Prevalence of suicidal behavior in Nigeria: A systematic review and meta-analysis

Prevalence of suicidal behavior in Nigeria: A systematic review and meta-analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Prevalence of suicidal behavior in Nigeria: A systematic review and meta-analysis Aminu Kende Abubakar, Ajibola Ibraheem Abioye, Mohammed Nakodi Yisa, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7990610/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Jan, 2026 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Suicidal behaviors are a growing global concern, particularly among young people, yet their burden remains poorly defined in Nigeria, a country with a predominantly young population. This systematic review and meta-analysis synthesized data from 30 studies involving 45,190 participants published up to August 2024 to estimate the prevalence and correlates of suicidal ideation, planning, and attempts in Nigeria. Studies reporting the prevalence of suicidal behaviors in the Nigerian general population or specific subgroups, using healthcare diagnosis or validated screening tools, were included. The pooled prevalence of suicidal ideation in the general population was 9.7%, while suicidal planning and attempts were estimated at 1.8% and 1.1%, respectively. Suicidal behaviors were more prevalent among adolescents, refugees, out-of-school youth, sexual minorities, and in northern regions. Prevalence estimates increased over time. These findings confirm that suicidal behaviors are common in Nigeria and underscore the need for targeted intervention strategies tailored to high-risk populations. Health sciences/Diseases Health sciences/Health care Health sciences/Medical research Biological sciences/Psychology Social science/Psychology Health sciences/Risk factors Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Mental health disorders represent a significant public health challenge globally. One in every eight individuals lives with some form of mental disorder 1 . Suicide and suicidal behavior are well-known to be strongly related to a history of mental illness 2,3 . Suicide accounts for over 700,000 annual deaths worldwide 4 . The global age-standardized suicide rate was 9.0 per 100,000 people, these rates varied significantly by age and gender, with higher rates in males and younger people 5 . More than half of all suicides in the world (58%) occur in individuals under the age of 50, with a significant majority (88%) of these incidents occurring in low- and middle-income countries (LMICs)(5.). Suicide is the fourth leading cause of death among young people aged 15–29 years 5 . Nigeria, one of the youngest nations in the world with a median age of about 18 years, had an age-standardized suicide rate of 6.9 per 100,000 population in 2019, based on World Health Organization (WHO) estimates 5 . For every suicide, there are usually multiple preceding suicide attempts 4 , highlighting the broader spectrum of suicidal behaviors, which are important risk factors for eventual suicide. Suicidal behaviors are broadly classified into suicidal ideation, suicidal planning, and suicidal attempts 6 , each representing different stages in the progression toward suicide. Understanding these behaviors is crucial for early intervention and prevention. Since the World Health Organization launched the Mental Health Gap Action Program (mhGAP) in 2008 7 , there has been a growing focus on suicide research. The WHO’s first report on suicide prevention in 2014 8 , advocating for global suicide prevention and comprehensive strategies, coincided with the inclusion of the suicide mortality rate (SDG3.4.2) as a key indicator for the Sustainable Development Goals. In Nigeria, significant strides have been made in mental health policy recently. The National Mental Health Act 2021, enacted in January 2023, represents a critical advancement in the country's commitment to mental health which was followed by the launch of the National Mental Health Policy and the National Suicide Prevention Strategic Framework in November 2023 by the Federal Ministry of Health 9–11 . Despite these developments, research on suicide behaviors in Nigeria remains limited and fragmented like in other developing regions, mainly due to a lack of effective and reliable vital records on suicide. Existing literature, mainly cross-sectional studies, has focused on specific groups such as HIV patients, adolescents, the elderly, individuals with mental illness and other sub-population groups 12–15 . Moreover, findings from general population studies in Nigeria have been inconsistent. An older national study from 2003, which informed most estimates and policies, reported a 3.2% prevalence of suicidal ideation 16 . However, a more recent 2015 study from a populous and diverse state found a higher rate of 7.2% 17 . These differences could be due to changes over time, variations in study design, or differences in diagnostic tools used. Therefore, a comprehensive and updated re-evaluation is necessary to integrate the findings from available studies. This study aimed to systematically review the existing literature and quantitatively synthesize the prevalence of suicidal behavior (ideation, plan, and attempt) in Nigeria, focusing on both the general population and specific subgroups. To our knowledge, the only other review on this subject offered qualitative analysis into suicidal behavior in the general population but did not include a meta-analysis 18 . Results Study selection The study selection process is shown in Fig. 1 using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA chart) 19 . A total of 30 cross-sectional studies met the inclusion criteria 12–14,16,17,20–44 : Thirty reported on suicide ideation, seven on suicide planning, and 14 on suicide attempts. Table 1 summarizes the characteristics of the studies included. Suicide Ideation A total of 30 studies with 45,190 participants, were analyzed to estimate the prevalence of suicidal ideation. The studies included various populations: seven studies focused on people living with HIV (PLHIV) 12,26,31,39,41,42,45 , six on secondary school students 22,28–30,34,46 , six on the general community 14,16,17,24,35,43 , five on tertiary institution students 20,25,32,33,44 , and one study each on female sex workers (FSW) 37 , stroke survivors 15 , healthcare workers (HCW) 38 , male juvenile institution residents 23 , men who have sex with men (MSM) 36 , out-of-school youth 27 , and a refugee population 24 . The pooled prevalence of suicidal ideation among the general population 14,16,17,24,35,43 was estimated at 9.7% (95% CI: 5.2–17.3; I 2 = 99%) (Fig. 2), based on six studies with 21,804 participants conducted between 2007 and 2015. These studies covered a wide range of regions and populations within the country, with participants ranging from small, local samples to large, multi-state surveys. All the studies used validated diagnostic tools, but they varied, with CIDI used in two studies, and PHQ-9, MINI, KADS, and Prime-MD each used in one study. The certainty of the evidence was very low – downgraded for imprecision, inconsistency and risk of bias – the sampling strategy was unclear for two studies 35,43 . Figure 3A presents a nomogram showing the yearly trends in the prevalence of suicidal behavior from community studies. The regression line indicates a meaningful increase in the proportion of individuals reporting suicidal behaviors over time ( p- heterogeneity = 0.0007). The Baujat plot ( Supplementary Fig. 1 ) shows the contribution of individual studies to the overall heterogeneity and their influence on the summary proportion. The study by Sweetland (2019) contributed the most to heterogeneity, with a high influence on the summary proportion, followed by Gureje (2007) – though the pooled prevalence did not change by > 20% on excluding any studies. The I 2 did not also change meaningfully. The studies assessed suicidal ideation using the Composite International Diagnostic Interview (CIDI) 3.0 14,16 , Mini International Neuropsychiatric Interview (MINI) 24 , Kutcher Adolescent Depression Scale (KADS-6) 35 , the PRIME-MD Patient Health Questionnaire 43 and the 9-item Patient Health Questionnaire (PHQ-9) 17 . The pooled prevalence of suicidal ideation based on studies that used the CIDI 3.0 among community-dwelling individuals was only 3.9% (95% CI: 3.2, 4.7) 14,16 . Table 2 presents the prevalence of suicidal ideation across various subgroups. The highest prevalence estimates (≥ 20%) were observed among refugees (27.2%; 95% CI: 7.4, 63.5), FSW (21.3%; 95% CI: 5.4, 56.2), MSM (21.3%; 95% CI: 5.5, 55.8), and out-of-school youth (19.9%; 95% CI: 5.1, 53.9). Table 1. Characteristics of Studies Included Author (Year) State Setting/Population Sample size Mean Age, y Female ,% Diagnostic Tool Risk of bias Adebowale, 2023 20 Osun Tertiary Schools Students 691 Suicidal Ideation Scale (adapted from Reynolds (1987)) Fair Adewuya, 2016 17 Lagos Community 11246 36.8 58 PHQ-9 Good Adewuya, 2020 22 Lagos Secondary School Students 9441 15.61 50.4 MINI-Kid Fair Adeyemo, 2020 45 Lagos PLHIV 201 13.88 38.3 MINI-Kid Good Ajiboye, 2009 23 Kwara Juvenile Institution 53 17.3 0 MINI-Kid Fair Akinyemi, 2015 24 Ogun Community 527 34.7 40.8 MINI Fair Refugee Community 444 34.7 40.8 MINI Fair Aroyewun, 2022 25 Southwest Tertiary Schools Students 2702 21.24 53.1 Adult Suicidal Ideation Questionnaire (ASIQ) Poor Bamidele, 2023 12 Ogun PLHIV 412 47.4 68.4 Custom Tool Based on SDVCS and SEM Framework Good Bankole, 2017 26 Cross River PLHIV 150 10.77 58.7 MINI-Kid Fair Cheng, 2014 27 Oyo Out-of-School Youth 449 16.65 51 Single-Item Question Adapted from the YRBSS Fair Chinawa, 2014 28 Enugu & Ebonyi Secondary School Students 764 15.87 35.7 Health Kids Colorado Questionnaire Fair Chinawa, 2023 29 Enugu Secondary School Students 450 16.2 65.6 Columbia Suicide Severity Rating Scale (C-SSRS) Good Dade-Matthews, 2024 30 Ogun Secondary School Students 225 15.3 51.2 MINI-Kid Good Egbe, 2017 31 35 States PLHIV 1187 39.3 66.5 WHO-CIDI 3.0 Good Gureje, 2007 16 21 States Community 6752 36.7 51 WHO-CIDI 3.0 Good Iweama, 2024 32 Adamawa Tertiary Schools Students 616 21.41 33.3 Suicidal Behaviors Questionnaire-Revised (SBQ-R) Good Ladi-Akinyemi, 2023 33 Lagos Tertiary Schools Students 750 21.5 54 PHQ-9 Good Mapayi, 2016 34 Osun Secondary School Students 500 13.96 50.4 DISC-DPS Fair Nyundo, 2020 35 Oyo Community 750 15.2 54.8 Kutcher Adolescent Depression Scale (KADS-6) Poor Ogunbajo, 2020 36 4 states MSM 389 29.2 0 CES-D Fair Ojagbemi, 2013 14 Yoruba Speaking Community 2149 75.06 53.8 WHO-CIDI 3.0 Good Okonkwo, 2022 37 Lagos FSW 224 26.3 100 MINI Good Olibamoyo, 2020 38 Lagos HCW 226 35.8 66.8 Attitudes Toward Suicide Scale (ATTS) Fair Omigbodun, 2008 13 Oyo Secondary School Students 1429 14.4 49.1 DISC-DPS Good Onyebueke, 2015 39 Enugu PLHIV 360 33.52 38.6 MINI Good Opakunle, 2018 40 Osun Secondary School Students 1015 14.84 50.9 Suicidal Behaviors Questionnaire-Revised (SBQ-R) Fair Oyedun, 2023 41 Gombe PLHIV 328 41.89 67.1 MINI Fair Seb-Akahomen, 2019 42 Edo PLHIV 410 40.41 75.9 MINI Good Sweetland, 2019 43 Kaduna Community 380 35.05 38.2 Self-report PRIME-MD Poor Uteh, 2022 44 Ondo Tertiary Schools Students 121 21.78 47.1 Beck's Scale for Suicide Ideation Good Table 2: Subgroups Estimated Prevalence of Suicidal Behaviors Prevalence (95% CI) Sample Size (No. of Studies) Suicide Ideation Community 9.7% (5.2, 17.3) 21,804 (6) Secondary Schools 10.5% (6.2, 17.4) 13,824 (7) Tertiary Institutions 13.4% (6.6, 25.2) 4,759 (4) PLHIV 9.7% (5.6, 16.3) 4,235 (8) FSW 21.3% (5.4, 56.2) 224 (1) MSM 21.3% (5.5, 55.8) 389 (1) Out-of-school Youth 20.0% (5.1, 53.9) 449 (1) Refugees 27.2% (7.4, 63.5) 444 (1) Stroke survivors 1.7% (0.3, 8.0) 150 (2) Suicide Plan Community 1.8% (0.7, 4.5) 9651 (3) Secondary Schools 4.4% (1.5, 12.2) 9441 (1) Out-of-school Youth 15.1% (5.4, 35.6) 444 (1) PLHIV 4.4% (1.9, 9.7) 822 (1) Suicide Attempt Community 1.1% (0.2, 4.8) 9,651 (3) Secondary Schools 5.3% (2.6, 10.3) 12,385 (1) Out-of-school Youth 14.2% (3.7, 41.2) 449 (1) HCW 7.4% (1.7, 26.4) 226 (1) MSM 10.2% (2.6, 32.8) 389 (1) PLHIV 2.5% (1.3, 4.9 2,159 (4) The minor differences in community prevalence estimates from the forest plots are due to rounding. Table 3: Risk factors of Suicidal Behavior Characteristic Categories Suicide Ideation Suicide Plan Suicide Attempt Value (95% CI) p- heterogeneity Value (95% CI) p- heterogeneity Value (95% CI) p- heterogeneity Age, % Adolescents, <20y 9.4% (6.8, 12.9) 0.20 7.3% (3.7, 13.7) 0.0078 5.3% (3.0,9.3) 0.0029 20 - 35y 17.2% (7.6, 34.6) NA 10.2% (2.4,34.4) 35 - 49y 15.3% (8.7, 25.8) 2.6% (1.3, 5.3) 2.6% (1.3,5.2) 50 – 65 y NA NA NA 65+ y 4.6% (1.9, 10.8) 0.9% (0.3, 3.2) 0.3% (0.1,1.4) Sex, OR Female 0.99 (0.97, 1.02) 0.69 0.99 (0.96, 1.01) 0.28 0.99 (0.96, 1.01) 0.21 Marital status, OR Married 1.00 (0.98, 1.01) 0.24 0.99 (0.97, 1.02) 0.66 0.99 (0.96, 1.03) 0.70 Education, OR None 0.84 (0.69, 1.03) 0.22 NA NA Primary or secondary Ref Tertiary 1.01 (0.95, 1.08) Employment, OR Employed 0.98 (0.97, 1.00) 0.091 NA Region, % North-Central 6.8% (2.7, 16.0) 0.0041 NA 0.66 2.27% (0.36, 13.2) 0.30 North-East 25.9% (11.8, 47.6) NA NA North-West 29.7% (15.4, 49.6) NA NA South-East 6.3% (2.9, 13.0) NA NA South-South 9.8% (3.9, 22.6) 3.2% (0.6, 15.8) 1.5% (0.3, 6.7) South-West 13.2% (10.0, 17.2) 4.8% (2.3, 9.7) 4.8% (2.6, 8.7) Table 3 presents the prevalence of suicidal ideation across levels of sociodemographic risk characteristics reported in all suicidal ideation studies. Meta-regression indicated that the prevalence of suicidal ideation was significantly related to the study location ( p- heterogeneity = 0.041) and employment status ( p- heterogeneity = 0.091). The predicted prevalence of suicidal ideation was greatest in the North-East (25.9%; 95% CI: 11.8, 47.6) and North-West (29.7%; 95% CI: 15.4, 49.6) regions. For every one percentage point higher proportion of individuals who were employed, the odds of suicidal ideation were lower by 0.98 (95% CI: 0.97, 1.00). The other demographic factors examined were not related to the prevalence of suicidal ideation: age ( p- heterogeneity = 0.20), sex ( p- heterogeneity = 0.66), marital status ( p- heterogeneity = 0.24) and educational attainment ( p- heterogeneity = 0.22). The prevalence of suicidal ideation was greatest among adolescents and young adults, but the confidence intervals were too wide and overlapped. Suicide Planning Seven studies involving 20,363 participants were included in the analysis of suicide planning. The studies were distributed across three different subgroups, three community-based studies 14,16,35 , two studies on PLHIV 12,42 , one study among secondary school students 22 , and one study among out-of-school youth 27 . The pooled prevalence of suicidal planning in the general community was 1.8% (95% CI: 0.7–4.5%; I 2 = 96%; Fig. 4A), based on three studies among 9,651 participants. One study used the KADS tool and focused on a single state, Oyo. The other two studies, using the CIDI tool, were conducted across multiple states with Oyo included in both. The certainty of the evidence was low – downgraded for imprecision and risk of bias – the sampling strategy was unclear for one study 35 . Baujat plots (Supplementary Fig. 1B) indicate that the study by Nyundo (2020) had a significant influence on the summary proportion, contributing considerably to the overall heterogeneity 35 . This study was conducted in a Nigerian city, as part of an international multi-country study. On excluding this study, the prevalence of suicide planning was 1.0% (95% CI: 0.8, 1.2), which is lower by > 20%. The I 2 also became 0.0%. The other two were multi-center studies that assessed suicide planning using the CIDI 3.0 14,16 . Of the subgroups assessed (Table 2), the prevalence of suicide planning was greatest in out-of-school youths (15.1%; 95% CI: 5.4, 35.6). The prevalence of suicide planning was 4.4% (95% CI: 1.5, 12.2) based on a single study among secondary school students and 4.4% (95% CI: 1.9, 9.7) based on a single study among PLHIV. Meta-regression indicated that the prevalence of suicide planning was significantly related to the age ( p- heterogeneity = 0.0078). The prevalence was 7.3% (95% CI: 3.7, 13.7) among adolescents but only 2.6% (95% CI: 1.3, 5.3) among adults 35–49 y, and 0.9% (95% CI: 0.3, 3.2) among adults ≥ 65 years. The other demographic factors examined were not related to the prevalence of suicide planning: sex ( p- heterogeneity = 0.28), marital status ( p- heterogeneity = 0.66) and study location ( p- heterogeneity = 0.66). Suicide Attempt Fourteen studies involving 25,259 participants were included in the analysis of suicidal attempts. The studies were distributed across six different subgroups: three community-based studies 14,16,35 , four studies involving PLHIV 12,26,31,42 , four studies among secondary school students 13,22,34,46 , and one study each among out-of-school youth 27 , MSM 36 , and HCWs 38 . The pooled prevalence of suicidal attempts among community-dwelling individuals was estimated at 1.1% (95% CI: 0.23–4.8; I 2 = 98%; Fig. 4B), based on three studies among 9,651 participants. The certainty of the evidence was low – downgraded for imprecision and risk of bias – the sampling strategy was unclear for one study 35 . Baujat plots (Supplementary Fig. 1B) indicate that the study by Nyundo (2020) had a significant influence on the summary proportion, contributing considerably to the overall heterogeneity 35 . On excluding this study, the prevalence of suicide planning was 0.5% (95% CI: 0.3, 0.9), which is lower by > 20%. The I 2 also became 76%. Of the subgroups assessed (Table 2), out-of-school youth were the most likely to have had a previous suicide attempt (14.2%; 95% CI: 3.7, 41.2). Meta-regression indicated that the prevalence of suicidal attempts was significantly related to the age ( p- heterogeneity = 0.0029). The prevalence was the greatest among adolescents (5.3%; 95% CI: 3.0, 9.3) and young adults (10.2%; 95% CI: 2.4, 34.4). Discussion We reviewed 30 studies conducted between 2007 and 2024 to provide pooled prevalence estimates of suicidal behaviors in Nigeria for the general population and key subgroups. Among the general population, the prevalence of suicidal ideation was 9.7%, with employment status and study location significantly associated with prevalence rates. The prevalence of suicide planning and suicide attempts among the general population were 1.8% and 1.1%, respectively, both strongly linked to age, with adolescents showing the highest rates. Over time, the proportion of individuals reporting suicidal behaviors has increased, and notable variations were observed across different subgroups. Our estimates for suicidal ideation, planning, and attempts among the general population are similar to a meta-analysis from Ethiopia 47 , the World Health Mental Health survey from 17 countries including Nigeria published in 2008 48 , and a national study from German population 49 , but much higher than reports from Europe 50 , China 51 and some LMICs 52 . Our results are lower than the prevalence from community studies in India and South Africa 52 . These differences may reflect variations in the availability of mental health services, diagnostic practices, and exposure to risk factors of suicidal behaviors. Our findings revealed significant subgroup variations in the prevalence of suicidal behaviors. The estimated prevalence of suicidal ideation for MSM (21.3%), refugees (27.2%), FSW (21.3%), and out-of-school youth (20%) were markedly higher than those for the general population. This pattern was similar for suicide planning and attempts. Our findings are consistent with published studies, which consistently show elevated suicide risk among these groups (56–60). This is likely driven by the compounded effects of socio-economic factors, stigma, discrimination, and disease burden. Importantly, these groups also experience higher rates of mental health disorders, which are well-established risk factors for suicidal behavior 2,3 . These findings underscore the role of social inequities in shaping mental health outcomes, highlighting the need for nuanced population-specific interventions tailored to these vulnerable populations. Our analysis also showed significant age-related variations in suicidal behaviors. Suicidal ideation was most common among young adults (17.2%) and middle-aged adults, 35–49 years (15.3%), with adolescents reporting relatively lower but still concerning rates (9.4%), while older adults showed the lowest prevalence (4.6%). The prevalence of suicidal planning followed a similar pattern, with adolescents showing the highest rates (7.3%) and older adults reporting the lowest (2.6%). Suicidal attempts were also more frequent among younger populations, especially young adults (10.2%) and adolescents (5.3%). We also found higher rates of suicidal behaviors among secondary (Ideation 10.5%, Plan 4.4%, Attempt, 5.3%) and tertiary (Ideation 13.4%) school students This pattern is consistent with global trends, where younger populations are showing higher burden of mental health issues and suicidal behavior 5,58–60 , a critical issue highlighted by the Lancet Psychiatry Commission on youth mental health 61 . The Commission emphasized that the mental health of emerging adults has steadily worsened over the past two decades, with the COVID-19 pandemic and its aftermath further intensifying this crisis 61 . Factors such as developmental challenges, socio-economic pressures, identity formation stress, and increased exposure to social media and digital environments have all been linked to this growing public health issue 59,62–64 . In contrast, older adults may benefit from greater emotional resilience 65 , companionship, and established social networks 66,67 , which could contribute to their lower prevalence of suicidal behaviors. Study location and employment status are other key factors associated with suicidal ideation in our results. The highest prevalence was observed in the northern regions, particularly the North-East and North-West. These regions suffer from high poverty rates and have been severely impacted by conflict, terrorism, and displacement; this could partly explain our result. These findings should however be interpreted with caution as the studies from the North-East and North-West were not from the general population. They were conducted among young people attending university 32 and PLHIV 41 , though the national prevalence of suicidal behavior was not exceedingly high among university students and PLHIV. Unemployment was also linked to higher suicidal ideation in our findings. Employment appears to offer protection against suicide and suicidal behaviors 68 . No significant associations were found with sex, marital status, or education level —factors often linked to suicide risk. This may be due to the limitations of pooled studies. The findings of this study have important implications for public health policy in Nigeria and will support the implementation of the National Suicide Prevention Strategic Framework (NSPSF) 2023–2030 9–11 . Suicide prevention efforts should prioritize improving access to mental health services for higher-risk groups. Given the association between economic instability and suicidal behaviors, policies aimed at reducing unemployment and improving economic conditions will be critical. Expanding mental health services in primary care, increasing the community health workforce, enhancing community-based initiatives, and improving health insurance are key to addressing the growing burden of suicide in Nigeria. More than half of the country are under 18 years old. Specific interventions targeted at this demographic are required to provide crucial help to them. This analysis offers several strengths, including the separate pooling of data for the general population and subgroups, which provided a more nuanced understanding of suicidal behaviors across diverse populations. By grouping studies based on behavior, subgroup, and setting, we ensured more accurate inferences. Additionally, the use of GRADE principles to assess the strength of evidence increased the transparency and reliability of our findings. However, there are limitations to consider when interpreting our findings. The availability and quality of studies were limited, with many subgroups represented by only a few or single studies, highlighting significant gaps for future research. Most of the studies were conducted in urban areas, limiting the representation of the data, and the absence of older studies restricted the analysis of long-term trends. Furthermore, although the studies included used validated diagnostic tools, their variation across studies may have introduced inconsistencies. Finally, methodological constraints prevented us from assessing publication bias, which could have affected the pooled estimates. We systematically reviewed the published studies of the prevalence of suicidal behaviors in Nigeria, and found that suicidal behaviors are common, with the greatest burden among certain demographic subgroups – adolescents, refugees, female sex workers, men who have sex with men, and out-of-school youth. National and subnational mental health policies and interventions should account for this variation and target the groups with the highest burden. Methods Reporting This review was developed according to the PRISMA guidelines 19 and the Joanna Briggs Institute (JBI) methodology for systematic reviews on prevalence 69 . The protocol is registered with the International Prospective Register of Systematic Reviews (PROSPERO; CRD42024559090) and has been published elsewhere. 70 Eligibility criteria Studies were included if they focused on suicidal behavior (ideation, planning, and attempt) diagnosed by healthcare professionals or identified through validated tools, and provided prevalence estimates among individuals in Nigeria, representing the general population or specific subgroups. There were no restrictions on age, sex, or subgroup, but studies from psychiatric patients were excluded. Eligible studies were cross-sectional surveys or baseline data from cohort studies conducted in Nigeria. We also excluded studies that did not focus on prevalence, were case-control studies, reviews, case reports, duplicates, or involved non-human research. Information sources and Search strategy We searched medical literature databases including PUBMED/Medline (U.S. National Library of Medicine), EMBASE (Elsevier) and African Journals Online (AJOL) for studies of mental disorders in Nigeria as part of a larger project. This paper reports on suicidal behaviors. Studies from the inception of the databases until July 2024 were included. Hand-searching was also done by examining the reference list of included papers and Google Scholar for additional papers. The search strings included a combination of MeSH terms (Medical Subject Headings), Emtree terms, and topics by which articles are indexed for the PubMed/Medline and Embase databases, respectively, as well as relevant text and keywords (Supplementary Table 1). The search strings were focused on the following concepts: Nigeria, mental disorder, and prevalence. Database records were exported to a Zotero library for managing search results and removing duplicates. Study Selection and Data Extraction The study selection involved three rounds: an initial title/abstract review to exclude non-qualifying studies, a full-text review to determine eligibility, and data extraction from the eligible studies. Two independent investigators performed the first two rounds in duplicate, with disagreements resolved by a third reviewer. Rayyan Software was used for study screening and data extraction was carried out independently using a custom cloud-based spreadsheet, which also included risk of bias assessments for collaborative record-keeping. The extracted data were organized into five sections: study identification, participant demographics, study characteristics, outcome measures, and risk of bias assessment. Risk of bias assessment The risk of bias was assessed using the National Institute of Health Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies 71 . The tool assesses population clarity, minimal non-response, consistent sampling, representativeness, sample size rigor, and clear definition of the health condition. Effect Measure and Data Synthesis The effect measure is the prevalence or proportion of participants with the outcome. Random-effects meta-analyses models were used to synthesize data from studies reporting on the prevalence of the three types of suicidal behavior, accounting for study variability. The main summary measure was the pooled prevalence rate. Meta-analysis was performed in R version 4.5.1 using the metafor package version 4.8-0. Heterogeneity was assessed using the I² statistic, categorized as minimal (0–40%), moderate (> 40–60%), substantial (60–80%), or considerable (> 80%) 72 . To evaluate the influence of each study on the pooled estimate and its contribution to heterogeneity for meta-analyses with more than three studies, Baujat plots were generated to depict the relationship of each study’s influence on the pooled estimate to its contribution to the overall heterogeneity - represented by the Cochran Q-statistic 73 . Influence analysis involved sequentially omitting studies to compare the pooled estimate and I² statistic. Meta-regression was conducted to examine variations by age group, subgroup, and study period, with trends presented using a nomogram. Publication bias was not assessed, as traditional methods like funnel plots and Egger’s tests do not apply to meta-analyses of proportions. 73 Certainty Assessment For each prevalence measure, we systematically assessed the certainty of the evidence using a modification of the GRADE approach 74,75 . The certainty of evidence was rated down if included studies were not likely representative based on participant selection strategy (risk of bias), if the pooled estimate was imprecise (imprecision), if the point estimates and confidence intervals from each study substantially varied (inconsistency), or if the assessed population or outcome assessment differs from the population or outcome assessment of interest (indirectness). For imprecision, the following evidence thresholds based on a rule of thumb were used: 50%, 30%, 10%, 5%, 1%, 0.10 and 0%, as they change clinical and public health perceptions of how prevalent or rare the condition is. While a summary grade of moderate or high certainty evidence indicates we believe the true prevalence is correctly estimated or close to the estimated prevalence, a low or very low certainty evidence indicates we believe the true prevalence is probably meaningfully different from the estimated prevalence 76 . Declarations Data and Code Availability The authors compiled the data used in this analysis from studies identified through a systematic review of PubMed (https://pubmed.ncbi.nlm.nih.gov), Embase (https://www.embase.com), African Journals Online (https://www.ajol.info/index.php/ajol), and manual searches of reference lists of included articles. The data and analysis code are available from the corresponding author upon reasonable request. Author contributions I.A. conceived and designed the study and performed the systematic search. I.A. and M.Y. developed the preliminary protocol and assembled the study team. A.K.A., I.A., D.O., T.O., S.O.O., J.M., M.A.K., M.Y., O.T., S.O., M.O.O., and E.I. performed study screening, data extraction, and quality appraisal. A.K.A. and I.A. conducted the statistical analysis. M.A.K. and A.A. provided clinical expertise. A.K.A., I.A., and M.Y. drafted the manuscript. A.K.A., I.A., D.O., T.O., S.O.O., J.M., M.A.K., M.Y., O.T., S.O., M.O.O., E.I., and A.A. contributed to the study design, drafting, and critical revision of the manuscript. I.A. and A.A. provided supervision. All authors had full access to the data, are responsible for the integrity of the study, and approved the final version of the manuscript for publication. Competing interests None Funding The authors did not receive any funding for this work. 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Supplementary Files 251030SuicidalBehaviourNigeriaPRISMA2020checklist.docx S.Fig1.docx AppendixTables.docx Cite Share Download PDF Status: Published Journal Publication published 20 Jan, 2026 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 17 Nov, 2025 Reviews received at journal 15 Nov, 2025 Reviews received at journal 14 Nov, 2025 Reviewers agreed at journal 09 Nov, 2025 Reviewers agreed at journal 05 Nov, 2025 Reviewers invited by journal 05 Nov, 2025 Editor invited by journal 04 Nov, 2025 Editor assigned by journal 01 Nov, 2025 Submission checks completed at journal 01 Nov, 2025 First submitted to journal 30 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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1","display":"","copyAsset":false,"role":"figure","size":304987,"visible":true,"origin":"","legend":"\u003cp\u003ePRISMA Flow Diagram of Study Selection\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7990610/v1/793e159e696bdf1c778905f8.png"},{"id":96245574,"identity":"38fb597a-554e-4bbc-b498-9120cbb5e7a2","added_by":"auto","created_at":"2025-11-19 07:21:02","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":361075,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence of Suicidal Ideation in Nigeria\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7990610/v1/dd79349d307a2aac6a1deb3a.png"},{"id":95939949,"identity":"140773f5-1514-4416-b0df-d6d38271fb5d","added_by":"auto","created_at":"2025-11-14 16:08:29","extension":"png","order_by":3,"title":"Figure 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globally. One in every eight individuals lives with some form of mental disorder \u003csup\u003e1\u003c/sup\u003e. Suicide and suicidal behavior are well-known to be strongly related to a history of mental illness \u003csup\u003e2,3\u003c/sup\u003e. Suicide accounts for over 700,000 annual deaths worldwide \u003csup\u003e4\u003c/sup\u003e. The global age-standardized suicide rate was 9.0 per 100,000 people, these rates varied significantly by age and gender, with higher rates in males and younger people\u003csup\u003e5\u003c/sup\u003e. More than half of all suicides in the world (58%) occur in individuals under the age of 50, with a significant majority (88%) of these incidents occurring in low- and middle-income countries (LMICs)(5.). Suicide is the fourth leading cause of death among young people aged 15\u0026ndash;29 years\u003csup\u003e5\u003c/sup\u003e. Nigeria, one of the youngest nations in the world with a median age of about 18 years, had an age-standardized suicide rate of 6.9 per 100,000 population in 2019, based on World Health Organization (WHO) estimates\u003csup\u003e5\u003c/sup\u003e. For every suicide, there are usually multiple preceding suicide attempts\u003csup\u003e4\u003c/sup\u003e, highlighting the broader spectrum of suicidal behaviors, which are important risk factors for eventual suicide. Suicidal behaviors are broadly classified into suicidal ideation, suicidal planning, and suicidal attempts\u003csup\u003e6\u003c/sup\u003e, each representing different stages in the progression toward suicide. Understanding these behaviors is crucial for early intervention and prevention.\u003c/p\u003e\u003cp\u003eSince the World Health Organization launched the Mental Health Gap Action Program (mhGAP) in 2008\u003csup\u003e7\u003c/sup\u003e, there has been a growing focus on suicide research. The WHO\u0026rsquo;s first report on suicide prevention in 2014\u003csup\u003e8\u003c/sup\u003e, advocating for global suicide prevention and comprehensive strategies, coincided with the inclusion of the suicide mortality rate (SDG3.4.2) as a key indicator for the Sustainable Development Goals. In Nigeria, significant strides have been made in mental health policy recently. The National Mental Health Act 2021, enacted in January 2023, represents a critical advancement in the country's commitment to mental health which was followed by the launch of the National Mental Health Policy and the National Suicide Prevention Strategic Framework in November 2023 by the Federal Ministry of Health \u003csup\u003e9\u0026ndash;11\u003c/sup\u003e. Despite these developments, research on suicide behaviors in Nigeria remains limited and fragmented like in other developing regions, mainly due to a lack of effective and reliable vital records on suicide.\u003c/p\u003e\u003cp\u003eExisting literature, mainly cross-sectional studies, has focused on specific groups such as HIV patients, adolescents, the elderly, individuals with mental illness and other sub-population groups \u003csup\u003e12\u0026ndash;15\u003c/sup\u003e. Moreover, findings from general population studies in Nigeria have been inconsistent. An older national study from 2003, which informed most estimates and policies, reported a 3.2% prevalence of suicidal ideation \u003csup\u003e16\u003c/sup\u003e. However, a more recent 2015 study from a populous and diverse state found a higher rate of 7.2%\u003csup\u003e17\u003c/sup\u003e. These differences could be due to changes over time, variations in study design, or differences in diagnostic tools used. Therefore, a comprehensive and updated re-evaluation is necessary to integrate the findings from available studies.\u003c/p\u003e\u003cp\u003eThis study aimed to systematically review the existing literature and quantitatively synthesize the prevalence of suicidal behavior (ideation, plan, and attempt) in Nigeria, focusing on both the general population and specific subgroups. To our knowledge, the only other review on this subject offered qualitative analysis into suicidal behavior in the general population but did not include a meta-analysis \u003csup\u003e18\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eStudy selection\u003c/p\u003e\n\u003cp\u003eThe study selection process is shown in Fig.\u0026nbsp;1 using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA chart)\u003csup\u003e19\u003c/sup\u003e. A total of 30 cross-sectional studies met the inclusion criteria \u003csup\u003e12–14,16,17,20–44\u003c/sup\u003e: Thirty reported on suicide ideation, seven on suicide planning, and 14 on suicide attempts. \u003cstrong\u003eTable\u0026nbsp;1\u003c/strong\u003e summarizes the characteristics of the studies included.\u003c/p\u003e\n\u003cp\u003eSuicide Ideation\u003c/p\u003e\n\u003cp\u003eA total of 30 studies with 45,190 participants, were analyzed to estimate the prevalence of suicidal ideation. The studies included various populations: seven studies focused on people living with HIV (PLHIV) \u003csup\u003e12,26,31,39,41,42,45\u003c/sup\u003e, six on secondary school students\u003csup\u003e22,28–30,34,46\u003c/sup\u003e, six on the general community\u003csup\u003e14,16,17,24,35,43\u003c/sup\u003e, five on tertiary institution students\u003csup\u003e20,25,32,33,44\u003c/sup\u003e, and one study each on female sex workers (FSW)\u003csup\u003e37\u003c/sup\u003e, stroke survivors\u003csup\u003e15\u003c/sup\u003e, healthcare workers (HCW)\u003csup\u003e38\u003c/sup\u003e, male juvenile institution residents\u003csup\u003e23\u003c/sup\u003e, men who have sex with men (MSM)\u003csup\u003e36\u003c/sup\u003e, out-of-school youth\u003csup\u003e27\u003c/sup\u003e, and a refugee population\u003csup\u003e24\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe pooled prevalence of suicidal ideation among the general population\u003csup\u003e14,16,17,24,35,43\u003c/sup\u003e was estimated at 9.7% (95% CI: 5.2–17.3; I\u003csup\u003e2\u003c/sup\u003e = 99%) (Fig.\u0026nbsp;2), based on six studies with 21,804 participants conducted between 2007 and 2015. These studies covered a wide range of regions and populations within the country, with participants ranging from small, local samples to large, multi-state surveys. All the studies used validated diagnostic tools, but they varied, with CIDI used in two studies, and PHQ-9, MINI, KADS, and Prime-MD each used in one study. The certainty of the evidence was very low – downgraded for imprecision, inconsistency and risk of bias – the sampling strategy was unclear for two studies \u003csup\u003e35,43\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eFigure 3A presents a nomogram showing the yearly trends in the prevalence of suicidal behavior from community studies. The regression line indicates a meaningful increase in the proportion of individuals reporting suicidal behaviors over time (\u003cem\u003ep-\u003c/em\u003eheterogeneity = 0.0007). The Baujat plot (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;1\u003c/strong\u003e) shows the contribution of individual studies to the overall heterogeneity and their influence on the summary proportion. The study by Sweetland (2019) contributed the most to heterogeneity, with a high influence on the summary proportion, followed by Gureje (2007) – though the pooled prevalence did not change by \u0026gt; 20% on excluding any studies. The I\u003csup\u003e2\u003c/sup\u003e did not also change meaningfully. The studies assessed suicidal ideation using the Composite International Diagnostic Interview (CIDI) 3.0 \u003csup\u003e14,16\u003c/sup\u003e, Mini International Neuropsychiatric Interview (MINI)\u003csup\u003e24\u003c/sup\u003e, Kutcher Adolescent Depression Scale (KADS-6) \u003csup\u003e35\u003c/sup\u003e, the PRIME-MD Patient Health Questionnaire \u003csup\u003e43\u003c/sup\u003e and the 9-item Patient Health Questionnaire (PHQ-9) \u003csup\u003e17\u003c/sup\u003e. The pooled prevalence of suicidal ideation based on studies that used the CIDI 3.0 among community-dwelling individuals was only 3.9% (95% CI: 3.2, 4.7) \u003csup\u003e14,16\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;2 presents the prevalence of suicidal ideation across various subgroups. The highest prevalence estimates (≥ 20%) were observed among refugees (27.2%; 95% CI: 7.4, 63.5), FSW (21.3%; 95% CI: 5.4, 56.2), MSM (21.3%; 95% CI: 5.5, 55.8), and out-of-school youth (19.9%; 95% CI: 5.1, 53.9).\u003c/p\u003e\n\u003cp\u003eTable 1. Characteristics of Studies Included\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAuthor (Year)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eState\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSetting/Population\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSample size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eAge, y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e,%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiagnostic Tool\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisk of bias\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAdebowale, 2023 \u003csup\u003e20\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOsun\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTertiary Schools Students\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e691\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSuicidal Ideation Scale (adapted from Reynolds (1987))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFair\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAdewuya, 2016\u003csup\u003e17\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLagos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCommunity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePHQ-9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAdewuya, 2020\u003csup\u003e22\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLagos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSecondary School Students\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9441\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e50.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMINI-Kid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFair\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAdeyemo, 2020\u003csup\u003e45\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLagos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePLHIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e38.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMINI-Kid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAjiboye, 2009\u003csup\u003e23\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eKwara\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eJuvenile Institution\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMINI-Kid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFair\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAkinyemi, 2015 \u003csup\u003e24\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOgun\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCommunity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e527\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMINI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFair\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRefugee Community\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e444\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMINI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFair\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAroyewun, 2022 \u003csup\u003e25\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSouthwest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTertiary Schools Students\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2702\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e53.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAdult Suicidal Ideation Questionnaire (ASIQ)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePoor\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBamidele, 2023 \u003csup\u003e12\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOgun\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePLHIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e412\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e47.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e68.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCustom Tool Based on SDVCS and SEM Framework\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGood\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBankole, 2017 \u003csup\u003e26\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCross River\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePLHIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e58.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMINI-Kid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFair\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCheng, 2014 \u003csup\u003e27\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOyo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOut-of-School Youth\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e449\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSingle-Item Question Adapted from the YRBSS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFair\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eChinawa, 2014 \u003csup\u003e28\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEnugu \u0026amp; Ebonyi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSecondary School Students\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e764\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHealth Kids Colorado Questionnaire\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFair\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eChinawa, 2023 \u003csup\u003e29\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEnugu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSecondary School Students\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e450\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e65.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eColumbia Suicide Severity Rating Scale (C-SSRS)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGood\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDade-Matthews, 2024 \u003csup\u003e30\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOgun\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSecondary School Students\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e51.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMINI-Kid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGood\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEgbe, 2017 \u003csup\u003e31\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35 States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePLHIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e66.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWHO-CIDI 3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGureje, 2007 \u003csup\u003e16\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21 States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCommunity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6752\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWHO-CIDI 3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGood\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIweama, 2024 \u003csup\u003e32\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAdamawa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTertiary Schools Students\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e616\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e33.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSuicidal Behaviors Questionnaire-Revised (SBQ-R)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGood\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLadi-Akinyemi, 2023 \u003csup\u003e33\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLagos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTertiary Schools Students\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePHQ-9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMapayi, 2016 \u003csup\u003e34\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOsun\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSecondary School Students\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e50.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDISC-DPS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFair\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNyundo, 2020 \u003csup\u003e35\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOyo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCommunity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e54.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eKutcher Adolescent Depression Scale (KADS-6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePoor\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOgunbajo, 2020 \u003csup\u003e36\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4 states\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e389\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCES-D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFair\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOjagbemi, 2013 \u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eYoruba Speaking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCommunity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e75.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e53.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWHO-CIDI 3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGood\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOkonkwo, 2022 \u003csup\u003e37\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLagos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFSW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e224\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e26.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMINI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGood\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOlibamoyo, 2020 \u003csup\u003e38\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLagos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHCW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e66.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAttitudes Toward Suicide Scale (ATTS)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFair\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOmigbodun, 2008 \u003csup\u003e13\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOyo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSecondary School Students\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1429\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e49.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDISC-DPS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOnyebueke, 2015 \u003csup\u003e39\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEnugu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePLHIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e33.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e38.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMINI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGood\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOpakunle, 2018 \u003csup\u003e40\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOsun\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSecondary School Students\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e50.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSuicidal Behaviors Questionnaire-Revised (SBQ-R)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFair\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOyedun, 2023 \u003csup\u003e41\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGombe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePLHIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e41.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e67.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMINI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFair\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSeb-Akahomen, 2019 \u003csup\u003e42\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEdo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePLHIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e410\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e75.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMINI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSweetland, 2019 \u003csup\u003e43\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eKaduna\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCommunity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e380\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e38.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSelf-report PRIME-MD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePoor\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUteh, 2022 \u003csup\u003e44\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOndo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTertiary Schools Students\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e47.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBeck's Scale for Suicide Ideation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGood\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;Table 2: Subgroups Estimated Prevalence of Suicidal Behaviors\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"399\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eSample Size\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(No. of Studies)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eSuicide Ideation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;Community\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e9.7% (5.2, 17.3)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e21,804 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;Secondary Schools\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e10.5% (6.2, 17.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e13,824 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;Tertiary Institutions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e13.4% (6.6, 25.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e4,759 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;PLHIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e9.7% (5.6, 16.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e4,235 (8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;FSW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e21.3% (5.4, 56.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e224 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;MSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e21.3% (5.5, 55.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e389 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;Out-of-school Youth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e20.0% (5.1, 53.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e449 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;Refugees\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e27.2% (7.4, 63.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e444 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eStroke survivors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.7% (0.3, 8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e150 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eSuicide Plan\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;Community\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.8% (0.7, 4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e9651 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;Secondary Schools\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e4.4% (1.5, 12.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e9441 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;Out-of-school Youth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e15.1% (5.4, 35.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e444 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;PLHIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e4.4% (1.9, 9.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e822 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eSuicide Attempt\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;Community\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.1% (0.2, 4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e9,651 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;Secondary Schools\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e5.3% (2.6, 10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e12,385 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;Out-of-school Youth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e14.2% (3.7, 41.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e449 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;HCW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e7.4% (1.7, 26.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e226 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;MSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e10.2% (2.6, 32.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e389 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;PLHIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e2.5% (1.3, 4.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e2,159 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe minor differences in community prevalence estimates from the forest plots are due to rounding.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3: Risk factors of Suicidal Behavior\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategories\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eSuicide Ideation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eSuicide Plan\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eSuicide Attempt\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eValue (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ep-\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eheterogeneity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eValue (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ep-\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eheterogeneity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eValue (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ep-\u003c/em\u003eheterogeneity\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAge, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;Adolescents, \u0026lt;20y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e9.4% (6.8, 12.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e7.3% (3.7, 13.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e5.3% (3.0,9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0029\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;20 - 35y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e17.2% (7.6, 34.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e10.2% (2.4,34.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;35 - 49y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e15.3% (8.7, 25.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e2.6% (1.3, 5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e2.6% (1.3,5.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e50 – 65 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;65+ y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e4.6% (1.9, 10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.9% (0.3, 3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.3% (0.1,1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSex, OR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.99 (0.97, 1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.99 (0.96, 1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.99 (0.96, 1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMarital status, OR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.00 (0.98, 1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.99 (0.97, 1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.99 (0.96, 1.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEducation, OR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.84 (0.69, 1.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ePrimary or secondary\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eTertiary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.01 (0.95, 1.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEmployment, OR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eEmployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.98 (0.97, 1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRegion, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNorth-Central\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.8% (2.7, 16.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.0041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.27% (0.36, 13.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNorth-East\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e25.9% (11.8, 47.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNorth-West\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e29.7% (15.4, 49.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eSouth-East\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e6.3% (2.9, 13.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eSouth-South\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e9.8% (3.9, 22.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e3.2% (0.6, 15.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.5% (0.3, 6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eSouth-West\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e13.2% (10.0, 17.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e4.8% (2.3, 9.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e4.8% (2.6, 8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;Table 3 presents the prevalence of suicidal ideation across levels of sociodemographic risk characteristics reported in all suicidal ideation studies. Meta-regression indicated that the prevalence of suicidal ideation was significantly related to the study location (\u003cem\u003ep-\u003c/em\u003eheterogeneity = 0.041) and employment status (\u003cem\u003ep-\u003c/em\u003eheterogeneity = 0.091). The predicted prevalence of suicidal ideation was greatest in the North-East (25.9%; 95% CI: 11.8, 47.6) and North-West (29.7%; 95% CI: 15.4, 49.6) regions. For every one percentage point higher proportion of individuals who were employed, the odds of suicidal ideation were lower by 0.98 (95% CI: 0.97, 1.00). The other demographic factors examined were not related to the prevalence of suicidal ideation: age (\u003cem\u003ep-\u003c/em\u003eheterogeneity = 0.20), sex (\u003cem\u003ep-\u003c/em\u003eheterogeneity = 0.66), marital status (\u003cem\u003ep-\u003c/em\u003eheterogeneity = 0.24) and educational attainment (\u003cem\u003ep-\u003c/em\u003eheterogeneity = 0.22). The prevalence of suicidal ideation was greatest among adolescents and young adults, but the confidence intervals were too wide and overlapped.\u003c/p\u003e\n\u003cp\u003eSuicide Planning\u003c/p\u003e\n\u003cp\u003eSeven studies involving 20,363 participants were included in the analysis of suicide planning. The studies were distributed across three different subgroups, three community-based studies \u003csup\u003e14,16,35\u003c/sup\u003e, two studies on PLHIV \u003csup\u003e12,42\u003c/sup\u003e, one study among secondary school students \u003csup\u003e22\u003c/sup\u003e, and one study among out-of-school youth \u003csup\u003e27\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe pooled prevalence of suicidal planning in the general community was 1.8% (95% CI: 0.7–4.5%; I\u003csup\u003e2\u003c/sup\u003e = 96%; Fig.\u0026nbsp;4A), based on three studies among 9,651 participants. One study used the KADS tool and focused on a single state, Oyo. The other two studies, using the CIDI tool, were conducted across multiple states with Oyo included in both. The certainty of the evidence was low – downgraded for imprecision and risk of bias – the sampling strategy was unclear for one study \u003csup\u003e35\u003c/sup\u003e. Baujat plots \u003cstrong\u003e(Supplementary Fig.\u0026nbsp;1B)\u003c/strong\u003e indicate that the study by Nyundo (2020) had a significant influence on the summary proportion, contributing considerably to the overall heterogeneity \u003csup\u003e35\u003c/sup\u003e. This study was conducted in a Nigerian city, as part of an international multi-country study. On excluding this study, the prevalence of suicide planning was 1.0% (95% CI: 0.8, 1.2), which is lower by \u0026gt; 20%. The I\u003csup\u003e2\u003c/sup\u003e also became 0.0%. The other two were multi-center studies that assessed suicide planning using the CIDI 3.0 \u003csup\u003e14,16\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eOf the subgroups assessed (Table\u0026nbsp;2), the prevalence of suicide planning was greatest in out-of-school youths (15.1%; 95% CI: 5.4, 35.6). The prevalence of suicide planning was 4.4% (95% CI: 1.5, 12.2) based on a single study among secondary school students and 4.4% (95% CI: 1.9, 9.7) based on a single study among PLHIV.\u003c/p\u003e\n\u003cp\u003eMeta-regression indicated that the prevalence of suicide planning was significantly related to the age (\u003cem\u003ep-\u003c/em\u003eheterogeneity = 0.0078). The prevalence was 7.3% (95% CI: 3.7, 13.7) among adolescents but only 2.6% (95% CI: 1.3, 5.3) among adults 35–49 y, and 0.9% (95% CI: 0.3, 3.2) among adults ≥ 65 years. The other demographic factors examined were not related to the prevalence of suicide planning: sex (\u003cem\u003ep-\u003c/em\u003eheterogeneity = 0.28), marital status (\u003cem\u003ep-\u003c/em\u003eheterogeneity = 0.66) and study location (\u003cem\u003ep-\u003c/em\u003eheterogeneity = 0.66).\u003c/p\u003e\n\u003cp\u003eSuicide Attempt\u003c/p\u003e\n\u003cp\u003eFourteen studies involving 25,259 participants were included in the analysis of suicidal attempts. The studies were distributed across six different subgroups: three community-based studies \u003csup\u003e14,16,35\u003c/sup\u003e, four studies involving PLHIV \u003csup\u003e12,26,31,42\u003c/sup\u003e, four studies among secondary school students \u003csup\u003e13,22,34,46\u003c/sup\u003e, and one study each among out-of-school youth \u003csup\u003e27\u003c/sup\u003e, MSM \u003csup\u003e36\u003c/sup\u003e, and HCWs \u003csup\u003e38\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe pooled prevalence of suicidal attempts among community-dwelling individuals was estimated at 1.1% (95% CI: 0.23–4.8; I\u003csup\u003e2\u003c/sup\u003e = 98%; Fig.\u0026nbsp;4B), based on three studies among 9,651 participants. The certainty of the evidence was low – downgraded for imprecision and risk of bias – the sampling strategy was unclear for one study \u003csup\u003e35\u003c/sup\u003e. Baujat plots \u003cstrong\u003e(Supplementary Fig.\u0026nbsp;1B)\u003c/strong\u003e indicate that the study by Nyundo (2020) had a significant influence on the summary proportion, contributing considerably to the overall heterogeneity \u003csup\u003e35\u003c/sup\u003e. On excluding this study, the prevalence of suicide planning was 0.5% (95% CI: 0.3, 0.9), which is lower by \u0026gt; 20%. The I\u003csup\u003e2\u003c/sup\u003e also became 76%.\u003c/p\u003e\n\u003cp\u003eOf the subgroups assessed (Table\u0026nbsp;2), out-of-school youth were the most likely to have had a previous suicide attempt (14.2%; 95% CI: 3.7, 41.2).\u003c/p\u003e\n\u003cp\u003eMeta-regression indicated that the prevalence of suicidal attempts was significantly related to the age (\u003cem\u003ep-\u003c/em\u003eheterogeneity = 0.0029). The prevalence was the greatest among adolescents (5.3%; 95% CI: 3.0, 9.3) and young adults (10.2%; 95% CI: 2.4, 34.4).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe reviewed 30 studies conducted between 2007 and 2024 to provide pooled prevalence estimates of suicidal behaviors in Nigeria for the general population and key subgroups. Among the general population, the prevalence of suicidal ideation was 9.7%, with employment status and study location significantly associated with prevalence rates. The prevalence of suicide planning and suicide attempts among the general population were 1.8% and 1.1%, respectively, both strongly linked to age, with adolescents showing the highest rates. Over time, the proportion of individuals reporting suicidal behaviors has increased, and notable variations were observed across different subgroups.\u003c/p\u003e\u003cp\u003eOur estimates for suicidal ideation, planning, and attempts among the general population are similar to a meta-analysis from Ethiopia\u003csup\u003e47\u003c/sup\u003e, the World Health Mental Health survey from 17 countries including Nigeria published in 2008\u003csup\u003e48\u003c/sup\u003e, and a national study from German population\u003csup\u003e49\u003c/sup\u003e, but much higher than reports from Europe\u003csup\u003e50\u003c/sup\u003e, China\u003csup\u003e51\u003c/sup\u003e and some LMICs \u003csup\u003e52\u003c/sup\u003e. Our results are lower than the prevalence from community studies in India and South Africa \u003csup\u003e52\u003c/sup\u003e. These differences may reflect variations in the availability of mental health services, diagnostic practices, and exposure to risk factors of suicidal behaviors.\u003c/p\u003e\u003cp\u003eOur findings revealed significant subgroup variations in the prevalence of suicidal behaviors. The estimated prevalence of suicidal ideation for MSM (21.3%), refugees (27.2%), FSW (21.3%), and out-of-school youth (20%) were markedly higher than those for the general population. This pattern was similar for suicide planning and attempts. Our findings are consistent with published studies, which consistently show elevated suicide risk among these groups (56\u0026ndash;60). This is likely driven by the compounded effects of socio-economic factors, stigma, discrimination, and disease burden. Importantly, these groups also experience higher rates of mental health disorders, which are well-established risk factors for suicidal behavior \u003csup\u003e2,3\u003c/sup\u003e. These findings underscore the role of social inequities in shaping mental health outcomes, highlighting the need for nuanced population-specific interventions tailored to these vulnerable populations.\u003c/p\u003e\u003cp\u003eOur analysis also showed significant age-related variations in suicidal behaviors. Suicidal ideation was most common among young adults (17.2%) and middle-aged adults, 35\u0026ndash;49 years (15.3%), with adolescents reporting relatively lower but still concerning rates (9.4%), while older adults showed the lowest prevalence (4.6%). The prevalence of suicidal planning followed a similar pattern, with adolescents showing the highest rates (7.3%) and older adults reporting the lowest (2.6%). Suicidal attempts were also more frequent among younger populations, especially young adults (10.2%) and adolescents (5.3%). We also found higher rates of suicidal behaviors among secondary (Ideation 10.5%, Plan 4.4%, Attempt, 5.3%) and tertiary (Ideation 13.4%) school students This pattern is consistent with global trends, where younger populations are showing higher burden of mental health issues and suicidal behavior \u003csup\u003e5,58\u0026ndash;60\u003c/sup\u003e, a critical issue highlighted by the Lancet Psychiatry Commission on youth mental health\u003csup\u003e61\u003c/sup\u003e. The Commission emphasized that the mental health of emerging adults has steadily worsened over the past two decades, with the COVID-19 pandemic and its aftermath further intensifying this crisis \u003csup\u003e61\u003c/sup\u003e. Factors such as developmental challenges, socio-economic pressures, identity formation stress, and increased exposure to social media and digital environments have all been linked to this growing public health issue \u003csup\u003e59,62\u0026ndash;64\u003c/sup\u003e. In contrast, older adults may benefit from greater emotional resilience \u003csup\u003e65\u003c/sup\u003e, companionship, and established social networks \u003csup\u003e66,67\u003c/sup\u003e, which could contribute to their lower prevalence of suicidal behaviors.\u003c/p\u003e\u003cp\u003eStudy location and employment status are other key factors associated with suicidal ideation in our results. The highest prevalence was observed in the northern regions, particularly the North-East and North-West. These regions suffer from high poverty rates and have been severely impacted by conflict, terrorism, and displacement; this could partly explain our result. These findings should however be interpreted with caution as the studies from the North-East and North-West were not from the general population. They were conducted among young people attending university \u003csup\u003e32\u003c/sup\u003e and PLHIV \u003csup\u003e41\u003c/sup\u003e, though the national prevalence of suicidal behavior was not exceedingly high among university students and PLHIV. Unemployment was also linked to higher suicidal ideation in our findings. Employment appears to offer protection against suicide and suicidal behaviors \u003csup\u003e68\u003c/sup\u003e. No significant associations were found with sex, marital status, or education level \u0026mdash;factors often linked to suicide risk. This may be due to the limitations of pooled studies.\u003c/p\u003e\u003cp\u003eThe findings of this study have important implications for public health policy in Nigeria and will support the implementation of the National Suicide Prevention Strategic Framework (NSPSF) 2023\u0026ndash;2030 \u003csup\u003e9\u0026ndash;11\u003c/sup\u003e. Suicide prevention efforts should prioritize improving access to mental health services for higher-risk groups. Given the association between economic instability and suicidal behaviors, policies aimed at reducing unemployment and improving economic conditions will be critical. Expanding mental health services in primary care, increasing the community health workforce, enhancing community-based initiatives, and improving health insurance are key to addressing the growing burden of suicide in Nigeria. More than half of the country are under 18 years old. Specific interventions targeted at this demographic are required to provide crucial help to them.\u003c/p\u003e\u003cp\u003eThis analysis offers several strengths, including the separate pooling of data for the general population and subgroups, which provided a more nuanced understanding of suicidal behaviors across diverse populations. By grouping studies based on behavior, subgroup, and setting, we ensured more accurate inferences. Additionally, the use of GRADE principles to assess the strength of evidence increased the transparency and reliability of our findings. However, there are limitations to consider when interpreting our findings. The availability and quality of studies were limited, with many subgroups represented by only a few or single studies, highlighting significant gaps for future research. Most of the studies were conducted in urban areas, limiting the representation of the data, and the absence of older studies restricted the analysis of long-term trends. Furthermore, although the studies included used validated diagnostic tools, their variation across studies may have introduced inconsistencies. Finally, methodological constraints prevented us from assessing publication bias, which could have affected the pooled estimates. We systematically reviewed the published studies of the prevalence of suicidal behaviors in Nigeria, and found that suicidal behaviors are common, with the greatest burden among certain demographic subgroups \u0026ndash; adolescents, refugees, female sex workers, men who have sex with men, and out-of-school youth. National and subnational mental health policies and interventions should account for this variation and target the groups with the highest burden.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eReporting\u003c/p\u003e\u003cp\u003eThis review was developed according to the PRISMA guidelines \u003csup\u003e19\u003c/sup\u003e and the Joanna Briggs Institute (JBI) methodology for systematic reviews on prevalence \u003csup\u003e69\u003c/sup\u003e. The protocol is registered with the International Prospective Register of Systematic Reviews (PROSPERO; CRD42024559090) and has been published elsewhere.\u003csup\u003e70\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eEligibility criteria\u003c/p\u003e\u003cp\u003eStudies were included if they focused on suicidal behavior (ideation, planning, and attempt) diagnosed by healthcare professionals or identified through validated tools, and provided prevalence estimates among individuals in Nigeria, representing the general population or specific subgroups. There were no restrictions on age, sex, or subgroup, but studies from psychiatric patients were excluded. Eligible studies were cross-sectional surveys or baseline data from cohort studies conducted in Nigeria. We also excluded studies that did not focus on prevalence, were case-control studies, reviews, case reports, duplicates, or involved non-human research.\u003c/p\u003e\u003cp\u003eInformation sources and Search strategy\u003c/p\u003e\u003cp\u003eWe searched medical literature databases including PUBMED/Medline (U.S. National Library of Medicine), EMBASE (Elsevier) and African Journals Online (AJOL) for studies of mental disorders in Nigeria as part of a larger project. This paper reports on suicidal behaviors. Studies from the inception of the databases until July 2024 were included. Hand-searching was also done by examining the reference list of included papers and Google Scholar for additional papers. The search strings included a combination of MeSH terms (Medical Subject Headings), Emtree terms, and topics by which articles are indexed for the PubMed/Medline and Embase databases, respectively, as well as relevant text and keywords (Supplementary Table\u0026nbsp;1). The search strings were focused on the following concepts: Nigeria, mental disorder, and prevalence. Database records were exported to a Zotero library for managing search results and removing duplicates.\u003c/p\u003e\u003cp\u003eStudy Selection and Data Extraction\u003c/p\u003e\u003cp\u003eThe study selection involved three rounds: an initial title/abstract review to exclude non-qualifying studies, a full-text review to determine eligibility, and data extraction from the eligible studies. Two independent investigators performed the first two rounds in duplicate, with disagreements resolved by a third reviewer. Rayyan Software was used for study screening and data extraction was carried out independently using a custom cloud-based spreadsheet, which also included risk of bias assessments for collaborative record-keeping. The extracted data were organized into five sections: study identification, participant demographics, study characteristics, outcome measures, and risk of bias assessment.\u003c/p\u003e\u003cp\u003eRisk of bias assessment\u003c/p\u003e\u003cp\u003eThe risk of bias was assessed using the National Institute of Health Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies \u003csup\u003e71\u003c/sup\u003e. The tool assesses population clarity, minimal non-response, consistent sampling, representativeness, sample size rigor, and clear definition of the health condition.\u003c/p\u003e\u003cp\u003eEffect Measure and Data Synthesis\u003c/p\u003e\u003cp\u003eThe effect measure is the prevalence or proportion of participants with the outcome. Random-effects meta-analyses models were used to synthesize data from studies reporting on the prevalence of the three types of suicidal behavior, accounting for study variability. The main summary measure was the pooled prevalence rate. Meta-analysis was performed in R version 4.5.1 using the \u003cem\u003emetafor\u003c/em\u003e package version 4.8-0. Heterogeneity was assessed using the I\u0026sup2; statistic, categorized as minimal (0\u0026ndash;40%), moderate (\u0026gt;\u0026thinsp;40\u0026ndash;60%), substantial (60\u0026ndash;80%), or considerable (\u0026gt;\u0026thinsp;80%) \u003csup\u003e72\u003c/sup\u003e. To evaluate the influence of each study on the pooled estimate and its contribution to heterogeneity for meta-analyses with more than three studies, Baujat plots were generated to depict the relationship of each study\u0026rsquo;s influence on the pooled estimate to its contribution to the overall heterogeneity - represented by the Cochran Q-statistic \u003csup\u003e73\u003c/sup\u003e. Influence analysis involved sequentially omitting studies to compare the pooled estimate and I\u0026sup2; statistic. Meta-regression was conducted to examine variations by age group, subgroup, and study period, with trends presented using a nomogram. Publication bias was not assessed, as traditional methods like funnel plots and Egger\u0026rsquo;s tests do not apply to meta-analyses of proportions. \u003csup\u003e73\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eCertainty Assessment\u003c/p\u003e\u003cp\u003eFor each prevalence measure, we systematically assessed the certainty of the evidence using a modification of the GRADE approach \u003csup\u003e74,75\u003c/sup\u003e. The certainty of evidence was rated down if included studies were not likely representative based on participant selection strategy (risk of bias), if the pooled estimate was imprecise (imprecision), if the point estimates and confidence intervals from each study substantially varied (inconsistency), or if the assessed population or outcome assessment differs from the population or outcome assessment of interest (indirectness). For imprecision, the following evidence thresholds based on a rule of thumb were used: 50%, 30%, 10%, 5%, 1%, 0.10 and 0%, as they change clinical and public health perceptions of how prevalent or rare the condition is. While a summary grade of moderate or high certainty evidence indicates we believe the true prevalence is correctly estimated or close to the estimated prevalence, a low or very low certainty evidence indicates we believe the true prevalence is probably meaningfully different from the estimated prevalence \u003csup\u003e76\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eData and Code Availability\u003c/p\u003e\n\u003cp\u003eThe authors compiled the data used in this analysis from studies identified through a systematic review of PubMed (https://pubmed.ncbi.nlm.nih.gov), Embase (https://www.embase.com), African Journals Online (https://www.ajol.info/index.php/ajol), and manual searches of reference lists of included articles. The data and analysis code are available from the corresponding author upon reasonable request.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eI.A. conceived and designed the study and performed the systematic search. I.A. and M.Y. developed the preliminary protocol and assembled the study team. A.K.A., I.A., D.O., T.O., S.O.O., J.M., M.A.K., M.Y., O.T., S.O., M.O.O., and E.I. performed study screening, data extraction, and quality appraisal. A.K.A. and I.A. conducted the statistical analysis. M.A.K. and A.A. provided clinical expertise. A.K.A., I.A., and M.Y. drafted the manuscript. A.K.A., I.A., D.O., T.O., S.O.O., J.M., M.A.K., M.Y., O.T., S.O., M.O.O., E.I., and A.A. contributed to the study design, drafting, and critical revision of the manuscript. I.A. and A.A. provided supervision. All authors had full access to the data, are responsible for the integrity of the study, and approved the final version of the manuscript for publication.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors did not receive any funding for this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eMaterials \u0026amp; Correspondence\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence and requests for materials should be addressed to Mohammed Nakodi Yisa\u0026nbsp;\u003c/p\u003e\n\u003cp\[email protected]\u003c/p\u003e\n\n\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMental disorders. https://www.who.int/news-room/fact-sheets/detail/mental-disorders.\u003c/li\u003e\n\u003cli\u003eFranklin, J. 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J. \u003cem\u003eet al.\u003c/em\u003e Completing \u0026lsquo;Summary of findings\u0026rsquo; tables and grading the certainty of the evidence. in \u003cem\u003eCochrane Handbook for Systematic Reviews of Interventions\u003c/em\u003e 375\u0026ndash;402 (John Wiley \u0026amp; Sons, Ltd, 2019). doi:10.1002/9781119536604.ch14.\u003c/li\u003e\n\u003cli\u003eNoyes, J. \u003cem\u003eet al.\u003c/em\u003e Qualitative evidence. in \u003cem\u003eCochrane Handbook for Systematic Reviews of Interventions\u003c/em\u003e 525\u0026ndash;545 (John Wiley \u0026amp; Sons, Ltd, 2019). doi:10.1002/9781119536604.ch21.\u003c/li\u003e\n\u003cli\u003eBritish Medical Journal (BMJ),. What is GRADE? \u003cem\u003eBMJ Best Practice\u003c/em\u003e https://bestpractice.bmj.com/info/us/toolkit/learn-ebm/what-is-grade/.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7990610/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7990610/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSuicidal behaviors are a growing global concern, particularly among young people, yet their burden remains poorly defined in Nigeria, a country with a predominantly young population. This systematic review and meta-analysis synthesized data from 30 studies involving 45,190 participants published up to August 2024 to estimate the prevalence and correlates of suicidal ideation, planning, and attempts in Nigeria. Studies reporting the prevalence of suicidal behaviors in the Nigerian general population or specific subgroups, using healthcare diagnosis or validated screening tools, were included. The pooled prevalence of suicidal ideation in the general population was 9.7%, while suicidal planning and attempts were estimated at 1.8% and 1.1%, respectively. Suicidal behaviors were more prevalent among adolescents, refugees, out-of-school youth, sexual minorities, and in northern regions. Prevalence estimates increased over time. These findings confirm that suicidal behaviors are common in Nigeria and underscore the need for targeted intervention strategies tailored to high-risk populations.\u003c/p\u003e","manuscriptTitle":"Prevalence of suicidal behavior in Nigeria: A systematic review and meta-analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-14 16:08:14","doi":"10.21203/rs.3.rs-7990610/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-17T09:22:30+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-15T10:53:06+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-15T04:12:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"145231245278711201713592609963329623990","date":"2025-11-10T01:08:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"199440099244692031736114368550054435501","date":"2025-11-05T17:16:25+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-05T09:23:21+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-04T09:09:19+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-01T05:12:22+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-01T05:11:06+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-10-30T14:45:39+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"55fd2105-71b8-496a-9145-650f687b83a4","owner":[],"postedDate":"November 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":57733997,"name":"Health sciences/Diseases"},{"id":57733998,"name":"Health sciences/Health care"},{"id":57733999,"name":"Health sciences/Medical research"},{"id":57734000,"name":"Biological sciences/Psychology"},{"id":57734001,"name":"Social science/Psychology"},{"id":57734002,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2026-01-26T16:05:37+00:00","versionOfRecord":{"articleIdentity":"rs-7990610","link":"https://doi.org/10.1038/s41598-026-36002-6","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2026-01-20 15:57:49","publishedOnDateReadable":"January 20th, 2026"},"versionCreatedAt":"2025-11-14 16:08:14","video":"","vorDoi":"10.1038/s41598-026-36002-6","vorDoiUrl":"https://doi.org/10.1038/s41598-026-36002-6","workflowStages":[]},"version":"v1","identity":"rs-7990610","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7990610","identity":"rs-7990610","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}