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Objectives: Performance on cognitive tests can be affected by age, education, and also selection bias. We examined the distribution of scores on several cognitive screening tests by age and educational levels in a population-based cohort. Method: An age-stratified random sample of individuals aged 65+ years was drawn from the electoral rolls of an urban US community. Those obtaining age and education-corrected scores ≥21/30 on the Mini-Mental State Examination (MMSE) were designated as cognitively normal or only mildly impaired, and underwent a full assessment including a battery of neuropsychological tests. Participants were also rated on the Clinical Dementia Rating (CDR) scale. The distribution of neuropsychological test scores within demographic strata, among those receiving a CDR of 0 (no dementia), are reported here as cognitive test norms. After combining individual test scores into cognitive domain composite scores, multiple linear regression models were used to examine associations of cognitive test performance with age and education. Results: In this cognitively normal sample of older adults, younger age and higher education were associated with better performance in all cognitive domains. Age and education together explained 22% of the variation of memory, and less of executive function, language, attention, and visuospatial function. Conclusion: Older age and lesser education are differentially associated with worse neuropsychological test performance in cognitively normal older adult representatives of the community at large. The distribution of scores in these participants can serve as population-based norms for these tests, and can be especially useful to clinicians and researchers assessing older adults outside specialty clinic settings. [ABSTRACT FROM AUTHOR]

To elucidate the relationship between stroke and depressive symptoms and to determine whether disability or cerebrovascular risk factors mediate that relationship. A prospective longitudinal epidemiological survey. The mid-Monongahela Valley, a rural, nonfarm, low-socioeconomic-status community. Random sample of 1,134 subjects aged 65 and older. The dependent variable was clinically significant depressive symptoms, as defined by five or more symptoms on the modified Center for Epidemiological Studies Depression scale. The independent variables were demographics (age, sex, education), stroke, number of impaired instrumental activities of daily living (IADLs), diabetes mellitus, hypertension, atherosclerotic heart disease, and smoking. Logistic regression analyses were conducted for cross-sectional and longitudinal models examining whether stroke was associated with or predicted depressive symptoms, with other associated factors included as covariates. Clinically significant depressive symptoms were cross-sectionally associated with stroke (odds ratio (OR)=3.5, 95% confidence interval (CI)=1.4–8.3), diabetes mellitus (OR=2.8, 95% CI=1.7–4.6; P≤.05), and IADL impairment (OR=1.6, 95% CI=1.4–1.8; P<.05). Longitudinal analysis demonstrated that stroke (OR=6.3, 95% CI=1.7–23.2) and depressive symptoms at baseline (OR=15, 95% CI=7.7–29.5) predicted subsequent clinically significant depressive symptoms measured 2 years later, whereas education was protective (OR=0.4, 95% CI=0.2–0.8). Stroke survivors have a greatly elevated risk for clinically significant depressive symptoms even 2 or more years after index stroke, independent of functional disability, cerebrovascular risk factors, and previous depressive symptoms. [ABSTRACT FROM AUTHOR]