49 Examining Associations Between Intelligence and Adaptive Functioning in Adults with Down Syndrome at Risk for Alzheimer's Disease

Abstract

Objective:

Individuals with Down syndrome (DS) experience intellectual disability, such that measures of cognitive and adaptive functioning are near the normative floor upon evaluation. Individuals with DS are also at increased risk for Alzheimer's disease (AD) beginning around age 40; and test performances and adaptive ratings at the normative floor make it difficult to detect change in cognition and functioning. This study first assessed the range of raw intelligence scores and raw adaptive functioning of individuals with DS at the normative floor. Next, we assessed whether those raw intelligence scores were predictive of raw adaptive functioning scores, and by association, whether they may be meaningful when assessing change in individuals with a lower baseline of cognitive functioning.

Participants and Methods:

Participants were selected from a cohort of 117 adults with DS in a longitudinal study examining AD risk. Participants (n=96; M=40.9 years-old, SD=10.67; 57.3% female) were selected if they had both a completed measure of IQ (Kaufmann Brief Intelligence Test; KBIT2) and informant ratings of adaptive functioning (Vineland Adaptive Behavior Scales; VABS-II). Multiple regression was conducted predicting VABS-II total raw score using K-BIT2 total raw score, while controlling for age.

Results:

A slight majority (57.3%) of the sample had a standardized IQ score of 40 with the majority (95.7%) having a standardized score at or below 60. Additionally, 85.3% of the sample had a standard VABS-II score at or below 60. Within the normative floor for the KBIT2 (IQ=40), there was a normal distribution and substantial range of both KBIT2 raw scores (M = 31.19, SD = 13.19, range: 2 to 41) and VABS-II raw scores (M = 406.33, SD = 84.91, range: 198 to 569). Using the full sample, age significantly predicted raw VABS-II scores (ß = -.283, p = .008). When KBIT2 raw scores were included in the model, age was no longer an independently significant predictor. KBIT2 raw scores significantly predicted raw VABS-II scores (ß = .689, p < .001). Age alone accounted for 8.0% of variance in VABS-II raw scores and KBIT2 raw scores accounted for 43.8% additional variance in VABS-II raw scores. This relationship was maintained when the sample was reduced to individuals at the normative floor (n = 51) where KBIT2 raw scores accounted for 23.7% of the variance in raw VABS-II scores (ß = .549, p < .001).

Conclusions:

The results indicate that meaningful variability exists among raw intelligence test performances that may be masked by scores at the normative floor. Further, the variability in raw intelligence scores is associated with variability in adaptive functioning, such that lower intelligence scores are associated with lower ratings of adaptive functioning. Considering this relationship would be masked by a reduction of range due to norming, these findings indicate that raw test performances and adaptive functioning ratings may have value when monitoring change in adults with DS at risk for AD.