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Huang HN, Li X, Peng Z, Liao YF, Li L, Nardocci AC, Ou CQ, Yang Z. Mortality risk and burden of aortic aneurysm and dissection attributable to low temperatures: A nationwide case-crossover analysis in Brazil, a predominantly tropical country. ENVIRONMENT INTERNATIONAL 2024; 190:108895. [PMID: 39059022 DOI: 10.1016/j.envint.2024.108895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Revised: 06/05/2024] [Accepted: 07/17/2024] [Indexed: 07/28/2024]
Abstract
BACKGROUND Low temperatures are adverse contributors to cardiovascular diseases, but the associations between short-term exposure to cold and the risk of death from aortic dissection and aneurysm remain unclear, particularly in tropical regions. OBJECTIVE This study was conducted based on 123,951 records of deaths caused by aortic dissection and aneurysms extracted from the national Mortality Information System in Brazil between 2000 and 2019. METHODS Relative risks and 95 % confidence intervals (CI) for the aortic-related deaths associated with low ambient temperatures were estimated using the conditional logistic model combined with the distributed lag nonlinear model. Subgroup analyses were performed by age group, sex, race, education level, and residential region. Furthermore, this study calculated the number and fraction of aortic-related deaths attributed to temperatures below the temperature threshold to quantify the cold-related mortality burden of aortic diseases. RESULTS During the study period, aortic-related deaths and mortality rates in Brazil exhibited a steady increase, rising from 4419 (2.66/100,000) in 2000 to 8152 (3.88/100,000) in 2019. Under the identified temperature threshold (26 °C), per 1 °C decrease in daily mean temperature was associated with a 4.77 % (95 % CI: 4.35, 5.19) increase in mortality risk of aortic-related diseases over lag 0-3 days. Females, individuals aged 50 years or older, Asian and Black race, and northern residents were more susceptible to low temperatures. Low temperatures were responsible for 19.10 % (95 % CI: 17.71, 20.45) of aortic-related deaths in Brazil. CONCLUSION This study highlights that low temperatures were associated with an increased risk of aortic-related deaths, with a remarkable burden even in this predominantly tropical country.
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Affiliation(s)
- Hao-Neng Huang
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Xin Li
- Department of Emergency Medicine, Guangdong Provincial People's Hospital, (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Zhen Peng
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Yi-Fu Liao
- Department of Neurology, Guangdong Provincial People's Hospital, (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Li Li
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Adelaide C Nardocci
- Department of Environmental Health, School of Public Health, University of São Paulo, São Paulo, Brazil
| | - Chun-Quan Ou
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China; Department of Emergency Medicine, Guangdong Provincial People's Hospital, (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
| | - Zhou Yang
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China.
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Wen B, Wu Y, Guo Y, Gasparrini A, Tong S, Overcenco A, Urban A, Schneider A, Entezari A, Vicedo-Cabrera AM, Zanobetti A, Analitis A, Zeka A, Tobias A, Nunes B, Alahmad B, Armstrong B, Forsberg B, Pan SC, Íñiguez C, Ameling C, Valencia CDLC, Åström C, Houthuijs D, Van Dung D, Royé D, Indermitte E, Lavigne E, Mayvaneh F, Acquaotta F, de'Donato F, Rao S, Sera F, Carrasco-Escobar G, Kan H, Orru H, Kim H, Holobaca IH, Kyselý J, Madureira J, Schwartz J, Jaakkola JJK, Katsouyanni K, Diaz MH, Ragettli MS, Hashizume M, Pascal M, Coélho MDSZS, Ortega NV, Ryti N, Scovronick N, Michelozzi P, Matus Correa P, Goodman P, Saldiva PHN, Raz R, Abrutzky R, Osorio S, Dang TN, Colistro V, Huber V, Lee W, Seposo X, Honda Y, Kim Y, Guo YL, Bell ML, Li S. Comparison for the effects of different components of temperature variability on mortality: A multi-country time-series study. ENVIRONMENT INTERNATIONAL 2024; 187:108712. [PMID: 38714028 DOI: 10.1016/j.envint.2024.108712] [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: 11/23/2023] [Revised: 04/27/2024] [Accepted: 04/28/2024] [Indexed: 05/09/2024]
Abstract
BACKGROUND Temperature variability (TV) is associated with increased mortality risk. However, it is still unknown whether intra-day or inter-day TV has different effects. OBJECTIVES We aimed to assess the association of intra-day TV and inter-day TV with all-cause, cardiovascular, and respiratory mortality. METHODS We collected data on total, cardiovascular, and respiratory mortality and meteorology from 758 locations in 47 countries or regions from 1972 to 2020. We defined inter-day TV as the standard deviation (SD) of daily mean temperatures across the lag interval, and intra-day TV as the average SD of minimum and maximum temperatures on each day. In the first stage, inter-day and intra-day TVs were modelled simultaneously in the quasi-Poisson time-series model for each location. In the second stage, a multi-level analysis was used to pool the location-specific estimates. RESULTS Overall, the mortality risk due to each interquartile range [IQR] increase was higher for intra-day TV than for inter-day TV. The risk increased by 0.59% (95% confidence interval [CI]: 0.53, 0.65) for all-cause mortality, 0.64% (95% CI: 0.56, 0.73) for cardiovascular mortality, and 0.65% (95% CI: 0.49, 0.80) for respiratory mortality per IQR increase in intra-day TV0-7 (0.9 °C). An IQR increase in inter-day TV0-7 (1.6 °C) was associated with 0.22% (95% CI: 0.18, 0.26) increase in all-cause mortality, 0.44% (95% CI: 0.37, 0.50) increase in cardiovascular mortality, and 0.31% (95% CI: 0.21, 0.41) increase in respiratory mortality. The proportion of all-cause deaths attributable to intra-day TV0-7 and inter-day TV0-7 was 1.45% and 0.35%, respectively. The mortality risks varied by lag interval, climate area, season, and climate type. CONCLUSIONS Our results indicated that intra-day TV may explain the main part of the mortality risk related to TV and suggested that comprehensive evaluations should be proposed in more countries to help protect human health.
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Affiliation(s)
- Bo Wen
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yao Wu
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yuming Guo
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
| | - Antonio Gasparrini
- Department of Public Health, Environments and Society, London School of Hygiene & Tropical Medicine, London, UK; Centre for Statistical Methodology, London School of Hygiene & Tropical Medicine, London, UK; Centre on Climate Change & Planetary Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Shilu Tong
- Shanghai Children's Medical Centre, Shanghai Jiao Tong University, Shanghai, China; School of Public Health, Institute of Environment and Population Health, Anhui Medical University, Hefei, China; Center for Global Health, Nanjing Medical University, Nanjing, China; School of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia
| | - Ala Overcenco
- National Agency for Public Health of the Ministry of Health, Labour and Social Protection of the Republic of Moldova, Republic of Moldova
| | - Aleš Urban
- Institute of Atmospheric Physics, Czech Academy of Sciences, Prague, Czech Republic; Faculty of Environmental Sciences, Czech University of Life Sciences, Prague, Czech Republic
| | - Alexandra Schneider
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Alireza Entezari
- Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar, Iran
| | - Ana Maria Vicedo-Cabrera
- Department of Public Health, Environments and Society, London School of Hygiene & Tropical Medicine, London, UK; Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland; Oeschger Center for Climate Change Research, University of Bern, Bern, Switzerland
| | - Antonella Zanobetti
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Antonis Analitis
- Department of Hygiene, Epidemiology and Medical Statistics, National and Kapodistrian University of Athens, Athens, Greece
| | - Ariana Zeka
- Institute for Environment, Health and Societies, Brunel University London, London, UK
| | - Aurelio Tobias
- Institute of Environmental Assessment and Water Research, Spanish Council for Scientific Research, Barcelona, Spain; School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan
| | - Baltazar Nunes
- Department of Epidemiology, Instituto Nacional de Saúde Dr Ricardo Jorge, Porto, Portugal; Centro de Investigação em Saúde Pública, Escola Nacional de Saúde Pública, Universidade NOVA de Lisboa, Lisbon, Portugal
| | - Barrak Alahmad
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Ben Armstrong
- Department of Public Health, Environments and Society, London School of Hygiene & Tropical Medicine, London, UK
| | - Bertil Forsberg
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Shih-Chun Pan
- National Institute of Environmental Health Science, National Health Research Institutes, Zhunan, Taiwan
| | - Carmen Íñiguez
- Department of Statistics and Computational Research, Universitat de València, València, Spain; CIBER of Epidemiology and Public Health, Madrid, Spain
| | - Caroline Ameling
- National Institute for Public Health and the Environment (RIVM), Centre for Sustainability and Environmental Health, Bilthoven, Netherlands
| | | | - Christofer Åström
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Danny Houthuijs
- National Institute for Public Health and the Environment (RIVM), Centre for Sustainability and Environmental Health, Bilthoven, Netherlands
| | - Do Van Dung
- Department of Environmental Health, Faculty of Public Health, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Viet Nam
| | - Dominic Royé
- CIBER of Epidemiology and Public Health, Madrid, Spain; Department of Geography, University of Santiago de Compostela, Santiago de Compostela, Spain
| | - Ene Indermitte
- Institute of Family Medicine and Public Health, University of Tartu, Tartu, Estonia
| | - Eric Lavigne
- School of Epidemiology & Public Health, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada; Air Health Science Division, Health Canada, Ottawa, ON, Canada
| | - Fatemeh Mayvaneh
- Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar, Iran
| | | | | | - Shilpa Rao
- Norwegian Institute of Public Health, Oslo, Norway
| | - Francesco Sera
- Department of Statistics, Computer Science and Applications "G. Parenti", University of Florence, Florence, Italy
| | - Gabriel Carrasco-Escobar
- Health Innovation Lab, Institute of Tropical Medicine "Alexander von Humboldt", Universidad Peruana Cayetano Heredia, Lima, Peru; Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA
| | - Haidong Kan
- Department of Environmental Health, School of Public Health, Fudan University, Shanghai, China
| | - Hans Orru
- Institute of Family Medicine and Public Health, University of Tartu, Tartu, Estonia
| | - Ho Kim
- Graduate School of Public Health, Seoul National University, Seoul, South Korea
| | | | - Jan Kyselý
- Institute of Atmospheric Physics, Czech Academy of Sciences, Prague, Czech Republic; Faculty of Environmental Sciences, Czech University of Life Sciences, Prague, Czech Republic
| | - Joana Madureira
- Environmental Health Department, Instituto Nacional de Saúde Dr Ricardo Jorge, Porto, Portugal; EPIUnit - Instituto de Saúde Pública, Universidade do Porto, Porto, Portugal; Laboratório para a Investigação Integrativa e Translacional em Saúde Populacional (ITR), Porto, Portugal
| | - Joel Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Jouni J K Jaakkola
- Center for Environmental and Respiratory Health Research (CERH), University of Oulu, Oulu, Finland; Medical Research Center Oulu (MRC Oulu), Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Klea Katsouyanni
- Department of Hygiene, Epidemiology and Medical Statistics, National and Kapodistrian University of Athens, Athens, Greece; School of Population Health and Environmental Sciences, King's College London, London, UK
| | - Magali Hurtado Diaz
- Department of Environmental Health, National Institute of Public Health, Cuernavaca Morelos, Mexico
| | - Martina S Ragettli
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Masahiro Hashizume
- Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Mathilde Pascal
- Santé Publique France, Department of Environmental and Occupational Health, French National Public Health Agency, Saint Maurice, France
| | | | | | - Niilo Ryti
- Center for Environmental and Respiratory Health Research (CERH), University of Oulu, Oulu, Finland; Medical Research Center Oulu (MRC Oulu), Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Noah Scovronick
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Paola Michelozzi
- Department of Epidemiology, Lazio Regional Health Service, Rome, Italy
| | | | - Patrick Goodman
- School of Physics, Technological University Dublin, Dublin, Ireland
| | | | - Raanan Raz
- Braun School of Public Health and Community Medicine, The Hebrew University of Jerusalem, Israel
| | - Rosana Abrutzky
- Universidad de Buenos Aires, Facultad de Ciencias Sociales, Instituto de Investigaciones Gino Germani, Buenos Aires, Argentina
| | - Samuel Osorio
- Department of Environmental Health, University of São Paulo, São Paulo, Brazil
| | - Tran Ngoc Dang
- Department of Environmental Health, Faculty of Public Health, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Viet Nam
| | - Valentina Colistro
- Department of Quantitative Methods, School of Medicine, University of the Republic, Montevideo, Uruguay
| | - Veronika Huber
- IBE-Chair of Epidemiology, LMU Munich, Munich, Germany; Department of Physical, Chemical and Natural Systems, Universidad Pablo de Olavide, Sevilla, Spain
| | - Whanhee Lee
- School of the Environment, Yale University, New Haven, CT, USA; Department of Occupational and Environmental Medicine, School of Medicine, Ewha Womans University, Seoul, South Korea
| | - Xerxes Seposo
- School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan
| | - Yasushi Honda
- Center for Climate Change Adaptation, National Institute for Environmental Studies, Tsukuba, Japan
| | - Yoonhee Kim
- Department of Global Environmental Health, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Yue Leon Guo
- National Institute of Environmental Health Science, National Health Research Institutes, Zhunan, Taiwan; Environmental and Occupational Medicine, National Taiwan University College of Medicine and NTU Hospital, National Taiwan University, Taipei, Taiwan; Graduate Institute of Environmental and Occupational Health Sciences, National Taiwan University College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Michelle L Bell
- School of the Environment, Yale University, New Haven, CT, USA
| | - Shanshan Li
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
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Yin B, Fang W, Liu L, Guo Y, Ma X, Di Q. Effect of extreme high temperature on cognitive function at different time scales: A national difference-in-differences analysis. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 275:116238. [PMID: 38518609 DOI: 10.1016/j.ecoenv.2024.116238] [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: 12/06/2023] [Revised: 03/14/2024] [Accepted: 03/16/2024] [Indexed: 03/24/2024]
Abstract
BACKGROUND Mounting evidence has demonstrated that high temperature was associated with adverse health outcomes, especially morbidity and mortality. Nonetheless, the impact of extreme high temperature on cognitive performance, which is the fundamental capacity for interpreting one's surroundings, decision-making, and acquiring new abilities, has not been thoroughly investigated. METHODS We aimed to assess associations between extreme high temperature at different time scales and poor cognitive function. We used longitudinal survey data from the three waves of data from China Family Panel Study, providing an 8-year follow-up of 53,008 participants from China. We assessed temperature and extreme high temperature exposure for each participant based on the residential area and date of cognitive test. We defined the proportion of days/hours above 32 °C as the metric of the exposure to extreme high temperature. Then we used generalized additive model and difference-in-differences approach to explore the associations between extreme high temperature and cognitive function. RESULTS Our results demonstrated that either acute exposure or long-term exposure to extreme high temperature was associated with cognitive decline. At hourly level, 0-1 hour acute exposure to extreme high temperature would induce -0.93 % (95 % CI: -1.46 %, -0.39 %) cognitive change. At annual level, 10 percentage point increase in the hours proportion exceeding 32 °C in the past two years induced -9.87 % (95 % CI: -13.99 %, -5.75 %) cognitive change. Furthermore, subgroup analyses indicated adaptation effect: for the same 10 percentage increase in hours proportion exceeding 32 °C, people in warmer areas had cognitive change of -6.41 % (-11.22 %, -1.61 %), compared with -15.30 % (-21.07 %, -9.53 %) for people in cool areas. CONCLUSION Our results demonstrated that extreme high temperature was associated with reduced cognitive function at hourly, daily and annual levels, warning that people should take better measures to protect the cognitive function in the context of climate change.
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Affiliation(s)
- Bo Yin
- School of Medicine, Tsinghua University, Beijing 100084, China
| | - Wen Fang
- Division of Sports Science & Physical Education, Tsinghua University, Beijing 100084, China
| | - Linfeng Liu
- School of Medicine, Tsinghua University, Beijing 100084, China
| | - Yuming Guo
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Xindong Ma
- Division of Sports Science & Physical Education, Tsinghua University, Beijing 100084, China; IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China
| | - Qian Di
- Vanke School of Public Health, Tsinghua University, Beijing 100084, China; Institute for Healthy China, Tsinghua University, Beijing 100084, China.
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Guo J, Xue T, Cao M, Han X, Pan Z, Huang D, Sun W, Mi J, Liu Y, Guan T. Ambient temperature anomalies induce electrocardiogram abnormalities: Findings from a nationwide longitudinal study. ENVIRONMENTAL RESEARCH 2024; 246:117996. [PMID: 38128602 DOI: 10.1016/j.envres.2023.117996] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 12/02/2023] [Accepted: 12/19/2023] [Indexed: 12/23/2023]
Abstract
Electrocardiogram (ECG) outcomes serve as early manifestations of cardiovascular functional or structural changes. While temperature fluctuation has been demonstrated to be a risk factor for cardiovascular diseases, few epidemiological studies have reported its relationship with ECG outcomes. In this study, we employed temperature anomaly (TA) as an innovative indicator of temperature fluctuation to quantify its detrimental impacts on ECG outcomes. A longitudinal study design was conducted using the repeated ECG records of the China National Stroke Screening Survey from 2013 to 2019. Only individuals undergoing at least two ECG tests were included. The daily temperature was assimilated by combining three kinds of data: in situ observations, satellite remote sensing measurements and weather research forecast simulations. We used generalized estimating equations to control for autocorrelation among repeated records and to estimate the association between TA and the risk of ECG abnormalities. We found 6837 events of ECG abnormalities in 47,286 individuals with 102,030 visits. Each unit increment of TA increased the risk of ECG abnormalities [odds ratio (OR) = 1.009, 95% confidence interval (CI): 1.001-1.017] and the risk of myocardial ischemia (OR = 1.061, 95% CI: 1.012-1.111). Hierarchic analyses presented a similar association of TA with both ECG abnormalities (OR = 1.017, 95% CI: 1.008-1.026) and myocardial ischemia (OR = 1.061, 95%CI: 1.011-1.114) in Northern China, but not in Southern China. The exposure-response relationship was estimated as a U-shaped curve centered at the TA value of zero. Sudden warming tended to increase the risk of ECG abnormalities and myocardial ischemia, and sudden cooling tended to increase the risk of atrial fibrillation. All these detrimental effects of TA could be modified by specific individual characteristics. In summary, ambient temperature fluctuation increased the risk of ECG abnormalities. This result indicated that regular ECG tests could be an early-warning measure for monitoring the adverse health effects of temperature fluctuations.
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Affiliation(s)
- Jian Guo
- State Key Laboratory for Complex, Severe, and Rare Diseases, Peking Union Medical College Hospital, Beijing, 100730, China; Department of Cardiology, Peking Union Medical College Hospital, Beijing, 100730, China
| | - Tao Xue
- Department of Epidemiology and Biostatistics/Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, Peking University Health Science Centre, Beijing, 100191, China; State Environmental Protection Key Laboratory of Atmospheric Exposure and Health Risk Management, Center for Environment and Health, Peking University, Beijing, 100871, China; Advanced Institute of Information Technology, Peking University, Hangzhou, China.
| | - Man Cao
- School of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 10005, China
| | - Xueyan Han
- School of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 10005, China
| | - Zhaoyang Pan
- School of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 10005, China
| | - Dengmin Huang
- School of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 10005, China
| | - Wei Sun
- School of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 10005, China
| | - Jiarun Mi
- School of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 10005, China
| | - Yuanli Liu
- School of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 10005, China
| | - Tianjia Guan
- School of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 10005, China.
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Yang Z, Liu J, Yang J, Li L, Xiao T, Zhou M, Ou CQ. Haze weather and mortality in China from 2014 to 2020: Definitions, vulnerability, and effect modification by haze characteristics. JOURNAL OF HAZARDOUS MATERIALS 2024; 466:133561. [PMID: 38295725 DOI: 10.1016/j.jhazmat.2024.133561] [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: 11/11/2023] [Revised: 12/26/2023] [Accepted: 01/16/2024] [Indexed: 02/15/2024]
Abstract
Haze weather, characterized by low visibility due to severe air pollution, has aroused great public concern. However, haze definitions are inconclusive, and multicentre studies on the health impacts of haze are scarce. We collected data on the daily number of deaths and environmental factors in 190 Chinese cities from 2014 to 2020. The city-specific association was estimated using quasi-Poisson regression and then pooled using meta-analysis. We found a negative association between daily visibility and non-accidental deaths, and mortality risk sharply increased when visibility was < 10 km. Haze weather, defined as a daily average visibility of < 10 km without a limit for humidity, produced the best model fitness and greatest effect on mortality. A haze day was associated with an increase of 2.53% (95% confidence interval [CI]:1.96, 3.10), 2.84 (95% CI: 2.13, 3.56), and 2.99% (95% CI: 1.94, 4.04) in all non-accident, cardiovascular and respiratory mortality, respectively. Haze had the greatest effect on lung cancer mortality. The haze-associated risk of mortality increased with age. Severe haze (visibility <2 km) and damp haze (haze with relative humidity >90%) had greater health impacts. Our findings can help in the development of early warning systems and effective public health interventions for haze.
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Affiliation(s)
- Zhou Yang
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Jiangmei Liu
- National Center for Chronic and Noncommunicable Disease Control and Prevention (NCNCD), Chinese Center for Disease Control and Prevention (China CDC), Beijing 100050, China
| | - Jun Yang
- School of Public Health, Guangzhou Medical University, Guangzhou 511436, China
| | - Li Li
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Ting Xiao
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Maigeng Zhou
- National Center for Chronic and Noncommunicable Disease Control and Prevention (NCNCD), Chinese Center for Disease Control and Prevention (China CDC), Beijing 100050, China.
| | - Chun-Quan Ou
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China.
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Yan ZL, Liu WH, Long YX, Ming BW, Yang Z, Qin PZ, Ou CQ, Li L. Effects of meteorological factors on influenza transmissibility by virus type/subtype. BMC Public Health 2024; 24:494. [PMID: 38365650 PMCID: PMC10870479 DOI: 10.1186/s12889-024-17961-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Accepted: 02/02/2024] [Indexed: 02/18/2024] Open
Abstract
BACKGROUND Quantitative evidence on the impact of meteorological factors on influenza transmissibility across different virus types/subtypes is scarce, and no previous studies have reported the effect of hourly temperature variability (HTV) on influenza transmissibility. Herein, we explored the associations between meteorological factors and influenza transmissibility according to the influenza type and subtype in Guangzhou, a subtropical city in China. METHODS We collected influenza surveillance and meteorological data of Guangzhou between October 2010 and December 2019. Influenza transmissibility was measured using the instantaneous effective reproductive number (Rt). A gamma regression with a log link combined with a distributed lag non-linear model was used to assess the associations of daily meteorological factors with Rt by influenza types/subtypes. RESULTS The exposure-response relationship between ambient temperature and Rt was non-linear, with elevated transmissibility at low and high temperatures. Influenza transmissibility increased as HTV increased when HTV < around 4.5 °C. A non-linear association was observed between absolute humidity and Rt, with increased transmissibility at low absolute humidity and at around 19 g/m3. Relative humidity had a U-shaped association with influenza transmissibility. The associations between meteorological factors and influenza transmissibility varied according to the influenza type and subtype: elevated transmissibility was observed at high ambient temperatures for influenza A(H3N2), but not for influenza A(H1N1)pdm09; transmissibility of influenza A(H1N1)pdm09 increased as HTV increased when HTV < around 4.5 °C, but the transmissibility decreased with HTV when HTV < 2.5 °C and 3.0 °C for influenza A(H3N2) and B, respectively; positive association of Rt with absolute humidity was witnessed for influenza A(H3N2) even when absolute humidity was larger than 19 g/m3, which was different from that for influenza A(H1N1)pdm09 and influenza B. CONCLUSIONS Temperature variability has an impact on influenza transmissibility. Ambient temperature, temperature variability, and humidity influence the transmissibility of different influenza types/subtypes discrepantly. Our findings have important implications for improving preparedness for influenza epidemics, especially under climate change conditions.
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Affiliation(s)
- Ze-Lin Yan
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Wen-Hui Liu
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China
| | - Yu-Xiang Long
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Bo-Wen Ming
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Zhou Yang
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Peng-Zhe Qin
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China.
| | - Chun-Quan Ou
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China.
| | - Li Li
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China.
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Xia Y, Shi C, Li Y, Ruan S, Jiang X, Huang W, Chen Y, Gao X, Xue R, Li M, Sun H, Peng X, Xiang R, Chen J, Zhang L. Association between temperature and mortality: a multi-city time series study in Sichuan Basin, southwest China. Environ Health Prev Med 2024; 29:1. [PMID: 38220147 PMCID: PMC10788187 DOI: 10.1265/ehpm.23-00118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 09/30/2023] [Indexed: 01/16/2024] Open
Abstract
BACKGROUND There are few multi-city studies on the association between temperature and mortality in basin climates. This study was based on the Sichuan Basin in southwest China to assess the association of basin temperature with non-accidental mortality in the population and with the temperature-related mortality burden. METHODS Daily mortality data, meteorological and air pollution data were collected for four cities in the Sichuan Basin of southwest China. We used a two-stage time-series analysis to quantify the association between temperature and non-accidental mortality in each city, and a multivariate meta-analysis was performed to obtain the overall cumulative risk. The attributable fractions (AFs) were calculated to access the mortality burden attributable to non-optimal temperature. Additionally, we performed a stratified analyses by gender, age group, education level, and marital status. RESULTS A total of 751,930 non-accidental deaths were collected in our study. Overall, 10.16% of non-accidental deaths could be attributed to non-optimal temperatures. A majority of temperature-related non-accidental deaths were caused by low temperature, accounting for 9.10% (95% eCI: 5.50%, 12.19%), and heat effects accounted for only 1.06% (95% eCI: 0.76%, 1.33%). The mortality burden attributable to non-optimal temperatures was higher among those under 65 years old, females, those with a low education level, and those with an alternative marriage status. CONCLUSIONS Our study suggested that a significant association between non-optimal temperature and non-accidental mortality. Those under 65 years old, females, and those with a low educational level or alternative marriage status had the highest attributable burden.
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Affiliation(s)
- Yizhang Xia
- Sichuan Provincial Center for Disease Control and Prevention, No. 6, Zhongxue Road, Wuhou District, Chengdu 610041, China
- Zigong Center for Disease Control and Prevention, No. 826, Huichuan Road, Ziliujing District, Zigong 643000, China
- School of Public Health, Chengdu Medical College, No. 783, Xindu Road, Xindu District, Chengdu 610500, China
| | - Chunli Shi
- Sichuan Provincial Center for Disease Control and Prevention, No. 6, Zhongxue Road, Wuhou District, Chengdu 610041, China
| | - Yang Li
- Sichuan Provincial Center for Disease Control and Prevention, No. 6, Zhongxue Road, Wuhou District, Chengdu 610041, China
| | - Shijuan Ruan
- Sichuan Provincial Center for Disease Control and Prevention, No. 6, Zhongxue Road, Wuhou District, Chengdu 610041, China
| | - Xianyan Jiang
- Sichuan Provincial Center for Disease Control and Prevention, No. 6, Zhongxue Road, Wuhou District, Chengdu 610041, China
| | - Wei Huang
- Zigong Center for Disease Control and Prevention, No. 826, Huichuan Road, Ziliujing District, Zigong 643000, China
| | - Yu Chen
- School of Public Health, Chengdu Medical College, No. 783, Xindu Road, Xindu District, Chengdu 610500, China
| | - Xufang Gao
- Chengdu Center for Disease Control and Prevention, No. 6, Longxiang Road, Wuhou District, Chengdu 610041, China
| | - Rong Xue
- Guangyuan Center for Disease Control and Prevention, No. 996, Binhebei Road, Lizhou District, Guangyuan 628017, China
| | - Mingjiang Li
- Panzhi hua Center for Disease Control and Prevention, No. 996, Jichang Road, Dong District, Panzhi hua 617067, China
| | - Hongying Sun
- Mianyang Center for Disease Control and Prevention, No. 50, Mianxingdong Road, Gaoxin District, Mianyang 621000, China
| | - Xiaojuan Peng
- Yaan Center for Disease Control and Prevention, No. 9, Fangcao Road, Yucheng District, Yaan 625000, China
| | - Renqiang Xiang
- Fucheng Center for Disease Control and Prevention, No. 116, Changhong Road, Fucheng District, Mianyang 621000, China
| | - Jianyu Chen
- Sichuan Provincial Center for Disease Control and Prevention, No. 6, Zhongxue Road, Wuhou District, Chengdu 610041, China
| | - Li Zhang
- Sichuan Provincial Center for Disease Control and Prevention, No. 6, Zhongxue Road, Wuhou District, Chengdu 610041, China
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Amoatey P, Osborne NJ, Darssan D, Xu Z, Doan QV, Phung D. The effects of diurnal temperature range on mortality and emergency department presentations in Victoria state of Australia: A time-series analysis. ENVIRONMENTAL RESEARCH 2024; 240:117397. [PMID: 37879389 DOI: 10.1016/j.envres.2023.117397] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 07/30/2023] [Accepted: 10/11/2023] [Indexed: 10/27/2023]
Abstract
State of Victoria, Australia (SVA) has a wide variation of diurnal temperatures (DTR). DTR has been reported to be associated with risk of mortality and morbidity. We examined the association between exposure to DTR and risk of all-cause mortality and emergency department (ED) presentations in the SVA. We obtained data on daily counts of deaths and ED presentations, and weather data from 1 st January 2000─2019. We applied a quasi-Poisson time-series regression analysis to examine the association between daily DTR exposures and risk of mortality and ED presentations. The analyses were queried by age, sex, seasons, ED presentations triages, and departure status. Risk of mortality and ED presentation increased by 0.33% (95% CI: 0.24%-0.43%), and 0.094% (95% CI: 0.077%-0.11%) in relation to one degree increase in the daily DTR. The association between DTR and ED presentations was stronger in children (0-15 years) (0.38% [95% CI: 0.34%-0.42%]) and the elderly (75+ years) (0.34% [95% CI: 0.29%-0.39%]). Resuscitation, which was consistently accounted for the highest vulnerability to DTR variation, increased by 0.79% (95% CI: 0.60%-0.99%). This study suggests that the risk of mortality and ED presentations associates with the increase of DTR. Children, the elderly, and their caregivers need to be made aware of the health risk posed by DTR.
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Affiliation(s)
- Patrick Amoatey
- School of Public Health, Faculty of Medicine, The University of Queensland, Australia
| | - Nicholas J Osborne
- School of Public Health, Faculty of Medicine, The University of Queensland, Australia; School of Population Health, University of New South Wales, Sydney, NSW 2052, Australia; European Centre for Environment and Human Health (ECEHH), University of Exeter Medical School, Knowledge Spa, Royal Cornwall Hospital, Truro TR1 3HD, Cornwall, UK; Queensland Alliance for Environmental Health Sciences, The University of Queensland, Australia
| | - Darsy Darssan
- School of Public Health, Faculty of Medicine, The University of Queensland, Australia
| | - Zhiwei Xu
- School of Medicine and Dentistry, Griffith University, Australia
| | - Quang-Van Doan
- Center for Computational Sciences, University of Tsukuba, Japan
| | - Dung Phung
- School of Public Health, Faculty of Medicine, The University of Queensland, Australia; Queensland Alliance for Environmental Health Sciences, The University of Queensland, Australia.
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Liu J, Du X, Yin P, Kan H, Zhou M, Chen R. Cause-specific mortality and burden attributable to temperature variability in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 896:165267. [PMID: 37406687 DOI: 10.1016/j.scitotenv.2023.165267] [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: 02/01/2023] [Revised: 06/23/2023] [Accepted: 06/30/2023] [Indexed: 07/07/2023]
Abstract
BACKGROUND Few large-scale, nationwide studies have assessed cause-specific mortality risks and burdens associated with temperature variability (TV). OBJECTIVE To estimate associations between TV and cause-specific mortality and quantify the mortality burden in China. METHODS Data on daily total and cause-specific mortality in 272 Chinese cities between 2013 and 2015 were recorded. TVs were computed as the standard deviations of daily minimum and maximum temperatures over a duration of 2 to 7 days. The time-series quasi-Poisson regression model with adjustment of the cumulative effects of daily mean temperature over the same duration was applied to evaluate the city-specific associations of TV and mortality. Then, we pooled the effect estimates using a random-effects meta-analysis and calculated the mortality burdens. RESULTS Overall, TV showed significant and positive associations with total and cause-specific mortality. The TV-mortality associations were generally stronger when using longer durations. A 1 °C increase in TV at 0-7 days (TV0-7) was associated with a 0.79 % [95 % confidence interval (CI): 0.55 %, 0.96 %] increase in total mortality. Mortality fractions attributable to TV0-7 were 4.37 % for total causes, 4.75 % for overall cardiovascular disease, 4.37 % for coronary heart disease, 5.05 % for stroke, 8.28 % for ischaemic stroke, 1.08 % for haemorrhagic stroke, 6.93 % for respiratory disease, and 6.81 % for COPD, respectively. The mortality risk and burden were generally higher in the temperate monsoon zone, females, and elders. CONCLUSION This nationwide study indicated that TV was an independent risk factor of mortality, and could result in significant burden for main cardiorespiratory diseases.
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Affiliation(s)
- Jiangmei Liu
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xihao Du
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and National Health Commission (NHC) Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Peng Yin
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and National Health Commission (NHC) Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Maigeng Zhou
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
| | - Renjie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and National Health Commission (NHC) Key Lab of Health Technology Assessment, Fudan University, Shanghai, China; Shanghai Typhoon Institute/CMA, Shanghai Key Laboratory of Meteorology and Health, Shanghai, China.
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Zhao Z, Chu J, Xu X, Cao Y, Schikowski T, Geng M, Chen G, Bai G, Hu K, Xia J, Ma W, Liu Q, Lu Z, Guo X, Zhao Q. Association between ambient cold exposure and mortality risk in Shandong Province, China: Modification effect of particulate matter size. Front Public Health 2023; 10:1093588. [PMID: 36684922 PMCID: PMC9850236 DOI: 10.3389/fpubh.2022.1093588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 12/06/2022] [Indexed: 01/06/2023] Open
Abstract
Introduction Numerous studies have reported the modification of particulate matters (PMs) on the association between cold temperature and health. However, it remains uncertain whether the modification effect may vary by size of PMs, especially in Shandong Province, China where the disease burdens associated with cold temperature and PMs are both substantial. This study aimed to examine various interactive effects of cold exposure and ambient PMs with diameters ≤1/2.5 μm (PM1 and PM2.5) on premature deaths in Shandong Province, China. Methods In the 2013-2018 cold seasons, data on daily mortality, PM1 and PM2.5, and weather conditions were collected from the 1822 sub-districts of Shandong Province. A time-stratified case-crossover study design was performed to quantify the cumulative association between ambient cold and mortality over lag 0-12 days, with a linear interactive term between temperature and PM1 and PM2.5 additionally added into the model. Results The mortality risk increased with temperature decline, with the cumulative OR of extreme cold (-16.9°C, the 1st percentile of temperature range) being 1.83 (95% CI: 1.66, 2.02), compared with the minimum mortality temperature. The cold-related mortality risk was 2.20 (95%CI: 1.83, 2.64) and 2.24 (95%CI: 1.78, 2.81) on high PM1 and PM2.5 days, which dropped to 1.60 (95%CI: 1.39, 1.84) and 1.60 (95%CI: 1.37, 1.88) on low PM1 and PM2.5 days. PM1 showed greater modification effect for per unit concentration increase than PM2.5. For example, for each 10?g/m3 increase in PM1 and PM2.5, the mortality risk associated with extreme cold temperature increased by 7.6% (95% CI: 1.3%, 14.2%) and 2.6% (95% CI: -0.7%, 5.9%), respectively. Discussion The increment of smaller PMs' modification effect varied by population subgroups, which was particularly strong in the elderly aged over 75 years and individuals with middle school education and below. Specific health promotion strategies should be developed towards the greater modification effect of smaller PMs on cold effect.
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Affiliation(s)
- Zhonghui Zhao
- Department of Epidemiology, School of Public Health, Shandong University, Jinan, China,Shandong University Climate Change and Health Center, Jinan, China
| | - Jie Chu
- Shandong Center for Disease Control and Prevention, Jinan, China,Academy of Preventive Medicine, Shandong University, Jinan, China
| | - Xiaohui Xu
- Shandong Center for Disease Control and Prevention, Jinan, China,Academy of Preventive Medicine, Shandong University, Jinan, China
| | - Yanwen Cao
- Department of Epidemiology, School of Public Health, Shandong University, Jinan, China,Shandong University Climate Change and Health Center, Jinan, China
| | - Tamara Schikowski
- Department of Epidemiology, Leibniz Institute for Environmental Medicine (IUF)-Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany
| | - Mengjie Geng
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Gongbo Chen
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Guannan Bai
- Department of Child Health Care, The Children's Hospital, National Clinical Research Center for Child Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Kejia Hu
- Department of Big Data in Health Science, School of Public Health, Zhejiang University, Hangzhou, China
| | - Jingjing Xia
- School of Life Sciences, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
| | - Wei Ma
- Department of Epidemiology, School of Public Health, Shandong University, Jinan, China,Shandong University Climate Change and Health Center, Jinan, China
| | - Qiyong Liu
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zilong Lu
- Shandong Center for Disease Control and Prevention, Jinan, China,Academy of Preventive Medicine, Shandong University, Jinan, China
| | - Xiaolei Guo
- Shandong Center for Disease Control and Prevention, Jinan, China,Academy of Preventive Medicine, Shandong University, Jinan, China,Xiaolei Guo ✉
| | - Qi Zhao
- Department of Epidemiology, School of Public Health, Shandong University, Jinan, China,Shandong University Climate Change and Health Center, Jinan, China,Department of Epidemiology, Leibniz Institute for Environmental Medicine (IUF)-Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany,*Correspondence: Qi Zhao ✉
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11
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Fang W, Li Z, Gao J, Meng R, He G, Hou Z, Zhu S, Zhou M, Zhou C, Xiao Y, Yu M, Huang B, Xu X, Lin L, Xiao J, Jin D, Qin M, Yin P, Xu Y, Hu J, Liu T, Huang C, Ma W. The joint and interaction effect of high temperature and humidity on mortality in China. ENVIRONMENT INTERNATIONAL 2023; 171:107669. [PMID: 36508749 DOI: 10.1016/j.envint.2022.107669] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 11/20/2022] [Accepted: 11/28/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND Although many studies have reported the mortality effect of temperature, there were few studies on the mortality risk of humidity, let alone the joint effect of temperature and humidity. This study aimed to investigate the joint and interaction effect of high temperature and relative humidity on mortality in China, which will deepen understanding the health risk of mixture climate exposure. METHODS The mortality and meteorological data were collected from 353 locations in China (2013-2017 in Jilin, Hunan, Guangdong and Yunnan provinces, 2009-2017 in Zhejiang province, and 2006-2011 in other Provinces). We defined location-specific daily mean temperature ≥ 75th percentile of distribution as high temperature, while minimum mortality relative humidity as the threshold of high relative humidity. A time-series model with a distributed lag non-linear model was first employed to estimate the location-specific associations between humid-hot events and mortality, then we conducted meta-analysis to pool the mortality effect of humid-hot events. Finally, an additive interaction model was used to examine the interactive effect between high temperature and relative humidity. RESULTS The excess rate (ER) of non-accidental mortality attributed to dry-hot events was 10.18% (95% confidence interval (CI): 8.93%, 11.45%), which was higher than that of wet-hot events (ER = 3.21%, 95% CI: 0.59%, 5.89%). The attributable fraction (AF) of mortality attributed to dry-hot events was 10.00% (95% CI: 9.50%, 10.72%) with higher burden for females, older people, central China, cardiovascular diseases and urban city. While for wet-hot events, AF was much lower (3.31%, 95% CI: 2.60%, 4.30%). We also found that high temperature and low relative humidity had synergistic additive interaction on mortality risk. CONCLUSION Dry-hot events may have a higher risk of mortality than wet-hot events, and the joint effect of high temperature and low relative humidity may be greater than the sum of their individual effects.
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Affiliation(s)
- Wen Fang
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Zhixing Li
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Jinghua Gao
- School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Ruilin Meng
- 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 510632, China
| | - Zhulin Hou
- Jilin Provincial Center for Disease Control and Prevention, Changchun 130062, China
| | - Sui Zhu
- 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
| | - 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
| | - 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
| | - Donghui Jin
- Hunan Provincial Center for Disease Control and Prevention, Changsha 410005, China
| | - Mingfang Qin
- Yunnan Provincial Center for Disease Control and Prevention, Kunming 650034, China
| | - Peng Yin
- The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing 100050, China
| | - Yiqing Xu
- Hunan Provincial Center for Disease Control and Prevention, Changsha 410005, China
| | - Jianxiong Hu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Tao Liu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, 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 510632, China.
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12
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Mei Y, Li A, Zhao M, Xu J, Li R, Zhao J, Zhou Q, Ge X, Xu Q. Associations and burdens of relative humidity with cause-specific mortality in three Chinese cities. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:3512-3526. [PMID: 35947256 DOI: 10.1007/s11356-022-22350-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 07/28/2022] [Indexed: 06/15/2023]
Abstract
This study aimed to investigate the association between relative humidity (RH) and various cause of mortality, and then quantify the RH-related mortality fraction of low and high RH under the assumption that causal effects exist. Daily cause-specific mortality counts from 2008 to 2011, and contemporaneous meteorological data in three Chinese cities were collected. Distributed lag nonlinear models were adopted to quantify the nonlinear and delayed effects of RH on mortality risk. Low and high RH were defined as RH lower or higher than the minimum mortality risk RH (MMRH), respectively. Corresponding RH-related mortality fractions were calculated in the explanatory analysis. From the three cities, 736,301 deaths were collected. RH (mean ± standard deviation) were 50.9 ± 20.0 for Beijing, 75.5 ± 8.6 for Chengdu, and 70.8 ± 14.6 for Nanjing. We found that low RH in Beijing and high RH (about 80-90%) in Chengdu was associated with increased all-cause mortality risk. Both low and high RH may increase the CVD mortality risk in Beijing. Both low and high (about 80-85%) RH may increase the COPD mortality risk in Chengdu. Low RH (about < 45%) was associated with increased diabetes mortality risk in Nanjing. Effects of extreme low and extreme high RH were delayed in these cities, except that extreme low effects on COPD mortality appeared immediately in Chengdu. The effects of extreme low RH are higher than that of the extreme high RH in Beijing and Nanjing, while contrary in Chengdu. Finally, under the causal effect assumption, 6.80% (95% eCI: 2.90, 10.73) all-cause mortality and 12.48% (95% eCI: 7.17, 16.80) CVD deaths in Beijing, 9.59% (95% eCI: 1.38, 16.88) COPD deaths in Chengdu, and 23.79% (95% eCI: 0.92, 387.93) diabetes mortality in Nanjing were attributable to RH. Our study provided insights into RH-mortality risk, helped draw relative intervention policies, and is also significant for future predictions of climate change effects under different scenarios.
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Affiliation(s)
- Yayuan Mei
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China
- Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Ang Li
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China
- Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Meiduo Zhao
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China
- Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Jing Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China
- Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Runkui Li
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
| | - Jiaxin Zhao
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China
- Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Quan Zhou
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China
- Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Xiaoyu Ge
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China
- Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Qun Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China.
- Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China.
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Zhou F, Zhou W, Wang W, Fan C, Chen W, Ling L. Associations between Frailty and Ambient Temperature in Winter: Findings from a Population-Based Study. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 20:513. [PMID: 36612832 PMCID: PMC9819953 DOI: 10.3390/ijerph20010513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 12/13/2022] [Accepted: 12/23/2022] [Indexed: 06/17/2023]
Abstract
Frailty is an accumulation of deficits characterized by reduced resistance to stressors and increased vulnerability to adverse outcomes. However, there is little known about the effect of ambient temperature in winter on frailty among older adults, a population segment with the highest frailty prevalence. Thus, the objective of this study is to investigate the associations between frailty and ambient temperature in winter among older adults. This study was based on the Chinese Longitudinal Healthy Longevity Survey (CLHLS) of older adults aged ≥65 years from the 2005, 2008, 2011, and 2014 waves. The 39-item accumulation of frailty index (FI) was used to assess the frailty status of the participants. The FI was categorized into three groups as follows: robust (FI ≤ 0.10), prefrail (FI > 0.10 to <0.25), and frail (FI ≥ 0.25). Generalized linear mixed models (GLMMs) were conducted to explore the associations between frailty and ambient temperature in winter. A generalized estimating equation (GEE) modification was applied in the sensitivity analysis. A total of 9421 participants were included with a mean age of 82.81 (SD: 11.32) years. Compared with respondents living in the highest quartile (≥7.5 °C) of average temperature in January, those in the lowest quartile (<−1.9 °C) had higher odds of prefrailty (OR = 1.35, 95% CI 1.17−1.57) and frailty (OR = 1.61, 95%CI 1.32−1.95). The associations were stronger among the low-education groups, agricultural workers before retirement, and non-current exercisers. Additionally, results from the GEE model reported consistent findings. Lower levels of ambient temperature in winter were associated with higher likelihoods of prefrailty and frailty. The findings on vulnerability characteristics could help improve public health practices to tailor cold temperature health education and warning information.
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Yang J, Yang Z, Qi L, Li M, Liu D, Liu X, Tong S, Sun Q, Feng L, Ou CQ, Liu Q. Influence of air pollution on influenza-like illness in China: a nationwide time-series analysis. EBioMedicine 2022; 87:104421. [PMID: 36563486 PMCID: PMC9800295 DOI: 10.1016/j.ebiom.2022.104421] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 11/21/2022] [Accepted: 12/06/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Evidence concerning effects of air pollution on influenza-like illness (ILI) from multi-center is limited and little is known about how regional factors might modify this relationship. METHODS In this ecological study, ILI cases defined as outpatients with temperature ≥38 °C, accompanied by cough or sore throat, were collected from National Influenza Surveillance Network in China. We adopted generalized additive model with quasi-Poisson to estimate province-specific association between air pollution and ILI in 30 Chinese provinces during 2015-2019, after adjusting for time trend and meteorological factors. We then pooled province-specific association by using random-effect meta-analysis. Potential effect modifications of season and regional characteristics were explored. FINDINGS A total of 26, 004, 853 ILI cases and 777, 223, 877 hospital outpatients were collected. In general, effects of air pollutants were acute. An inter-quartile range increase of PM2.5, SO2, PM10, NO2 and CO at lag0, and O3 at lag0-2 was associated with 3.08% (95% CI: 1.91%, 4.27%), 3.00% (1.86%, 4.16%), 6.46% (4.71%, 8.25%), 7.21% (5.73%, 8.71%), 4.37% (3.05%, 5.70%), and -9.26% (-11.32%, -7.14%) change of ILI at national level, respectively. Associations between air pollutants and ILI varied by season and regions, with higher effect estimates in cold season, eastern and central regions and provinces with more humid condition and larger population. INTERPRETATION This study indicated that most air pollutants increased the risk of ILI in China. Our findings might provide implications for the development of policies to protect public health from air pollution and influenza. FUNDING National Natural Science Foundation of China and Chongqing Health Commission Program.
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Affiliation(s)
- Jun Yang
- School of Public Health, Guangzhou Medical University, Guangzhou, 511436, China,Corresponding author.
| | - Zhou Yang
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, 510515, China
| | - Li Qi
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, 400042, China
| | - Mengmeng Li
- Department of Cancer Prevention, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China
| | - Di Liu
- School of Public Health, Guangzhou Medical University, Guangzhou, 511436, China
| | - Xiaobo Liu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China
| | - Shilu Tong
- Shanghai Children's Medical Center, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Qinghua Sun
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Luzhao Feng
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China,Corresponding author.
| | - Chun-Quan Ou
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, 510515, China
| | - Qiyong Liu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China,Corresponding author.
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The Association between Gut Microbiome Diversity and Composition and Heat Tolerance in Cattle. Microorganisms 2022; 10:microorganisms10081672. [PMID: 36014088 PMCID: PMC9414853 DOI: 10.3390/microorganisms10081672] [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: 07/27/2022] [Revised: 08/11/2022] [Accepted: 08/12/2022] [Indexed: 11/16/2022] Open
Abstract
Cattle are raised around the world and are frequently exposed to heat stress, whether in tropical countries or in regions with temperate climates. It is universally acknowledged that compared to those in temperate areas, the cattle breeds developed in tropical and subtropical areas have better heat tolerance. However, the underlying mechanism of heat tolerance has not been fully studied, especially from the perspective of intestinal microbiomics. The present study collected fecal samples of cattle from four representative climatic regions of China, namely, the mesotemperate (HLJ), warm temperate (SD), subtropical (HK), and tropical (SS) regions. Then, the feces were analyzed using high-throughput 16S rRNA sequencing. The results showed that with increasing climatic temperature from HLJ to SS, the abundance of Firmicutes increased, accompanied by an increasing Firmicutes to Bacteroidota ratio. Proteobacteria showed a trend of reduction from HLJ to SS. Patescibacteria, Chloroflexi, and Actinobacteriota were particularly highest in SS for adapting to the tropical environment. The microbial phenotype in the tropics was characterized by an increase in Gram-positive bacteria and a decrease in Gram-negative bacteria, aerobic bacteria, and the forming of_biofilms. Consistently, the functional abundances of organismal systems and metabolism were decreased to reduce the material and energy demands in a hot environment. Genetic information processing and information storage and processing may be how gut flora deals with hot conditions. The present study revealed the differences in the structure and function of gut microbes of cattle from mesotemperate to tropical climates and provided an important reference for future research on the mechanism of heat tolerance regulated by the gut microbiota and a potential microbiota-based target to alleviate heat stress.
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