Ten Americas: a systematic analysis of life expectancy disparities in the USA.
Nearly two decades ago, the Eight Americas study offered a novel lens for examining health inequities in the USA by partitioning the US population into eight groups based on geography, race, urbanicity, income per capita, and homicide rate. That study found gaps of 12·8 years for females and 15·4 years for males in life expectancy in 2001 across these eight groups. In this study, we aimed to update and expand the original Eight Americas study, examining trends in life expectancy from 2000 to 2021 for ten Americas (analogues to the original eight, plus two additional groups comprising the US Latino population), by year, sex, and age group.
In this systematic analysis, we defined ten mutually exclusive and collectively exhaustive Americas comprising the entire US population, starting with all combinations of county and race and ethnicity, and assigning each to one of the ten Americas based on race and ethnicity and a variable combination of geographical location, metropolitan status, income, and Black-White residential segregation. We adjusted deaths from the National Vital Statistics System to account for misreporting of race and ethnicity on death certificates. We then tabulated deaths from the National Vital Statistics System and population estimates from the US Census Bureau and the National Center for Health Statistics from Jan 1, 2000, to Dec 31, 2021, by America, year, sex, and age, and calculated age-specific mortality rates in each of these strata. Finally, we constructed abridged life tables for each America, year, and sex, and extracted life expectancy at birth, partial life expectancy within five age groups (0-4, 5-24, 25-44, 45-64, and 65-84 years), and remaining life expectancy at age 85 years.
We defined the ten Americas as: America 1-Asian individuals; America 2-Latino individuals in other counties; America 3-White (majority), Asian, and American Indian or Alaska Native (AIAN) individuals in other counties; America 4-White individuals in non-metropolitan and low-income Northlands; America 5-Latino individuals in the Southwest; America 6-Black individuals in other counties; America 7-Black individuals in highly segregated metropolitan areas; America 8-White individuals in low-income Appalachia and Lower Mississippi Valley; America 9-Black individuals in the non-metropolitan and low-income South; and America 10-AIAN individuals in the West. Large disparities in life expectancy between the Americas were apparent throughout the study period but grew more substantial over time, particularly during the first 2 years of the COVID-19 pandemic. In 2000, life expectancy ranged 12·6 years (95% uncertainty interval 12·2-13·1), from 70·5 years (70·3-70·7) for America 9 to 83·1 years (82·7-83·5) for America 1. The gap between Americas with the lowest and highest life expectancies increased to 13·9 years (12·6-15·2) in 2010, 15·8 years (14·4-17·1) in 2019, 18·9 years (17·7-20·2) in 2020, and 20·4 years (19·0-21·8) in 2021. The trends over time in life expectancy varied by America, leading to changes in the ordering of the Americas over this time period. America 10 was the only America to experience substantial declines in life expectancy from 2000 to 2019, and experienced the largest declines from 2019 to 2021. The three Black Americas (Americas 6, 7, and 9) all experienced relatively large increases in life expectancy before 2020, and thus all three had higher life expectancy than America 10 by 2006, despite starting at a lower level in 2000. By 2010, the increase in America 6 was sufficient to also overtake America 8, which had a relatively flat trend from 2000 to 2019. America 5 had relatively similar life expectancy to Americas 3 and 4 in 2000, but a faster rate of increase in life expectancy from 2000 to 2019, and thus higher life expectancy in 2019; however, America 5 experienced a much larger decline in 2020, reversing this advantage. In some cases, these trends varied substantially by sex and age group. There were also large differences in income and educational attainment among the ten Americas, but the patterns in these variables differed from each other and from the patterns in life expectancy in some notable ways. For example, America 3 had the highest income in most years, and the highest proportion of high-school graduates in all years, but was ranked fourth or fifth in life expectancy before 2020.
Our analysis confirms the continued existence of different Americas within the USA. One's life expectancy varies dramatically depending on where one lives, the economic conditions in that location, and one's racial and ethnic identity. This gulf was large at the beginning of the century, only grew larger over the first two decades, and was dramatically exacerbated by the COVID-19 pandemic. These results underscore the vital need to reduce the massive inequity in longevity in the USA, as well as the benefits of detailed analyses of the interacting drivers of health disparities to fully understand the nature of the problem. Such analyses make targeted action possible-local planning and national prioritisation and resource allocation-to address the root causes of poor health for those most disadvantaged so that all Americans can live long, healthy lives, regardless of where they live and their race, ethnicity, or income.
State of Washington, Bloomberg Philanthropies, Bill & Melinda Gates Foundation.
Dwyer-Lindgren L
，Baumann MM
，Li Z
，Kelly YO
，Schmidt C
，Searchinger C
，La Motte-Kerr W
，Bollyky TJ
，Mokdad AH
，Murray CJ
... -
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What are the Trends in Racial Diversity Among Orthopaedic Applicants, Residents, and Faculty?
Orthopaedic surgery has recruited fewer applicants from underrepresented in medicine (UIM) racial groups than many other specialties, and recent studies have shown that although applicants from UIM racial groups are competitive for orthopaedic surgery, they enter the specialty at lower rates. Although previous studies have measured trends in orthopaedic surgery applicant, resident, or attending diversity in isolation, these populations are interdependent and therefore should be analyzed together. It is unclear how racial diversity among orthopaedic applicants, residents, and faculty has changed over time and how it compares with other surgical and medical specialties.
(1) How has the proportion of orthopaedic applicants, residents, and faculty from UIM and White racial groups changed between 2016 and 2020? (2) How does representation of orthopaedic applicants from UIM and White racial groups compare with that of other surgical and medical specialties? (3) How does representation of orthopaedic residents from UIM and White racial groups compare with that of other surgical and medical specialties? (4) How does representation of orthopaedic faculty from UIM and White racial groups compare with that of other surgical and medical specialties?
We drew racial representation data for applicants, residents, and faculty between 2016 and 2020. Applicant data on racial groups was obtained for 10 surgical and 13 medical specialties from the Association of American Medical Colleges Electronic Residency Application Services report, which annually publishes demographic data on all medical students applying to residency through Electronic Residency Application Services. Resident data on racial groups were obtained for the same 10 surgical and 13 medical specialties from the Journal of the American Medical Association Graduate Medical Education report, which annually publishes demographic data on residents in residency training programs accredited by the Accreditation Council for Graduate Medical Education. Faculty data on racial groups were obtained for four surgical and 12 medical specialties from the Association of American Medical Colleges Faculty Roster United States Medical School Faculty report, which annually publishes demographic data of active faculty at United States allopathic medical schools. UIM racial groups include American Indian or Alaska Native, Black or African American, Hispanic or Latino, and Native American or Other Pacific Islander. Chi-square tests were performed to compare representation of UIM and White groups among orthopaedic applicants, residents, and faculty between 2016 and 2020. Further, chi-square tests were performed to compare aggregate representation of applicants, residents, and faculty from UIM and White racial groups in orthopaedic surgery to aggregate representation among other surgical and medical specialties with available data.
The proportion of orthopaedic applicants from UIM racial groups increased between 2016 to 2020 from 13% (174 of 1309) to 18% (313 of 1699, absolute difference 0.051 [95% CI 0.025 to 0.078]; p < 0.001). The proportion of orthopaedic residents (9.6% [347 of 3617] to 10% [427 of 4242]; p = 0.48) and faculty (4.7% [186 of 3934] to 4.7% [198 of 4234]; p = 0.91) from UIM racial groups did not change from 2016 to 2020. There were more orthopaedic applicants from UIM racial groups (15% [1151 of 7446]) than orthopaedic residents from UIM racial groups (9.8% [1918 of 19,476]; p < 0.001). There were also more orthopaedic residents from UIM groups (9.8% [1918 of 19,476]) than orthopaedic faculty from UIM groups (4.7% [992 of 20,916], absolute difference 0.051 [95% CI 0.046 to 0.056]; p < 0.001). The proportion of orthopaedic applicants from UIM groups (15% [1151 of 7446]) was greater than that of applicants to otolaryngology (14% [446 of 3284], absolute difference 0.019 [95% CI 0.004 to 0.033]; p = 0.01), urology (13% [319 of 2435], absolute difference 0.024 [95% CI 0.007 to 0.039]; p = 0.005), neurology (12% [1519 of 12,862], absolute difference 0.036 [95% CI 0.027 to 0.047]; p < 0.001), pathology (13% [1355 of 10,792], absolute difference 0.029 [95% CI 0.019 to 0.039]; p < 0.001), and diagnostic radiology (14% [1635 of 12,055], absolute difference 0.019 [95% CI 0.009 to 0.029]; p < 0.001), and it was not different from that of applicants to neurosurgery (16% [395 of 2495]; p = 0.66), plastic surgery (15% [346 of 2259]; p = 0.87), interventional radiology (15% [419 of 2868]; p = 0.28), vascular surgery (17% [324 of 1887]; p = 0.07), thoracic surgery (15% [199 of 1294]; p = 0.94), dermatology (15% [901 of 5927]; p = 0.68), internal medicine (15% [18,182 of 124,214]; p = 0.05), pediatrics (16% [5406 of 33,187]; p = 0.08), and radiation oncology (14% [383 of 2744]; p = 0.06). The proportion of orthopaedic residents from UIM groups (9.8% [1918 of 19,476]) was greater than UIM representation among residents in otolaryngology (8.7% [693 of 7968], absolute difference 0.012 [95% CI 0.004 to 0.019]; p = 0.003), interventional radiology (7.4% [51 of 693], absolute difference 0.025 [95% CI 0.002 to 0.043]; p = 0.03), and radiation oncology (7.9% [289 of 3659], absolute difference 0.020 [95% CI 0.009 to 0.029]; p < 0.001), and it was not different from UIM representation among residents in plastic surgery (9.3% [386 of 4129]; p = 0.33), urology (9.7% [670 of 6877]; p = 0.80), dermatology (9.9% [679 of 6879]; p = 0.96), and diagnostic radiology (10% [2215 of 22,076]; p = 0.53). The proportion of orthopaedic faculty from UIM groups (4.7% [992 of 20,916]) was not different from UIM representation among faculty in otolaryngology (4.8% [553 of 11,413]; p = 0.68), neurology (5.0% [1533 of 30,871]; p = 0.25), pathology (4.9% [1129 of 23,206]; p = 0.55), and diagnostic radiology (4.9% [2418 of 49,775]; p = 0.51). Compared with other surgical and medical specialties with available data, orthopaedic surgery had the highest proportion of White applicants (62% [4613 of 7446]), residents (75% [14,571 of 19,476]), and faculty (75% [15,785 of 20,916]).
Orthopaedic applicant representation from UIM groups has increased over time and is similar to that of several surgical and medical specialties, suggesting relative success with efforts to recruit more students from UIM groups. However, the proportion of orthopaedic residents and UIM groups has not increased accordingly, and this is not because of a lack of applicants from UIM groups. In addition, UIM representation among orthopaedic faculty has not changed and may be partially explained by the lead time effect, but increased attrition among orthopaedic residents from UIM groups and racial bias likely also play a role. Further interventions and research into the potential difficulties faced by orthopaedic applicants, residents, and faculty from UIM groups are necessary to continue making progress.
A diverse physician workforce is better suited to address healthcare disparities and provide culturally competent patient care. Representation of orthopaedic applicants from UIM groups has improved over time, but further research and interventions are necessary to diversify orthopaedic surgery to ultimately provide better care for all orthopaedic patients.
Kalyanasundaram G
，Mener A
，DiCaprio MR
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ResearchGate
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