Using nationally representative data on US adults, we examined all-cause and cause-specific mortality disparities by race/ethnicity, mediation through key factors and moderation by age (20–49 vs. 50+), sex and poverty status. Among key findings, age, sex and poverty income ratio-adjusted hazard rates were higher among NHBs vs. NHWs. Within the above-poverty young men stratum where this association was the strongest, the socio-demographic-adjusted HR = 2.59, p < 0.001 was only partially attenuated by SES and other factors (full model HR = 2.08, p = 0.003). Income, education, diet quality, allostatic load and self-rated health, were among key mediators explaining NHB vs. NHW disparity in mortality. The Hispanic paradox was observed consistently among women above poverty (young and old). NHBs had higher CVD-related mortality risk compared to NHW which was explained by factors beyond SES. Those factors did not explain excess risk among NHBs for neoplasm-related death (fully adjusted HR = 1.41, 95 % CI: 1.02–2.75, p = 0.044). Moreover, those factors explained the lower risk of neoplasm-related death among MAs compared to NHW, while CVD-related mortality risk became lower among MAs compared to NHWs upon multivariate adjustment.
Race disparities in all-cause and cause-specific mortality rates, including death from cardiovascular disease and cancer, among U.S. adults have been previously reported, whereby Blacks or African Americans experienced consistently higher mortality rates compared to Whites [1, 24–26]. Several mediating and moderating factors have been examined in an attempt to explain these race disparities, including the moderating effects of gender, [27] age [4, 28, 29] – described as “Black-White mortality crossover” – and obesity, [30] the mediating [24, 29, 31–33] or moderating effects [4, 11, 25, 34, 35] of social factors, including poverty, culture and social injustice, [24] socioeconomic position, [25] socioeconomic status, [32, 35] social class, [36] education, [4] income, [4, 33, 34, 36] perceived stress, [31] health behaviors [31, 32] and health insurance [32]. Previous studies that examined these mediating and moderating effects were based on surveillance or large cohort data, including vital statistics, [1, 26] the National Health Interview Study, [28, 31, 36] the National Cancer Institute’s Surveillance, Epidemiology, and End Results program, [37] the Southern Community Cohort Study, [30, 35] the Health and Retirement Study, [32] the Multiple Risk Factor Intervention Trial, [33] the Americans’ Changing Lives Study [29].
A consistent finding from previous studies is that socioeconomic factors can moderate the effect of race on risk of death [4, 11, 25]. In addition, socio-economic status and other factors can act in mediating racial disparities in all-cause mortality [31, 32]. In a recent study, Krueger and colleagues used 1990 National Health Interview data involving 38,891 US adults and found distinct mediating effects of socioeconomic status, smoking status, physical activity, perceived stress, sleep duration and alcohol consumption on the relationship between race and all-cause mortality [31]. Similarly, analysis of the 1992–1998 Health and Retirement Study found distinct mediating effects of socioeconomic status, health behaviors and health insurance as mediators of the race disparities in all-cause mortality rates [32].
We find that NHBs had a higher rate of CVD mortality compared to NHWs, which is in accord with previous investigations [25, 33]. Our findings also suggest that by factors beyond SES mediated this association. Other variables may be important in explaining the higher CVD mortality in NHBs. Jones-Webb et al. found that neighborhood socioeconomic status moderated associations between race and CVD mortality among older men; older NHBs living in impoverished neighborhoods had a higher rate of CVD mortality, compared to older NHWs living in similar conditions [25]. Unsurprisingly, increased prevalence of CVD risk factors in NHBs may explain the higher prevalence of CVD mortality in this group [33].
Neoplasm-related death rates among NHB have remained high or have increased over time in certain instances [38]. Racial/Ethnic differences in neoplasm-related mortality can result from a combination of factors including smoking, nutrition, access to preventive, diagnostic, therapeutic, screening services and aggressiveness of treatment [38]. Modifying those factors could potentially prevent over half of cancer deaths and eliminate most racial/ethnic disparities [38]. Specifically, racial differences in breast cancer survival prevailed even after controlling for disease stage and known tumor characteristics, reflecting the potential mediating effects of social determinants beyond the biological, genetic and environmental factors, including the barriers of poverty (e.g. lack of a primary care physician, geographical access to care, competing survival priorities, burden of comorbidities, health insurance status, lack of information and knowledge, risk-promoting lifestyles and provider/system-level factors), culture (spirituality, perceived susceptibility to breast cancer, cultural beliefs and attitudes, and medical mistrust) and social injustice (racial prejudice and injustice) [24]. Menashe et al. indicated that the rate of decline in breast cancer mortality was slower among NH black women compared to White women, while age-specific incidence rate in black women was lower among blacks. Thus, the widening disparity in breast cancer mortality could not be explained by a higher incidence rate between 1990 and 2004 [37]. Thorpe et. al. showed that there was about 70 % excess risk of cancer mortality among Blacks compared to Whites, with socio-economic status, health insurance, psychosocial factors, behavioral factors and self-rated health accounting for 30 %, 18 %, 1 %, 17 % and 8 % of this excess risk [12]. Our study indicated that there was a 41 % excess risk of neoplasm-related death among NHBs compared to NHWs, which were not explained by SES, lifestyle or health-related factors.
In terms of diabetes-related mortality, studies have suggested that NHB have more than double the risk compared to NHW [12]. Using national death files and census data, for the 50 most populous US cities, that age-adjusted rate ratios of mortality from diabetes were higher in NHB compared to NHW in 39 of 41 cities, ranging from 1.57 (95 % CI: 1.33–1.86) in Baltimore to 3.78 (95 % CI: 2.84–5.02) in Washington, DC. Poverty alone explained 58.5 % of the NHB/NHW disparity in diabetes-related mortality and segregation explained 72.6 % of the disparity. However, those mediating effects of poverty and segregation varied widely across US cities [39]. Between 1994 and 2001, the annual rate of newly diagnosed elderly individuals with diabetes increased by 36.9 %, overall with Hispanics having the greatest increase at 55 % [40]. Our study indicated that MA had indeed a greater share of deaths attributed to diabetes compared to NHWs.
The Hispanic paradox, a consistently observed phenomenon, [9] occurs when mortality rates, specifically cardiovascular [6] and smoking-related mortality [5] among US Hispanics is similar or lower to NHWs’ rates, despite lower SES among Hispanics. Hunt et al. reported the age and sex-adjusted HR for all-cause mortality of US-born MAs vs. NHWs as 1.66 (95 % CI 1.15–2.40), while Mexico-born MAs vs. NHWs as 1.14 (95 % CI 0.63–2.06), [41] suggesting that “acculturation” in young MA may be a multifactorial covariate that is inadequately represented in large study sets such as NHANES III, which is sampling for a “paradoxically healthy” new immigrant population, rather than a truly representative sample of young Mexicans as a whole [42]. Generally, mortality rate differences between MA and NHW are greater among older age groups. Suggested mechanisms behind this paradox include less acculturation to the US resulting in better health, healthy migrant bias, and death records’ misreporting of ethnicity or missing records upon return to country of origin (“salmon bias”) [43]. Previous studies show that diet was healthier and smoking level was lower among Hispanics compared to non-Hispanics, which may partly explain their lower mortality rates [7, 8]. These findings are not universal, with studies in San Antonio [44, 45] and Corpus Christi [46] refuting the apparent paradox. Our findings support the Hispanic paradox mainly for cardiovascular mortality, which concurs with a recent meta-analysis [6]. It has been suggested that increased fruit and legume consumption among this group may have a protective effect [6]. Country of birth may be an important consideration; data from the San Antonio Heart Study show that diabetic MAs born in the US have higher rates of CVD mortality, compared to NHWs, while risk for CVD mortality was similar between diabetic US-born MAs and NHWs [41]. The findings also support the perplexing disassociation of several common risk factors with cardiovascular disease mortality in US Hispanic populations. MAs in our study had both lower income and a lower mean education years, when compared with NHWs. They also had a higher waist-hip-ratio and glycated hemoglobin levels, as well as lower access to health insurance. In contrast, MA were less likely to smoke and had a comparable diet quality to NHW. Smoking behavior differentials have accounted for >50 % life expectancy variability between Hispanics and non-Hispanics at age 50y [7]. Acculturation may influence our findings as only 51 % of MA in our sample were US-born.
Our study has several strengths. First, to our knowledge, it among few nationally representative studies testing associations between race/ethnicity and all-cause and cause-specific mortality in the adult US population by systematically examining effects within sex, age and poverty status and investigating potential mediators for all-cause and cause-specific mortality. Second, its large sample size allowed testing associations with mortality from homogeneous groups of causes. Competing risk, selection bias, missing data, unequal probability of sampling and design complexity were all addressed in our analyses. Some limitations include residual confounding, measurement error in covariates, particularly self-reported potential mediators (e.g. co-morbid conditions), and misclassification error of underlying and contributing causes of death.