1
|
Huang W, Yang Z, Zhang Y, Vogt T, Armstrong B, Yu W, Xu R, Yu P, Liu Y, Gasparrini A, Hundessa S, Lavigne E, Molina T, Geiger T, Guo YL, Otto C, Hales S, Pourzand F, Pan SC, Ju K, Ritchie EA, Li S, Guo Y. Tropical cyclone-specific mortality risks and the periods of concern: A multicountry time-series study. PLoS Med 2024; 21:e1004341. [PMID: 38252630 PMCID: PMC10843109 DOI: 10.1371/journal.pmed.1004341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 02/05/2024] [Accepted: 01/03/2024] [Indexed: 01/24/2024] Open
Abstract
BACKGROUND More intense tropical cyclones (TCs) are expected in the future under a warming climate scenario, but little is known about their mortality effect pattern across countries and over decades. We aim to evaluate the TC-specific mortality risks, periods of concern (POC) and characterize the spatiotemporal pattern and exposure-response (ER) relationships on a multicountry scale. METHODS AND FINDINGS Daily all-cause, cardiovascular, and respiratory mortality among the general population were collected from 494 locations in 18 countries or territories during 1980 to 2019. Daily TC exposures were defined when the maximum sustained windspeed associated with a TC was ≥34 knots using a parametric wind field model at a 0.5° × 0.5° resolution. We first estimated the TC-specific mortality risks and POC using an advanced flexible statistical framework of mixed Poisson model, accounting for the population changes, natural variation, seasonal and day of the week effects. Then, a mixed meta-regression model was used to pool the TC-specific mortality risks to estimate the overall and country-specific ER relationships of TC characteristics (windspeed, rainfall, and year) with mortality. Overall, 47.7 million all-cause, 15.5 million cardiovascular, and 4.9 million respiratory deaths and 382 TCs were included in our analyses. An overall average POC of around 20 days was observed for TC-related all-cause and cardiopulmonary mortality, with relatively longer POC for the United States of America, Brazil, and Taiwan (>30 days). The TC-specific relative risks (RR) varied substantially, ranging from 1.04 to 1.42, 1.07 to 1.77, and 1.12 to 1.92 among the top 100 TCs with highest RRs for all-cause, cardiovascular, and respiratory mortality, respectively. At country level, relatively higher TC-related mortality risks were observed in Guatemala, Brazil, and New Zealand for all-cause, cardiovascular, and respiratory mortality, respectively. We found an overall monotonically increasing and approximately linear ER curve of TC-related maximum sustained windspeed and cumulative rainfall with mortality, with heterogeneous patterns across countries and regions. The TC-related mortality risks were generally decreasing from 1980 to 2019, especially for the Philippines, Taiwan, and the USA, whereas potentially increasing trends in TC-related all-cause and cardiovascular mortality risks were observed for Japan. CONCLUSIONS The TC mortality risks and POC varied greatly across TC events, locations, and countries. To minimize the TC-related health burdens, targeted strategies are particularly needed for different countries and regions, integrating epidemiological evidence on region-specific POC and ER curves that consider across-TC variability.
Collapse
Affiliation(s)
- Wenzhong Huang
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Zhengyu Yang
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yiwen Zhang
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Thomas Vogt
- Potsdam Institute for Climate Impact Research, Potsdam, Germany
| | - Ben Armstrong
- Department of Public Health Environments and Society, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Wenhua Yu
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Rongbin Xu
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Pei Yu
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yanming Liu
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Antonio Gasparrini
- Department of Public Health Environments and Society, London School of Hygiene & Tropical Medicine, London, United Kingdom
- Centre on Climate Change & Planetary Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
- Centre for Statistical Methodology, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Samuel Hundessa
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Eric Lavigne
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, Canada
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada
| | - Tomas Molina
- Department Applied Physics, Universitat de Barcelona, Barcelona, Spain
| | - Tobias Geiger
- Deutscher Wetterdienst (DWD), Regional Climate Office Potsdam, Potsdam, Germany
| | - Yue Leon Guo
- Department of Environmental and Occupational Medicine, National Taiwan University (NTU) and NTU Hospital, Taipei, Taiwan
- National Institute of Environmental Health Sciences, National Health Research Institutes, Miaoli, Taiwan
- Institute of Environmental and Occupational Health Sciences, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Christian Otto
- Potsdam Institute for Climate Impact Research, Potsdam, Germany
| | - Simon Hales
- Department of Public Health, University of Otago, Wellington, New Zealand
| | - Farnaz Pourzand
- Department of Public Health, University of Otago, Wellington, New Zealand
| | - Shih-Chun Pan
- National Institute of Environmental Health Sciences, National Health Research Institutes, Miaoli, Taiwan
| | - Ke Ju
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Elizabeth A. Ritchie
- School of Earth Atmosphere and Environment, Monash University, Melbourne, Australia
- Department of Civil Engineering, Monash University, Melbourne, Australia
| | - Shanshan Li
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yuming Guo
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | | |
Collapse
|
2
|
Burrows K, Anderson GB, Yan M, Wilson A, Sabath MB, Son JY, Kim H, Dominici F, Bell ML. Health disparities among older adults following tropical cyclone exposure in Florida. Nat Commun 2023; 14:2221. [PMID: 37076480 PMCID: PMC10115860 DOI: 10.1038/s41467-023-37675-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 03/27/2023] [Indexed: 04/21/2023] Open
Abstract
Tropical cyclones (TCs) pose a significant threat to human health, and research is needed to identify high-risk subpopulations. We investigated whether hospitalization risks from TCs in Florida (FL), United States, varied across individuals and communities. We modeled the associations between all storms in FL from 1999 to 2016 and over 3.5 million Medicare hospitalizations for respiratory (RD) and cardiovascular disease (CVD). We estimated the relative risk (RR), comparing hospitalizations during TC-periods (2 days before to 7 days after) to matched non-TC-periods. We then separately modeled the associations in relation to individual and community characteristics. TCs were associated with elevated risk of RD hospitalizations (RR: 4.37, 95% CI: 3.08, 6.19), but not CVD (RR: 1.04, 95% CI: 0.87, 1.24). There was limited evidence of modification by individual characteristics (age, sex, or Medicaid eligibility); however, risks were elevated in communities with higher poverty or lower homeownership (for CVD hospitalizations) and in denser or more urban communities (for RD hospitalizations). More research is needed to understand the potential mechanisms and causal pathways that might account for the observed differences in the association between tropical cyclones and hospitalizations across communities.
Collapse
Affiliation(s)
- K Burrows
- Institute at Brown for Environment and Society, Brown University, Providence, RI, USA.
| | - G B Anderson
- Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO, USA
| | - M Yan
- Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO, USA
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, China
| | - A Wilson
- Department of Statistics, Colorado State University, Fort Collins, CO, USA
| | - M B Sabath
- T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - J Y Son
- School of the Environment, Yale University, New Haven, CT, USA
| | - H Kim
- Division of Environmental and Occupational Health Sciences, School of Public Health, IL, Chicago, USA
| | - F Dominici
- T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - M L Bell
- School of the Environment, Yale University, New Haven, CT, USA
| |
Collapse
|