Suicide is a major public health problem and a cause of premature mortality. With a view to prevention, a great deal of research has been devoted to the determinants of suicide, focusing mostly on individual risk factors, particularly depression. In addition to causes intrinsic to the individual, the social environment has also been widely studied, particularly social isolation. This paper examines the social dimension of suicide etiology through a review of the literature on the relationship between suicide and social isolation.

Medline searches via PubMed and PsycINFO were conducted. The keywords were “suicid*” AND “isolation.”

Of the 2,684 articles initially retrieved, 46 were included in the review.

Supported by proven theoretical foundations, mainly those developed by E. Durkheim and T. Joiner, a large majority of the articles included endorse the idea of a causal relationship between social isolation and suicide, and conversely, a protective effect of social support against suicide. Moreover, the association between suicide and social isolation is subject to variations related to age, gender, psychopathology, and specific circumstances. The social etiology of suicide has implications for intervention and future research.

Suicide is one of the main preventable causes of death. Artificial intelligence (AI) could improve methods for assessing suicide risk. The objective of this review is to assess the potential of AI in identifying patients who are at risk of attempting suicide.

A systematic review of the literature was conducted on PubMed, EMBASE, and SCOPUS databases, using relevant keywords.

Thanks to this research, 296 studies were identified. Seventeen studies, published between 2014 and 2020 and matching inclusion criteria, were selected as relevant. Included studies aimed at predicting individual suicide risk or identifying at-risk individuals in a specific population. The AI performance was overall good, although variable across different algorithms and application settings.

AI appears to have a high potential for identifying patients at risk of suicide. The precise use of these algorithms in clinical situations, as well as the ethical issues it raises, remain to be clarified.

This study sought to identify coronavirus disease 2019 (COVID-19) risk communication materials distributed in Jamaica to mitigate the effects of the disease outbreak. It also sought to explore the effects of health risk communication on vulnerable groups in the context of the pandemic.

A qualitative study was conducted, including a content analysis of health risk communications and in-depth interviews with 35 purposively selected elderly, physically disabled, persons with mental health disorders, representatives of government agencies, advocacy and service groups, and caregivers of the vulnerable. Axial coding was applied to data from the interviews, and all data were analyzed using the constant comparison technique.

Twelve of the 141 COVID-19 risk communication messages directly targeted the vulnerable. All participants were aware of the relevant risk communication and largely complied. Barriers to messaging awareness and compliance included inappropriate message medium for the deaf and blind, rural location, lack of Internet service or digital devices, limited technology skills, and limited connection to agencies that serve the vulnerable.

The vulnerable are at increased risk in times of crisis. Accessibility of targeted information was inadequate for universal access to health information and support for vulnerable persons regardless of location and vulnerability.

Alcohol use disorder (AUD) and schizophrenia (SCZ) frequently co-occur, and large-scale genome-wide association studies (GWAS) have identified significant genetic correlations between these disorders.

We used the largest published GWAS for AUD (total cases = 77 822) and SCZ (total cases = 46 827) to identify genetic variants that influence both disorders (with either the same or opposite direction of effect) and those that are disorder specific.

We identified 55 independent genome-wide significant single nucleotide polymorphisms with the same direction of effect on AUD and SCZ, 8 with robust effects in opposite directions, and 98 with disorder-specific effects. We also found evidence for 12 genes whose pleiotropic associations with AUD and SCZ are consistent with mediation via gene expression in the prefrontal cortex. The genetic covariance between AUD and SCZ was concentrated in genomic regions functional in brain tissues (p = 0.001).

Our findings provide further evidence that SCZ shares meaningful genetic overlap with AUD.

Clinically normal older adults (52–92 years old) were followed longitudinally for up to 8 years after completing a memory paradigm at baseline [Story Recall Test (SRT)] that assessed delayed recall at 30 min and 1 week. Subsets of the cohort underwent neuroimaging (N = 134, mean age = 75) and neuropsychological testing (N = 178–207, mean ages = 74–76) at annual study visits occurring approximately 15–18 months apart. Mixed-effects regression models evaluated if baseline SRT performance predicted longitudinal changes in gray matter volumes and cognitive composite scores, controlling for demographics.

Worse SRT 1-week recall was associated with more precipitous rates of longitudinal decline in medial temporal lobe volumes (p = .037), episodic memory (p = .003), and executive functioning (p = .011), but not occipital lobe or total gray matter volumes (demonstrating neuroanatomical specificity; p > .58). By contrast, SRT 30-min recall was only associated with longitudinal decline in executive functioning (p = .044).

Memory paradigms that capture longer-term recall may be particularly sensitive to age-related medial temporal lobe changes and neurodegenerative disease trajectories. (JINS, 2020, xx, xx-xx)

Rey’s Auditory Verbal Learning Test (AVLT) is a widely used word list memory test. We update normative data to include adjustment for verbal memory performance differences between men and women and illustrate the effect of this sex adjustment and the importance of excluding participants with mild cognitive impairment (MCI) from normative samples.

This study advances the Mayo’s Older Americans Normative Studies (MOANS) by using a new population-based sample through the Mayo Clinic Study of Aging, which randomly samples residents of Olmsted County, Minnesota, from age- and sex-stratified groups. Regression-based normative T-score formulas were derived from 4428 cognitively unimpaired adults aged 30–91 years. Fully adjusted T-scores correct for age, sex, and education. We also derived T-scores that correct for (1) age or (2) age and sex. Test-retest reliability data are provided.

From raw score analyses, sex explained a significant amount of variance in performance above and beyond age (8–10%). Applying original age-adjusted MOANS norms to the current sample resulted in significantly fewer-than-expected participants with low delayed recall performance, particularly in women. After application of new T-scores adjusted only for age, even in normative data derived from this sample, these age-adjusted T-scores showed scores <40 T occurred more frequently among men and less frequently among women relative to T-scores that also adjusted for sex.

Our findings highlight the importance of using normative data that adjust for sex with measures of verbal memory and provide new normative data that allow for this adjustment for the AVLT.

To identify predominant dietary patterns in four African populations and examine their association with obesity.

Cross-sectional study.

We used data from the Africa/Harvard School of Public Health Partnership for Cohort Research and Training (PaCT) pilot study established to investigate the feasibility of a multi-country longitudinal study of non-communicable chronic disease in sub-Saharan Africa. We applied principal component analysis to dietary intake data collected from an FFQ developed for PaCT to ascertain dietary patterns in Tanzania, South Africa, and peri-urban and rural Uganda. The sample consisted of 444 women and 294 men.

We identified two dietary patterns: the Mixed Diet pattern characterized by high intakes of unprocessed foods such as vegetables and fresh fish, but also cold cuts and refined grains; and the Processed Diet pattern characterized by high intakes of salad dressing, cold cuts and sweets. Women in the highest tertile of the Processed Diet pattern score were 3·00 times more likely to be overweight (95 % CI 1·66, 5·45; prevalence=74 %) and 4·24 times more likely to be obese (95 % CI 2·23, 8·05; prevalence=44 %) than women in this pattern’s lowest tertile (both P<0·0001; prevalence=47 and 14 %, respectively). We found similarly strong associations in men. There was no association between the Mixed Diet pattern and overweight or obesity.

We identified two major dietary patterns in several African populations, a Mixed Diet pattern and a Processed Diet pattern. The Processed Diet pattern was associated with obesity.

Little is known about the association of cortical Aβ with depression and anxiety among cognitively normal (CN) elderly persons.

We conducted a cross-sectional study derived from the population-based Mayo Clinic Study of Aging in Olmsted County, Minnesota; involving CN persons aged ≥ 60 years that underwent PiB-PET scans and completed Beck Depression Inventory-II (BDI-II) and Beck Anxiety Inventory (BAI). Cognitive diagnosis was made by an expert consensus panel. Participants were classified as having abnormal (≥1.4; PiB+) or normal PiB-PET (<1.4; PiB−) using a global cortical to cerebellar ratio. Multi-variable logistic regression analyses were performed to calculate odds ratios (OR) and 95% confidence intervals (95% CI) after adjusting for age and sex.

Of 1,038 CN participants (53.1% males), 379 were PiB+. Each one point symptom increase in the BDI (OR = 1.03; 1.00–1.06) and BAI (OR = 1.04; 1.01–1.08) was associated with increased odds of PiB-PET+. The number of participants with BDI > 13 (clinical depression) was greater in the PiB-PET+ than PiB-PET- group but the difference was not significant (OR = 1.42; 0.83–2.43). Similarly, the number of participants with BAI > 10 (clinical anxiety) was greater in the PiB-PET+ than PiB-PET− group but the difference was not significant (OR = 1.77; 0.97–3.22).

As expected, depression and anxiety levels were low in this community-dwelling sample, which likely reduced our statistical power. However, we observed an informative albeit weak association between increased BDI and BAI scores and elevated cortical amyloid deposition. This observation needs to be tested in a longitudinal cohort study.