Sci Rep. 2025 Apr 27;15(1):14734. doi: 10.1038/s41598-025-99895-9.
ABSTRACT
The suicide rate in Bonab County, northwest Iran, has been reported to exceed 16 per 100,000. To develop and implement an effective suicide prevention program (SPP) at the local level in this County, a population-based epidemiological study was conducted to investigate factors associated with suicide and suicide attempts (SA). In this population and registry-based descriptive-analytical study, all deaths of suicide and SA from 2021 to 2023 were analyzed. Data were collected through a population-based registry for suicide and using community health workers in primary care. The study compared epidemiological characteristics and related risk factors between suicide and SA. Multiple logistic regression was used to adjust for potential confounders and calculated the adjusted odds ratios (AOR) for the likelihood of suicide compared to attempts. During 2021-2023, the suicide rates were 16.2, 11.44, and 12.08, while the SA rates were 212, 234, and 237 per 100,000 people. Overall, the suicide rate decreased, whereas the SA rate increased during this period. In the final analysis, males (AOR = 1.97: 1.2-3.6), individuals aged 35-60 (AOR = 1.56: 1.01-3.7), hanging (AOR = 7.4: 2.6-14.2), family conflicts (AOR = 2.65: 1.8-6.13), stressful life events (AOR = 1.25: 1.1-3.9), and unemployment (AOR = 1.8: 1.04-3.5) were associated with an increased likelihood of suicide. The suicide rate in this county surpasses the national average. Predictors of suicide and SA exhibit fundamental differences in this County. The study identified family conflicts, stressful life events, the hanging method, male gender, unemployment, and adult age as reliable predictors for suicide, while factors such as having psychiatric disorders, previous SA, and being female were linked to SA. These factors should be taken into account when developing SPP in Bonab County. Furthermore, the study highlights the need to consider various socioeconomic and cultural factors when developing SPP.
PMID:40289233 | DOI:10.1038/s41598-025-99895-9
AI-assisted Evidence Research
Share Evidence Blueprint
Search Google Scholar