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Cohen G, Rowland ST, Benavides J, Lindert J, Kioumourtzoglou MA, Parks RM. Daily temperature variability and mental health-related hospital visits in New York State. ENVIRONMENTAL RESEARCH 2024; 257:119238. [PMID: 38815717 DOI: 10.1016/j.envres.2024.119238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 05/11/2024] [Accepted: 05/25/2024] [Indexed: 06/01/2024]
Abstract
BACKGROUND Despite plausible behavioral and physiological pathways, limited evidence exists on how daily temperature variability is associated with acute mental health-related episodes. OBJECTIVES We aimed to explore associations between daily temperature range (DTR) and mental health-related hospital visits using data of all hospital records in New York State during 1995-2014. We further examined factors that may modify these associations, including age, sex, hospital visit type and season. METHODS Using a case-crossover design with distributed lag non-linear DTR terms (0-6 days), we estimated associations between ZIP Code-level DTR and hospital visits for mood (4.6 million hospital visits), anxiety (2.4 million), adjustment (∼368,000), and schizophrenia disorders (∼211,000), controlling for daily mean temperature, via conditional logistic regression models. We assessed potential heterogeneity by age, sex, hospital visit type (in-patient vs. out-patient), and season (summer, winter, and transition seasons). RESULTS For all included outcomes, we observed positive associations from period minimum DTR (0.1 °C) until 25th percentile (5.2 °C) and between mean DTR (7.7 °C) and 90th percentile (12.2 °C), beyond which we observed negative associations. For mood disorders, an increase in DTR from 0.1 °C to 12.2 °C was associated with a cumulative 16.0% increase (95% confidence interval [CI]: 12.8, 19.2%) in hospital visit rates. This increase was highest during transition seasons (32.5%; 95%CI: 26.4, 39.0%) compared with summer (10.7%; 95%CI: 4.8, 16.8%) and winter (-1.6%; 95%CI: -7.6, 4.7%). For adjustment and schizophrenia disorders, the strongest associations were seen among the youngest group (0-24 years) with almost no association in the oldest group (65+ years). We observed no evidence for modification by sex and hospital visit type. DISCUSSION Daily temperature variability was positively associated with mental health-related hospital visits within specific DTR ranges in New York State, after controlling for daily mean temperature. Given uncertainty on how climate change modifies temperature variability, additional research is crucial to comprehend the implications of these findings, particularly under different scenarios of future temperature variability.
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Affiliation(s)
- Gali Cohen
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA; Department of Epidemiology and Preventive Medicine, School of Public Health, Faculty of Medicine, Tel Aviv University, Israel
| | - Sebastian T Rowland
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Jaime Benavides
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Jutta Lindert
- Department of Health and Social Work, University of Applied Sciences Emden, Emden, Germany
| | | | - Robbie M Parks
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA.
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Jiang F, Wang R, Yang Y, Jia X, Ma L, Yuan M, Liu K, Bao J. Effects of intra- and inter-day temperature change on acute upper respiratory infections among college students, assessments of three temperature change indicators. Front Public Health 2024; 12:1406415. [PMID: 39247226 PMCID: PMC11377250 DOI: 10.3389/fpubh.2024.1406415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Accepted: 07/31/2024] [Indexed: 09/10/2024] Open
Abstract
Background Acute upper respiratory infection (AURI) is a significant disease affecting all age groups worldwide. The differences in the impacts of different temperature change indicators, such as diurnal temperature range (DTR), temperature variation (TV), and temperature change between neighboring days (TCN), on AURI morbidity, are not clear. Methods We collected data on 87,186 AURI patients during 2014-2019 in Zhengzhou. Distributed lag non-linear model was adopted to examine the effects of different temperature change indicators on AURI. We calculated and compared the attributable fractions (AF) of AURI morbidity caused by various indicators. We used stratified analysis to investigate the modification effects of season and gender. Results With the increase in DTR and TV, the risk of AURI tended to increase; the corresponding AF values (95% eCI) higher than the references (5% position of the DTR or TV distribution) were 24.26% (15.46%, 32.05%), 23.10% (15.59%, 29.20%), and 19.24% (13.90%, 24.63%) for DTR, TV0 - 1, and TV0 - 7, respectively. The harmful effects of TCN on AURI mainly occurred when the temperature dropped (TCN < 0), and the AF value of TCN below the reference (0°C) was 3.42% (1.60%, 5.14%). The harm of DTR and TV were statistically significant in spring, autumn and winter, but not in summer, while the harm of TCN mainly occurred in winter. Three indicators have statistically significant effects on both males and females. Conclusions High DTR and TV may induce AURI morbidity, while the harm of TCN occurs when the temperature drops. The impacts of DTR and TV on AURI are higher than that of TCN, and the impact of few-day TV is higher than that of multi-day TV. The adverse effects of DTR and TV are significant except in summer, while the hazards of TCN mainly occur in winter.
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Affiliation(s)
- Feng Jiang
- Department of Disease Prevention and Control, Zhengzhou University Hospital, Zhengzhou University, Zhengzhou, Henan, China
| | - Rensong Wang
- Department of Emergency, Shanghai Fengxian District Medical Emergency Center, Shanghai, China
| | - Yongli Yang
- Department of Biostatistics and Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Xiaocan Jia
- Department of Biostatistics and Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Leying Ma
- Department of Biostatistics and Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Mengyang Yuan
- Department of Biostatistics and Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Kangkang Liu
- Department of Research Center for Medicine, The Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen, China
| | - Junzhe Bao
- Department of Biostatistics and Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
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Wen B, Wu Y, Guo Y, Gasparrini A, Tong S, Overcenco A, Urban A, Schneider A, Entezari A, Vicedo-Cabrera AM, Zanobetti A, Analitis A, Zeka A, Tobias A, Nunes B, Alahmad B, Armstrong B, Forsberg B, Pan SC, Íñiguez C, Ameling C, Valencia CDLC, Åström C, Houthuijs D, Van Dung D, Royé D, Indermitte E, Lavigne E, Mayvaneh F, Acquaotta F, de'Donato F, Rao S, Sera F, Carrasco-Escobar G, Kan H, Orru H, Kim H, Holobaca IH, Kyselý J, Madureira J, Schwartz J, Jaakkola JJK, Katsouyanni K, Diaz MH, Ragettli MS, Hashizume M, Pascal M, Coélho MDSZS, Ortega NV, Ryti N, Scovronick N, Michelozzi P, Matus Correa P, Goodman P, Saldiva PHN, Raz R, Abrutzky R, Osorio S, Dang TN, Colistro V, Huber V, Lee W, Seposo X, Honda Y, Kim Y, Guo YL, Bell ML, Li S. Comparison for the effects of different components of temperature variability on mortality: A multi-country time-series study. ENVIRONMENT INTERNATIONAL 2024; 187:108712. [PMID: 38714028 DOI: 10.1016/j.envint.2024.108712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 04/27/2024] [Accepted: 04/28/2024] [Indexed: 05/09/2024]
Abstract
BACKGROUND Temperature variability (TV) is associated with increased mortality risk. However, it is still unknown whether intra-day or inter-day TV has different effects. OBJECTIVES We aimed to assess the association of intra-day TV and inter-day TV with all-cause, cardiovascular, and respiratory mortality. METHODS We collected data on total, cardiovascular, and respiratory mortality and meteorology from 758 locations in 47 countries or regions from 1972 to 2020. We defined inter-day TV as the standard deviation (SD) of daily mean temperatures across the lag interval, and intra-day TV as the average SD of minimum and maximum temperatures on each day. In the first stage, inter-day and intra-day TVs were modelled simultaneously in the quasi-Poisson time-series model for each location. In the second stage, a multi-level analysis was used to pool the location-specific estimates. RESULTS Overall, the mortality risk due to each interquartile range [IQR] increase was higher for intra-day TV than for inter-day TV. The risk increased by 0.59% (95% confidence interval [CI]: 0.53, 0.65) for all-cause mortality, 0.64% (95% CI: 0.56, 0.73) for cardiovascular mortality, and 0.65% (95% CI: 0.49, 0.80) for respiratory mortality per IQR increase in intra-day TV0-7 (0.9 °C). An IQR increase in inter-day TV0-7 (1.6 °C) was associated with 0.22% (95% CI: 0.18, 0.26) increase in all-cause mortality, 0.44% (95% CI: 0.37, 0.50) increase in cardiovascular mortality, and 0.31% (95% CI: 0.21, 0.41) increase in respiratory mortality. The proportion of all-cause deaths attributable to intra-day TV0-7 and inter-day TV0-7 was 1.45% and 0.35%, respectively. The mortality risks varied by lag interval, climate area, season, and climate type. CONCLUSIONS Our results indicated that intra-day TV may explain the main part of the mortality risk related to TV and suggested that comprehensive evaluations should be proposed in more countries to help protect human health.
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Affiliation(s)
- Bo Wen
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yao Wu
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yuming Guo
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
| | - Antonio Gasparrini
- Department of Public Health, Environments and Society, London School of Hygiene & Tropical Medicine, London, UK; Centre for Statistical Methodology, London School of Hygiene & Tropical Medicine, London, UK; Centre on Climate Change & Planetary Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Shilu Tong
- Shanghai Children's Medical Centre, Shanghai Jiao Tong University, Shanghai, China; School of Public Health, Institute of Environment and Population Health, Anhui Medical University, Hefei, China; Center for Global Health, Nanjing Medical University, Nanjing, China; School of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia
| | - Ala Overcenco
- National Agency for Public Health of the Ministry of Health, Labour and Social Protection of the Republic of Moldova, Republic of Moldova
| | - Aleš Urban
- Institute of Atmospheric Physics, Czech Academy of Sciences, Prague, Czech Republic; Faculty of Environmental Sciences, Czech University of Life Sciences, Prague, Czech Republic
| | - Alexandra Schneider
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Alireza Entezari
- Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar, Iran
| | - Ana Maria Vicedo-Cabrera
- Department of Public Health, Environments and Society, London School of Hygiene & Tropical Medicine, London, UK; Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland; Oeschger Center for Climate Change Research, University of Bern, Bern, Switzerland
| | - Antonella Zanobetti
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Antonis Analitis
- Department of Hygiene, Epidemiology and Medical Statistics, National and Kapodistrian University of Athens, Athens, Greece
| | - Ariana Zeka
- Institute for Environment, Health and Societies, Brunel University London, London, UK
| | - Aurelio Tobias
- Institute of Environmental Assessment and Water Research, Spanish Council for Scientific Research, Barcelona, Spain; School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan
| | - Baltazar Nunes
- Department of Epidemiology, Instituto Nacional de Saúde Dr Ricardo Jorge, Porto, Portugal; Centro de Investigação em Saúde Pública, Escola Nacional de Saúde Pública, Universidade NOVA de Lisboa, Lisbon, Portugal
| | - Barrak Alahmad
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Ben Armstrong
- Department of Public Health, Environments and Society, London School of Hygiene & Tropical Medicine, London, UK
| | - Bertil Forsberg
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Shih-Chun Pan
- National Institute of Environmental Health Science, National Health Research Institutes, Zhunan, Taiwan
| | - Carmen Íñiguez
- Department of Statistics and Computational Research, Universitat de València, València, Spain; CIBER of Epidemiology and Public Health, Madrid, Spain
| | - Caroline Ameling
- National Institute for Public Health and the Environment (RIVM), Centre for Sustainability and Environmental Health, Bilthoven, Netherlands
| | | | - Christofer Åström
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Danny Houthuijs
- National Institute for Public Health and the Environment (RIVM), Centre for Sustainability and Environmental Health, Bilthoven, Netherlands
| | - Do Van Dung
- Department of Environmental Health, Faculty of Public Health, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Viet Nam
| | - Dominic Royé
- CIBER of Epidemiology and Public Health, Madrid, Spain; Department of Geography, University of Santiago de Compostela, Santiago de Compostela, Spain
| | - Ene Indermitte
- Institute of Family Medicine and Public Health, University of Tartu, Tartu, Estonia
| | - Eric Lavigne
- School of Epidemiology & Public Health, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada; Air Health Science Division, Health Canada, Ottawa, ON, Canada
| | - Fatemeh Mayvaneh
- Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar, Iran
| | | | | | - Shilpa Rao
- Norwegian Institute of Public Health, Oslo, Norway
| | - Francesco Sera
- Department of Statistics, Computer Science and Applications "G. Parenti", University of Florence, Florence, Italy
| | - Gabriel Carrasco-Escobar
- Health Innovation Lab, Institute of Tropical Medicine "Alexander von Humboldt", Universidad Peruana Cayetano Heredia, Lima, Peru; Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA
| | - Haidong Kan
- Department of Environmental Health, School of Public Health, Fudan University, Shanghai, China
| | - Hans Orru
- Institute of Family Medicine and Public Health, University of Tartu, Tartu, Estonia
| | - Ho Kim
- Graduate School of Public Health, Seoul National University, Seoul, South Korea
| | | | - Jan Kyselý
- Institute of Atmospheric Physics, Czech Academy of Sciences, Prague, Czech Republic; Faculty of Environmental Sciences, Czech University of Life Sciences, Prague, Czech Republic
| | - Joana Madureira
- Environmental Health Department, Instituto Nacional de Saúde Dr Ricardo Jorge, Porto, Portugal; EPIUnit - Instituto de Saúde Pública, Universidade do Porto, Porto, Portugal; Laboratório para a Investigação Integrativa e Translacional em Saúde Populacional (ITR), Porto, Portugal
| | - Joel Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Jouni J K Jaakkola
- Center for Environmental and Respiratory Health Research (CERH), University of Oulu, Oulu, Finland; Medical Research Center Oulu (MRC Oulu), Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Klea Katsouyanni
- Department of Hygiene, Epidemiology and Medical Statistics, National and Kapodistrian University of Athens, Athens, Greece; School of Population Health and Environmental Sciences, King's College London, London, UK
| | - Magali Hurtado Diaz
- Department of Environmental Health, National Institute of Public Health, Cuernavaca Morelos, Mexico
| | - Martina S Ragettli
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Masahiro Hashizume
- Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Mathilde Pascal
- Santé Publique France, Department of Environmental and Occupational Health, French National Public Health Agency, Saint Maurice, France
| | | | | | - Niilo Ryti
- Center for Environmental and Respiratory Health Research (CERH), University of Oulu, Oulu, Finland; Medical Research Center Oulu (MRC Oulu), Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Noah Scovronick
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Paola Michelozzi
- Department of Epidemiology, Lazio Regional Health Service, Rome, Italy
| | | | - Patrick Goodman
- School of Physics, Technological University Dublin, Dublin, Ireland
| | | | - Raanan Raz
- Braun School of Public Health and Community Medicine, The Hebrew University of Jerusalem, Israel
| | - Rosana Abrutzky
- Universidad de Buenos Aires, Facultad de Ciencias Sociales, Instituto de Investigaciones Gino Germani, Buenos Aires, Argentina
| | - Samuel Osorio
- Department of Environmental Health, University of São Paulo, São Paulo, Brazil
| | - Tran Ngoc Dang
- Department of Environmental Health, Faculty of Public Health, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Viet Nam
| | - Valentina Colistro
- Department of Quantitative Methods, School of Medicine, University of the Republic, Montevideo, Uruguay
| | - Veronika Huber
- IBE-Chair of Epidemiology, LMU Munich, Munich, Germany; Department of Physical, Chemical and Natural Systems, Universidad Pablo de Olavide, Sevilla, Spain
| | - Whanhee Lee
- School of the Environment, Yale University, New Haven, CT, USA; Department of Occupational and Environmental Medicine, School of Medicine, Ewha Womans University, Seoul, South Korea
| | - Xerxes Seposo
- School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan
| | - Yasushi Honda
- Center for Climate Change Adaptation, National Institute for Environmental Studies, Tsukuba, Japan
| | - Yoonhee Kim
- Department of Global Environmental Health, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Yue Leon Guo
- National Institute of Environmental Health Science, National Health Research Institutes, Zhunan, Taiwan; Environmental and Occupational Medicine, National Taiwan University College of Medicine and NTU Hospital, National Taiwan University, Taipei, Taiwan; Graduate Institute of Environmental and Occupational Health Sciences, National Taiwan University College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Michelle L Bell
- School of the Environment, Yale University, New Haven, CT, USA
| | - Shanshan Li
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
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Chiu KC, Hsieh MS, Huang YT, Liu CY. Exposure to ambient temperature and heat index in relation to DNA methylation age: A population-based study in Taiwan. ENVIRONMENT INTERNATIONAL 2024; 186:108581. [PMID: 38507934 DOI: 10.1016/j.envint.2024.108581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 03/13/2024] [Accepted: 03/14/2024] [Indexed: 03/22/2024]
Abstract
BACKGROUND Climate change caused an increase in ambient temperature in the past decades. Exposure to high ambient temperature could result in biological aging, but relevant studies in a warm environment were lacking. We aimed to study the exposure effects of ambient temperature and heat index (HI) in relation to age acceleration in Taiwan, a subtropical island in Asia. METHODS The study included 2,084 participants from Taiwan Biobank. Daily temperature and relative humidity data were collected from weather monitoring stations. Individual residential exposure was estimated by ordinary kriging. Moving averages of ambient temperature and HI from 1 to 180 days prior to enrollment were calculated to estimate the exposure effects in multiple time periods. Age acceleration was defined as the difference between DNA methylation age and chronological age. DNA methylation age was calculated by the Horvath's, Hannum's, Weidner's, ELOVL2, FHL2, phenotypic (Pheno), Skin & blood, and GrimAge2 (Grim2) DNA methylation age algorithms. Multivariable linear regression models, generalized additive models (GAMs), and distributed lag non-linear models (DLNMs) were conducted to estimate the effects of ambient temperature and HI exposures in relation to age acceleration. RESULTS Exposure to high ambient temperature and HI were associated with increased age acceleration, and the associations were stronger in prolonged exposure. The heat stress days with maximum HI in caution (80-90°F), extreme caution (90-103°F), danger (103-124°F), and extreme danger (>124°F) were also associated with increased age acceleration, especially in the extreme danger days. Each extreme danger day was associated with 571.38 (95 % CI: 42.63-1100.13), 528.02 (95 % CI: 36.16-1019.87), 43.9 (95 % CI: 0.28-87.52), 16.82 (95 % CI: 2.36-31.28) and 15.52 (95 % CI: 2.17-28.88) days increase in the Horvath's, Hannum's, Weidner's, Pheno, and Skin & blood age acceleration, respectively. CONCLUSION High ambient temperature and HI may accelerate biological aging.
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Affiliation(s)
- Kuan-Chih Chiu
- Institute of Environmental and Occupational Health Sciences, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Ming-Shun Hsieh
- Department of Emergency Medicine, Taipei Veterans General Hospital, Taoyuan Branch, Taoyuan, Taiwan; Department of Emergency Medicine, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Yen-Tsung Huang
- Institute of Statistical Science, Academia Sinica, Taipei, Taiwan; Department of Mathematics, College of Science, National Taiwan University, Taipei, Taiwan; Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Chen-Yu Liu
- Institute of Environmental and Occupational Health Sciences, College of Public Health, National Taiwan University, Taipei, Taiwan; Department of Public Health, College of Public Health, National Taiwan University, Taipei, Taiwan; Population Health Research Center, National Taiwan University, Taipei, Taiwan.
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Lane M, Ebelt S, Wu Z, Scovronick N, D'Souza RR, Chang HH. Time-series analysis of temperature variability and cardiovascular emergency department visits in Atlanta over a 27-year period. Environ Health 2024; 23:9. [PMID: 38254140 PMCID: PMC10804549 DOI: 10.1186/s12940-024-01048-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 01/07/2024] [Indexed: 01/24/2024]
Abstract
BACKGROUND Short-term temperature variability, defined as the temperature range occurring within a short time span at a given location, appears to be increasing with climate change. Such variation in temperature may influence acute health outcomes, especially cardiovascular diseases (CVD). Most research on temperature variability has focused on the impact of within-day diurnal temperature range, but temperature variability over a period of a few days may also be health-relevant through its impact on thermoregulation and autonomic cardiac functioning. To address this research gap, this study utilized a database of emergency department (ED) visits for a variety of cardiovascular health outcomes over a 27-year period to investigate the influence of three-day temperature variability on CVD. METHODS For the period of 1993-2019, we analyzed over 12 million CVD ED visits in Atlanta using a Poisson log-linear model with overdispersion. Temperature variability was defined as the standard deviation of the minimum and maximum temperatures during the current day and the previous two days. We controlled for mean temperature, dew point temperature, long-term time trends, federal holidays, and day of week. We stratified the analysis by age group, season, and decade. RESULTS All cardiovascular outcomes assessed, except for hypertension, were positively associated with increasing temperature variability, with the strongest effects observed for stroke and peripheral vascular disease. In stratified analyses, adverse associations with temperature variability were consistently highest in the moderate-temperature season (October and March-May) and in the 65 + age group for all outcomes. CONCLUSIONS Our results suggest that CVD morbidity is impacted by short-term temperature variability, and that patients aged 65 and older are at increased risk. These effects were more pronounced in the moderate-temperature season and are likely driven by the Spring season in Atlanta. Public health practitioners and patient care providers can use this knowledge to better prepare patients during seasons with high temperature variability or ahead of large shifts in temperature.
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Affiliation(s)
- Morgan Lane
- Gangarosa Department of Environmental Health, Emory University, 1518 Clifton Rd, Atlanta, GA, USA.
| | - Stefanie Ebelt
- Gangarosa Department of Environmental Health, Emory University, 1518 Clifton Rd, Atlanta, GA, USA
| | - Zhen Wu
- Department of Biostatistics and Bioinformatics, Emory University, 1518 Clifton Rd, Atlanta, GA, USA
| | - Noah Scovronick
- Gangarosa Department of Environmental Health, Emory University, 1518 Clifton Rd, Atlanta, GA, USA
| | - Rohan R D'Souza
- Gangarosa Department of Environmental Health, Emory University, 1518 Clifton Rd, Atlanta, GA, USA
| | - Howard H Chang
- Department of Biostatistics and Bioinformatics, Emory University, 1518 Clifton Rd, Atlanta, GA, USA
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Xu Q, Zhou Q, Chen J, Li T, Ma J, Du R, Su M, Li J, Xu M, Sun S, Ma J, Ramanathan M, Zhang Z. The incidence of asthma attributable to temperature variability: An ecological study based on 1990-2019 GBD data. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 904:166726. [PMID: 37659541 DOI: 10.1016/j.scitotenv.2023.166726] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Revised: 08/22/2023] [Accepted: 08/29/2023] [Indexed: 09/04/2023]
Abstract
BACKGROUND Asthma, the second leading cause of death from chronic respiratory diseases, is associated with climate change, especially temperature changes. It is currently unclear about the relationship between long-term temperature variability and the incidence of asthma on a global scale. METHODS We used asthma incidence, demographic and socioeconomic data from the Global Burden of Disease (GBD) Results Database, and environmental and geographical statistics from TerraClimate between 1990 and 2019 to determine the association between maximum temperature variability and asthma incidence. We also predicted the incidence of heat-related asthma in the future (2020-2100) under four shared socioeconomic pathways (SSPs: 126, 245, 370, and 585). RESULTS Between 1990 and 2019, the global median incidence of asthma was 402.0 per 100,000 with a higher incidence (median: 1380.3 per 100,000) in children under 10 years old. We found that every 1 °C increase in maximum temperature variability increased the risk of asthma globally by 5.0 %, and the effect was robust for individuals living in high-latitude areas or aged from 50 to 70 years. By 2100, the average incidence of asthma is estimated to be reduced by 95.55 %, 79.32 %, and 40.02 % under the SSP126, SSP245, and SSP370 scenarios, respectively, compared to the SSP585 at latitudes >60°. CONCLUSION Our study provides evidence that maximum temperature variability is associated with asthma incidence. These findings suggest that implementing stricter mitigation and adaptation strategies may be importment in reducing asthma cases caused by climate change.
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Affiliation(s)
- Qingsong Xu
- School of Public Health, Peking University, Beijing, China
| | - Qinfeng Zhou
- School of Public Health, Peking University, Beijing, China
| | - Junjun Chen
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, USA
| | - Tong Li
- School of Public Health, Peking University, Beijing, China
| | - Junxiong Ma
- School of Public Health, Peking University, Beijing, China
| | - Runming Du
- School of Public Health, Peking University, Beijing, China
| | - Mintao Su
- School of Public Health, Peking University, Beijing, China
| | - Jing Li
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing, China
| | - Ming Xu
- School of Public Health, Peking University, Beijing, China; Institute for Global Health and Development, Peking University, Beijing, China
| | - Shengzhi Sun
- School of Public Health, Capital Medical University, Beijing, China
| | - Jing Ma
- Department of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, China
| | - Murugappan Ramanathan
- Department of Otolaryngology-Head and Neck Surgery, Johns Hopkins School of Medicine, USA
| | - Zhenyu Zhang
- School of Public Health, Peking University, Beijing, China; Institute for Global Health and Development, Peking University, Beijing, China.
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Liu J, Du X, Yin P, Kan H, Zhou M, Chen R. Cause-specific mortality and burden attributable to temperature variability in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 896:165267. [PMID: 37406687 DOI: 10.1016/j.scitotenv.2023.165267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 06/23/2023] [Accepted: 06/30/2023] [Indexed: 07/07/2023]
Abstract
BACKGROUND Few large-scale, nationwide studies have assessed cause-specific mortality risks and burdens associated with temperature variability (TV). OBJECTIVE To estimate associations between TV and cause-specific mortality and quantify the mortality burden in China. METHODS Data on daily total and cause-specific mortality in 272 Chinese cities between 2013 and 2015 were recorded. TVs were computed as the standard deviations of daily minimum and maximum temperatures over a duration of 2 to 7 days. The time-series quasi-Poisson regression model with adjustment of the cumulative effects of daily mean temperature over the same duration was applied to evaluate the city-specific associations of TV and mortality. Then, we pooled the effect estimates using a random-effects meta-analysis and calculated the mortality burdens. RESULTS Overall, TV showed significant and positive associations with total and cause-specific mortality. The TV-mortality associations were generally stronger when using longer durations. A 1 °C increase in TV at 0-7 days (TV0-7) was associated with a 0.79 % [95 % confidence interval (CI): 0.55 %, 0.96 %] increase in total mortality. Mortality fractions attributable to TV0-7 were 4.37 % for total causes, 4.75 % for overall cardiovascular disease, 4.37 % for coronary heart disease, 5.05 % for stroke, 8.28 % for ischaemic stroke, 1.08 % for haemorrhagic stroke, 6.93 % for respiratory disease, and 6.81 % for COPD, respectively. The mortality risk and burden were generally higher in the temperate monsoon zone, females, and elders. CONCLUSION This nationwide study indicated that TV was an independent risk factor of mortality, and could result in significant burden for main cardiorespiratory diseases.
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Affiliation(s)
- Jiangmei Liu
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xihao Du
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and National Health Commission (NHC) Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Peng Yin
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and National Health Commission (NHC) Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Maigeng Zhou
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
| | - Renjie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and National Health Commission (NHC) Key Lab of Health Technology Assessment, Fudan University, Shanghai, China; Shanghai Typhoon Institute/CMA, Shanghai Key Laboratory of Meteorology and Health, Shanghai, China.
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8
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Healy JP, Danesh Yazdi M, Wei Y, Qiu X, Shtein A, Dominici F, Shi L, Schwartz JD. Seasonal Temperature Variability and Mortality in the Medicare Population. ENVIRONMENTAL HEALTH PERSPECTIVES 2023; 131:77002. [PMID: 37404028 PMCID: PMC10321237 DOI: 10.1289/ehp11588] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 04/17/2023] [Accepted: 06/12/2023] [Indexed: 07/06/2023]
Abstract
BACKGROUND Seasonal temperature variability remains understudied and may be modified by climate change. Most temperature-mortality studies examine short-term exposures using time-series data. These studies are limited by regional adaptation, short-term mortality displacement, and an inability to observe longer-term relationships in temperature and mortality. Seasonal temperature and cohort analyses allow the long-term effects of regional climatic change on mortality to be analyzed. OBJECTIVES We aimed to carry out one of the first investigations of seasonal temperature variability and mortality across the contiguous United States. We also investigated factors that modify this association. Using adapted quasi-experimental methods, we hoped to account for unobserved confounding and to investigate regional adaptation and acclimatization at the ZIP code level. METHODS We examined the mean and standard deviation (SD) of daily temperature in the warm (April-September) and cold (October-March) season in the Medicare cohort from 2000 to 2016. This cohort comprised 622,427,230 y of person-time in all adults over the age of 65 y from 2000 to 2016. We used daily mean temperature obtained from gridMET to develop yearly seasonal temperature variables for each ZIP code. We used an adapted difference-in-difference approach model with a three-tiered clustering approach and meta-analysis to observe the relationship between temperature variability and mortality within ZIP codes. Effect modification was assessed with stratified analyses by race and population density. RESULTS For every 1°C increase in the SD of warm and cold season temperature, the mortality rate increased by 1.54% [95% confidence interval (CI): 0.73%, 2.15%] and 0.69% (95% CI: 0.22%, 1.15%) respectively. We did not see significant effects for seasonal mean temperatures. Participants who were classified by Medicare into an "other" race group had smaller effects than those classified as White for Cold and Cold SD and areas with lower population density had larger effects for Warm SD. DISCUSSION Warm and cold season temperature variability were significantly associated with increased mortality rates in U.S. individuals over the age of 65 y, even after controlling for seasonal temperature averages. Warm and cold season mean temperatures showed null effects on mortality. Cold SD had a larger effect size for those who were in the racial subgroup other, whereas Warm SD was more harmful for those living in lower population density areas. This study adds to the growing calls for urgent climate mitigation and environmental health adaptation and resiliency. https://doi.org/10.1289/EHP11588.
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Affiliation(s)
- James P. Healy
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Mahdieh Danesh Yazdi
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Yaguang Wei
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Xinye Qiu
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Alexandra Shtein
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Francesca Dominici
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Liuhua Shi
- Gangarosa Department of Environmental Health, Emory Rollins School of Public Health, Atlanta, Georgia, USA
| | - Joel D. Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
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9
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Sanches FHC, Martins FR, Conti WRP, Christofoletti RA. The increase in intensity and frequency of surface air temperature extremes throughout the western South Atlantic coast. Sci Rep 2023; 13:6293. [PMID: 37185936 PMCID: PMC10130182 DOI: 10.1038/s41598-023-32722-1] [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: 12/08/2022] [Accepted: 03/31/2023] [Indexed: 05/17/2023] Open
Abstract
The climate is changing. At this stage, it is important to specify an 'extreme' climate and identify patterns that indicate its potential harm worldwide, including the coastal zones. Herein, we considered extremes based on the "Peaks Over Threshold" method from the "Extreme Value Theory". We looked after geographical patterns of surface air temperature (SAT) extremes (e.g., Tmax, Tmin, daily temperature range (DTR), and inter-daily temperature range) over the last 40 years throughout the Brazilian coast. Overall, we found a trend increase in intensity and frequency, but the duration was barely affected. The latitudinal pattern of extremes and the temperatures considered extremes followed the settled perception that areas in higher latitudes will be more affected by the extent of warming. Additionally, the seasonal pattern of DTR demonstrated to be a good approach to make inferences about air mass changes, but joint analyses on extremes with other atmospheric variables are desirable. Given the potential effects of extreme climates on society and natural systems over the world, our study highlights the urge for action to mitigate the effects of the increase in SAT in coastal zones.
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Affiliation(s)
- Fábio H C Sanches
- Institute of Marine Science, Federal University of São Paulo (IMar/UNIFESP), Santos, SP, 11070-102, Brazil.
| | - Fernando R Martins
- Institute of Marine Science, Federal University of São Paulo (IMar/UNIFESP), Santos, SP, 11070-102, Brazil
| | - William R P Conti
- Institute of Marine Science, Federal University of São Paulo (IMar/UNIFESP), Santos, SP, 11070-102, Brazil
| | - Ronaldo A Christofoletti
- Institute of Marine Science, Federal University of São Paulo (IMar/UNIFESP), Santos, SP, 11070-102, Brazil
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10
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Zong J, Wang L, Lu C, Du Y, Wang Q. Mapping health vulnerability to short-term summer heat exposure based on a directional interaction network: Hotspots and coping strategies. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 881:163401. [PMID: 37044341 DOI: 10.1016/j.scitotenv.2023.163401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 03/22/2023] [Accepted: 04/05/2023] [Indexed: 04/14/2023]
Abstract
Health risk resulting from non-optimal temperature exposure, referred to as "systematic risk", has been a sustainable-development challenge in the context of global warming. Previous studies have recognized interactions between and among system components while assessing the vulnerability to climate change, but have left open the question of indicator directional interactions. The question is important, not least because indicator directional association analysis provides guidance to address climate risks by revealing the key nodes and pathways. The purpose of this work was to assess health vulnerability to short-term summer heat exposure based on a directional interaction network. Bayesian network model and network analysis were used to conduct a directional interaction network. Using indicator directional associations as weights, a weighted technique for the order of preference by similarity to ideal solution method was then proposed to assess heat-related health vulnerability. Finally, hotspots and coping strategies were explored based on the directional interaction network and health vulnerability assessments. The results showed that (1) indicator directional interactions were revealed in the health vulnerability framework, and the interactions differed between northern and southern China; (2) there was a dramatic spatial imbalance of health vulnerability in China, with the Beijing-Tianjin-Hebei Region and the Yangtze River Basin identified as hotspots; (3) particulate matter and ozone were recognized as priority indicators in the most vulnerable cities of northern China, while summer heat exposure level and variation were priority indicators in southern China; and (4) adaptive capacity could alter the extent of risk; thus, mitigation and adaptation should be implemented in an integrated way. Our study has important implications for strengthening the theoretical basis for the vulnerability assessment framework by providing indicator directional associations and for guiding policy design in dealing with heat-related health vulnerability in China.
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Affiliation(s)
- Jingru Zong
- School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, China; National Institute of Health Data Science of China, Shandong University, Jinan, Shandong 250012, China
| | - Lingli Wang
- School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, China; National Institute of Health Data Science of China, Shandong University, Jinan, Shandong 250012, China
| | - Chunyu Lu
- School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, China; National Institute of Health Data Science of China, Shandong University, Jinan, Shandong 250012, China
| | - Yajie Du
- School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, China; National Institute of Health Data Science of China, Shandong University, Jinan, Shandong 250012, China
| | - Qing Wang
- School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, China; National Institute of Health Data Science of China, Shandong University, Jinan, Shandong 250012, China.
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11
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Wang P, O'Donnell KJ, Warren JL, Dubrow R, Chen K. Temperature variability and birthweight: Epidemiological evidence from Africa. ENVIRONMENT INTERNATIONAL 2023; 173:107792. [PMID: 36841185 DOI: 10.1016/j.envint.2023.107792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 12/19/2022] [Accepted: 01/30/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Mounting evidence supports an association between nonoptimal ambient temperatures (i.e., heat or cold) and risk of low birthweight (LBW) (<2500 g), while the effect of temperature variability (TV) is largely unknown. We aimed to quantify the association between TV and risk of LBW in Africa. METHODS Data on birthweight in 37 countries during 1990-2020 were collected from the Demographic and Health Surveys program. We calculated overall, intraday, and interday TV during the entire pregnancy and each trimester using hourly temperatures at ∼ 9 km resolution from ERA5-Land. We employed generalized linear mixed logistic regression, with random effects for country and survey cluster, to quantify the association between LBW and three separate TV metrics. RESULTS In total there were 33,863 (10.2%) LBW births out of 333,618 records. We found a J-shaped association between TV and LBW. Compared to the reference TV where the lowest risk was observed, extremely high (97.5th percentile) overall, intraday, and interday TV during the entire pregnancy increased the odds of LBW birth by 37.3% (26.7-48.8%), 24.1% (16.4-32.3%), and 15.1% (6.9-24.0%), respectively. In total, 7.3% of all LBW births in Africa were attributable to elevated overall TV. These associations were observed in dry climate zones, but not in tropical or temperate zones. CONCLUSIONS Our study suggests an adverse impact of TV on the risk of LBW in Africa, according to three different TV definitions, underlining the significance of climate-health risk assessment in those most vulnerable to climate change.
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Affiliation(s)
- Pin Wang
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut, USA; Yale Center on Climate Change and Health, Yale School of Public Health, New Haven, Connecticut, USA.
| | - Kieran J O'Donnell
- Yale Child Study Center & Department of Obstetrics Gynecology & Reproductive Sciences, Yale School of Medicine, New Haven, Connecticut, USA; Department of Psychiatry, McGill University, Montreal, Quebec, Canada; Child & Brain Development Program, CIFAR, Toronto, Ontario, Canada
| | - Joshua L Warren
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, USA
| | - Robert Dubrow
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut, USA; Yale Center on Climate Change and Health, Yale School of Public Health, New Haven, Connecticut, USA
| | - Kai Chen
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut, USA; Yale Center on Climate Change and Health, Yale School of Public Health, New Haven, Connecticut, USA
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12
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Zheng J, Yue L, Wang B, Li Y, Zhang L, Xue B, Tian X, Lei R, Luo B. Seasonal characteristics of ambient temperature variation (DTR, TCN, and TV 0-t) and air pollutants on childhood asthma attack in a dry and cold city in China. ENVIRONMENTAL RESEARCH 2023; 217:114872. [PMID: 36435499 DOI: 10.1016/j.envres.2022.114872] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Revised: 11/16/2022] [Accepted: 11/20/2022] [Indexed: 06/16/2023]
Abstract
Very few researches have concentrated on a variety of time scales to evaluate the association between temperature variation (TV) and childhood asthma (CA), and the evidence for the interaction of air pollutants on this association is lacking. In this study, we aim to estimate the relative risks (RRs) of CA due to TV by following metrics: diurnal temperature range (DTR), temperature changes between neighboring days (TCN), and temperature variability (TV0-t); to quantify the seasonal attributable fraction (AF) and number (AN) of CA due to TV; to examine the interactive effects of the TV and air pollutants on CA in different seasons. We mainly applied distributed lagged nonlinear model (DLNM) and conditional Poisson models to evaluate the associations between TV and outpatient visits for CA during 2014-2019 in Lanzhou, China. Additionally, the bivariate response surface model was used to examine the interplay effect of air pollutants. We found that in warm season, the risks of DTR maximum at lag5 (RR = 1.073, 95% CI: 1.017-1.133); TCN showed protective effect. In cold season, the risks of DTR peaked at lag8 (RR = 1.063, 95% CI: 1.027-1.100); the risks of TCN maximum at lag0 (RR = 1.058 95% CI: 1.009-1.109); the estimation of total cases maximized at TV0-4 in cold season (RR = 1.039 at TV0-3, 95% CI: 1.001, 1.077) and was the lowest at TV0-1 in warm season (RR = 0.999, 95% CI: 0.969, 1.030). In addition, the response surface model graphically pictured ambient air pollutants enhanced the DTR/TV0-4-CA effect for girls. In conclusion, the RRs of CA are markedly increased by TV exposure, particularly during the colder months. A combined evaluation of DTR, TCN, TV0-5∼TV0-6, NO2, SO2, and PM2.5 should be used to identify the adverse effects of TV on CA.
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Affiliation(s)
- Jie Zheng
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou, Gansu, 730000, PR China
| | - Li Yue
- Department of Child Healthcare of Gansu Provincial Maternity and Child-Care Hospital, Lanzhou, Gansu, 730030, PR China
| | - Bo Wang
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou, Gansu, 730000, PR China
| | - Yanlin Li
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou, Gansu, 730000, PR China
| | - Ling Zhang
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou, Gansu, 730000, PR China
| | - Baode Xue
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou, Gansu, 730000, PR China
| | - Xiaoyu Tian
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou, Gansu, 730000, PR China
| | - Ruoyi Lei
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou, Gansu, 730000, PR China
| | - Bin Luo
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou, Gansu, 730000, PR China.
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13
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Xiao L, Wang Q, Ni H, Xu T, Zeng Q, Yu X, Wu H, Guo P, Zhang Q, Zhang X. Effect of ambient temperature variability on sperm quality: A retrospective population-based cohort study. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 851:158245. [PMID: 36007649 DOI: 10.1016/j.scitotenv.2022.158245] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 07/26/2022] [Accepted: 08/19/2022] [Indexed: 02/05/2023]
Abstract
BACKGROUNDS Abnormal sperm quality in men is one of the common causes of infertility. Both ambient temperature and extreme heat exposure have been shown to be associated with sperm quality, but there is no epidemiological evidence for the effect of ambient temperature variability. Our aim was to investigate the association between ambient temperature variability exposure and a decline in sperm quality at different stages of sperm development. METHODS A total of 4912 semen samples collected from the Guangdong Human Sperm Bank between 1 January 2019 and 31 December 2019 were analyzed. We selected three exposure periods: the full-stage (0-90 lag days), early-stage (34-77 lag days) and late-stage (0-37 lag days) of sperm development, and then calculated the standard deviation of daily temperature (TVSD), the maximum day-to-day temperature difference (TVDmax) and the mean day-to-day temperature difference (TVDmean) for the three exposure periods. A linear mixed model was used to explore the exposure response relationship between temperature variability exposure and sperm quality indicators (including sperm concentration, sperm count and sperm motility). RESULTS There was a significant negative association of decreased sperm count with the exposure to temperature variability during 0-90 days prior to sperm collection. (TVDmax: -0.041; -0.063, -0.019; TVDmean: -0.237; -0.386, -0.088; TVSD: -0.103; -0.196, -0.011). We observed a significant association between the decline in sperm concentration, sperm count and per 1 °C increase in TVDmean during early spermatogenesis. No significant association of temperature variability with sperm motility was found. CONCLUSIONS The results indicate that exposure to temperature variability during the entire period of sperm development is significantly associated with a decline in sperm counts. We found that mean day-to-day temperature differences had a detrimental effect on sperm counts in the early-stage. Our findings provide a scientific basis for public health policy and further mechanistic studies.
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Affiliation(s)
- Lina Xiao
- Department of Preventive Medicine, Shantou University Medical College, No. 22 Xinling Road, Shantou 515041, China
| | - Qiling Wang
- National Health Commission Key Laboratory of Male Reproduction and Genetics, Guangzhou, China; Department of Andrology, Guangdong Provincial Reproductive Science Institute (Guangdong Provincial Fertility Hospital), China
| | - Haobo Ni
- Department of Preventive Medicine, Shantou University Medical College, No. 22 Xinling Road, Shantou 515041, China
| | - Ting Xu
- Department of Preventive Medicine, Shantou University Medical College, No. 22 Xinling Road, Shantou 515041, China
| | - Qinghui Zeng
- Department of Preventive Medicine, Shantou University Medical College, No. 22 Xinling Road, Shantou 515041, China
| | - Xiaolin Yu
- Department of Preventive Medicine, Shantou University Medical College, No. 22 Xinling Road, Shantou 515041, China
| | - Haisheng Wu
- Department of Preventive Medicine, Shantou University Medical College, No. 22 Xinling Road, Shantou 515041, China
| | - Pi Guo
- Department of Preventive Medicine, Shantou University Medical College, No. 22 Xinling Road, Shantou 515041, China
- Guangdong Provincial Key Laboratory of Infectious Diseases and Molecular Immunopathology, Shantou 515041, China
| | - Qingying Zhang
- Department of Preventive Medicine, Shantou University Medical College, No. 22 Xinling Road, Shantou 515041, China
| | - Xinzong Zhang
- National Health Commission Key Laboratory of Male Reproduction and Genetics, Guangzhou, China
- Department of Andrology, Guangdong Provincial Reproductive Science Institute (Guangdong Provincial Fertility Hospital), China
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14
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Wu Y, Li S, Zhao Q, Wen B, 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, De la Cruz Valencia C, 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, Hurtado Diaz M, Ragettli MS, Hashizume M, Pascal M, de Sousa Zanotti Stagliorio Coélho M, Ortega NV, Ryti N, Scovronick N, Michelozzi P, Correa PM, Goodman P, Nascimento Saldiva PH, Abrutzky R, Osorio S, Dang TN, Colistro V, Huber V, Lee W, Seposo X, Honda Y, Guo YL, Bell ML, Guo Y. Global, regional, and national burden of mortality associated with short-term temperature variability from 2000-19: a three-stage modelling study. Lancet Planet Health 2022; 6:e410-e421. [PMID: 35550080 PMCID: PMC9177161 DOI: 10.1016/s2542-5196(22)00073-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 03/22/2022] [Accepted: 03/23/2022] [Indexed: 05/08/2023]
Abstract
BACKGROUND Increased mortality risk is associated with short-term temperature variability. However, to our knowledge, there has been no comprehensive assessment of the temperature variability-related mortality burden worldwide. In this study, using data from the MCC Collaborative Research Network, we first explored the association between temperature variability and mortality across 43 countries or regions. Then, to provide a more comprehensive picture of the global burden of mortality associated with temperature variability, global gridded temperature data with a resolution of 0·5° × 0·5° were used to assess the temperature variability-related mortality burden at the global, regional, and national levels. Furthermore, temporal trends in temperature variability-related mortality burden were also explored from 2000-19. METHODS In this modelling study, we applied a three-stage meta-analytical approach to assess the global temperature variability-related mortality burden at a spatial resolution of 0·5° × 0·5° from 2000-19. Temperature variability was calculated as the SD of the average of the same and previous days' minimum and maximum temperatures. We first obtained location-specific temperature variability related-mortality associations based on a daily time series of 750 locations from the Multi-country Multi-city Collaborative Research Network. We subsequently constructed a multivariable meta-regression model with five predictors to estimate grid-specific temperature variability related-mortality associations across the globe. Finally, percentage excess in mortality and excess mortality rate were calculated to quantify the temperature variability-related mortality burden and to further explore its temporal trend over two decades. FINDINGS An increasing trend in temperature variability was identified at the global level from 2000 to 2019. Globally, 1 753 392 deaths (95% CI 1 159 901-2 357 718) were associated with temperature variability per year, accounting for 3·4% (2·2-4·6) of all deaths. Most of Asia, Australia, and New Zealand were observed to have a higher percentage excess in mortality than the global mean. Globally, the percentage excess in mortality increased by about 4·6% (3·7-5·3) per decade. The largest increase occurred in Australia and New Zealand (7·3%, 95% CI 4·3-10·4), followed by Europe (4·4%, 2·2-5·6) and Africa (3·3, 1·9-4·6). INTERPRETATION Globally, a substantial mortality burden was associated with temperature variability, showing geographical heterogeneity and a slightly increasing temporal trend. Our findings could assist in raising public awareness and improving the understanding of the health impacts of temperature variability. FUNDING Australian Research Council, Australian National Health & Medical Research Council.
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Affiliation(s)
- Yao Wu
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia; Climate, Air Quality Research Unit, 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; Climate, Air Quality Research Unit, 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; Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Bo Wen
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia; Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 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, QLD, Australia
| | - Ala Overcenco
- National Agency for Public Health of the Ministry of Health, Labour and Social Protection of the Republic of Moldova, Chișinău, 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 TH 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 TH 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
- NationalInstitute 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, Vietnam
| | - 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 TH 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
| | | | - 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, Vietnam
| | - 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
| | - Yue Leon Guo
- NationalInstitute 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
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia; Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
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15
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Hu Y, Cheng J, Yin Y, Liu S, Tan J, Li S, Wu M, Yan C, Yu G, Hu Y, Tong S. Association of childhood asthma with intra-day and inter-day temperature variability in Shanghai, China. ENVIRONMENTAL RESEARCH 2022; 204:112350. [PMID: 34762926 DOI: 10.1016/j.envres.2021.112350] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Revised: 09/28/2021] [Accepted: 11/03/2021] [Indexed: 06/13/2023]
Abstract
OBJECTIVES Short-term temperature variability (TV) is associated with the exacerbation of asthma, but little is known about the relative effects of intra- and inter-day TV. We aimed to assess the relative impacts of intra- and inter-day TV on childhood asthma and to explore the modification effects by season. METHODS A quasi-Poisson generalized linear regression model combined with a distributed lag nonlinear model was adopted to evaluate the nonlinear and lagged effects of TV on childhood asthma in Shanghai from 2009 to 2017. Intra- and inter-day TV was measured with diurnal temperature range (DTR) and temperature changes between neighboring days (TCN), respectively. RESULTS Increased DTR was associated with the elevated relative risk (RR) of daily outpatient visits for childhood asthma (DOVCA) in both the whole year (RRlag0-14 for the 99th percentile: 1.264, 95% confidence interval (CI): 1.052, 1.518) and cold season (RRlag0-12 for the 99th percentile: 1.411, 95% CI: 1.053, 1.889). Higher TCN in the warm season was associated with the increased RR of DOVCA (RRlag0-14 for the 99th percentile: 2.964, 95% CI: 1.636, 5.373). The number and fraction of DOVCA attributed to an interquartile range (IQR) increase of TCN were higher than those attributed to DTR in both the whole year period and warm season. However, the number and fraction of DOVCA attributed to an IQR increase of DTR were greater than those attributed to TCN in the cold season. CONCLUSIONS Our results provide novel evidence that both intra- and inter-day TV might be a trigger of childhood asthma. Higher DTR appeared to have greater impacts on childhood asthma in the cold season while an increase in TCN seemed to have bigger effects in the warm season.
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Affiliation(s)
- Yabin Hu
- Department of Clinical Epidemiology and Biostatistics, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Jian Cheng
- School of Public Health, Department of Epidemiology and Biostatistics, Anhui Medical University, Hefei, China
| | - Yong Yin
- Department of Respiratory Medicine, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Shijian Liu
- Department of Clinical Epidemiology and Biostatistics, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Jianguo Tan
- Shanghai Key Laboratory of Meteorology and Health (Shanghai Meteorological Service), Shanghai, China
| | - Shenghui Li
- School of Public Health, Shanghai Jiao Tong University, Shanghai, China
| | - Meiqin Wu
- MOE-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chonghuai Yan
- MOE-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Guangjun Yu
- Center for Biomedical Informatics, Shanghai Children's Hospital, Shanghai, China
| | - Yi Hu
- Center for Biomedical Informatics, Shanghai Children's Hospital, Shanghai, China
| | - Shilu Tong
- Department of Clinical Epidemiology and Biostatistics, Shanghai Children's Medical Center, School of Medicine, 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, School of Public Health, Nanjing Medical University, Nanjing, China; School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia.
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16
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Miao H, Wu H, Zhu Y, Kong L, Yu X, Zeng Q, Chen Y, Zhang Q, Guo P, Wang D. Congenital anomalies associated with ambient temperature variability during fetal organogenesis period of pregnancy: Evidence from 4.78 million births. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 798:149305. [PMID: 34340080 DOI: 10.1016/j.scitotenv.2021.149305] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 07/13/2021] [Accepted: 07/23/2021] [Indexed: 02/05/2023]
Abstract
BACKGROUNDS Evidence for the effects of temperature variability on risk of congenital anomalies is lacking. We aimed to examine the association of temperature variability during fetal organogenesis period (weeks 3-8 post-conception) with major congenital anomalies. METHODS A retrospective cohort study comprising 4,787,356 singleton live-births and stillbirths in China was performed. We defined two temperature variability indices within gestational week i: the standard deviation (SD) of daily temperature (TVSDi) and the maximum day-to-day temperature difference (TVDi). At 6-week long timescales, we computed the SD of daily temperature (TVSD3-8) and the average value of TVDi (TVD3-8). We matched two temperature variability indices, pollutant exposure levels over entire exposure window and data of each mother-infant pairs. An extended generalized estimating equation log-binomial regression model was constructed to explore their associations after adjusting for individual characters, temperature extremes and air pollutants. Stratified and sensitivity analyses were also performed. RESULTS 59,571 neonates were registered as major congenital anomalies besides genetic and chromosomal anomalies. At weekly levels, the highest risk estimates of two temperature variability indices occurred at the 5th week for most anomaly groups. All TVSD5, TVD5, and maximum weekly TVSD and TVD were significantly associated with all anomaly groups; with the increment of 1 °C, the estimated risk ratio (RR) and corresponding 95% confidence interval (CI) ranges from 1.03 (1.01-1.05) to 1.19 (1.08-1.31). At 6-week scales, TVSD3-8 and TVD3-8 were associated with most anomaly subgroups. Overall, the strongest associations were estimated for isolated defects among morphology subgroups and cardiac defects among type subgroups. CONCLUSIONS Exposure to temperature variability during fetal organogenesis period of pregnancy is associated with increased risk of major congenital defects. Our findings provide a research foundation for public health policies, and further mechanism investigation.
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Affiliation(s)
- Huazhang Miao
- School of Health Management, Southern Medical University, Guangzhou 510515, Guangdong Province, China; Guangdong Women and Children Hospital, No.521 Xingnan Road, Guangzhou 511442, China
| | - Haisheng Wu
- Department of Preventive Medicine, Shantou University Medical College, Shantou 515041, China
| | - Yingxian Zhu
- Guangdong Women and Children Hospital, No.521 Xingnan Road, Guangzhou 511442, China
| | - Lei Kong
- LAPC & ICCES, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaolin Yu
- Department of Preventive Medicine, Shantou University Medical College, Shantou 515041, China
| | - Qinghui Zeng
- Department of Preventive Medicine, Shantou University Medical College, Shantou 515041, China
| | - Yuliang Chen
- Department of Preventive Medicine, Shantou University Medical College, Shantou 515041, China
| | - Qingying Zhang
- Department of Preventive Medicine, Shantou University Medical College, Shantou 515041, China.
| | - Pi Guo
- Department of Preventive Medicine, Shantou University Medical College, Shantou 515041, China; Guangdong Provincial Key Laboratory of Infectious Diseases and Molecular Immunopathology, Shantou 515041, China.
| | - Dong Wang
- School of Health Management, Southern Medical University, Guangzhou 510515, Guangdong Province, China.
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