Random effect and model comparison.

BackgroundThis issue represents a major global public health concern, accounting for approximately 703,000 deaths each year. Despite Mozambique having the 9th highest suicide rate in the world and the highest in Africa, there is no national data quantifying the burden of suicide attempts. Therefore, this study aimed to assess the prevalence of suicide attempts and identify individual and community-level factors associated with them using mixed-effects logistic regression. This study is crucial for developing early interventions, which can help reduce the risk of suicide and enhance overall mental health outcomes for young people.MethodThe data used in this study were drawn from the 2022/2023 Mozambique Demographic and Health Survey (MDHS). A weighted sample of 10,909 individuals (7,716 males and 3,149 females) aged 15–29 was included. The fitted model was evaluated using AIC and BIC, with the model having the lowest Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) is another statistical measure used to assess the quality of a model, similar to the Akaike Information Criterion (AIC). The results of the final model were presented as Adjusted Odds Ratios (AOR) with 95% confidence intervals (CI). Variables were considered statistically significant if their p-value was less than 0.05 in the multivariable analysis.ResultsAbout 3.60% (95% CI: 3.33%-4.03%) of participants were seriously considered suicide attempt in the past 12 months of before the survey. Educational status, occupation, marital status, depression, anxiety, and geographic region were significant factors associated with suicidal attempt.ConclusionThe findings of this study enhance our understanding of the intricate relationships between suicide attempts and their predictors. Additionally, the results highlight the need for targeted interventions and mental health promotion strategies that consider the identified individual and community-level factors to reduce suicide rates in Mozambique.