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Variation in racial/ethnic disparities in COVID-19 mortality by age in the United States: A cross-sectional study


Autoři: Mary T. Bassett aff001;  Jarvis T. Chen aff001;  Nancy Krieger aff001
Působiště autorů: Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America aff001;  Francois-Xavier Bagnoud Center for Health and Human Rights, Harvard University, Boston, Massachusetts, United States of America aff002
Vyšlo v časopise: Variation in racial/ethnic disparities in COVID-19 mortality by age in the United States: A cross-sectional study. PLoS Med 17(10): e1003402. doi:10.1371/journal.pmed.1003402
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pmed.1003402

Souhrn

Background

In the United States, non-Hispanic Black (NHB), Hispanic, and non-Hispanic American Indian/Alaska Native (NHAIAN) populations experience excess COVID-19 mortality, compared to the non-Hispanic White (NHW) population, but racial/ethnic differences in age at death are not known. The release of national COVID-19 death data by racial/ethnic group now permits analysis of age-specific mortality rates for these groups and the non-Hispanic Asian or Pacific Islander (NHAPI) population. Our objectives were to examine variation in age-specific COVID-19 mortality rates by racial/ethnicity and to calculate the impact of this mortality using years of potential life lost (YPLL).

Methods and findings

This cross-sectional study used the recently publicly available data on US COVID-19 deaths with reported race/ethnicity, for the time period February 1, 2020, to July 22, 2020. Population data were drawn from the US Census. As of July 22, 2020, the number of COVID-19 deaths equaled 68,377 for NHW, 29,476 for NHB, 23,256 for Hispanic, 1,143 for NHAIAN, and 6,468 for NHAPI populations; the corresponding population sizes were 186.4 million, 40.6 million, 2.6 million, 19.5 million, and 57.7 million. Age-standardized rate ratios relative to NHW were 3.6 (95% CI 3.5, 3.8; p < 0.001) for NHB, 2.8 (95% CI 2.7, 3.0; p < 0.001) for Hispanic, 2.2 (95% CI 1.8, 2.6; p < 0.001) for NHAIAN, and 1.6 (95% CI 1.4, 1.7; p < 0.001) for NHAP populations. By contrast, NHB rate ratios relative to NHW were 7.1 (95% CI 5.8, 8.7; p < 0.001) for persons aged 25–34 years, 9.0 (95% CI 7.9, 10.2; p < 0.001) for persons aged 35–44 years, and 7.4 (95% CI 6.9, 7.9; p < 0.001) for persons aged 45–54 years. Even at older ages, NHB rate ratios were between 2.0 and 5.7. Similarly, rate ratios for the Hispanic versus NHW population were 7.0 (95% CI 5.8, 8.7; p < 0.001), 8.8 (95% CI 7.8, 9.9; p < 0.001), and 7.0 (95% CI 6.6, 7.5; p < 0.001) for the corresponding age strata above, with remaining rate ratios ranging from 1.4 to 5.0. Rate ratios for NHAIAN were similarly high through age 74 years. Among NHAPI persons, rate ratios ranged from 2.0 to 2.8 for persons aged 25–74 years and were 1.6 and 1.2 for persons aged 75–84 and 85+ years, respectively. As a consequence, more YPLL before age 65 were experienced by the NHB and Hispanic populations than the NHW population—despite the fact that the NHW population is larger—with a ratio of 4.6:1 and 3.2:1, respectively, for NHB and Hispanic persons. Study limitations include likely lag time in receipt of completed death certificates received by the Centers for Disease Control and Prevention for transmission to NCHS, with consequent lag in capturing the total number of deaths compared to data reported on state dashboards.

Conclusions

In this study, we observed racial variation in age-specific mortality rates not fully captured with examination of age-standardized rates alone. These findings suggest the importance of examining age-specific mortality rates and underscores how age standardization can obscure extreme variations within age strata. To avoid overlooking such variation, data that permit age-specific analyses should be routinely publicly available.

Klíčová slova:

Alaska – Cancer risk factors – COVID 19 – Death rates – Hispanic people – Medical risk factors – Open data – United States


Zdroje

1. Eligon J, Burch ADS, Searcey D, Oppel RA Jr. Black Americans face alarming rates of virus infection in some states. New York Times. 2020 Apr 14 [cited 2020 Jun 24]. Available from: https://www.nytimes.com/2020/04/07/us/coronavirus-race.html.

2. Bauer S. Milwaukee’s black community hit hard by coronavirus. AP News. 2020 Mar 27 [cited 2020 Jun 24]. Available from: https://apnews.com/b52e4e9a63d64e3a25109f09010508b6.

3. Krieger N, Gonsalves G, Bassett MT, Hanage W. Krumholz HM. The fierce urgency of now: closing glaring gaps in us surveillance data on COVID-19. Health Affairs Blog, 2020 Apr 14 [cited 2020 Jun 24]. Available from: https://www.healthaffairs.org/do/10.1377/hblog20200414.238084/full/.

4. New York City Department of Health and Mental Hygiene. COVID-19: data. New York: New York City Department of Health and Mental Hygiene; 2020 [cited 2020 Jun 24]. Available from: https://www1.nyc.gov/site/doh/covid/covid-19-data.page.

5. Gross CP, Essien UR, Pasha S, Gross JR, Wang S-Y, Nunez-Smith M. Racial and ethnic disparities in population-level Covid-19 mortality. medRxiv. 2020 May 11. doi: 10.1101/2020.05.07.20094250

6. Cunningham TJ, Croft B, Liu Y, Lu H, Eke PI, Giles WH. Vital signs: racial disparities in age-specific mortality among Blacks or African-Americans—United States, 1999–2015. MMWR Morb Mortal Wkly Rep. 2017;66:444–56. doi: 10.15585/mmwr.mm6617e1 28472021

7. Chen Y, Freedman ND, Rodriquez EJ. Shiels MS, Napoles AM, Withrow DR, et al. Trends in premature deaths among adults in the United States and Latin America. JAMA Netw Open. 2020;3(2):e1921085. doi: 10.1001/jamanetworkopen.2019.21085 32049297

8. Williams DR. The health of US racial and ethnic populations. J Gerontol B Psychol Sci Soc Sci. 2005;60(Spec No 2):53–62.

9. Oppel RA Jr, Gebeloff R, Lai KKR, Wright W, Smith M. The fullest look yet at the racial inequity of coronavirus. New York Times. 2020 July 5 [cited 2020 Jul 31]. Available from: https://www.nytimes.com/interactive/2020/07/05/us/coronavirus-latinos-african-americans-cdc-data.html.

10. National Center for Health Statistics. Deaths involving coronavirus disease (COVID-19) by race and Hispanic origin group and age, by state. Atlanta: Centers for Disease Control and Prevention; 2020 Jul 20 [cited 2020 Jul 22]. Available from: https://data.cdc.gov/NCHS/Deaths-involving-coronavirus-disease-2019-COVID-19/ks3g-spdg.

11. Centers for Disease Control and Prevention. Coronavirus Disease 2019 (COVID-19). Atlanta: Centers for Disease Control and Prevention; 2020 [cited 2020 Jul 31]. Available from: https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/cases-in-us.html.

12. CDC WONDER. Bridged-race resident population estimates: United States, state and county for the years 1990–2019. Atlanta: Centers for Disease Control and Prevention; 2020 [cited 2020 Oct 5]. Available from: https://wonder.cdc.gov/wonder/help/bridged-race.html/.

13. National Cancer Institute Surveillance, Epidemiology, and End Results Program. Standard populations (millions) for age-adjustment. Bethesda (MD): National Cancer Institute; 2020 [cited 2020 Jun 24]. Available from: https://seer.cancer.gov/stdpopulations/.

14. Rothman KJ, Greenland S. Modern epidemiology. 2nd edition. Philadelphia: Lippincott-Raven; 1998.

15. CDC WONDER. Underlying cause of death 1999–2018. Atlanta: Centers for Disease Control and Prevention; 2020 [cited 2020 Oct 2]. Available from: https://wonder.cdc.gov/wonder/help/ucd.html.

16. Centers for Disease Control (CDC). Premature mortality in the United States: public health issues in the use of years of potential life lost. MMWR Suppl. 1986;35(2):1S‐11S. 3097485

17. Krieger N, Rehkopf DH, Chen JT, Waterman PD, Marcelli E, Kennedy M. The fall and rise of US inequities in premature mortality: 1960–2002. PLoS Med. 2008;5(2):e46. doi: 10.1371/journal.pmed.0050046 18303941

18. Arias E, Heron M, National Center for Health Statistics, Hakes J, US Census Bureau. The validity of race and Hispanic-origin reporting on death certificates in the United States: an update. Vital Health Stat 2. 2016;(172):1–21. 28436642

19. Anderson RN, Copeland G, Hayes JM. Linkages to improve mortality data for American Indians and Alaska Natives: a new model for death reporting? Am J Public Health. 2014;104(Suppl 3):S258–62.

20. Krieger N. The US Census and the people’s health: public health engagement from enslavement and “Indians not taxed” to census tracts and health equity (1790–2018). Am J Public Health. 2019;109(8):1092–100. doi: 10.2105/AJPH.2019.305017 31219723

21. Bigback KM, Hoopes M, Dankovchik J, Knaster E, Warren-Mears V, Joshi S, et al. Using record linkage to improve data quality for American Indian and Alaska Natives in two Pacific Northwest state hospital discharge databases. Health Serv Res. 2015;50(Suppl 1):1390–402.

22. Kochanek KD, Murphy SL, Xu JQ, Arias E. Deaths: final data for 2017. Natl Vital Stat Rep. 2019;68(9):1–76. 32501199

23. Umberson D. Black deaths matter: race, relationship loss, and effects on survivors. J Health Soc Behav. 2017;58(4):405–20. doi: 10.1177/0022146517739317 29172766

24. Umberson D, Olson JS, Crosnoe R, Liu H, Pudrovska T, Donnelly R. Death of family members as an overlooked source of racial disadvantage in the United States. Proc Natl Acad Sci U S A. 2017;114(5):915–20. doi: 10.1073/pnas.1605599114 28115712

25. Thyden NH, Schmidt NM, Osypuk TL. The unequal distribution of sibling and parent deaths by race and its effect on attaining a college degree. Ann Epidemiol. 2020;45:76–82.e1. doi: 10.1016/j.annepidem.2020.03.002 32371043

26. Lieberman-Cribbin W, Tuminello S, Flores RM, Taioli E. Disparities in COVID-19 testing and positivity in New York City. Am J Prev Med. 2020;59(3):326–32. doi: 10.1016/j.amepre.2020.06.005 32703702

27. Servick K. ‘Huge hole’ in COVID-19 testing data makes it harder to study racial disparities. Science Magazine. 2020 Jul 10 [cited 2020 Jul 31]. Available from: https://www.sciencemag.org/news/2020/07/huge-hole-covid-19-testing-data-makes-it-harder-study-racial-disparities.

28. Leon DA, Shkolnikov VM Smeeth L, Magnus P, Pecholdová M, Jarvis CI. COVID-19: a need for real-time monitoring of weekly excess deaths. Lancet. 2020;395(10234):e81. doi: 10.1016/S0140-6736(20)30933-8 32333839

29. New York Department of Health and Mental Hygiene (DOHMH) COVID-19 Response Team. Preliminary estimate of excess mortality during the COVID-19 outbreak—New York City, March 11–May 2, 2020. MMWR Morb Mortal Wkly Rep. 2020;69:603–5. doi: 10.15585/mmwr.mm6919e5

30. Chen JT, Waterman PD, Krieger N. COVID-19 and the unequal surge in mortality rates in Massachusetts, by city/town and ZIP Code measures of poverty, household crowding, race/ethnicity, and racialized economic segregation. HCPDS Working Paper Volume 19, Number 2. Cambridge: Harvard Center for Population and Development Studies; 2020 May 9 [cited 2020 Jun 24]. Available from: https://cdn1.sph.harvard.edu/wp-content/uploads/sites/1266/2020/05/20_jtc_pdw_nk_COVID19_MA-excess-mortality_text_tables_figures_final_0509_with-cover-1.pdf.

31. COVID-19 Health Equity Advisory Group. Health Equity Advisory Group recommendations—July 2020. Boston: Massachusetts Department of Public Health; 2020 Jul 9 [cited 2020 Oct 5]. Available from: https://www.mass.gov/orgs/covid-19-health-equity-advisory-group.

32. Hales CM, Carroll MD, Fryar CD, Ogden CL. Prevalence of obesity and severe obesity among adults: United States, 2017–2018. NCHS Data Brief. 2020;(360):1–8. 32487284

33. Office of Minority Health. Obesity and African Americans. Washington (DC): US Department of Health and Human Services; 2020 [cited 2020 Jun 24]. Available from: https://www.minorityhealth.hhs.gov/omh/browse.aspx?lvl=4&lvlid=25.

34. Afridi A, Block L. Frontline communities hit hardest by COVID-19. New York: Association for Neighborhood and Housing Development; 2020 Apr 2 [cited 2020 Jun 24]. Available from: https://anhd.org/blog/frontline-communities-hit-hardest-covid-19.

35. Kissler SM, Kishore N, Prabhu M, Goffman D, Beilin Y, Landau R, et al. Reductions in commuting mobility predict geographic differences in SARS-CoV-2 prevalence in New York City. Cambridge: Harvard University; 2020 [cited 2020 Jun 24]. Available from: http://nrs.harvard.edu/urn-3:HUL.InstRepos:42665370.

36. Glaeser EL, Gorback CS, Redding SJ. How much does COVID-19 increase with mobility? Evidence from New York and four other U.S. cities. NBER Working Paper No. 27519. Cambridge: National Bureau of Economic Research; 2020 Jul [cited 2020 Jul 31]. Available from: https://www.nber.org/papers/w27519.

37. Fernandez E, Weiler N. Initial results of Mission District COVID-19 testing announced. Latinx Community, men and economically vulnerable are at highest risk. San Francisco: University of California, San Francisco; 2020 May 4 [cited 2020 Jun 24]. Available from: https://www.ucsf.edu/news/2020/05/417356/initial-results-mission-district-covid-19-testing-announced.


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