Predicting the Population Risk of Suicide Using Routinely Collected Health Administrative Data in Quebec, Canada: Model-Based Synthetic Estimation Study.

BACKGROUND: Suicide is a significant public health issue. Many risk prediction tools have been developed to estimate an individual's risk of suicide. Risk prediction models can go beyond individual risk assessment; one important application of risk prediction models is population health planning. Suicide is a result of the interaction among the risk and protective factors at the individual, health care system, and community levels. Thus, policy and decision makers can play an important role in suicide prevention. However, few prediction models for the population risk of suicide have been developed. OBJECTIVE: This study aims to develop and validate prediction models for the population risk of suicide using health administrative data, considering individual-, health system-, and community-level predictors. METHODS: We used a case-control study design to develop sex-specific risk prediction models for suicide, using the health administrative data in Quebec, Canada. The training data included all suicide cases (n=8899) that occurred from January 1, 2002, to December 31, 2010. The control group was a 1% random sample of living individuals in each year between January 1, 2002, and December 31, 2010 (n=645,590). Logistic regression was used to develop the prediction models based on individual-, health care system-, and community-level predictors. The developed model was converted into synthetic estimation models, which concerted the individual-level predictors into community-level predictors. The synthetic estimation models were directly applied to the validation data from January 1, 2011, to December 31, 2019. We assessed the performance of the synthetic estimation models with four indicators: the agreement between predicted and observed proportions of suicide, mean average error, root mean square error, and the proportion of correctly identified high-risk regions. RESULTS: The sex-specific models based on individual data had good discrimination (male model: C=0.79; female model: C=0.85) and calibration (Brier score for male model 0.01; Brier score for female model 0.005). With the regression-based synthetic models applied in the validation data, the absolute differences between the synthetic risk estimates and observed suicide risk ranged from 0% to 0.001%. The root mean square errors were under 0.2. The synthetic estimation model for males correctly predicted 4 of 5 high-risk regions in 8 years, and the model for females correctly predicted 4 of 5 high-risk regions in 5 years. CONCLUSIONS: Using linked health administrative databases, this study demonstrated the feasibility and the validity of developing prediction models for the population risk of suicide, incorporating individual-, health system-, and community-level variables. Synthetic estimation models built on routinely collected health administrative data can accurately predict the population risk of suicide. This effort can be enhanced by timely access to other critical information at the population level.

A descriptive review of variable selection methods in four epidemiologic journals: there is still room for improvement.

A review of epidemiological papers conducted in 2009 concluded that several studies employed variable selection methods susceptible to introduce bias and yield inadequate inferences. Many new confounder selection methods have been developed since then. The goal of the study was to provide an updated descriptive portrait of which variable selection methods are used by epidemiologists for analyzing observational data. Studies published in four major epidemiological journals in 2015 were reviewed. Only articles concerned with a predictive or explicative objective and reporting on the analysis of individual data were included. Method(s) employed for selecting variables were extracted from retained articles. A total of 975 articles were retrieved and 299 met eligibility criteria, 292 of which pursued an explicative objective. Among those, 146 studies (50%) reported using prior knowledge or causal graphs for selecting variables, 34 (12%) used change in effect estimate methods, 26 (9%) used stepwise approaches, 16 (5%) employed univariate analyses, 5 (2%) used various other methods and 107 (37%) did not provide sufficient details to allow classification (more than one method could be employed in a single article). Despite being less frequent than in the previous review, stepwise and univariable analyses, which are susceptible to introduce bias and produce inadequate inferences, were still prevalent. Moreover, 37% studies did not provide sufficient details to assess how variables were selected. We thus believe there is still room for improvement in variable selection methods used by epidemiologists and in their reporting.

Assessment of the healthy worker survivor effect in the relationship between psychosocial work-related factors and hypertension.

OBJECTIVES: The healthy worker survivor effect (HWSE) usually leads to underestimation of the effects of harmful occupational exposures. HWSE is characterised by the concomitance of three associations: (1) job status-subsequent exposure, (2) job status-disease and (3) previous exposure-job status. No study has reported the coexistence of these associations in the relationship between psychosocial work-related factors and health. We assessed if HWSE is present when measuring the effects of cumulative exposure to psychosocial work-related factors on the prevalence of hypertension in white-collar workers. METHODS: Data were obtained from two timepoints (1991-1993 at baseline and 1999-2001 at follow-up) of a prospective cohort study. At baseline, the population was composed of 9188 white-collar employees (women: 49.9%) in Quebec City. Job strain as psychosocial work-related factor and blood pressure were measured using validated methods. Job status (retirees vs employees) at follow-up was self-reported. Multiple multilevel robust Poisson regressions were used to estimate prevalence ratios of hypertension and risk ratios of retirement separately by gender. We performed multiple imputations to control selection bias due to missing values. RESULTS: Retirement eliminated the subsequent exposure to job strain de facto and was associated with the reduction in the prevalence of hypertension in younger (-33%) and older (-11%) men and in older women (-39%). Job strain was associated with job status in younger men and in women of any age. CONCLUSION: Data showed the presence of HWSE in younger men and older women given the coexistence of the three structural associations.

[Stress syndrome in patients receiving outpatient treatment at the General Hospital, in Bangui, in a context of armed conflict]. / États de stress en consultation externe à l'hôpital général de Bangui dans un contexte de conflit arme: étude transversale descriptive.

CONTEXT: in Africa's zones of conflict, recent studies report a high frequency of post-traumatic stress disorder (PTSD) particularly in community settings. OBJECTIVE: This study aimed to contribute to a better management of patients experiencing violence subsequent to the Central African Republic socio-political conflict. MATERIAL AND METHODS: We conducted a cross-sectional study of the medical records of patients receiving outpatient treatment in the Doctors Without Borders/Médecins Sans Frontières (France) Trauma Center, Bangui. RESULTS: 33.33% (n=35) of patients had PTSD, while 17.14% (n=18) of patients had acute stress syndrome. Stress syndrome (SS) was associated with female sex, rape, anxiety and depression. Rape multiplied the risk of SS occurrence by 8. The average age was 30 years (P25:22 years; P75:40 years). The majority of patients had mood disorder (63.81%; n=67). Insomnia was present in 62.83% (n=66) of patients. Hospital Anxiety and Depression Scale (HADS) was present in 44.76 % of patients. Depression was found in 40.95% (n=43) of patients. CONCLUSION: The obtained results show how the society, apart from militia members, is affected by conflict-related violence in the country. These results can enrich the reflections on health organisation and on the management of patients in Central African, by considering the impact of conflict-related acute stress syndome in the short, medium and long term.