Good social connections are proposed to positively influence the course of cognitive decline by stimulating cognitive reserve and buffering harmful stress-related health effects. Prior meta-analytic research has uncovered links between social connections and the risk of poor health outcomes such as mild cognitive impairment, dementia, and mortality. These studies have primarily used aggregate data from North America and Europe with limited markers of social connections. Further research is required to explore these associations longitudinally across a wider range of social connection markers in a global setting.

We examined the associations between social connection structure, function, and quality and the risk of our primary outcomes (mild cognitive impairment, dementia, and mortality).

Individual participant-level data were obtained from 13 longitudinal studies of ageing from across the globe. We conducted survival analysis using Cox regression models and combined estimates from each study using two-stage meta-analysis. We examined three social constructs: connection structure (living situation, relationship status, interactions with friends/family, community group engagement), function (social support, having a confidante) and quality (relationship satisfaction, loneliness) in relation to the risks of three primary outcomes (mild cognitive impairment, dementia, and mortality). In our partially adjusted models, we included age, sex, and education and in fully adjusted models used these variables as well as diabetes, hypertension, smoking, cardiovascular risk, and depression.

In our fully adjusted models we observed: a lower risk of mild cognitive impairment was associated with being married/in a relationship (vs. being single), weekly community group engagement (vs. no engagement), weekly family/friend interactions (vs. not interacting), and never feeling lonely (vs. often feeling lonely); a lower risk of dementia was associated with monthly/weekly family/friend interactions and having a confidante (vs. no confidante); a lower risk of mortality was associated with living with others (vs. living alone), yearly/monthly/weekly community group engagement, and having a confidante.

Good social connection structure, function, and quality are associated with reduced risk of incident MCI, dementia, and mortality. Our results provide actionable evidence that social connections are required for healthy ageing.

Health disparities between communities with greater and lesser advantages are a global concern. In the USA, self-identified race as African American (AA) is consistently associated with mild cognitive impairment (MCI) and dementia, compared to Americans of European descent. In a prospective population-based study, we sought to confirm this association and investigate potential explanatory factors.

The Monongahela-Youghiogheny Healthy Aging Team (MYHAT) and Seniors Project 15104 (SP15104) studies recruited adults aged 65+ years from a group of small towns of lower socioeconomic status in the US. MYHAT recruited by age-stratified random sampling from the voter registration list for all towns; SP15104 recruited by intensive community engagement from three towns with populations that are 60% AA. Based on the Clinical Dementia Rating (CDR), MCI was defined as CDR=0.5 and dementia as CDR > 1. Using Cox proportional hazard models, we modeled time to incident CDR > 0.5 from baseline as a function of race (AA vs. all other), other demographics, and several other covariates at baseline.

The sample of 2120 individuals was 8% AA, and 62% female, with median age of 73y, and median educational level of partial college. During follow up of up to 14.5 years, 499 participants developed new-onset MCI/dementia (CDR >0.5). Cox models revealed that being AA was significantly associated with incident CDR > 0.5 (HR=1.45. 95% CI:1.01,2.10). Inclusion of age, sex, and education in the model increased the HR for race to 1.63 (1.1, 2.3). Adding number of regularly taken prescription drugs (reflecting overall morbidity), depression symptoms, preceding year alcohol consumption, and number of visits to emergency or urgent care together reduced the HR to 1.4 (0.96, 2.0), no longer statistically significant

In this population-based cohort study, self-identified African Americans had an about 40% elevated risk of developing MCI/dementia. Adjusting for demographics, the significant association between race and incident MCI/dementia was attenuated by variables reflecting depression, greater general morbidity, and lesser access to regular health services. These variables possibly reflect downstream effects of historic discrimination, but couldstill be modifiable risk factors for MCI/dementia. Addressing them could potentially mitigate ethno-racial disparities in cognitive impairment.

Older adults commonly take benzodiazepines (BZDs) that may have long-term adverse cognitive effects. We investigated whether BZD use was related to developing mild cognitive impairment (MCI) or dementia in cognitively normal older adults in the community.

A population-based cohort (n = 1959) of adults aged 65 and over, recruited from communities of low socioeconomic status.

BZD use, Clinical Dementia Rating (CDR), anxiety symptoms, depression symptoms, sleep difficulties, and APOE genotype.

We examined time from study entry to MCI (CDR = 0.5) and time from study entry to dementia (CDR ≥ 1) in participants who were cognitively normal at baseline (CDR = 0). We used survival analysis (Cox model), adjusted for age, sex, education, sleep, anxiety, and depression. For all the models, we included an interaction term between BZD use and APOE*4.

Taking BZDs was significantly associated with higher risk of developing MCI, but not of developing dementia. The effect was not affected by APOE genotype.

In a population-based sample of cognitively normal older adults, BZD use is associated with developing MCI, but not dementia. BZD use may be a potentially modifiable risk factor for MCI.

The restrictions put in place in 2020 to mitigate the spread of the coronavirus disease 2019 limited or eliminated social connections that are vital for psychosocial well-being. The objectives of this research were to examine the impact of early pandemic-related restrictions on feelings of loneliness, depression, and anxiety as well as social activity disruption and their concomitant associations in a sample of community-dwelling older adults residing in a small-town region in the USA.

Cross-sectional data collected from an ongoing population-based cohort study in Southwestern, Pennsylvania.

Analyses included 360 adults aged 65 years and older whose annual study assessment occurred during the first 120 days of pandemic-related restrictions.

Self-reported feelings of loneliness, depression, and anxiety due to the pandemic-related restrictions were each measured using a single question. Depressive symptoms and anxiety were also assessed with the modified Center for Epidemiologic Studies-Depression and Generalized Anxiety Disorder-7 item tools. Disruption in a variety of common social activities was also assessed.

Feeling lonely affected 36% of participants who were more likely to be female, not currently married, and living alone. Giving up in-person visits with family was associated with significantly higher odds of feeling lonely, and feeling lonely was associated with significantly higher odds of feelings of anxiety and depression.

Loneliness is a serious outcome of pandemic-related restrictions among older adults, potentially linked to loss of connection with family, and may be associated with increased feelings of depression and anxiety.

Low and middle-income countries like India anticipate rapid population aging and increases in dementia burden. In India, dementia screening scales originally developed in other contexts need to be assessed for feasibility and validity, given the number of different languages and varying levels of literacy and education.

Using data from the Longitudinal Aging Study in India-Diagnostic Assessment of Dementia (N = 4,028), we characterize the performance of the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE). We described patterns and correlates of missingness, evaluated the psychometric properties of the scale, and assessed criterion validity against the Hindi Mental State Examination (HMSE) using linear regression.

Several IQCODE items had high levels of missingness, which was associated with urbanicity, respondent’s gender, and informant’s generation (same vs. younger generation). Full IQCODE scores showed strong criterion validity against the HMSE; each 1-point increase in IQCODE score was associated with a 3.03-point lower score on the HMSE, controlling for age, gender, and urbanicity. The statistically significant association between IQCODE and HMSE was stronger in urban than rural settings (p-value for interaction = 0.04). Associations between IQCODE and HMSE remained unchanged after removing the three items with the highest levels of differential missingness (remembering addresses and telephone numbers, ability to work with familiar machines, ability to learn to use new gadget or machine).

Findings raise questions about the value of including items with high proportions of missingness, which may signal cultural irrelevance, while removing them did not affect criterion validity.

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.

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.

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).

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.

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.

To characterize participants lost to follow-up which can be useful in the study design and interpretation of results.

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.

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.

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.

To assess independent and joint effects of pairs of vascular and cardiometabolic risk factors (VCMRFs) in relation to risk of all-cause dementia.

Population-based longitudinal cohort study of cognitive impairment. We used an algorithm to select pairs of VCMRFs and tested their joint effects in time-dependent Cox models. We used attributable proportions (AP) to measure the proportion of risk from interactions beyond any additive effect.

Economically depressed small-town population.

Adults age 65+ years with up to 10 yearly study visits (N=1701, median (Q1, Q3) age, 78 (71.0, 83.0), 62.3% female, 94.9% white).

Among 1701 participants free from prevalent dementia with at least one follow-up visit, 109 developed incident all-cause dementia. In pairings of APOE*4 with hypertension (HTN) and congestive heart failure (CHF), the variables contributed independently and additively to all-cause dementia risk. In pairings of APOE*4 with stroke and stroke with CHF, the variables demonstrated independent contributions to all-cause dementia risk; their joint effects showed excess detriment demonstrating synergistic interactions (joint HR [95% CI]: 28.33 [6.74, 119.01] and 50.30 [14.57, 173.57] respectively, fully adjusted models). Physical activity (PA) was independently associated with lower all-cause dementia risk when paired with APOE*4, stroke, and CHF in unadjusted models; these associations did not survive covariate adjustment. The joint effect of low PA and APOE*4 was associated with additively increased all-cause dementia risk (joint HR [95% CI]: 4.61 [2.07, 10.23], fully adjusted model).

Reduction of VCMRFs, including low PA, could be valuable for dementia prevention, especially among APOE*4 carriers.

Evidence suggests that semantic interference may be a sensitive indicator of early dementia. We examined the utility of the Semantic Interference Test (SIT), a cognitive stress memory paradigm which taps proactive and retroactive semantic interference, for predicting progression from mild cognitive impairment (MCI) to dementia in both a clinical and a population-based sample.

Participants with MCI in the clinical (n = 184) and population-based (n = 435) samples were followed for up to four years. We employed receiver operating characteristic (ROC) methods to establish optimal thresholds for four different SIT indices. Threshold performance was compared in the two samples using logistic and Cox proportional hazard regression models.

Within four years, 42 (22.8%) MCI individuals in the clinical sample and 45 (10.3%) individuals in the population-based sample progressed to dementia. Overall classification accuracy of SIT thresholds ranged from 61.4% to 84.8%. Different subtests of the SIT had slightly different performance characteristics in the two samples. However, regression models showed that thresholds established in the clinical sample performed similarly in the population sample before and after adjusting for demographics and other baseline neuropsychological test scores.

Despite differences in demographic composition and progression rates, baseline SIT scores predicted progression from MCI to dementia similarly in both samples. Thresholds that best predicted progression were slightly below thresholds established for distinguishing between amnestic MCI and cognitively normal subjects in clinical practice. This confirms the utility of the SIT in both clinical and population-based samples and establishes thresholds most predictive of progression of individuals with MCI.

Previous research regarding anxiety as a predictor of future cognitive decline in older adults is limited and inconsistent. We examined the independent relationship between anxiety symptoms and subsequent cognitive decline.

We included 2,818 community-dwelling older men (mean age = 76.1, SD ±5.3 years) who were followed on an average for 3.4 years. We assessed anxiety symptoms at baseline using the Goldberg Anxiety Scale (GAS; range = 0–9). We assessed cognitive function at baseline and at two subsequent visits using the Modified Mini-Mental State Examination (3MS; global cognition) and the Trails B test (executive function).

At baseline, there were 690 (24%) men with mild anxiety symptoms (GAS 1–4) and 226 (8%) men with moderate/severe symptoms (GAS 5–9). Men with anxiety symptoms were more likely to have depressed mood, poor sleep, more chronic medical conditions, and more impairment in activities of daily living compared to those with no anxiety symptoms. Compared to those with no anxiety symptoms at baseline, men with any anxiety symptoms were more likely to have substantial worsening in Trails B completion time (OR = 1.56, 95% CI 1.19, 2.05). The association was attenuated after adjusting for potential confounders, including depression and poor sleep, but remained significant (OR = 1.40, 95% CI 1.04, 1.88).

In cognitively healthy older men, mild anxiety symptoms may potentially predict future decline in executive functioning. Anxiety is likely a manifestation of an underlying neurodegenerative process rather than a cause.

In many developed countries, cognitive functioning (as measured by neuropsychological tests) appears to be improving over time in the population at large, in parallel with the declining age-specific incidence of dementia. Here, we investigated cohort effects in the age-associated trajectories of verbal memory function in older adults. We sought to determine whether they varied by decade of birth and, if so, whether the change would be explained by increasing educational attainment.

Pooling data from two prospective US population-based studies between 1987 and 2015, we identified four birth cohorts born 1902–1911, 1912–1921, 1922–1931, and 1932–1943. Among these cohorts, we compared age-associated trajectories both of performance and of practice effects on immediate and delayed recall of a 10-item Word List. We used mixed effects models, first including birth cohorts and cohort X age interaction terms, and then controlling for education and education X age interaction.

We observed significant cohort effects in performance (baseline and age-associated trajectories) in both immediate recall and delayed recall, with function improving between the earliest- and latest-born cohorts. For both tests, we also observed cohort effects on practice effects with the highest levels in the latest-born cohorts. Including education in the models did not attenuate these effects.

In this longitudinal population study, across four decade-long birth cohorts, there were significant improvements in test performance and practice effects in verbal memory tests, not explained by education. Whether this reflects declining disease incidence or other secular trends awaits further investigation.

To describe covariates and patterns of late-life analgesic use in the rural, population-based MoVIES cohort from 1989 to 2002.

Secondary analysis of epidemiologic survey of elderly people conducted over six biennial assessment waves. Potential covariates of analgesic use included age, gender, depression, sleep, arthritis, smoking, alcohol, and general health status. Of the original cohort of 1,681, this sample comprised 1,109 individuals with complete data on all assessments. Using trajectory analysis, participants were characterized as chronic or non-chronic users of opioid and non-opioid analgesics. Multivariable regression was used to model predictors of chronic analgesic use.

The cohort was followed for mean (SD) 7.3 (2.7) years. Chronic use of opioid analgesics was reported by 7.2%, while non-opioid use was reported by 46.1%. In the multivariable model, predictors of chronic use of both opioid and non-opioid analgesics included female sex, taking ≥2 prescription medications, and “arthritis” diagnoses. Chronic opioid use was also associated with age 75–84 years; chronic non-opioid use was also associated with sleep continuity disturbance.

These epidemiological data confirm clinical observations and generate hypotheses for further testing. Future studies should investigate whether addressing sleep problems might lead to decreased use of non-opioid analgesics and possibly enhanced pain management.