Reductions in 2020 US life expectancy due to COVID-19 and the disproportionate impact on the Black and Latino populations.
Ontology highlight
ABSTRACT:
SUBMITTER: Andrasfay T
PROVIDER: S-EPMC7865122 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:COVID-19 has resulted in a staggering death toll in the US: over 180,000 by the end of August 2020, according to the National Center for Health Statistics. Black and Latino Americans have experienced a disproportionate burden of COVID-19 morbidity and mortality, reflecting persistent structural inequalities that increase risk of exposure to COVID-19 and mortality risk for those infected. We estimate life expectancy at birth and at age 65 for 2020, for the total US population and by race and ethnicity, using four scenarios of deaths - one in which the COVID-19 pandemic had not occurred and three including COVID-19 mortality projections produced by the Institute for Health Metrics and Evaluation. Our most likely estimate indicates a reduction in US life expectancy at birth of 1.41 years. This decline results in a life expectancy of 77.2 years, a value last observed in 2003. We also project a 1.08-year reduction in life expectancy at age 65. The Black and Latino populations are estimated to experience declines in life expectancy at birth of 2.69 and 3.66 years, respectively, both of which are several times the 0.84-year reduction for whites. These projections imply an increase of over 50% in the Black-white life expectancy gap, from 3.6 to 5.5 years, thereby eliminating twenty years of progress made in reducing this differential. Latinos, who have consistently experienced lower mortality than whites (a phenomenon known as the Latino or Hispanic paradox), would see their more than three-year survival advantage almost eliminated.
| S-EPMC7523145 | biostudies-literature
Project description:Tobacco smoking is a major burden on the Australian population in terms of health, social and economic costs. Because of this, in 2008, all Australian Governments agreed to set targets to reduce prevalence of smoking to 10 % by 2018 and subsequently introduced several very strong anti-smoking measures. On this backdrop, we estimated in 2012-13 the impact of several scenarios related to reduction of smoking prevalence to 10 % across the entire Australian population and for below specific ages, on improving life expectancy.Using the risk percentiles method the Australian Diabetes, Obesity and Lifestyle (AUSDIAB) baseline survey and the Australian Bureau of Statistics (ABS) age-sex specific death counts were analyzed.Amongst men the gains in life expectancy associated with 10 % smoking prevalence are generally greater than those of women with average life expectancy for men increasing by 0.11 to 0.41 years, and for women by 0.12 to 0.29 years. These are at best 54 % and 49 % for men and women of the gains achieved by complete smoking cessation. The gains plateau for interventions targeting those <70 and <80 years. Amongst smokers the potential gains are much greater, with an increase in average life expectancy amongst men smokers of 0.43 to 2.08 years, and 0.73 to 2.05 years amongst women smokers. These are at best 46 % and 38 % for men and women smokers of the gains achieved by complete smoking cessation.The estimated optimum gain in life expectancy is consistent with potentially moderate gains which occur when both men and women below 60 years are targeted to reduce smoking prevalence to 10 %.
| S-EPMC4729127 | biostudies-other
Project description: Not available
| S-EPMC1403259 | biostudies-literature
Project description:BACKGROUND:During the previous century the average lifespan in the United States (US) increased by over 30 years, with much of this increase attributed to public health initiatives. This report examines further gains that might be achieved through reduced occurrence of injury-related death. METHODS:US life tables and injury death rate data were used to estimate potential increases in life expectancy assuming various reductions in the rate of fatal injuries. Corresponding numbers of deaths potentially averted annually were also estimated; unit (per death) medical and lifetime work loss costs were employed to estimate total costs potentially averted annually. RESULTS:Through elimination of injury as a cause of death, average US life expectancy at birth could be increased by approximately 1.5 years, with notable variations by sex, ethnicity, and race. More conservatively, average life expectancy at birth could be increased by 0.41 years assuming that the national injury death rate could be brought into line with the lowest state-specific rate. Under this more conservative but plausible assumption, an estimated 48,400 injury deaths and $61 billion in medical and work loss costs would be averted annually. CONCLUSIONS:Increases in life expectancy of the magnitude considered in this report are arguably attainable based on long-term historical reductions in the US injury death rate, as well as significant continuing reductions seen in other developed countries. Contemporary evidence-based interventions can play an important role in reducing injury-related deaths, such as those due to drug overdoses and older adult falls, as well as suicides.
| S-EPMC5577772 | biostudies-literature
Project description:BACKGROUND:Although the black-white gap in life expectancy has narrowed in the U.S., there is considerable variability across states. In Wisconsin, the black-white gap exceeds 6 years, well above the national average. Reducing this disparity is an urgent public health priority, but there is limited understanding of what contributes to Wisconsin's racial gap in longevity. Our investigation identifies causes of death that contribute most to Wisconsin's black-white gap in life expectancy among males and females, and highlights specific ages where each cause of death contributes most to the gap. METHODS:Our study employs 1999-2016 restricted-use mortality data provided by the National Center for Health Statistics. After generating race- and sex-specific life tables for each 3-year period of observation (e.g., 1999-2001), we trace recent trends in the black-white life expectancy gap in Wisconsin. We subsequently conduct a series of analyses to decompose the black-white gap in three time periods into 13 separate causes and 19 different age groups. RESULTS:In 2014-16, Wisconsin's black-white gap in life expectancy was 7.34 years for males (67% larger than the national gap), and 5.61 years for females (115% larger than the national gap). Among males, homicide was the single largest contributor, accounting for 1.56 years of the total gap. Heart disease and cancer followed, contributing 1.43 and 1.42 years, respectively. Among females, heart disease and cancer were the two leading contributors to the gap, accounting for 1.12 and 1.00 years, respectively. Whereas homicide contributed most to the racial gap in male longevity during late adolescence and early adulthood, heart disease and cancer exerted most of their influence between ages 50-70 for both males and females. Other notable contributors were unintentional injuries (males), diabetes and cerebrovascular disease (females), and perinatal conditions (males and females). CONCLUSIONS:Our study identifies targets for future policy interventions that could substantially reduce Wisconsin's racial gap in life expectancy. Concerted efforts to eliminate racial disparities in perinatal mortality and homicide early in the life course, and chronic conditions such as cancer and heart disease in later life, promise to help Wisconsin achieve the public health objective of racial parity in longevity.
| S-EPMC6612087 | biostudies-other
Project description:In many countries of the world, COVID-19 pandemic has led to exceptional changes in mortality trends. Some studies have tried to quantify the effects of Covid-19 in terms of a reduction in life expectancy at birth in 2020. However, these estimates might need to be updated now that, in most countries, the mortality data for the whole year are available. We used data from the Human Mortality Database (HMD) Short-Term Mortality Fluctuations (STMF) data series to estimate life expectancy in 2020 for several countries. The changes estimated using these data and the appropriate methodology seem to be more pessimistic than those that have been proposed so far: life expectancy dropped in the Russia by 2.16 years, 1.85 in USA, and 1.27 in England and Wales. The differences among countries are substantial: many countries (e.g. Denmark, Island, Norway, New Zealand, South Korea) saw a rather limited drop in life expectancy or have even seen an increase in life expectancy.
| S-EPMC8803147 | biostudies-literature
Project description:IntroductionIn the 2016 U.S. Presidential election, voters in communities with recent stagnation or decline in life expectancy were more likely to vote for the Republican candidate than in prior Presidential elections. We aimed to assess the association between change in life expectancy and voting patterns in the 2020 Presidential election.MethodsWith data on county-level life expectancy from the Institute for Health Metrics and Evaluation and voting data from a GitHub repository of results scraped from news outlets, we used weighted multivariable linear regression to estimate the association between the change in life expectancy from 1980 to 2014 and the proportion of votes for the Republican candidate and change in the proportion of votes cast for the Republican candidate in the 2020 Presidential election.ResultsAmong 3110 U.S counties and Washington, D.C., change in life expectancy at the county level was negatively associated with Republican share of the vote in the 2020 Presidential election (parameter estimate -7.2, 95% confidence interval, -7.8 to -6.6). With the inclusion of state, sociodemographic, and economic variables in the model, the association was attenuated (parameter estimate -0.8; 95% CI, -1.5 to -0.2). County-level change in life expectancy was positively associated with change in Republican vote share 0.29 percentage points (95% CI, 0.23 to 0.36). The association was attenuated when state, sociodemographic, and economic variables were added (parameter estimate 0.24; 95% CI, 0.15 to 0.33).ConclusionCounties with a less positive trajectory in life expectancy were more likely to vote for the Republican candidate in the 2020 U.S. Presidential election, but the Republican candidate's share improved in some counties that experienced marked gains in life expectancy. Associations were moderated by demographic, social and economic factors.
| S-EPMC8209240 | biostudies-literature
Project description:Although the black-white gap in life expectancy has been shrinking in the U.S., national improvement conceals ongoing disparities. Nowhere is this more evident than Washington D.C., where the black-white gap has persistently exceeded 10 years. Using 1999-2017 mortality data from the National Center for Health Statistics, we employed demographic techniques to pursue three aims: first, we created period life tables to examine longevity trends in Washington D.C.; second, we decomposed black-white life expectancy differences into 23 causes of death in three time periods (2000, 2008, 2016); third, we assessed age-specific contributions for each cause of death. Findings revealed that heart disease (4.14 years), homicide (2.43 years), and cancer (2.30 years) contributed most to the 17.23-year gap among males in 2016. Heart disease and cancer contributed most at ages 55-69; homicide contributed most at ages 20-29. Among females in 2016, heart disease (3.24 years), cancer (2.36 years), and unintentional injuries (0.85 years) contributed most to the 12.06-year gap. Heart disease and cancer contributed most at ages 55-69, and unintentional injuries at ages 50-59. Our investigation provides detailed evidence about contributors to the black-white longevity gap in Washington D.C., which can aid in the development of targeted public health interventions.
| S-EPMC7453009 | biostudies-literature
Project description:BackgroundLife expectancy is a simple measure of assessing health differences between two or more populations but current life expectancy calculations are not reliable for small populations. A potential solution to this is to borrow strength from larger populations from the same source, but this has not formally been investigated.MethodsUsing data on 451,222 individuals from the Clinical Practice Research Datalink on the presence/absence of intellectual disability and type 2 diabetes mellitus, we compared stratified and combined flexible parametric models, and Chiang's methods, for calculating life expectancy. Confidence intervals were calculated using the Delta method, Chiang's adjusted life table approach and bootstrapping.ResultsThe flexible parametric models allowed calculation of life expectancy by exact age and beyond traditional life expectancy age thresholds. The combined model that fit age interaction effects as a spline term provided less bias and greater statistical precision for small covariate subgroups by borrowing strength from the larger subgroups. However, careful consideration of the distribution of events in the smallest group was needed.ConclusionsLife expectancy is a simple measure to compare health differences between populations. The use of combined flexible parametric methods to calculate life expectancy in small samples has shown promising results by allowing life expectancy to be modelled by exact age, greater statistical precision, less bias and prediction of different covariate patterns without stratification. We recommend further investigation of their application for both policymakers and researchers.
| S-EPMC10498577 | biostudies-literature
Project description:Background Four decades of population-based tobacco control strategies have contributed to substantial reduction in smoking prevalence in Australia. However, smoking prevalence is still double in socially disadvantaged groups compared to those that are not. But not all tobacco control strategies successfully used in the general population is effective in specific high-risk population groups. Hence, an effective way to reduce smoking in high risk population groups may include targeting them specifically to identify and support smokers to quit. In this backdrop, we examined whether tobacco control interventions at the population-level are more effective in increasing life expectancy among Australians compared to interventions targeting a high risk group or a combination of the two when smoking prevalence is reduced to 10 and 0% respectively. Methods Using the risk percentiles approach, analyses were performed separately for men and women using data from various sources such as the 2014–15 National Health Survey linked to death registry, simulated data for high risk groups, and the Australian population and deaths data from the census. Indigenous status was simulated by preferentially assigning those who are indigenous to lower SES quintiles. The age-sex distribution of mental disorder status was simulated using its distribution from 2016 National Drug Strategy Household Survey with 25.9% of mentally ill being assigned to current smoking category and the rest to non-smoking category. The age-sex distribution of prisoners was simulated based on 2014 ABS Prisoners Australia survey with 74% of prisoners being assigned to current smoker category and the rest to non-smoker category. Homelessness status was simulated according to age, sex and indigenous status for 2011 census with all homeless being allocated to the lowest SES category. The age-sex distribution of total cholesterol level was simulated based on 2011–13 Australian Health Survey. Results The results showed that the combined approach for reducing smoking is most effective for improving life expectancy of Australians particularly for the socially disadvantaged and mentally ill groups both of which have high fraction of smokers in the population. For those who were mentally ill the gain in ALE due to reduction of smoking to 10% was 0.53?years for males and 0.36?years for females which were around 51 and 42% respectively of the maximal gains in ALE that could be achieved through complete cessation. Conclusions Targeting high-risk population groups having substantial fraction of smokers in the population can strongly complement the existing population-based smoking reduction strategies. As population and high risk approaches are both important, the national prevention policies should make judicious use of both to maximize health gain.
| S-EPMC7526239 | biostudies-literature