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US Racial-Ethnic Mortality Gap Adjusted for Population Structure.

Héctor Pifarré I Arolas1,2, Enrique Acosta3, Christian Dudel3,4

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Area of Science:

  • Public Health
  • Health Disparities
  • Biostatistics

Background:

  • Racial-ethnic mortality disparities in the US are significant and widely studied.
  • Traditional metrics like life expectancy use synthetic populations, not reflecting real-world health inequalities.
  • Existing measures may not fully capture the extent of health disparities across different racial and ethnic groups.

Purpose of the Study:

  • To analyze US mortality disparities among Asian Americans, Blacks, Hispanics, and Native Americans/Alaska Natives compared to Whites.
  • To introduce and apply a novel method for estimating mortality gaps adjusted for population structure, using real population exposures.
  • To compare the findings from this new metric with standard metrics to highlight differences in perceived disparities.

Main Methods:

  • Utilized 2019 data from the Centers for Disease Control and Prevention (CDC) and National Center for Health Statistics (NCHS).
  • Employed a novel approach to calculate a population structure-adjusted mortality gap, accounting for age structures and real population exposures.
  • Compared the magnitude of these adjusted mortality gaps with standard metrics like life expectancy and years of life lost.

Main Results:

  • The population structure-adjusted mortality gap reveals Black and Native American mortality disadvantages exceeding those from circulatory diseases.
  • Blacks experience a 72% mortality disadvantage (men: 47%, women: 98%), and Native Americans a 65% disadvantage (men: 45%, women: 92%).
  • Asian Americans show an estimated advantage 3 times larger (men: 176%, women: 283%), and Hispanics 2 times larger (men: 123%, women: 190%) than life expectancy measures suggest.

Conclusions:

  • Standard metrics for mortality inequalities can significantly differ from population structure-adjusted estimates.
  • Disregarding actual population age structures leads standard metrics to underestimate racial-ethnic disparities.
  • Exposure-corrected measures of inequality may offer a more accurate basis for health policy and resource allocation.