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Article

Global Lifetime and 12-Month Prevalence of Suicidal Behavior, Deliberate Self-Harm and Non-Suicidal Self-Injury in Children and Adolescents between 1989 and 2018: A Meta-Analysis

by
Kim-San Lim
1,
Celine H. Wong
2,
Roger S. McIntyre
3,4,
Jiayun Wang
5,*,
Zhisong Zhang
5,
Bach X. Tran
6,7,8,
Wanqiu Tan
9,
Cyrus S. Ho
10 and
Roger C. Ho
1,5,11,12
1
Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
2
Division of Child and Adolescent Psychiatry, Department of Psychological Medicine, National University Health System, Singapore 119228, Singapore
3
Mood Disorders Psychopharmacology Unit, University Health Network, University of Toronto, Toronto, ON M5T 1R8, Canada
4
Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
5
Institute of Cognitive Neuroscience, Huaibei Normal University, Huaibei 235000, China
6
Institute for Preventive Medicine and Public Health, Hanoi Medical University, Hanoi 100000, Vietnam
7
Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
8
Vietnam Young Physicians’ Association, Hanoi 100000, Vietnam
9
The China-Singapore (Chongqing) Demonstration Initiative on Strategic Connectivity Think Tank, Chongqing 400043, China
10
Department of Psychological Medicine, National University Health System, Singapore 119228, Singapore
11
Health Innovation and Technology (iHealthtech), National University of Singapore, Singapore 119228, Singapore
12
Center of Excellence in Behavioral Medicine, Nguyen Tat Thanh University, Ho Chi Minh City 70000, Vietnam
 
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*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2019, 16(22), 4581; https://doi.org/10.3390/ijerph16224581
Submission received: 4 October 2019 / Revised: 3 November 2019 / Accepted: 7 November 2019 / Published: 19 November 2019
(This article belongs to the Special Issue Adult Psychiatry)
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Abstract

:
Objective: This meta-analysis aimed to estimate the global lifetime and 12-month prevalence of suicidal behavior, deliberate self-harm and non-suicidal self-injury in children and adolescents. Methods: A systematic search for relevant articles published between 1989 to 2018 was performed in multiple electronic databases. The aggregate 12-month and lifetime prevalence of suicidal behavior, deliberate self-harm, and non-suicidal self-injury were calculated based on the random-effects model. Subgroup analyses were performed to compare the prevalence according to school attendance and geographical regions. Results: A total of 686,672 children and adolescents were included. The aggregate lifetime and 12-month prevalence of suicide attempts was 6% (95% CI: 4.7–7.7%) and 4.5% (95% CI: 3.4–5.9%) respectively. The aggregate lifetime and 12-month prevalence of suicidal plan was 9.9% (95% CI: 5.5–17%) and 7.5% (95% CI: 4.5–12.1%) respectively. The aggregate lifetime and 12-month prevalence of suicidal ideation was 18% (95% CI: 14.2–22.7%) and 14.2% (95% CI: 11.6–17.3%) respectively. The aggregate lifetime and 12-month prevalence of non-suicidal self-injury was 22.1% (95% CI: 16.9–28.4%) and 19.5% (95% CI: 13.3–27.6%) respectively. The aggregate lifetime and 12-month prevalence of deliberate self-harm was 13.7% (95% CI: 11.0–17.0%) and 14.2% (95% CI: 10.1–19.5%) respectively. Subgroup analyses showed that full-time school attendance, non-Western countries, low and middle-income countries, and geographical locations might contribute to the higher aggregate prevalence of suicidal behaviors, deliberate self-harm, and non-suicidal self-injury. Conclusions: This meta-analysis found that non-suicidal self-injury, suicidal ideation, and deliberate self-harm were the three most common suicidal and self-harm behaviors in children and adolescents.

1. Introduction

During the past 30 years, suicide has become a severe cause of mortality across all ages in the world. In 2015, the number of suicide deaths worldwide was estimated to be 788,000 [1], with a global average of 10.7 per 100,000. Suicide was ranked second as a cause of mortality amongst those aged 15–29 years old globally [2], making it a global public health concern. Suicidal behavior, deliberate self-harm and non-suicidal self-injury are important antecedents of suicide in children and adolescents [2]. Suicidal behaviors involve suicidal ideation, planning for suicide and suicide attempts [3]. Self-harm behavior is defined here as an act of intentionally causing harm to own self, irrespective of the type, motive or suicidal intent [2]. Non-suicidal self-injury is defined as deliberate direct destruction or alteration of body tissue without conscious suicidal intent [4]. Deliberate self-harm is an encompassing term for self-injurious behavior, both with and without suicidal intent that has a non-fatal outcome [5]. Non-suicidal self-injury and deliberate self-harm are common in young people who will have borderline personality traits or disorder [6]. Non-suicidal self-injury and deliberate self-harm have been known to predict future suicide attempts [7].
There are potential factors that affect the global prevalence of suicidal and self-harm behavior in children and adolescents. From cross-cultural perspectives, there are ethnic differences in risk factors of suicide attempts [8,9]. In Western countries like Canada, suicide accounts for 10% of deaths in children aged 10 to 14 years and for 23% of deaths in adolescents aged 15 to 19 years [10]. In New Zealand, children and adolescents from the lowest socio-economic status were found to be 31 times more likely to attempt suicide compared to individuals in the higher socio-economic status [11]. In Asia, relationship issues, academic and environmental stressors are common precipitants for suicide attempts among young people [12]. In Singapore, a peak in suicide attempts has been observed in adolescents and young adults aged 15 to 24 years old [12]. Cross-cultural studies found that self-harm behaviors amongst eighth-graders in Hong Kong (23.5%) were less frequent compared to those in the United States (32%) [13]. The lower self-harm rate in Hong Kong adolescents was attributed to cultural differences between the Eastern and Western cultures, with a stronger emphasis on family structures and rules in Asian culture [13]. A meta-analysis is required to study cross-cultural perspectives of suicidal behavior, deliberate self-harm, and non-suicidal self-injury among young people in different countries in a systematic manner.
From a gender perspective, Lewinsohn et al. found female adolescents to have a significantly higher risk of suicide attempts compared to male counterparts, with the differences between genders diminishing as participants increased with age [14]. Furthermore, gender was found to predict lethality in suicide attempts as more males than females made attempts with high perceived lethality and medical lethality [15]. Youth who experienced difficulty in school were at risk for suicide [16]. However, there is little published information specific to the relationship between school attendance, suicidal behaviors, deliberate self-harm, and non-suicidal self-injury in children and adolescents.
Despite the seriousness and scope of the problem, little is known about the global prevalence of suicidal and self-harm behaviors in children and adolescents in the past 30 years. Further research is required to compare the prevalence of suicidal, and self-harm behavior among children and adolescents from different geographical regions as contextual differences (e.g., exposure to adversity) across countries may affect prevalence estimates. Given the above findings and observations, we aimed to conduct a meta-analyze to estimate the global 12-month and lifetime prevalence of adolescents having a history of suicide attempts, suicide plans, suicidal ideation, non-suicidal self-injury, and deliberate self-harm between 1989 to 2018.

2. Methods

2.1. Search Strategy

During the past thirty years, the advent of computer technology, the Internet, and the widespread use of social media have affected suicidal behaviors, deliberate self-harm and non-suicidal self-injury in young people. Many young people report that computers and the Internet facilitate their communication with peers [17]. The effect of social media on suicidal behaviors, deliberate self-harm and non-suicidal self-injury is still under evaluation. Some studies suggested that social media use has led to the growth of suicide clusters [18], while others showed that it had a positive impact on the prevention of suicide given the myriad of support platforms for the children and adolescents at risk [19]. Given the above findings and observations, this meta-analysis focused from 1989 to 2018.
This study was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses PRISMA) guidelines. A systematic search was performed with dates covered from 1 January 1989 to 31 December 2018, using a combination of search terms (* indicates truncation): ‘suicid */suicide attempt *’, ‘self harm’ or ’self-harm’,’self injury’ or ’self-injury’, ‘adolescent’, ’youth’, ’young’, ’child *’,’teen *’,’student *’,’school *’ and ‘prevalence’. Electronic databases such as PubMed, Web of Science, PsycINFO, and Embase were utilized. The reference lists of reviews, reports, and other relevant articles were also examined to identify additional studies.

2.2. Eligibility Criteria

Two authors (K.-S.L. and R.C.H.) independently identified the eligibility of studies. The studies included in this review must fulfil the following inclusion criteria: (1) the study provided cross-sectional data on the lifetime and 12-month prevalence of suicidal behavior, deliberate self-harm or non-suicidal self-injury; (2) the study population was children or adolescents and (3) a clear definition of suicidal behavior, deliberate self-harm or non-suicidal self-injury were reported. Any study that did not meet the aforementioned inclusion criteria were excluded. Any discrepancies between the two authors were reviewed by another author (C.S.H.) and resolved with consensus.

2.3. Data Extraction

Two authors (K.-S.L. and R.C.H.) independently extracted the following data from each eligible study: first author, year of publication, the country where the study was conducted, number of participants with suicidal behavior, deliberate self-harm or non-suicidal self-injury, total sample size, mean age of participants, proportion of female gender and school attendance. Any disagreements between the two authors were resolved via discussion with a third author (C.S.H.). The three authors involved in this process were trained in medicine and psychiatry.

2.4. Study Outcomes

A suicide attempt is defined as an act in which an adolescent tries to end his or her life but survives [20]. A suicide plan is a proposed plan of carrying out a suicidal act that may lead to potential death [21]. Suicidal ideation is defined as any self-reported thoughts of engaging in suicide-related behavior [22]. Non-suicidal self-injury is defined as the deliberate, self-inflicted destruction of body tissue without suicidal intent and for purposes not socially sanctioned, such as cutting, burning, and biting [23]. Deliberate self-harm is defined as self-injurious behaviors with and without suicidal intent and that have non-fatal outcomes. The 12-month and lifetime prevalence of suicide attempts, suicide plans, suicide ideation, non-suicidal self-injury, and deliberate self-harm were extracted from each study, which met inclusion criteria.

2.5. Statistical Analysis

All statistical analyses were conducted in Comprehensive Meta-analysis statistical software version 3.0 (BioStat Solutions, Inc, Frederick, MD, USA). The aggregate prevalence was calculated based on the random-effects model. The random-effects model was used as it assumes varying effect sizes between studies, because of differing study design and study population [24,25]. A forest plot was then constructed and reported the aggregate prevalence, 95% confidence interval (CI) and p-value based on the method adopted by previous meta-analysis on prevalence [26,27]. The statistical significance level was set at p < 0.05. The I 2 statistic was used to assess the between-study heterogeneity [28], which describes the percentage of variance on the basis of real differences in study effects. I 2 value of 25% was considered low, 50% moderate and 75% substantial [29].
Publication bias was assessed with the utilization of Egger’s regression [25]. A p-values of 0.05 or less was used as the cut off for the presence of statistically significant publication bias [30]. The presence of publication bias was then further investigated using both the standard and Orwin’s fail-safe N tests to provide an estimated number of additional studies required to make the eventual effect size insignificant [31]. Meta-regression analyses with a mixed-effect model were performed to identify the effects of potential moderators on the overall heterogeneity. Potential moderators include mean age of sample and proportion of female gender. Subgroup analyses were performed to compare the aggregate prevalence of each study outcome with regards to school attendance and study location. The definitions of developing and developed countries were based on Standard Country or Area Codes for Statistical Use developed by the United Nations [32].

3. Results

3.1. Selection Results and Study Characteristics

A total of 668 potentially relevant citations were gathered after an extensive literature search was performed on the databases listed in Figure 1. A total of 106 studies were found to be duplicated. Of the remaining 562 studies for which titles and abstracts were screened, 400 were excluded. The final 162 studies were then reviewed in full, of which 96 were excluded, leaving 66 studies that met the inclusion criteria to be used in this meta-analysis. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses—chart depicting the detailed process of paper selection can be seen in Figure 1. The 66 studies included in the meta-analysis yields a total population of 686,672 study participants. Table 1 shows the characteristics of the included studies.

3.2. Aggregate Prevalence of Suicide Attempts in Children and Adolescents

The aggregate lifetime prevalence of suicide attempts was found to be 6.0% (95% Confidence Interval (CI): 4.7–7.7%). The forest plot is shown in Figure 2. There was a significantly high level of heterogeneity across the included studies (I2 = 98.60, p <0.001). There was no evidence of publication bias (intercept = 0.16, 95% CI: −5.87–6.2, t = 0.06, df = 27, p = 0.96).
The aggregate 12-month prevalence of suicide attempts was found to be 4.5% (95% CI: 3.4–5.9%). The result is demonstrated using the forest plot as shown in Figure 3. There was a significant high level of heterogeneity across the included studies (I2 = 99.64, p < 0.001). There was no evidence of publication bias (intercept = 0.39, 95% CI: −11.71–12.49, t = 0.07, df = 21, p = 0.95).

3.3. Aggregate Prevalence of Suicide Plans in Children and Adolescents

The aggregate lifetime prevalence of suicide plans was found to be 9.9% (95% CI: 5.5–17.0%). The result is demonstrated using the forest plot, as shown in Figure 4. There was a significantly high level of heterogeneity across the included studies (I2 = 99.35, p < 0.001). The aggregate 12-month prevalence of suicide plans was found to be 7.5% (95% CI: 4.5–12.1%). There was a significantly high level of heterogeneity across the included studies (I2 = 99.82, p < 0.001). The result is demonstrated using the forest plot, as shown in Figure 4. There was no evidence of publication bias (intercept = 15.24, 95% CI: −5.06–35.54, t = 1.58, df = 17, p = 0.13).

3.4. Aggregate Prevalence of Suicide Ideation in Children and Adolescents

The aggregate lifetime prevalence of suicidal ideation was found to be 18% (95% CI: 14.2–22.7%). The result is demonstrated using the forest plot, as shown in Figure 5. There was a significantly high level of heterogeneity across the included studies (I2 = 99.68, p <0.001). There was no evidence of publication bias (intercept = −11.18, 95% CI: −21.49–0.88, t = 2.21, df = 31, p = 0.03).
The aggregate 12-month prevalence of suicidal ideation was found to be 14.2% (95% CI: 11.6–17.3%). The result is demonstrated using the forest plot as shown in Figure 6. There was a significant high level of heterogeneity across the included studies (I2 = 99.82, p < 0.001). There was no evidence of publication bias (intercept = −5.18, 95% CI: −18.64–8.29, t = 0.79, df = 26, p = 0.44).

3.5. Aggregate prevalence of Non-Suicidal Self Injury in Children and Adolescents

The aggregate lifetime prevalence of non-suicidal self-injury was 22.1% (95% CI: 16.9–28.4%). The result is demonstrated using the forest plot, as shown in Figure 7. There was a significantly high level of heterogeneity across the included studies (I2 = 99.22, p < 0.001). The aggregate 12-month prevalence was 19.5% (95% CI: 13.3–27.6%). There was a significantly high level of heterogeneity across the included studies (I2 = 99.63, p < 0.001). There was no evidence of publication bias (intercept = −4.84, 95% CI: −14.85–6.174, t = 1.0, df = 24, p = 0.33).

3.6. Aggregate Prevalence of Deliberate Self-Harm in Children and Adolescents

The aggregate lifetime prevalence of deliberate self-harm was 13.7% (95% CI: 10.9–17.1%). The result is demonstrated using the forest plot, as shown in Figure 8.
There was a significantly high level of heterogeneity across the included studies (I2 = 99.46, p < 0.001). The aggregate 12-month prevalence of deliberate self-harm was 14.2% (95% CI: 10.1–19.5%). There was a significantly high level of heterogeneity across the included studies (I2 = 99.63, p < 0.001). There was no evidence of publication bias (intercept = −9.21, 95% CI: −18.93–0.52, t = 1.93, df = 31, p = 0.06).

3.7. Subgroup Analyses Based on School Attendance

A higher aggregate lifetime prevalence of suicide attempts is found amongst young people who attended school full-time as compared to young people from the mixed group of education consisting partial and non-school attendees (6.7% (95% CI: 5.3–8.4%) vs. 4.3% (95% CI: 2.7–6.7%)). The aggregate prevalence of suicide attempts in the past 12 months for full-time school attendees (5.6%, 95% CI: 4.2–7.3%) was found to be higher than partial and non-school attendees (2.1%, 95% CI: 1.3–3.6%).
The aggregate lifetime prevalence of suicide plans was found to be 12.4% (95% CI: 8.5–17.8%) in young people who attended school as compared to 5.1% (95% CI: 2.6–9.9%) from partial and non-school attendees. Similarly, the aggregate 12-month prevalence of suicide plans was also higher in the school-attending group (10.3%, 95% CI: 7.6–13.7%) as compared to partial and non-school attending group (3.1%, 95% CI: 1.8–5.2%).
The aggregate lifetime prevalence of suicidal ideation and 12-month prevalence of suicidal ideation were found to be higher in the school-attending group as compared to the partial and non-school attending group (19.5%, 95% CI: 15.0–25.0% vs. 13.9%, 95% CI: 8.5–22.1%) and (14.6%, 95% CI: 11.8–18.0% vs. 12.4%, 95% CI: 7.7–19.5%) respectively.
Both the lifetime and 12-month aggregate prevalence of non-suicidal self-injury were higher in the school-attending group as compared to the partial and non-school attending group (22.8%, 95% CI: 17.1–29.8% vs. 19.0%, 95% CI: 9.7–33.7%), and (21.5%, 95% CI: 15.0–30.0% vs. 8.0%, 95% CI: 2.4–23.3%) respectively.
There was a higher aggregate lifetime and 12-month prevalence of deliberate self-harm in the school-attending group (15.3%, 95% CI: 11.7–19.9%) compared to the partial and non-school attending group (10.4%, 95% CI: 6.6–15.9%).

3.8. Subgroup Analyses Based on Western and Non-Western Countries

The aggregate lifetime prevalence of suicide attempts was higher in Western (6.5%, 95% CI: 4.7–9.0%) than non-Western countries (5.4%, 95% CI: 3.6–7.9%). In contrast, aggregate prevalence of suicide attempts in the past 12 months was higher in non-Western countries (6.9%, 95% CI: 4.8–9.6%) than western (2.8%, 95% CI: 1.9–4.0%).
The aggregate lifetime prevalence of suicide plans was higher in non-Western (12.9%, 95% CI: 6.7–23.3%) than Western countries (7.6%, 95% CI: 3.9–14.3%). Similarly, the aggregate past 12-month prevalence of suicide plans was higher in non-Western (10.3%, 95% CI: 7.6–13.7%) than Western countries (3.1%, 95% CI: 1.8–5.2%).
The aggregate lifetime prevalence of suicide ideation was higher in non-Western (18.7%, 95% CI: 12.5–26.9%) than Western countries (17.6%, 95% CI: 12.7–23.8%). The aggregate 12-month prevalence of SI was higher in non-Western (15.2%, 95% CI: 12.6–18.1%) than Western countries (13.0%, 95% CI: 10.5–16.1%).
The aggregate lifetime prevalence of non-suicidal self-injury was higher in non-Western countries (32.6%, 95% CI: 20.0–48.5%) than Western countries (19.4%, 95% CI: 14.2–25.8%). The aggregate 12-month prevalence of non-suicidal self-injury was similar between in non-Western (19.1%, 95% CI: 9.3–35.3%) and the Western countries (19.7%, 95% CI: 10.4–34.2%).
The aggregate lifetime prevalence of deliberate self-harm was higher in Western countries (14.2%, 95% CI: 10.7–18.6%) than non-Western countries (12.8%, 95% CI: 8.5–18.7%). The aggregate 12-month prevalence of deliberate self-harm was higher in non-Western countries (25.2%, 95% CI: 16.8–36.0%). than Western countries (8.5%, 95% CI: 5.5–12.8%).

3.9. Subgroup Analyses Based on Developing and Developed Countries

The lifetime prevalence of suicide attempts in developed (6.1% 95% CI: 4.3–8.5%) and low and middle-income countries (6.0% 95% CI: 4.1–7.7%) were similar. However, the past 12-month prevalence of suicide attempts was higher in low and middle-income countries (6.9% 95% CI: 4.8–9.6%) than developed countries (2.8% 95% CI: 1.9–4.0%).
The lifetime prevalence of suicide plans was higher in developing (12.9% 95% CI: 6.7–23.3%) than developed countries (7.6% 95% CI: 3.9–14.3%). Similarly, the 12-month prevalence of suicide plans was higher in low and middle-income countries (10.3% 95% CI: 7.6–13.7%) than developed countries (3.1% 95% CI: 1.8–5.2%).
The lifetime prevalence of suicide ideation was higher in developing (17.7% 95% CI: 11.1–27.0%) than developed countries (17.3% 95% CI: 12.0–24.4%). The 12-month prevalence of suicide ideation was higher in low and middle-income countries (15.9% 95% CI: 13.5–18.6%) than developed countries (11.9% 95% CI: 9.6–14.7%).
The lifetime prevalence of non-suicidal self-injury was significantly higher in low- and middle-income countries (33.7% 95% CI: 19.0–52.5%) as compared to developed countries (20.0% 95% CI: 14.9–26.4%). However, the 12-month prevalence of non-suicidal self-injury was found to be similar between developed countries (19.7% 95% CI: 10.4–34.2%) and low- and middle-income countries (19.1% 95% CI: 9.3–35.3%).
The lifetime prevalence of deliberate self-harm was similar between low- and middle-income countries (13.9% 95% CI: 10.6–18.1%) and developed countries (13.2% 95% CI: 8.5–19.9%). The past 12-month prevalence of deliberate self-harm was found to be higher in low- and middle-income countries (25.2% 95% CI: 16.8–36.0%) than developed countries (8.5 % 95% CI: 5.5–12.8%).

3.10. Subgroup Analyses Based on Continents

The lifetime prevalence of suicide attempts was found to be highest in South America (19.0% 95% CI: 17.1–21.0%). The lifetime prevalence of suicide attempts in Africa was 11.2% (95% CI: 2.7%–36.1%). The lifetime prevalence of suicide attempts in Australia was 9.2% (95% CI: 7.5%–11.2%). The lifetime prevalence of suicide attempts in North America was 8.6% (95% CI: 5.4–13.6%). The lifetime prevalence of suicide attempts was lowest in Asia 4.6% (95% CI: 2.7–7.6%) and Europe 4.6% (95% CI: 3.2–6.6%).
The past 12-month prevalence of suicide attempts was found to be highest in Africa at (16.3% 95% CI: 8.4–29%). The past 12-month prevalence of suicide attempts in Asia was 5.8% (95% CI: 4.9–6.7%). The past 12-month prevalence of suicide attempts in Europe was 3% (95% CI: 2.7–3.4%). The past 12-month prevalence of suicide attempts in North America was 3% (95% CI: 1.1–8%). The past 12-month prevalence of suicide attempts was lowest in Australia (2.4%, 95% CI: 1.4–4.4%).
For the lifetime and 12-month prevalence for suicide plans, Asia had the highest prevalence (10.4% 95% CI: 7.7–13.9%). The lifetime and 12-month prevalence of suicide plans in Africa was 13.9% (95% CI: 8.1–22.8%). The lifetime and 12-month prevalence of suicide plans in Europe was 10% (95% CI: 4.3%–21.6%). The lifetime and 12-month prevalence of suicide plans in Australia was 5.2% (95% CI: 4.4–6.1%). The lifetime and 12-month prevalence of suicide plans were lowest in North America (3.7%, 95% CI: 2.3–5.9%).
The lifetime prevalence of suicide ideation was found to be highest in Africa (37.0%, 95% CI: 32.6–41.7%). The lifetime prevalence of suicide ideation in North America was 30.2% (95% CI: 13.4–54.8%). The lifetime prevalence of suicide ideation in South America was 28.5% (95% CI: 8.8–62.3%). The lifetime prevalence of suicide ideation in Asia was 14.2% (95% CI: 8.5–22.7%). The lifetime prevalence of suicide ideation was lowest in Europe (13.7% 95% CI: 9–20.2%).
The past 12-month prevalence of suicide ideation was found to be highest in Africa months (20.6%, 95% CI: 13.7–29.7%). The past 12-month prevalence of suicide ideation in South America was 18.4% (95% CI: 16.3–20.7%). The past 12-month prevalence of suicide ideation in Europe was 16.3% (95% CI: 15.3–17.5%). The past 12-month prevalence of suicide ideation in North America was 12.8% (95% CI: 6.4–24.1%). The lifetime prevalence of suicide ideation was lowest in Asia (13.3%, 95% CI: 10.9–16.3%).
The lifetime and past 12-month prevalence of non-suicidal self-injury were found to be highest in Australia (30.9%, 95% CI: 1.8–91.7%). The lifetime and past 12-month prevalence of non-suicidal self-injury in Asia was 25.7% (95% CI: 18.9–33.8%). The lifetime and past 12-month prevalence of non-suicidal self-injury in North America was 18.7% (95% CI: 14.3–24%). The lifetime and past 12-month prevalence of non-suicidal self-injury were lowest in Europe (18.4%, 95% CI: 12.1–27.2%).
The lifetime and past 12-month prevalence of deliberate self-harm was found to be highest in Asia (17.4%, 95% CI: 12.5–23.7%). The lifetime and past 12-month prevalence of deliberate self-harm in Europe was 12.9% (95% CI: 10.3–16.0%). The lifetime and past 12-month prevalence of deliberate self-harm in Australia was 11.1% (95% CI: 5.4–21.3%). The lifetime and past 12-month prevalence of deliberate self-harm was lowest in North America (7.3%, 95% CI: 6.5–8.2%).

3.11. Meta-Regression Analyses

For suicide attempts, mean age (B = 0.0812, z = 2.12, p = 0.034) was identified as significant moderator that contributed to heterogeneity between studies. For suicidal plan, mean age (B = 0.20, z = 5.63, p < 0.001) was identified as significant moderator that contributed to heterogeneity between studies. For SI, mean age (B = −0.0087, z = −0.28, p = 0.78) was a non-significant moderator. For non-suicidal self-injury, mean age (B = 0.11, z = 1.77, p = 0.08). was a non-significant moderator. Fordeliberate self-harm, mean age (B = 0.01, z = 0.33, p = 0.74) was a non-significant moderator.
For suicide attempts, the proportion of females (B = 1.86, z = 1.05, p = 0.29) was a non-significant moderator. For suicidal plan, the proportion of females (B = −0.36, z = −0.14, p = 0.89) was a non-significant moderator. For suicidal ideation, the proportion of females (B = 0.77, z = 0.63 p = 0.53) was a non-significant moderator. For non-suicidal self-injury, the proportion of females (B = −0.29, z = −0.25, p = 0.81) was a non-significant moderator. For deliberate self-harm, the proportion of females (B = −1.79, z = −0.85, p = 0.4) was a non-significant moderator.

4. Discussion

To the best of our knowledge, this is the first meta-analysis that analyzed suicidal and self-harm phenomena based on 686,672 young people worldwide. The key findings are summarized as follows. non-suicidal self-injury was most frequent with aggregate lifetime and 12-month prevalence of 22.1% and 19.5% respectively. Suicidal ideation was second most frequent with aggregate lifetime and 12-month prevalence of 18% and 14.2% respectively. Deliberate self-harm was third most frequent with aggregate lifetime and 12-montnh prevalence of 13.7% and 14.2% respectively. Suicidal plan ranked fourth with aggregate lifetime and 12-month prevalence 9.9% and 7.5% respectively. Suicide attempt was least frequent with aggregate lifetime and 12-month prevalence of 6.0% and 4.5% respectively.
This meta-analysis found that the aggregate lifetime prevalence of suicide attempts was higher in Western (6.5%, 95% CI: 4.7–9.0%) than non-Western countries. There are several reasons to explain higher prevalence of suicide attempts among young people in western countries. First, substance abuse appeared to have affected suicide rates of young males in Western countries [129]. Second, high suicide rates among young indigenous people in Western countries have been attributed to internalised anger and despair related to social disruption and disempowerment [130]. Third, young people in Western countries could have more access to suicide means, including firearms. In contrast, the aggregate lifetime prevalence of suicide plans, suicide ideation and non-suicidal self-injury were higher in non-Western countries than Western countries. This finding suggests that young people in non-Western countries could have thought about suicide but did not attempt suicide. Attempted suicide is illegal in some of the non-Western countries including Bangladesh, Hungary, India and Japan, though in Japan it is not punishable [129]. The legal implication could deter suicide attempts in some of the non-Western countries.
This meta-analysis found that non-suicidal self-injury had the highest aggregate lifetime and 12-month prevalence worldwide. Non-suicidal self-injury is defined as the intentional destruction of one’s own body tissue without suicidal intent [27]. Examples of non-suicidal self-injury, including self-laceration, skin scratching, burning and hitting. Klonsky et al. proposed functional theories that explain the reasons for non-suicidal self-injury in young people [131]. The reasons include alleviation of negative emotion, self-punishment, self-directed anger, and expression of distress. Klonsky et al. highlighted the misconception that non-suicidal self-injury is always a symptom of borderline personality disorder [132]. For young people with engaging non-suicidal self-injury, a psychological intervention which aims at building positive emotion, reducing self-directed anger and promoting more adaptive way to express distress may reduce the prevalence of non-suicidal self-injury.
A recent study found that the 12-month prevalence rates of youth self-harm in low and middle- income countries were comparable to high-income countries. This meta-analysis with a larger sample size showed that children and adolescents from low- and middle-income countries with lower income had a higher aggregate 12-month prevalence of deliberate self-harm than children and adolescents from developed countries with higher income. Previous research reported that non-suicidal self-injury appeared to be more common among Caucasians than non-Caucasians [133]. Our meta-analysis found that the 12-month prevalence of non-suicidal self-injury was highest in Australia which has 74.3% of the population who are Caucasians [134].
The subgroup analysis yielded several interesting findings. The aggregate lifetime and 12-month prevalence of suicidal and self-harm behavior were higher in full-time school attendees as compared with partial and non-attendees. School attendees are more likely to be exposed to risk factors, including academic stress and school bullying. Academic stress leads to anger, anxiety, helplessness, shame, and boredom [135]. A previous study found that skin picking, which causes skin damage was positively correlated with academic stress and trait anxiety was a predisposing factor [136]. The other risk factors faced by school attendees are peer victimization, which reflects the experience of overt (e.g., hitting, pushing), reputational (e.g., spreading rumors), or relational aggression from peers (e.g., being excluded, gossiped about) [137,138]. Vergara et al. (2019) found that peer victimization was associated with the frequency of past month non-suicidal self-injury thoughts and past month non-suicidal self-injury behaviors [139]. The aggregate lifetime and 12-month prevalence of suicidal and self-harm behavior were higher in developing and non-western countries.
We found that the lifetime prevalence of suicide ideation, the 12-month prevalence of suicide attempts and suicide ideation were highest in Africa. This could be due to the fact that large numbers of African children and adolescents were exposed to adverse childhood experiences [140]. Young people in developing and non-western countries are more likely to be exposed to adverse childhood experiences including alcohol abuse [141], lack of access to care for mental health problems, orphanage, and early parental death [142], human immunodeficiency virus (HIV) infection [142] and violence against children and adolescents [143]. Interventions to reduce African children and adolescent suicidality include those improving family functioning, reducing poverty, mitigating the impacts of HIV and the provision of effective mental health services for adversity-exposed children and adolescent [140]. As the infrastructure for mental health service is still developing, the main challenge is to reach out to children and adolescents in low and middle-income countries and educate them to handle suicidal and self-harm behaviors. Electronic health (E-health) was found to provide a cost-effective solution in mental health [144]. As the use of smartphones becomes increasingly prevalent and affordable, more children and adolescents in low and middle-income countries can own a smartphone device and download health-related applications [17]. Proof of concept feasibility studies and randomized trials should be conducted in low and middle-income countries to determine that smartphone applications are efficacious to reduce suicidal and self-harm behavior in children and adolescents before their actual implementation [145].
The lifetime and 12-month prevalence of suicide plans and DSH were found to be highest in Asia. Asian children and adolescents face more academic-related stress due to the competitiveness in the education system, and getting poor grades in the examination have been found to bear two major significant sources of anxiety and depression amongst Asian children and adolescents [146]. Willingness to seek help was found to be a protective factor against suicidal and self-harm behavior for Asian children and adolescents [15]. Nevertheless, help-seeking from peers may not be beneficial [147]. Children and adolescents may not receive the help that they require, as peers often might be poorly equipped to provide appropriate advice.
Meta-regression found that age was a critical moderator that explains for heterogeneity for a lifetime and 12-month prevalence of suicide attempts and suicide plans. Children and young adolescents were less exposed to suicide risk factors as compared with older adolescents [148]. Older adolescents are predisposed to specific risk factors associated with suicidal behaviors, including baseline interpersonal problems in one’s social circle [149], psychiatric disorders [148], and STD-related risk [150]. Meta-regression also found that gender was not a vital moderator that explains for heterogeneity of the prevalence of suicidal and self-harm behavior. This finding may challenge the gender paradox, which suggests significant epidemiological differences in suicidal and self-harm behaviors between adolescent females and males [151]. A previous study found that there were no gender differences in family problems and school problems which are well-known risk factors associated with suicidal and self-harm behavior in young people [152].
The strengths of this meta-analysis include an extensive search in identifying a large number of articles on suicidal and self-harm behaviour in 686,672 children and adolescents, adherence to the guidelines, the inclusion of meta-regression and subgroup analysis as well as lack of publication bias [28]. Nevertheless, this meta-analysis has several limitations. First, this meta-analysis classified suicidal and self-harm phenomena into five sub-categories and not able to study their inter-relationship. Klonsky et al. proposed that non-suicidal self-injury may be an essential risk factor for suicidal behaviour [132]. Future study is required to study the inter-relationship between suicidal behaviour, deliberate self-harm, and non-suicidal self-injury in young people. Second, we could not classify dliberate self-harm as suicidal and non-suicidal deliberate self-harm. Future research is required to understand the differences between young people who attempt suicidal and non-suicidal deliberate self-harm.

5. Conclusions

In conclusion, this meta-analysis found that the three most common suicidal and self-harm behaviors were non-suicidal self-injury (aggregate lifetime and 12-month prevalence of 22.1% and 19.5% respectively), suicidal ideation (aggregate lifetime and 12-month prevalence of 18% and 14.2% respectively) and deliberate self-harm (aggregate lifetime and 12-month prevalence of 13.7% and 14.2% respectively). The aggregate lifetime prevalence of suicide attempts was higher in Western than non-Western countries, in contrast, the aggregate lifetime prevalence of suicide plans, suicide ideation and non-suicidal self-injury were higher in non-Western countries than Western countries. Suicidal and self-harm behavior was higher in children and adolescents who were full-time school attendees and those who live in developing countries. Meta-regression analyses showed that the mean age of participants was a significant moderator that contributed to heterogeneity for a lifetime and 12-month prevalence of suicide attempts and suicidal plans. Psychological interventions targeting self-harm and suicidal behavior, social interventions targeting adversities in low- and middle-income countries, and electronic—health interventions to reach out to children and adolescents may reduce the global prevalence of suicidal and self-harm behavior in children and adolescents.

Author Contributions

K.-S.L., C.H.W., C.S.H., and R.C.H. contributed to the concept and design of this study. K.-S.L., R.C.H., and C.S.H. contributed to the data acquisition, analysis, and interpretation. K.-S.L., C.H.W., J.W., W.T., Z.Z. and R.C.H. drafted the manuscript. B.X.T. and R.S.M. critically revised the manuscript for important intellectual content. All authors approved the final version of publication.

Funding

J.W. and Z.Z. declared the receipt of the following financial support for the research, authorship and/or publication of this article. This study was supported in part by National Science Education Planning Project, China (BIA180193).

Acknowledgments

We are grateful to all authors of the full-text articles.

Conflicts of Interest

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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Figure 1. Process of systematic selection using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow chart.
Figure 1. Process of systematic selection using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow chart.
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Figure 2. Forest plot of the aggregate lifetime prevalence of suicide attempts.
Figure 2. Forest plot of the aggregate lifetime prevalence of suicide attempts.
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Figure 3. Forest plot of the aggregate 12-month prevalence of suicide attempts.
Figure 3. Forest plot of the aggregate 12-month prevalence of suicide attempts.
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Figure 4. Forest plot of the aggregate lifetime and 12-month prevalence of suicidal plans.
Figure 4. Forest plot of the aggregate lifetime and 12-month prevalence of suicidal plans.
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Figure 5. Forest plot of the lifetime aggregate prevalence of suicidal ideation.
Figure 5. Forest plot of the lifetime aggregate prevalence of suicidal ideation.
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Figure 6. Forest plot of the aggregate 12-month prevalence of suicidal ideation.
Figure 6. Forest plot of the aggregate 12-month prevalence of suicidal ideation.
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Figure 7. Forest plot of the aggregate lifetime and 12-month prevalence of non-suicidal self-injury.
Figure 7. Forest plot of the aggregate lifetime and 12-month prevalence of non-suicidal self-injury.
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Figure 8. Forest plot of the aggregate lifetime and 12-month prevalence of deliberate self-harm.
Figure 8. Forest plot of the aggregate lifetime and 12-month prevalence of deliberate self-harm.
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Table
Table 1. Characteristics of the Studies Included in This Meta-Analysis.
Table 1. Characteristics of the Studies Included in This Meta-Analysis.
First AuthorYearStudy LocationSample SizeMean AgeProportion of Female GenderPrevalence of Suicide AttemptsPrevalence of Suicide PlansPrevalence of Suicide IdeationPrevalence of Non-Suicidal Self-InjuryPrevalence of Deliberate Self-Harm
Abell [33]2012Jamaica2997NANANANA12M:0.097NANA
Altangerel [34]2014Mongolian5191NA0.56712M: 0.08612M:0.12512M: 0.196NANA
Asante [35]2017Ghana1984NA0.45812M: 0.22112M:0.22112M: 0.181NANA
Atlam [36]2017Turkey2973NA0.548NALT: 0.248NANALT: 0.154
Baetens [37]2011Belgium141715.130.814NANALT: 0.605LT: 0.216NA
Begum [38]2017Bangladesh2476NANANANALT:0.05NANA
Benjet [39]2017Mexico1071NA0.57NANANALT: 0.186NA
Borges [40]2011United States1004NA0.56NANA12M:NA12M: 0.076
Brunner [41]2007Germany575914.90.498LT: 0.079LT: 0.065LT: 0.144NALT: 0.149
Brunner [42]2014Various European countries1207314.90.556NANANANALT:0.275
Calvete [43]2015Spain186415.320.514NANANA12M: 0.536NA
Carvalho [44]2017Brazil176316.750.53NANALT: 0.22LT:0296NA
Cerutti [45]2011Italy23416.470.5NANANANALT: 0.419
Chan [46]2008Hong Kong10239NANANANALT: 0.291NANA
Chan [46]2008Hong Kong5688NANANANALT: 0.269NANA
Cheung [47]2013Hong Kong231716.40.54812M: 0.0967NA12M: 0.14312M: 0.14NA
Choquet [48]1990France151914.70.45NANA12M:0.18NANA
Chou [49]2013Taiwan283519.750.55412M: 0.105NANANANA
Claes [50]2013Belgium53215.110.258NANANALT: 0.265NA
Coughlan [51]2014Ireland21211.540.519LT: 0.005NALT: 0.068LT: 0.0660.068
Donald [52]2001Australia3082NANALT: 0.0185NANANANA
Doyle [53]2015Ireland856NA0.5NANANANALT: 0.12
Fleming [54]2007New Zealand9570NA0.53912M:0.078NANANANA
Garisch [55]2015New Zealand116216.350.615NANANALT: 0.696NA
Ghrayeb [56]2014Palestine 72015.40.496NA12M: 0.25312M: 0.246NANA
Giletta [57]2012Italy, Netherlands, United States186215.690.49NANANA12M: 0.24NA
Gonzalez-Forteza [55]2005Mexico253116.670.5440.808NANANALT: 0.072
Grunbaum [58]2001United States1626216.16NA12M: 0.077NANANANA
Han [59]2016United States135300NA0.49812M: 0.01312M:0.021412M: 0.069NANA
Han [60] 2018United States17000NANA12M:0.01612M:0.02712M: 0.083NANA
Hawton [61]2002United Kingdom5801NA0.466NANA12M: 0.149NA12M: 0.069
Hesketh [62]2002China1576NANALT: 0.090NALT: 0.160NANA
Kądziela-Olech [63]2015Poland222016.70.463NANANA12M:0.04812M:0.083
Kang [64]2015South Korea72623NANA12M: 0.04912M: 0.19112M:0.191NANA
Kataoka [65]2014Japan9778NA0.486NANA12M: 0.05NANA
Kidger [66]2012England485516.670.589NANANANALT: 0.186
Kvernmo [67]2009Norway44714.70.526NANA12M:0.161NALT: 0.136
Kirmayer [68]1996Canada9919.40.516LT: 0.341NALT: 0.429NANA
Larsson [69]2008Norway246413.70.508LT: 0.030NALT: 0.040LT: 0.029NA
Laskyte [70]2009Lithuania3848NA0.572NANANANALT:0.07
Law [13]2013Hong Kong2579120.512M: 0.039NA12M:0.046NA12M:0.233
Laukkanen [71]2009Finland420515.580.536NANANANALT: 0.217
Le [72]2011Vietnam7584NA0.560LT: 0.005NALT: 0.034NALT: 0.028
Lee [73]2008South Korea368NA0.389LT: 0.033NATW: 0.098NANA
Lee [74]2013South Korea74698NA0.47212M:0.0597NA12M:0.238NANA
Lewinsohn [75]1996USA1709NANALT: 0.071LT: 0.083LT: 0.129NANA
Lin [76]2017Taiwan217015.830.511NANANA12M:0.2NA
Liu [77]2018China1183114.970.49LT: 0.040LT: 0.098LT: 0.205NANA
Lucassen [78]2011New Zealand9107NA0.4612M: 0.042NA12M:0.125NA12M:0.184
Madu [79]2003 South America43517.250.559LT: 0.209LT: 0.161LT: 0.371NANA
Mahfoud [80]2011Lebanon510913.80.543NANA12M: 0.157NANA
Madge [5]2008Australia/Belgium/ England/Hungary/ Ireland/The Netherlands/ Norway.3042715.60.49NANANANALT: 0.089
Matsumoto [81]2008Japan172614.50.51NANALT: 0.398NALT: 0.099
McCann [82]2010Ireland3178NA0.59NANANANALT: 0.105
Meehan [83]1992United States694NANALT: 0.104NALT 0.539NANA
Mohl [84]2011Denmark2864170.608NANALT: 0.215NANA
Mojs [85]2012Poland1065NA0.72NANALT: 0.015NANA
Morey [86]2008Ireland364616.010.53NANALT: 0.056NALT: 0.091
Morey [87]2017England200015.60.52NANANANALT: 0.155
Muehlenkamp [88] 2009United States137515.480.561LT: 0.065NANALT: 0.214NA
Muehlenkamp [89] 2011United States39016.270.549LT: 0.056NANALT 0.159NA
Nada-Raja [90]2004New Zealand966NA0.489LT: 0.092NALT: 0.090NALT: 0.135
Nath [91]2012India181719.11NALT: 0.040NALT: 0.116NANA
Nixon [92]2008Canada56815.20.537NANANALT: 0.169NA
Nobakht [93]2017Iran200NA0.5NANANANALT: 0.405
Nock [94]2013USA6483NA0.482LT: 0.040LT: 0.040LT: 0.121NANA
O’Connor [95]2009Scotland1967NA0.534NANANANALT: 0.138
Omigbodun [96]2008Nigeria142914.40.49112M: 0.117NA12M: 0.229NANA
Patton [97]1997Australia1699NANA12M: 0.002NANANA12M: 0.051
Pawlowska [98]2016Poland568517.180.3LT: 0.044LT: 0.150LT: 0.243NALT: 0.137
Pérez-Amezcua [99]2010Mexico12424NA0.55LT: 0.088NALT: 0.466NANA
Plener [100]2009USA66514.80.571LT: 0.065NALT: 0.359LT: 0.256NA
Portzky [101] 2008Netherlands/Belgium888915.480.51NANANANALT: 0.072
Rey Gex [102]1998Switzerland926817.460.431LT: 0.030NA12M: 0.172NANA
Rudatsikira [103]2007Guyana1197NA0.579NANA12M: 0.184NANA
Rudd [104]1989United States737NA0.6112M: 0.056NA12M:0.437NANA
Sampasa-Kanyinga [105]2017Canada192214.40.5412M: 0.029NA12M: 0.105NANA
Sarno [106]2010Italy578NA0.825NANANALT: 0.206NA
Shaikh [107]2014India5184NA0.248NA12M:0.07612M: 0.033NANA
Shek [108]2012Hong Kong332812.590.472NA12M:0.047512M: 0.134NA12M: 0.327
Sidhartha [109]2006India120514.730.4LT: 0.080NALT: 0.217NALT: 0.180
Silviken [110]2007Norway269116.90.521LT: 0.095NASM: 0.151NANA
Soares [111]2015Brazil549NA0.801LT:0.027NALT: 0.118NANA
Somer [112]2015Turkey165616.80.55NANANALT: 0.313NA
Sornberger [113]2012Canada174414.920.508NANANALT: 0.245NA
Straub [114]2015Germany111714.830.527LT:0.056NALT: 0.317NANA
Tang [115]2011Hong Kong201315.60.45312M: 0.0348NA12M:0.08812M: 0.155NA
Tang [116] 2018China1562315.20.48512M: 0.044312M:0.0812M: 0.15912M: 0.292NA
Teo [117] 2011Australia207NANANANANANALT: 0.14
Thaku [118]2015India705NA0.488NANA12M: 0.309NANA
Toprak [119]2010Turkey63619.360.539LT:0.072NALT: 0.126NALT: 0.171
Tresno [120]2012Indonesia20719.78NALT:0.121NANALT: 0.565NA
Valdez-Santiago [121]2017Mexico2150915.4NALT: 0.027NANANANA
Vawda [122]2013South Africa22213.30.482LT: 0.054LT: 0.059LT 0.225NANA
Ventura-Junca [123] 2010Chile156716.20.459LT: 0.190NALT: 0.620NANA
Wan [124]2011China1762216.10.512NANANANA12M: 0.17
Whitlock [125]2011United States11529NA0.576NANANALT:0.154NA
Xin [126]2017China1188014.620.50512M: 0.049112M:0.1112M: 0.209NA12M: 0.30
Zetterqvist [127]2013Sweden3060NA0.505NANANA12M:0.356NA
Zubrick [128]2016Australia2563NA0.69212M: 0.024112M: 0.05212M: 0.07512M:0.08NA

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MDPI and ACS Style

Lim, K.-S.; Wong, C.H.; McIntyre, R.S.; Wang, J.; Zhang, Z.; Tran, B.X.; Tan, W.; Ho, C.S.; Ho, R.C. Global Lifetime and 12-Month Prevalence of Suicidal Behavior, Deliberate Self-Harm and Non-Suicidal Self-Injury in Children and Adolescents between 1989 and 2018: A Meta-Analysis. Int. J. Environ. Res. Public Health 2019, 16, 4581. https://doi.org/10.3390/ijerph16224581

AMA Style

Lim K-S, Wong CH, McIntyre RS, Wang J, Zhang Z, Tran BX, Tan W, Ho CS, Ho RC. Global Lifetime and 12-Month Prevalence of Suicidal Behavior, Deliberate Self-Harm and Non-Suicidal Self-Injury in Children and Adolescents between 1989 and 2018: A Meta-Analysis. International Journal of Environmental Research and Public Health. 2019; 16(22):4581. https://doi.org/10.3390/ijerph16224581

Chicago/Turabian Style

Lim, Kim-San, Celine H. Wong, Roger S. McIntyre, Jiayun Wang, Zhisong Zhang, Bach X. Tran, Wanqiu Tan, Cyrus S. Ho, and Roger C. Ho. 2019. "Global Lifetime and 12-Month Prevalence of Suicidal Behavior, Deliberate Self-Harm and Non-Suicidal Self-Injury in Children and Adolescents between 1989 and 2018: A Meta-Analysis" International Journal of Environmental Research and Public Health 16, no. 22: 4581. https://doi.org/10.3390/ijerph16224581

APA Style

Lim, K.-S., Wong, C. H., McIntyre, R. S., Wang, J., Zhang, Z., Tran, B. X., Tan, W., Ho, C. S., & Ho, R. C. (2019). Global Lifetime and 12-Month Prevalence of Suicidal Behavior, Deliberate Self-Harm and Non-Suicidal Self-Injury in Children and Adolescents between 1989 and 2018: A Meta-Analysis. International Journal of Environmental Research and Public Health, 16(22), 4581. https://doi.org/10.3390/ijerph16224581

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