Racial Disparities in Cognitive Function Among Middle-Aged and Older Adults: The Roles of Cumulative Stress Exposures Across the Life Course

Abstract

Background: Racial disparities in cognitive function are well documented, but factors driving these disparities remain underexplored. This study aims to quantify the extent to which cumulative stress exposures across the life course explain Black-White disparities in executive function and episodic memory in middle-aged and older adults.

Method: Data were drawn from the 2004-2006 wave of the Midlife Development in the United States Study (MIDUS 2) and the MIDUS Refresher study (N = 5,947; 5,262 White and 685 Black). Cumulative stress exposures were assessed by 10 stressor domains (ie, childhood stress, stressful life events in adulthood, financial stress, work psychological stress, work physical stress, work-family conflicts, neighborhood disorder, relationship stress, perceived inequality, and perceived discrimination). Cognitive function was assessed using the Brief Test of Adult Cognition by Telephone. Marginal structural models were used to quantify the proportion of the effect of race/ethnicity status on cognitive function mediated through cumulative stress exposures.

Results: After adjusting for age, sex, and sample, on average, Black participants had lower levels of executive function (difference: -0.83 SD units, 95% CI: -0.91, -0.75) and episodic memory (difference: -0.53 SD units, 95% CI: -0.60, -0.45) scores than White participants. Cumulative stress exposures accounted for 8.4% of the disparity in executive function and 13.2% of the disparity in episodic memory.

Conclusions: Cumulative stress exposures across the life course explained modest proportions of Black-White disparities in cognitive function in this large cross-sectional study.

Keywords: Episodic memory; Executive function; Health disparities; Race; Stressors.

Figure 1.

Directed acyclic graph showing the hypothesized relationships between the exposure, mediator, outcome, and confounders. “C” denotes exposure–outcome confounders, including age, sex, and sample status; “L” denotes mediator–outcome confounders, including education, income, spousal status, parental status, working status, and chronic conditions.

Figure 2.

Age-adjusted mean and standard errors of executive function and episodic memory in Black and White participants in the Midlife Development in the United States Study.

Figure 3.

Relationships between race/ethnicity status, cumulative stress exposures, and executive function.Notes: ^aTotal effects of race/ethnicity status on executive function, adjusting for age, sex, and sample. ^bAssociations between race/ethnicity status on cumulative stress exposures, adjusting for age, sex, and sample. ^cAssociations between cumulative stress exposures and executive function, adjusting for age, sex, race/ethnicity status, sample, education, income, spousal status, parental status, working status, and chronic conditions. ^dMarginal structural model evaluating the controlled direct effect of race/ethnicity status on executive function. ^eGeneralized estimating equations with identity link and normal distribution were used in all models to adjust for clustering by family and were calculated using SAS PROC GENMOD. ^fResults were generated from 20 multiply imputed datasets.

Figure 4.

Relationships between race/ethnicity status, cumulative stress exposures, and episodic memory.Notes: ^aTotal effects of race/ethnicity status on episodic memory, adjusting for age, sex, and sample. ^bAssociations between race/ethnicity status on cumulative stress exposures, adjusting for age, sex, and sample. ^cAssociations between cumulative stress exposures and episodic memory, adjusting for age, sex, race/ethnicity status, sample, education, income, spousal status, parental status, working status, and chronic conditions. ^dMarginal structural model evaluating the controlled direct effect of race/ethnicity status on episodic memory. ^eGeneralized estimating equations with identity link and normal distribution were used in all models to adjust for clustering by family and were calculated using SAS PROC GENMOD. ^fResults were generated from 20 multiply imputed datasets.