We examined the association between perceived discrimination and the risk of cognitive impairment with no dementia (CIND) and Alzheimer’s disease and related dementias (ADRD) while considering the potential effects of nativity status.

A prospective analysis of discrimination and nativity status with dementia and cognitive impairment was conducted among Latinx adults aged 51 years and older who participated in the Health and Retirement Study.

A national representative sample.

A sample of 1,175 Latinx adults aged 51 years and older.

Demographics, cognitive functioning, perceived discrimination, and nativity status (US-born vs. non-US born) were assessed. Traditional survival analysis methods (Fine and gray models) were used to account for the semi-competing risk of death with up to 10 years of follow-up.

According to our results, neither everyday discrimination nor nativity status on their own had a statistically significant association with CIND/ADRD; however, non-US-born Latinx adults who reported no discrimination had a 42% lower risk of CIND/ADRD (SHR = 0.58 [0.41, 0.83], p = .003) than US-born adults.

These results highlight the need for healthcare providers to assess for discrimination and provide support and resources for those experiencing discrimination. It also highlights the need for better policies that address discrimination and reduce health disparities.

Social connections have a significant impact on health across age groups, including older adults. Loneliness and social isolation are known risk factors for Alzheimer’s disease and related dementias (ADRD). Yet, we did not find a review focused on meta-analyses and systematic reviews of studies that had examined associations of social connections with cognitive decline and trials of technology-based and other social interventions to enhance social connections in people with ADRD.

We conducted a scoping review of 11 meta-analyses and systematic reviews of social connections as possible determinants of cognitive decline in older adults with or at risk of developing ADRD. We also examined eight systematic reviews of technology-based and other social interventions in persons with ADRD.

The strongest evidence for an association of social connections with lower risk of cognitive decline was related to social engagement and social activities. There was also evidence linking social network size to cognitive function or cognitive decline, but it was not consistently significant. A number of, though not all, studies reported a significant association of marital status with risk of ADRD. Surprisingly, evidence showing that social support reduces the risk of ADRD was weak. To varying degrees, technology-based and other social interventions designed to reduce loneliness in people with ADRD improved social connections and activities as well as quality of life but had no significant impact on cognition. We discuss strengths and limitations of the studies included.

Social engagement and social activities seem to be the most consistent components of social connections for improving cognitive health among individuals with or at risk for ADRD. Socially focused technology-based and other social interventions aid in improving social activities and connections and deserve more research.

Nursing home (NH) residents with dementia is exposed to high rates of psychotropic prescriptions. Our objectives were to: (1) pool the prevalence estimates of psychotropic polypharmacy from the existing literature and (2) examine potentially influential factors that are related to a higher or lower prevalence.

Meta-analysis of data collected from randomized trials, quasi-experimental, prospective or retrospective cohort, and cross-sectional studies. English-language searches of PubMed and PsycINFO were completed by November 2020. Included studies reported prevalence estimates of psychotropic polypharmacy (i.e. defined as either two-or-more or three-or-more medications concurrently) in NH residents with dementia.

NH residents with dementia.

Random-effects models were used to pool the prevalence of psychotropic polypharmacy in NH residents with dementia across studies. Estimates were provided for both two-or-more and three-or-more concurrent medications. Heterogeneity and publication bias were measured. Meta-regression examined the influence of the percentage of the sample who were male, mean age of the sample, geographic region (continent), sample size, and study year on the prevalence of psychotropic polypharmacy.

Twenty-five unique articles were included comprising medications data from 92,370 NH residents with dementia in 12 countries. One-in-three (33%, [95% CI: 28%, 39%]) NH residents with dementia received two-or-more psychotropic medications concurrently. One-in-eight (13%, [95% CI: 10%, 17%]) received three-or-more psychotropic medications concurrently. Estimates were highly variable across both definitions of psychotropic polypharmacy (p < 0.001). Among study-level demographics, geographic region, sample size, or study year, only male sex was associated with greater use of two-or-more psychotropic medications (Unadjusted OR = 1.02, p = 0.006; Adjusted OR = 1.04, p = 0.07).

Psychotropic polypharmacy is common among NH residents with dementia. Identifying the causes of utilization and the effects on resident health and well-being should be prioritized by federal entities seeking to improve NH quality.

To compare cognitive phenotypes of participants with subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI), estimate progression to MCI/dementia by phenotype and assess classification error with machine learning.

Dataset consisted of 163 participants with SCD and 282 participants with aMCI from the Czech Brain Aging Study. Cognitive assessment included the Uniform Data Set battery and additional tests to ascertain executive function, language, immediate and delayed memory, visuospatial skills, and processing speed. Latent profile analyses were used to develop cognitive profiles, and Cox proportional hazards models were used to estimate risk of progression. Random forest machine learning algorithms reported cognitive phenotype classification error.

Latent profile analysis identified three phenotypes for SCD, with one phenotype performing worse across all domains but not progressing more quickly to MCI/dementia after controlling for age, sex, and education. Three aMCI phenotypes were characterized by mild deficits, memory and language impairment (dysnomic aMCI), and severe multi-domain aMCI (i.e., deficits across all domains). A dose–response relationship between baseline level of impairment and subsequent risk of progression to dementia was evident for aMCI profiles after controlling for age, sex, and education. Machine learning more easily classified participants with aMCI in comparison to SCD (8% vs. 21% misclassified).

Cognitive performance follows distinct patterns, especially within aMCI. The patterns map onto risk of progression to dementia.