US racial-ethnic mortality gap adjusted for population structure

Abstract

Background U.S. racial/ethnic mortality disparities are well-documented and central to debates on social inequalities in health. Standard measures, like life expectancy or years of life lost, are based on synthetic populations and do not account for the real underlying populations experiencing the inequalities. Methods We analyze U.S. mortality disparities comparing Asian Americans, Blacks, Hispanics, and Native Americans/Alaska Natives to Whites using 2019 CDC and NCHS data. We develop a novel approach that estimates the mortality Gap, Adjusted for Population structure (GAP) by accounting for real-population exposures. GAP is tailored for analyses where age structures are a fundamental component, not merely a confounder. We highlight the magnitude of inequalities by comparing GAP against standard metrics’ estimates of loss of life due to leading causes of death. Results Based on GAP, Black and Native American mortality disadvantage is as deadly or deadlier than circulatory diseases (U.S. top cause of death); and is overall 72% (Men: 47%, Women: 98% women) and 65% (Men: 45%, Women: 92%) larger than life-expectancy measured disadvantage. Asian Americans and Hispanics have, according to GAP, a mortality advantage over Whites that is over three (Men: 176% , Women: 283%) and two times (Men: 123%, Women: 190%) larger than that based on life expectancy, respectively. Conclusions Mortality inequalities based on standard metrics’ synthetic populations can differ markedly from GAP estimates. We demonstrate that standard metrics underestimate racial/ethnic disparities through disregarding actual population age structures. For health policy, exposure-corrected inequalities such as GAP may provide a more reasonable signal on where to allocate scarce resources.