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Experimental Aging Research
An International Journal Devoted to the Scientific Study of the Aging Process
Volume 34, 2007 - Issue 1
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Original Articles

Characterizing and Explaining Differences in Cognitive Test Performance Between African American and European American Older Adults

, &
Pages 80-100 | Received 23 Oct 2005, Accepted 11 Aug 2006, Published online: 11 Jan 2008
 

Abstract

The present study examined differences in cognitive performance of African American and European American older adults on cognitive and intellectual measures, and the extent to which literacy status or reading level was useful in explaining these group differences. African American elders performed more poorly than European American elders on 12 of 13 cognitive tests administered, p < .05. After controlling for reading level achievement, differences in performance became nonsignificant for 5 of these 12 tests. Nonetheless, some differences persisted, suggesting that other potential mediators of race differences remain to be explored in future research.

Acknowledgments

This work was completed in fulfillment of Ms. Aiken Morgan's Masters Thesis.

Notes

*Significant at p < .05; m = mean score (standard deviation).

1The cutoff score of 22 was used to ensure adequate recruitment of African American older adults to meet the goals of the pilot and overall ACTIVE clinical trial.

Note

a From the Kit of Factor-Cognitive Reference Tests.

b From Schaie-Thurstone Adult Mental Abilities Test.

Note. Group means shown are estimated marginal means before WRAT-3 adjustment, standard errors are presented in parenthesis. Age, education, gender, and site of recruitment were used as background covariates in all models. Semipartial r 2 values for race represent the squared semipartial correlations after adjusting for all other background covariates; i.e., the change in r 2 resulting when race was entered in a final step of a hierarchical regression in which all other predictors had been added in an earlier step. Model 1: Score = Block 1 (age, education, gender, site) + Block 2 (race); Model 2: Score = Block 1 (age, education, gender, site, WRAT-3) + Block 2 (race); Model 3: Score = Block 1 (age, education, gender, site, WRAT-3, arthritis, diabetes, heart disease, cancer, CES-D score) + Block 2 (race).

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