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Yu P, Xu R, Wu Y, Huang W, Coelho MSZS, Saldiva PHN, Ye T, Wen B, Liu Y, Yang Z, Li S, Abramson MJ, Guo Y. Cancer mortality risk from short-term PM 2.5 exposure and temporal variations in Brazil. JOURNAL OF HAZARDOUS MATERIALS 2024; 473:134606. [PMID: 38788590 DOI: 10.1016/j.jhazmat.2024.134606] [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: 02/01/2024] [Revised: 04/30/2024] [Accepted: 05/11/2024] [Indexed: 05/26/2024]
Abstract
Although some studies have found that short-term PM2.5 exposure is associated with lung cancer deaths, its impact on other cancer sites is unclear. To answer this research question, this time-stratified case-crossover study used individual cancer death data between January 1, 2000, and December 31, 2019, extracted from the Brazilian mortality information system to quantify the associations between short-term PM2.5 exposure and cancer mortality from 25 common cancer sites. Daily PM2.5 concentration was aggregated at the municipality level as the key exposure. The study included a total of 34,516,120 individual death records, with the national daily mean PM2.5 exposure 15.3 (SD 4.3) μg/m3. For every 10-μg/m3 increase in three-day average PM2.5 exposure, the odds ratio (OR) for all-cancer mortality was 1.04 (95% CI 1.03-1.04). Apart from all-cancer deaths, PM2.5 exposure may impact cancers of oesophagus (1.04, 1.00-1.08), stomach (1.05, 1.02-1.08), colon-rectum (1.04, 1.01-1.06), lung (1.04, 1.02-1.06), breast (1.03, 1.00-1.06), prostate (1.07, 1.04-1.10), and leukaemia (1.05, 1.01-1.09). During the study period, acute PM2.5 exposure contributed to an estimated 1,917,994 cancer deaths, ranging from 0 to 6,054 cases in each municipality. Though there has been a consistent downward trend in PM2.5-related all-cancer mortality risks from 2000 to 2019, the impact remains significant, indicating the continued importance of cancer patients avoiding PM2.5 exposure. This nationwide study revealed a notable association between acute PM2.5 exposure and heightened overall and site-specific cancer mortality for the first time to our best knowledge. The findings suggest the importance of considering strategies to minimize such exposure in cancer care guidelines. ENVIRONMENTAL IMPLICATION: The 20-year analysis of nationwide death records in Brazil revealed that heightened short-term exposure to PM2.5 is associated with increased cancer mortality at various sites, although this association has gradually decreased over time. Despite the declining impact, the research highlights the persistent adverse effects of PM2.5 on cancer mortality, emphasizing the importance of continued research and preventive measures to address the ongoing public health challenges posed by air pollution.
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Affiliation(s)
- Pei Yu
- Climate Air quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Rongbin Xu
- 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
| | - Wenzhong Huang
- Climate Air quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Micheline S Z S Coelho
- Laboratory of Urban Health Insper/Faculty of Medicine of the University of São Paulo, Brazil
| | - Paulo H N Saldiva
- Laboratory of Urban Health Insper/Faculty of Medicine of the University of São Paulo, Brazil
| | - Tingting Ye
- Climate Air quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Bo Wen
- Climate Air quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yanming Liu
- Climate Air quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Zhengyu Yang
- Climate Air quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Shanshan Li
- Climate Air quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Michael J Abramson
- 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.
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Yu P, Xu R, Huang W, Yang Z, Coelho MSZS, Saldiva PHN, Wen B, Wu Y, Ye T, Zhang Y, Sun HZ, Abramson MJ, Li S, Guo Y. Short-term ozone exposure and cancer mortality in Brazil: A nationwide case-crossover study. Int J Cancer 2024. [PMID: 38985095 DOI: 10.1002/ijc.35069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Revised: 05/24/2024] [Accepted: 06/06/2024] [Indexed: 07/11/2024]
Abstract
Exposure to ambient ozone (O3) is linked to increased mortality risks from various diseases, but epidemiological investigations delving into its potential implications for cancer mortality are limited. We aimed to examine the association between short-term O3 exposure and site-specific cancer mortality and investigate vulnerable subgroups in Brazil. In total 3,459,826 cancer death records from 5570 Brazilian municipalities between 2000 and 2019, were included. Municipal average daily O3 concentration was calculated from a global estimation at 0.25°×0.25° spatial resolution. The time-stratified case-crossover design was applied to assess the O3-cancer mortality association. Subgroup analyses by age, sex, season, time-period, region, urban hierarchy, climate classification, quantiles of GDP per capita and illiteracy rates were performed. A linear and non-threshold exposure-response relationship was observed for short-term exposure to O3 with cancer mortality, with a 1.00% (95% CI: 0.79%-1.20%) increase in all-cancer mortality risks for each 10-μg/m3 increment of three-day average O3. Kidney cancer was most strongly with O3 exposure, followed by cancers of the prostate, stomach, breast, lymphoma, brain and lung. The associated cancer risks were relatively higher in the warm season and in southern Brazil, with a decreasing trend over time. When restricting O3 concentration to the national minimum value during 2000-2019, a total of 147,074 (116,690-177,451) cancer deaths could be avoided in Brazil, which included 17,836 (7014-28,653) lung cancer deaths. Notably, these associations persisted despite observed adaptation within the Brazilian population, highlighting the need for a focus on incorporating specific measures to mitigate O3 exposure into cancer care recommendations.
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Affiliation(s)
- Pei Yu
- Climate Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Rongbin Xu
- Climate Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Wenzhong Huang
- Climate Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Zhengyu Yang
- Climate Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Micheline S Z S Coelho
- Laboratory of Urban Health Insper/ Faculty of Medicine of the University of São Paulo, Sao Paulo, Brazil
| | - Paulo H N Saldiva
- Laboratory of Urban Health Insper/ Faculty of Medicine of the University of São Paulo, Sao Paulo, Brazil
| | - 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
| | - Tingting Ye
- Climate Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yiwen Zhang
- Climate Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Haitong Z Sun
- Centre for Sustainable Medicine (CoSM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Michael J Abramson
- Climate Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Shanshan Li
- 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
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3
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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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Zhang T, Huang R, Yang M, Lin G, Ma X, Wang X, Huang Q. Perceptions of the health risk from hot days and the cooling effect of urban green spaces: a case study in Xi'an, China. Front Public Health 2023; 11:1211164. [PMID: 37674680 PMCID: PMC10477602 DOI: 10.3389/fpubh.2023.1211164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Accepted: 08/08/2023] [Indexed: 09/08/2023] Open
Abstract
Background Hot days are one of the typical threats to human health and sustainable cities. The exploration of residents' perceptions of thermal environment and its mitigation measures will support the health risk prevention. Methods A survey with a combination of closed-ended and open-ended questions was conducted in July 2021 among 13 urban parks in Xi'an City, China. With the help of ANOVA and ordinal logistic regression, this study investigated the influencing factors both on residents' health risk perception of hot days and their perception of the effect of urban ecological landscape on reducing the thermal risk. The relationship between health risk perception and residents' needs of urban ecological construction was also explored. Results According to 325 valid questionnaires, the male-female ratio of respondents was found to be 1:0.87, young people aged 18-29 (26.46%), the retirees (27.08%) and the ones with undergraduate education (33.23%) were, relatively, the largest groups. The results show that 92.31% of the respondents believed that their daily lives were under the influence of hot days. Housing types, occupation, cooling equipment at work, and outdoor working hours all had a significant impact on their high temperature perceptions. The proportion of respondents who were under a huge health risk and sought medical treatment due to hot days was 30.16% and 44.92%, respectively. Women were 18.52 and 2.33 times more likely to suffer health threats and experience discomforts than men. Furthermore, 73.23% of the respondents believed that the urban ecological landscapes in Xi'an had an enhanced cooling effect in recent years. Compared with the morphological characteristics, residents' recognition of the restriction of landscape's area on its cooling effect was higher, and the residence duration showed a significant influence. Conclusion The cooling effect of green spaces and water effectively resisted urban thermal threats, and residents' needs of the urban ecological landscapes was associated with their health risk perceptions of hot days. In the future, it is necessary to promote the early warning of hot days, meanwhile, the optimization of landscape patterns of green infrastructures should be implemented in urban planning for the purposes of residents' health risk prevention.
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Affiliation(s)
- Tian Zhang
- Northwest Land and Resource Research Center, Shaanxi Normal University, Xi’an, China
| | - Rong Huang
- School of Geography and Tourism, Shaanxi Normal University, Xi’an, China
| | - Mei Yang
- School of Geography and Tourism, Shaanxi Normal University, Xi’an, China
| | - Guohua Lin
- School of Geography and Tourism, Shaanxi Normal University, Xi’an, China
| | - Xiaoyan Ma
- School of Geography and Tourism, Shaanxi Normal University, Xi’an, China
| | - Xuan Wang
- School of Geography and Tourism, Shaanxi Normal University, Xi’an, China
| | - Qian Huang
- School of Geography and Tourism, Shaanxi Normal University, Xi’an, China
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Chen S, Lin X, Du Z, Zhang Y, Zheng L, Ju X, Guo T, Wang X, Chen L, Jiang J, Hu W, Zhang W, Hao Y. Potential causal links between long-term ambient particulate matter exposure and cerebrovascular mortality: Insights from a large cohort in southern China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 328:121336. [PMID: 36822305 DOI: 10.1016/j.envpol.2023.121336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 02/18/2023] [Accepted: 02/20/2023] [Indexed: 05/09/2023]
Abstract
Cohort studies conducted in North America and Europe have linked cerebrovascular mortality to long-term exposure to particulate matter (PM). However, limited evidence from large cohorts in high-exposure areas and the traditional approach of association assessment may cause residual confounding issues. In this study, we aimed to investigate the causal links between cerebrovascular mortality and long-term exposure to PM2.5, PM10, and PM2.5-10 in an ongoing cohort study with 580,757 participants in southern China. Using satellite-based estimates of PM concentration at a 1-km2 spatial resolution, we assigned exposure levels to each participant and used the marginal structural Cox model to assess the association between PM exposure and cerebrovascular mortality while accounting for time-varying covariates. We also explored the potential modification effects of sociodemographic and behavioral factors on the PM-health associations. Adjusted hazard ratios (HR) for overall cerebrovascular mortality were 1.041 (95% confidence interval (CI): 1.034-1.049) and 1.032 (95% CI: 1.026-1.038) for each 1 μg/m3 increase in PM2.5, and PM10, respectively. Similar trends were observed in the mortality risk from stroke and ischemic stroke, with HRs ranging from 1.040 to 1.069 and 1.025 to 1.052, respectively, across 2 p.m. exposures. The impact of PM exposure was generally more apparent among women, participants with primary school diplomas and below, and the subgroup under low-exposure. Multiple sensitivity analyses confirmed the robustness of the results. In conclusion, this sizable prospective cohort study hypothesizes causal links between long-term PM exposure and cerebrovascular mortality, particularly among vulnerable participants, supporting the rationale for reducing PM concentration in China to reduce cerebrovascular mortality.
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Affiliation(s)
- Shirui Chen
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Xiao Lin
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Zhicheng Du
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Yuqin Zhang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Lingling Zheng
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Xu Ju
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Tong Guo
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Xinran Wang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Lichang Chen
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Jie Jiang
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking, China
| | - Weihua Hu
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking, China
| | - Wangjian Zhang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Yuantao Hao
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking, China.
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Fatima SH, Rothmore P, Giles LC, Bi P. Intra-urban risk assessment of occupational injuries and illnesses associated with current and projected climate: Evidence from three largest Australian cities. ENVIRONMENTAL RESEARCH 2023; 228:115855. [PMID: 37028539 DOI: 10.1016/j.envres.2023.115855] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 04/03/2023] [Accepted: 04/04/2023] [Indexed: 05/16/2023]
Abstract
BACKGROUND Increased risk of occupational injuries and illnesses (OI) is associated with ambient temperature. However, most studies have reported the average impacts within cities, states, or provinces at broader scales. METHODS We assessed the intra-urban risk of OI associated with ambient temperature in three Australian cities at statistical area level 3 (SA3). We collected daily workers' compensation claims data and gridded meteorological data from July 1, 2005, to June 30, 2018. Heat index was used as the primary temperature metric. We performed a two-stage time series analysis: we generated location-specific estimates using Distributed Lag Non-Linear Models (DLNM) and estimated the cumulative effects with multivariate meta-analysis. The risk was estimated at moderate heat (90th percentile) and extreme heat (99th percentile). Subgroup analyses were conducted to identify vulnerable groups of workers. Further, the OI risk in the future was estimated for two projected periods: 2016-2045 and 2036-2065. RESULTS The cumulative risk of OI was 3.4% in Greater Brisbane, 9.5% in Greater Melbourne, and 8.9% in Greater Sydney at extreme heat. The western inland regions in Greater Brisbane (17.4%) and Greater Sydney (32.3%) had higher risk of OI for younger workers, workers in outdoor and indoor industries, and workers reporting injury claims. The urbanized SA3 regions posed a higher risk (19.3%) for workers in Greater Melbourne. The regions were generally at high risk for young workers and illness-related claims. The projected risk of OI increased with time in climate change scenarios. CONCLUSIONS This study provides a comprehensive spatial profile of OI risk associated with hot weather conditions across three cities in Australia. Risk assessment at the intra-urban level revealed strong spatial patterns in OI risk distribution due to heat exposure. These findings provide much-needed scientific evidence for work, health, and safety regulators, industries, unions, and workers to design and implement location-specific preventative measures.
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Affiliation(s)
- Syeda Hira Fatima
- School of Public Health, The University of Adelaide, Adelaide, South Australia, Australia
| | - Paul Rothmore
- School of Allied Health Science and Practice, The University of Adelaide, Adelaide, South Australia, Australia
| | - Lynne C Giles
- School of Public Health, The University of Adelaide, Adelaide, South Australia, Australia
| | - Peng Bi
- School of Public Health, The University of Adelaide, Adelaide, South Australia, Australia.
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7
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Wang S, Wu G, Du Z, Wu W, Ju X, Yimaer W, Chen S, Zhang Y, Li J, Zhang W, Hao Y. The causal links between long-term exposure to major PM 2.5 components and the burden of tuberculosis in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 870:161745. [PMID: 36690108 DOI: 10.1016/j.scitotenv.2023.161745] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Revised: 01/09/2023] [Accepted: 01/17/2023] [Indexed: 06/17/2023]
Abstract
BACKGROUND We aimed to estimate the causal impacts of long-term exposure to major PM2.5 components - including black carbon, organic matter, sulfate, nitrate, and ammonium - on the incidence and mortality of tuberculosis in China. METHODS We collected annual and provincial-level tuberculosis incidence and mortality, concentrations of PM2.5 components, and socioeconomic indicators from between 2004 and 2018 in mainland China. We used the difference-in-differences (DID) causal inference approach with a generalized weighted quantile sum (gWQS) regression model to estimate the long-term effects and relative contributions of PM2.5 components' exposure on tuberculosis incidence and mortality. RESULTS We found that long-term multi-components exposure was significantly associated with tuberculosis incidence (WQS index IR%:8.34 %, 95 % CI:4.54 %-12.27 %) and mortality (WQS index IR%:19.49 %, 95 % CI: 9.72 %-30.13 %). Primary pollutants, black carbon and organic matter, contributed most of the overall mixture effect (over 85 %). Nitrate showed a critical role in tuberculosis burden in not-aging provinces and in regions at the Q3 stratum (i.e., the 3rd quartile) of GDP per capita and urbanization rate. Meanwhile the contribution of sulfate to tuberculosis burden in regions at the Q1 stratum of GDP per capita and urbanization rate was the largest among the effect of secondary pollutants (i.e., sulfate, nitrate, and ammonium). CONCLUSION The mitigation of black carbon and organic matter pollution may significantly reduce the tuberculosis burden in China. Controlling nitrate emissions and increasing clean energy (i.e., energy sources with limited pollution emissions, such as natural gas and clean coal) may also be effective in certain regions.
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Affiliation(s)
- Shenghao Wang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Gonghua Wu
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Zhicheng Du
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Wenjing Wu
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Xu Ju
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Wumitijiang Yimaer
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Shirui Chen
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Yuqin Zhang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Jinghua Li
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China.
| | - Wangjian Zhang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China.
| | - Yuantao Hao
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking, China.
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8
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Zhang W, Wu Y, Wen B, Zhang Y, Wang Y, Yin W, Sun S, Wei X, Sun H, Zhang Z, Li S, Guo Y. Non-pharmaceutical interventions for COVID-19 reduced the incidence of infectious diseases: a controlled interrupted time-series study. Infect Dis Poverty 2023; 12:15. [PMID: 36895021 PMCID: PMC9996566 DOI: 10.1186/s40249-023-01066-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 02/06/2023] [Indexed: 03/11/2023] Open
Abstract
BACKGROUND Non-pharmaceutical interventions (NPIs) have been implemented worldwide to suppress the spread of coronavirus disease 2019 (COVID-19). However, few studies have evaluated the effect of NPIs on other infectious diseases and none has assessed the avoided disease burden associated with NPIs. We aimed to assess the effect of NPIs on the incidence of infectious diseases during the COVID-19 pandemic in 2020 and evaluate the health economic benefits related to the reduction in the incidence of infectious diseases. METHODS Data on 10 notifiable infectious diseases across China during 2010-2020 were extracted from the China Information System for Disease Control and Prevention. A two-stage controlled interrupted time-series design with a quasi-Poisson regression model was used to examine the impact of NPIs on the incidence of infectious diseases. The analysis was first performed at the provincial-level administrative divisions (PLADs) level in China, then the PLAD-specific estimates were pooled using a random-effect meta-analysis. RESULTS A total of 61,393,737 cases of 10 infectious diseases were identified. The implementation of NPIs was associated with 5.13 million (95% confidence interval [CI] 3.45‒7.42) avoided cases and USD 1.77 billion (95% CI 1.18‒2.57) avoided hospital expenditures in 2020. There were 4.52 million (95% CI 3.00‒6.63) avoided cases for children and adolescents, corresponding to 88.2% of total avoided cases. The top leading cause of avoided burden attributable to NPIs was influenza [avoided percentage (AP): 89.3%; 95% CI 84.5‒92.6]. Socioeconomic status and population density were effect modifiers. CONCLUSIONS NPIs for COVID-19 could effectively control the prevalence of infectious diseases, with patterns of risk varying by socioeconomic status. These findings have important implications for informing targeted strategies to prevent infectious diseases.
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Affiliation(s)
- Wenyi Zhang
- Division of Disease Surveillance, Chinese PLA Center for Disease Control and Prevention, Beijing, 100071, China
| | - Yao Wu
- School of Public Health and Preventive Medicine, Monash University, Level 2, 553 St Kilda Road, Melbourne, VIC, 3004, Australia
| | - Bo Wen
- School of Public Health and Preventive Medicine, Monash University, Level 2, 553 St Kilda Road, Melbourne, VIC, 3004, Australia
| | - Yongming Zhang
- Department of Respiratory and Critical Care Medicine, China-Japan Friendship Hospital, Beijing, 100029, China
| | - Yong Wang
- Division of Disease Surveillance, Chinese PLA Center for Disease Control and Prevention, Beijing, 100071, China
| | - Wenwu Yin
- Division of Infectious Diseases, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, 102206, China
| | - Shanhua Sun
- Beijing Center for Disease Prevention and Control, Beijing, 100013, China
| | - Xianyu Wei
- Division of Disease Surveillance, Chinese PLA Center for Disease Control and Prevention, Beijing, 100071, China
| | - Hailong Sun
- Division of Disease Surveillance, Chinese PLA Center for Disease Control and Prevention, Beijing, 100071, China
| | - Zhijie Zhang
- Department of Epidemiology and Health Statistics, Fudan University, Shanghai, 200032, China
| | - Shanshan Li
- School of Public Health and Preventive Medicine, Monash University, Level 2, 553 St Kilda Road, Melbourne, VIC, 3004, Australia.
| | - Yuming Guo
- School of Public Health and Preventive Medicine, Monash University, Level 2, 553 St Kilda Road, Melbourne, VIC, 3004, Australia.
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9
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Jurgilevich A, Käyhkö J, Räsänen A, Pörsti S, Lagström H, Käyhkö J, Juhola S. Factors influencing vulnerability to climate change-related health impacts in cities - A conceptual framework. ENVIRONMENT INTERNATIONAL 2023; 173:107837. [PMID: 36921561 DOI: 10.1016/j.envint.2023.107837] [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: 09/29/2022] [Revised: 01/27/2023] [Accepted: 02/16/2023] [Indexed: 06/18/2023]
Abstract
Climate change will have adverse impacts on human health, which are amplified in cities. For these impacts, there are direct, indirect, and deferred pathways. The first category is well-studied, while indirect and deferred impacts are not well-understood. Moreover, the factors moderating the impacts have received little attention, although understanding these factors is critical for adaptation. We developed a conceptual framework that shows the pathways of climate impacts on human health, focusing specifically on the factors of urban environment moderating the emergence and severity of these health impacts. Based on the framework and literature review, we illustrate the mechanisms of direct, indirect, and deferred health impact occurrence and the factors that exacerbate or alleviate the severity of these impacts, thus presenting valuable insights for anticipatory adaptation. We conclude that an integrated systemic approach to preventing health risks from climate change can provide co-benefits for adaptation and address multiple health risks. Such an approach should be mainstreamed horizontally to all sectors of urban planning and should account for the spatiotemporal aspects of policy and planning decisions and city complexity.
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Affiliation(s)
| | - Janina Käyhkö
- University of Helsinki, Environment and Ecosystems Research Programme, Finland
| | | | | | - Hanna Lagström
- University of Turku, Centre for Population Health Research and Turku University Hospital, Finland
| | - Jukka Käyhkö
- University of Turku, Department of Geography and Geology, Finland
| | - Sirkku Juhola
- University of Helsinki, Environment and Ecosystems Research Programme, Finland
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10
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Hu J, He G, Meng R, Gong W, Ren Z, Shi H, Lin Z, Liu T, Zeng F, Yin P, Bai G, Qin M, Hou Z, Dong X, Zhou C, Pingcuo Z, Xiao Y, Yu M, Huang B, Xu X, Lin L, Xiao J, Zhong J, Jin D, Zhao Q, Li Y, Gama C, Xu Y, Lv L, Zeng W, Li X, Luo L, Zhou M, Huang C, Ma W. Temperature-related mortality in China from specific injury. Nat Commun 2023; 14:37. [PMID: 36596791 PMCID: PMC9810693 DOI: 10.1038/s41467-022-35462-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 12/05/2022] [Indexed: 01/04/2023] Open
Abstract
Injury poses heavy burden on public health, accounting for nearly 8% of all deaths globally, but little evidence on the role of climate change on injury exists. We collect data during 2013-2019 in six provinces of China to examine the effects of temperature on injury mortality, and to project future mortality burden attributable to temperature change driven by climate change based on the assumption of constant injury mortality and population scenario. The results show that a 0.50% (95% confident interval (CI): 0.13%-0.88%) increase of injury mortality risk for each 1 °C rise in daily temperature, with higher risk for intentional injury (1.13%, 0.55%-1.71%) than that for unintentional injury (0.40%, 0.04%-0.77%). Compared to the 2010s, total injury deaths attributable to temperature change in China would increase 156,586 (37,654-272,316) in the 2090 s under representative concentration pathways 8.5 scenario with the highest for transport injury (64,764, 8,517-115,743). Populations living in Western China, people aged 15-69 years, and male may suffer more injury mortality burden from increased temperature caused by climate change. Our findings may be informative for public health policy development to effectively adapt to climate change.
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Affiliation(s)
- Jianxiong Hu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Guanhao He
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, 511443, China
| | - Ruilin Meng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Weiwei Gong
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, 310009, China
| | - Zhoupeng Ren
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
| | - Heng Shi
- Tibet Autonomous Region Center for Disease Control and Prevention, Lhasa, 850002, China
| | - Ziqiang Lin
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, 511443, China
| | - Tao Liu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, 511443, China
| | - Fangfang Zeng
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, 511443, China
| | - Peng Yin
- The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing, 100050, China
| | - Guoxia Bai
- Tibet Autonomous Region Center for Disease Control and Prevention, Lhasa, 850002, China
| | - Mingfang Qin
- Yunnan Provincial Center for Disease Control and Prevention, Kunming, 650034, China
| | - Zhulin Hou
- Jilin Provincial Center for Disease Control and Prevention, Changchun, 130062, China
| | - Xiaomei Dong
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, 511443, China
| | - Chunliang Zhou
- Hunan Provincial Center for Disease Control and Prevention, Changsha, 410005, China
| | - Zhuoma Pingcuo
- Tibet Autonomous Region Center for Disease Control and Prevention, Lhasa, 850002, China
| | - Yize Xiao
- Yunnan Provincial Center for Disease Control and Prevention, Kunming, 650034, China
| | - Min Yu
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, 310009, China
| | - Biao Huang
- Jilin Provincial Center for Disease Control and Prevention, Changchun, 130062, China
| | - Xiaojun Xu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Lifeng Lin
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Jianpeng Xiao
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Jieming Zhong
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, 310009, China
| | - Donghui Jin
- Hunan Provincial Center for Disease Control and Prevention, Changsha, 410005, China
| | - Qinglong Zhao
- Jilin Provincial Center for Disease Control and Prevention, Changchun, 130062, China
| | - Yajie Li
- Tibet Autonomous Region Center for Disease Control and Prevention, Lhasa, 850002, China
| | - Cangjue Gama
- Tibet Autonomous Region Center for Disease Control and Prevention, Lhasa, 850002, China
| | - Yiqing Xu
- Hunan Provincial Center for Disease Control and Prevention, Changsha, 410005, China
| | - Lingshuang Lv
- Hunan Provincial Center for Disease Control and Prevention, Changsha, 410005, China
| | - Weilin Zeng
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Xing Li
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Liying Luo
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Maigeng Zhou
- The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing, 100050, China
| | - Cunrui Huang
- Vanke School of Public Health, Tsinghua University, Beijing, 100084, China
| | - Wenjun Ma
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, 511443, China.
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11
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Ye T, Xu R, Yue X, Chen G, Yu P, Coêlho MSZS, Saldiva PHN, Abramson MJ, Guo Y, Li S. Short-term exposure to wildfire-related PM 2.5 increases mortality risks and burdens in Brazil. Nat Commun 2022; 13:7651. [PMID: 36496479 PMCID: PMC9741581 DOI: 10.1038/s41467-022-35326-x] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Accepted: 11/29/2022] [Indexed: 12/13/2022] Open
Abstract
To assess mortality risks and burdens associated with short-term exposure to wildfire-related fine particulate matter with diameter ≤ 2.5 μm (PM2.5), we collect daily mortality data from 2000 to 2016 for 510 immediate regions in Brazil, the most wildfire-prone area. We integrate data from multiple sources with a chemical transport model at the global scale to isolate daily concentrations of wildfire-related PM2.5 at a 0.25 × 0.25 resolution. With a two-stage time-series approach, we estimate (i) an increase of 3.1% (95% confidence interval [CI]: 2.4, 3.9%) in all-cause mortality, 2.6% (95%CI: 1.5, 3.8%) in cardiovascular mortality, and 7.7% (95%CI: 5.9, 9.5) in respiratory mortality over 0-14 days with each 10 μg/m3 increase in daily wildfire-related PM2.5; (ii) 0.65% of all-cause, 0.56% of cardiovascular, and 1.60% of respiratory mortality attributable to acute exposure to wildfire-related PM2.5, corresponding to 121,351 all-cause deaths, 29,510 cardiovascular deaths, and 31,287 respiratory deaths during the study period. In this study, we find stronger associations in females and adults aged ≥ 60 years, and geographic difference in the mortality risks and burdens.
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Affiliation(s)
- Tingting Ye
- grid.1002.30000 0004 1936 7857Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004 Australia
| | - Rongbin Xu
- grid.1002.30000 0004 1936 7857Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004 Australia
| | - Xu Yue
- grid.260478.f0000 0000 9249 2313Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology (NUIST), Nanjing, 210044 China
| | - Gongbo Chen
- grid.1002.30000 0004 1936 7857Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004 Australia
| | - Pei Yu
- grid.1002.30000 0004 1936 7857Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004 Australia
| | - Micheline S. Z. S. Coêlho
- grid.11899.380000 0004 1937 0722Urban Health Laboratory University of São Paulo, Faculty of Medicine/INSPER, São Paulo, 01246-903 Brazil
| | - Paulo H. N. Saldiva
- grid.11899.380000 0004 1937 0722Urban Health Laboratory University of São Paulo, Faculty of Medicine/INSPER, São Paulo, 01246-903 Brazil
| | - Michael J. Abramson
- grid.1002.30000 0004 1936 7857Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004 Australia
| | - Yuming Guo
- grid.1002.30000 0004 1936 7857Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004 Australia
| | - Shanshan Li
- grid.1002.30000 0004 1936 7857Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004 Australia
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12
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Luo L, Zeng F, Bai G, Gong W, Ren Z, Hu J, He G, Shi H, Lin Z, Liu T, Yin P, Qin M, Hou Z, Meng R, Zhou C, Dong X, Pingcuo Z, Xiao Y, Yu M, Huang B, Xu X, Lin L, Xiao J, Zhong J, Jin D, Li Y, Gama C, Xiong P, Xu Y, Lv L, Zeng W, Li X, Zhou M, Huang C, Ma W. Future injury mortality burden attributable to compound hot extremes will significantly increase in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 845:157019. [PMID: 35798110 DOI: 10.1016/j.scitotenv.2022.157019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 06/23/2022] [Accepted: 06/24/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND As climate change, compound hot extremes (CHEs), daytime and nighttime persistent hot extremes, are projected to become much more frequent and intense, which may pose a serious threat to human health. However, evidence on the impact of CHEs on injury is rare. METHODS We collected injury death data and daily meteorological data from six Chinese provinces during 2013-2018. A time-stratified case-crossover design with two-stage analytic approach was applied to assess the associations of CHEs with injury mortality by intention, mechanism, age and gender. Using the projected daily temperatures of five General Circulation Models (GCMs), we projected the frequency of CHEs and CHEs-attributable mortality burden of injury under three Representative Concentration Pathway (RCP) scenarios. RESULTS CHEs were significantly associated with increased injury mortality risk (RR = 1.14, 95%CI: 1.09-1.19), with strong effects on unintentional injuries (RR = 1.16, 95%CI:1.11,1.22) and intentional injuries (RR = 1.11, 95%CI:0.99,1.25). Female (RR = 1.21,95%CI: 1.13-1.29) and the elderly (RR = 1.30, 95%CI: 1.22-1.39) were more susceptible to CHEs. Both the frequency and injury mortality burden of CHEs showed a steep rising trend under RCP8.5 scenario, with a 7.37-fold and 8.22-fold increase respectively, by the end of the century, especially in southern, eastern, central and northwestern China. CONCLUSION CHEs were associated with increased injury mortality risk, and the CHEs-attributable injury mortality burden was projected to aggravate substantially in the future as global warming. It is urgent to develop targeted adaptation policies to alleviate the health burden of CHEs.
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Affiliation(s)
- Liying Luo
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Fangfang Zeng
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 511443, China
| | - Guoxia Bai
- Tibet Autonomous Region Center for Disease Control and Prevention, Lhasa 850002, China
| | - Weiwei Gong
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, 310009, China
| | - Zhoupeng Ren
- State Key Laboratory of Resources and Environmental Information System (LREIS), Institute of Geographic Science and Natural Resource Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Jianxiong Hu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Guanhao He
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Heng Shi
- Tibet Autonomous Region Center for Disease Control and Prevention, Lhasa 850002, China
| | - Ziqiang Lin
- Department of Psychiatry, New York University School of Medicine, One Park Ave, New York, NY 10016, United States
| | - Tao Liu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 511443, China
| | - Peng Yin
- The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing 100050, China
| | - Mingfang Qin
- Yunnan Provincial Center for Disease Control and Prevention, Kunming 650034, China
| | - Zhulin Hou
- Jilin Provincial Center for Disease Control and Prevention, Changchun 130062, China
| | - Ruilin Meng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Chunliang Zhou
- Hunan Provincial Center for Disease Control and Prevention, Changsha 410005, China
| | - Xiaomei Dong
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 511443, China
| | - Zhuoma Pingcuo
- Tibet Autonomous Region Center for Disease Control and Prevention, Lhasa 850002, China
| | - Yize Xiao
- Yunnan Provincial Center for Disease Control and Prevention, Kunming 650034, China
| | - Min Yu
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, 310009, China
| | - Biao Huang
- Jilin Provincial Center for Disease Control and Prevention, Changchun 130062, China
| | - Xiaojun Xu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Lifeng Lin
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Jianpeng Xiao
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Jieming Zhong
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, 310009, China
| | - Donghui Jin
- Hunan Provincial Center for Disease Control and Prevention, Changsha 410005, China
| | - Yajie Li
- Tibet Autonomous Region Center for Disease Control and Prevention, Lhasa 850002, China
| | - Cangjue Gama
- Tibet Autonomous Region Center for Disease Control and Prevention, Lhasa 850002, China
| | - Peng Xiong
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 511443, China
| | - Yiqing Xu
- Hunan Provincial Center for Disease Control and Prevention, Changsha 410005, China
| | - Lingshuang Lv
- Hunan Provincial Center for Disease Control and Prevention, Changsha 410005, China
| | - Weilin Zeng
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Xing Li
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Maigeng Zhou
- The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing 100050, China
| | - Cunrui Huang
- Vanke School of Public Health, Tsinghua University, Beijing 100084, China
| | - Wenjun Ma
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 511443, China.
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Kharwadkar S, Attanayake V, Duncan J, Navaratne N, Benson J. The impact of climate change on the risk factors for tuberculosis: A systematic review. ENVIRONMENTAL RESEARCH 2022; 212:113436. [PMID: 35550808 DOI: 10.1016/j.envres.2022.113436] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 04/03/2022] [Accepted: 05/04/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Tuberculosis (TB) continues to pose a major public health risk in many countries. The current incidence of disease exceeds guidelines proposed by the World Health Organisation and United Nations. Whilst the relationship between climate change and TB has surfaced in recent literature, it remains neglected in global agendas. There is a need to acknowledge TB as a climate-sensitive disease to facilitate its eradication. OBJECTIVE To review epidemiological and prediction model studies that explore how climate change may affect the risk factors for TB, as outlined in the Global Tuberculosis Report 2021: HIV infection, diabetes mellitus, undernutrition, overcrowding, poverty, and indoor air pollution. METHODS We conducted a systematic literature search of PubMed, Embase, and Scopus databases to identify studies examining the association between climate variables and the risk factors for TB. Each study that satisfied the inclusion criteria was assessed for quality and ethics. Studies then underwent vote-counting and were categorised based on whether an association was found. RESULTS 53 studies met inclusion criteria and were included in our review. Vote-counting revealed that two out of two studies found a positive association between the examined climate change proxy and HIV, nine out of twelve studies for diabetes, eight out of seventeen studies for undernutrition, four out of five studies for overcrowding, twelve out of fifteen studies for poverty and one out of three studies for indoor air pollution. DISCUSSION We found evidence supporting a positive association between climate change and each of the discussed risk factors for TB, excluding indoor air pollution. Our findings suggest that climate change is likely to affect the susceptibility of individuals to TB by increasing the prevalence of its underlying risk factors, particularly in developing countries. This is an evolving field of research that requires further attention in the scientific community.
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Affiliation(s)
- Sahil Kharwadkar
- School of Medicine, The University of Adelaide, Australia; School of Public Health, The University of Adelaide, Australia.
| | | | - John Duncan
- School of Medicine, The University of Adelaide, Australia.
| | | | - Jill Benson
- Discipline of General Practice, School of Medicine, The University of Adelaide, Australia.
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Li H, Li M, Zhang S, Qian ZM, Zhang Z, Zhang K, Wang C, Arnold LD, McMillin SE, Wu S, Tian F, Lin H. Interactive effects of cold spell and air pollution on outpatient visits for anxiety in three subtropical Chinese cities. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 817:152789. [PMID: 34990686 PMCID: PMC8907861 DOI: 10.1016/j.scitotenv.2021.152789] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 12/13/2021] [Accepted: 12/26/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND Although low temperature and air pollution exposures have been associated with the risk of anxiety, their combined effects remain unclear. OBJECTIVE To investigate the independent and interactive effects of low temperature and air pollution exposures on anxiety. METHOD Using a case-crossover study design, the authors collected data from 101,636 outpatient visits due to anxiety in three subtropical Chinese cities during the cold season (November to April in 2013 through 2018), and then built conditional logistic regression models based on individual exposure assessments [temperature, relative humidity, particulate matter (PM2.5, PM10), sulfur dioxide (SO2), and nitrogen dioxide (NO2)] and twelve cold spell definitions. Additive-scale interactions were assessed using the relative excess risk due to interaction (RERI). RESULTS Both cold spell and air pollution were significantly associated with outpatients for anxiety. The effects of cold spell increased with its intensity, ranging from 8.98% (95% CI: 2.02%, 16.41%) to 15.24% (95% CI: 6.75%, 24.39%) in Huizhou. Additionally, each 10 μg/m3 increase of PM2.5, PM10, NO2 and SO2 was associated with a 1.51% (95% CI: 0.61%, 2.43%), 1.58% (95% CI: 0.89%, 2.28%), 13.95% (9.98%, 18.05%) and 11.84% (95% CI: 8.25%, 15.55%) increase in outpatient visits for anxiety. Synergistic interactions (RERI >0) of cold spell with all four air pollutants on anxiety were observed, especially for more intense cold spells. For particulate matters, these interactions were found even under mild cold spell definitions [RERI: 0.11 (95% CI: 0.02, 0.21) for PM2.5, and 0.24 (95% CI: 0.14, 0.33) for PM10]. Stratified analyses yielded a pronounced results in people aged 18-65 years. CONCLUSIONS These findings indicate that both cold spell and air pollution are important drivers of the occurrence of anxiety, and simultaneous exposure to these two factors might have synergistic effects on anxiety. These findings highlight the importance of controlling air pollution and improving cold-warning systems.
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Affiliation(s)
- Huan Li
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Min Li
- Department of Preventive Medicine, The Third Affiliated Hospital of Guangzhou University of Chinese Medicine, The Third Clinical Medical Institute Affiliated to Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Shiyu Zhang
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Zhengmin Min Qian
- Department of Epidemiology and Biostatistics, College for Public Health & Social Justice, Saint Louis University, Saint Louis, USA
| | - Zilong Zhang
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Kai Zhang
- Department of Environmental Health Sciences, School of Public Health, University at Albany, State University of New York, USA
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan 450001, China
| | - Lauren D Arnold
- Department of Epidemiology and Biostatistics, College for Public Health & Social Justice, Saint Louis University, Saint Louis, USA
| | - Stephen Edward McMillin
- School of Social Work, College for Public Health & Social Justice, Saint Louis University, Saint Louis, USA
| | - Shaowei Wu
- Department of Occupational and Environmental Health, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710000, China
| | - Fei Tian
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Hualiang Lin
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
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15
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Wen B, Wu Y, Xu R, Guo Y, Li S. Excess emergency department visits for cardiovascular and respiratory diseases during the 2019-20 bushfire period in Australia: A two-stage interrupted time-series analysis. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 809:152226. [PMID: 34890657 DOI: 10.1016/j.scitotenv.2021.152226] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 11/14/2021] [Accepted: 12/03/2021] [Indexed: 06/13/2023]
Abstract
The health effects of the unprecedented bushfires in Australia in 2019-20 have not been fully examined. We aimed to examine the excess emergency department (ED) visits related to the 2019-20 bushfires in New South Wales (NSW). We obtained weekly data of ED visits for cardiovascular and respiratory diseases in all the 28 Statistical Area Level 4 (SA4) regions in NSW during the bushfire seasons from 2017 to 2020. A two-stage interrupted time-series analysis was applied to quantify the excess risk for ED visits in 2019-20. The total number of excess ED visits, excess percentages, and their empirical confidence intervals (eCIs) were calculated to estimate the impacts of the bushfire season. A total of 416,057 records of cardiorespiratory ED visits were included in our analysis. The bushfire season in 2019-20 was significantly associated with a 6.0% increase (95% eCI: 1.9, 10.3) in ED visits for respiratory diseases and a 10.0% increase (95% eCI: 5.0, 15.2) for cardiovascular diseases, corresponding to 6177 (95% eCI: 1989, 10,166) and 3120 (95% eCI: 1628, 4544) excess ED visits, respectively. The percentage of excess ED visits was higher in regions with lower SES and high fire density. In the context of climate change, more targeted strategies should be developed to prevent adverse bushfire effects and recover from such extreme environmental events.
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Affiliation(s)
- Bo Wen
- School of Public Health and Preventive Medicine, Monash University, Level 2, 553 St Kilda Road, Melbourne, VIC 3004, Australia
| | - Yao Wu
- School of Public Health and Preventive Medicine, Monash University, Level 2, 553 St Kilda Road, Melbourne, VIC 3004, Australia
| | - Rongbin Xu
- School of Public Health and Preventive Medicine, Monash University, Level 2, 553 St Kilda Road, Melbourne, VIC 3004, Australia
| | - Yuming Guo
- School of Public Health and Preventive Medicine, Monash University, Level 2, 553 St Kilda Road, Melbourne, VIC 3004, Australia.
| | - Shanshan Li
- School of Public Health and Preventive Medicine, Monash University, Level 2, 553 St Kilda Road, Melbourne, VIC 3004, Australia.
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Wen B, Xu R, Wu Y, Coêlho MDSZS, Saldiva PHN, Guo Y, Li S. Association between ambient temperature and hospitalization for renal diseases in Brazil during 2000-2015: A nationwide case-crossover study. LANCET REGIONAL HEALTH. AMERICAS 2022; 6:100101. [PMID: 36777886 PMCID: PMC9904055 DOI: 10.1016/j.lana.2021.100101] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 09/23/2021] [Accepted: 09/27/2021] [Indexed: 12/24/2022]
Abstract
Background Climate change is increasing the risks of injuries, diseases, and deaths globally. However, the association between ambient temperature and renal diseases has not been fully characterized. This study aimed to quantify the risk and attributable burden for hospitalizations of renal diseases related to ambient temperature. Methods Daily hospital admission data from 1816 cities in Brazil were collected during 2000 and 2015. A time-stratified case-crossover design was applied to evaluate the association between temperature and renal diseases. Relative risks (RRs), attributable fractions (AFs), and their confidence intervals (CIs) were calculated to estimate the associations and attributable burden. Findings A total of 2,726,886 hospitalizations for renal diseases were recorded during the study period. For every 1°C increase in daily mean temperature, the estimated risk of hospitalization for renal diseases over lag 0-7 days increased by 0·9% (RR = 1·009, 95% CI: 1·008-1·010) at the national level. The associations between temperature and renal diseases were largest at lag 0 days but remained for lag 1-2 days. The risk was more prominent in females, children aged 0-4 years, and the elderly ≥ 80 years. 7·4% (95% CI: 5·2-9·6%) of hospitalizations for renal diseases could be attributable to the increase of temperature, equating to 202,093 (95% CI: 141,554-260,594) cases. Interpretation This nationwide study provides robust evidence that more policies should be developed to prevent heat-related hospitalizations and mitigate climate change. Funding China Scholarship Council, and the Australian National Health and Medical Research Council.
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Affiliation(s)
- Bo Wen
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Rongbin Xu
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yao Wu
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | | | | | - Yuming Guo
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Shanshan Li
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
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Sun S, Weinberger KR, Nori-Sarma A, Spangler KR, Sun Y, Dominici F, Wellenius GA. Ambient heat and risks of emergency department visits among adults in the United States: time stratified case crossover study. BMJ 2021; 375:e065653. [PMID: 34819309 PMCID: PMC9397126 DOI: 10.1136/bmj-2021-065653] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/01/2021] [Indexed: 12/23/2022]
Abstract
OBJECTIVE To quantify the association between ambient heat and visits to the emergency department (ED) for any cause and for cause specific conditions in the conterminous United States among adults with health insurance. DESIGN Time stratified case crossover analyses with distributed lag non-linear models. SETTING US nationwide administrative healthcare claims database. PARTICIPANTS All commercial and Medicare Advantage beneficiaries (74.2 million) aged 18 years and older between May and September 2010 to 2019. MAIN OUTCOME MEASURES Daily rates of ED visits for any cause, heat related illness, renal disease, cardiovascular disease, respiratory disease, and mental disorders based on discharge diagnosis codes. RESULTS 21 996 670 ED visits were recorded among adults with health insurance living in 2939 US counties. Days of extreme heat-defined as the 95th centile of the local warm season (May through September) temperature distribution (at 34.4°C v 14.9°C national average level)-were associated with a 7.8% (95% confidence interval 7.3% to 8.2%) excess relative risk of ED visits for any cause, 66.3% (60.2% to 72.7%) for heat related illness, 30.4% (23.4% to 37.8%) for renal disease, and 7.9% (5.2% to 10.7%) for mental disorders. Days of extreme heat were associated with an excess absolute risk of ED visits for heat related illness of 24.3 (95% confidence interval 22.9 to 25.7) per 100 000 people at risk per day. Heat was not associated with a higher risk of ED visits for cardiovascular or respiratory diseases. Associations were more pronounced among men and in counties in the north east of the US or with a continental climate. CONCLUSIONS Among both younger and older adults, days of extreme heat are associated with a higher risk of ED visits for any cause, heat related illness, renal disease, and mental disorders. These results suggest that the adverse health effects of extreme heat are not limited to older adults and carry important implications for the health of adults across the age spectrum.
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Affiliation(s)
- Shengzhi Sun
- Department of Environmental Health, Boston University School of Public Health, Boston 02118, MA, USA
- OptumLabs, Eden Prairie, MN, USA
| | - Kate R Weinberger
- School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada
| | - Amruta Nori-Sarma
- Department of Environmental Health, Boston University School of Public Health, Boston 02118, MA, USA
| | - Keith R Spangler
- Department of Environmental Health, Boston University School of Public Health, Boston 02118, MA, USA
| | - Yuantong Sun
- Department of Environmental Health, Boston University School of Public Health, Boston 02118, MA, USA
| | - Francesca Dominici
- Harvard T H Chan School of Public Health, Department of Biostatistics, Boston, MA, USA
| | - Gregory A Wellenius
- Department of Environmental Health, Boston University School of Public Health, Boston 02118, MA, USA
- OptumLabs, Eden Prairie, MN, USA
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18
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Xu R, Li S, Li S, Wong EM, Southey MC, Hopper JL, Abramson MJ, Guo Y. Ambient temperature and genome-wide DNA methylation: A twin and family study in Australia. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 285:117700. [PMID: 34380236 DOI: 10.1016/j.envpol.2021.117700] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 06/29/2021] [Accepted: 06/30/2021] [Indexed: 06/13/2023]
Abstract
Little is known about the association between ambient temperature and DNA methylation, which is a potential biological process through which ambient temperature affects health. This study aimed to evaluate the association between ambient temperature and DNA methylation across human genome. We included 479 Australian women, including 132 twin pairs and 215 sisters of these twins. Blood-derived DNA methylation was measured using the HumanMethylation450 BeadChip array. Data on average ambient temperature during eight different exposure windows [lag0d (the blood draw day), lag0-7d (the current day and previous seven days prior to blood draw), lag0-14d, lag0-21d, lag0-28d, lag0-90d, lag0-180d, and lag0-365d)] was linked to each participant's home address. For each cytosine-guanine dinucleotide (CpG), we evaluated the association between its methylation level and temperature using generalized estimating equations (GEE), adjusting for important covariates. We used comb-p and DMRcate to identify differentially methylated regions (DMRs). We identified 31 CpGs at which blood DNA methylation were significantly associated with ambient temperature with false discovery rate [FDR] < 0.05. There were 82 significant DMRs identified by both comb-p (Sidak p-value < 0.01) and DMRcate (FDR < 0.01). Most of these CpGs and DMRs only showed association with temperature during one specific exposure window. These CpGs and DMRs were mapped to 85 genes. These related genes have been related to many human chronic diseases or phenotypes (e.g., diabetes, arthritis, breast cancer, depression, asthma, body height) in previous studies. The signals of short-term windows (lag0d and lag0-21d) showed enrichment in biological processes related to cell adhesion. In conclusion, short-, medium-, and long-term exposures to ambient temperature were all associated with blood DNA methylation, but the target genomic loci varied by exposure window. These differential methylation signals may serve as potential biomarkers to understand the health impacts of temperature.
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Affiliation(s)
- Rongbin Xu
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
| | - Shuai Li
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, 3010, Australia; Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK; Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, 3800, Australia
| | - Shanshan Li
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
| | - Ee Ming Wong
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, 3800, Australia; Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Melbourne, VIC, 3010, Australia
| | - Melissa C Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, 3800, Australia; Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Melbourne, VIC, 3010, Australia; Cancer Epidemiology Division, Cancer Council Victoria, VIC, 3004, Australia
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, 3010, Australia
| | - Michael J Abramson
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
| | - Yuming Guo
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia.
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19
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Yu P, Xu R, Coelho MSZS, Saldiva PHN, Li S, Zhao Q, Mahal A, Sim M, Abramson MJ, Guo Y. The impacts of long-term exposure to PM 2.5 on cancer hospitalizations in Brazil. ENVIRONMENT INTERNATIONAL 2021; 154:106671. [PMID: 34082238 DOI: 10.1016/j.envint.2021.106671] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 04/16/2021] [Accepted: 05/24/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND Long-term exposure to PM2.5 has been linked to cancer incidence and mortality. However, it was unknown whether there was an association with cancer hospitalizations. METHODS Data on cancer hospitalizations and annual PM2.5 concentrations were collected from 1,814 Brazilian cities during 2002-2015. A difference-in-difference approach with quasi-Poisson regression was applied to examine State-specific associations. The State-specific associations were pooled at a national level using random-effect meta-analyses. PM2.5 attributable burden were estimated for cancer hospitalization admissions, inpatient days and costs. RESULTS We included 5,102,358 cancer hospitalizations (53.8% female). The mean annual concentration of PM2.5 was 7.0 μg/m3 (standard deviation: 4.0 μg/m3). With each 1 μg/m3 increase in two-year-average (current year and previous one year) concentrations of PM2.5, the relative risks (RR) of hospitalization were 1.04 (95% confidence interval [CI]: 1.02 to 1.07) for all-site cancers from 2002 to 2015 without sex and age differences. We estimated that 33.82% (95%CI: 14.97% to 47.84%) of total cancer hospitalizations could be attributed to PM2.5 exposure in Brazil during the study time. For every 100,000 population, 1,190 (95%CI: 527 to 1,836) cancer hospitalizations, 8,191 (95%CI: 3,627 to 11,587) inpatient days and US$788,775 (95%CI: $349,272 to $1,115,825) cost were attributable to PM2.5 exposure. CONCLUSIONS Long-term exposure to ambient PM2.5 was positively associated with hospitalization for many cancer types in Brazil. Inpatient days and cost would be saved if the annual PM2.5 exposure was reduced.
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Affiliation(s)
- Pei Yu
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Rongbin Xu
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | | | | | - Shanshan Li
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Qi Zhao
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia; Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Ajay Mahal
- Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia
| | - Malcolm Sim
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Michael J Abramson
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yuming Guo
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
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20
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Bergmans RS, Larson P, Bennion E, Mezuk B, Wozniak MC, Steiner AL, Gronlund CJ. Short-term exposures to atmospheric evergreen, deciduous, grass, and ragweed aeroallergens and the risk of suicide in Ohio, 2007-2015: Exploring disparities by age, gender, and education level. ENVIRONMENTAL RESEARCH 2021; 200:111450. [PMID: 34102161 PMCID: PMC8404218 DOI: 10.1016/j.envres.2021.111450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Revised: 05/27/2021] [Accepted: 05/29/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND Seasonal trends in suicide mortality are observed worldwide, potentially aligning with the seasonal release of aeroallergens. However, only a handful of studies have examined whether aeroallergens increase the risk of suicide, with inconclusive results thus far. The goal of this study was to use a time-stratified case-crossover design to test associations of speciated aeroallergens (evergreen, deciduous, grass, and ragweed) with suicide deaths in Ohio, USA (2007-2015). METHODS Residential addresses for 12,646 persons who died by suicide were linked with environmental data at the 4-25 km grid scale including atmospheric aeroallergen concentrations, maximum temperature, sunlight, particulate matter <2.5 μm, and ozone. A case-crossover design was used to examine same-day and 7-day cumulative lag effects on suicide. Analyses were stratified by age group, gender, and educational level. RESULTS In general, associations were null between aeroallergens and suicide. Stratified analyses revealed a relationship between grass pollen and same-day suicide for women (OR = 3.84; 95% CI = 1.44, 10.22) and those with a high school degree or less (OR = 2.03; 95% CI = 1.18, 3.49). CONCLUSIONS While aeroallergens were generally not significantly related to suicide in this sample, these findings provide suggestive evidence for an acute relationship of grass pollen with suicide for women and those with lower education levels. Further research is warranted to determine whether susceptibility to speciated aeroallergens may be driven by underlying biological mechanisms or variation in exposure levels.
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Affiliation(s)
- Rachel S Bergmans
- Institute for Social Research, University of Michigan, Ann Arbor, MI, 48106, USA.
| | - Peter Larson
- Institute for Social Research, University of Michigan, Ann Arbor, MI, 48106, USA
| | - Erica Bennion
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Briana Mezuk
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Matthew C Wozniak
- Department of Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Allison L Steiner
- Department of Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Carina J Gronlund
- Institute for Social Research, University of Michigan, Ann Arbor, MI, 48106, USA
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21
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Ye T, Guo Y, Chen G, Yue X, Xu R, Coêlho MDSZS, Saldiva PHN, Zhao Q, Li S. Risk and burden of hospital admissions associated with wildfire-related PM 2·5 in Brazil, 2000-15: a nationwide time-series study. Lancet Planet Health 2021; 5:e599-e607. [PMID: 34508681 DOI: 10.1016/s2542-5196(21)00173-x] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 06/08/2021] [Accepted: 06/08/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND In the context of climate change and deforestation, Brazil is facing more frequent and unprecedented wildfires. Wildfire-related PM2·5 is associated with multiple adverse health outcomes; however, the magnitude of these associations in the Brazilian context is unclear. We aimed to estimate the association between daily exposure to wildfire-related PM2·5 and cause-specific hospital admission and attributable health burden in the Brazilian population using a nationwide dataset from 2000 to 2015. METHODS In this nationwide time-series analysis, data for daily all-cause, cardiovascular, and respiratory hospital admissions were collected through the Brazilian Unified Health System from 1814 municipalities in Brazil between Jan 1, 2000, and Dec 31, 2015. Daily concentrations of wildfire-related PM2·5 were estimated using the 3D chemical transport model GEOS-Chem at a 2·0° latitude by 2·5° longitude resolution. A time-series analysis was fitted using quasi-Poisson regression to quantify municipality-specific effect estimates, which were then pooled at the regional and national levels using random-effects meta-analyses. Analyses were stratified by sex and ten age groups. The attributable fraction and attributable cases of hospital admissions due to wildfire-related PM2·5 were also calculated. FINDINGS At the national level, a 10 μg/m3 increase in wildfire-related PM2·5 was associated with a 1·65% (95% CI 1·51-1·80) increase in all-cause hospital admissions, a 5·09% (4·73-5·44) increase in respiratory hospital admissions, and a 1·10% (0·78-1·42) increase in cardiovascular hospital admissions, over 0-1 days after the exposure. The effect estimates for all-cause hospital admission did not vary by sex, but were particularly high in children aged 4 years or younger (4·88% [95% CI 4·47-5·28]), children aged 5-9 years (2·33% [1·77-2·90]), and people aged 80 years and older (3·70% [3·20-4·20]) compared with other age groups. We estimated that 0·53% (95% CI 0·48-0·58) of all-cause hospital admissions were attributable to wildfire-related PM2·5, corresponding to 35 cases (95% CI 32-38) per 100 000 residents annually. The attributable rate was greatest for municipalities in the north, south, and central-west regions, and lowest in the northeast region. Results were consistent for all-cause and respiratory diseases across regions, but remained inconsistent for cardiovascular diseases. INTERPRETATION Short-term exposure to wildfire-related PM2·5 was associated with increased risks of all-cause, respiratory, and cardiovascular hospital admissions, particularly among children (0-9 years) and older people (≥80 years). Greater attention should be paid to reducing exposure to wildfire smoke, particularly for the most susceptible populations. FUNDING Australian Research Council and Australian National Health and Medical Research Council.
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Affiliation(s)
- Tingting Ye
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia; School of Public Health and Management, Binzhou Medical University, Yantai, China
| | - Yuming Guo
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia; School of Public Health and Management, Binzhou Medical University, Yantai, China.
| | - Gongbo Chen
- Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Xu Yue
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, China
| | - Rongbin Xu
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | | | | | - Qi Zhao
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia; Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Shanshan Li
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
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Xu R, Li S, Li S, Wong EM, Southey MC, Hopper JL, Abramson MJ, Guo Y. Surrounding Greenness and Biological Aging Based on DNA Methylation: A Twin and Family Study in Australia. ENVIRONMENTAL HEALTH PERSPECTIVES 2021; 129:87007. [PMID: 34460342 PMCID: PMC8404778 DOI: 10.1289/ehp8793] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 08/06/2021] [Accepted: 08/10/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND High surrounding greenness has many health benefits and might contribute to slower biological aging. However, very few studies have evaluated this from the perspective of epigenetics. OBJECTIVES We aimed to evaluate the association between surrounding greenness and biological aging based on DNA methylation. METHODS We derived Horvath's DNA methylation age (DNAmAge), Hannum's DNAmAge, PhenoAge, and GrimAge based on DNA methylation measured in peripheral blood samples from 479 Australian women in 130 families. Measures of DNAmAge acceleration (DNAmAgeAC) were derived from the residuals after regressing each DNAmAge metric on chronological age. Greenness was represented by satellite-derived Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) metrics within 300-, 500-, 1,000-, and 2,000-m buffers surrounding participant addresses. Greenness-DNAmAgeAC associations were estimated using a within-sibship design fitted by linear mixed effect models, adjusting for familial clustering and important covariates. RESULTS Greenness metrics were associated with significantly lower DNAmAgeAC based on GrimAge acceleration, suggesting slower biological aging with higher greenness based on both NDVI and EVI in 300-2,000m buffer areas. For example, each interquartile range increase in NDVI within 1,000m was associated with a 0.59 (95% CI: 0.18, 1.01)-year decrease in GrimAge acceleration. Greenness was also inversely associated with three of the eight components of GrimAge, specifically, DNA methylation-based surrogates of serum cystatin-C, serum growth differentiation factor 15, and smoking pack years. Associations between greenness and biological aging measured by Horvath's and Hannum's DNAmAgeAC were less consistent, and depended on neighborhood socioeconomic status. No significant associations were estimated for PhenoAge acceleration. DISCUSSION Higher surrounding greenness was associated with slower biological aging, as indicated by GrimAge age acceleration, in Australian women. Associations were also evident for three individual components of GrimAge, but were inconsistent for other measures of biological aging. Additional studies are needed to confirm our results. https://doi.org/10.1289/EHP8793.
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Affiliation(s)
- Rongbin Xu
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Shuai Li
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Shanshan Li
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Ee Ming Wong
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Department of Clinical Pathology, Melbourne Medical School, University of Melbourne, Melbourne, Victoria, Australia
| | - Melissa C. Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Department of Clinical Pathology, Melbourne Medical School, University of Melbourne, Melbourne, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Victoria, Australia
| | - John L. Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Michael J. Abramson
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Yuming Guo
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
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Han C, Xu R, Gao CX, Yu W, Zhang Y, Han K, Yu P, Guo Y, Li S. Socioeconomic disparity in the association between long-term exposure to PM 2.5 and mortality in 2640 Chinese counties. ENVIRONMENT INTERNATIONAL 2021; 146:106241. [PMID: 33160162 DOI: 10.1016/j.envint.2020.106241] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Revised: 10/20/2020] [Accepted: 10/22/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND Although the association between long-term exposure to PM2.5 and mortality has been evaluated intensively, little is known about the socioeconomic disparity in the association. METHODS We collected data on annual all-cause mortality, PM2.5 concentration, socioeconomic and demographic characteristics of 2640 counties from the two most recent Chinese censuses in 2000 and 2010. We applied the difference-in-differences (DID) method to estimate PM2.5-mortality association for counties at different quartiles of literacy rate, college rate, urbanization rate and GDP per capita, respectively. RESULTS Overall, every 10 µg/m3 increase in annual average PM2.5 was associated with 3.8% (95% confidence interval [CI]: 3.0-5.0) increase of all-cause mortality. The stratified analysis suggested higher health impact of exposure in counties with lower socioeconomic status. For counties of the lowest quartile (Q1) of literacy rate, college rate, urbanization rate and GDP per capita, the effect estimates were 6.0% (95% CI: 4.2-7.7), 4.4% (95% CI: 2.8-6.0), 3.5% (95% CI: 2.0-5.1) and 4.9% (95% CI: 2.7-7.1), respectively. There was strong evidence for elevated risk in mortality associated with PM2.5 of all socioeconomic factors in the lowest quartile (Q1) compared with the highest quartile counties (Q4) (p-value for difference < 0.05). CONCLUSIONS There was socioeconomic disparity in the PM2.5-mortality association in China. Dwellers living in less developed counties are more vulnerable to long-term exposure to ambient PM2.5 than those living in developed counties.
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Affiliation(s)
- Chunlei Han
- School of Public Health and Management, Binzhou Medical University, Yantai, Shandong, China; Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Rongbin Xu
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Caroline X Gao
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia; Centre for Youth Mental Health (Orygen), University of Melbourne, Melbourne, Australia
| | - Wenhua Yu
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yajuan Zhang
- School of Public Health and Management, Ningxia Medical University, Yinchuan, Ningxia Hui Autonomous Region, China
| | - Kun Han
- School of Economy, Shandong University, Jinan, Shandong, China
| | - Pei Yu
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yuming Guo
- School of Public Health and Management, Binzhou Medical University, Yantai, Shandong, China; Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
| | - Shanshan Li
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
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Xu R, Zhao Q, Coelho MSZS, Saldiva PHN, Abramson MJ, Li S, Guo Y. Socioeconomic inequality in vulnerability to all-cause and cause-specific hospitalisation associated with temperature variability: a time-series study in 1814 Brazilian cities. Lancet Planet Health 2020; 4:e566-e576. [PMID: 33278374 DOI: 10.1016/s2542-5196(20)30251-5] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Revised: 09/06/2020] [Accepted: 10/02/2020] [Indexed: 06/12/2023]
Abstract
BACKGROUND Exposure to temperature variability has been associated with increased risk of mortality and morbidity. We aimed to evaluate whether the association between short-term temperature variability and hospitalisation was affected by local socioeconomic level in Brazil. METHODS In this time-series study, we collected city-level socioeconomic data, and daily hospitalisation and weather data from 1814 Brazilian cities between Jan 1, 2000, and Dec 31, 2015. All-cause and cause-specific hospitalisation data was from the Hospital Information System of the Unified Health System in Brazil. City-specific daily minimum and maximum temperatures came from a 0·25° × 0·25° Brazilian meteorological dataset. We represented city-specific socioeconomic level using literacy rate, urbanisation rate, average monthly household income per capita (using the 2000 and 2010 Brazilian census), and GDP per capita (using statistics from the Brazilian Institute of Geography and Statistics for 2000-15), and cities were categorised according to the 2015 World Bank standard. We used quasi-Poisson regression to do time-series analyses and obtain city-specific associations between temperature variability and hospitalisation. We pooled city-specific estimates according to different socioeconomic quartiles or levels using random-effect meta-analyses. Meta-regressions adjusting for demographic and climatic characteristics were used to evaluate the modification effect of city-level socioeconomic indicators on the association between temperature variability and hospitalisation. FINDINGS We included a total of 147 959 243 hospitalisations (59·0% female) during the study period. Overall, we estimated that the hospitalisation risk due to every 1°C increase in the temperature variability in the current and previous day (TV0-1) increased by 0·52% (95% CI 0·50-0·55). For lower-middle-income cities, this risk was 0·63% (95% CI 0·58-0·69), for upper-middle-income cities it was 0·50% (0·47-0·53), and for high-income cities it was 0·39% (0·33-0·46). The socioeconomic inequality in vulnerability to TV0-1 was especially evident for people aged 0-19 years (effect estimate 1·21% [1·11-1·31] for lower-middle income vs 0·52% [0·41-0·63] for high income) and people aged 60 years or older (0·60% [0·50-0·70] vs 0·43% [0·31-0·56]), and for hospitalisation due to infectious diseases (1·62% [1·46-1·78] vs 0·56% [0·30-0·82]), respiratory diseases (1·32% [1·20-1·44] vs 0·55% [0·37-0·74]), and endocrine diseases (1·21% [0·99-1·43] vs 0·32% [0·02-0·62]). INTERPRETATION People living in less developed cities in Brazil were more vulnerable to hospitalisation related to temperature variability. This disparity could exacerbate existing health and socioeconomic inequalities in Brazil, and it suggests that more attention should be paid to less developed areas to mitigate the adverse health effects of short-term temperature fluctuations. FUNDING None.
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Affiliation(s)
- Rongbin Xu
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Qi Zhao
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Micheline S Z S Coelho
- Department of Pathology, Faculty of Medicine, University of São Paulo, São Paulo, Brazil
| | - Paulo H N Saldiva
- Department of Pathology, Faculty of Medicine, University of São Paulo, São Paulo, Brazil
| | - Michael J Abramson
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Shanshan Li
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia; College of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
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Xu R, Xiong X, Abramson MJ, Li S, Guo Y. Ambient temperature and intentional homicide: A multi-city case-crossover study in the US. ENVIRONMENT INTERNATIONAL 2020; 143:105992. [PMID: 32738768 DOI: 10.1016/j.envint.2020.105992] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Revised: 06/30/2020] [Accepted: 07/16/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND There has been an increasing interest in the association between ambient temperature and violence and crime, in the context of global warming. We aimed to evaluate the association between daily ambient temperature and intentional homicide-a proxy for overall inter-personal violence. METHODS We collected daily weather and crime data from 9 large US cities (Chicago, Detroit, Fort Worth, Kansas City, Los Angeles, Louisville, New York, Tucson and Virginia Beach) from 2007 to 2017. A time-stratified case-crossover design was used. The associations were quantified by conditional logistic regression with distributed lag models, adjusting for relative humidity, precipitation and effects of public holidays. City-specific odds ratios (OR) were used to calculate the attributable fractions in each city. RESULTS Based on 19,523 intentional homicide cases, we found a linear temperature-homicide association. Every 5 °C increase in daily mean temperature was associated with a 9.5% [95% confidence interval (CI): 4.3-15.0%] and 8.8% (95% CI: 1.5-16.6%) increase in intentional homicide over lag 0-7 days in Chicago and New York, respectively. The association was not statistically significant in the other seven cities and seemed to be stronger for cases that happened during the hot season, at night (18:00-06:00) and on the street. During the study period, 8.7% (95%CI: 4.3-12.7%) and 7.1% (95% CI: 1.4-12.0%) intentional homicide cases could be attributed to temperatures above city-specific median temperatures, corresponding to 488 and 316 excess cases in Chicago and New York, respectively. CONCLUSIONS Our study suggests that the interpersonal violence might increase with temperature in some US cities. We also provide some insights into the mechanisms and targeted prevention strategies for heat-related violence.
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Affiliation(s)
- Rongbin Xu
- School of Public Health and Management, Binzhou Medical University, Yantai, Shandong, China; Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria 3004, Australia
| | - Xiuqin Xiong
- Centre for Health Policy, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria 3010, Australia
| | - Michael J Abramson
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria 3004, Australia
| | - Shanshan Li
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria 3004, Australia.
| | - Yuming Guo
- School of Public Health and Management, Binzhou Medical University, Yantai, Shandong, China; Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria 3004, Australia.
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