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Our replication of Deaton and Lubotsky's [(2003). Mortality, inequality and race in American cities and states. Social Science & Medicine, 56.] study “Mortality, Inequality and Race in American Cities and States" identifies a coding error in the econometric analysis in the original paper. Correcting the error changes the basic results of the paper with respect to inequality and mortality in a relevant and substantive way. We also propose an alternative interpretation of the other main result of the paper regarding racial composition and mortality. [Copyright &y& Elsevier]

Empirical evidence points to a persistent Black-White racial gap in police-caused homicides. Some scholarship treats the gap as denoting criminal justice exposure either in terms of involvement in crime or living in a high-crime context. By contrast, health scholarship typically points to the importance of racism including the attitudes, institutional practices, and overall structures that operate to privilege one group over another. Still, given the demographics of US society, the Black-White racial contrast overlooks the 25% of Americans who are neither Black nor White: Native Americans, Latinos, and Asians. The question of how the groups should be organized vis-a-vis the current Black-White model and theories arises. An answer is not straightforward. There is a rank-ordering to the groups' mortality rates as well as an exponential increase in the number of possible comparisons. In this paper we systematically review the literature on race and police-caused homicide with a particular focus on studies that attempt to move beyond the Black-White model. We find that studies on race and police-caused homicide either make no comparison between the groups, or, alternatively, use a White-non-White, a Black-non-Black, and/or a Black-Native American-Latino vs. White-Asian comparison. We use data on group-specific mortality rates to examine the strengths and limits of each of these practices. The limits are the selection of counterfactual gaps, the selection of smaller gaps, and/or the omission of larger gaps. To address these limits, we propose that a Black-Native American vs. Latino-White-Asian model best captures the higher and lower mortality rates in police-caused homicide data. • Mortality rates from police-caused homicide vary by race and ethnicity. • The Black group has the highest rate followed by the Native American, Latino, White and Asian groups. • The literature makes one of several contrasts between these groups. • These are White-non-White; Black-non-Black, or Black-Native American-Latino vs. White-Asian. • Black-Native American vs. Latino-White-Asian contrast best reflects the groups' mortality rates. [ABSTRACT FROM AUTHOR]

All individuals are subject to multiple risk factors for mortality. In this paper, we consider the nature of interactions between certain major sociodemographic and behavioral risk factors associated with all-cause mortality in the United States. We develop the formal logic pertaining to two forms of interaction between risk factors, additive and multiplicative relations. We then consider the general circumstances in which additive or multiplicative relations might be expected. We argue that expectations about interactions among socio-demographic variables, and their relation to behavioral variables, have been stated in terms of additivity. However, the statistical models typically used to estimate the relation between risk factors and mortality assume that risk factors act multiplicatively. We examine empirically the nature of interactions among five major risk factors associated with all-cause mortality: smoking, obesity, race, sex, and educational attainment. Data were drawn from the cross-sectional NHANES III (1988–1994) and NHANES 1999–2010 surveys, linked to death records through December 31, 2011. Our analytic sample comprised 35,604 respondents and 5369 deaths. We find that obesity is additive with each of the remaining four variables. We speculate that its additivity is a reflection of the fact that obese status is generally achieved later in life. For all pairings of socio-demographic variables, risks are multiplicative. For survival chances, it is much more dangerous to be poorly educated if you are black or if you are male. And it is much riskier to be a male if you are black. These traits, established at birth or during childhood, literally result in deadly combinations. We conclude that the identification of interactions among risk factors can cast valuable light on the nature of the process being studied. It also has public health implications by identifying especially vulnerable groups and by properly identifying the proportion of deaths attributable to a risk factor. [ABSTRACT FROM AUTHOR]

This paper examines the association between US county occupational structure, services availability, prevalence of risk factors, and coronary mortality rates by sex and race, for 1984–1998. The 3137 US counties were classified into five occupational structure categories; counties with the lowest percentages of the labor force in managerial, professional, and technical occupations were classified in category I (5–16%), counties with the highest percentages were in category V (32–59%). Directly age-adjusted coronary heart disease (CHD) mortality rates, for aged 35–64 years, (from vital statistics and Census data), per-capita services (County Business Patterns), and the prevalence of CHD risk factors (Behavioral Risk Factor Surveillance Surveys data) were calculated for each occupational structure category. CHD mortality rates and the prevalence of risk factors were inversely monotonically associated with occupational structure categories for white men and women but not among black men and women. Numbers of producer services for banking, business credit, overall business services and personnel/employment services were 2–12 times greater in category V versus I counties. Consumer services such as fruit/vegetable markets, fitness facilities, doctor offices and social services were 1.6–3 times greater in category V versus I counties. Residential racial segregation scores remained high in most areas despite declines during 1980–1990; occupational segregation by race and gender were shown indicating continued institutional racism. An ecological model for conceptualizing communities and health and the overall influence of state and national occupational structure is discussed; intervention strategies such as decreased wage disparities and ‘living wage’ standards and development is discussed. [Copyright &y& Elsevier]

This paper explores the idea that in societies that experience racial tension, increasing racial heterogeneity will be associated with poorer health outcomes, and this effect will be observable in the health of both the minority and the majority group. Here, the association between mortality and racial homogeneity in the United States is examined. The level of racial homogeneity, indexed by the proportion of blacks in each state of the 50 states in the US, was examined in relation to all-cause mortality, adjusted for age and disaggregated by race and sex. The level of poverty in each state was controlled for in ordinary least squares regression models. The level of racial homogeneity was significantly associated with age adjusted mortality rates for both blacks and whites, accounting for around 30% of the variance in mortality rates in the total population and the white population. Every 1% increase in the percentage of the state population who were black was associated with an increase in the total mortality rate of 5.06 per 100,000 and an increase in the white mortality rate of 3.58 per 100,000. Based on the data, this suggests, for example, that racial heterogeneity in Mississippi accounts for around 14% of the white mortality rate and in New York and Delaware it accounts for around 7%. These results appear to support the social cohesion thesis that in societies that are intolerant, mortality rates will increase as the proportion of racial or ethnic minorities increase in population. Limitations and explanations for the findings are discussed. [Copyright &y& Elsevier]