The contribution of suicide to maternal mortality: A nationwide population-based cohort study.

OBJECTIVE: To identify the incidence and characteristics of maternal suicide. DESIGN: Nationwide population-based cohort study. SETTING: The Netherlands, 2006-2020. POPULATION: Women who died during pregnancy or within 1 year postpartum, and a reference population of women aged 25-45 years. METHODS: The Cause of Death Register and Medical Birth Register were linked to identify women who died within 1 year postpartum. Data were combined with deaths reported to the Audit Committee for Maternal Mortality and Morbidity (ACMMM), which performs confidential enquiries. Maternal suicides were compared with a previous period (1996-2005). Risk factors were obtained by combining vital statistics databases. MAIN OUTCOME MEASURES: Comparison of incidence and proportion of maternal suicides among all maternal deaths over time, sociodemographic and patient-related risk factors and underreporting of postpartum suicides. RESULTS: The maternal suicide rate remained stable with 68 deaths: 2.6 per 100 000 live births in 2006-2020 versus 2.5 per 100 000 in 1996-2005. The proportion of suicides among all maternal deaths increased from 18% to 28%. Most suicides occurred throughout the first year postpartum (64/68); 34 (53%) of the women who died by suicide postpartum were primiparous. Compared with mid-level, low educational level was a risk factor (odds ratio 4.2, 95% confidence interval 2.3-7.9). Of 20 women reported to the ACMMM, 11 (55%) had a psychiatric history and 13 (65%) were in psychiatric treatment at the time of death. Underreporting to ACMMM was 78%. CONCLUSIONS: Although the overall maternal mortality ratio declined, maternal suicides did not and are now the leading cause of maternal mortality if late deaths up to 1 year postpartum are included. Data collection and analysis of suicides must improve.

Identifying populations at ultra-high risk of suicide using a novel machine learning method.

BACKGROUND: Targeted interventions for suicide prevention rely on adequate identification of groups at elevated risk. Several risk factors for suicide are known, but little is known about the interactions between risk factors. Interactions between risk factors may aid in detecting more specific sub-populations at higher risk. METHODS: Here, we use a novel machine learning heuristic to detect sub-populations at ultra high-risk for suicide based on interacting risk factors. The data-driven and hypothesis-free model is applied to investigate data covering the entire population of the Netherlands. FINDINGS: We found three sub-populations with extremely high suicide rates (i.e. >50 suicides per 100,000 person years, compared to 12/100,000 in the general population), namely: (1) people on unfit for work benefits that were never married, (2) males on unfit for work benefits, and (3) those aged 55-69 who live alone, were never married and have a relatively low household income. Additionally, we found two sub-populations where the rate was higher than expected based on individual risk factors alone: widowed males, and people aged 25-39 with a low level of education. INTERPRETATION: Our model is effective at finding ultra-high risk groups which can be targeted using sub-population level interventions. Additionally, it is effective at identifying high-risk groups that would not be considered risk groups based on conventional risk factor analysis.

Identifying socio-demographic risk factors for suicide using data on an individual level.

BACKGROUND: Suicide is a complex issue. Due to the relative rarity of the event, studies into risk factors are regularly limited by sample size or biased samples. The aims of the study were to find risk factors for suicide that are robust to intercorrelation, and which were based on a large and unbiased sample. METHODS: Using a training set of 5854 suicides and 596,416 control cases, we fit a logistic regression model and then evaluate the performance on a test set of 1425 suicides and 594,893 control cases. The data used was micro-data of Statistics Netherlands (CBS) with data on each inhabitant of the Netherlands. RESULTS: Taking the effect of possible correlating risk factors into account, those with a higher risk for suicide are men, middle-aged people, people with low income, those living alone, the unemployed, and those with mental or physical health problems. People with a lower risk are the highly educated, those with a non-western immigration background, and those living with a partner. CONCLUSION: We confirmed previously known risk factors such as male gender, middle-age, and low income and found that they are risk factors that are robust to intercorrelation. We found that debt and urbanicity were mostly insignificant and found that the regional differences found in raw frequencies are mostly explained away after correction of correlating risk factors, indicating that these differences were primarily caused due to the differences in the demographic makeup of the regions. We found an AUC of 0.77, which is high for a model predicting suicide death and comparable to the performance of deep learning models but with the benefit of remaining explainable.

The effect of local Suicide Prevention Action Networks (SUPRANET) on stigma, taboo and attitudes towards professional help-seeking: an exposure-response analysis.

PURPOSE: In 2017, the European Alliance against Depression (EAAD) programme was introduced in the Netherlands through the creation of six local Suicide Prevention Action Networks (SUPRANET Community). This programme consists of interventions on four levels: (1) a public awareness campaign, (2) training local gatekeepers, (3) targeting high-risk persons in the community and (4) training of primary care professionals. This study aims to gain insight into the effectiveness of the SUPRANET programme on attitudinal changes in the general public by studying the exposure-response relationship. METHODS: A repeated cross-sectional design, using general population surveys to measure key variables over time. The surveys were conducted in the six intervention regions (N = 2586) and in the Netherlands as a whole as a control region (N = 4187) and include questions on socio-demographic variables, brand awareness of the Dutch helpline, perceived taboo on suicide, attitudes towards depression and help-seeking. To examine the exposure-response relationship, regions were differentiated into 3 groups: low, medium and high exposure of the SUPRANET programme. RESULTS: The results revealed that respondents in the intervention regions considered professional help to be more valuable and were more likely to be familiar with the Dutch helpline than respondents in the control region. In the exposure-response analyses, the grading of effects was too small to reach statistical significance. CONCLUSION: Our study provides the first evidence for the effectiveness of the SUPRANET Community programme on creating attitudinal change in the general public.

Who didn't consult the doctor? Understanding sociodemographic factors in relation to health care uptake before suicide.

OBJECTIVE: This study aimed to establish differences between suicide decedents and a reference population across various health care settings. METHODS: This population-wide registration study combined death statistics, sociodemographic data and health care data from Statistics Netherlands. From 2010 to 2016, 12,015 suicide cases and a random reference group of 132,504 were included and assigned to one of the three health care settings; mental health (MH) care, primary care or no care. Logistic regression analyses were performed to determine differences in suicide risk factors across settings. RESULTS: In the 1-2 year period before suicide, 52% of the suicide decedents received MH care, 41% received GP care only and 7% received neither. Although sociodemographic factors showed significant differences across settings, the suicide risk profiles were not profoundly distinctive. A decreasing trend in suicide risk across health care settings became apparent for male gender, income level and being in a one-person or one-parent household, whereas for other factors (middle and older age, non-Western migration background, couples without children and people living in more sparsely populated areas), risk of suicide increased when health care setting became more specialized. LIMITATIONS: Because of the data structure, 18 months of suicide decedents' health care use were compared with two years health care use of the reference group, which likely led to an underestimation of the reported differences. CONCLUSION: Although there are differences between suicide decedents and a reference group across health care settings, these are not sufficiently distinctive to advocate for a setting-specific approach to suicide prevention.

The impact of a suicide prevention awareness campaign on stigma, taboo and attitudes towards professional help-seeking.

BACKGROUND: In 2017, the European Alliance against Depression (EAAD) was introduced in The Netherlands through the creation of six Suicide Prevention Action Networks (SUPRANET Community). The intervention was launched with a national suicide prevention awareness campaign. This campaign aims to encourage the general public to talk about suicide. This study aimed to gain insight into the effectiveness of the campaign in achieving attitudinal change in the general public, as stigmas related to mental health disorders and -services are an important reason for insufficient help-seeking. METHODS: A repeated cross-section design, using general population surveys (N = 6,773) to measure key variables over time. The survey includes questions on socio-demographic variables, campaign visibility, brand awareness of the Dutch helpline, perceived taboo on suicide, attitudes towards depression and help-seeking. RESULTS: The public awareness campaign was predominantly visible among the younger generation. Respondents who indicated having seen the public awareness campaign showed more openness towards seeking professional help and were considerably more likely to be familiar with the Dutch helpline than those who reported not having seen the campaign. Campaign awareness also seemed to relate to a higher perceived taboo on suicide and a lower estimation of the value of professional help. LIMITATIONS: Due to the nature of the intervention, we used a quasi-experimental design. Self-report can lead to desirability bias, especially when measuring attitudes and stigmas. CONCLUSIONS: Our results strengthen the idea that awareness campaigns can make a contribution to informing the general public about mental health services and improving help-seeking behaviour.

Demographic Risk Factors for Suicide among Youths in The Netherlands.

In 2000 to 2016 the highest number of suicides among Dutch youths under 20 in any given year was 58 in 2013. In 2017 this number increased to 81 youth suicides. To get more insight in what types of youths died by suicide, particularly in recent years (2013-2017) we looked at micro-data of Statistics Netherlands and counted suicides among youths till 23, split out along gender, age, regions, immigration background and place in household and compared this to the general population of youths in the Netherlands. We also compared the demographics of young suicide victims to those of suicide victims among the population as a whole. We found higher suicide rates among male youths, older youths, those of Dutch descent and youths living alone. These differences were generally smaller than in the population as a whole. There were also substantial geographical differences between provinces and healthcare regions. The method of suicide is different in youth compared to the population as a whole: relatively more youth suicides by jumping or lying in front of a moving object and relatively less youth suicides by autointoxication or drowning, whereas the most frequent method of suicide among both groups is hanging or suffocation.