Insomnia and the incidence, recurrence and persistence of common mental disorders: Sex-differences in the general population.

Insomnia is common throughout the population and thought to be a risk factor for mental disorders. We assessed the association of insomnia symptoms with incidence, recurrence and persistence of mood, anxiety and substance use disorders. In 4007 participants (55 % women, mean age 51.0 ± 12.3) of the population-based Netherlands Mental Health Survey and Incidence Study (NEMESIS), having insomnia symptoms increased the odds of developing, recurring and persisting mood disorders, mostly in men. Insomnia only associated with recurring anxiety disorders, particularly in women, and not with substance use disorders. Treating insomnia may aid recovery and prevention of mental disorders, particularly mood disorders.

Validity of the five-item mental health inventory for screening current mood and anxiety disorders in the general population.

OBJECTIVES: The Mental Health Inventory (MHI-5) is frequently used as a screener for mood and anxiety disorders. However, few population-based studies have validated it against a diagnostic instrument assessing disorders following current diagnostic criteria. METHODS: Within the third Netherlands Mental Health Survey and Incidence Study (NEMESIS-3), a representative population-based study of adults (N = 6194; age: 18-75 years), the MHI-5 was used to measure general mental ill-health in the past month. Presence of mood (major depressive disorder, persistent depressive disorder, or bipolar disorder) and anxiety disorders (panic disorder, agoraphobia, social phobia, or generalized anxiety disorder) in the past month was assessed with a slightly modified version of the Composite International Diagnostic Interview 3.0 per the Diagnostic and Statistical Manual of Mental disorders-5. RESULTS: The MHI-5 was good to excellent at distinguishing people with and without a mood disorder, an anxiety disorder, and any mood or anxiety disorder. The cut-off value associated with the highest sensitivity and highest specificity for mood disorder was ≤68, and ≤76 for an anxiety disorder or any mood or anxiety disorder. CONCLUSIONS: The MHI-5 can identify individuals at high risk of a current mood or anxiety disorder in the general population when diagnostic interviews are too time consuming.

Exposome-Wide Association Study of Body Mass Index Using a Novel Meta-Analytical Approach for Random Forest Models.

BACKGROUND: Overweight and obesity impose a considerable individual and social burden, and the urban environments might encompass factors that contribute to obesity. Nevertheless, there is a scarcity of research that takes into account the simultaneous interaction of multiple environmental factors. OBJECTIVES: Our objective was to perform an exposome-wide association study of body mass index (BMI) in a multicohort setting of 15 studies. METHODS: Studies were affiliated with the Dutch Geoscience and Health Cohort Consortium (GECCO), had different population sizes (688-141,825), and covered the entire Netherlands. Ten studies contained general population samples, others focused on specific populations including people with diabetes or impaired hearing. BMI was calculated from self-reported or measured height and weight. Associations with 69 residential neighborhood environmental factors (air pollution, noise, temperature, neighborhood socioeconomic and demographic factors, food environment, drivability, and walkability) were explored. Random forest (RF) regression addressed potential nonlinear and nonadditive associations. In the absence of formal methods for multimodel inference for RF, a rank aggregation-based meta-analytic strategy was used to summarize the results across the studies. RESULTS: Six exposures were associated with BMI: five indicating neighborhood economic or social environments (average home values, percentage of high-income residents, average income, livability score, share of single residents) and one indicating the physical activity environment (walkability in 5-km buffer area). Living in high-income neighborhoods and neighborhoods with higher livability scores was associated with lower BMI. Nonlinear associations were observed with neighborhood home values in all studies. Lower neighborhood home values were associated with higher BMI scores but only for values up to €300,000. The directions of associations were less consistent for walkability and share of single residents. DISCUSSION: Rank aggregation made it possible to flexibly combine the results from various studies, although between-study heterogeneity could not be estimated quantitatively based on RF models. Neighborhood social, economic, and physical environments had the strongest associations with BMI. https://doi.org/10.1289/EHP13393.