40 Educational Quality vs Years of Education is More Strongly Associated with Neuropsychological Test Performance
Authors: Steinbach Marilyn J , Bolton Corey J , Gogniat Marissa A , Jefferson Angela L , Westervelt Holly J 
Published: December 2023

Objective:

Education is known to impact neuropsychological test performance, and self-reported years of education is often used in stratifying normative data. However, this variable does not always reflect education quality, particularly among underrepresented populations, and may overestimate cognitive impairment in individuals with low education quality. This cross-sectional study evaluated relative contributions of years of education and reading level to several verbally mediated assessments to improve interpretation of neuropsychological performance.

Participants and Methods:

Data was obtained from the Vanderbilt Memory and Aging Project. Cognitively-unimpaired participants (n=175, 72±7 years, 59% male, 87% Non-Hispanic White, 16±2 years of education) completed a comprehensive neuropsychological protocol. Stepwise linear regressions were calculated using education and Wide Range Achievement Test (WRAT)-3 Reading subtest scores as predictors and letter fluency (FAS, CFL), category fluency (Vegetable and Animal Naming), the Boston Naming Test (BNT), and California Verbal Learning Test (CVLT)-II as outcomes to assess increase in variance explained by educational quality. Models covaried for age and sex. The False Discovery Rate (FDR) based on the Benjamini-Hochberg procedure (Benjamini & Hochberg, 1995) was used to correct for multiple comparisons.

Results:

The mean WRAT-3 score was 51±4 (range:37-57), indicating post-high school reading level. Education and WRAT-3 scores were moderately correlated (r=0.36, p<0.01). Both WRAT-3 and years of education independently predicted letter fluency (WRAT-3 p<0.001; education p<0.02), category fluency (WRAT-3 p<0.001; education p<0.05), and CVLT-II performance (WRAT-3 p-values<0.005; education p-values<0.02) in single predictor models. On BNT, WRAT-3 (p<0.001), but not education (p=0.06), predicted performance in single predictor models. In combined models with both WRAT-3 and education, WRAT-3 scores remained a significant predictor of FAS (WRAT-3 b=1.21, p<0.001; education b=0.006, p=0.99) and CFL performance (WRAT-3 b=1.02, p<0.001; education b=0.51, p=0.14). Both WRAT-3 (b=0.21, p=0.01) and years of education (b=0.35, p=0.03) predicted Animal Naming, while WRAT-3 (b=0.16,p=0.008), but not years of education (p=0.37), predicted Vegetable Naming. WRAT-3 was a significant predictor of BNT performance (b=0.21, p<0.001) but not years of education (p=0.65). WRAT-3 predicted CVLT-II learning (b=0.32, p=0.04), immediate recall (b=0.16, p=0.005), and delayed recall performances (b=0.15, p=0.005), while education did not (p-values>0.14). All significant results persisted after FDR correction. WRAT-3 scores explained an additional level of variance beyond the covariates and education alone for FAS (AR=18%), CFL (AR=13%), Animal Naming and Vegetable Naming (AR= 3%), BNT (AR=18%), and CVLT-II learning (AR=2%), immediate recall (AR=4%), and delayed recall (AR=3%).

Conclusions:

Reading level more strongly associated with performance on several verbally mediated neuropsychological measures than years of education. For all measures, the addition of reading level significantly increased the amount of variance explained by the model compared to covariates and education alone, which aligns with existing research. However, most of this past work looks at individuals with lower levels of educational quality. Because our cohort was highly educated and at the upper end of the reading spectrum, our results suggest that reading level is important to consider even for more highly educated individuals. Therefore, reading level is a critical variable to consider when interpreting verbally mediated neuropsychological measures for individuals across the educational spectrum.