Across all countries included in this analysis, the prevalence of suicidal ideation among adolescents aged 13–17 years is strikingly higher among girls than boys with very little differences between younger and older adolescents. However, suicide attempt did not differ by age group or sex. From our multivariable model, significant indicators associated with suicidal ideation or attempt included being bullied, having no close friends, being in a physical fight and/or a having had a serious injury. Not surprisingly, indicators related to parental connection or country income status failed to be significant, whereas those related to peer connection or isolation were significantly associated with suicide ideation and/or attempts. The convergence of bullying, aggression (fighting) and no friends reflects a problem in social relationships during the entire phase of adolescence, with little difference between HIC and LMIC.
Over the last 15 years, GSHS has collected information on the health behaviours in adolescents. Comparable tools, such as the Health Behavior in School-aged Children (HBSC), Youth Risk Behavior Surveillance System (YRBSS) and Korean Youth Risk Behavior Web-based Survey (KYRBS) have generated knowledge on suicidal ideation and suicide attempts in adolescents in predominantly developed countries [27,28,29]. The sex paradox observed in large epidemiological surveys conducted in high-income countries, including the YRBSS and KYRBS, where adolescent females more often plan and attempt suicide, while adolescent males more often complete suicide was not apparent in the GSHS data [28, 29].
Respondents of the Samoan GSHS (2011) experienced a disproportionately higher burden of suicidal ideation and attempt compared to other countries, particularly among boys. (Supplementary Figs. 1 and 2). This finding is consistent with historical data on youth suicide in Samoa. Countries in the Pacific Region, including Samoa, experienced epidemic youth suicide rates between 1960 to 1995 with a peak in 1980 [30]. High suicide rates in Samoa continued until 2013 despite significant investments in prevention programs [31]. More recent estimates from Samoa (2016) show a 20–40% decrease of adult suicide mortality attributed largely to the success in a ban on lethal pesticides like paraquat [4, 32,33,34,35]. Administering another GSHS in Samoa would be of great use to determine the possibility of similar success among adolescents.
Within our study, after adjusting for covariates, bullying remains a significant risk indicator associated with suicide attempt in both males and females. Our findings are consistent with the HBSC study, which found adolescents from Israel, Lithuania and Luxembourg who experienced cyberbullying and school bullying, had a significantly higher risk associated with suicidal ideations, plans and attempts [16]. From a LMIC perspective, the Young Lives study analyzed longitudinal predictors and associations of bullying in nearly 12,000 adolescents, over a 15-year period in Peru, Ethiopia, India and Vietnam through mixed methods. Their results suggest that bullying is corrosive and associated with long-term negative effects on self-esteem, self-efficacy, peer and parental relations [36]. The authors noted that indirect bullying (i.e. humiliation and social exclusion) was the most prevalent type of bullying experienced by age 15, in three of four countries ranging from 15% in Ethiopia to 28% in India. Our findings are also consistent with two recent systematic reviews which found that bullying perpetration and victimization via traditional (face-to-face) or cyberbullying were associated with deliberate self-harm in adolescents [37, 38].
Furthermore, our findings indicate a vulnerability to bullying during early adolescence suggesting early, preventive and context-appropriate interventions may be necessary to impact suicide behaviours and to help resolve mental health issues. Particularly, the results from GSHS corroborate this need in LMIC [39]. In fact, a previous systematic review and meta-analysis reviewed 99 studies on youth suicide interventions, where only 2% were conducted in a LMIC. Several challenges exist in these settings, including the paucity of mental health services and personnel, as well as, poor monitoring and evaluation systems [40]. Though school-based interventions have been effective in promoting mental health through education, there is potential to miss vulnerable adolescents, as dropout rates are higher in LMIC, especially in females, as compared to HIC [39]. Moreover, as bullying and cyberbullying have become a systemic public health issue, innovative approaches that transcend the school, including the integration of community, parental and mobile health interventions, are necessary to intervene early and prevent social marginalization and victimization. Given our findings, future research should focus on the generalizability of HIC bullying prevention and intervention models towards LMIC, as well as, understanding the temporality and progression of suicide risk indicators to ideation and suicide attempts in adolescents.
Our findings have important implications for policy and programmatic action. Notably, that adolescents are vulnerable humans who are susceptible to both positive and negative influences of environment, is evident from our work. Intervening with these individuals at critical points of entry, such as in schools, in families and within communities, is critical to bringing about sustainable change. To this end, governments should prioritize school-based intervention models to target both in-person and cyber bullying. Peer-to-peer support or self-help groups coordinated by teachers and administrators may be one approach to consider. Encouraging social activities that focus on building relationships and fostering a sense of trust, may be ways that schools and communities can prevent bullying and help adolescents build close friendships. Government’s focus on identifying and providing physical, emotional and social support to youth who have experienced injuries is important. For instance, through health walk-in clinics or through youth networks, would yield notable dividends on health and survival of this population. Widespread education campaigns on mental health and well-being for parents, teachers, public service offices and communities will be invaluable to building a supportive environment for at-risk youth.
Several limitations of this work should be considered. The GSHS’s cross-sectional design precludes temporal and causal inference. As the survey is school-based, information on important national, community and household indicators factors were missing, such as socioeconomic status, food security, family risk and protective factors, cultural and religious factors or national political climate. Additionally, in some LMIC where school attendance is low (especially among girls), the data may not be nationally representative. The GSHS did not ask specific questions on previous childhood abuse, behaviour, family history, previous mental illness or questions related to severity of depression which are also known risk indicators for poor mental health. Such data should be evaluated for inclusion in future phases of the GSHS. The sensitive nature of questions, self-reporting may have introduced bias due to under- or over-reporting on certain questions. Specific questions related to serious injury and bullying included in our analyses are limited in that they potentially under- or over- capture true responses. More specifically, ‘serious injury’ captures injuries from both intentional (violence, self-harm) and unintentional (road accidents) causes, while bullying may have only captured classical bullying (face-to-face), as opposed to the inclusion of cyberbullying. Sexual orientation may be a hidden risk indicator since it is not available in the current GSHS data. A recent systematic review reported higher rates of depression among young lesbian, gay, bisexual, transgender and questioning (LGBTQ) and LGBTQ-factors were associated with suicide risk [41, 42]. This may help explain some of the findings regarding bullying, injuries, etc. Since our analyses were ecological (i.e. using country-year data points), caution should be applied when making individual-level inferences. Lastly, since the GSHS design is intended to capture a representative sample of younger adolescents, prevalence estimates of older adolescents (16–17 years) may not be representative. While our results should be interpreted in light of these limitations, this pooled analysis represents a large number of participants in predominately LMIC, where much data on adolescents are lacking. Strengths of this analysis lie with the use of a validated tool administered in a large number of countries over approximately 15 years.