Challenges in Preventing Heart Disease in Hispanics: Early Lessons Learned from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL)

The challenge of preventing cardiovascular disease (CVD) in US Hispanics depends upon being able to understand and communicate about the diversity within this population in terms of environmental exposures, health behaviors, socio-cultural experiences and genetic background to CVD risk factor profiles and disease burdens. Recent publications from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) launched by the National Institutes of Health (NIH) have begun to accomplish this task. In this article we review some of the HCHS/SOL findings concerning cardiometabolic and other CVD risk factors and relate them to the need for increased access to health care and attention to lifestyle variables including nutrition. A major challenge that needs to be accomplished is to alert our lawmakers, public health officials, health care providers and the Hispanic population at large about how to lighten the CVD risk factor and disease burdens now carried by our Hispanic population

American College of Cardiology/American Heart Association (ACC/AHA) Class I Guidelines for the Treatment of Cholesterol to Reduce Atherosclerotic Cardiovascular Risk: Implications for US Hispanics/Latinos Based on Findings From the Hispanic Community Health Study/Study of Latinos (HCHS/SOL)

BACKGROUND: The prevalence estimates of statin eligibility among Hispanic/Latinos living in the United States under the new 2013 American College of Cardiology/American Heart Association (ACC/AHA) cholesterol treatment guidelines are not known. METHODS AND RESULTS: We estimated prevalence of statin eligibility under 2013 ACC/AHA and 3rd National Cholesterol Education Program Adult Treatment Panel (NCEP/ATP III) guidelines among Hispanic Community Health Study/Study of Latinos (n=16 415; mean age 41 years, 40% males) by using sampling weights calibrated to the 2010 US census. We examined the characteristics of Hispanic/Latinos treated and not treated with statins under both guidelines. We also redetermined the statin-therapy eligibility by using black risk estimates for Dominicans, Cubans, Puerto Ricans, and Central Americans. Compared with NCEP/ATP III guidelines, statin eligibility increased from 15.9% (95% CI 15.0-16.7%) to 26.9% (95% CI 25.7-28.0%) under the 2013 ACC/AHA guidelines. This was mainly driven by the ≥7.5% atherosclerotic cardiovascular disease risk criteria (prevalence 13.9% [95% CI 13.0-14.7%]). Of the participants eligible for statin eligibility under NCEP/ATP III and ACC/AHA guidelines, only 28.2% (95% CI 26.3-30.0%) and 20.6% (95% CI 19.4-21.9%) were taking statins, respectively. Statin-eligible participants who were not taking statins had a higher prevalence of cardiovascular risk factors compared with statin-eligible participants who were taking statins. There was no significant increase in statin eligibility when atherosclerotic cardiovascular disease risk was calculated by using black estimates instead of recommended white estimates (increase by 1.4%, P=0.12) for Hispanic/Latinos. CONCLUSIONS: The eligibility of statin therapy increased consistently across all Hispanic/Latinos subgroups under the 2013 ACC/AHA guidelines and therefore will potentially increase the number of undertreated Hispanic/Latinos in the United States

Characterization of patients who present with insomnia : is there room for a symptom cluster-based approach?

Study Objectives: This study examined empirically derived symptom cluster profiles among patients who present with insomnia using clinical data and polysomnography. Methods: Latent profile analysis was used to identify symptom cluster profiles of 175 individuals (63% female) with insomnia disorder based on total scores on validated self-report instruments of daytime and nighttime symptoms (Insomnia Severity Index, Glasgow Sleep Effort Scale, Fatigue Severity Scale, Beliefs and Attitudes about Sleep, Epworth Sleepiness Scale, Pre-Sleep Arousal Scale), mean values from a 7-day sleep diary (sleep onset latency, wake after sleep onset, and sleep efficiency), and total sleep time derived from an in-laboratory PSG. Results: The best-fitting model had three symptom cluster profiles: "High Subjective Wakefulness" (HSW), "Mild Insomnia" (MI) and "Insomnia-Related Distress" (IRD). The HSW symptom cluster profile (26.3% of the sample) reported high wake after sleep onset, high sleep onset latency, and low sleep efficiency. Despite relatively comparable PSG-derived total sleep time, they reported greater levels of daytime sleepiness. The MI symptom cluster profile (45.1%) reported the least disturbance in the sleep diary and questionnaires and had the highest sleep efficiency. The IRD symptom cluster profile (28.6%) reported the highest mean scores on the insomnia-related distress measures (eg, sleep effort and arousal) and waking correlates (fatigue). Covariates associated with symptom cluster membership were older age for the HSW profile, greater obstructive sleep apnea severity for the MI profile, and, when adjusting for obstructive sleep apnea severity, being overweight/obese for the IRD profile. Conclusions: The heterogeneous nature of insomnia disorder is captured by this data-driven approach to identify symptom cluster profiles. The adaptation of a symptom cluster-based approach could guide tailored patient-centered management of patients presenting with insomnia, and enhance patient care

Exportación de conservas de pescado: revisión sistemática de la literatura científica (2001-2021)

Objective. To show experiences and export plans of canned fish in South America presented in ScienceDirect, Redalyc, Scielo, Doaj, Econbiz, Sisbib, La Referencia and Fedesarrollo, between the years 2001 and 2021. In addition, the specific objectives were to identify the countries from which these experiences and export plans originate, to which countries they are oriented, their logistic methods, conclusions and recommendations. Method. A systematic review was conducted in which 1,069,944 records were identified, which, after application of exclusion and inclusion criteria, were reduced to 10 final records for analysis. Results. Data was extracted referring to the authors' names, the year of publication, the title of the record, the type of document (thesis, scientific article or technical report), the export product, exporting and importing country, logistic method and conclusions of the original authors. Conclusion. Of the selected records, most of the exports come from Ecuador (4 cases), the most used logistical method is maritime transport and their main destination is the U.S. market (5 cases), which concentrates the greatest demand for canned fish from the region, especially of Ecuadorian origin.Objetivo. Evidenciar experiencias y planes de exportación de conservas de pescado en Sudamérica presentadas en ScienceDirect, Redalyc, Scielo, Doaj, Econbiz, Sisbib, La Referencia y Fedesarrollo, entre los años 2001 y 2021. Además, se tuvo como objetivos específicos identificar de qué países provienen dichas experiencias y planes de exportación, a qué países se orientan, sus métodos logísticos, conclusiones y recomendaciones. Método. Se condujo una revisión sistemática en la que se identificaron 1 069 944 registros, los cuales, luego de la aplicación de criterios de exclusión e inclusión, se redujeron a 10 registros finales para el análisis. Resultados. Se extrajo data alusiva a los nombres de los autores, el año de publicación, el título del registro, el tipo de documento (tesis, artículo científico o informe técnico), el producto de exportación, país exportador e importador, método logístico y conclusiones de los autores originales. Conclusión. De los registros seleccionados, la mayoría de las exportaciones proviene de Ecuador (4 casos), el método logístico más utilizado es el transporte marítimo y tienen como destino principal el mercado estadounidense (5 casos) que concentra la mayor demanda por conservas de pescado de la región, especialmente de origen ecuatoriano

Is there a link between wealth and cardiovascular disease risk factors among Hispanic/Latinos? : Results from the HCHS/SOL sociocultural ancillary study

OBJECTIVE: To examine the relationship between wealth and cardiovascular disease risk factors among Hispanic/Latinos of diverse backgrounds. DESIGN: This cross-sectional study used data from 4971 Hispanic/Latinos, 18-74 years, who participated in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) baseline exam and the HCHS/SOL Sociocultural Ancillary Study. Three objectively measured cardiovascular disease risk factors (hypertension, hypercholesterolemia, and obesity) were included. Wealth was measured using an adapted version of the Home Affluence Scale, which included questions regarding the ownership of a home, cars, computers, and recent vacations. RESULTS: After adjusting for traditional socioeconomic indicators (income, employment, education), and other covariates, we found that wealth was not associated with hypertension, hypercholesterolemia or obesity. Analyses by sex showed that middle-wealth women were less likely to have hypercholesterolemia or obesity. Analyses by Hispanic/Latino background groups showed that while wealthier Central Americans were less likely to have obesity, wealthier Puerto Ricans were more likely to have obesity. CONCLUSION: This is the first study to explore the relationship between wealth and health among Hispanic/Latinos of diverse backgrounds, finding only partial evidence of this association. Future studies should utilize more robust measures of wealth, and address mechanisms by which wealth may impact health status among Hispanic/Latinos of diverse backgrounds in longitudinal designs

Is there a link between wealth and cardiovascular disease risk factors among Hispanic/Latinos? Results from the HCHS/SOL sociocultural ancillary study

Objective: To examine the relationship between wealth and cardiovascular disease risk factors among Hispanic/Latinos of diverse backgrounds. Design: This cross-sectional study used data from 4971 Hispanic/Latinos, 18-74 years, who participated in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) baseline exam and the HCHS/SOL Sociocultural Ancillary Study. Three objectively measured cardiovascular disease risk factors (hypertension, hypercholesterolemia, and obesity) were included. Wealth was measured using an adapted version of the Home Affluence Scale, which included questions regarding the ownership of a home, cars, computers, and recent vacations. Results: After adjusting for traditional socioeconomic indicators (income, employment, education), and other covariates, we found that wealth was not associated with hypertension, hypercholesterolemia or obesity. Analyses by sex showed that middle-wealth women were less likely to have hypercholesterolemia or obesity. Analyses by Hispanic/Latino background groups showed that while wealthier Central Americans were less likely to have obesity, wealthier Puerto Ricans were more likely to have obesity. Conclusion: This is the first study to explore the relationship between wealth and health among Hispanic/Latinos of diverse backgrounds, finding only partial evidence of this association. Future studies should utilize more robust measures of wealth, and address mechanisms by which wealth may impact health status among Hispanic/Latinos of diverse backgrounds in longitudinal designs

Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950-2019 : a comprehensive demographic analysis for the Global Burden of Disease Study 2019

Background: Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019. Methods: 8078 country-years of vital registration and sample registration data, 938 surveys, 349 censuses, and 238 other sources were identified and used to estimate age-specific fertility. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate age-specific fertility rates for 5-year age groups between ages 15 and 49 years. With extensions to age groups 10–14 and 50–54 years, the total fertility rate (TFR) was then aggregated using the estimated age-specific fertility between ages 10 and 54 years. 7417 sources were used for under-5 mortality estimation and 7355 for adult mortality. ST-GPR was used to synthesise data sources after correction for known biases. Adult mortality was measured as the probability of death between ages 15 and 60 years based on vital registration, sample registration, and sibling histories, and was also estimated using ST-GPR. HIV-free life tables were then estimated using estimates of under-5 and adult mortality rates using a relational model life table system created for GBD, which closely tracks observed age-specific mortality rates from complete vital registration when available. Independent estimates of HIV-specific mortality generated by an epidemiological analysis of HIV prevalence surveys and antenatal clinic serosurveillance and other sources were incorporated into the estimates in countries with large epidemics. Annual and single-year age estimates of net migration and population for each country and territory were generated using a Bayesian hierarchical cohort component model that analysed estimated age-specific fertility and mortality rates along with 1250 censuses and 747 population registry years. We classified location-years into seven categories on the basis of the natural rate of increase in population (calculated by subtracting the crude death rate from the crude birth rate) and the net migration rate. We computed healthy life expectancy (HALE) using years lived with disability (YLDs) per capita, life tables, and standard demographic methods. Uncertainty was propagated throughout the demographic estimation process, including fertility, mortality, and population, with 1000 draw-level estimates produced for each metric. Findings: The global TFR decreased from 2·72 (95% uncertainty interval [UI] 2·66–2·79) in 2000 to 2·31 (2·17–2·46) in 2019. Global annual livebirths increased from 134·5 million (131·5–137·8) in 2000 to a peak of 139·6 million (133·0–146·9) in 2016. Global livebirths then declined to 135·3 million (127·2–144·1) in 2019. Of the 204 countries and territories included in this study, in 2019, 102 had a TFR lower than 2·1, which is considered a good approximation of replacement-level fertility. All countries in sub-Saharan Africa had TFRs above replacement level in 2019 and accounted for 27·1% (95% UI 26·4–27·8) of global livebirths. Global life expectancy at birth increased from 67·2 years (95% UI 66·8–67·6) in 2000 to 73·5 years (72·8–74·3) in 2019. The total number of deaths increased from 50·7 million (49·5–51·9) in 2000 to 56·5 million (53·7–59·2) in 2019. Under-5 deaths declined from 9·6 million (9·1–10·3) in 2000 to 5·0 million (4·3–6·0) in 2019. Global population increased by 25·7%, from 6·2 billion (6·0–6·3) in 2000 to 7·7 billion (7·5–8·0) in 2019. In 2019, 34 countries had negative natural rates of increase; in 17 of these, the population declined because immigration was not sufficient to counteract the negative rate of decline. Globally, HALE increased from 58·6 years (56·1–60·8) in 2000 to 63·5 years (60·8–66·1) in 2019. HALE increased in 202 of 204 countries and territories between 2000 and 2019

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

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