Annexin A2 is a novel Cellular Redox Regulatory Protein involved in Tumorigenesis

Annexins are a structurally related family of calcium and phospholipid-binding proteins that are involved in the regulation of a wide range of molecular and cellular processes. Annexin A2 is unique among the annexins in that it possesses redox sensitive cysteine(s). The ubiquitous and abundant expression of ANXA2 in cells and its reactivity with hydrogen peroxide led us to hypothesize that this protein could play a role in cellular redox regulation. Here we show that ANXA2 protein levels are induced by hydrogen peroxide. Furthermore, depletion of ANXA2 resulted in the elevation of cellular reactive oxygen species (ROS) upon oxidative stress, increased activation of the ROS-induced pro-apoptotic kinases, JNK, p38 and Akt and elevated sensitivity to ROS-mediated cellular damage/death. ANXA2-null mice showed significantly elevated protein oxidation in the liver and lung tissues compared to WT mice. ANXA2 depleted cancer cells showed enhanced cellular protein oxidationconcomitant with decreased tumor growth compared to control cancer cells andboth the oxidation of cellular proteins and tumor growth deficit werereversed by the antioxidant N-acetyl cysteine, indicating that ANXA2 plays akey role in the regulation of cellular redox during tumorigenesis. Ex-vivo human cancer studies showed that up-regulation of the reduced form of ANXA2 is associated with protection of the tumor proteins from oxidation. In summary, our results indicate that ANXA2 plays an important role incellular redox regulation by protecting cells from oxidative stress, aneffect that is particularly important during tumorigenesis

Comparison of weather station and climate reanalysis data for modelling temperature-related mortality

Multi-Country Multi-City (MCC) Collaborative Research Network: Barrak Alahmad, Rosana Abrutzky, Paulo Hilario Nascimento Saldiva, Patricia Matus Correa, Nicolás Valdés Orteg, Haidong Kan, Samuel Osorio, Ene Indermitte, Jouni J K Jaakkola, Niilo Ryti, Alexandra Schneider, Veronika Huber, Klea Katsouyanni, Antonis Analitis, Alireza Entezari, Fatemeh Mayvaneh, Paola Michelozzi, Francesca de'Donato, Masahiro Hashizume, Yoonhee Kim, Magali Hurtado Diaz, César De la Cruz Valencia, Ala Overcenco, Danny Houthuijs, Caroline Ameling, Shilpa Rao, Xerxes Seposo, Baltazar Nunes, Iulian-Horia Holobaca, Ho Kim, Whanhee Lee, Carmen Íñiguez, Bertil Forsberg, Christofer Åström, Martina S Ragettli, Yue-Liang Leon Guo, Bing-Yu Chen, Valentina Colistro, Antonella Zanobetti, Joel Schwartz, Tran Ngoc Dang, Do Van DungErratum in: Author Correction: Sci Rep. 2022 May 13;12(1):7960. doi: 10.1038/s41598-022-11769-6. https://www.nature.com/articles/s41598-022-11769-6Epidemiological 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.The study was primarily supported by Grants from the European Commission’s Joint Research Centre Seville (Research Contract ID: JRC/SVQ/2020/MVP/1654), Medical Research Council-UK (Grant ID: MR/R013349/1), Natural Environment Research Council UK (Grant ID: NE/R009384/1), European Union’s Horizon 2020 Project Exhaustion (Grant ID: 820655). The following individual Grants also supported this work: J.K and A.U were supported by the Czech Science Foundation, project 20-28560S. A.T was supported by MCIN/AEI/10.13039/501100011033, Grant CEX2018-000794-S. V.H was supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant agreement No 101032087.info:eu-repo/semantics/publishedVersio

a three-stage modelling study

Funding Information: This study was supported by the Australian Research Council (DP210102076) and the Australian National Health and Medical Research Council (APP2000581). YW was supported by the China Scholarship Council (number 202006010044). SL was supported by an Emerging Leader Fellowship of the Australian National Health and Medical Research Council (number APP2009866). QZ was supported by the Program of Qilu Young Scholars of Shandong University, Jinan, China. BW was supported by the China Scholarship Council (number 202006010043). JK and AU were supported by the Czech Science Foundation (project number 20–28560S). NS was supported by the National Institute of Environmental Health Sciences-funded HERCULES Center (P30ES019776). S-CP and YLG were supported by the Ministry of Science and Technology (Taiwan; MOST 109–2621-M-002–021). YH was supported by the Environment Research and Technology Development Fund (JPMEERF15S11412) of the Environmental Restoration and Conservation Agency. MdSZSC and PHNS were supported by the São Paulo Research Foundation (FAPESP). ST was supported by the Science and Technology Commission of Shanghai Municipality (grant number 18411951600). HO and EI were supported by the Estonian Ministry of Education and Research (IUT34–17). JM was supported by a fellowship of Fundação para a Ciência e a Tecnlogia (SFRH/BPD/115112/2016). AG and FS 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). AS, SR, and FdD were supported by the EU's Horizon 2020 project, Exhaustion (grant ID 820655). VH was supported by the Spanish Ministry of Economy, Industry and Competitiveness (grant ID PCIN-2017–046). AT was supported by MCIN/AEI/10.13039/501100011033 (grant CEX2018-000794-S). YG was supported by the Career Development Fellowship (number APP1163693) and Leader Fellowship (number APP2008813) 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. Publisher Copyright: © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licenseBackground: 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° × 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 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° × 0·5° 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.publishersversionpublishe

Interactive effects of ambient fine particulate matter and ozone on daily mortality in 372 cities: two stage time series analysis

OBJECTIVE: To investigate potential interactive effects of fine particulate matter (PM2.5) and ozone (O3) on daily mortality at global level. DESIGN: Two stage time series analysis. SETTING: 372 cities across 19 countries and regions. POPULATION: Daily counts of deaths from all causes, cardiovascular disease, and respiratory disease. MAIN OUTCOME MEASURE: Daily mortality data during 1994-2020. Stratified analyses by co-pollutant exposures and synergy index (>1 denotes the combined effect of pollutants is greater than individual effects) were applied to explore the interaction between PM2.5 and O3 in association with mortality. RESULTS: During the study period across the 372 cities, 19.3 million deaths were attributable to all causes, 5.3 million to cardiovascular disease, and 1.9 million to respiratory disease. The risk of total mortality for a 10 μg/m3 increment in PM2.5 (lag 0-1 days) ranged from 0.47% (95% confidence interval 0.26% to 0.67%) to 1.25% (1.02% to 1.48%) from the lowest to highest fourths of O3 concentration; and for a 10 μg/m3 increase in O3 ranged from 0.04% (-0.09% to 0.16%) to 0.29% (0.18% to 0.39%) from the lowest to highest fourths of PM2.5 concentration, with significant differences between strata (P for interaction <0.001). A significant synergistic interaction was also identified between PM2.5 and O3 for total mortality, with a synergy index of 1.93 (95% confidence interval 1.47 to 3.34). Subgroup analyses showed that interactions between PM2.5 and O3 on all three mortality endpoints were more prominent in high latitude regions and during cold seasons. CONCLUSION: The findings of this study suggest a synergistic effect of PM2.5 and O3 on total, cardiovascular, and respiratory mortality, indicating the benefit of coordinated control strategies for both pollutants

Coarse particulate air pollution and daily mortality a global study in 205 cities

Please read abstract in the article.The National Natural Science Foundation of China; the Ministry of Science and Technology, Taiwan; the Medical Research Council-UK; Fundação para a Ciência e a Tecnologia; the Australian Research Council the European Union’s Horizon 2020 Project Exhaustion ; the Natural Environment Research Council UK; the Australian National Health and Medical Research Council; and an Emerging Leader Fellowship of the Australian National Health and Medical Research Council.http://www.atsjournals.org/journal/ajrccm2023-06-07hj2023Geography, Geoinformatics and Meteorolog

Global, regional, and national burden of mortality associated with non-optimal ambient temperatures from 2000 to 2019: a three-stage modelling study.

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

Geographical Variations of the Minimum Mortality Temperature at a Global Scale

Background: Minimum mortality temperature (MMT) is an important indicator to assess the temperature-mortality association, indicating long-term adaptation to local climate. Limited evidence about the geographical variability of the MMT is available at a global scale.Methods: We collected data from 658 communities in 43 countries under different climates. We estimated temperature-mortality associations to derive the MMT for each community using Poisson regression with distributed lag nonlinear models. We investigated the variation in MMT by climatic zone using a mixed-effects meta-analysis and explored the association with climatic and socioeconomic indicators.Results: The geographical distribution of MMTs varied considerably by country between 14.2 and 31.1 °C decreasing by latitude. For climatic zones, the MMTs increased from alpine (13.0 °C) to continental (19.3 °C), temperate (21.7 °C), arid (24.5 °C), and tropical (26.5 °C). The MMT percentiles (MMTPs) corresponding to the MMTs decreased from temperate (79.5th) to continental (75.4th), arid (68.0th), tropical (58.5th), and alpine (41.4th). The MMTs indreased by 0.8 °C for a 1 °C rise in a community’s annual mean temperature, and by 1 °C for a 1 °C rise in its SD. While the MMTP decreased by 0.3 centile points for a 1 °C rise in a community’s annual mean temperature and by 1.3 for a 1 °C rise in its SD.Conclusions: The geographical distribution of the MMTs and MMTPs is driven mainly by the mean annual temperature, which seems to be a valuable indicator of overall adaptation across populations. Our results suggest that populations have adapted to the average temperature, although there is still more room for adaptation

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° × 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 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° × 0·5° 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

Mortality risk attributable to wildfire-related PM2·5 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° × 0·25° 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 μg/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.The Australian Research Council, the Australian National Health and Medical Research Council, a Career Development Fellowship of the Australian National Health and Medical Research Council, an Early Career Fellowship of the Australian National Health and Medical Research Council, the National Natural Science Foundation of China, the Czech Science Foundation, the Spanish Ministry of Economy, Industry and Competitiveness, the National Key Research and Development Program of China, EU’s Horizon 2020 Project Exhaustion, the Ministry of Science and Technology of Taiwan, the Medical Research Council UK, the Natural Environment Research Council UK, a fellowship of the Fundação para a Ciência e a Tecnologia, the Science and Technology Commission of Shanghai Municipality and the National Institute of Environmental Health Sciences-funded HERCULES Center.http://www.thelancet.com/planetary-healtham2022Geography, Geoinformatics and Meteorolog

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation