Lina Madaniyazi1,2, Ben Armstrong3, Yeonseung Chung4, Chris Fook Sheng Ng2, Xerxes Seposo2, Yoonhee Kim5, Aurelio Tobias2,6, Yuming Guo7,8, Francesco Sera3,9, Yasushi Honda10,11, Antonio Gasparrini3,12,13, Masahiro Hashizume1,2,14. 1. Department of Paediatric Infectious Disease, Institute of Tropical Medicine, Nagasaki University, Nagasaki, Japan. 2. School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan. 3. Department of Public Health, Environments and Society, London School of Hygiene & Tropical Medicine, London, UK. 4. Department of Mathematical Sciences, Korea Advanced Institute of Science and Technology, Daejeon, South Korea. 5. Department of Global Environmental Health, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan. 6. Institute of Environmental Assessment and Water Research (IDAEA), Spanish Council for Scientific Research (CSIS), Barcelona, Spain. 7. Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia. 8. Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia. 9. Department of Statistics, Computer Science and Applications 'G. Parenti', University of Florence, Florence, Italy. 10. Center for Climate Change Adaptation, National Institute for Environmental Studies, Tsukuba, Japan. 11. Faculty of Health and Sport Sciences, University of Tsukuba, Tsukuba, Japan. 12. Centre for Statistical Methodology, London School of Hygiene & Tropical Medicine, London, UK. 13. Centre on Climate Change & Planetary Health, London School of Hygiene & Tropical Medicine, London, UK. 14. Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Abstract
BACKGROUND: Although seasonal variations in mortality have been recognized for millennia, the role of temperature remains unclear. We aimed to assess seasonal variation in mortality and to examine the contribution of temperature. METHODS: We compiled daily data on all-cause, cardiovascular and respiratory mortality, temperature and indicators on location-specific characteristics from 719 locations in tropical, dry, temperate and continental climate zones. We fitted time-series regression models to estimate the amplitude of seasonal variation in mortality on a daily basis, defined as the peak-to-trough ratio (PTR) of maximum mortality estimates to minimum mortality estimates at day of year. Meta-analysis was used to summarize location-specific estimates for each climate zone. We estimated the PTR with and without temperature adjustment, with the differences representing the seasonal effect attributable to temperature. We also evaluated the effect of location-specific characteristics on the PTR across locations by using meta-regression models. RESULTS: Seasonality estimates and responses to temperature adjustment varied across locations. The unadjusted PTR for all-cause mortality was 1.05 [95% confidence interval (CI): 1.00-1.11] in the tropical zone and 1.23 (95% CI: 1.20-1.25) in the temperate zone; adjusting for temperature reduced the estimates to 1.02 (95% CI: 0.95-1.09) and 1.10 (95% CI: 1.07-1.12), respectively. Furthermore, the unadjusted PTR was positively associated with average mean temperature. CONCLUSIONS: This study suggests that seasonality of mortality is importantly driven by temperature, most evidently in temperate/continental climate zones, and that warmer locations show stronger seasonal variations in mortality, which is related to a stronger effect of temperature.
BACKGROUND: Although seasonal variations in mortality have been recognized for millennia, the role of temperature remains unclear. We aimed to assess seasonal variation in mortality and to examine the contribution of temperature. METHODS: We compiled daily data on all-cause, cardiovascular and respiratory mortality, temperature and indicators on location-specific characteristics from 719 locations in tropical, dry, temperate and continental climate zones. We fitted time-series regression models to estimate the amplitude of seasonal variation in mortality on a daily basis, defined as the peak-to-trough ratio (PTR) of maximum mortality estimates to minimum mortality estimates at day of year. Meta-analysis was used to summarize location-specific estimates for each climate zone. We estimated the PTR with and without temperature adjustment, with the differences representing the seasonal effect attributable to temperature. We also evaluated the effect of location-specific characteristics on the PTR across locations by using meta-regression models. RESULTS: Seasonality estimates and responses to temperature adjustment varied across locations. The unadjusted PTR for all-cause mortality was 1.05 [95% confidence interval (CI): 1.00-1.11] in the tropical zone and 1.23 (95% CI: 1.20-1.25) in the temperate zone; adjusting for temperature reduced the estimates to 1.02 (95% CI: 0.95-1.09) and 1.10 (95% CI: 1.07-1.12), respectively. Furthermore, the unadjusted PTR was positively associated with average mean temperature. CONCLUSIONS: This study suggests that seasonality of mortality is importantly driven by temperature, most evidently in temperate/continental climate zones, and that warmer locations show stronger seasonal variations in mortality, which is related to a stronger effect of temperature.