8 research outputs found
Fluctuating temperature modifies heat-mortality association around the globe
Studies have investigated the effects of heat and temperature variability (TV) on mortality. However, few assessed whether TV modifies the heat-mortality association. Data on daily temperature and mortality in the warm season were collected from 717 locations across 36 countries. TV was calculated as the standard deviation of the average of the same and previous daysâ minimum and maximum temperatures. We used location-specific quasi-Poisson regression models with an interaction term between the cross-basis term for mean temperature and quartiles of TV to obtain heat-mortality associations under each quartile of TV, and then pooled estimates at the country, regional, and global levels. Results show the increased risk in heat-related mortality with increments in TV, accounting for 0.70% (95% confidence interval [CI]: â0.33 to 1.69), 1.34% (95% CI: â0.14 to 2.73), 1.99% (95% CI: 0.29â3.57), and 2.73% (95% CI: 0.76â4.50) of total deaths for Q1âQ4 (first quartileâfourth quartile) of TV. The modification effects of TV varied geographically. Central Europe had the highest attributable fractions (AFs), corresponding to 7.68% (95% CI: 5.25â9.89) of total deaths for Q4 of TV, while the lowest AFs were observed in North America, with the values for Q4 of 1.74% (95% CI: â0.09 to 3.39). TV had a significant modification effect on the heat-mortality association, causing a higher heat-related mortality burden with increments of TV. Implementing targeted strategies against heat exposure and fluctuant temperatures simultaneously would benefit public health. © 2022 The Author(s)Funding text 1: This study was supported by the Australian Research Council (DP210102076) and the Australian National Health and Medical Research Council (APP2000581). Y.W and B.W. were supported by the China Scholarship Council (nos. 202006010044 and 202006010043); S.L. was supported by an Emerging Leader Fellowship of the Australian National Health and Medical Research Council (no. APP2009866); Y.G. was supported by Career Development Fellowship (no. APP1163693) and Leader Fellowship (no. APP2008813) of the Australian National Health and Medical Research Council; J.K. and A.U. were supported by the Czech Science Foundation (project no. 20â28560S); N.S. was supported by the National Institute of Environmental Health Sciences-funded HERCULES Center (no. P30ES019776); Y.H. was supported by the Environment Research and Technology Development Fund (JPMEERF15S11412) of the Environmental Restoration and Conservation Agency; M.d.S.Z.S.C. and P.H.N.S. were supported by the SĂŁo Paulo Research Foundation (FAPESP); H.O. and E.I. were supported by the Estonian Ministry of Education and Research (IUT34â17); J.M. was supported by a fellowship of Fundação para a CiĂȘncia e a Tecnlogia (SFRH/BPD/115112/2016); A.G. and F.S. were supported by the Medical Research Council UK (grant ID MR/R013349/1), the Natural Environment Research Council UK (grant ID NE/R009384/1), and the EU's Horizon 2020 project, Exhaustion (grant ID 820655); A.S. and F.d.D. were supported by the EU's Horizon 2020 project, Exhaustion (grant ID 820655); V.H. was supported by the Spanish Ministry of Economy, Industry and Competitiveness (grant ID PCIN-2017â046); and A.T. by MCIN/AEI/10.13039/501100011033 (grant CEX2018-000794-S). Statistics South Africa kindly provided the mortality data, but had no other role in the study. Y.G. A.G. M.H. and B. Armstrong set up the collaborative network. Y.G. S.L. and Y.W. designed the study. Y.G. S.L. and A.G. developed the statistical methods. Y.W. B.W. S.L. and Y.G. took the lead in drafting the manuscript and interpreting the results. Y.W. B.W. Y.G. A.G. S.T. A.O. A.U. A.S. A.E. A.M.V.-C. A. Zanobetti, A.A. A. Zeka, A.T. B. Alahmad, B. Armstrong, B.F. C.Ă. C. Ameling, C.D.l.C.V. C. Ă
ström, D.H. D.V.D. D.R. E.I. E.L. F.M. F.A. F.D. F.S. G.C.-E. H. Kan, H.O. H. Kim, I.-H.H. J.K. J.M. J.S. K.K. M.H.-D. M.S.R. M.H. M.P. M.d.S.Z.S.C. N.S. P.M. P.G. P.H.N.S. R.A. S.O. T.N.D. V.C. V.H. W.L. X.S. Y.H. M.L.B. and S.L. provided the data and contributed to the interpretation of the results and the submitted version of the manuscript. Y.G. S.L. and Y.W. accessed and verified the data. All of the authors had full access to all of the data in the study and had final responsibility for the decision to submit for publication. The authors declare no competing interests.; Funding text 2: This study was supported by the Australian Research Council ( DP210102076 ) and the Australian National Health and Medical Research Council ( APP2000581 ). Y.W and B.W. were supported by the China Scholarship Council (nos. 202006010044 and 202006010043 ); S.L. was supported by an Emerging Leader Fellowship of the Australian National Health and Medical Research Council (no. APP2009866 ); Y.G. was supported by Career Development Fellowship (no. APP1163693) and Leader Fellowship (no. APP2008813) of the Australian National Health and Medical Research Council ; J.K. and A.U. were supported by the Czech Science Foundation (project no. 20â28560S ); N.S. was supported by the National Institute of Environmental Health Sciences -funded HERCULES Center (no. P30ES019776 ); Y.H. was supported by the Environment Research and Technology Development Fund ( JPMEERF15S11412 ) of the Environmental Restoration and Conservation Agency; M.d.S.Z.S.C. and P.H.N.S. were supported by the SĂŁo Paulo Research Foundation (FAPESP); H.O. and E.I. were supported by the Estonian Ministry of Education and Research ( IUT34â17 ); J.M. was supported by a fellowship of Fundação para a CiĂȘncia e a Tecnlogia ( SFRH/BPD/115112/2016 ); A.G. and F.S. were supported by the Medical Research Council UK (grant ID MR/R013349/1 ), the Natural Environment Research Council UK (grant ID NE/R009384/1 ), and the EUâs Horizon 2020 project, Exhaustion (grant ID 820655 ); A.S. and F.d.D. were supported by the EUâs Horizon 2020 project, Exhaustion (grant ID 820655 ); V.H. was supported by the Spanish Ministry of Economy, Industry and Competitiveness (grant ID PCIN-2017â046 ); and A.T. by MCIN/AEI/10.13039/501100011033 (grant CEX2018-000794-S). Statistics South Africa kindly provided the mortality data, but had no other role in the study
Global, regional, and national burden of mortality associated with short-term temperature variability from 2000-19: a three-stage modelling study
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 degrees x 0.5 degrees 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 degrees x 0.5 degrees 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
Recommended from our members
Fluctuating temperature modifies heat-mortality association around the globe
Studies have investigated the effects of heat and temperature variability (TV) on mortality. However, few assessed whether TV modifies the heat-mortality association. Data on daily temperature and mortality in the warm season were collected from 717 locations across 36 countries. TV was calculated as the standard deviation of the average of the same and previous daysâ minimum and maximum temperatures. We used location-specific quasi-Poisson regression models with an interaction term between the cross-basis term for mean temperature and quartiles of TV to obtain heat-mortality associations under each quartile of TV, and then pooled estimates at the country, regional, and global levels. Results show the increased risk in heat-related mortality with increments in TV, accounting for 0.70% (95% confidence interval [CI]: â0.33 to 1.69), 1.34% (95% CI: â0.14 to 2.73), 1.99% (95% CI: 0.29â3.57), and 2.73% (95% CI: 0.76â4.50) of total deaths for Q1âQ4 (first quartileâfourth quartile) of TV. The modification effects of TV varied geographically. Central Europe had the highest attributable fractions (AFs), corresponding to 7.68% (95% CI: 5.25â9.89) of total deaths for Q4 of TV, while the lowest AFs were observed in North America, with the values for Q4 of 1.74% (95% CI: â0.09 to 3.39). TV had a significant modification effect on the heat-mortality association, causing a higher heat-related mortality burden with increments of TV. Implementing targeted strategies against heat exposure and fluctuant temperatures simultaneously would benefit public health.This study was supported by the Australian Research Council ( DP210102076 ) and the Australian National Health and Medical Research Council ( APP2000581 ). Y.W and B.W. were supported by the China Scholarship Council (nos. 202006010044 and 202006010043 ); S.L. was supported by an Emerging Leader Fellowship of the Australian National Health and Medical Research Council (no. APP2009866 ); Y.G. was supported by Career Development Fellowship (no. APP1163693) and Leader Fellowship (no. APP2008813) of the Australian National Health and Medical Research Council ; J.K. and A.U. were supported by the Czech Science Foundation (project no. 20â28560S ); N.S. was supported by the National Institute of Environmental Health Sciences -funded HERCULES Center (no. P30ES019776 ); Y.H. was supported by the Environment Research and Technology Development Fund ( JPMEERF15S11412 ) of the Environmental Restoration and Conservation Agency; M.d.S.Z.S.C. and P.H.N.S. were supported by the SĂŁo Paulo Research Foundation (FAPESP); H.O. and E.I. were supported by the Estonian Ministry of Education and Research ( IUT34â17 ); J.M. was supported by a fellowship of Fundação para a CiĂȘncia e a Tecnlogia ( SFRH/BPD/115112/2016 ); A.G. and F.S. were supported by the Medical Research Council UK (grant ID MR/R013349/1 ), the Natural Environment Research Council UK (grant ID NE/R009384/1 ), and the EUâs Horizon 2020 project, Exhaustion (grant ID 820655 ); A.S. and F.d.D. were supported by the EUâs Horizon 2020 project, Exhaustion (grant ID 820655 ); V.H. was supported by the Spanish Ministry of Economy, Industry and Competitiveness (grant ID PCIN-2017â046 ); and A.T. by MCIN/AEI/10.13039/501100011033 (grant CEX2018-000794-S). Statistics South Africa kindly provided the mortality data, but had no other role in the study
Global, regional, and national burden of mortality associated with short-term temperature variability from 2000â19: a three-stage modelling study
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° Ă 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 2000â19. 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° Ă 0·5° from 2000â19. Temperature variability was calculated as the SD of the average of the same and previous daysâ 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 901â2 357 718) were associated with temperature variability per year, accounting for 3·4% (2·2â4·6) 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% (3·7â5·3) per decade. The largest increase occurred in Australia and New Zealand (7·3%, 95% CI 4·3â10·4), followed by Europe (4·4%, 2·2â5·6) and Africa (3·3, 1·9â4·6). 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
Global, regional, and national burden of mortality associated with non-optimal ambient temperatures from 2000 to 2019: a three-stage modelling study
© 2021 The Author(s). 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° Ă 0·5° across the globe. A three-stage analysis strategy was used. First, the temperatureâmortality 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 temperatureâmortality 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 967â5 965 520) were associated with non-optimal temperatures per year, accounting for 9·43% (95% eCI 7·58â11·07) of all deaths (8·52% [6·19â10·47] were cold-related and 0·91% [0·56â1·36] were heat-related). There were 74 temperature-related excess deaths per 100 000 residents (95% eCI 60â87). 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 2000â03 to 2016â19, the global cold-related excess death ratio changed by â0·51 percentage points (95% eCI â0·61 to â0·42) and the global heat-related excess death ratio increased by 0·21 percentage points (0·13â0·31), 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.Australian Research Council; Australian National Health and Medical Research Council
Recommended from our members
Comparison for the effects of different components of temperature variability on mortality: A multi-country time-series study
Data availability:
The authors do not have permission to share data.Supplementary data are available online at: https://www.sciencedirect.com/science/article/pii/S0160412024002988?via%3Dihub#s0095 .Background:
Temperature variability (TV) is associated with increased mortality risk. However, it is still unknown whether intra-day or inter-day TV has a higher effect.
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 TV0â7 (0.9âŻÂ°C). An IQR increase in inter-day TV0â7 (1.6âŻÂ°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 TV0â7 and inter-day TV0â7 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.This study was supported by the Australian Research Council (DP210102076) and the Australian National Health and Medical Research Council (GNT2000581). BW by China Scholarship Council (number 202006010043); WY by China Scholarship Council (number 202006010044); SL by an Emerging Leader Fellowship of the Australian National Health and Medical Research Council (number GNT2009866); JK and AU by the Czech Science Foundation (project number 20â28560S); NS by the National Institute of Environmental Health Sciences-funded HERCULES Center (P30ES019776); S-CP and YLG by the Ministry of Science and Technology (Taiwan; MOST 109â2621-M-002â021); YH by the Environment Research and Technology Development Fund (JPMEERF15S11412) of the Environmental Restoration and Conservation Agency; MdSZSC and PHNS by the SĂŁo Paulo Research Foundation (FAPESP); ST by the Science and Technology Commission of Shanghai Municipality (grant number 18411951600); HO and EI by the Estonian Ministry of Education and Research (IUT34â17); JM by a fellowship of Fundação para a CiĂȘncia e a Tecnlogia (SFRH/BPD/115112/2016); AG by the Medical Research Council UK (grant IDs: MR/V034162/1 and MR/R013349/1), the Natural Environment Research Council UK (grant ID: NE/R009384/1), and the EU's Horizon 2020 project, Exhaustion (grant ID: 820655); AS, SR, and FdD by the EU's Horizon 2020 project, Exhaustion (grant ID 820655); VH by the Spanish Ministry of Economy, Industry and Competitiveness (grant ID PCIN-2017â046); AT by MCIN/AEI/10.13039/501100011033 (grant CEX2018-000794-S); YG by Career Development Fellowship (number GNT1163693) and Leader Fellowship (number GNT2008813) of the Australian National Health and Medical Research Council; Statistics South Africa kindly provided the mortality data, but had no other role in the study. This Article is published in memory of Simona Fratianni who helped to contribute the data for Romania
Comparison of weather station and climate reanalysis data for modelling temperature-related mortality.
Epidemiological analyses of health risks associated with non-optimal temperature are traditionally based on ground observations from weather stations that offer limited spatial and temporal coverage. Climate reanalysis represents an alternative option that provide complete spatio-temporal exposure coverage, and yet are to be systematically explored for their suitability in assessing temperature-related health risks at a global scale. Here we provide the first comprehensive analysis over multiple regions to assess the suitability of the most recent generation of reanalysis datasets for health impact assessments and evaluate their comparative performance against traditional station-based data. Our findings show that reanalysis temperature from the last ERA5 products generally compare well to station observations, with similar non-optimal temperature-related risk estimates. However, the analysis offers some indication of lower performance in tropical regions, with a likely underestimation of heat-related excess mortality. Reanalysis data represent a valid alternative source of exposure variables in epidemiological analyses of temperature-related risk
Mortality risk attributable to wildfire-related PM<sub>2·5</sub> pollution: A global time series study in 749 locations.
BACKGROUND: Many regions of the world are now facing more frequent and unprecedentedly large wildfires. However, the association between wildfire-related PM2·5 and mortality has not been well characterised. We aimed to comprehensively assess the association between short-term exposure to wildfire-related PM2·5 and mortality across various regions of the world. METHODS: For this time series study, data on daily counts of deaths for all causes, cardiovascular causes, and respiratory causes were collected from 749 cities in 43 countries and regions during 2000-16. Daily concentrations of wildfire-related PM2·5 were estimated using the three-dimensional chemical transport model GEOS-Chem at a 0·25°âĂâ0·25° resolution. The association between wildfire-related PM2·5 exposure and mortality was examined using a quasi-Poisson time series model in each city considering both the current-day and lag effects, and the effect estimates were then pooled using a random-effects meta-analysis. Based on these pooled effect estimates, the population attributable fraction and relative risk (RR) of annual mortality due to acute wildfire-related PM2·5 exposure was calculated. FINDINGS: 65·6 million all-cause deaths, 15·1 million cardiovascular deaths, and 6·8 million respiratory deaths were included in our analyses. The pooled RRs of mortality associated with each 10 ÎŒg/m3 increase in the 3-day moving average (lag 0-2 days) of wildfire-related PM2·5 exposure were 1·019 (95% CI 1·016-1·022) for all-cause mortality, 1·017 (1·012-1·021) for cardiovascular mortality, and 1·019 (1·013-1·025) for respiratory mortality. Overall, 0·62% (95% CI 0·48-0·75) of all-cause deaths, 0·55% (0·43-0·67) of cardiovascular deaths, and 0·64% (0·50-0·78) of respiratory deaths were annually attributable to the acute impacts of wildfire-related PM2·5 exposure during the study period. INTERPRETATION: Short-term exposure to wildfire-related PM2·5 was associated with increased risk of mortality. Urgent action is needed to reduce health risks from the increasing wildfires. FUNDING: Australian Research Council, Australian National Health & Medical Research Council