Safety planning-type interventions (SPTIs) for patients at risk of suicide are often used in clinical practice, but it is unclear whether these interventions are effective.

This article reports on a meta-analysis of studies that have evaluated the effectiveness of SPTIs in reducing suicidal behaviour and ideation.

We searched Medline, EMBASE, PsycINFO, Web of Science and Scopus from their inception to 9 December 2019, for studies that compared an SPTI with a control condition and had suicidal behaviour or ideation as outcomes. Two researchers independently extracted the data. To assess suicidal behaviour, we used a random-effects model of relative risk based on a pooled measure of suicidal behaviour. For suicidal ideation, we calculated effect sizes with Hedges’ g. The study was registered at PROSPERO (registration number CRD42020129185).

Of 1816 unique abstracts screened, 6 studies with 3536 participants were eligible for analysis. The relative risk of suicidal behaviour among patients who received an SPTI compared with control was 0.570 (95% CI 0.408–0.795, P = 0.001; number needed to treat, 16). No significant effect was found for suicidal ideation.

To our knowledge, this is the first study to report a meta-analysis on SPTIs for suicide prevention. Results support the use of SPTIs to help preventing suicidal behaviour and the inclusion of SPTIs in clinical guidelines for suicide prevention. We found no evidence for an effect of SPTIs on suicidal ideation, and other interventions may be needed for this purpose.

Studies on neighbourhood characteristics and depression show equivocal results.

This large-scale pooled analysis examines whether urbanisation, socioeconomic, physical and social neighbourhood characteristics are associated with the prevalence and severity of depression.

Cross-sectional design including data are from eight Dutch cohort studies (n= 32 487). Prevalence of depression, either DSM-IV diagnosis of depressive disorder or scoring for moderately severe depression on symptom scales, and continuous depression severity scores were analysed. Neighbourhood characteristics were linked using postal codes and included (a) urbanisation grade, (b) socioeconomic characteristics: socioeconomic status, home value, social security beneficiaries and non-Dutch ancestry, (c) physical characteristics: air pollution, traffic noise and availability of green space and water, and (d) social characteristics: social cohesion and safety. Multilevel regression analyses were adjusted for the individual's age, gender, educational level and income. Cohort-specific estimates were pooled using random-effects analysis.

The pooled analysis showed that higher urbanisation grade (odds ratio (OR) = 1.05, 95% CI 1.01–1.10), lower socioeconomic status (OR = 0.90, 95% CI 0.87–0.95), higher number of social security beneficiaries (OR = 1.12, 95% CI 1.06–1.19), higher percentage of non-Dutch residents (OR = 1.08, 95% CI 1.02–1.14), higher levels of air pollution (OR = 1.07, 95% CI 1.01–1.12), less green space (OR = 0.94, 95% CI 0.88–0.99) and less social safety (OR = 0.92, 95% CI 0.88–0.97) were associated with higher prevalence of depression. All four socioeconomic neighbourhood characteristics and social safety were also consistently associated with continuous depression severity scores.

This large-scale pooled analysis across eight Dutch cohort studies shows that urbanisation and various socioeconomic, physical and social neighbourhood characteristics are associated with depression, indicating that a wide range of environmental aspects may relate to poor mental health.

None.

Major depressive disorder (MDD), represent a major source of risk for suicidality. However, knowledge about risk factors for future suicide attempts (SAs) within MDD is limited. The present longitudinal study examined a wide range of putative non-clinical risk factors (demographic, social, lifestyle, personality) and clinical risk factors (depressive and suicidal indicators) for future SAs among persons with MDD. Furthermore, we examined the relationship between a number of significant predictors and the incidence of a future SA.

Data are from 1713 persons (18–65 years) with a lifetime MDD at the baseline measurement of the Netherlands Study of Depression and Anxiety who were subsequently followed up 2, 4 and 6 years. SAs were assessed in the face-to-face measurements. Cox proportional hazard regression analyses were used to examine a wide range of possible non-clinical and clinical predictors for subsequent SAs during 6-year follow-up.

Over a period of 6 years, 3.4% of the respondents attempted suicide. Younger age, lower education, unemployment, insomnia, antidepressant use, a previous SA and current suicidal thoughts independently predicted a future SA. The number of significant risk factors (ranging from 0 to 7) linearly predicted the incidence of future SAs: in those with 0 predictors the SA incidence was 0%, which increased to 32% incidence in those with 6+ predictors.

Of the non-clinical factors, particularly socio-economic factors predicted a SA independently. Furthermore, preexisting suicidal ideation and insomnia appear to be important clinical risk factors for subsequent SA that are open to preventative intervention.

Which neighbourhood factors most consistently impact on depression and anxiety remains unclear. This study examines whether objectively obtained socioeconomic, physical and social aspects of the neighbourhood in which persons live are associated with the presence and severity of depressive and anxiety disorders.

Cross-sectional data are from the Netherlands Study of Depression and Anxiety including participants (n = 2980) with and without depressive and anxiety disorders in the past year (based on DSM-based psychiatric interviews). We also determined symptom severity of depression (Inventory of Depression Symptomatology), anxiety (Beck Anxiety Inventory) and fear (Fear Questionnaire). Neighbourhood characteristics comprised socioeconomic factors (socioeconomic status, home value, number of social security beneficiaries and percentage of immigrants), physical factors (air pollution, traffic noise and availability of green space and water) and social factors (social cohesion and safety). Multilevel regression analyses were performed with the municipality as the second level while adjusting for individual sociodemographic variables and household income.

Not urbanization grade, but rather neighbourhood socioecononomic factors (low socioeconomic status, more social security beneficiaries and more immigrants), physical factors (high levels of traffic noise) and social factors (lower social cohesion and less safety) were associated with the presence of depressive and anxiety disorders. Most of these neighbourhood characteristics were also associated with increased depressive and anxiety symptoms severity.

These findings suggest that it is not population density in the neighbourhood, but rather the quality of socioeconomic, physical and social neighbourhood characteristics that is associated with the presence and severity of affective disorders.

Inconsistent findings have been reported on the role of comorbid alcohol use disorders as risk factors for a persistent course of depressive and anxiety disorders.

To determine whether the course of depressive and/or anxiety disorders is conditional on the type (abuse or dependence) or severity of comorbid alcohol use disorders.

In a large sample of participants with current depression and/or anxiety (n = 1369) we examined whether the presence and severity of DSM-IV alcohol abuse or alcohol dependence predicted the 2-year course of depressive and/or anxiety disorders.

The persistence of depressive and/or anxiety disorders at the 2-year follow-up was significantly higher in those with remitted or current alcohol dependence (persistence 62% and 67% respectively), but not in those with remitted or current alcohol abuse (persistence 51% and 46% respectively), compared with no lifetime alcohol use disorder (persistence 53%). Severe (meeting six or seven diagnostic criteria) but not moderate (meeting three to five criteria) current dependence was a significant predictor as 95% of those in the former group still had a depressive and/or anxiety disorder at follow-up. This association remained significant after adjustment for severity of depression and anxiety, psychosocial factors and treatment factors.

Alcohol dependence, especially severe current dependence, is a risk factor for an unfavourable course of depressive and/or anxiety disorders, whereas alcohol abuse is not.

Past episodes of depressive or anxiety disorders and subthreshold symptoms have both been reported to predict the occurrence of depressive or anxiety disorders. It is unclear to what extent the two factors interact or predict these disorders independently.

To examine the extent to which history, subthreshold symptoms and their combination predict the occurrence of depressive (major depressive disorder, dysthymia) or anxiety disorders (social phobia, panic disorder, agoraphobia, generalised anxiety disorder) over a 2-year period.

This was a prospective cohort study with 1167 participants: the Netherlands Study of Depression and Anxiety. Anxiety and depressive disorders were determined with the Composite International Diagnostic Interview, subthreshold symptoms were determined with the Inventory of Depressive Symptomatology–Self Report and the Beck Anxiety Inventory.

Occurrence of depressive disorder was best predicted by a combination of a history of depression and subthreshold symptoms, followed by either one alone. Occurrence of anxiety disorder was best predicted by both a combination of a history of anxiety disorder and subthreshold symptoms and a combination of a history of depression and subthreshold symptoms, followed by any subthreshold symptoms or a history of any disorder alone.

A history and subthreshold symptoms independently predicted the subsequent occurrence of depressive or anxiety disorder. Together these two characteristics provide reasonable discriminative value. Whereas anxiety predicted the occurrence of an anxiety disorder only, depression predicted the occurrence of both depressive and anxiety disorders.