The Relationship Between Cognition and Mortality Among Older Black and White Men in Advanced Cognitive Training for Independent and Vital Elderly

Abstract

Objective: To determine the association between baseline cognition and all-cause mortality among Black men and White men. Methods: Data were from 614 Black and White men aged ≥65 years at baseline in the Advanced Cognitive Training for Independent and Vital Elderly trial and their linked mortality information. Cox proportional hazards models were used to determine the association between baseline cognition (memory, reasoning, speed of processing, Mini Mental State Exam) and mortality risk over 20 years, adjusting for covariates. Results: Among White men, higher performance on the memory composite measure was associated with a decreased risk of all-cause mortality (HR: 0.93; 95% CI: 0.89–0.98), whereas the other cognitive measures were not associated with all-cause mortality risk. Among Black men, none of the cognitive measures was associated with all-cause mortality risk. Discussion: There is a need for future work to recruit and retain a larger sample of older Black men to better understand the cognition-mortality relationship.

Keywords

black men cognitive function mortality disparities

Introduction

The horrific health profile that has been portrayed for African American men has been largely ascribed to structural determinants of health—social and political mechanisms that shape social determinants of health that impact health outcomes (Solar & Irwin, 2010) (Crear-Perry et al., 2021), and consistent and constant heightened exposure to the deleterious effects of stressors—many yielding from racism across the life course (Griffith & Johnson, 2013; Hargrove & Brown, 2015; Thorpe & Archibald, 2019; Thorpe et al., 2019; Williams, 2003, 2015). For example, key impacts of residential segregation among African American men include a longer duration of exposure to living in despondent social and environmental conditions in neighborhoods, poor quality housing, and low resourced public schools relative to White men (Thorpe et al., 2013; Williams, 2003, 2015). These exposures are likely to influence the choices that African American men have across their life course as it relates to their health and cognition, thereby delaying mortality (Geronimus et al., 2006; Thorpe & Archibald, 2019; Thorpe et al., 2013, 2019).

There is a growing body of research that links cognitive performance to mortality among older adults (Batterham et al., 2012; Batty et al., 2016; Bosworth et al., 1999; Connors et al., 2015; Lv et al., 2019; Van Gelder et al., 2007). In general, those who perform worse on cognitive tasks have higher mortality risk in later life (Loureiro et al., 2020; Perna et al., 2015; Vassilaki et al., 2015). Because previous work examining cognition has largely focused on studies with a high proportion of older women or has examined sex-related differences in cognition, there has been modest attention examining cognitive performance only among older men. Yet there is a critical need to understand the association between cognitive function and mortality among Black men and White men specifically due to the differential burden of chronic disease morbidity that leads to mortality disparities (Sims et al., 2015). This need will likely continue over the next several years because of the aging population, increases in racial diversity in the US, and lagging life expectancy for Black men despite increases in life expectancy among Black men and White men (Bond & Herman, 2016; Sloan et al., 2010).

The objective of this study was to determine the association between baseline cognition and 20-year all-cause mortality among a sample of community-dwelling older Black men and older White men without dementia in the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) trial. This study extends the literature on the long-term influence of specific aspects of cognition on subsequent mortality disparities in Black and White men.

Methods

Sample

Advanced cognitive training for independent and vital elderly is a randomized, controlled trial that tests whether cognitive training can improve basic mental abilities and, subsequently, functional independence in older adults. Participants included in ACTIVE are aged 65 years and older and were cognitively and functionally healthy at baseline. At study inception in 1998, participants were randomized to one of three training groups (memory, inductive reasoning (or problem solving), and speed of processing) or a no-contact control group. The intervention training programs were implemented across 10 one-hour sessions over a period of 5–6 weeks. Follow-up assessments were conducted at post-test and 1, 2, 3, 5, and 10 years post-intervention. Additional details regarding the ACTIVE study design are described elsewhere (Ball et al., 2002; Jobe et al., 2001). The ACTIVE 20-Year Follow-up Study (2017–present; R01AG056486) linked ACTIVE baseline data to the National Death Index (NDI). As the current study aims to look specifically at differences between Black men and White men, men of other racial groups (i.e., Asian, Indian, biracial, and other) were excluded from the analytic sample (n = 46). The analytic sample for the current study includes 614 older Black men and older White men.

Measures

Mortality

Mortality status as of December 2019 and age of death were obtained through linkage of ACTIVE data to data from the NDI. Participants were linked via Social Security Number, name, date of birth, and state of residence to NDI records. Mortality information was also collected using other public sources such as LexisNexis, published obituaries, and ancestry.com. Participants were classified as deceased if they were successfully matched via personal identifiable information to an NDI record or another public source. Men (n = 16) whose personal identifiable information was unavailable were excluded from the analyses. Deaths for Black men and White men up to 20 years post-intervention were included in these analyses.

Cognition

The ACTIVE Study had multiple cognitive ability measures. Cognitive composites were used to represent three cognitive ability domains—memory, reasoning, and speed of processing—targeted by the ACTIVE interventions (Jobe et al., 2001). Composite scores were created for each domain of cognition using the average of the standardized scores for each test in that composite measure. The range of the composite scores is from 0 to 1 with lower scores reflecting poorer performance on the cognitive test.

Memory assessment focused on verbal episodic memory tasks and included the Hopkins Verbal Learning Test (Brandt, 1991), the Rey Auditory-Verbal Learning Test (Schmidt, 1996) (Schmidt, 1996), and the Rivermead Behavioural Paragraph Recall Test (Wilson et al., 1999) (Wilson et al., 1999). Reasoning assessment focused on tasks requiring the identification of patterns and included the total correct number of items for Letter Sets (Thurstone & Thurstone, 1949) (Thurstone & Thurstone, 1949), Letter Series (Ekstrom, 1976) (Ekstrom, 1976), and Word Series (Gonda, 1985). Speed of processing assessment included three Useful Field of View (UFOV) conditions (Ball et al., 1988) (Ball et al., 1988), which required identification and localization of visual information under varying levels of cognitive demand. The global measure of cognition—the Mini Mental State Exam (MMSE)—evaluates language, memory, orientation, attention, and construction skills (Folstein et al., 1975). The MMSE has been widely used as a measure of general mental status to screen for dementia (Arevalo-Rodriguez et al., 2015). Scores range from 0 to 30, with lower scores reflecting poorer mental functioning.

Race and Ethnicity

Men self-reported their race as White, African American, or other (includes Asian, Indian, biracial, and other). In addition, men reported their ethnicity as Hispanic/Latinx or not.

We conceptualize race as a social construct. This is important given the history of how people of color have been systematically excluded from opportunities that could lead to better cognition (Glymour & Manly, 2008).

Covariates

Demographic variables included age in years and years of education completed. Health-related characteristics consisted of number of depressive symptoms, number of chronic conditions, and physical functioning. Depressive symptomatology was measured using the 12-item version of the Center for Epidemiologic Studies-Depression (CES-D) scale (Radloff, 1977). Men rated how often over the past week they experienced positive or negative symptoms associated with depression (e.g., feeling depressed, crying spells, feeling hopeful, being happy, could not get going, or trouble keeping mind on task). Response options included: 0 = Rarely or None of the Time, 1 = Some or Little of the Time, 2 = Moderately or Much of the Time, or 3 = Most or Almost All the Time. Positive symptoms (e.g., “I was happy”) were reverse coded to reflect higher depressive symptomatology. Scores range from 0 to 36. Physical functioning was assessed using the Medical Outcomes Study 36-Item Short Form physical functioning scale (Ware Jr & Sherbourne, 1992). Activities (e.g., ability to lift and carry groceries) were assessed on a 3-level continuum. Scores for this domain range from 0 to 100, with higher scores reflecting better physical functioning. Chronic conditions were based on self-report of hypertension, stroke, heart disease, congestive heart failure, high cholesterol, cancer, asthma, cataracts, diabetes, diabetic retinopathy, glaucoma, macular degeneration, and osteoporosis. Each of the chronic conditions was coded as a binary variable (0 = absent or 1 = present). All 13 variables were summed to create a variable that reflects the number of chronic conditions each man reported.

Study design variables included intervention group, intervention site, and replicate code. Intervention group (memory, reasoning, speed of processing, and [reference: control]) was included to account for possible training effects. Site of participation (Indiana University School of Medicine, Hebrew Rehabilitation Center for the Aged (HRCA), Johns Hopkins University, Wayne State University, Penn State University, [reference: University of Alabama, Birmingham]) was included to account for between-site differences. Replicate code, an indicator of the study design that enabled recruitment scaling, was included to account for period effects as they relate to wave of testing and training. All covariates were measured at baseline.

Statistical Analysis

The characteristics of the men in the sample were described for the total sample and by race. Chi-Square and ANOVA techniques were used to examine the proportional and mean differences between characteristics on men by race. The distribution of mortality and mortality rates (deaths per 1000 person-years) were calculated for the total sample and by race. Cox proportional hazard models were specified to examine the relation between each measure of baseline cognition and mortality among Black men and White men. All analyses were conducted in Stata 15.

Results

The distribution of the select characteristics of 614 Black men and White men in the ACTIVE Study for the total sample and by race is shown in Table 1. Fifteen of the Black men and White men in the sample (0.54%) were also Hispanic/Latinx. Over 3/4th of the men in the study were White and approximately a quarter of the men were assigned to each of the intervention groups. On average, men were 73.7 ± 6.0 years old and completed 14.4 ± 2.9 years of education. Regarding the cognitive measures for the sample, on average, the memory score was −0.52 ± 2.3, the reasoning score was 0.33 ± 2.6, and the speed score was −0.20 ± 2.6. The mean MMSE score of the sample was 27.5 ± 1.9. As it relates to health and function, men exhibited the following health-related profile: a mean score of 4.5 ± 4.8 depressive symptoms, 2.0 ± 1.4 chronic conditions, and a 74.9 ± 22.2 on the SF-36 functioning scale. Eighty percent of the men were deceased, and the mean age at death was 86.0 ± 6.8 years. Examining the characteristics by race revealed that Black men were younger at baseline, completed fewer years of education, performed worse, on average, on all cognition tests—MMSE, memory, reasoning, and speed of processing, reported worse functioning, and were more likely to be deceased at follow-up compared to White men. No differences were observed between Black men and White men with respect to being assigned to the intervention group, number of depressive symptoms, number of chronic conditions, and mean age at death. The unadjusted mortality rate was 63.0 per 1000 person-years.

Table 1.

Distribution of Select Characteristics of White Men and Black Men in the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) Study.

Characteristic	Total (N = 614)	White men (n = 500)	Black men (n = 114)	p-value
Demographic, mean ± SD	Total (N = 614)	White men (n = 500)	Black men (n = 114)	p-value
Age at baseline	73.7 ± 6.0	74.0 ± 6.1	72.0 ± 5.1	.0009
Years of education	14.4 ± 2.9	14.7 ± 2.8	13.0 ± 2.6	.0001
Cognitive performance, mean ± SD
Memory score*	−0.52 ± 2.3	−0.31 ± 2.4	−1.42 ± 1.9	.0001
Reasoning score*	0.33 ± 2.6	0.74 ± 2.5	−1.49 ± 2.3	.0001
Speed score*	−0.20 ± 2.6	−0.41 ± 2.6	0.70 ± 2.6	.0001
Mini mental state exam total	27.5 ± 1.9	27.7 ± 1.8	26.8 ± 2.0	.0001
Intervention group, N (%)
Memory	154 (25.1)	126 (25.2)	28 (24.6)	.0770
Reasoning	144 (23.4)	117 (23.4)	27 (23.7)
Speed of processing	149 (24.3)	122 (24.4)	27 (23.7)
Control	167 (27.2)	135 (27.0)	32 (28.0)
Health and function, mean ± SD
Depressive symptoms (CES-D) score	4.5 ± 4.8	4.4 ± (4.9)	5.0 ± 4.3	.2225
Number of chronic conditions	2.0 ± 1.4	2.0 ± (1.4)	2.2 ± 1.5	.0947
Physical functioning scale of the short-form (SF) 36	74.9 ± 22.2	76.0 ± 21.5	70.3 ± 24.4	.0133
Deceased, N (%)	492 (80.1)	393 (78.6)	99 (86.8)	.0470
Age at death, mean ± SD	85.9 ± 6.8	86.2 ± 6.7	84.9 ± 6.8	.0771
Study design
Site, N (%)
Alabama	172 (28.0)	167 (33.4)	5 (4.4)	.0001
Indiana	106 (17.3)	69 (13.8)	37 (32.5)
Hebrew rehabilitation center for the aged (HRCA)	82 (13.4)	80 (16.0)	2 (1.8)
Johns Hopkins University	72 (11.7)	62 (12.4)	10 (8.8)
Wayne state	109 (17.7)	59 (10.0)	50 (51.7)
Penn state	73 (11.9)	72 (14.4)	1 (0.9)
Replicate code, mean ± SD	3.93 ± 1.6	4.10 ± 1.5	3.18 ± 1.6	.0001

Note: Depressive symptoms score was based on the 12-item version of the CES-D scale. Number of chronic conditions included hypertension, stroke, heart disease, congestive heart failure, high cholesterol, cancer, asthma, cataracts, diabetes, diabetic retinopathy, glaucoma, macular degeneration, and osteoporosis. Items marked with an asterisk (*) are standardized at baseline.

The association between each baseline cognitive composite measure and 20-year all-cause mortality risk for Black men and White men is shown in Figure 1 and Table 2. Among White men, after adjusting for age, education, intervention group, number of depressive symptoms, number of chronic conditions, physical functioning, intervention site, and replicate code, higher performance on the memory composite was associated with a 7% decreased risk of all-cause mortality (HR: 0.93; 95% CI: 0.89–0.98), whereas the reasoning, speed of processing, and MMSE cognitive measures were not associated with all-cause mortality. Regarding Black men, none of the cognitive measures—memory, reasoning, speed of processing, or MMSE—were associated with all-cause mortality risk adjusting for all covariates.

Figure 1.

Hazard ratios for the Association between Baseline Cognition and Mortality in Black and White men in the Advanced Cognitive Training for Independent and Vital Elderly Study.

Table 2.

Association between Baseline Cognition (Memory, Reasoning, Speed, MMSE) and All-Cause Mortality in Black and White Men in the ACTIVE Study.

	HR	95% CI		p-value
White men (n = 500)
Memory score	0.93	0.89	0.98	.01
Reasoning score	0.97	0.92	1.02	.18
Speed of processing score	0.96	0.91	1.01	.09
MMSE	0.98	0.92	1.04	.43
Black men (n = 114)
Memory score	0.91	0.79	1.04	.17
Reasoning score	0.92	0.82	1.04	.18
Speed of processing score	0.93	0.82	1.05	.24
MMSE	0.93	0.83	1.04	.19

Models adjusted for age, levels of education, intervention group, number of chronic conditions, CES-D depression score, SF-36 self-rated health, intervention site, and replicate code.

Discussion

In this study, we sought to examine the association between baseline cognition—memory, reasoning, speed of processing, and MMSE—and 20-year all-cause mortality among a sample of community-dwelling older Black men and older White men without dementia in the ACTIVE Study. We found that higher performance on a baseline memory composite measure was associated with a decreased risk of all-cause mortality among White men, adjusting for covariates. However, none of the other baseline cognitive measures was related to all-cause mortality among White men, and there were no associations observed between baseline cognition and all-cause mortality risk among Black men. Additional cognitive measures should be explored for the relation with subsequent mortality among older Black men and older White men.

White men who had a higher performance on the memory composite measure at baseline had a lower subsequent mortality risk. This finding is consistent with previous work showing better memory performance is independently associated with lower mortality (Villarejo et al., 2011). However, there were no observed associations between the other cognitive measures and mortality for White men, although higher scores on the reasoning and speed of processing measures statistically trended in the direction of lower mortality (Hayat et al., 2018; Johnson et al., 2007). Our finding that scores on the MMSE were unrelated to mortality is consistent with other research (e.g., see Hayat et al., 2018; Johnson et al., 2007) showing that tests of global cognition do not perform as well as composite measures which are a combination of individual tests in different cognitive ability domains.

Baseline cognitive measures were not significantly associated with mortality for Black men. However, the mean effects of the cognitive scores were larger than that of older White men. Based on previous work (Hayat et al., 2018; Johnson et al., 2007; Rebok et al., 2022), this finding was unexpected. Using the full ACTIVE sample, we found that higher baseline cognitive performance on all measures, including the MMSE, was associated with a lower hazard of mortality over 20 years (Rebok et al., 2022). Although this association was not observed in the current study, the hazard ratios were in the expected direction, but the confidence intervals were somewhat wide. This is likely indicative of the small sample size of Black men (n = 114) in the ACTIVE study. Future work should place an emphasis on recruitment and retention efforts to ensure a sufficient sample of Black men in research focusing on cognition and future health outcomes including mortality. In addition to sample size, there are structural determinants of cognition and all-cause mortality such as structural racism that would likely impact the relationship between cognition and all-cause mortality among older Black men. There are many pathways by which social adversities that are constrained by structural determinants can impact cognition and all-cause mortality across the life course (Glymour & Manly, 2008; James & Bennett, 2019).

There are aspects of the study that warrant comment. Regarding limitations, there might have been misclassification in mortality status for men with incomplete data for key identifiers that are used for linkage of study data to NDI data. To address the potential of misclassification, additional searches of public record obituaries and LexisNexis and Ancestry.com databases were performed by the ACTIVE team to confirm mortality status. There were a few men (n = 16) who were excluded due to their unknown mortality status. Second, the external validity of the study is limited. This is largely in part because men were included in the ACTIVE study if they were, at baseline, living independently and cognitively and physically healthy. In addition, we focus on White and Black men; therefore, we are unable to comment on the association between the cognitive measures and all-cause mortality for other racial or ethnic groups of older men. Finally, the ACTIVE study has limited diversity of its cognitive measures (Marsiske et al., 2013) (see Marsiske et al., 2013, JAH). The tests heavily sampled fluid intelligence domains (episodic memory, inductive reasoning, speed of processing) since these were the targets of the ACTIVE cognitive training intervention. However, knowledge-based, or crystallized domains were not well-represented in the study except for the vocabulary measure. The latter domain might be expected to show greater sensitivity to different levels of literacy across the two racial groups examined. Other factors may also account for the lack of significant associations that differ by race. It is clear that ACTIVE enrolled a higher proportion of positively selective African Americans than Whites, given higher rates of exclusion for African Americans than for Whites (24.5% vs. 15.4%). Persons were excluded from ACTIVE if they had MMSE scores less than 23, vision worse than 20/70, or health conditions such as history of stroke or low-survival cancers or had experienced substantial ADL impairment. However, even in this more selective sample of older Black men, mortality rates were higher, which might be due to the cumulative effects of a lifetime of racial discrimination and less favorable social determinants of health.

Despite the limitations, there are some notable strengths. The longitudinal study design allowed for 20 years of mortality follow-up. This study used three standard composite measures of memory, reasoning, and speed of processing tasks that are often used in cognitive aging research. Second, this is one of a few studies that has sought to examine the association between baseline cognitive measures and mortality among older Black men and older White men. Finally, this study provides the basis for future work focusing on Black and White men to better understand the cognition-mortality relation among different racial/ethnic groups of older men.

In conclusion, these findings underscore the need for a concerted effort to recruit Black men, particularly older Black men, into research regarding cognition. These findings also emphasize the need to consider other aspects such as social determinants of health and how they might impact the association between cognition and all-cause mortality. Measuring cognition beyond just baseline may influence disparities between older Black men and older White men and all-cause mortality. Future studies should consider other cognitive measures in relation to all-cause mortality among older Black and older White men,

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Institute on Aging; (K02AG059140, P30AG059298, R01AG054363, R01AG056486, T32AG000247, T32AG027668).

ORCID iDs

Roland J. Thorpe

Olivio J. Clay

Lorraine Dean

Adrienne Aiken-Morgan

George W. Rebok

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