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Global, regional, and national burden of mortality associated with non-optimal ambient temperatures from 2000 to 2019: a three-stage modelling study
2021, Zhao, Qi, Guo, Yuming, Ye, Tingting, Gasparrini, Antonio, Tong, Shilu, Overcenco, Ala, Urban, Aleš, Schneider, Alexandra, Entezari, Alireza, Vicedo-Cabrera, Ana Maria, Zanobetti, Antonella, Analitis, Antonis, Zeka, Ariana, Tobias, Aurelio, Nunes, Baltazar, Alahmad, Barrak, Armstrong, Ben, Forsberg, Bertil, Pan, Shih-Chun, Íñiguez, Carmen, Ameling, Caroline, De la Cruz Valencia, César, Åström, Christofer, Houthuijs, Danny, Dung, Do Van, Royé, Dominic, Indermitte, Ene, Lavigne, Eric, Mayvaneh, Fatemeh, Acquaotta, Fiorella, de'Donato, Francesca, Di Ruscio, Francesco, Sera, Francesco, Carrasco-Escobar, Gabriel, Kan, Haidong, Orru, Hans, Kim, Ho, Holobaca, Iulian-Horia, Kyselý, Jan, Madureira, Joana, Schwartz, Joel, Jaakkola, Jouni J. K., Katsouyanni, Klea, Hurtado Diaz, Magali, Ragettli, Martina S., Hashizume, Masahiro, Pascal, Mathilde, de Sousa Zanotti Stagliorio Coélho, Micheline, Valdés Ortega, Nicolás, Ryti, Niilo, Scovronick, Noah, Michelozzi, Paola, Matus Correa, Patricia, Goodman, Patrick, Nascimento Saldiva, Paulo Hilario, Abrutzky, Rosana, Osorio, Samuel, Rao, Shilpa, Fratianni, Simona, Dang, Tran Ngoc, Colistro, Valentina, Huber, Veronika, Lee, Whanhee, Seposo, Xerxes, Honda, Yasushi, Guo, Yue Leon, Bell, Michelle L., Li, Shanshan
Background: Exposure to cold or hot temperatures is associated with premature deaths. We aimed to evaluate the global, regional, and national mortality burden associated with non-optimal ambient temperatures. Methods: In this modelling study, we collected time-series data on mortality and ambient temperatures from 750 locations in 43 countries and five meta-predictors at a grid size of 0·5° × 0·5° across the globe. A three-stage analysis strategy was used. First, the temperature–mortality association was fitted for each location by use of a time-series regression. Second, a multivariate meta-regression model was built between location-specific estimates and meta-predictors. Finally, the grid-specific temperature–mortality association between 2000 and 2019 was predicted by use of the fitted meta-regression and the grid-specific meta-predictors. Excess deaths due to non-optimal temperatures, the ratio between annual excess deaths and all deaths of a year (the excess death ratio), and the death rate per 100 000 residents were then calculated for each grid across the world. Grids were divided according to regional groupings of the UN Statistics Division. Findings: Globally, 5 083 173 deaths (95% empirical CI [eCI] 4 087 967–5 965 520) were associated with non-optimal temperatures per year, accounting for 9·43% (95% eCI 7·58–11·07) of all deaths (8·52% [6·19–10·47] were cold-related and 0·91% [0·56–1·36] were heat-related). There were 74 temperature-related excess deaths per 100 000 residents (95% eCI 60–87). The mortality burden varied geographically. Of all excess deaths, 2 617 322 (51·49%) occurred in Asia. Eastern Europe had the highest heat-related excess death rate and Sub-Saharan Africa had the highest cold-related excess death rate. From 2000–03 to 2016–19, the global cold-related excess death ratio changed by −0·51 percentage points (95% eCI −0·61 to −0·42) and the global heat-related excess death ratio increased by 0·21 percentage points (0·13–0·31), leading to a net reduction in the overall ratio. The largest decline in overall excess death ratio occurred in South-eastern Asia, whereas excess death ratio fluctuated in Southern Asia and Europe. Interpretation: Non-optimal temperatures are associated with a substantial mortality burden, which varies spatiotemporally. Our findings will benefit international, national, and local communities in developing preparedness and prevention strategies to reduce weather-related impacts immediately and under climate change scenarios. Funding: Australian Research Council and the Australian National Health and Medical Research Council. © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license
Projections of temperature-related excess mortality under climate change scenarios
2017, Gasparrini, A., Guo, Y., Sera, F., Vicedo-Cabrera, A.M., Huber, V., Tong, S., de Sousa Zanotti Stagliorio Coelho, M., Nascimento Saldiva, P.H., Lavigne, E., Matus Correa, P., Valdes Ortega, N., Kan, H., Osorio, S., Kyselý, J., Urban, A., Jaakkola, J.J.K., Ryti, N.R.I., Pascal, M., Goodman, P.G., Zeka, A., Michelozzi, P., Scortichini, M., Hashizume, M., Honda, Y., Hurtado-Diaz, M., Cesar Cruz, J., Seposo, X., Kim, H., Tobias, A., Iñiguez, C., Forsberg, B., Åström, D.O., Ragettli, M.S., Guo, Y.L., Wu, C.-F., Zanobetti, A., Schwartz, J., Bell, M.L., Dang, T.N., Van, D.D., Heaviside, C., Vardoulakis, S., Hajat, S., Haines, A., Armstrong, B.
Background: Climate change can directly affect human health by varying exposure to non-optimal outdoor temperature. However, evidence on this direct impact at a global scale is limited, mainly due to issues in modelling and projecting complex and highly heterogeneous epidemiological relationships across different populations and climates. Methods: We collected observed daily time series of mean temperature and mortality counts for all causes or non-external causes only, in periods ranging from Jan 1, 1984, to Dec 31, 2015, from various locations across the globe through the Multi-Country Multi-City Collaborative Research Network. We estimated temperature–mortality relationships through a two-stage time series design. We generated current and future daily mean temperature series under four scenarios of climate change, determined by varying trajectories of greenhouse gas emissions, using five general circulation models. We projected excess mortality for cold and heat and their net change in 1990–2099 under each scenario of climate change, assuming no adaptation or population changes. Findings: Our dataset comprised 451 locations in 23 countries across nine regions of the world, including 85 879 895 deaths. Results indicate, on average, a net increase in temperature-related excess mortality under high-emission scenarios, although with important geographical differences. In temperate areas such as northern Europe, east Asia, and Australia, the less intense warming and large decrease in cold-related excess would induce a null or marginally negative net effect, with the net change in 2090–99 compared with 2010–19 ranging from −1·2% (empirical 95% CI −3·6 to 1·4) in Australia to −0·1% (−2·1 to 1·6) in east Asia under the highest emission scenario, although the decreasing trends would reverse during the course of the century. Conversely, warmer regions, such as the central and southern parts of America or Europe, and especially southeast Asia, would experience a sharp surge in heat-related impacts and extremely large net increases, with the net change at the end of the century ranging from 3·0% (−3·0 to 9·3) in Central America to 12·7% (−4·7 to 28·1) in southeast Asia under the highest emission scenario. Most of the health effects directly due to temperature increase could be avoided under scenarios involving mitigation strategies to limit emissions and further warming of the planet. Interpretation: This study shows the negative health impacts of climate change that, under high-emission scenarios, would disproportionately affect warmer and poorer regions of the world. Comparison with lower emission scenarios emphasises the importance of mitigation policies for limiting global warming and reducing the associated health risks. Funding: UK Medical Research Council.