Racial gaps
How does the racial gap compound with sex, and who sits at the very bottom?
Life expectancy in 2023 ranged from 85.2 years for Asian Americans to 70.1 for American Indian and Alaska Native Americans, a 15.1-year spread. The uninsured rate for Hispanic adults was nearly four times the rate for Asian adults.
The problem
Racial inequity is embedded across the hospital and health-system landscape through coverage, access, mortality, geography, and the cumulative effects of social and clinical risk. Race-only averages can make the problem look simpler than it is, because the greatest harm often appears where race intersects with sex, place, income, and care access.
The recommendation
Make equity management population-specific and operational, not descriptive. The recommended model is to identify compounded-risk populations, link disparities to coverage and access levers, and require hospital, payer, and public-health interventions to show whether the gap is narrowing for the groups at the bottom of the distribution.
The lifespan gap
How wide the racial gap in life expectancy is, whether it is closing, and how it compounds with sex to a 20-year extreme.
Life expectancy by race and ethnicity, 2023
Longer bar is more years of life. The dashed line marks the White value, and the top-to-bottom spread is 15.1 years.
Read it this way Each bar is one racial or ethnic group's average life expectancy in 2023, ranked highest to lowest, so you can see where each group falls relative to the White reference line. The chart shows the size of the gap, 15.1 years top to bottom, but not why it exists, since the underlying causes are not part of this dataset. Use this chart to identify which population carries the disparity and which operational lever, coverage, access, affordability, or safety, should be connected to the equity recommendation.
⊞ data table⬇ CSV
| Race and ethnicity | Life expectancy (yrs) |
|---|---|
| Asian | 85.2 |
| Hispanic | 81.3 |
| White | 78.4 |
| Black | 74 |
| AIAN | 70.1 |
CDC NCHS, United States Life Tables, 2023 · 2023 · source
Life expectancy by race and sex, 2023
Two bars per group, women and men. The widest human gap here, Asian women to AIAN men, is 20.4 years.
Read it this way Compare the two bars within a group to see the sex gap for that race, and compare across groups to see the racial gap; the widest combination is Asian women at 87.1 years against AIAN men at 66.7. This chart cannot separate how much of that 20.4-year spread comes from race versus from sex. Use this chart to identify which population carries the disparity and which operational lever, coverage, access, affordability, or safety, should be connected to the equity recommendation.
⊞ data table⬇ CSV
| Race and ethnicity | Women LE (yrs) | Men LE (yrs) |
|---|---|---|
| Asian | 87.1 | 83.2 |
| Hispanic | 84 | 78.5 |
| White | 80.9 | 76 |
| Black | 77.6 | 70.3 |
| AIAN | 73.5 | 66.7 |
CDC NCHS, United States Life Tables, 2023 · 2023 · source
Black and white life expectancy, 2019 to 2023
Two lines that recovered from the 2020 trough but never meet. The vertical distance between them is the gap.
Read it this way Both lines dropped in 2020 and have since recovered toward their 2019 levels, but the Black line stays below the White line in every year shown. The chart tracks each group's recovery path, not whether the gap between them is closing. Use this chart to identify which population carries the disparity and which operational lever, coverage, access, affordability, or safety, should be connected to the equity recommendation.
⊞ data table⬇ CSV
| Year | White LE (yrs) | Black LE (yrs) | Gap (yrs) |
|---|---|---|---|
| 2019 | 78.8 | 74.8 | 4 |
| 2020 | 77.4 | 71.5 | 5.9 |
| 2021 | 76.7 | 71.2 | 5.5 |
| 2022 | 77.5 | 72.8 | 4.7 |
| 2023 | 78.4 | 74 | 4.4 |
CDC NCHS, United States Life Tables · 2019 to 2023 · source
The Black-white gap itself, 2019 to 2023
One line for the gap alone. It widened to 5.9 years in 2020 and at 4.4 in 2023 is still above its 4.0 level in 2019.
Read it this way This single line isolates the Black-white gap itself: it widened to 5.9 years in 2020 and by 2023 had narrowed to 4.4, still above the 4.0-year gap recorded in 2019. Five data points are not enough on their own to call this a stable improving trend rather than pandemic-era volatility settling out. Use this chart to identify which population carries the disparity and which operational lever, coverage, access, affordability, or safety, should be connected to the equity recommendation.
⊞ data table⬇ CSV
| Year | Gap (yrs) |
|---|---|
| 2019 | 4 |
| 2020 | 5.9 |
| 2021 | 5.5 |
| 2022 | 4.7 |
| 2023 | 4.4 |
CDC NCHS, United States Life Tables · 2019 to 2023 · source
Death rates and the coverage lever
From the summary statistic to the age-adjusted death rates that drive it, and the coverage and affordability barriers whose hierarchy differs from the mortality one.
Age-adjusted death rate by race and sex, 2023
Deaths per 100,000, corrected for race misclassification. AIAN and Black men sit far above every other group.
Read it this way Bars are age-adjusted death rates per 100,000, corrected for race misclassification on death certificates, and AIAN and Black men sit far above every other group shown. Reading the bars tells you where each group's mortality rate stood in 2023, not what drives the difference between groups. Use this chart to identify which population carries the disparity and which operational lever, coverage, access, affordability, or safety, should be connected to the equity recommendation.
Caveat NCHS corrects for undercounting of Hispanic, AIAN, and Asian decedents on death certificates. Uncorrected rates would be lower, by about 3% for Hispanic and Asian and about 34% for AIAN.
⊞ data table⬇ CSV
| Race and ethnicity | Women deaths per 100k | Men deaths per 100k |
|---|---|---|
| AIAN | 920.3 | 1277.7 |
| Black | 753.6 | 1151.6 |
| White | 662.8 | 906.4 |
| Hispanic | 472.4 | 692.8 |
| Asian | 334.6 | 476.1 |
CDC NCHS, Mortality in the United States, 2023 (Data Brief 521) · 2023 · source
Death rate among men by race, 2022 vs 2023
Every group's rate fell from 2022 to 2023, but the highest-rate groups started far higher, so the gap persists. Women's rates fell in parallel and are in the table.
Read it this way Every racial group's male death rate fell from 2022 to 2023, but the groups that started highest, AIAN and Black, remain the highest after the decline. A shared year-over-year drop across all groups does not by itself mean the relative gap between them is shrinking. Use this chart to identify which population carries the disparity and which operational lever, coverage, access, affordability, or safety, should be connected to the equity recommendation.
Caveat Men are shown because their rates are higher and the AIAN and Black gap is starkest, but the same 2022-to-2023 decline holds for women. All four columns are in the table below.
⊞ data table⬇ CSV
| Race and ethnicity | Men 2022 | Men 2023 | Women 2022 | Women 2023 |
|---|---|---|---|---|
| AIAN | 1444.1 | 1277.7 | 1063.6 | 920.3 |
| Black | 1263.3 | 1151.6 | 813.2 | 753.6 |
| White | 971.9 | 906.4 | 691.9 | 662.8 |
| Hispanic | 774.2 | 692.8 | 512.9 | 472.4 |
| Asian | 522.2 | 476.1 | 354.9 | 334.6 |
CDC NCHS, Mortality in the United States, 2023 (Data Brief 521) · 2022 to 2023 · source
Uninsured rate by race and ethnicity, adults 18 to 64, 2023
Longer bar means a larger share had no coverage at the time of interview. Hispanic adults are uninsured at more than five times the Asian rate.
Read it this way Bar length shows the share of adults with no health coverage at the time of interview, and Hispanic adults are uninsured at more than five times the Asian rate, 24.8% versus 4.4%. This is a point-in-time snapshot for 2023, not a measure of how long any individual went without coverage. Use this chart to identify which population carries the disparity and which operational lever, coverage, access, affordability, or safety, should be connected to the equity recommendation.
⊞ data table⬇ CSV
| Race and ethnicity | Uninsured (%) |
|---|---|
| Hispanic | 24.8 |
| Black, non-Hispanic | 10.4 |
| White, non-Hispanic | 6.8 |
| Asian, non-Hispanic | 4.4 |
CDC NCHS, NHIS Health Insurance Coverage Early Release, 2023 · 2023 · source
Could not afford needed medical care by race and ethnicity, 2023
Share reporting a cost barrier to care. The hierarchy differs from both coverage and mortality, so no single lever explains the death gap.
Read it this way This bar order does not match either the uninsured-rate or mortality-rate rankings shown elsewhere on this page, which is the point: no single barrier accounts for the outcome gap on its own. The AIAN estimate of 9.5% carries a wide confidence interval of 5.1 to 15.9 percent, so it should be read as directional rather than precise. Use this chart to identify which population carries the disparity and which operational lever, coverage, access, affordability, or safety, should be connected to the equity recommendation.
Caveat The AIAN row includes respondents of any Hispanic origin because the non-Hispanic-only breakout was suppressed for small sample size, so it carries a wide confidence interval of 5.1 to 15.9 percent and should be read with caution.
⊞ data table⬇ CSV
| Race and ethnicity | Cost barrier to care (%) |
|---|---|
| AIAN (wide CI 5.1 to 15.9) | 9.5 |
| Hispanic or Latino | 8.7 |
| Black or African American, non-Hispanic | 8.2 |
| White, non-Hispanic | 6.2 |
| Asian, non-Hispanic | 3.9 |
Healthy People 2030 (AHS-04), reporting CDC NCHS NHIS estimates · 2023 · source
Geography
The same question, state by state and then county by county. Pick a state in the filter above to drill into its counties.
Population below poverty
County · direct countEach tile is a state. Pick a state in the Scope control above to drill into its counties.
CDC/ATSDR Social Vulnerability Index · 2022 · source
Why this matters
Because the ranking of racial groups differs across mortality, insurance coverage, and self-reported cost barriers, the gap cannot be pinned on one policy lever such as coverage alone. Structural factors appear to operate across multiple access points at once, and a tracking system built around a single metric will systematically miss where the largest gap for any given group actually sits.
Recommended actions
- Target enrollment and outreach resources at Hispanic adults, whose uninsured rate (24.8%) is the largest single coverage gap measured here.
- Direct mortality-focused interventions toward AIAN and Black communities, where age-adjusted death rates are highest.
- Monitor the Black-white life-expectancy gap year over year; it widened to 5.9 years in 2020 and has only partly retreated to 4.4 in 2023, still above the 4.0-year 2019 baseline.
- Make race-stratified reporting the default on every new access and outcome measure so gaps cannot be averaged into a single national figure.
- Pilot a combined coverage-cost-mortality dashboard by race in a few states to test whether tracking all three together changes how resources get allocated.
The recommendation
Therefore, make equity management population-specific and operational, not descriptive. The recommended model is to identify compounded-risk populations, link disparities to coverage and access levers, and require hospital, payer, and public-health interventions to show whether the gap is narrowing for the groups at the bottom of the distribution.
Demographic slice race. CDC NCHS/WONDER race-stratified; and Access's own race-sliced coverage data.
Sources
- United States Life Tables, 2023 (National Vital Statistics Reports, Vol. 74, No. 6) · 2025
- United States Life Tables, 2019 (National Vital Statistics Reports, Vol. 70, No. 19) · 2022
- Mortality in the United States, 2023 (NCHS Data Brief No. 521), age-adjusted death rates by race and sex · 2024
- Health Insurance Coverage: Early Release of Estimates From the National Health Interview Survey, 2023 · 2024
- Healthy People 2030 (AHS-04), can't get medical care when needed, by race and ethnicity, reporting NCHS NHIS estimates · 2025