METHODS: A community-based cross-sectional study was conducted among 1,344 adolescents in Sarawak using face-to-face interviews. Hierarchical binary logistic regression analysis was performed to identify factors that determine the risk of suicide among adolescents.
RESULTS: Two predictive models were constructed. Both models revealed that being female (OR=1.578, 95 % CI: 1.191, 2.092, p=0.001), having Malay ethnicity (OR=1.733, 95 % CI: 1.236, 2.429, p=0.001) and having a disease significantly increased the risk of suicide (OR=1.895, 95 % CI: 1.221, 2.942, p=0.004). In particular, Model 2, which showed a better fit, found that occasional religious practice (OR=1.610, 95 % CI: 1.126, 2.303, p=0.009), poor parental relationships (OR=1.739, 95 % CI: 1.035, 2.922, p=0.037) and higher addiction (OR=1.015, 95 % CI: 1.008, 1.022, p=0.001), depression (OR=1.919, 95 % CI: 1.241, 2.968, p=0.003), and stress (OR=2.707, 95 % CI: 1.689, 4.340, p=0.001) scores were significantly associated with an increased risk of suicide.
CONCLUSIONS: This study sheds light on multiple factors that contribute to the risk of suicide among adolescents in Sarawak. These findings underscore the importance of holistic prevention strategies, including psychological and social dimensions, to mitigate the risk of suicide in this population. Further research is warranted to understand the complex interplay of these factors and guide the development of targeted interventions.
METHODS: A nationwide data set was examined for this secondary data analysis. The dependent variable was the degree of risk, which was measured based on the number of high-risk behaviours in which adolescents participated. Age, gender, ethnicity, self-rated academic performance, family size, parental marital status and parental academic attainment were included as independent variables. Analyses stratified by educational level were conducted. Odds ratios (ORs) were calculated using ordered logit.
RESULTS: The most common high-risk behaviour among Malaysian adolescents was physical inactivity (35.97%), followed by smoking (13.27%) and alcohol consumption (4.45%). The majority of adolescents had low risks (52.93%), while only a small proportion had high risks (6.08%). Older age was associated with increased odds of having high risks (OR: 1.26). Male adolescents had higher odds of being in a high-risk category compared to female adolescents (OR: 1.28). Compared to Malays, Chinese adolescents had higher odds of being in a high-risk category (OR: 1.71), whereas Indian adolescents had lower odds (OR: 0.65). Excellent academic performance was associated with reduced odds of participating in high-risk behaviours (OR: 0.41).
CONCLUSION: Personal factors are important determinants of high-risk behaviours. This study provides a better understanding of those adolescent groups that are at greater risk.
PRACTICAL IMPLICATIONS: An intervention directed towards reducing participation in high-risk behaviours among adolescents who have both poor academic performance and less-educated parents may yield promising outcomes.