Vascular Depression and Cognition in Mexican Americans.

BACKGROUND: Mexican Americans are at increased risk of developing mild cognitive impairment (MCI) and Alzheimer's disease compared to non-Hispanic whites. This study sought to examine the relationship between vascular risk, depression, and cognition in Mexican American elders. METHODS: Data from 470 (390 normal controls, 80 MCI patients) Mexican Americans enrolled in the Health and Aging Brain among Latino Elders (HABLE) study were used. The cardiovascular risk was assessed by the Framingham Risk Score. Cognition was assessed with a neuropsychological battery, and depression was assessed based on scores from the Geriatric Depression Scale (GDS). ANOVAs were utilized to determine the differences in neuropsychological scores of normal controls with and without depression and CVD risk (low vs. high). Follow-up logistic regression was conducted to determine MCI risk. RESULTS: The results of this study indicated that comorbid depression and a high CVD risk were associated with poorer cognitive performance in Mexican Americans. Depressed women with high CVD risk were more likely to have executive dysfunction, language deficits, and poorer global cognition than nondepressed women with a high CVD risk. In Mexican American men, those with a high vascular risk and depression were more likely to have executive dysfunction and poorer immediate memory than the nondepressed high-risk group. Higher GDS scores (OR = 1.10; 95% CI 1.02-1.10, p = 0.001) and higher vascular risk scores (OR = 1.05; 95% CI 1.02-1.10, p = 0.001) significantly predicted MCI status in Mexican Americans. CONCLUSION: The results of this study indicated that comorbid depression and a high CVD risk were associated with poorer cognitive performance and increased risk of MCI in Mexican Americans.

Addition of EEG improves accuracy of a logistic model that uses neuropsychological and cardiovascular factors to identify dementia and MCI.

To investigate whether addition of EEG would improve accuracy of a logistic model that uses neuropsychological assessment and cardiovascular history to identify dementia and mild cognitive impairment (MCI) as a single group, we collected data and constructed logistic models from a sample of 78 normal adults and 33 patients (aged 50-85 years). To determine accuracy, we compared logistic regression results to a geriatrician's diagnosis of MCI or dementia that included Alzheimer's disease, vascular dementia or mixed dementia. We found that the addition of EEG (non-linear complexity) to a logistic model that included both neuropsychological assessment (ADAS-Cog) and cardiovascular history increased overall accuracy from 80% to 92%. The logistic model identified dementia and MCI as a single group comprised of the following subgroups (with accuracies): Alzheimer's disease (92%; 12/13), vascular dementia (73%; 8/11), mixed dementia (100%; 4/4), and mild cognitive impairment (80%; 4/5). Whereas the analysis is limited by small sample sizes and mixing of diverse pathologies, the findings do provide support that the subgroups may share changes in neuropsychological, cardiovascular, and electroencephalographic factors (specifically ADAS-Cog total score, cardiovascular history, and EEG complexity). Taken together, the study results provide support that EEG might complement the clinician's evaluation of dementia and MCI.