Effect of metabolic syndrome risk factors on processing speed in three racial groups: Dementia care research (research projects; nonpharmacological) / Behavioral interventions. (7th December 2020)

• Record Type: Journal Article
• Authors: Bouges, Shenikqua; Norton, Derek L; Wyman, Mary F; Lambrou, Nickolas H; Zuelsdorff, Megan; Van Hulle, Carol A; Ennis, Gilda E; James, Taryn T; Johnson, Adrienne L; Clark, Lindsay R; Carlsson, Cynthia M; Gleason, Carey E
• Is Part Of: Alzheimer's & dementia. Volume 16(2020)Supplement 7
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-12-07
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.039570
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Metabolic syndrome (MetS) in mid‐life is a known risk factor for Alzheimer's disease & related dementias (ADRD). Racial and ethnic minorities represent under‐represented groups (URGs) in ADRD research. Targeted outreach, recruitment and retention initiatives broaden the reach of Alzheimer Disease Research Centers (ADRC) within prioritized communities. Understanding the association between MetS risk factors and cognition during preclinical ADRD in URGs may elucidate avenues for ameliorating ADRD risk in URGs prior to dementia onset. Generalizability of findings vary by the population represented within an analytic sample. We describe MetS‐cognition relationships within URGs and referral source, a key determinant of our sample composition. Methods: Cognitively unimpaired adults from the Wisconsin ADRC and the Wisconsin Registry for Alzheimer's Disease Prevention (WRAP) completed blood‐work and neuropsychological testing. Sample sizes varied based on the outcome analyzed and ranged from 714 to 1088 subjects. The 6 cognitive outcomes were: Trails A, Trails B, Animal Fluency, Digit Symbol, a Simple Speed composite, and Speed/Executive composite. Linear mixed effect models with an Age‐by‐Race‐by‐MetS interaction tested whether MetS count moderated age‐related cognitive trajectories differently in White (N=990), African American (AA; N=85), and Native American (NA; N=15) participants. In secondary analyses, referral source was examined for WRAP and ADRC cohorts to assess the potential for selection‐based effects in our data. Results: Only Trails A had a significant 3‐way interaction (p=0.004). Graphing this interaction revealed that the cognitive trajectory in Whites remained stable as MetS count increased, while the NA trajectory appeared to worsen with increasing MetS count. AA and Whites appeared to have similar longitudinal trajectories despite a faster processing speed in White group. A small NA sample limits the precision of our results. Examinations of referral source data (Figure 5) suggest that enrollment differed between WRAP and the Wisconsin ADRC participants. Conclusion: Results indicate disparities for level and decline in cognitive function for racial minority participants. Affected cognitive domain varies by race, but overall findings highlight the importance of prioritizing recruitment and retention of URG participants. Sample size, social & enrollment factors are all possible contributors to our findings and need to be examined in the future.