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Article

Adolescent Suicides in the Western Pacific Region Have Become a More Serious Public Health Problem than in Other Regions

by
Ruri Okubo
,
Ryusuke Matsumoto
,
Eishi Motomura
and
Motohiro Okada
*
Department of Neuropsychiatry, Division of Neuroscience, Graduate School of Medicine, Mie University, Tsu 514-8507, Japan
*
Author to whom correspondence should be addressed.
Psychiatry Int. 2024, 5(4), 564-584; https://doi.org/10.3390/psychiatryint5040041
Submission received: 11 August 2024 / Revised: 11 September 2024 / Accepted: 20 September 2024 / Published: 24 September 2024
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Abstract

:
Globally, suicide mortality rates have decreased in this century; however, it has been reported that the decreasing trends of some subgroups were attenuated in the late 2010s. These tendencies are pronounced among adolescents. In this study, the temporal fluctuations of the age-standardized death rate of suicide (ASDR-suicide), crude mortality rate of suicide (CMR-suicide), and percentage of suicides per total deaths (PTD-suicide) among adolescents (10–24 years) in the global high-income and middle-income countries and in the Western Pacific Region (WPR) from 1990 to 2019, as well as the fixed effects of communication factors (penetration of cellular telephones and the Internet) on the ASDR-suicide/CMR-suicide/PTD-suicide of adolescents, were analyzed using the WHO Mortality Database. The male ASDR-suicide in global middle-income countries decreased, and those of males in global high-income countries and females in middle-income countries were unchanged, while the rate of other groups (males in the WPR and females in high-income countries and the WPR) increased. The ASDR-suicide of adolescent males in the WPR was almost equivalent to that of males in global high-income and middle-income countries in the 1990s but was higher than the rate in the 2010s. The ASDR-suicide of adolescent females in the WPR was consistently higher than that of females in global high-income and middle-income countries from 1990 to 2019, but the differences widened over time. The PTD-suicide of both males and females in middle-income countries was unchanged, whereas the PTD-suicide in global high-income countries and the WPR increased over time. The PTD-suicide in the WPR markedly increased by >40% in the late 2010s. The fixed effects of cellular telephone and Internet penetrations were negatively and positively related to adolescent suicide in the WPR, respectively. Therefore, these results suggest that, in this century, suicide prevention in adolescent health activities has been increasing in importance in the WPR compared with other regions.

1. Introduction

Adolescence (10–24 years of age) is the most stable generation in biological life prognosis; indeed, the crude mortality rate per 100,000 population (CMR) of all causes is the lowest among overall generations [1,2,3,4,5]. The leading causes of death drastically change with age, shifting from congenital abnormalities and infections in newborns/young children to road traffic accidents, interpersonal violence, and self-harm in adolescence [2,3,4,5].
It is well known that suicide displays age-dependent and geographic features. The suicide mortalities and the sex ratio (males/females) of suicide mortality in Asia countries have been higher than those in Western countries [6]. Previous epidemiologic findings suggested that complicated interactions among traditional cultural values, rapid economic transitions under market globalization, higher sensitivity to family conflicts, and financial security issues play important roles in these suicidal features in Asia [6,7,8]. It has been suggested that the relatively higher suicide mortality among females in Asia may be related to the higher prevalence of psychiatric disorders (mood disorders) and vulnerability to psychosocial stress [9], whereas other reports have emphasized that the role of mental deterioration in suicide in Asia was less important than in Western countries [6,10]. Suicide among younger children (younger than 10 years of age) is very rare; however, it begins to be detected in younger adolescents and drastically increases during adolescence [11]. Although the global age-standardized death rate of suicide per 100,000 population (ASDR-suicide) was 9.2 in 2019, the CMR of suicide (CMR-suicide) increased from 1.6 (10–14 years of age) to 5.9 (15–19 years of ages) in 2019 [12]. The CMR-suicide among adolescents was lower than that in adults, whereas from another perspective, suicide was the fifth leading cause of death globally in those aged 10–19 years [11,13,14,15]. Suicide was especially severe in Europe and the Western Pacific Region (WPR) and was the second leading cause of death among adolescents in those regions [12]. Therefore, suicide is one of the most severe adolescent health concerns globally, but it appears to be more serious in Europe and the WPR [11,13,14,15]. In other words, to discuss the seriousness of adolescent suicide, it is necessary to consider not only ASDR/CMR-suicide but also the proportion of suicides in the total number of deaths (PTD-suicide) among adolescents.
The Comprehensive Mental Health Action Plan of the World Health Organization (WHO) set a target of reducing global suicide mortality by 10% between 2012 and 2020 [16]. Temporal fluctuations of ASDR/CMR-suicide have usually been adopted to evaluate the Comprehensive Mental Health Action Plan [13]. Globally, ASDR-suicide has decreased in this century; however, the decreasing trends in some regions have attenuated or, conversely, increased after the late 2010s in countries such as Japan (attenuated decreasing trends) and the United States (increasing) [13,14,17,18,19]. These tendencies are particularly pronounced in adolescents [18,20,21,22]. Furthermore, recent studies using the “WHO Mortality Database” revealed that fluctuations in ASDR/CMR-suicide varied geographically [18,20,21,22]. In particular, although suicide was the second leading cause among all causes of death for adolescents in both the WPR and Europe, ASDR-suicide among adolescents consistently decreased in Europe [20] but increased in the WPR [18,21,23,24,25,26]. These previous findings suggest that evidence-based suicide prevention measures for adolescent health require not only knowledge of trends in suicide mortality rates (ASDR-suicide and CMR-suicide) but also the temporal fluctuations of the PTD-suicide of adolescents.
It is well known that various factors, such as socioeconomic and psychosocial factors, play important roles in suicide. Indeed, a number of studies have reported a plethora of findings regarding the causes and/or backgrounds of adolescent suicide [11,23,27,28,29,30]. Previously, the various risk factors for suicide among adolescents in the United States were reported to be diverse, depending on sex, ethnic group, and religion [31]. A longitudinal study of clinical cases integrating various risk factors and their interactions showed that health problems, including physical and psychiatric disabilities, were risk factors for suicide [32,33]. The majority of previous studies suggested that suicide risks across countries in the WPR may be consistent with those found in Western/European countries; however, countries in the WPR are composed of culturally, religiously, and economically diverse peoples. Indeed, diverse features related to suicide among the WPR countries have been revealed. In New Zealand, adolescents with the lowest socioeconomic status were reported to be over thirty times more likely to attempt suicide than individuals with a higher socioeconomic status [34]. However, in several Asian countries, school-related problems were common precipitants of adolescent suicide attempts [22,35], and the impacts of school-related problems also constituted over 40% of the causes of suicide among adolescents in Japan [18,21]. The populations in urban areas among WPR countries are larger compared with those among OECD member countries. In both the Republic of Korea (South Korea) and Japan, the CMR-suicide in the urban areas is lower than that in the rural areas, but the increasing trends of CMR-suicide in urban areas are greater than those in the rural areas [17,22,36]. Despite these efforts, cross-national causality analyses have been underestimated compared with time-series analyses, since valid international data on suicide risk factors for each country are limited and difficult to obtain. Thus, the majority of studies are limited to speculation due to the indirect comparisons of results between different cohort studies [18,20,21,22,37,38].
Adolescence represents a dramatic transition in psychosocial development, as a stage from dependence to independence [1]. Adolescents must strive for education, training, and physical strengthening for their future psychosocial and socioeconomic independence [1]. Therefore, the drastic psychosocial and socioeconomic transformation may affect adolescent individuals through education, training, and physical strengthening processes. In this century, the increasing penetrations of both the Internet and cellular telephones have been affecting adolescent lifestyles, including education, recreation, and communication with peers [39,40,41,42]. Although the Internet has become an important tool in the education of students, the adverse health consequences associated with inappropriate Internet use are a matter of concern [42,43,44,45,46]. The prevalence of Internet addiction is also increasing over time with increasing Internet penetration [44]. Notably, it is concerning that the increase in Internet usage has been related to an increase in health-risk behaviors, including suicide [42,43,45,46]. Thus, cross-national comparative analysis of the impact of the penetrations of the Internet and cellular telephones on adolescent suicide can provide important information for planning adolescent suicide prevention measures.
The WHO recommends dividing the 194 member countries into six regions (including the WPR) to promote its comprehensive health policies [47]. Based on these backgrounds, this study aimed to clarify the following three points: (1) the identification of the temporal fluctuations of adolescent suicides (ASDR/CMR-suicide) in the WPR in comparison with the global high-income and middle-income countries; (2) the determination of the proportion of suicides among causes of overall adolescents (PTD-suicide) in the WPR; and (3) the impacts of the penetration of the Internet and cellular telephones on adolescent suicide mortalities, using the “WHO Mortality Database” and the International Telecommunication Union (ITU) database [47,48]. Finally, through the findings of this study (temporal fluctuation of several values related to adolescent suicide, including ASDR-, CMR-, and PTD-suicide, as analyzed by time series analysis in the WPR and the impacts of the penetrations of the Internet and cellular telephones on adolescent suicide), we discuss how to improve suicide prevention measures for adolescents in the post-COVID-19 era.

2. Materials and Methods

This cross-sectional study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines [49]. The Medical Ethics Review Committee of Mie University waived the requirement for informed consent and ethical approval because these data were publicly available.

2.1. Data Source

Populations and the annual number of death caused by suicides (X60–X84, Y87.0 in ICD-10), infectious and parasitic diseases (A00–B99, G00–G04, G14, N70–N73, P37.3, P37.4 in ICD-10), respiratory infections (H65–H66, J00–J22, P23, U04, U07.1, U07.2, U09.9, U10.9 in ICD-10), malignant neoplasms (cancer: C00–C97 in ICD-10), road traffic accidents (V01–04, V06, V09, V10–79, V80–89, V99, Y85.0 in ICD-10) and violence (X85–Y09, Y871 in ICD-10) disaggregated by sex (male and female), age (5-year intervals: 10–14, 15–19, and 20–24 years), and overall age from 1990 to 2019 were obtained from the WHO Mortality Database [47]. Cellular telephone penetration (number of subscriptions per 100 people: mobile-sub) and Internet penetration (number of Internet users per 100 people: Internet users) were obtained from the International Telecommunication Union (ITU) [48].
The crude mortality rate per 100,000 population (CMR) of all-cause, suicide, infectious/parasitic disease, respiratory infection, cancer, traffic accidents, and violence, disaggregated by sex, age, and calendar year, was calculated by dividing the annual number of deaths by the 100,000 population of the corresponding group in the same calendar year. The age-standardized death rate per 100,000 suicides (ASDR-suicide) of overall ages and adolescents (10–25 years of age) was calculated using the WHO World Standard Population Model [50]. The proportion of suicides among all deaths (percentage of suicides per total deaths: PTD-suicide) was calculated by dividing the number of suicides by all deaths in the same groups. In the present study, the observation period was set to be from 1990 to 2019 to eliminate the impact of the COVID-19 pandemic and the incomplete suicide data in the WHO Mortality Database. According to the country income classification of the World Bank, the ASDR-suicide and PTD-suicide of global high-income and middle-income (upper-middle and lower-middle income) countries were calculated.

2.2. Statistical Analysis

Joinpoint regression was used to conduct a time-trend analysis of ASDR-suicide, CMR-suicide, and PTD-suicide from 1990 to 2019 using Joinpoint Regression Software (ver 5.0.2; National Cancer Institute). Joinpoint regression, which is well known for segmented regression analysis, simply fits the joinpoint model allowed by the trend data and identifies significant points where the trends change [18,22,26,51]. The estimated annual percent change (APC) and the corresponding 95% confidence interval (95%CI) were calculated for each identified segment by fitting a regression line to the natural logarithm of each value using the calendar year as a regressor variable [ln (rate) = a × (calendar year) + b; APC was estimated as 100 × (eb−1)]. The estimated average annual percent change from 1990 to 2019 (AAPC) was also calculated using the method that was used to estimate the APC [18,25,26,51,52]. Two-tailed p-values of <0.05 were considered to indicate statistical significance. The fixed effects of communication factors (mobile-sub and Internet-user) on adolescent ASDR-suicide and CMR-suicide at 10–14, 15–19, and 20–24 years of age were analyzed using hierarchical linear model with robust standard error (HLM) using Gretl v2023c [17,21,22]. Currently, the HLM is established as the most popular and useful statistical method for analyzing suicide causality at the national and international levels [53,54]. In particular, the HLM is considered to be a powerful statistical method for determining fixed effects on suicide mortality due to the elimination of “Simpson’s paradox” [55]. Two-tailed p-values of <0.05 were considered to indicate statistical significance. The time-dependent fluctuations of ASDR-suicide and PTD-suicide in the 1990s, 2000s, and 2010s were analyzed using two-way analysis of variance (ANOVA) with Scheffe’s post hoc test using BellCurve for Excel version 3.2 (Social Survey Research Information Co., Ltd., Tokyo, Japan). When the F-value of the ANOVA was significant (p < 0.05) and there was no significant variance inhomogeneity, the data were analyzed using Scheffe’s post hoc test [56].
The WHO Mortality Database published the mortality data in the WPR, including Australia, Brunei Darussalam, Hong Kong, Japan, the Republic of Korea (South Korea), Malaysia, New Zealand, the Philippines, Singapore, and Thailand. This study adopted the mortality data from Australia, Hong Kong, Japan, South Korea, New Zealand, and Singapore, which are high-income countries, while the data from Brunei Darussalam, Malaysia, the Philippines, and Thailand were incomplete and included many missing values, making an accurate statistical analysis impossible. Data were missing for Australia in 2005, Hong Kong in 2018–2019, and New Zealand in 2016–2019. No manipulation was performed for the missing values [47].

3. Results

The descriptive statistics, average populations, and total suicide numbers from 1990 to 2019 in the global high-income countries, global middle-income countries, and the WPR are summarized in Table 1.

3.1. ASDR-Suicide and PTD-Suicide of Overall Ages among Global High-Income and Middle-Income Countries and the WPR from 1990 to 2019

The ASDR-suicide of males of overall ages in global high-income and middle-income countries decreased from 1990 to 2019 (Figure 1, Table 2). Conversely, the ASDR-suicide of males of overall ages in the WPR did not change from 1990 to 2019, whereas that displayed the reversed U-shaped pattern (the joinpoint from increasing to decreasing was 2004) was observed in the WPR (Figure 1, Table 2). In the 1990s, the ASDR-suicides of males in the three groups (global high-income countries, middle-income countries, and the WPR) were almost equal, whereas the ASDR-suicide of males in the WPR was higher in comparison with that of the high-income and middle-income countries (Figure 2). The fluctuations of the ASDR-suicide of females were similar to those of males, indicating that the gaps among the three groups increased over time (Figure 1, Table 2). In the 1990s, the ASDR-suicide of females in the WPR was already higher in comparison with that of high-income and middle-income countries (Figure 2).
The fluctuations of the PTD-suicide of males and females in the global middle-income countries and the WPR were similar to the fluctuations of the ASDR-suicide (Figure 1, Table 2). However, the PTD-suicide in the global high-income countries showed different patterns from the ASDR-suicide. The PTD-suicide of males in the global high-income countries increased from 1990 to 2010, then decreased from 2010 to 2019, whereas the PTD-suicide of females increased from 1990 to 1999 and 2007 to 2019 but decreased from 1999 to 2007 (Figure 1).

3.2. ASDR-Suicide and PTD-Suicide among Adolescents in Global High-Income, Middle-Income, and WPR Countries from 1990 to 2019

In contrast to overall age, the ASDR-suicide of adolescent males in the global middle-income countries decreased; that of males in high-income countries and females in middle-income countries did not change, whereas the rate of other groups (males in the WPR and females in high-income countries and the WPR) increased (Figure 3, Table 3). The PTD-suicide of males and females in middle-income countries did not change, whereas the rates in global high-income countries and the WPR increased over time (Figure 3, Table 3). Notably, the PTD-suicide in the WPR markedly increased by approximately 40% in the late 2010s (Figure 4).

3.3. Adolescent ASDR-Suicide among Countries in the WPR from 1990 to 2019

The fluctuations in adolescent ASDR-suicide among countries in the WPR showed particularly complicated patterns. The ASDR-suicide of males in Australia (approximately 20) and New Zealand (approximately 30) in the 1990s was markedly higher than that in other countries (Figure 5). The ASDR-suicide of males in New Zealand consistently decreased, whereas that of males in Australia also decreased from 1990 to 2010, followed by an increase during the 2010s (U-shaped pattern) (Figure 5). Notably, the ASDR-suicide of males and females in Japan increased, but the rates in South Korea, Hong Kong, and Singapore did not change from 1990 to 2019 (Figure 5, Table 4).

3.4. Adolescent PTD-Suicide among Countries in the WPR from 1990 to 2019

In contrast to the ASDR-suicide, the PTD-suicide in all the countries in the WPR increased consistently from 1990 to 2019 (Figure 6, Table 5). The PTD-suicide in all the countries in the WPR was approximately ≤20% in the 1990s; however, it then increased to over 40% (except for Singapore) (Figure 6, Table 5).

3.5. Age-Dependent Fluctuation of PTD among Global High-Income, Middle-Income, and WPR Countries from 1990 to 2019

The discrepancy in temporal fluctuation patterns between the ASDR-suicide and PTD-suicide in adolescents in the WPR probably involved a combination of a relative increase in ASDR-suicide and a decrease in the ASDR of other causes. In global high-income countries and the WPR, the leading causes of death at 10–14 and 15–24 years of age in the 1990s were cancer and traffic accidents, respectively (Figure 7 and Figure 8). The impact of cancer was consistent, whereas that of traffic accidents decreased from the 1990s to the 2010s. In contrast to traffic accidents, PTD-suicide increased, resulting in suicide becoming the leading cause of death among adolescents in global high-income countries and in the WPR (Figure 4 and Figure 5). These relations between traffic accidents and suicides were much more pronounced in the WPR in comparison with the global high-income countries (Figure 7 and Figure 8).

3.6. Causality Analyses for Increasing Adolescent Suicides in the WPR from 1990 to 2019

The fixed effects of the PTD caused by traffic accidents were negatively related to PTD-suicide in all male and female adolescent groups in the WPR. The fixed effects of the PTD caused by cancer were negatively related to PTD-suicide in all adolescent female groups, whereas the negative impact of cancer was only observed in males under 15 years of age (the PTD-suicide of males > 15 years of age was not related to the PTD caused by cancer) (Table 6). In the population over 20 years of age, PTD-suicide in males was negatively related to infectious and parasitic diseases, respiratory infections, traffic accidents, and violence, while PTD-suicide in males was negatively related to cancer, respiratory infections, traffic accidents, and violence. In contrast to the PTD, CMR-suicide was not related to any CMR other than suicide in any of the adolescent groups (Table 6). The increase in PTD-suicide in the WPR is assumed to be relatively attributable to deaths from causes other than suicide. However, the increase in CMR-suicide among adolescents in the WPR was not related to the CMR of other causes of death.
In contrast to the cause of death, the fixed effects of communication factors (penetrations of cellular telephone and Internet) on CMR-suicide and PTD-suicide showed similar relations. The penetration of cellular telephones (mobile-sub) was negatively related to CMR-suicide in males > 15 years and in females > 20 years of age and to PTD-suicide in all groups other than males < 15 years of age (Table 7). In contrast, Internet penetration (Internet-user) was positively related to PTD-suicide in males > 15 years of age and all female groups. In females, the positive impacts of Internet penetration on CMR-suicide were only detected at >20 years of age (Table 7).

4. Discussion

This study revealed the common temporal fluctuations in adolescent suicide mortality underlying the recent increase in ASDR-suicide/CMR-suicide/PTD-suicide from 1990 to 2019 in the WPR. The ASDR-suicide of adolescent males in global high-income, global middle-income, and WPR countries (Australia, Hong Kong, Japan, South Korea, New Zealand, and Singapore) remained unchanged, decreased, and increased from 1990 to 2019, respectively. Conversely, in adolescent females, ASDR-suicide in global middle-income countries remained unchanged, while the rate in both the WPR and global high-income countries increased from 1990 to 2019. PTD-suicide in global middle-income countries remained unchanged from 1990 to 2019, while that in both the WPR and global high-income countries increased. These findings indicate the possibility that adolescent suicide in the WPR has emerged as a major public health issue compared with other regions from 1990 to 2019 (before the COVID-19 pandemic outbreak). This possibility is supported by the fact that in the 1990s, PTD-suicide in the WPR and global high-income countries was almost equal (approximately 15%), while in the 2010s, PTD-suicide increased to approximately 20% in the global high-income countries and 40% in the WPR. The fixed effects of cellular telephone penetration contributed to a decrease in adolescent suicide, while Internet penetration contributed to an increase in adolescent suicide. The findings of this study suggest that medical and public health measures in the WPR have promoted adolescent health; however, some challenges related to communication factors, such as excessive use of the Internet, might, at least partially, have had serious negative impacts and act as risk factors for adolescent suicide in the WPR from 1990 to 2019 (before the COVID-19 pandemic outbreak).

4.1. Characteristics of Fluctuation of Adolescent Suicide in the WPR

The increasing fluctuation pattern of adolescent ASDR-suicide in the WPR was greater than that observed in the global high-income countries, but the patterns of fluctuation were not identical in each country in the WPR. In the 1990s, the ASDR-suicide of adolescent males in both Australia (approximately 20) and New Zealand (approximately 30) was markedly higher in comparison with the other WPR countries and then decreased from the 1990s to the early 2010s. It is well known that the ASDR-suicide/CMR-suicide of overall age in Asian countries sharply increased after the Asian financial crisis in 1997 [6,57,58,59,60]. A nonsignificant increase in adolescent ASDR-suicide, which synchronized with the Asian financial crisis, was observed in both Japan and South Korea. National/government suicide prevention programs were implemented in Australia, New Zealand, South Korea, and Japan in 1992, 1996, 2004, and 2007, respectively [21,34,61,62,63]. For several years after the implementation of the national/governmental suicide prevention programs, adolescent ASDR-suicide decreased; this decreasing trend continued for approximately 10 years, followed by an attenuation of the decreasing trend or a transformation to an increasing trend. In contrast, the fluctuation pattern of PTD-suicide shows a consistent increase in the WPR countries. Furthermore, in the 2010s, PTD-suicide among adolescent males and females consistently increased in all the WPR countries. It is well known that the sex ratio (males/females) of suicide mortality in Asia is consistently lower than that in Western countries [6,13,64,65,66]. In South Korea, surprisingly, the PTD-suicide of female adolescents was higher in comparison with that of males, with the male-to-female sex ratio of ASDR-suicide in South Korea being lower than that in other countries in the WPR, indicating that adolescent female suicide in South Korea is dominant in comparison with other countries.
Considering the findings obtained from the causality analyses, the drastic increase in adolescent PTD-suicide in the WPR is considered to be the result of the interaction between decreasing death from other causes and increasing adolescent suicide, but the increase in adolescent ASDR-suicide itself is not affected by the decrease in other causes of death. Therefore, the measures promoting adolescent public health have successfully contributed to a decrease in overall adolescent deaths from causes other than suicide but may have made relatively little progress in reducing suicide compared with other targets.

4.2. Impacts of Communication Tool Factors on Adolescent Suicide in the WPR

In this century, communication methods have drastically transformed with the advent of the cellular telephone and the Internet. During the COVID-19 pandemic, social restrictions to suppress the pandemic made digital communication tools even more important, resulting in both cellular telephones and the Internet becoming essential social infrastructures for education, recreation, and communication with peers [39,40,41]. However, it is concerning that increased Internet usage has been related to increased health-risk behaviors, including suicide [42,43,45,46]. In this study, cellular telephone penetration consistently suppressed suicide among adolescents, whereas increasing opportunities for Internet usage possibly contributed to the increase in adolescent suicides. Considering that the cellular telephone is a major terminal of Internet access, this discrepancy suggests that the cellular telephone is an essential and useful communication tool for the majority of adolescents but that Internet use may be a risk factor for suicide for some vulnerable adolescents. The adverse health consequences associated with inappropriate Internet use, especially among students, are a matter of concern [43,44]. The prevalence of Internet addiction is increasing over time, with increasing Internet penetration [44]. In the relevant literature, the major discourse regarding social media use and the risk factors for adolescent health has focused on the frequency of Internet use, such as screen time; currently, however, Internet use patterns are being evaluated to better understand the adverse health consequences, including suicide among adolescents [43,44,67].
Although this study did not analyze the impacts of Internet use patterns on suicide mortality, the fixed effects of Internet penetration on national-level adolescent suicides in the WPR indicated that there was a positive relationship. The fixed-effects model can control for unobserved time-invariant factors, such as culture, climate, and economic and educational situation (as well as sleep, diet, exercise, and social rhythms), which may affect the incidence or mortality induced by Internet use, resulting in an effect on regional suicide mortality rates each period [68,69,70]. The present study adopted robust standard errors, clustered according to the countries in the WPR, to prevent heteroscedasticity and autocorrelation. Given the advantages of fixed-effect analysis using the hierarchical linear regression model with robust standard errors, the positive impacts of increasing Internet penetration on adolescent suicides in the WPR, as demonstrated in this study, cannot be ignored.
This study detected interesting findings regarding the impacts of Internet penetration on adolescent suicide mortality. Internet penetration was positively related to the female adolescent PTD-suicide of those aged 10–24 and the male PTD-suicide of those aged 15–24, but it was not related to the PTD-suicide of those aged 10–15. Additionally, the β-values (coefficients) of the HLM of the female PTD-suicide were larger than those of the males among all the age groups. These results suggest the possibility that the increasing Internet penetration was probably involved, at least partially, in drastically increasing the female adolescent PTD-suicide in the WPR in the 2010s. Various studies conducted after 2010 support the possibility that females are more likely to suffer from the health hazards caused by the Internet than males. The Internet or social media exposure times of female adolescents are greater than those of male adolescents, and female adolescents use the Internet more actively than males [43]. Female adolescents are also more likely to be victims of cyberbullying compared with males [71]. There have even been reported findings showing that the association between Internet-based behavior and mental health deterioration, such as depression and suicide risks, was predominant in female adolescents in comparison with males [72,73,74]. Considering these previous findings, the results in this study emphasize the importance of exploring the impacts of the penetration of the Internet on female adolescent suicides compared with male suicides.
The sex ratio of PTD-suicide was particularly low in South Korea and Japan, among the WPR countries. Traditionally, it is well known that in both countries, hanging has been the leading method of suicide compared with the methods used in the United States and Australia [64]. In 2024, a very shocking finding regarding the sex differences in suicides in Japan was reported [75]. The association between suicides and mosaic chromosomal alterations, including mosaic loss of the X and Y chromosomes, revealed that mosaic losses of the X chromosome were significantly increased in female suicide [75]. This finding is preliminary, but it may indicate the impacts of genetic backgrounds on suicide mortality and the sex differences in suicides in Japan.

4.3. Limitation

The present study was associated with several limitations. To identify the regional features of adolescent suicide mortality in the WPR, this study determined the temporal fluctuations of various suicide values (ASDR-suicide, CMR-suicide, and PTD-suicide) in the WPR, including Australia, Hong Kong, Japan, South Korea, New Zealand, and Singapore, using the WHO Mortality Database. However, all six countries are high-income countries. The WHO Mortality Database published suicide statistics for middle-income countries in the WPR, including Malaysia, the Philippines, and Thailand. The suicide statistics of these three middle-income countries in the WPR were incomplete and had numerous missing values, which made it impossible to perform an accurate statistical analysis. The data from China, which has the largest population and number of suicides in the WPR [76,77,78], were also not published in the WHO Mortality Database. To clarify the actual features of adolescent suicides in the WPR, it is necessary to conduct analyses that include suicide mortality in middle-income countries in the WPR.
This was a cross-sectional observational study that may have been subject to an ecological fallacy [79,80]. Comparisons of suicide mortality across different populations over the same period or within the same population over time are subject to confounding. Considering the ecological fallacy, the positive impact of Internet penetration on suicide mortality among adolescents in the WPR should be clarified through more detailed analyses.
In order to identify the actual circumstances of suicide, it is necessary to determine the suicidal behavior, which is composed of completed suicide, the suicide attempt, and suicidal ideation [81]. However, this study could not conduct a survey that included suicidal ideation and suicide attempts, since this study analyzed the data from the WHO Mortality Database.

5. Conclusions

This cross-sectional study revealed the existence of specific patterns of fluctuation in adolescent ASDR-suicide/CMR-suicide among six high-income countries in the WPR in comparison with global high- and middle-income countries. In the 1990s, male ASDR-suicide in Oceanian countries (Australia and New Zealand) was markedly higher than in other countries, whereas, after the implementation of national/government suicide prevention programs, ASDR-suicide in these countries decreased. ASDR-suicide in Japan and South Korea also decreased after the implementation of national/government suicide prevention programs in the 2000s. Surprisingly, despite these efforts, in the late 2010s, ASDR-suicide among adolescents in the WPR increased. The increasing penetration of cellular telephones is a protective factor for adolescent suicide, while the increasing penetration of the Internet is a risk factor. In contrast to ASDR-suicide, PTD-suicide consistently increased in all countries in the WPR from 1990 to 2019. Therefore, among adolescent health activities, the importance of suicide prevention in the WPR has been increasing in comparison with other regions in the current century. Considering the discrepancy between the effects of the penetrations of cellular telephones and the Internet on adolescent suicide mortality, analyses of both the actual state of Internet usage in adolescents and the impact of Internet usage patterns on adolescent suicide mortality should be required in the development of guidelines for appropriate Internet use for vulnerable adolescents. An examination of the temporal fluctuations of adolescent suicide mortalities in the WPR before the COVID-19 pandemic outbreak, from 1990 to 2019 (for 30 years), using the WHO Mortality Database, could strengthen the validity of the findings from this study. When the annual numbers of suicides during and after the COVID-19 pandemic are published in the WHO Mortality Database, the findings from this study could contribute to a more detailed understanding of the impact of COVID-19 and its side effects on suicide mortality through analyses with an extended observation period.

Author Contributions

M.O. had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. R.O. and R.M., concept and design, acquisition, analysis, or interpretation of data, drafting of the manuscript, critical review of the manuscript for important intellectual content, statistical analysis, obtained funding; E.M., acquisition, analysis, or interpretation of data, drafting of the manuscript and statistical analysis; M.O., concept and design, acquisition, analysis, or interpretation of data, drafting of the manuscript, critical review of the manuscript for important intellectual content, statistical analysis, obtained funding, administrative, technical, or material support, and supervision. All authors have read and agreed to the published version of the manuscript.

Funding

This study is supported by the Japan Society for the Promotion of Science (23K06987) and the Regional Suicide Countermeasures Emergency Enhancement Fund of Mie Prefecture (2024-40). The views and opinions expressed therein are those of the authors and do not necessarily reflect those of the JSPS or Mie Prefecture. The funder played no role in the study design, in the collection, analysis, or interpretation of the data, in the writing of the paper, or in the decision to submit the article for publication. All authors were independent from the funders.

Institutional Review Board Statement

The Medical Ethics Review Committee of Mie University waived the need for ethical approval due to the use of publicly available governmental data.

Informed Consent Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest.

Data Availability Statement

All raw data are publicly available to any persons via the databases in WHO (https://www.who.int/data/data-collection-tools/who-mortality-database), World Bank (https://data.worldbank.org/indicator) (accessed on 11 September 2024), and ITU (https://datahub.itu.int/data/) (accessed on 11 September 2024). Participant consent for data sharing was not obtained, but the presented data are anonymized by WHO and all governments, and the risk of identification is none.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Temporal fluctuations of ASDR-suicide and PTD-suicide of overall ages among global high-income, middle-income, and the WPR countries from 1990 to 2019. Temporal fluctuation of annual ASDR-suicide (upper side panels: (A1–C1)) and PTD-suicide (lower side panels: (A2–C2)) of overall ages among males (blue) and females (red) in high-income (A1,A2), middle-income (B1,B2), and the WPR (C1,C2) countries from 1990 to 2019 using joinpoint regression. Ordinates indicate the annual ASDR-suicide (per 100,000 population: (A1–C1)) or PTD-suicide (%: (A2–C2)). Abscissas indicate calendar years. Circles indicate the observed data. Solid and dotted lines indicate the significant and nonsignificant trends of ASDR-suicide and PTD-suicide detected by joinpoint regression, respectively.
Figure 1. Temporal fluctuations of ASDR-suicide and PTD-suicide of overall ages among global high-income, middle-income, and the WPR countries from 1990 to 2019. Temporal fluctuation of annual ASDR-suicide (upper side panels: (A1–C1)) and PTD-suicide (lower side panels: (A2–C2)) of overall ages among males (blue) and females (red) in high-income (A1,A2), middle-income (B1,B2), and the WPR (C1,C2) countries from 1990 to 2019 using joinpoint regression. Ordinates indicate the annual ASDR-suicide (per 100,000 population: (A1–C1)) or PTD-suicide (%: (A2–C2)). Abscissas indicate calendar years. Circles indicate the observed data. Solid and dotted lines indicate the significant and nonsignificant trends of ASDR-suicide and PTD-suicide detected by joinpoint regression, respectively.
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Figure 2. ASDR-suicide and PTD-suicide of overall ages among males and females in global high-income, middle-income, and WPR countries from 1990 to 2019. Upper side panels indicate ASDR-suicide of males (A1) and females (A2). Lower side panels indicate PTD-suicide of males (B1) and females (B2). * p < 0.05, ** p < 0.01 relative to high-income countries, # p < 0.05, ## p < 0.01 relative to 1990s by two-way analysis of variance (ANOVA) with Scheffe’s post hoc test. F-values of ASDR-suicide of males and females were [Fregion(2,89) = 75.3 (p < 0.01), Fyear(2,89) = 75.7 (p < 0.01), Fregion*year(4,89) = 42.0 (p < 0.01)] and [Fregion(2,89) = 49.4 (p < 0.01), Fyear(2,89) = 59.9 (p < 0.01), Fregion*year(4,89) = 24.3 (p < 0.01)], respectively. F-values of ASDR-suicide of males and females were [Fregion(2,89) = 73.6 (p < 0.01), Fyear(2,89) = 74.0 (p < 0.01), Fregion*year(4,89) = 33.8 (p < 0.01)] and [Fregion(2,89) = 74.1 (p < 0.01), Fyear(2,89) = 53.3 (p < 0.01), Fregion*year(4,89) = 15.2 (p < 0.01)], respectively.
Figure 2. ASDR-suicide and PTD-suicide of overall ages among males and females in global high-income, middle-income, and WPR countries from 1990 to 2019. Upper side panels indicate ASDR-suicide of males (A1) and females (A2). Lower side panels indicate PTD-suicide of males (B1) and females (B2). * p < 0.05, ** p < 0.01 relative to high-income countries, # p < 0.05, ## p < 0.01 relative to 1990s by two-way analysis of variance (ANOVA) with Scheffe’s post hoc test. F-values of ASDR-suicide of males and females were [Fregion(2,89) = 75.3 (p < 0.01), Fyear(2,89) = 75.7 (p < 0.01), Fregion*year(4,89) = 42.0 (p < 0.01)] and [Fregion(2,89) = 49.4 (p < 0.01), Fyear(2,89) = 59.9 (p < 0.01), Fregion*year(4,89) = 24.3 (p < 0.01)], respectively. F-values of ASDR-suicide of males and females were [Fregion(2,89) = 73.6 (p < 0.01), Fyear(2,89) = 74.0 (p < 0.01), Fregion*year(4,89) = 33.8 (p < 0.01)] and [Fregion(2,89) = 74.1 (p < 0.01), Fyear(2,89) = 53.3 (p < 0.01), Fregion*year(4,89) = 15.2 (p < 0.01)], respectively.
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Figure 3. Temporal fluctuations of ASDR-suicide and PTD-suicide among adolescents in global high-income, middle-income, and WPR countries from 1990 to 2019. Temporal fluctuation of annual ASDR-suicide (upper side panels: (A1–C1)) and PTD-suicide (lower side panels: (A2–C2)) among adolescent males (blue) and females (red) in high-income (A1,A2), middle-income (B1,B2), and WPR (C1,C2) countries from 1990 to 2019 using joinpoint regression. Ordinates indicate the annual ASDR-suicide (per 100,000 population: (A1–C1)) or PTD-suicide (%: (A2–C2)). Abscissas indicate calendar years. Circles indicate the observed data. Solid and dotted lines indicate the significant and nonsignificant trends of ASDR-suicide and PTD-suicide detected by joinpoint regression, respectively.
Figure 3. Temporal fluctuations of ASDR-suicide and PTD-suicide among adolescents in global high-income, middle-income, and WPR countries from 1990 to 2019. Temporal fluctuation of annual ASDR-suicide (upper side panels: (A1–C1)) and PTD-suicide (lower side panels: (A2–C2)) among adolescent males (blue) and females (red) in high-income (A1,A2), middle-income (B1,B2), and WPR (C1,C2) countries from 1990 to 2019 using joinpoint regression. Ordinates indicate the annual ASDR-suicide (per 100,000 population: (A1–C1)) or PTD-suicide (%: (A2–C2)). Abscissas indicate calendar years. Circles indicate the observed data. Solid and dotted lines indicate the significant and nonsignificant trends of ASDR-suicide and PTD-suicide detected by joinpoint regression, respectively.
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Figure 4. ASDR-suicide and PTD-suicide among adolescent (10–24 years of age) males and females in global high-income, middle-income, and WPR countries from 1990 to 2019. Upper side panels indicate ASDR-suicide of males (A1) and females (A2). Lower side panels indicate PTD-suicide of males (B1) and females (B2). * p < 0.05, ** p < 0.01 relative to high-income countries, # p < 0.05, ## p < 0.01 relative to 1990s by two-way analysis of variance (ANOVA) with Scheffe’s post hoc test. F-values of ASDR-suicide of males and females were [Fregion(2,89) = 4.8 (p < 0.05), Fyear(2,89) = 38.4 (p < 0.01), Fregion*year(4,89) = 31.7 (p < 0.01)] and [Fregion(2,89) = 11.9 (p < 0.01), Fyear(2,89) = 22.4 (p < 0.01), Fregion*year(4,89) = 16.5 (p < 0.01)], respectively. F-values of ASDR-suicide of males and females were [Fregion(2,89) = 81.4 (p < 0.01), Fyear(2,89) = 64.7 (p < 0.01), Fregion*year(4,89) = 60.5 (p < 0.01)] and [Fregion(2,89) = 73.7 (p < 0.01), Fyear(2,89) = 62.6 (p < 0.01), Fregion*year(4,89) = 40.2 (p < 0.01)], respectively.
Figure 4. ASDR-suicide and PTD-suicide among adolescent (10–24 years of age) males and females in global high-income, middle-income, and WPR countries from 1990 to 2019. Upper side panels indicate ASDR-suicide of males (A1) and females (A2). Lower side panels indicate PTD-suicide of males (B1) and females (B2). * p < 0.05, ** p < 0.01 relative to high-income countries, # p < 0.05, ## p < 0.01 relative to 1990s by two-way analysis of variance (ANOVA) with Scheffe’s post hoc test. F-values of ASDR-suicide of males and females were [Fregion(2,89) = 4.8 (p < 0.05), Fyear(2,89) = 38.4 (p < 0.01), Fregion*year(4,89) = 31.7 (p < 0.01)] and [Fregion(2,89) = 11.9 (p < 0.01), Fyear(2,89) = 22.4 (p < 0.01), Fregion*year(4,89) = 16.5 (p < 0.01)], respectively. F-values of ASDR-suicide of males and females were [Fregion(2,89) = 81.4 (p < 0.01), Fyear(2,89) = 64.7 (p < 0.01), Fregion*year(4,89) = 60.5 (p < 0.01)] and [Fregion(2,89) = 73.7 (p < 0.01), Fyear(2,89) = 62.6 (p < 0.01), Fregion*year(4,89) = 40.2 (p < 0.01)], respectively.
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Figure 5. Temporal fluctuations of adolescent ASDR-suicide in the WPR countries from 1990 to 2019. Temporal fluctuation of annual ASDR-suicide among adolescent males (blue) and females (red) in six countries in the WPR, including Japan (A), South Korea (B), Australia (C), New Zealand (D), Hong Kong (E), and Singapore (F), from 1990 to 2019 using joinpoint regression. Ordinates indicate the annual ASDR-suicide (per 100,000 population). Abscissas indicate calendar years. Circles indicate the observed data. Solid and dotted lines indicate the significant and nonsignificant trends of ASDR-suicide detected by joinpoint regression, respectively.
Figure 5. Temporal fluctuations of adolescent ASDR-suicide in the WPR countries from 1990 to 2019. Temporal fluctuation of annual ASDR-suicide among adolescent males (blue) and females (red) in six countries in the WPR, including Japan (A), South Korea (B), Australia (C), New Zealand (D), Hong Kong (E), and Singapore (F), from 1990 to 2019 using joinpoint regression. Ordinates indicate the annual ASDR-suicide (per 100,000 population). Abscissas indicate calendar years. Circles indicate the observed data. Solid and dotted lines indicate the significant and nonsignificant trends of ASDR-suicide detected by joinpoint regression, respectively.
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Figure 6. Temporal fluctuations of adolescent PTD-suicide in the WPR countries from 1990 to 2019. Temporal fluctuation of annual PTD-suicide among adolescent males (blue) and females (red) in six countries in the WPR, including Japan (A), South Korea (B), Australia (C), New Zealand (D), Hong Kong (E) and Singapore (F), from 1990 to 2019 using joinpoint regression. Ordinates indicate the annual PTD-suicide (%). Abscissas indicate calendar years. Circles indicate the observed data. Solid and dotted lines indicate the significant and nonsignificant trends of PTD-suicide detected by joinpoint regression, respectively.
Figure 6. Temporal fluctuations of adolescent PTD-suicide in the WPR countries from 1990 to 2019. Temporal fluctuation of annual PTD-suicide among adolescent males (blue) and females (red) in six countries in the WPR, including Japan (A), South Korea (B), Australia (C), New Zealand (D), Hong Kong (E) and Singapore (F), from 1990 to 2019 using joinpoint regression. Ordinates indicate the annual PTD-suicide (%). Abscissas indicate calendar years. Circles indicate the observed data. Solid and dotted lines indicate the significant and nonsignificant trends of PTD-suicide detected by joinpoint regression, respectively.
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Figure 7. Age-dependent fluctuation of PTD of major causes of death among males in global high-income, middle-income, and WPR countries from 1990 to 2019. Age-dependent fluctuation of PTD of major causes of death, such as suicide (blue), infectious and parasitic diseases (green), respiratory infections (light green), malignant neoplasms (cancer: blown), road traffic accidents (red), and violence (pink) among males in high-income (A1–A3), middle-income (B1–B3), and WPR (C1–C3) countries in the 1990s ((A1,B1,C1): 1990–1999), 2000s ((A2,B2,C2): 2000–2009), and 2010s ((A3,B3,C3): 2010–2019). Ordinates and abscissas indicate PTD (%) and 5 interval ages, respectively.
Figure 7. Age-dependent fluctuation of PTD of major causes of death among males in global high-income, middle-income, and WPR countries from 1990 to 2019. Age-dependent fluctuation of PTD of major causes of death, such as suicide (blue), infectious and parasitic diseases (green), respiratory infections (light green), malignant neoplasms (cancer: blown), road traffic accidents (red), and violence (pink) among males in high-income (A1–A3), middle-income (B1–B3), and WPR (C1–C3) countries in the 1990s ((A1,B1,C1): 1990–1999), 2000s ((A2,B2,C2): 2000–2009), and 2010s ((A3,B3,C3): 2010–2019). Ordinates and abscissas indicate PTD (%) and 5 interval ages, respectively.
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Figure 8. Age-dependent fluctuation of PTD of major causes of death among females in global high-income, middle-income, and WPR countries from 1990 to 2019. Age-dependent fluctuation of PTD of major causes of death, such as suicide (blue), infectious and parasitic diseases (green), respiratory infections (light green), malignant neoplasms (cancer: blown), road traffic accidents (red), and violence (pink) among females in high-income (A1–A3), middle-income (B1–B3), and WPR (C1–C3) countries in the 1990s ((A1,B1,C1): 1990–1999), 2000s ((A2,B2,C2): 2000–2009), and 2010s ((A3,B3,C3): 2010–2019). Ordinates and abscissas indicate PTD (%) and 5 interval ages, respectively.
Figure 8. Age-dependent fluctuation of PTD of major causes of death among females in global high-income, middle-income, and WPR countries from 1990 to 2019. Age-dependent fluctuation of PTD of major causes of death, such as suicide (blue), infectious and parasitic diseases (green), respiratory infections (light green), malignant neoplasms (cancer: blown), road traffic accidents (red), and violence (pink) among females in high-income (A1–A3), middle-income (B1–B3), and WPR (C1–C3) countries in the 1990s ((A1,B1,C1): 1990–1999), 2000s ((A2,B2,C2): 2000–2009), and 2010s ((A3,B3,C3): 2010–2019). Ordinates and abscissas indicate PTD (%) and 5 interval ages, respectively.
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Table 1. Mean ± SD of population, total suicide numbers across overall ages and for the age ranges of 10–14, 15–19, and 20–24 years from 1990 to 2019.
Table 1. Mean ± SD of population, total suicide numbers across overall ages and for the age ranges of 10–14, 15–19, and 20–24 years from 1990 to 2019.
Overall Ages10–14 Years15–19 Years20–24 YearsMissing Data
PopulationSuicidesPopulationSuicidesPopulationSuicidesPopulationSuicides(Year)
(average)(Total)(average)(Total)(average)(Total)(average)(Total)
(million)(thousand)(million)(thousand)(million)(thousand)(million)(thousand)
GlobalSex
High-incomeTotal983.63961.94059.23519.61261.668127.24065.603238.195
Males482.52964.12630.37312.95831.65796.29833.573190.213
Females497.4997.79628.8436.65430.00630.94132.02847.980
Middle-incomeTotal1127.13149.720100.62936.568100.134190.59397.230286.868
Males553.32528.32751.28123.37150.840134.33649.092235.519
Females573.8621.13649.33713.19549.29156.24648.13851.321
Western Pacific Region (WPR)
WPR countriesTotal195.1 1156.746 10.897 3.778 11.847 25.987 12.680 58.786
Males95.6 808.167 5.612 2.235 6.103 17.169 6.502 40.916
Females98.8 348.579 5.284 1.543 5.743 8.818 6.179 17.870
JapanTotal125.1 776.337 6.411 2.050 7.105 13.897 7.609 36.321
Males61.1 542.057 3.285 1.334 3.645 9.303 3.899 25.645
Females64.0 234.280 3.126 0.716 3.460 4.594 3.710 10.676
Republic of KoreaTotal48.1 299.470 3.286 1.373 3.571 8.156 3.801 15.356
(South Korea)Males24.1 205.682 1.716 0.687 1.860 4.862 1.970 9.319
Females24.0 93.788 1.570 0.686 1.711 3.294 1.831 6.037
Hong KongTotal6.7 25.062 0.384 0.144 0.422 0.614 0.460 1.457 2018–2019
Males3.2 15.554 0.198 0.071 0.217 0.374 0.225 0.930
Females3.5 9.508 0.186 0.073 0.205 0.240 0.235 0.527
SingaporeTotal3.5 9.677 0.228 0.080 0.229 0.359 0.237 0.607
Males1.7 6.172 0.117 0.042 0.118 0.211 0.119 0.381
Females1.7 3.505 0.111 0.038 0.112 0.148 0.118 0.226
AustraliaTotal20.7 72.672 1.367 0.351 1.395 3.861 1.498 6.968 2005
Males10.3 56.352 0.701 0.208 0.716 2.889 0.764 5.642
Females10.4 16.320 0.666 0.143 0.680 0.972 0.734 1.326
New ZealandTotal4.0 13.819 0.288 0.149 0.296 1.397 0.293 1.833 2016–2019
Males2.0 10.537 0.148 0.086 0.151 0.992 0.148 1.477
Females2.0 3.282 0.140 0.063 0.145 0.405 0.145 0.356
Table 2. Summary of AAPC values of ASDR-suicide and PTD-suicide of overall age from 1990 to 2019.
Table 2. Summary of AAPC values of ASDR-suicide and PTD-suicide of overall age from 1990 to 2019.
ASDR-Suicide (Overall Age)
AAPC(95%CI)pDifference(95%CI)p
MaleHigh−1.384(−1.884~−0.882)<0.001
Middle−1.567(−2.129~−1.002)<0.0010.183(−0.571~0.937)0.635
WPR0.228(−0.797~1.263)0.664−1.612(−2.757~−0.467)0.006
FemaleHigh−2.234(−2.585~−1.881)<0.001
Middle−2.314(−2.911~−1.714)<0.0010.080(−0.614~0.775)0.820
WPR−0.203(−1.142~0.745)0.674−2.031(−3.038~−1.024)<0.001
PTD-suicide (Overall Age)
AAPC(95%CI)pDifference(95%CI)p
MaleHigh−0.121(−0.297~0.055)0.178
Middle−1.408(−2.496~−0.308)0.0121.287(0.179~2.395)0.023
WPR−0.726(−1.785~−0.344)0.1830.605(−0.474~1.684)0.272
FemaleHigh−0.836(−1.209~−0.462)<0.001
Middle−2.079(−2.95~−1.201)<0.0011.243(0.293~2.194)0.010
WPR−1.429(−2.361~−0.489)0.0030.593(−0.414~1.602)0.248
AAPC: the estimated average annual percent change from 1990 to 2019, ASDR-suicide: age-standardized death rate per 100,000 population, PTD-suicide: percentage of suicides per total deaths (%), 95%CI: 95% confidence interval value.
Table 3. Summary of AAPC values of ASDR-suicide and PTD-suicide among adolescents in the global high-income, middle-income, and WPR countries from 1990 to 2019.
Table 3. Summary of AAPC values of ASDR-suicide and PTD-suicide among adolescents in the global high-income, middle-income, and WPR countries from 1990 to 2019.
ASDR-Suicide (Adolescents)
AAPC(95%CI)pDifference(95%CI)p
MaleHigh−0.199(−0.924~0.532)0.593
Middle−1.242(−2.217~−0.258)0.0131.043(−0.177~2.264)0.094
WPR1.378(0.707~2.053)<0.001−1.577(−2.568~−0.586)0.002
FemaleHigh1.083(0.101~2.075)0.031
Middle−0.091(−1.455~1.292)0.8971.174(−0.517~2.866)0.173
WPR2.506(0.479~4.573)0.015−1.423(−3.695~0.850)0.220
PTD-suicide (Adolescents)
AAPC(95%CI)pDifference(95%CI)p
MaleHigh1.537(0.044~3.053)0.044
Middle0.478(−0.45~1.413)0.3141.059(−0.710~2.829)0.241
WPR3.930(3.022~4.846)<0.001−2.393(−2.757~−0.467)0.008
FemaleHigh2.188(1.943~2.434)<0.001
Middle0.619(−0.252~1.498)0.1641.569(0.517~2.866)0.001
WPR3.837(3.071~4.609)<0.001−1.649(−3.038~−1.024)<0.001
AAPC: the estimated average annual percent change from 1990 to 2019, ASDR-suicide: age-standardized death rate per 100,000 population, PTD-suicide: percentage of suicides per total deaths (%), 95%CI: 95% confidence interval value.
Table 4. Summary of AAPC values of adolescent ASDR-suicide in the WPR countries from 1990 to 2019.
Table 4. Summary of AAPC values of adolescent ASDR-suicide in the WPR countries from 1990 to 2019.
ASDR-Suicide (Males) (Females)
AAPC(95%CI)pAAPC(95%CI)p
Japan2.193(1.417~2.974)<0.0012.164(0.085~4.286)0.041
South Korea1.094(−2.641~4.973)0.571−0.091(−1.455~1.292)0.897
Australia−0.725(−2.779~1.373)0.4951.054(−3.654~5.993)0.667
New Zealand−2.304(−3.697~−0.891)<0.0013.195(−4.141~11.094)0.403
Hong Kong1.919(−0.588~4.49)0.135−0.624(−6.864~6.034)0.850
Singapore−0.068(−2.48~2.404)0.957−0.559(−7.424~6.816)0.878
AAPC: the estimated average annual percent change from 1990 to 2019, ASDR-suicide: age-standardized death rate per 100,000 population, 95%CI: 95% confidence interval value.
Table 5. Summary of AAPC values of PTD-suicide among adolescents in the WPR countries from 1990 to 2019.
Table 5. Summary of AAPC values of PTD-suicide among adolescents in the WPR countries from 1990 to 2019.
PTD-Suicide (Males) (Females)
AAPC(95%CI)pAAPC(95%CI)p
Japan4.715(4.081~5.353)<0.0013.733(3.076~4.394)<0.001
South Korea5.869(4.909~6.838)<0.0017.176(3.558~10.921)<0.001
Australia1.969(1.218~2.726)<0.0013.989(2.686~5.309)<0.001
New Zealand1.193(0.515~1.875)<0.0015.088(2.219~8.038)<0.001
Hong Kong4.670(1.917~7.499)<0.0011.997(0.86~3.146)<0.001
Singapore3.458(1.163~5.806)0.0031.835(0.398~3.292)0.014
AAPC: the estimated average annual percent change from 1990 to 2019, PTD-suicide: percentage of suicides per total deaths (%), 95%CI: 95% confidence interval value.
Table 6. Fixed effects of other causes of death on CMR-suicide and PTD-suicide among adolescent males and females in the WPR from 1990 to 2019.
Table 6. Fixed effects of other causes of death on CMR-suicide and PTD-suicide among adolescent males and females in the WPR from 1990 to 2019.
CMR-Suicide (Males) CMR-Suicide (Females)
AgeF pFactorβSET p AgeF pFactorβSET p
10–14137.85<0.001infection0.4110.2451.6790.154 10–141.510.218infection−0.0290.173−0.1650.870
cancer−0.0030.036−0.0820.938 cancer0.0460.0700.6660.511
respiratory−0.2110.164−1.2880.254 respiratory0.1910.1401.3630.183
traffic−0.0260.026−1.0130.358 traffic−0.0850.098−0.8640.395
violence−0.0230.100−0.2300.828 violence−0.0590.217−0.2730.787
15–191.260.403infection−0.2400.372−0.6440.548 15–192.430.176infection0.0580.3920.1470.889
cancer0.1210.1121.0740.332 cancer−0.3990.191−2.0900.091
respiratory−0.0090.153−0.0570.957 respiratory0.4870.1902.5680.052
traffic0.0350.0640.5480.607 traffic−0.1180.087−1.3610.232
violence0.1160.3420.3390.748 violence0.1780.3820.4650.661
20–249.640.013infection0.8360.8730.9580.382 20–244.890.053infection−0.5950.603−0.9870.369
cancer0.1320.2810.4710.658 cancer−0.1450.195−0.7420.492
respiratory−0.2990.491−0.6090.569 respiratory−0.0310.358−0.0860.935
traffic0.1190.1900.6280.558 traffic−0.1340.075−1.7910.133
violence0.2830.8880.3190.763 violence0.3990.3071.3010.250
PTD-suicide (Males) PTD-suicide (Females)
AgeF pfactorβSET p AgeF pfactorβSET p
10–148.280.018infection−0.4920.281−1.7490.141 10–1422.710.002infection0.0070.1220.0560.958
cancer−0.3500.106−3.2930.022* cancer−0.1560.029−5.4550.003**
respiratory−0.1840.190−0.9680.377 respiratory−0.1390.127−1.0880.326
traffic−0.6080.102−5.9630.002** traffic−0.5240.150−3.4870.018*
violence−0.5090.272−1.8700.120 violence−0.0690.239−0.2910.783
15–19275.38<0.001infection−1.0660.939−1.1350.308 15–19237.68<0.001infection−0.6750.580−1.1640.297
cancer−0.4150.415−1.0000.363 cancer−0.5520.144−3.8400.012*
respiratory−0.3390.245−1.3820.226 respiratory−0.4710.204−2.3080.069
traffic−0.7150.079−8.999<0.001** traffic−0.9780.121−8.067<0.001**
violence−1.1250.462−2.4350.059 violence−0.7950.402−1.9790.105
20–2418,085.80<0.001infection−0.8850.334−2.6480.046*20–24250.66<0.001infection−1.5930.737−2.1630.083
cancer−0.5440.324−1.6780.154 cancer−0.6350.174−3.6540.015*
respiratory−0.5960.132−4.5070.006** respiratory−0.5350.167−3.1940.024*
traffic−0.9260.158−5.8460.002** traffic−1.0580.175−6.0460.002**
violence−1.4900.411−3.6270.015* violence−0.9580.324−2.9590.032*
CMR-suicide: crude mortality rate per 100,000 population, PTD-suicide: percentage of suicides per total deaths (%), β: coefficient, SE: standard error; infection (A00-B99, G00-G04, G14, N70-N73, P37.3, P37.4 in ICD-10), respiratory (H65-H66, J00-J22, P23, U04, U07.1, U07.2, U09.9, U10.9 in ICD-10), cancer (C00-C97 in ICD-10), traffic (V01–04, V06, V09, V10–79, V80–89, V99, Y85.0 in ICD-10), violence (X85-Y09, Y871 in ICD-10), * p < 0.05, ** p < 0.01.
Table 7. Fixed effects of communication factors on ASDR-suicide, CMR-suicide, and PTD-suicide among adolescent males and females in the WPR from 1990 to 2019.
Table 7. Fixed effects of communication factors on ASDR-suicide, CMR-suicide, and PTD-suicide among adolescent males and females in the WPR from 1990 to 2019.
ASDR-Suicide/CMR-Suicide (Males) ASDR-Suicide/CMR-Suicide (Females)
AgeF pFactorβSETp AgeF pFactorβSET p
10–142.280.194Internet-user−0.0060.007−0.8530.433 10–1411.71 0.009Internet-user−0.0040.010−0.3630.732
(CMR) mobile-sub0.0020.0050.4850.648 (CMR) mobile-sub0.0060.0051.1880.288
15–194.120.008Internet-user−0.0380.025−1.5510.134 15–191.49 0.231Internet-user0.0070.0100.7510.460
(CMR) mobile-sub−0.0370.014−2.6580.014*(CMR) mobile-sub−0.0180.012−1.4970.147
20–2421.49<0.001Internet-user−0.0750.050−1.5010.147 20–244.69 0.004Internet-user0.0830.0283.0040.006**
(CMR) mobile-sub−0.0870.033−2.6620.014*(CMR) mobile-sub−0.0440.016−2.7430.011*
Adolescents4.440.005Internet-user−0.0160.019−0.8160.422 Adolescents2.49 0.059Internet-user0.0280.0112.5220.019*
(ASDR) mobile-sub−0.0320.009−3.4580.002**(ASDR) mobile-sub−0.0180.007−2.5390.018*
PTD-suicide (Males) PTD-suicide (Females)
AgeFpfactorβSET p AgeF valuepfactorβSETp
10–14400.26<0.001Internet-user0.0190.0630.3030.774 10–143.590.011Internet-user0.0910.0432.0900.047*
mobile-sub−0.0210.055−0.3770.722 mobile-sub−0.0590.0272.1780.039*
15–1915.81<0.001Internet-user0.2240.0534.222<0.001**15–1914.51<0.001Internet-user0.2500.0733.4100.001**
mobile-sub−0.1250.036−3.4470.002** mobile-sub−0.1150.054−2.1110.037*
20–2414.02<0.001Internet-user0.1780.0523.4420.002**20–246.060.035Internet-user0.3250.0973.3450.020*
mobile-sub−0.1070.032−3.3430.003** mobile-sub−0.1170.028−4.0960.009**
Adolescents18.13<0.001Internet-user0.1640.0483.4500.002**Adolescents18.46<0.001Internet-user0.2790.0555.036<0.001**
mobile-sub−0.0800.029−2.8110.010* mobile-sub−0.0980.041−2.4030.018*
ASDR-suicide: age-standardized death rate per 100,000 population, CMR-suicide: crude mortality rate per 100,000 population, PTD-suicide: percentage of suicides per total deaths (%), β: coefficient, SE: standard error, Internet-user: penetration of Internet (number of Internet users per 100 people), mobile-sub: penetration of cellular telephones (number of subscriptions per 100 people), * p < 0.05, ** p < 0.01.
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MDPI and ACS Style

Okubo, R.; Matsumoto, R.; Motomura, E.; Okada, M. Adolescent Suicides in the Western Pacific Region Have Become a More Serious Public Health Problem than in Other Regions. Psychiatry Int. 2024, 5, 564-584. https://doi.org/10.3390/psychiatryint5040041

AMA Style

Okubo R, Matsumoto R, Motomura E, Okada M. Adolescent Suicides in the Western Pacific Region Have Become a More Serious Public Health Problem than in Other Regions. Psychiatry International. 2024; 5(4):564-584. https://doi.org/10.3390/psychiatryint5040041

Chicago/Turabian Style

Okubo, Ruri, Ryusuke Matsumoto, Eishi Motomura, and Motohiro Okada. 2024. "Adolescent Suicides in the Western Pacific Region Have Become a More Serious Public Health Problem than in Other Regions" Psychiatry International 5, no. 4: 564-584. https://doi.org/10.3390/psychiatryint5040041

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