SI, He J, Iannucci VC, Larson SL, Lim SS, Liu J, Murray CJL, Zheng P, Zhou M, Stanaway JD. Estimating the cause-specific relative risks of non-optimal temperature on daily mortality: a two-part modelling approach applied to the Global Burden of Disease Study. Lancet 2021; 398:685-697. [PMID: 34419204 PMCID: PMC8387975 DOI: 10.1016/s0140-6736(21)01700-1] [Citation(s) in RCA: 180] [Impact Index Per Article: 45.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Revised: 07/15/2021] [Accepted: 07/20/2021] [Indexed: 01/07/2023]
Abstract
BACKGROUND Associations between high and low temperatures and increases in mortality and morbidity have been previously reported, yet no comprehensive assessment of disease burden has been done. Therefore, we aimed to estimate the global and regional burden due to non-optimal temperature exposure. METHODS In part 1 of this study, we linked deaths to daily temperature estimates from the ERA5 reanalysis dataset. We modelled the cause-specific relative risks for 176 individual causes of death along daily temperature and 23 mean temperature zones using a two-dimensional spline within a Bayesian meta-regression framework. We then calculated the cause-specific and total temperature-attributable burden for the countries for which daily mortality data were available. In part 2, we applied cause-specific relative risks from part 1 to all locations globally. We combined exposure-response curves with daily gridded temperature and calculated the cause-specific burden based on the underlying burden of disease from the Global Burden of Diseases, Injuries, and Risk Factors Study, for the years 1990-2019. Uncertainty from all components of the modelling chain, including risks, temperature exposure, and theoretical minimum risk exposure levels, defined as the temperature of minimum mortality across all included causes, was propagated using posterior simulation of 1000 draws. FINDINGS We included 64·9 million individual International Classification of Diseases-coded deaths from nine different countries, occurring between Jan 1, 1980, and Dec 31, 2016. 17 causes of death met the inclusion criteria. Ischaemic heart disease, stroke, cardiomyopathy and myocarditis, hypertensive heart disease, diabetes, chronic kidney disease, lower respiratory infection, and chronic obstructive pulmonary disease showed J-shaped relationships with daily temperature, whereas the risk of external causes (eg, homicide, suicide, drowning, and related to disasters, mechanical, transport, and other unintentional injuries) increased monotonically with temperature. The theoretical minimum risk exposure levels varied by location and year as a function of the underlying cause of death composition. Estimates for non-optimal temperature ranged from 7·98 deaths (95% uncertainty interval 7·10-8·85) per 100 000 and a population attributable fraction (PAF) of 1·2% (1·1-1·4) in Brazil to 35·1 deaths (29·9-40·3) per 100 000 and a PAF of 4·7% (4·3-5·1) in China. In 2019, the average cold-attributable mortality exceeded heat-attributable mortality in all countries for which data were available. Cold effects were most pronounced in China with PAFs of 4·3% (3·9-4·7) and attributable rates of 32·0 deaths (27·2-36·8) per 100 000 and in New Zealand with 3·4% (2·9-3·9) and 26·4 deaths (22·1-30·2). Heat effects were most pronounced in China with PAFs of 0·4% (0·3-0·6) and attributable rates of 3·25 deaths (2·39-4·24) per 100 000 and in Brazil with 0·4% (0·3-0·5) and 2·71 deaths (2·15-3·37). When applying our framework to all countries globally, we estimated that 1·69 million (1·52-1·83) deaths were attributable to non-optimal temperature globally in 2019. The highest heat-attributable burdens were observed in south and southeast Asia, sub-Saharan Africa, and North Africa and the Middle East, and the highest cold-attributable burdens in eastern and central Europe, and central Asia. INTERPRETATION Acute heat and cold exposure can increase or decrease the risk of mortality for a diverse set of causes of death. Although in most regions cold effects dominate, locations with high prevailing temperatures can exhibit substantial heat effects far exceeding cold-attributable burden. Particularly, a high burden of external causes of death contributed to strong heat impacts, but cardiorespiratory diseases and metabolic diseases could also be substantial contributors. Changes in both exposures and the composition of causes of death drove changes in risk over time. Steady increases in exposure to the risk of high temperature are of increasing concern for health. FUNDING Bill & Melinda Gates Foundation.
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Affiliation(s)
- Katrin G Burkart
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.
| | - Michael Brauer
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA; School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada
| | - Aleksandr Y Aravkin
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - William W Godwin
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Simon I Hay
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - Jaiwei He
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Vincent C Iannucci
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Samantha L Larson
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Stephen S Lim
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - Jiangmei Liu
- Non-Communicable Disease Center, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Christopher J L Murray
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - Peng Zheng
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - Maigeng Zhou
- Non-Communicable Disease Center, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jeffrey D Stanaway
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
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Dimitrova A, Ingole V, Basagaña X, Ranzani O, Milà C, Ballester J, Tonne C. Association between ambient temperature and heat waves with mortality in South Asia: Systematic review and meta-analysis. ENVIRONMENT INTERNATIONAL 2021; 146:106170. [PMID: 33395923 DOI: 10.1016/j.envint.2020.106170] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 09/16/2020] [Accepted: 09/26/2020] [Indexed: 06/12/2023]
Abstract
BACKGROUND South Asia is highly vulnerable to climate change and is projected to experience some of the highest increases in average annual temperatures throughout the century. Although the adverse impacts of ambient temperature on human health have been extensively documented in the literature, only a limited number of studies have focused on populations in this region. OBJECTIVES Our aim was to systematically review the current state and quality of available evidence on the direct relationship between ambient temperature and heat waves and all-cause mortality in South Asia. METHODS The databases Pubmed, Web of Science, Scopus and Embase were searched from 1990 to 2020 for relevant observational quantitative studies. We applied the Navigation Guide methodology to assess the strength of the evidence and performed a meta-analysis based on a novel approach that allows for combining nonlinear exposure-response associations without access to data from individual studies. RESULTS From the 6,759 screened papers, 27 were included in the qualitative synthesis and five in a meta-analysis. Studies reported an association of all-cause mortality with heat wave episodes and both high and low daily temperatures. The meta-analysis showed a U-shaped pattern, with increasing mortality for both high and low temperatures, but a statistically significant association was found only at higher temperatures - above 31° C for lag 0-1 days and above 34° C for lag 0-13 days. Effects were found to vary with cause of death, age, sex, location (urban vs. rural), level of education and socio-economic status, but the profile of vulnerabilities was somewhat inconsistent and based on a limited number of studies. Overall, the strength of the evidence for ambient temperature as a risk factor for all-cause mortality was judged as limited and for heat wave episodes as inadequate. CONCLUSIONS The evidence base on temperature impacts on mortality in South Asia is limited due to the small number of studies, their skewed geographical distribution and methodological weaknesses. Understanding the main determinants of the temperature-mortality association as well as how these may evolve in the future in a dynamic region such as South Asia will be an important area for future research. Studies on viable adaptation options to high temperatures for a region that is a hotspot for climate vulnerability, urbanisation and population growth are also needed.
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Affiliation(s)
- Asya Dimitrova
- Barcelona Institute for Global Health (ISGlobal), Barcelona Biomedical Research Park (PRBB), Doctor Aiguader, 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Plaça de la Mercè, 10, 08002 Barcelona, Spain; CIBER Epidemiología y Salud Pública, Avda. Monforte de Lemos 3-5, Madrid, Spain
| | - Vijendra Ingole
- Barcelona Institute for Global Health (ISGlobal), Barcelona Biomedical Research Park (PRBB), Doctor Aiguader, 88, 08003 Barcelona, Spain; CIBER Epidemiología y Salud Pública, Avda. Monforte de Lemos 3-5, Madrid, Spain
| | - Xavier Basagaña
- Barcelona Institute for Global Health (ISGlobal), Barcelona Biomedical Research Park (PRBB), Doctor Aiguader, 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Plaça de la Mercè, 10, 08002 Barcelona, Spain; CIBER Epidemiología y Salud Pública, Avda. Monforte de Lemos 3-5, Madrid, Spain
| | - Otavio Ranzani
- Barcelona Institute for Global Health (ISGlobal), Barcelona Biomedical Research Park (PRBB), Doctor Aiguader, 88, 08003 Barcelona, Spain; CIBER Epidemiología y Salud Pública, Avda. Monforte de Lemos 3-5, Madrid, Spain
| | - Carles Milà
- Barcelona Institute for Global Health (ISGlobal), Barcelona Biomedical Research Park (PRBB), Doctor Aiguader, 88, 08003 Barcelona, Spain; CIBER Epidemiología y Salud Pública, Avda. Monforte de Lemos 3-5, Madrid, Spain
| | - Joan Ballester
- Barcelona Institute for Global Health (ISGlobal), Barcelona Biomedical Research Park (PRBB), Doctor Aiguader, 88, 08003 Barcelona, Spain; CIBER Epidemiología y Salud Pública, Avda. Monforte de Lemos 3-5, Madrid, Spain
| | - Cathryn Tonne
- Barcelona Institute for Global Health (ISGlobal), Barcelona Biomedical Research Park (PRBB), Doctor Aiguader, 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Plaça de la Mercè, 10, 08002 Barcelona, Spain; CIBER Epidemiología y Salud Pública, Avda. Monforte de Lemos 3-5, Madrid, Spain.
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Tang J, Xiao CC, Li YR, Zhang JQ, Zhai HY, Geng XY, Ding R, Zhai JX. Effects of diurnal temperature range on mortality in Hefei city, China. INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 2018; 62:851-860. [PMID: 29224119 DOI: 10.1007/s00484-017-1486-y] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2017] [Revised: 11/23/2017] [Accepted: 11/29/2017] [Indexed: 06/07/2023]
Abstract
Although several studies indicated an association between diurnal temperature range (DTR) and mortality, the results about modifiers are inconsistent, and few studies were conducted in developing inland country. This study aims to evaluate the effects of DTR on cause-specific mortality and whether season, gender, or age might modify any association in Hefei city, China, during 2007-2016. Quasi-Poisson generalized linear regression models combined with a distributed lag non-linear model (DLNM) were applied to evaluate the relationships between DTR and non-accidental, cardiovascular, and respiratory mortality. We observed a J-shaped relationship between DTR and cause-specific mortality. With a DTR of 8.3 °C as the reference, the cumulative effects of extremely high DTR were significantly higher for all types of mortality than effects of lower or moderate DTR in full year. When stratified by season, extremely high DTR in spring had a greater impact on all cause-specific mortality than other three seasons. Male and the elderly (≥ 65 years) were consistently more susceptible to extremely high DTR effect than female and the youth (< 65 years) for non-accidental and cardiovascular mortality. To the contrary, female and the youth were more susceptible to extremely high DTR effect than male and the elderly for respiratory morality. The study suggests that extremely high DTR is a potential trigger for non-accidental mortality in Hefei city, China. Our findings also highlight the importance of protecting susceptible groups from extremely high DTR especially in the spring.
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Affiliation(s)
- Jing Tang
- Department of Occupational and Environmental Health, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui Province, 230032, China
| | - Chang-Chun Xiao
- Hefei Center for Disease Control and Prevention, 86 Luan Road, Hefei, Anhui Province, 230032, China
| | - Yu-Rong Li
- Zhejiang Provincial Center for Disease Control and Prevention, 3399 Bin Sheng Road, Hangzhou, Zhejiang Province, 310021, China
| | - Jun-Qing Zhang
- Hefei Center for Disease Control and Prevention, 86 Luan Road, Hefei, Anhui Province, 230032, China
| | - Hao-Yuan Zhai
- School of Clinical Medicine, Wannan Medical College, 22 Wenchang West Road, Wuhu, Anhui Province, 241000, China
| | - Xi-Ya Geng
- Department of Occupational and Environmental Health, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui Province, 230032, China
| | - Rui Ding
- Department of Occupational and Environmental Health, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui Province, 230032, China
| | - Jin-Xia Zhai
- Department of Occupational and Environmental Health, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui Province, 230032, China.
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