Association of the COVID-19 Pandemic With Estimated Life Expectancy by Race/Ethnicity in the United States, 2020.
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ABSTRACT:
SUBMITTER: Andrasfay T
PROVIDER: S-EPMC8226419 | biostudies-literature | 2021 Jun
REPOSITORIES: biostudies-literature
Publications
Association of the COVID-19 Pandemic With Estimated Life Expectancy by Race/Ethnicity in the United States, 2020.
Andrasfay Theresa T Goldman Noreen N
JAMA network open 20210601 6
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Project description:Background/objectiveInvestigating trends in life expectancy and lifespan variation can highlight disproportionate mortality burdens among population subgroups. We examined inequalities in life expectancy and lifespan variation by race/ethnicity and by urbanicity in the US from 1990 to 2019.MethodsUsing vital registration data for 322.0 million people in 3,141 counties from the National Center for Health Statistics, we obtained life expectancy at birth and lifespan variation for 16 race/ethnicity-gender-urbanicity combinations in six 5-year periods (1990-1994 to 2015-2019). Race/ethnicity was categorized as Hispanic, and non-Hispanic White, Black, and Asian/Pacific Islander. Urbanicity was categorized as metropolitan vs nonmetropolitan areas, or in six further detailed categorizations. Life expectancy and lifespan variation (coefficient of variation) were computed using life tables.ResultsIn 2015-2019, residents in metropolitan areas had higher life expectancies than their nonmetropolitan counterparts (79.6 years compared to 77.0 years). The widest inequality in life expectancy occurred between Asian/Pacific Islander women and Black men, with a 17.7-year gap for residents in metropolitan areas and a 16.9-year gap for residents in nonmetropolitan areas. Nonmetropolitan areas had greater dispersion around average age at death. Black individuals had the highest lifespan variations in both metropolitan and nonmetropolitan areas. Until the mid-2010s, life expectancy increased while lifespan variation decreased; however, recent trends show stagnation in life expectancy and increases in lifespan variation. Metropolitan-nonmetropolitan inequalities in both life expectancy and lifespan variation widened over time.ConclusionDespite previous improvements in longevity, life expectancy is now stagnating while lifespan variation is increasing. Our results highlight that early-life deaths (i.e., young- and middle-age mortality) disproportionately affect Black individuals, who not only live the shortest lifespans but also have the most variability with respect to age at death.
| S-EPMC9485214 | biostudies-literature
Project description:ObjectivesSince the 1980s, life expectancy at birth (e0) in the United States has fallen steadily behind that of other high-income countries, widening the U.S. e0 disadvantage. We estimate how that disadvantage was affected by high mortality rates in 2020, the first full year of the coronavirus disease 2019 pandemic.MethodsWe contrast male and female e0 in the United States and 18 peer countries for years 1980, 1995, 2010, 2019, and 2020. Using Arriaga decomposition, we show how differences in age-specific death rates have contributed to U.S. e0 disadvantages.ResultsIn 2020, U.S. male and female e0 changed by -2.33 (-2.50, -2.15) and -1.69 (-1.85, -1.53) years, respectively, whereas corresponding changes in peer countries averaged -0.67 (-0.82, -0.51) and -0.50 (-0.65, -0.35) years, respectively. This accelerated a longstanding and widening U.S. e0 disadvantage relative to its peers, which increased from 3.49 to 5.15 years in males and from 2.78 to 3.97 years in females between 2019 and 2020. Whereas deaths before age 65 accounted for 55% and 40% of declines in U.S. male and female life expectancy, respectively, they accounted for only 24% and 11% of the respective declines in peer countries.DiscussionU.S. life expectancy declines in 2020 were larger than in peer countries and involved deaths across a broader age range, particularly among young and middle-aged adults. Both the longstanding U.S. e0 disadvantage and acute losses of life in 2020 signal the need for systemic policy changes in the United States.
| S-EPMC9154231 | biostudies-literature
Project description:BackgroundEnd-of-life care is a prominent consideration in patients on maintenance dialysis, especially when death appears imminent and quality of life is poor. To date, examination of race- and ethnicity-associated disparities in end-of-life care for patients with ESRD has largely been restricted to comparisons of white and black patients.MethodsWe performed a retrospective national study using United States Renal Data System files to determine whether end-of-life care in United States patients on dialysis is subject to racial or ethnic disparity. The primary outcome was a composite of discontinuation of dialysis and death in a nonhospital or hospice setting.ResultsAmong 1,098,384 patients on dialysis dying between 2000 and 2014, the primary outcome was less likely in patients from any minority group compared with the non-Hispanic white population (10.9% versus 22.6%, P<0.001, respectively). We also observed similar significant disparities between any minority group and non-Hispanic whites for dialysis discontinuation (16.7% versus 31.2%), as well as hospice (10.3% versus 18.1%) and nonhospital death (34.4% versus 46.4%). After extensive covariate adjustment, the primary outcome was less likely in the combined minority group than in the non-Hispanic white population (adjusted odds ratio, 0.55; 95% confidence interval, 0.55 to 0.56; P<0.001). Individual minority groups (non-Hispanic Asian, non-Hispanic black, non-Hispanic Native American, and Hispanic) were significantly less likely than non-Hispanic whites to experience the primary outcome. This disparity was especially pronounced for non-Hispanic Native American and Hispanic subgroups.ConclusionsThere appear to be substantial race- and ethnicity-based disparities in end-of-life care practices for United States patients receiving dialysis.
| S-EPMC6115657 | biostudies-literature
Project description:BackgroundLife expectancy (LE) differences within and between states by race/ethnicity have not been examined.ObjectiveTo estimate LE for selected race/ethnicity groups in states from 1990 to 2019.DesignCross-sectional time-series analysis.SettingUnited States.ParticipantsDeidentified death records and Census data were used to construct regression models with smoothed time series of mortality from 1990 to 2019.MeasurementsLE at birth, by sex and year, for subgroups of people reporting Hispanic, non-Hispanic Black, or non-Hispanic White race/ethnicity.ResultsDisparities in LE across states were 8.0 years for females and 12.2 years for males in 1990 and 7.9 years for females and 7.8 years for males in 2019. When race/ethnicity groups were accounted for, disparities across states were 20.7 years for females and 24.5 years for males in 1990, decreasing to 18.5 years for females and 23.7 years for males in 2019. Disparities across states increased within each race/ethnicity group between 1990 and 2019, with the largest increase for non-Hispanic White males and the smallest for Hispanic females. The disparity between race/ethnicity groups within states decreased for most of the 23 states with estimates for all 3 groups but increased for females in 7 states and males in 5 states.LimitationBecause of small sample size, LE was not estimated for 37 of 153 state-race/ethnicity groups.ConclusionDisparity in LE across states was greater when race/ethnicity groups were considered. Disparities across all state-race/ethnicity groups in general have decreased over the past 3 decades. Within each race/ethnicity group, disparities across states have increased. Although racial/ethnic disparities decreased in most of the 23 states for which LE was estimated for all 3 groups, they increased for females in 7 states and males in 5 states.Primary funding sourceNational Heart, Lung, and Blood Institute.
| S-EPMC10519623 | biostudies-literature
Project description:ImportanceThe relationship between income and life expectancy is well established but remains poorly understood.ObjectivesTo measure the level, time trend, and geographic variability in the association between income and life expectancy and to identify factors related to small area variation.Design and settingIncome data for the US population were obtained from 1.4 billion deidentified tax records between 1999 and 2014. Mortality data were obtained from Social Security Administration death records. These data were used to estimate race- and ethnicity-adjusted life expectancy at 40 years of age by household income percentile, sex, and geographic area, and to evaluate factors associated with differences in life expectancy.ExposurePretax household earnings as a measure of income.Main outcomes and measuresRelationship between income and life expectancy; trends in life expectancy by income group; geographic variation in life expectancy levels and trends by income group; and factors associated with differences in life expectancy across areas.ResultsThe sample consisted of 1,408,287,218 person-year observations for individuals aged 40 to 76 years (mean age, 53.0 years; median household earnings among working individuals, $61,175 per year). There were 4,114,380 deaths among men (mortality rate, 596.3 per 100,000) and 2,694,808 deaths among women (mortality rate, 375.1 per 100,000). The analysis yielded 4 results. First, higher income was associated with greater longevity throughout the income distribution. The gap in life expectancy between the richest 1% and poorest 1% of individuals was 14.6 years (95% CI, 14.4 to 14.8 years) for men and 10.1 years (95% CI, 9.9 to 10.3 years) for women. Second, inequality in life expectancy increased over time. Between 2001 and 2014, life expectancy increased by 2.34 years for men and 2.91 years for women in the top 5% of the income distribution, but by only 0.32 years for men and 0.04 years for women in the bottom 5% (P < .001 for the differences for both sexes). Third, life expectancy for low-income individuals varied substantially across local areas. In the bottom income quartile, life expectancy differed by approximately 4.5 years between areas with the highest and lowest longevity. Changes in life expectancy between 2001 and 2014 ranged from gains of more than 4 years to losses of more than 2 years across areas. Fourth, geographic differences in life expectancy for individuals in the lowest income quartile were significantly correlated with health behaviors such as smoking (r = -0.69, P < .001), but were not significantly correlated with access to medical care, physical environmental factors, income inequality, or labor market conditions. Life expectancy for low-income individuals was positively correlated with the local area fraction of immigrants (r = 0.72, P < .001), fraction of college graduates (r = 0.42, P < .001), and government expenditures (r = 0.57, P < .001).Conclusions and relevanceIn the United States between 2001 and 2014, higher income was associated with greater longevity, and differences in life expectancy across income groups increased over time. However, the association between life expectancy and income varied substantially across areas; differences in longevity across income groups decreased in some areas and increased in others. The differences in life expectancy were correlated with health behaviors and local area characteristics.
| S-EPMC4866586 | biostudies-literature
Project description:ObjectiveFederal funds have been spent to reduce the disproportionate effects of HIV/AIDS on racial/ethnic minority groups in the United States. We investigated the association between federal domestic HIV funding and age-adjusted HIV death rates by race/ethnicity in the United States during 1999-2017.MethodsWe analyzed HIV funding data from the Kaiser Family Foundation by federal fiscal year (FFY) and US age-adjusted death rates (AADRs) by race/ethnicity (Hispanic, non-Hispanic white, non-Hispanic black, and Asian/Pacific Islander and American Indian/Alaska Native [API+AI/AN]) from Centers for Disease Control and Prevention WONDER detailed mortality files. We fit joinpoint regression models to estimate the annual percentage change (APC), average APC, and changes in AADRs per billion US dollars in HIV funding, with 95% confidence intervals (CIs). For 19 data points, the number of joinpoints ranged from 0 to 4 on the basis of rules set by the program or by the user. A Monte Carlo permutation test indicated significant (P < .05) changes at joinpoints, and 2-sided t tests indicated significant APCs in AADRs.ResultsDomestic HIV funding increased from $10.7 billion in FFY 1999 to $26.3 billion in FFY 2017, but AADRs decreased at different rates for each racial/ethnic group. The average rate of change in AADR per US billion dollars was -9.4% (95% CI, -10.9% to -7.8%) for Hispanic residents, -7.8% (95% CI, -9.0% to -6.6%) for non-Hispanic black residents, -6.7% (95% CI, -9.3% to -4.0%) for non-Hispanic white residents, and -5.2% (95% CI, -7.8% to -2.5%) for non-Hispanic API+AI/AN residents.ConclusionsIncreased domestic HIV funding was associated with faster decreases in age-adjusted HIV death rates for Hispanic and non-Hispanic black residents than for residents in other racial/ethnic groups. Increasing US HIV funding could be associated with decreasing future racial/ethnic disparities in the rate of HIV-related deaths.
| S-EPMC7804047 | biostudies-literature
Project description:The relevance of race and ethnicity to genetics and medicine has long been a matter of debate. An emerging consensus holds that race and ethnicity are social constructs and thus poor proxies for genetic diversity. The goal of this study was to evaluate the relationship between race, ethnicity, and clinically relevant pharmacogenomic variation in cosmopolitan populations. We studied racially and ethnically diverse cohorts of 65,120 participants from the United States All of Us Research Program (All of Us) and 31,396 participants from the United Kingdom Biobank (UKB). Genome-wide patterns of pharmacogenomic variation-6311 drug response-associated variants for All of Us and 5966 variants for UKB-were analyzed with machine learning classifiers to predict participants' self-identified race and ethnicity. Pharmacogenomic variation predicts race/ethnicity with averages of 92.1% accuracy for All of Us and 94.3% accuracy for UKB. Group-specific prediction accuracies range from 99.0% for the White group in UKB to 92.9% for the Hispanic group in All of Us. Prediction accuracies are substantially lower for individuals who identified with more than one group in All of Us (16.7%) or as Mixed in UKB (70.7%). There are numerous individual pharmacogenomic variants with large allele frequency differences between race/ethnicity groups in both cohorts. Frequency differences for toxicity-associated variants predict hundreds of adverse drug reactions per 1000 treated participants for minority groups in All of Us. Our results indicate that race and ethnicity can be used to stratify pharmacogenomic risk in the US and UK populations and should not be discounted when making treatment decisions. We resolve the contradiction between the results reported here and the orthodoxy of race and ethnicity as non-genetic, social constructs by emphasizing the distinction between global and local patterns of human genetic diversity, and we stress the current and future limitations of race and ethnicity as proxies for pharmacogenomic variation.
| S-EPMC10383154 | biostudies-literature
Project description:ObjectivePhysical symptoms are common and a leading reason for primary care visits; however, data are lacking on their prevalence among racial/ethnic minorities in the United States. This study aimed to compare the prevalence of physical symptoms among White, Latino and Asian Americans, and examine the association of symptoms and acculturation.MethodsWe analyzed data from the National Latino and Asian American Study, a nationally representative survey of 4864 White, Latino and Asian American adults. We compared the age- and gender-adjusted prevalence of 14 physical symptoms among the racial/ethnic groups and estimated the association between indicators of acculturation (English proficiency, nativity, generational status and proportion of lifetime in the United States) and symptoms among Latino and Asian Americans.ResultsAfter adjusting for age and gender, the mean number of symptoms was similar for Whites (1.00) and Latinos (0.95) but significantly lower among Asian Americans (0.60, P<.01 versus Whites). Similar percentages of Whites (15.4%) and Latinos (13.0%) reported three or more symptoms, whereas significantly fewer Asian Americans (7.7%, P<.05 versus Whites) did. In models adjusted for sociodemographic variables and clinical status (psychological distress, medical conditions and disability), acculturation was significantly associated with physical symptoms among both Latino and Asian Americans, such that the most acculturated individuals had the most physical symptoms.ConclusionsThe prevalence of physical symptoms differs across racial/ethnic groups, with Asian Americans reporting fewer symptoms than Whites. Consistent with a "healthy immigrant" effect, increased acculturation was strongly associated with greater symptom burden among both Latino and Asian Americans.
| S-EPMC3383871 | biostudies-literature
Project description:Current evidence and professional guidance recommend sleeping between 7 and 9 h in a 24-h period for optimal health. The present study examines the association between sleep duration and mortality and assesses whether this association varies by racial/ethnic identity for a large and diverse sample of United States adults. We use data on 274,836 adults, aged 25 and older, from the 2004-2014 waves of the National Health Interview Survey (NHIS) linked to prospective mortality through 2015 (23,382 deaths). Cox proportional hazards models were used in multi-variable regressions to estimate hazard ratios for mortality by sleep duration and racial/ethnic identity, controlling for sociodemographic, socioeconomic, and psychological distress variables. We find elevated risks of mortality from any cause for adults who sleep less than 5 h or more than 9 h in a 24-h period after all adjustments. Further, we find evidence that these elevated risks for mortality are more pronounced for some racial/ethnic groups and less pronounced for others. Improved understanding of differences in sleep duration and sleep health can facilitate more effective and culturally-tailored interventions around sleep health, improving overall well-being and enhancing longevity.
| S-EPMC9920264 | biostudies-literature
Project description:BackgroundIn a 2018 descriptive study, cancer incidence in children (age 0-19) in diagnosis years 2003 to 2014 was reported as being highest in New Hampshire and in the Northeast region.MethodsUsing the Cancer in North America (CiNA) analytic file, we tested the hypotheses that incidence rates in the Northeast were higher than those in other regions of the United States either overall or by race/ethnicity group, and that rates in New Hampshire were higher than the Northeast region as a whole.ResultsIn 2003 to 2014, pediatric cancer incidence was significantly higher in the Northeast than other regions of the United States overall and among non-Hispanic Whites and Blacks, but not among Hispanics and other racial minorities. However, there was no significant variability in incidence in the states within the Northeast overall or by race/ethnicity subgroup. Overall, statistically significantly higher incidence was seen in the Northeast for lymphomas [RR, 1.15; 99% confidence interval (CI), 1.10-1.19], central nervous system neoplasms (RR, 1.12; 99% CI, 1.07-1.16), and neuroblastoma (RR, 1.13; 99% CI, 1.05-1.21).ConclusionsPediatric cancer incidence is statistically significantly higher in the Northeast than in the rest of the United States, but within the Northeast, states have comparable incidence. Differences in cancer subtypes by ethnicity merit further investigation.ImpactOur analyses clarify and extend previous reports by statistically confirming the hypothesis that the Northeast has the highest pediatric cancer rates in the country, by providing similar comparisons stratified by race/ethnicity, and by assessing variability within the Northeast.
| S-EPMC9578755 | biostudies-literature