Distinct age and self-rated health crossover mortality effects for African Americans: Evidence from a national cohort study
Introduction
Numerous reports of all-cause mortality in the United States have documented a persistent excess mortality rate and shorter life expectancy for African Americans compared to Whites (Heron, 2013, Hoyert and Xu, 2012, Ng-Mak et al., 1999). This excess mortality of African Americans is believed to be an important indicator of persistent health disparities (Williams, 2012), and its impact on the population could have far-reaching consequences including socioeconomic and political effects that might serve to perpetuate those disparities (Rodriguez et al., 2015) and a lack of sufficient aging-related services being developed for African American and other disadvantaged populations (Markides and Machalek, 1984). For all of these reasons, it is vital that we better understand the root causes of this excess mortality experienced by African Americans in comparison to Whites and design programs and policies that seek to reduce this important disparity.
Detailed statistical analyses often further indicate that the excess mortality of African Americans, while being pervasive, is not consistently observed across all stages of the lifespan. At younger ages, African Americans typically have proportionally much higher mortality rates than Whites, but this imbalance clearly diminishes with increasing age. Multiple studies have shown that the excess mortality of African Americans tends to disappear altogether for older adults, when, at approximately 75–80 years of age, the race-specific mortality rates often reach a point where elderly African Americans have lower mortality rates than age-matched Whites (Johnson, 2000, Manton et al., 1979, Markides and Machalek, 1984, Preston and Elo, 2006, Wing et al., 1985, Yao and Robert, 2011). This phenomenon, frequently referred to as the race “crossover” mortality effect, is equivalent to a statistical interaction effect such that advancing age is a stronger predictor of mortality for Whites than it is for African Americans.
A frequent interpretation of the age-based crossover mortality effect for African Americans is that it is due to a “selective survival” effect. This hypothesis maintains that, because of the higher mortality rates of younger African Americans compared to younger Whites, those in the African American population with poorer health are more likely die young, leading to a greater survival selection process and a comparatively healthier group of African Americans who survive into old age (Manton et al., 1979, Markides and Machalek, 1984, Zajacova and Burgard, 2013). This is often presented as a health-related hypothesis, although selective survival effects can also emerge for other reasons (Horiuchi and Wilmoth, 1998), including different rates of physiological aging and environmental factors (Manton et al., 1979). In addition, because each organism in a population dies only once, any cause of death not directly related to health or a biological mechanism, such as an accident or an act of violence, for example, removes the opportunity for that organism to die later from another cause, including an age-related disease condition. If this occurs frequently enough within any specific subpopulation, then this phenomenon would attenuate the significance of both age- and health-related factors as predictors of mortality for that subpopulation.
Epidemiological research examining the predictors of mortality have identified other factors besides age that may also have differential impacts on mortality across minority subgroups. One such predictor is the relatively simple rating of one's overall health as excellent, very good, good, fair, or poor. This simple self-rated health (SRH) measure is a surprisingly strong and robust predictor of mortality even after controlling for many medical, behavioral, and demographic risk factors (Benyamini et al., 2003, Benyamini and Idler, 1999, DeSalvo et al., 2006, Lima-Costa et al., 2012a, McGee et al., 1999). It is sometimes considered to be a remarkably sensitive overall summary indicator of one's health-related risk for subsequent mortality (Idler and Benyamini, 1997, Jylha, 2009). Interestingly, many studies have found minority groups to report poorer SRH in comparison to Whites even after adjusting for relevant sociodemographic, health, and physical performance covariates (Boardman, 2004, Borrell and Crawford, 2006, Ferraro, 1993, Ren and Amick, 1996, Skarupski et al., 2007, Spencer et al., 2009).
Similar to research on the age-related crossover mortality effect, some investigators have sought to determine whether the SRH–mortality association is stronger or weaker in certain demographic subgroups compared to a referent group. Data from the national Health and Retirement Study, for example, have shown that the SRH–mortality association is much weaker for African Americans than it is for Whites (Lee et al., 2007). In that analysis, poor SRH, in comparison to excellent SRH, was much more strongly linked with subsequent mortality for Whites (odds ratio (OR) = 10.4) than for African Americans (OR = 2.9). Similar findings of attenuated SRH–mortality associations have been found for Hispanics compared to Whites (McGee et al., 1999) and for those with less education or income compared to their respective reference groups (Dowd and Zajacova, 2007, Lima-Costa et al., 2012b). Socioeconomic differences, however, do not appear to explain the attenuated SRH–mortality associations that have been found for African Americans (Ferraro and Kelley-Moore, 2001, Lee et al., 2007).
It is interesting that the diminished SRH–mortality association for African Americans compared to Whites has a pattern that is quite similar to the age-based “crossover” mortality effect for African Americans. In both instances, two straightforward and replicable risk factors for mortality–poorer SRH and advancing age–show weaker associations with subsequent mortality for African Americans than for Whites. Surprisingly, in spite of the numerous studies on both age- or SRH-based mortality crossover effects for African Americans, no previous study has, to our knowledge, examined both of these possible crossover effects simultaneously. Furthermore, if the age-based mortality crossover effect is due to a health-related selective survival effect, then SRH effects in an age-based model should reduce some of the diminished age-related mortality differences between African Americans and Whites. That is, it is possible that the age-based race crossover mortality effect for African Americans is confounded, or overlapping, with a SRH-related race crossover mortality effect, and such a finding would support the health-related selective survival effect as an explanation for the age-based crossover effect. A simultaneous analysis would, therefore, determine whether these effects are overlapping or if they reflect mostly distinct phenomena due to different and independent mechanisms.
To advance understanding of these effects and inform future investigation into the root causes of race disparities in mortality, we sought to examine both age-based and SRH-related race crossover mortality effects in the national REasons for Geographic and Racial Differences in Stroke (REGARDS) study. This study enrolled a large and well-characterized national sample of African Americans and Whites who were 45 years of age or older at the time of enrollment (Howard et al., 2005) and it provides a unique opportunity to further examine African American vs. White differences in the predictors of all-cause mortality. Using rigorously collected mortality data from the REGARDS study, we conducted an independent examination of potential SRH- and age-crossover mortality effects for the two race groups enrolled in this national cohort study. Two hypotheses were advanced based on the proposition that the age-based crossover mortality effect for African Americans is due to a health-related selective survival effect. First, this selective survival effect should result in a finding that race-based differences in SRH are diminished for older participants compared to younger participants. Second, adding health history covariates, SRH, and SRH*age interaction effects to survival models should diminish the significance of the race*age interaction effect that reflects the age-based crossover mortality effect for African Americans.
Section snippets
Participants
Participants in the REGARDS study were randomly sampled from a commercially available nationwide list purchased through Genesys, Incorporated (Howard et al., 2005). Exclusion criteria included age less than 45, race other than African American or White, previous diagnosis of cancer requiring chemotherapy, or residence in or on a waiting list for a nursing home. The goals of the REGARDS study are to examine the reasons why African Americans and residents of southern states of the United States
Descriptive information
Table 1 depicts summary data by race group for the REGARDS participants included in the present analyses. Of the 29,617 participants included in the analyses, 4881 (16.5%) died at some point during the follow-up period. Unadjusted differences by race were observed on all variables in Table 1 including mortality as determined by chi-square tests of association (all p values < 0.001).
Race differences in self-rated health
Unadjusted differences in SRH as a function of race are described in Table 1 and illustrated graphically in Fig. 1
Discussion
The present analyses provide a more comprehensive and integrated picture of the multiple associations that have been reported previously among age, SRH, race, and all-cause mortality. The findings for age and SRH in relation to subsequent mortality were remarkably similar, with both predictors showing significant, monotonic relationships with mortality that were, nonetheless, significantly attenuated for African Americans compared to Whites. Our paper contributes to the literature by further
Acknowledgments
This work was supported by the National Institute of Neurological Disorders and Stroke, National Institutes of Health, and Department of Health and Human Service (Cooperative Agreement U01 NS041588); the National Institute on Aging (Grant R01 AG039588 to V. J. H. and Grant K07AG043588 to J. L. L.); and the National Institute of Diabetes and Digestive and Kidney Diseases (Grant K23DK097184 to D. C. C. and Grant P30DK056336 to J. L. L). The content is solely the responsibility of the authors and
References (44)
- et al.
Two views of self-rated general health status
Soc. Sci. Med.
(2003) Health pessimism among black and white adults: the role of interpersonal and institutional maltreatment
Soc. Sci. Med.
(2004)- et al.
Comparability of national death index plus and standard procedures for determining causes of death in epidemiologic studies
Ann. Epidemiol.
(2001) - et al.
Estimates of prospective change in self-rated health in older people were biased owing to potential recalibration response shift
J. Clin. Epidemiol.
(2012) What is self-rated health and why does it predict mortality? Towards a unified conceptual model
Soc. Sci. Med.
(2009)- et al.
The influence of socioeconomic status on the predictive power of self-rated health for 6-year mortality in English and Brazilian older adults: the ELSA and Bambui cohort studies
Ann. Epidemiol.
(2012) - et al.
Selective survival, aging and society
Arch. Gerontol. Geriatr.
(1984) - et al.
Black lives matter: differential mortality and the racial composition of the U.S. electorate, 1970–2004
Soc. Sci. Med.
(2015) Survival Analysis Using SAS: a Practical Guide
(2010)- et al.
Gender differences in the self-rated health-mortality association: is it poor self-rated health that predicts mortality or excellent self-rated health that predicts survival?
Gerontologist
(2003)
Community studies reporting association between self-rated health and mortality: additional studies, 1995–1998
Res. Aging
Social networks, host-resistance, and mortality: a nine-year follow-up study of Alameda County residents
Am. J. Epidemiol.
Race, ethnicity, and self-rated health status in the behavioral risk factor surveillance system survey
Hisp. J. Behav. Sci.
Mortality prediction with a single general self-rated health question. A meta-analysis
J. Gen. Intern. Med.
Does the predictive power of self-rated health for subsequent mortality risk vary by socioeconomic status in the US?
Int. J. Epidemiol.
Are Black older adults health-pessimistic?
J. Health Soc. Behav.
Self-rated health and mortality among black and white adults: examining the dynamic evaluation thesis
J. Gerontol. Ser. B Psychol. Sci. Soc. Sci.
Agreement on cause of death between proxies, death certificate, and clinician adjudicators in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study
Am. J. Epidemiol.
Deaths: leading causes for 2010, Natl. Vital Stat. Rep.
Deceleration in the age pattern of mortality at older ages
Demography
Evaluation of social status as a contributing factor to the stroke belt region of the United States
Stroke
Traditional risk factors as the underlying cause of racial disparities in stroke: lessons from the half-full (empty?) glass
Stroke
Cited by (12)
Birth in the U.S. Plantation South and Racial Differences in all-cause mortality in later life
2023, Social Science and MedicineSelf-Rated Health as a Predictor of Mortality in Older Adults: A Systematic Review
2023, International Journal of Environmental Research and Public HealthTransitions to Family Caregiving and Latent Variables of Systemic Inflammation Over Time
2023, Research on AgingHuman Behavior in the Social Environment: Perspectives on Development and the Life Course, Sixth Edition
2022, Human Behavior in the Social Environment: Perspectives on Development and the Life Course, Sixth EditionLong-Term Effects of Cognitive Training on All-Cause Mortality in US Older Adults
2022, Journal of Aging and HealthSelf-rated health and pain problems in mothers of healthy children or children requiring outpatient observation or hospitalisation: A pilot cross-sectional study
2021, International Journal of Environmental Research and Public Health