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Objective: Emerging evidence suggests low vision may be a modifiable risk factor for cognitive decline. We examined effects of baseline visual acuity (VA) on level of, and change in, cognitive test performance over 9 years. Method: A population-based sample of 1,621 participants (average age 77 years) completed a comprehensive neuropsychological evaluation and VA testing at baseline and reassessed at nine subsequent annual visits. Linear regression modeled the association between baseline VA and concurrent cognitive test performance. Joint modeling of a longitudinal sub-model and a survival sub-model to adjust for attrition were used to examine associations between baseline VA and repeated cognitive test performance over time. Results: Better baseline VA was associated cross-sectionally with younger age, male sex, greater than high school education, and higher baseline neuropsychological test scores on both vision-dependent (B coefficient range −0.163 to −0.375, p =.006 to <.001) and vision-independent tests (−0.187 to −0.215, p =.003 to.002). In longitudinal modeling, better baseline VA was associated with slower decline in vision-dependent tests (B coefficient range −0.092 to 0.111, p =.005 to <.001) and vision-independent tests (−0.107 to 0.067, p =.007 to <.001). Conclusions: Higher VA is associated with higher concurrent cognitive abilities and slower rates of decline over 9 years in both vision-dependent and vision-independent tests of memory, language, and executive functioning. Findings are consistent with emerging literature supporting vision impairment in aging as a potentially modifiable risk factor for cognitive decline. Clinicians should encourage patient utilization of vision assessment and correction with the added aim of protecting cognition. [ABSTRACT FROM AUTHOR]

Background: Longitudinal studies predictably experience non-random attrition over time. Among older adults, risk factors for attrition may be similar to risk factors for outcomes such as cognitive decline and dementia, potentially biasing study results.Objective: To characterize participants lost to follow-up which can be useful in the study design and interpretation of results.Methods: In a longitudinal aging population study with 10 years of annual follow-up, we characterized the attrited participants (77%) compared to those who remained in the study. We used multivariable logistic regression models to identify attrition predictors. We then implemented four machine learning approaches to predict attrition status from one wave to the next and compared the results of all five approaches.Results: Multivariable logistic regression identified those more likely to drop out as older, male, not living with another study participant, having lower cognitive test scores and higher clinical dementia ratings, lower functional ability, fewer subjective memory complaints, no physical activity, reported hobbies, or engagement in social activities, worse self-rated health, and leaving the house less often. The four machine learning approaches using areas under the receiver operating characteristic curves produced similar discrimination results to the multivariable logistic regression model.Conclusions: Attrition was most likely to occur in participants who were older, male, inactive, socially isolated, and cognitively impaired. Ignoring attrition would bias study results especially when the missing data might be related to the outcome (e.g. cognitive impairment or dementia). We discuss possible solutions including oversampling and other statistical modeling approaches. [ABSTRACT FROM AUTHOR]

Objectives: To investigate potential birth cohort effects in depression symptoms in older adults.Design: Population-based prospective cohort.Setting: Small-town communities in Pennsylvania.Participants: Three thousand two hundred and twenty seven older adults (average baseline age = 71.6) born between 1902 and 1941.Measurements: Four decade-long birth cohorts were the primary predictors in this study: 1902-1911, 1912-1921, 1922-1931, and 1932-1941. The outcome was symptoms of depression assessed at baseline and follow-up study visits using a modified Center for Epidemiologic Studies Depression Scale (mCES-D). The depression outcome was operationalized as: 1). A binary outcome of having greater than equal to 5 depression symptoms on the total mCES-D at any study visit, and 2). A continuous outcome of four factor-analyzed component scores of the mCES-D including depressed mood, anergia/hopelessness, withdrawal, and poor self-esteem. All analyses were jointly modeled with attrition and adjusted for age, sex, education, Mini Mental State Examination score, antidepressant medications, and total prescription medications.Results: Participants from more recently born cohorts were significantly less likely to have a study visit in which they reported greater than or equal to 5 depression symptoms, controlling for attrition. Specifically, in comparison to the 1902-1911 referent cohort, the 1912-1921 birth cohort was 43% less likely (odds ratio [OR] = 0.566, 95% confidence interval [CI]: 0.341-0.939), the 1922-1931 birth cohort was 63% less likely (OR = 0.0369, 95% CI: 0.215-0.632), and the 1932-1941 cohort was 79% less likely (OR = 0.205, 95% CI: 0.106-0.399). The cohort effect was most evident in the depressed mood and anergia/hopelessness symptom composites.Conclusion: Reduced rates of depression symptoms observed in successive birth cohorts of older adults may reflect compression of morbidity or other secular trends. [ABSTRACT FROM AUTHOR]

Background: Incidence rates of dementia appear to be declining in high-income countries according to several large epidemiological studies. We aimed to describe declining incident dementia rates across successive birth cohorts in a U.S. population-based sample and to explore the influences of sex and education on these trends.Methods: We pooled data from two community-sampled prospective cohort studies with similar study aims and contiguous sampling regions: the Monongahela Valley Independent Elders Survey (1987-2001) and the Monongahela-Youghiogheny Healthy Aging Team (2006-Ongoing). We identified four decade-long birth cohorts spanning birth years 1902-1941. In an analysis sample of 3,010 participants (61% women, mean baseline age = 75.7 years, mean follow-up = 7.1 years), we identified 257 cases of incident dementia indicated by a Clinical Dementia Rating of 1.0 or higher. We used Poisson regression to model incident dementia rates by birth cohort, age, sex, education, and interactions of Sex × Cohort and Sex × Education. We further examined whether cohort effects varied by education, testing a Cohort × Education interaction and stratifying the models by education.Results: Compared to the earliest birth cohort (1902-1911), each subsequent cohort had a significantly lower incident dementia rate (1912-1921: incidence rate ratio [IRR] = 0.655, 95% confidence interval [95% CI] = 0.477-0.899; 1922-1931: IRR = 0.387, 95% CI = 0.265-0.564; 1932-1941: IRR = 0.233, 95% CI = 0.121-0.449). We observed no significant interactions of either sex or education with birth cohort.Conclusions: A decline in incident dementia rates was observed across successive birth cohorts independent of sex, education, and age. [ABSTRACT FROM AUTHOR]