Resumen
There is strong experimental evidence that physiologic stress from high temperatures is greater if humidity is higher. However, heat indices developed to allow for this have not consistently predicted mortality better than dry-bulb temperature.
Objectives:
We aimed to clarify the potential contribution of humidity an addition to temperature in predicting daily mortality in summer by using a large multicountry dataset.
Methods:
In 445 cities in 24 countries, we fit a time-series regression model for summer mortality with a distributed lag nonlinear model (DLNM) for temperature (up to lag 3) and supplemented this with a range of terms for relative humidity (RH) and its interaction with temperature. City-specific associations were summarized using meta-analytic techniques.
Results:
Adding a linear term for RH to the temperature term improved fit slightly, with an increase of 23% in RH (the 99th percentile anomaly) associated with a 1.1% [95% confidence interval (CI): 0.8, 1.3] decrease in mortality. Allowing curvature in the RH term or adding terms for interaction of RH with temperature did not improve the model fit. The humidity-related decreased risk was made up of a positive coefficient at lag 0 outweighed by negative coefficients at lags of 1–3 d. Key results were broadly robust to small model changes and replacing RH with absolute measures of humidity. Replacing temperature with apparent temperature, a metric combining humidity and temperature, reduced goodness of fit slightly.
Discussion:
The absence of a positive association of humidity with mortality in summer in this large multinational study is counter to expectations from physiologic studies, though consistent with previous epidemiologic studies finding little evidence for improved prediction by heat indices. The result that there was a small negative average association of humidity with mortality should be interpreted cautiously; the lag structure has unclear interpretation and suggests the need for future work to clarify.
| Idioma original | Inglés |
|---|---|
| Páginas (desde-hasta) | 097007-1-097007-8 |
| Publicación | Environmental Health Perspectives |
| Volumen | 127 |
| N.º | 9 |
| DOI | |
| Estado | Publicada - sep. 2019 |
Nota bibliográfica
Publisher Copyright:© 2019, Public Health Services, US Dept of Health and Human Services. All rights reserved.
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En: Environmental Health Perspectives, Vol. 127, N.º 9, 09.2019, p. 097007-1-097007-8.
Producción científica: Contribución a una revista › Artículo › revisión exhaustiva
TY - JOUR
T1 - The role of humidity in associations of high temperature with mortality
T2 - A multicountry, multicity study
AU - Armstrong, Ben
AU - Sera, Francesco
AU - Vicedo-Cabrera, Ana Maria
AU - Abrutzky, Rosana
AU - Åström, Daniel Oudin
AU - Bell, Michelle L.
AU - Chen, Bing Yu
AU - Coelho, Micheline de Sousa Zanotti Stagliorio
AU - Correa, Patricia Matus
AU - Dang, Tran Ngoc
AU - Diaz, Magali Hurtado
AU - Van Dung, Do
AU - Forsberg, Bertil
AU - Goodman, Patrick
AU - Guo, Yue Liang Leon
AU - Guo, Yuming
AU - Hashizume, Masahiro
AU - Honda, Yasushi
AU - Indermitte, Ene
AU - Íñiguez, Carmen
AU - Kan, Haidong
AU - Kim, Ho
AU - Kyselý, Jan
AU - Lavigne, Eric
AU - Michelozzi, Paola
AU - Orru, Hans
AU - Ortega, Nicolás Valdés
AU - Pascal, Mathilde
AU - Ragettli, Martina S.
AU - Saldiva, Paulo Hilario Nascimento
AU - Schwartz, Joel
AU - Scortichini, Matteo
AU - Seposo, Xerxes
AU - Tobias, Aurelio
AU - Tong, Shilu
AU - Urban, Aleš
AU - Valencia, César De la Cruz
AU - Zanobetti, Antonella
AU - Zeka, Ariana
AU - Gasparrini, Antonio
N1 - Funding Information: 1Department of Public Health, Environments and Society, London School of Hygiene and Tropical Medicine, London, UK 2Center for Statistical Methodology, London School of Hygiene and Tropical Medicine, London, UK 3Universidad de Buenos Aires, Facultad de Ciencias Sociales, Instituto de Investigaciones Gino Germani, Buenos Aires, Argentina 4Section of Sustainable Health, Department of Occupational and Environmental Medicine, Umeå University, Umeå, Sweden 5School of Forestry and Environmental Studies, Yale University, New Haven, Connecticut, USA 6National Institute of Environmental Health Science, National Health Research Institutes, Zhunan, Taiwan 7Institute of Advanced Studies, University of São Paulo, São Paulo, Brazil 8Department of Public Health, Universidad de los Andes, Santiago, Chile 9Institute of Research and Development, Duy Tan University, Da Nang, Vietnam 10Department of Environmental Health, Faculty of Public Health, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam 11Department of Environmental Health, National Institute of Public Health, Cuernavaca, Morelos, Mexico 12Department of Public Health and Clinical Medicine, Umeå University, Sweden 13Technological University Dublin (TU Dublin), Dublin, Ireland 14Department of Environmental and Occupational Medicine, National Taiwan University (NTU) Hospital, Taipei, Taiwan 15Institute of Occupational Medicine and Industrial Hygiene, NTU Hospital, Taipei, Taiwan 16Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia 17Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia 18Department of Pediatric Infectious Diseases, Institute of Tropical Medicine, Nagasaki University, Nagasaki, Japan 19Faculty of Health and Sport Sciences, University of Tsukuba, Tsukuba, Japan 20Department of Family Medicine and Public Health, University of Tartu, Tartu, Estonia 21Department of Statistics and Computational Research, University of València, València, Spain 22Biomedical Research Center Network of Epidemiology and Public Health (CIBERESP), Madrid, Spain 23Department of Environmental Health, School of Public Health, Fudan University, Shanghai, China 24Graduate School of Public Health, Seoul National University, Seoul, Republic of Korea 25Institute of Atmospheric Physics, Academy of Sciences of the Czech Republic, Prague, Czech Republic 26Faculty of Environmental Sciences, Czech University of Life Sciences, Prague, Czech Republic 27School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, Canada 28Air Health Science Division, Health Canada, Ottawa, Canada 29Department of Epidemiology, Lazio Regional Health Service, Rome, Italy 30Santé Publique France, Department of Environmental Health, French National Public Health Agency, Saint Maurice, France 31Swiss Tropical and Public Health Institute, Basel, Switzerland 32University of Basel, Basel, Switzerland 33Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA 34Department of Environmental Engineering, Graduate School of Engineering, Kyoto University, Kyoto, Japan 35Department of Global Ecology, Graduate School of Global Environmental Studies, Kyoto University, Kyoto, Japan 36Institute of Environmental Assessment and Water Research (IDAEA), Spanish Council for Scientific Research (CSIC), Barcelona, Spain 37Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China 38School of Public Health, Institute of Environment and Population Health, Anhui Medical University Hefei, China 39School of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia 40Institute for the Environment, Brunel University London, London, UK BACKGROUND: There is strong experimental evidence that physiologic stress from high temperatures is greater if humidity is higher. However, heat indices developed to allow for this have not consistently predicted mortality better than dry-bulb temperature. OBJECTIVES: We aimed to clarify the potential contribution of humidity an addition to temperature in predicting daily mortality in summer by using a large multicountry dataset. METHODS: In 445 cities in 24 countries, we fit a time-series regression model for summer mortality with a distributed lag nonlinear model (DLNM) for temperature (up to lag 3) and supplemented this with a range of terms for relative humidity (RH) and its interaction with temperature. City-specific associations were summarized using meta-analytic techniques. RESULTS: Adding a linear term for RH to the temperature term improved fit slightly, with an increase of 23% in RH (the 99th percentile anomaly) associated with a 1.1% [95% confidence interval (CI): 0.8, 1.3] decrease in mortality. Allowing curvature in the RH term or adding terms for interaction of RH with temperature did not improve the model fit. The humidity-related decreased risk was made up of a positive coefficient at lag 0 Address correspondence to Ben Armstrong, London School of Hygiene and Tropical Medicine, Keppel St., London WC1E 7HT, UK. Telephone: 0044 (0) 20 79272232. Email: [email protected] Supplemental Material is available online (https://doi.org/10.1289/EHP5430). The authors declare they have no actual or potential competing financial interests. Received 11 April 2019; Revised 7 August 2019; Accepted 6 September 2019; Published 25 September 2019; Corrected 4 October 2019. Funding Information: B.A. was supported by the UK National Institute for Health Research (NIHR) Health Protection Research Unit in Environmental Change and Health; A.G., F.S., and A.V.C. were supported by grants from the UK Medical Research Council (grant IDs: MR/M022625/1, MR/R013349/1) and from the UK Natural Environment Research Council (grant ID: NE/R009384/1); and M.L.B. was supported by Assistance Agreement No. 83587101 awarded by the U.S. Environmental Protection Agency and R01 MD012769 awarded by the U.S. National Institutes of Health. Y.G. was supported by the Career Development Fellowship of Australian National Health and Medical Research Council (APP1107107). A.T. was supported by the Japanese Society for the Promotion of Science (JSPS) Invitational Fellowships for Research in Japan (S18149). Y.L.G. was supported by NHRI-105-EMSP09 from National Health Research Institutes, Taiwan. H.O. and E.I. were supported by Ministry of Education and Research (Estonia) grant IUT34-17. J.K. and A.U. were supported by the Czech Science Foundation, grant 18-22125S. H.K., M.H., and Y.H. were supported by the Global Research Lab (#K2100400000110A0500-00710) through the National Research Foundation of Korea. M.H. and Y.H. were supported by the Environment Research and Technology Development Fund (S-14) of the Environmental Restoration and Conservation Agency. Funding Information: B.A. was supported by the UK National Institute for Health Research (NIHR) Health Protection Research Unit in Environmental Change and Health; A.G., F.S., and A.V.C. were supported by grants from the UK Medical Research Council (grant IDs: MR/M022625/1, MR/R013349/1) and from the UK Natural Environment Research Council (grant ID: NE/R009384/1); and M.L.B. was supported by Assistance Agreement No. 83587101 awarded by the U.S. Environmental Protection Agency and R01 MD012769 awarded by the U.S. National Institutes of Health. Y.G. was supported by the Career Development Fellowship of Australian National Health and Medical Research Council (APP1107107). A.T. was supported by the Japanese Society for the Promotion of Science (JSPS) Invitational Fellowships for Research in Japan (S18149). Y.L.G. was supported by NHRI-105-EMSP09 from National Health Research Institutes, Taiwan. H.O. and E.I. were supported by Ministry of Education and Research (Estonia) grant IUT34-17. J.K. and A.U. were supported by the Czech Science Foundation, grant 18-22125S. H.K., M.H., and Y.H. were supported by the Global Research Lab (#K21004000001-10A0500-00710) through the National Research Foundation of Korea. M.H. and Y.H. were supported by the Environment Research and Technology Development Fund (S-14) of the Environmental Restoration and Conservation Agency. Publisher Copyright: © 2019, Public Health Services, US Dept of Health and Human Services. All rights reserved.
PY - 2019/9
Y1 - 2019/9
N2 - BACKGROUND: There is strong experimental evidence that physiologic stress from high temperatures is greater if humidity is higher. However, heat indices developed to allow for this have not consistently predicted mortality better than dry-bulb temperature. OBJECTIVES: We aimed to clarify the potential contribution of humidity an addition to temperature in predicting daily mortality in summer by using a large multicountry dataset. METHODS: In 445 cities in 24 countries, we fit a time-series regression model for summer mortality with a distributed lag nonlinear model (DLNM) for temperature (up to lag 3) and supplemented this with a range of terms for relative humidity (RH) and its interaction with temperature. Cityspecific associations were summarized using meta-analytic techniques. RESULTS: Adding a linear term for RH to the temperature term improved fit slightly, with an increase of 23% in RH (the 99th percentile anomaly) associated with a 1.1% [95% confidence interval (CI): 0.8, 1.3] decrease in mortality. Allowing curvature in the RH term or adding terms for interaction of RH with temperature did not improve the model fit. The humidity-related decreased risk was made up of a positive coefficient at lag 0 outweighed by negative coefficients at lags of 1–3 d. Key results were broadly robust to small model changes and replacing RH with absolute measures of humidity. Replacing temperature with apparent temperature, a metric combining humidity and temperature, reduced goodness of fit slightly. DISCUSSION: The absence of a positive association of humidity with mortality in summer in this large multinational study is counter to expectations from physiologic studies, though consistent with previous epidemiologic studies finding little evidence for improved prediction by heat indices. The result that there was a small negative average association of humidity with mortality should be interpreted cautiously; the lag structure has unclear interpretation and suggests the need for future work to clarify. https://doi.org/10.1289/EHP5430.
AB - BACKGROUND: There is strong experimental evidence that physiologic stress from high temperatures is greater if humidity is higher. However, heat indices developed to allow for this have not consistently predicted mortality better than dry-bulb temperature. OBJECTIVES: We aimed to clarify the potential contribution of humidity an addition to temperature in predicting daily mortality in summer by using a large multicountry dataset. METHODS: In 445 cities in 24 countries, we fit a time-series regression model for summer mortality with a distributed lag nonlinear model (DLNM) for temperature (up to lag 3) and supplemented this with a range of terms for relative humidity (RH) and its interaction with temperature. Cityspecific associations were summarized using meta-analytic techniques. RESULTS: Adding a linear term for RH to the temperature term improved fit slightly, with an increase of 23% in RH (the 99th percentile anomaly) associated with a 1.1% [95% confidence interval (CI): 0.8, 1.3] decrease in mortality. Allowing curvature in the RH term or adding terms for interaction of RH with temperature did not improve the model fit. The humidity-related decreased risk was made up of a positive coefficient at lag 0 outweighed by negative coefficients at lags of 1–3 d. Key results were broadly robust to small model changes and replacing RH with absolute measures of humidity. Replacing temperature with apparent temperature, a metric combining humidity and temperature, reduced goodness of fit slightly. DISCUSSION: The absence of a positive association of humidity with mortality in summer in this large multinational study is counter to expectations from physiologic studies, though consistent with previous epidemiologic studies finding little evidence for improved prediction by heat indices. The result that there was a small negative average association of humidity with mortality should be interpreted cautiously; the lag structure has unclear interpretation and suggests the need for future work to clarify. https://doi.org/10.1289/EHP5430.
UR - http://www.scopus.com/inward/record.url?scp=85072666411&partnerID=8YFLogxK
U2 - 10.1289/EHP5430
DO - 10.1289/EHP5430
M3 - Article
C2 - 31553655
AN - SCOPUS:85072666411
SN - 0091-6765
VL - 127
SP - 097007-1-097007-8
JO - Environmental Health Perspectives
JF - Environmental Health Perspectives
IS - 9
ER -