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There is an association between stress and dementia. However, less is known about dementia among persons with varied stress responses and sex differences in these associations. We used this population-based cohort study to examine dementia among persons with a range of clinician-diagnosed stress disorders, as well as the interaction between stress disorders and sex in predicting dementia, in Denmark from 1995 to 2011. This study included Danes aged 40 years or older with a stress disorder diagnosis (n = 47,047) and a matched comparison cohort (n = 232,141) without a stress disorder diagnosis with data from 1995 through 2011. Diagnoses were culled from national registries. We used Cox proportional hazards regression to estimate associations between stress disorders and dementia. Risk of dementia was higher for persons with stress disorders than for persons without such diagnosis; adjusted hazard ratios ranged from 1.6 to 2.8. There was evidence of an interaction between sex and stress disorders in predicting dementia, with a higher rate of dementia among men with stress disorders except posttraumatic stress disorder, for which women had a higher rate. Results support existing evidence of an association between stress and dementia. This study contributes novel information regarding dementia risk across a range of stress responses, and interactions between stress disorders and sex.

Studies have highlighted the potential importance of modeling interactions for suicide attempt prediction. This case-cohort study identified risk factors for suicide attempts among persons with depression in Denmark using statistical approaches that do (random forests) or do not (least absolute shrinkage and selection operator regression [LASSO]) model interactions. Cases made a nonfatal suicide attempt (n  = 6032) between 1995 and 2015. The comparison subcohort was a 5% random sample of all persons in Denmark on January 1, 1995 (n  = 11 963). We used random forests and LASSO for sex-stratified prediction of suicide attempts from demographic variables, psychiatric and somatic diagnoses, and treatments. Poisonings, psychiatric disorders, and medications were important predictors for both sexes. Area under the receiver-operating characteristic curve (AUC) values were higher in LASSO models (in men, 0.85, 95% CI, 0.84-0.86; in women, 0.89, 95% C, 0.88-0.90) than random forests (in men, 0.76, 95% CI, 0.74-0.78; in women, 0.79, 95% CI = 0.78-0.81). Automatic detection of interactions via random forests did not result in better model performance than LASSO models that did not model interactions. Due to the complex nature of psychiatric comorbidity and suicide, modeling interactions may not always be the optimal statistical approach to enhancing suicide attempt prediction in high-risk samples. This article is part of a Special Collection on Mental Health. [ABSTRACT FROM AUTHOR]

The article responds to comments on a 2021 study which show that psychiatric medications, and certain social variables and physical health diagnoses predict nonfatal suicide attempts. Topics covered include the balanced quality of the study's source population, the reasons for non-emphasis on positive predictive value (PPV) of risk classification, and the complex task of using machine learning methods in predicting suicidal behavior. Also noted is the need for wider studies on the subject.