Eight Americas: Investigating Mortality Disparities across Races, Counties, and Race-Counties in the United States

Abstract

BackgroundThe gap between the highest and lowest life expectancies for race-county combinations in the United States is over 35 y. We divided the race-county combinations of the US population into eight distinct groups, referred to as the “eight Americas,” to explore the causes of the disparities that can inform specific public health intervention policies and programs.Methods and FindingsThe eight Americas were defined based on race, location of the county of residence, population density, race-specific county-level per capita income, and cumulative homicide rate. Data sources for population and mortality figures were the Bureau of the Census and the National Center for Health Statistics. We estimated life expectancy, the risk of mortality from specific diseases, health insurance, and health-care utilization for the eight Americas. The life expectancy gap between the 3.4 million high-risk urban black males and the 5.6 million Asian females was 20.7 y in 2001. Within the sexes, the life expectancy gap between the best-off and the worst-off groups was 15.4 y for males (Asians versus high-risk urban blacks) and 12.8 y for females (Asians versus low-income southern rural blacks). Mortality disparities among the eight Americas were largest for young (15–44 y) and middle-aged (45–59 y) adults, especially for men. The disparities were caused primarily by a number of chronic diseases and injuries with well-established risk factors. Between 1982 and 2001, the ordering of life expectancy among the eight Americas and the absolute difference between the advantaged and disadvantaged groups remained largely unchanged. Self-reported health plan coverage was lowest for western Native Americans and low-income southern rural blacks. Crude self-reported health-care utilization, however, was slightly higher for the more disadvantaged populations.ConclusionsDisparities in mortality across the eight Americas, each consisting of millions or tens of millions of Americans, are enormous by all international standards. The observed disparities in life expectancy cannot be explained by race, income, or basic health-care access and utilization alone. Because policies aimed at reducing fundamental socioeconomic inequalities are currently practically absent in the US, health disparities will have to be at least partly addressed through public health strategies that reduce risk factors for chronic diseases and injuries.

Social Determinants of Risk and Outcomes for Cardiovascular Disease

“…16 For example, in the Eight Americas Study, the authors identified 7 distinct groups within the United States based on race, geographic location, and income and found significant differences in life expectancy. 34 These groups are, in order of decreasing life expectancy, Asian Americans (84.9 years), whites living in rural Northern Plains/Dakotas, low-income whites in Appalachia and the Mississippi Valley, western Native Americans, middle-income blacks, southern rural blacks, and blacks in poor urban areas (71.1 years), representing a 14-year difference between the highest and lowest group. CVD was the greatest source of differences in life expectancy.…”

“…First, socioeconomically disadvantaged populations suffer from a great burden of Framingham risk factors. 34,[268][269][270][271][272][273][274] This is an important consideration because it may be possible to use clinical 109 and public health interventions 92 to reduce this burden, thereby narrowing health disparities. Second, social and economic stresses lead to a biological wear and tear, or allostatic stress response, [275][276][277][278][279][280] involving a number of pathways, including stimulation of stress hormones, [280][281][282] inflammation, 283 endothelial dysfunction, thrombosis, vascular hyperreactivity, 270,274,[284][285][286][287] and metabolic disturbances.…”

A neighbourhood level mortality classification of England and Wales, 2006–2009

“…An area classification allows a move away from one-dimensional approaches to a multidimensional understanding of the health of areas through summarising the main patterns across a range of variables. Knowing and understanding how causes of death vary and coassociate within an area is important for the effective targeting of policies, resources and location of services (Murray et al 2006). This paper details the construction of an area classification of mortality patterns in England andWales (2006-2009).…”

Disentangling Race and Social Context in Understanding Disparities in Chronic Conditions among Men

“…9,26,27 In the EHDIC-SWB sample, African-American and whites had similar access to health care resources which has been shown to produce similar health outcomes. 17,28 Furthermore, Thorpe and colleagues demonstrated that African-American men in EHDIC-SWB engaged in preventive health screenings more than white men.…”