Human flourishing and suicide: A national-level analysis with 22 countries

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Lennon, Xavier Symons, Aswin Ratheesh, Joseph Suttie, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8487304/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Purpose Suicide rates continue to increase in many nations despite awareness and prevention campaigns. While economic factors, substance abuse and availability of means have been associated with suicide rates, much of the population-level variability remains unexplained. To assess the association between national-level flourishing index scores, flourishing subdomains and age-standardised suicide mortality rates. Methods This study used national-level, cross-sectional data from Global Flourishing Study (GFS) and the Global Burden of Disease (GBD) Study (2021). Generalised linear models were used to assess the relationships between the exposures and outcomes. The exposures included the flourishing index and flourishing domain scores (happiness/life satisfaction, mental/physical health, meaning/purpose, character/virtue, close social relationships, and financial/material stability). The primary outcome was suicide mortality (GBD 2021). Results There were 202,838 participants included in the GFS from 22 countries nations that differed widely by socioeconomic status, cultural background, and religious tradition. In the main age-adjusted analysis, national flourishing index scores were inversely associated with the GBD estimates of suicide mortality (B=-5.2; 95%CI[-8.9, -1.4]). The two flourishing domains associated with suicide mortality were meaning/purpose (B=-4.6; 95%CI[-7.3, -1.8]) and close social relationships (B=-4.8; 95%CI[-8, -1.6]), with little evidence of associations found with the other four domains. Conclusion Measures of flourishing may be more closely associated with suicide mortality than previously used measures of wellbeing. Flourishing, particularly in domains of meaning/purpose and close social relationships, should be considered in further research of causal factors and in national frameworks for suicide prevention. Suicide Flourishing Meaning Purpose Relationships Happiness Figures Figure 1 Figure 2 Introduction In 2021, approximately 746,000 people worldwide died by suicide, [1] with suicide being the third leading cause of death among young adults and adolescents. Suicide mortality rates vary significantly by country, with particularly high rates observed in some regions such as Eastern Europe and Asia [2]. Recent decades have seen alarming suicide rate increase in countries such as the United States, South Korea, and India, and many of the fundamental drivers of these increases remain unclear [3,4]. There are a panoply of known risk factors for suicide mortality rates at a national level. Economic factors such as unemployment and economic downturns consistently correlate with increased suicide rates, reflecting the profound psychological and social impacts of real-world financial instability [5]. Substance abuse also frequently emerges as a major risk factor, exacerbating mental health challenges and increasing impulsivity and vulnerability [2]. Religious belief and practice on the other hand may be protective factors for suicide risk through mechanisms of social cohesion, moral frameworks, and community support; however, these patterns vary widely by cultural context [6–8]. Particularly interesting is the relationship between rates of happiness in a community and suicide. Some studies suggest that nations with higher rates of happiness may also have higher rates of suicide [9], while others indicate that there may be no relationship at all between the two measures [10] or that the relationship may be largely explained by differences in human development indices. Despite the known, established risk factors, a significant amount of variability in suicide rates remains unexplained by current models [11]. This inadequacy in predictive capability poses serious challenges to public health interventions, potentially explaining why well-intentioned suicide prevention interventions and frameworks, may be followed by increased rates of suicide despite greater suicide awareness and support programs. Human flourishing as an explanatory factor There is a need for better explanatory models incorporating cultural dimensions and broader measures of wellbeing beyond self-reported personal happiness. The Global Flourishing Study, introduced by VanderWeele et al.[12], offers a novel multinational opportunity, with nationally representative sampling, to assess and monitor individual flourishing across six domains: happiness/life satisfaction, physical/mental health, meaning/purpose, character/virtue, close social relationships, and financial/material stability. These domains collectively provide a richer, multidimensional understanding of human wellbeing, potentially capturing crucial elements influencing suicide risk that more unidimensional measures of wellbeing may lack. In this study, we use nationally representative data from the Global Flourishing Study (GFS) and the Global Burden of Disease (GBD) Study to examine the relationship between national average scores on the flourishing index, national suicide rates and the suicide-related constructs of intentional self-harm and depressive disorders. Methods Primary and secondary predictors Flourishing index data were taken from Wave 1 of the GFS, which was collected between April 2022 and December 2023, [12,13] including 22 countries and over 200,000 participants. The participating countries were Argentina, Australia, Brazil, China (Hong Kong), Egypt, Germany, India, Indonesia, Israel, Japan, Kenya, Mexico, Nigeria, the Philippines, Poland, South Africa, Spain, Sweden, Tanzania, Turkey, the United Kingdom, and the United States. These countries represent a diverse global perspective, allowing the flourishing index and its domains to be analysed across varied cultural, economic, and demographic contexts. Nationally representative surveys were conducted to generate estimates of the primary predictor, the flourishing index, and the secondary predictors, the 6 flourishing index domains (happiness/life satisfaction, mental/physical health, meaning/purpose, character/virtue, close social relationships, and financial/material stability) (See table 1 for the 12 items comprising the flourishing index). The GFS collected data using Gallup polling methodologies to ensure approximately nationally representative samples [13]. The description of sampling methods and study design can be found in the methodology report [14] and the survey development report [15] by Gallup Inc. as well as the previous publications by the GFS research team [13,16] . These papers explain in detail the processes of survey development, survey translation, interviewer training, sampling design and collection, the use of probability and non-probability-based samples, post-data collection quality evaluation and the weighting and design effects. Missing data Following the standardised analytic methodology [17] of the GFS, missing flourishing domain data was imputed using multiple imputation by chained equations [18] in the R package mice . Imputations were performed separately for each nation, with 5 imputed datasets being formed. This within-country approach allowed the imputation to appropriately capture country-specific contexts and assessment methods. Sampling weights were included in the imputation model to adjust for the specific-variable missingness that could be linked to the likelihood of study inclusion. The rate of missing data needing to be imputed was very low, varying from 0.32 to 0.73% across the 6 flourishing domains. Further details of the multiple imputation approach and example code can be found in the references [17,19]. Accounting for complex sampling design The GFS applied disparate sampling methodologies between countries based on recruitment needs and participant availability [14]. All estimates of national-level flourishing and its domains accounted for this complex survey design, using the R package survey [20] , by applying individual weights, primary sampling units (PSUs) and strata. More detail on the methodology of the GFS has been provided in previous papers [13,14]. Primary and secondary outcomes Suicide rates and secondary outcome data are sourced from the Global Burden of Diseases (GBD) Study 2021. The GBD study [21] calculates national age-standardised suicide mortality rates (suicide mortality), our primary outcome, by integrating multiple data sources, including vital registration systems, surveys, and health facility records, using advanced modelling techniques to adjust for potential biases and underreporting [1]. However, the GBD study has been criticised for its possible overreliance on modelled data for regions with low quality reporting, potentially distorting real-world data [1,21]. To evaluate the robustness of results to a different data sources, a separate source of national age-standardised suicide mortality rates was taken from the World Health Organisation 2021 Global Health Estimates Report [22] (Supplementary Methods). At the time of writing the fully developed research paper on GBD 2023 [23] Suicide Mortality and subgroups have not been developed however some results are publicly available and were similarly tested to examine for the robustness of the results [24]. The primary outcome was the national age-standardised suicide mortality rate. Suicide mortality data, particularly in some jurisdictions, is known to be inaccurately reported [25] in part due to religious and cultural taboos around suicide. As such, this study included two suicide-related secondary outcomes, also from the GBD 2021 Study, that may be more reliably reported than suicide. Intentional self-harm (ISH) [26] is an indicator of psychological distress and emotional dysregulation, is a predictor of suicide and may overlap with suicide mortality. However, ISH, has a distinct risk factor profile when compared to completed suicide, most notably that it is 2-3 times more prevalent in women, whereas completed suicide is 2-3 times more common in men [26]. National age-adjusted ISH disability-adjusted life years (DALYs) was used as a measure of the burden of disease. Depressive disorders prevalence [27], which includes ICD-10 codes for both Major Depressive Disorder (MDD) and Dysthymia, are orders of magnitude more common than suicide and are associated with suicide mortality. Similar to ISH, depressive disorders have a distinctive risk factor profile and is more common in women [28]. Ethics Approval This study involves analysis of publicly available data; thus, specific ethical approval for this analysis is not required. The Global Flourishing Study received prior ethical approval to collect and disseminate de-identified data from participating countries from the Institutional Review Boards of Gallup (IRB Reference #: 2021-11-02) and Baylor University (IRB Reference #: 1841317). The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2013. Statistical Analysis Each of the 22 countries served as an individual datapoint in the analyses. High influence outliers were identified for each outcome using a Cook’s D threshold of 4/22 (0.1818) (See Supplementary Methods and Supplementary Table 1). Models were run excluding and including high influence outlier countries. Median age within each country was included as the main covariate, as study primary and secondary outcomes have been shown to vary across the age range. This simple age-adjusted analysis was the main analysis. As an additional set of analyses, covariates used in the GBD 2021 suicide mortality study [1] were included in stepwise regression models. These covariates included years of education, gross domestic product (GDP) per capita, sociodemographic index (SDI), population density, mean annual temperature, and numbers of firearms per capita (see Supplementary Methods for covariate sources and descriptions). Given the limited data availability (i.e. up to 21 degrees of freedom) models needed to be parsimonious and optimised for fit without discarding important covariates. Model optimization utilized Akaike Information Criterion (AIC) to select the most relevant covariates, refining model accuracy and efficiency, using a backwards-stepwise approach (Supplementary Table 2). Generalized linear models (GLMs) were used to investigate the relationships between predictors and outcomes. The primary analysis included the flourishing index as the main predictor, while secondary analyses assessed flourishing index domains. Supplementary analyses were performed examining if relationships remained consistent in analyses stratified by sex and distinct age groups (18–29, 30–49, 50–69, and 70+). A further supplementary analysis was performed repeating the main analysis, examining the relationship between flourishing and its domains with two suicide-related constructs of ISH and depressive disorder, as well as the alternative WHO reported age-standardised suicide mortality rates. The results included both unstandardised and standardised estimates to allow for comparability between disparate outcomes and subgroups on differing scales. All statistical analysis was performed in R (version 4.4.2). Results In the main age-adjusted analysis (Table 2) that excluded Turkey as an outlier, the flourishing index showed an inverse association with suicide mortality (B=-5.2; 95%CI[-8.9, -1.4]; p=0.0142). The two flourishing index domains most strongly associated with suicide mortality rates were meaning/purpose (B=-4.6; 95%CI[-7.3, -1.8]; p=0.0047) and close social relationships (B=-4.8; 95%CI[-8, -1.6]; p=0.0088) (Figure 1B–G), while there was little evidence of association between suicide mortality and the other domains. In the backwards stepwise regression analysis the flourishing index, meaning/purpose and close social relationships all similarly had significant associations with suicide mortality (Table 2, Supplementary Table 2). In the analyses that included Turkey, the high influence outlier country, the effect sizes were slightly muted both for the age-adjusted model (B=-3.1; 95%CI[-6.8, 0.8]; p=0.128) and the in stepwise regressions analysis (B=-3.8; 95%CI[-7.1, -0.4]; p=0.0405) (Supplementary Table 3, Supplementary Figure 1), though still with notable evidence of association in the latter. Analyses of the flourishing domains, with the Turkey outlier included, again suggested notable evidence for meaning/purpose B=-3.2; 95%CI[-6.1, -0.2]; p=0.048) and close social relationships B=-3.7; 95%CI[-7.1, -0.4]; p=0.042), in the age-adjusted analysis, with nearly identical estimates and p-values in the backwards stepwise regression; there was again less evidence for the other domains (Supplementary Table 3). Examining subgroups (Table 2, Figure 2), there was a negative association between flourishing and suicide mortality in females (B=-3.6; 95%CI[-5.8, -1.3]; p=0.0056); the effect size was larger for males but with a wider confidence interval (B=-6.2; 95%CI[-12.4, -0.1); p=0.0606]. When examined by age groups, the effect sizes were generally increasing with age and there was evidence of associations between the flourishing index and suicide mortality within the 50-69 (B = -7.7; 95%CI[-13.8, -1.6], p=0.0229) and 70+ age groups (B=-19.6; 95%CI[-33.7, -5.5]; p = 0.0139). These results were largely consistent with the stepwise regression analysis. In the age-adjusted analysis examining the effect of flourishing domains on subgroup suicide mortality (Supplementary Table 4) meaning/purpose had a significant association in every subgroup (male, female, 18 – 29, 30 – 49, 50 – 69) except the 70+ age group and close social relationships had a significant association in all subgroups except the 18 – 29 and 30 – 49 age groups. In the further supplementary analysis, high-influence outliers were identified as Japan and Indonesia for depressive disorders, Turkey for the ISH DALYs, Turkey and South Africa for WHO suicide mortality rates, and Turkey and Japan for the 2023 GBD estimates (Supplementary Table 1). The analysis excluding outliers found an association between the flourishing index and ISH DALYs (B=-228; 95%CI[-416.2, -39.9]; p=0.0288), but not depressive disorders prevalence (Supplementary Table 5). ISH DALYs and depressive disorders did show evidence of association with the domains of meaning and purpose (B=-193.9; 95%CI[-338.4, -49.4]; p=0.017 and B=-995.1; 95%CI[-1844, -146.1]; p = 0.0346 respectively) and close social relationships (B=-191.1; 95%CI[-358.5, -23.7]; p=0.0381 and B=-1287.3; 95%CI[-2355.9, -218.6], p=0.0304 respectively). In the age-adjusted analysis there were associations between the flourishing index (B = -5.3; 95%CI[-10.2, -0.5]; p = 0.0448), meaning/purpose (B = -5.1; 95%CI[-8.7, -1.5]; p = 0.0122) and close social relationships (B = -5.1; 95%CI[-9.2, -0.9]; p = 0.0284) with the WHO reported suicide mortality rates. For the preliminary GBD 2023 suicide statistics there were similar findings, albeit the association with close social relationships was not significant (Supplementary Table 5). Unlike the primary outcome, evidence for associations with the secondary outcomes did not persist in the analyses that included outliers (Supplementary Table 5). Discussion This is the first study to have found an association between the flourishing index and suicide mortality rate, with the strongest associations observed for the domains of meaning/purpose and close social relationships. When adjacent suicide-related constructs were considered, these two domains (but not other domains) were also consistently associated with the outcomes. A range of previous studies have demonstrated a relationship between both a sense of meaning/purpose [29] and close social relationships [30], with suicidal ideation, but illustrating this connection with completed suicide is challenging in longitudinal studies because of the rarity of suicide and the required sample size to detect such associations. The GFS, by using complex survey design to produce nationally representative estimates of flourishing and its domains, provides an opportunity to explore linkages with completed suicide mortality. Our findings corroborate previous large USA based longitudinal analyses including the Health Professionals Follow-up Study [31] (n=34 901, age range=40-75, follow up=24 years) and the Nurses Health Study [32] (n=72 607, age range=46-71, follow up=18 years) which found that high levels of social integration was associated with a 2 – 3 times lower risk of completed suicide in males and females. The limited prior evidence linking meaning/purpose or close social relationships with completed suicide has meant that such constructs are rarely considered in suicide prevention frameworks. This is perhaps surprising, given that meaning/purpose are thought to play a central role in addressing the 'existential vacuum' that can lead to vulnerabilities (e.g., hopelessness) that heighten risk of suicide [33] . When more people within a given population perceive their lives as meaningful or having purpose, fewer may be at risk of experiencing emptiness or despair that tend to precede suicidal thoughts and behaviors [34]. In their expert review, Tureki et al (2019) [35] outline a number of primary prevention strategies (e.g. restricting access to means, media strategies for better reporting, and suicide awareness campaigns), but none deal with considerations of population flourishing, sense of meaning, or social relationships. Similarly, the USA Health and Human Services (HHS) National Strategy for Suicide Prevention[36] nominates a range of strategies, with only a cursory mention of social relationships and no discussion of meaning or purpose. Both the quality and number of close social relationships in the USA were found to be declining in a 2023 US Surgeon General’s Report on the epidemic of loneliness, [37] and younger generations show lower trust of and involvement in institutions that have been previously associated with a sense of meaning and purpose (e.g. national civic institutions, religious organisations and family) [38]. Our study raises the possibility that both common measures of wellbeing (e.g. life satisfaction or happiness) and national frameworks may be missing factors that may be especially crucial to suicide prevention. While national levels of meaning/purpose and close relationships were understandably associated with suicide, it was surprising the other putatively important flourishing domains were not. These results should be considered with caution given that the sample size of 22 countries may lack the power to detect associations of a smaller effect size. However, consistent with a previous larger study [10] (n = 122 countries), we found that national-level self-rated happiness/life satisfaction was not associated with suicide rates. Previous studies have postulated that in nations where more value is placed on individual happiness and wellbeing [9], when an individual lacks such an sense of happiness life becomes relatively more intolerable, potentially “unliveable” and has a higher risk of suicide. Turkey was an statistical outlier with regard to suicide and Japan with regard to depression. The analyses including all countries had a smaller effect sizes. Pritchard et al . (2020) [25] has identified that Turkey has an anomalous low rate of suicide mortality and higher rates of accidental and undetermined cause of death, likely reflecting an underreporting due to cultural taboos and relatively under-developed mental health infrastructure. Similarly, rates of depressive disorder are known to be significantly underreported in Japan, due to factors including mental illness stigmatised as “weakness” and a preference for handling problems privately [39]. With more reliably collected and reported data and a greater number of countries the relationships between suicide and flourishing may be strengthened. Strengths and Limitations Strengths of this study include the use of large, representative data sources, sensitivity analyses, and multiple adjacent outcomes to corroborate findings. Limitations include restriction of the small sample to 22 countries, which limits generalisability, statistical power, and the ability to comprehensively adjust for covariates in analyses. There are a range of covariates that have not been included in the analysis, including universal healthcare coverage/access to mental health care, national rates of substance abuse and rates of religiosity. The analyses concern cross-sectional group-averaged associations and can be interpreted predictively, but not causally. The temporal sequence between the timing the 1–2-year difference in timing of estimation of exposures and outcomes limits the interpretation of directionality of effects. However, given the relative persistence of national suicide trends over such a short period [1], the associations are unlikely to be radically different with precisely contemporaneous data collection. The GBD data should also be understood with its limitations, with some national estimates of suicide modelled or adjusted heavily due to limited reporting or data in those countries (e.g. South Africa, India), potentially introducing measurement error. Conclusion In summary, this study found that the flourishing index was associated with suicide mortality and intentional self-harm, with the domains of meaning/purpose and relationships being the most strongly associated. Further research is needed examining the effect of flourishing longitudinally, at the level of the individual, and within the context of public health interventions. Declarations All participants provided informed consent to participate. Data availability All data used is available. The full dataset and example R code used are available as part of the Supplementary Materials. Acknowledgements We would like to acknowledge the work of all the Human Flourishing Study Team core teams at Baylor University, Gallup and Harvard University. Author contributions MJL was responsible for conceptualisation, data curation, formal analysis, investigation, methodology, project administration, validation, and writing the original draft. XS, AR, JS, PBM, CL, RC, and TJV were responsible for the development of the methodology and reviewing/editing iterations of the draft. Funding MJL was funded by the Higher Education Training Institute (HETI) NSW Special Training Award during the development of this research. The Global Flourishing Study was supported by funding from the John Templeton Foundation (grant no. 61665, T.J.V.), Templeton Religion Trust (no. 1308, T.J.V.), Templeton World Charity Foundation (no. 0605, T.J.V.), Well-Being for Planet Earth Foundation, Fetzer Institute (no. 4354, T.J.V.), Well Being Trust, Paul L. Foster Family Foundation and the David and Carol Myers Foundation. Declaration of interest TJV reports consulting fees from Gloo Inc., along with shared revenue received by Harvard University in its license agreement with Gloo according to the University IP policy. CL is on the Clinical Advisory Board for Douglas Pharmaceuticals and Sigmastim and has received fees for the following: Janssen Cilag advisory board, Medical Director of Neurostimulation and Interventional Psychiatry at Ramsay Health Care. PBM has received remuneration from Janssen (Australia) and Sanofi (Hangzhou) for lectures or advisory board membership within the past 3 years. All other authors declare no conflicts of interest. Analytic code availability Pre-registration of this project is available here https://osf.io/2wa4g. The data had been viewed prior to pre-registration of this exploratory analysis. Example R Code is available with this paper. Supplementary material Supplementary Material is available including Supplementary Methods, Supplementary Tables 1 – 5 and Supplementary Figures 1 and 2. References GBD 2021 Suicide Collaborators. Global, regional, and national burden of suicide, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet Public Heal. 2025;10:e189–e202. Turecki G, Brent DA. Suicide and suicidal behaviour. Lancet. 2016;387:1227–1239. Curtin SC, Warner M, Hedegaard H. Increase in Suicide in the United States, 1999-2014. NCHS Data Brief. 2016:1–8. 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Turecki G, Brent DA, Gunnell D, O’Connor RC, Oquendo MA, Pirkis J, et al. Suicide and suicide risk. Nat Rev Dis Prim. 2019;5:74. U.S. Department of Health and Human Services (HHS). National Strategy for Suicide Prevention. Washington, DC; 2024. Murthy VH. Our epidemic of loneliness and isolation: the U.S. surgeon general’s advisory on the healing effects of social connection and community. Off US Surg Gen. 2023:1–82. Pew Research Centre. Where Americans Find Meaning in Life. Reports. 2018. https://www.pewresearch.org/religion/2018/11/20/where-americans-find-meaning-in-life/. Accessed 27 July 2025. Kanehara A, Umeda M, Kawakami N. Barriers to mental health care in Japan: Results from the World Mental Health Japan Survey. Psychiatry Clin Neurosci. 2015;69:523–533. Tables Table 1: The underlying measures contributing to the flourishing index. Each response is rated from 1 – 10. The domains are computed taking the average of two questions and the flourishing index is computed taking the average of the 6 domains. Taken from VanderWeele et al (2025) - Each question or statement is evaluated 0–10. Anchors are Q1 (0, not satisfied at all,; 10, completely satisfied); Q2 (0, extremely unhappy; 10, extremely happy); Q3 and Q4 (0, poor; 10, excellent); Q5 (0, not at all worthwhile; 10, completely worthwhile); Q6, Q9 and Q10 (0, strongly disagree; 10, strongly agree); Q7 and Q8 (0, not true of me; 10, completely true of me); Q11 and Q12 (0, worry all of the time; 10, do not ever worry). Domain Question/statement D1. Happiness and life satisfaction Q1. Overall, how satisfied are you with life as a whole these days? D1. Happiness and life satisfaction Q2. In general, how happy or unhappy do you usually feel? D2. Mental and physical health Q3. In general, how would you rate your physical health? D2. Mental and physical health Q4. How would you rate your overall mental health? D3. Meaning and Purpose Q5. Overall, to what extent do you feel the things you do in your life are worthwhile? D3. Meaning and Purpose Q6. I understand my purpose in life. D4. Character and Virtue Q7. I always act to promote good in all circumstances, even in difficult and challenging situations. D4. Character and Virtue Q8. I am always able to give up some happiness now for greater happiness later. D5. Close social relationships Q9. I am content with my friendships and relationships. D5. Close social relationships Q10. My relationships are as satisfying as I would want them to be. D6. Financial/material stability Q11. How often do you worry about being able to meet normal monthly living expenses? D6. Financial/material stability Q12. How often do you worry about safety, food or housing? Table 2: Summary of generalised linear models examining the relationship between the flourishing index and suicide mortality rates using both a simple age-adjusted model and stepwise regression models in the total population and stratified by sex and age groups with the outlier country Turkey removed. Flourishing index and flourishing domains were accounted for complex sampling design using primary sampling units, strata and annual weights so that estimates were nationally representative. Stepwise backwards regression models considered covariates of national GDP per capita, average temperatures, average years of education, sociodemographic index (SDI), population density and numbers of guns owned per 100 persons as covariates. Details on included covariates for each analyses can be found in Supplementary Table 2. Age-adjusted model Stepwise model Group B (95%CI) Beta p-value B (95%CI) Beta p-value Flourishing Index, Total Population -5.2 (-8.9, -1.4) -0.61 0.0142* -4.6 (-7.8, -1.4) -0.55 0.0104* Flourishing Index, Subgroups Female -3.6 (-5.8, -1.3) -0.68 0.0056** -3.2 (-5.1, -1.4) -0.62 0.003** Male -6.2 (-12.4, -0.1) -0.48 0.0606 -4.4 (-9.8, 1.1) -0.34 0.1336 18 – 29 -3.7 (-7.3, -0.2) -0.54 0.0503 -3.3 (-6.5, -0.1) -0.47 0.0625 30 – 49 -5.1 (-10.1, -0.1) -0.46 0.0632 -5.5 (-9.6, -1.4) -0.5 0.0183* 50 – 69 -7.7 (-13.8, -1.6) -0.52 0.0229* -7.7 (-13.4, -2) -0.52 0.0152* 70+ -19.6 (-33.7, -5.5) -0.52 0.0139* -10.2 (-27.1, 6.6) -0.27 0.253 Flourishing domains, Total population Happiness/Life Satisfaction -2.2 (-5.6, 1.3) -0.28 0.2321 -1.9 (-5.2, 1.5) -0.24 0.2894 Physical and Mental Health -2.5 (-6.4, 1.4) -0.46 0.2297 -2.7 (-6, 0.7) -0.49 0.1356 Meaning/Purpose -4.6 (-7.3, -1.8) -0.78 0.0047** -4.3 (-6.8, -1.8) -0.73 0.004** Character/Virtue -3.1 (-6.4, 0.2) -0.53 0.0788 -2.4 (-4.9, 0) -0.41 0.0634 Close social relationships -4.8 (-8, -1.6) -0.73 0.0088** -4 (-6.9, -1) -0.6 0.0173* Financial/Material Stability -0.4 (-2.1, 1.3) -0.12 0.6232 -1.1 (-3, 0.9) -0.31 0.2943 p<0.05* p<0.01** Additional Declarations Competing interest reported. TJV reports consulting fees from Gloo Inc., along with shared revenue received by Harvard University in its license agreement with Gloo according to the University IP policy. CL is on the Clinical Advisory Board for Douglas Pharmaceuticals and Sigmastim and has received fees for the following: Janssen Cilag advisory board, Medical Director of Neurostimulation and Interventional Psychiatry at Ramsay Health Care. PBM has received remuneration from Janssen (Australia) and Sanofi (Hangzhou) for lectures or advisory board membership within the past 3 years. All other authors declare no conflicts of interest. Supplementary Files GlobalFlourishingStudyandSuicideRatesSupplementaryMaterialv6.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 13 May, 2026 Reviews received at journal 08 May, 2026 Reviews received at journal 04 May, 2026 Reviewers agreed at journal 20 Apr, 2026 Reviewers agreed at journal 20 Apr, 2026 Reviewers agreed at journal 19 Apr, 2026 Reviewers agreed at journal 17 Apr, 2026 Reviewers invited by journal 17 Apr, 2026 Editor assigned by journal 03 Feb, 2026 Submission checks completed at journal 03 Jan, 2026 First submitted to journal 31 Dec, 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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06:36:10","extension":"html","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":81044,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8487304/v1/ed6c5b6188cefe9afb95ed76.html"},{"id":100357616,"identity":"ac15a074-d9cd-411c-81ad-c46219bb324a","added_by":"auto","created_at":"2026-01-16 07:20:06","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":328347,"visible":true,"origin":"","legend":"\u003cp\u003eSuicide mortality rate per 100,000 (y-axis) and flourishing index (x-axis) (1A) and the 6 flourishing domains (B – G). The blue line indicates the locally weighted polynomial that estimates the shape of the relationship. The red line indicates the predicted linear relationship between flourishing and suicide. The above graphs exclude the high influence outlier Turkey.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8487304/v1/348fe38992215965aaf5fbb8.jpeg"},{"id":100357543,"identity":"8cac58b5-84bb-4410-9f32-629323d13e15","added_by":"auto","created_at":"2026-01-16 07:20:01","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":596737,"visible":true,"origin":"","legend":"\u003cp\u003eSuicide mortality rate per 100,000 (y-axis) and flourishing index (x-axis) and the subgroups. A – Female; B – Male; C – 18-29; D - 30 – 49; E - 50 – 69; F - 70+. The blue line indicates the locally weighted polynomial that estimates the shape of the relationship. The red line indicates the predicted linear relationship between flourishing and suicide. The above graphs exclude the high-influence outlier Turkey.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8487304/v1/474cd5ce1defb560f6b75400.jpeg"},{"id":100376844,"identity":"20117750-835b-42be-8dcd-7d9edda47d65","added_by":"auto","created_at":"2026-01-16 08:46:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1785278,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8487304/v1/537ef05b-19de-4e13-afd6-b1324d7016f3.pdf"},{"id":99858865,"identity":"4b262238-1c9f-4bb1-ba96-dbc5d9ab2d01","added_by":"auto","created_at":"2026-01-09 06:36:10","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":674084,"visible":true,"origin":"","legend":"","description":"","filename":"GlobalFlourishingStudyandSuicideRatesSupplementaryMaterialv6.docx","url":"https://assets-eu.researchsquare.com/files/rs-8487304/v1/a62b58feff872dadc38fdab6.docx"}],"financialInterests":"Competing interest reported. TJV reports consulting fees from Gloo Inc., along with shared revenue received by Harvard University in its license agreement with Gloo according to the University IP policy.\n\nCL is on the Clinical Advisory Board for Douglas Pharmaceuticals and Sigmastim and has received fees for the following: Janssen Cilag advisory board, Medical Director of Neurostimulation and Interventional Psychiatry at Ramsay Health Care.\n\nPBM has received remuneration from Janssen (Australia) and Sanofi (Hangzhou) for lectures or advisory board membership within the past 3 years.\n\nAll other authors declare no conflicts of interest.","formattedTitle":"Human flourishing and suicide: A national-level analysis with 22 countries","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn 2021, approximately 746,000 people worldwide died by suicide, [1] with suicide being the third leading cause of death among young adults and adolescents. Suicide mortality rates vary significantly by country, with particularly high rates observed in some regions such as Eastern Europe and Asia [2]. Recent decades have seen alarming suicide rate increase in countries such as the United States, South Korea, and India, and many of the fundamental drivers of these increases remain unclear [3,4].\u003c/p\u003e\n\u003cp\u003eThere are a panoply of known risk factors for suicide mortality rates at a national level. Economic factors such as unemployment and economic downturns consistently correlate with increased suicide rates, reflecting the profound psychological and social impacts of real-world financial instability [5]. Substance abuse also frequently emerges as a major risk factor, exacerbating mental health challenges and increasing impulsivity and vulnerability [2]. Religious belief and practice on the other hand may be protective factors for suicide risk through mechanisms of social cohesion, moral frameworks, and community support; however, these patterns vary widely by cultural context [6\u0026ndash;8]. Particularly interesting is the relationship between rates of happiness in a community and suicide. Some studies suggest that nations with higher rates of happiness may also have higher rates of suicide [9], while others indicate that there may be no relationship at all between the two measures [10] or that the relationship may be largely explained by differences in human development indices. Despite the known, established risk factors, a significant amount of variability in suicide rates remains unexplained by current models [11]. This inadequacy in predictive capability poses serious challenges to public health interventions, potentially explaining why well-intentioned suicide prevention interventions and frameworks, may be followed by increased rates of suicide despite greater suicide awareness and support programs.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHuman flourishing as an explanatory factor\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere is a need for better explanatory models incorporating cultural dimensions and broader measures of wellbeing beyond self-reported personal happiness. The Global Flourishing Study, introduced by VanderWeele et al.[12], offers a novel multinational opportunity, with nationally representative sampling, to assess and monitor \u0026nbsp; individual flourishing across six domains: happiness/life satisfaction, physical/mental health, meaning/purpose, character/virtue, close social relationships, and financial/material stability. These domains collectively provide a richer, multidimensional understanding of human wellbeing, potentially capturing crucial elements influencing suicide risk that more unidimensional measures of wellbeing may lack. In this study, we use nationally representative data from the Global Flourishing Study (GFS) and the Global Burden of Disease (GBD) Study to examine the relationship between national average scores on the flourishing index, national suicide rates and the suicide-related constructs of intentional self-harm and depressive disorders.\u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003ePrimary and secondary predictors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFlourishing index data were taken from Wave 1 of the GFS, which was collected between April 2022 and December 2023, [12,13] including 22 countries and over 200,000 participants. The participating countries were Argentina, Australia, Brazil, China (Hong Kong), Egypt, Germany, India, Indonesia, Israel, Japan, Kenya, Mexico, Nigeria, the Philippines, Poland, South Africa, Spain, Sweden, Tanzania, Turkey, the United Kingdom, and the United States. These countries represent a diverse global perspective, allowing the flourishing index and its domains to be analysed across varied cultural, economic, and demographic contexts. Nationally representative surveys were conducted to generate estimates of the primary predictor, the flourishing index, and the secondary predictors, the 6 flourishing index domains (happiness/life satisfaction, mental/physical health, meaning/purpose, character/virtue, close social relationships, and financial/material stability) (See table 1 for the 12 items comprising the flourishing index).\u003c/p\u003e\n\u003cp\u003eThe GFS collected data using Gallup polling methodologies to ensure approximately nationally representative samples [13]. The description of sampling methods and study design can be found in the methodology report [14] and the survey development report [15] by Gallup Inc. as well as the previous publications by the GFS research team [13,16] . These papers explain in detail the processes of survey development, survey translation, interviewer training, sampling design and collection, the use of probability and non-probability-based samples, post-data collection quality evaluation and the weighting and design effects.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMissing data\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFollowing the standardised analytic methodology [17] of the GFS, missing flourishing domain data was imputed using multiple imputation by chained equations [18] in the R package \u003cem\u003emice\u003c/em\u003e. Imputations were performed separately for each nation, with 5 imputed datasets being formed. This within-country approach allowed the imputation to appropriately capture country-specific contexts and assessment methods. Sampling weights were included in the imputation model to adjust for the specific-variable missingness that could be linked to the likelihood of study inclusion. The rate of missing data needing to be imputed was very low, varying from 0.32 to 0.73% across the 6 flourishing domains. Further details of the multiple imputation approach and example code can be found in the references [17,19].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAccounting for complex sampling design\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe GFS applied disparate sampling methodologies between countries based on recruitment needs and participant availability [14]. All estimates of national-level flourishing and its domains accounted for this complex survey design, using the R package \u003cem\u003esurvey\u0026nbsp;\u003c/em\u003e[20]\u003cem\u003e,\u0026nbsp;\u003c/em\u003e by applying individual weights, primary sampling units (PSUs) and strata. More detail on the methodology of the GFS has been provided in previous papers [13,14].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrimary and secondary outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSuicide rates and secondary outcome data are sourced from the Global Burden of Diseases (GBD) Study 2021. The GBD study [21] calculates national age-standardised suicide mortality rates (suicide mortality), our primary outcome, by integrating multiple data sources, including vital registration systems, surveys, and health facility records, using advanced modelling techniques to adjust for potential biases and underreporting [1]. However, the GBD study has been criticised for its possible overreliance on modelled data for regions with low quality reporting, potentially distorting real-world data [1,21]. To evaluate the robustness of results to a different data sources, a separate source of national age-standardised suicide mortality rates was taken from the World Health Organisation 2021 Global Health Estimates Report [22] (Supplementary Methods). At the time of writing the fully developed research paper on GBD 2023 [23] Suicide Mortality and subgroups have not been developed however some results are publicly available and were similarly tested to examine for the robustness of the results [24].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe primary outcome was the national age-standardised suicide mortality rate. Suicide mortality data, particularly in some jurisdictions, is known to be inaccurately reported [25] in part due to religious and cultural taboos around suicide. As such, this study included two suicide-related secondary outcomes, also from the GBD 2021 Study, that may be more reliably reported than suicide. Intentional self-harm (ISH) [26] is an indicator of psychological distress and emotional dysregulation, is a predictor of suicide and may overlap with suicide mortality. However, ISH, has a distinct risk factor profile when compared to completed suicide, most notably that it is 2-3 times more prevalent in women, whereas completed suicide is 2-3 times more common in men [26]. \u0026nbsp;National age-adjusted ISH disability-adjusted life years (DALYs) was used as a measure of the burden of disease. Depressive disorders prevalence [27], which includes ICD-10 codes for both Major Depressive Disorder (MDD) and Dysthymia, are orders of magnitude more common than suicide and are associated with suicide mortality. Similar to ISH, depressive disorders have a distinctive risk factor profile and is more common in women [28].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study involves analysis of publicly available data; thus, specific ethical approval for this analysis is not required. The Global Flourishing Study received prior ethical approval to collect and disseminate de-identified data from participating countries from the Institutional Review Boards of Gallup (IRB Reference #: 2021-11-02) and Baylor University (IRB Reference #: 1841317). \u003cem\u003eThe authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2013.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEach of the 22 countries served as an individual datapoint in the analyses. High influence outliers were identified for each outcome using a Cook\u0026rsquo;s D threshold of 4/22 (0.1818) (See Supplementary Methods and Supplementary Table 1). Models were run excluding and including high influence outlier countries.\u003c/p\u003e\n\u003cp\u003eMedian age within each country was included as the main covariate, as study primary and secondary outcomes have been shown to vary across the age range. This simple age-adjusted analysis was the main analysis. As an additional set of analyses, covariates used in the GBD 2021 suicide mortality study [1] were included in stepwise regression models. These covariates included years of education, gross domestic product (GDP) per capita, sociodemographic index (SDI), population density, mean annual temperature, and numbers of firearms per capita (see Supplementary Methods for covariate sources and descriptions). Given the limited data availability (i.e. up to 21 degrees of freedom) models needed to be parsimonious and optimised for fit without discarding important covariates. Model optimization utilized Akaike Information Criterion (AIC) to select the most relevant covariates, refining model accuracy and efficiency, using a backwards-stepwise approach (Supplementary Table 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGeneralized linear models (GLMs) were used to investigate the relationships between predictors and outcomes. The primary analysis included the flourishing index as the main predictor, while secondary analyses assessed flourishing index domains. Supplementary analyses were performed examining if relationships remained consistent in analyses stratified by sex and distinct age groups (18\u0026ndash;29, 30\u0026ndash;49, 50\u0026ndash;69, and 70+). A further supplementary analysis was performed repeating the main analysis, examining the relationship between flourishing and its domains with two suicide-related constructs of ISH and depressive disorder, as well as the alternative WHO reported age-standardised suicide mortality rates. The results included both unstandardised and standardised estimates to allow for comparability between disparate outcomes and subgroups on differing scales. All statistical analysis was performed in R (version 4.4.2).\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eIn the main age-adjusted analysis (Table 2) that excluded Turkey as an outlier, the flourishing index showed an inverse association with suicide mortality (B=-5.2; 95%CI[-8.9, -1.4]; p=0.0142). The two flourishing index domains most strongly associated with suicide mortality rates were meaning/purpose (B=-4.6; 95%CI[-7.3, -1.8]; p=0.0047) and close social relationships (B=-4.8; 95%CI[-8, -1.6]; p=0.0088) (Figure 1B\u0026ndash;G), while there was little evidence of association between suicide mortality and the other domains. In the backwards stepwise regression analysis the flourishing index, meaning/purpose and close social relationships all similarly had significant associations with suicide mortality (Table 2, Supplementary Table 2).\u003c/p\u003e\n\u003cp\u003eIn the analyses that included Turkey, the high influence outlier country, the effect sizes were slightly muted both for the age-adjusted model (B=-3.1; 95%CI[-6.8, 0.8]; p=0.128) and the in stepwise regressions analysis (B=-3.8; \u0026nbsp; 95%CI[-7.1, -0.4]; p=0.0405) (Supplementary Table 3, Supplementary Figure 1), though still with notable evidence of association in the latter. Analyses of the flourishing domains, with the Turkey outlier included, again suggested notable evidence for meaning/purpose B=-3.2; 95%CI[-6.1, -0.2]; p=0.048) and close social relationships B=-3.7; 95%CI[-7.1, -0.4]; p=0.042), in the age-adjusted analysis, with nearly identical estimates and p-values in the backwards stepwise regression; there was again less evidence for the other domains (Supplementary Table 3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eExamining subgroups (Table 2, Figure 2), there was a negative association between flourishing and suicide mortality in females (B=-3.6; 95%CI[-5.8, -1.3]; p=0.0056); the effect size was larger for males but with a wider confidence interval (B=-6.2; 95%CI[-12.4, -0.1); p=0.0606]. When examined by age groups, the effect sizes were generally increasing with age and there was evidence of associations between the flourishing index and suicide mortality within the 50-69 (B\u003cstrong\u003e=\u003c/strong\u003e-7.7; 95%CI[-13.8, -1.6], p=0.0229) and 70+ age groups (B=-19.6; 95%CI[-33.7, -5.5]; p = 0.0139). These results were largely consistent with the stepwise regression analysis. In the age-adjusted analysis examining the effect of flourishing domains on subgroup suicide mortality (Supplementary Table 4) meaning/purpose had a significant association in every subgroup (male, female, 18 \u0026ndash; 29, 30 \u0026ndash; 49, 50 \u0026ndash; 69) except the 70+ age group and close social relationships had a significant association in all subgroups except the 18 \u0026ndash; 29 and 30 \u0026ndash; 49 age groups.\u003c/p\u003e\n\u003cp\u003eIn the further supplementary analysis, high-influence outliers were identified as Japan and Indonesia for depressive disorders, Turkey for the ISH DALYs, Turkey and South Africa for WHO suicide mortality rates, and Turkey and Japan for the 2023 GBD estimates (Supplementary Table 1). The analysis excluding outliers found an association between the flourishing index and ISH DALYs (B=-228; 95%CI[-416.2, -39.9]; p=0.0288), but not depressive disorders prevalence (Supplementary Table 5). ISH DALYs and depressive disorders did show evidence of association with the domains of meaning and purpose (B=-193.9; 95%CI[-338.4, -49.4]; p=0.017 and B=-995.1; 95%CI[-1844, -146.1]; p = 0.0346 respectively) and close social relationships (B=-191.1; 95%CI[-358.5, -23.7]; p=0.0381 and B=-1287.3; 95%CI[-2355.9, -218.6], p=0.0304 respectively). In the age-adjusted analysis there were associations between the flourishing index (B = -5.3; 95%CI[-10.2, -0.5]; \u0026nbsp;p = 0.0448), meaning/purpose (B = -5.1; 95%CI[-8.7, -1.5]; p = 0.0122) and close social relationships (B = -5.1; 95%CI[-9.2, -0.9]; p = 0.0284) with the WHO reported suicide mortality rates. For the preliminary GBD 2023 suicide statistics there were similar findings, albeit the association with close social relationships was not significant (Supplementary Table 5). Unlike the primary outcome, evidence for associations with the secondary outcomes did not persist in the analyses that included outliers (Supplementary Table 5).\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis is the first study to have found an association between the flourishing index and suicide mortality rate, with the strongest associations observed for the domains of meaning/purpose and close social relationships. When adjacent suicide-related constructs were considered, these two domains (but not other domains) were also consistently associated with the outcomes. A range of previous studies have demonstrated a relationship between both a sense of meaning/purpose [29] and close social relationships [30], with suicidal ideation, but illustrating this connection with completed suicide is challenging in longitudinal studies because of the rarity of suicide and the required sample size to detect such associations. The GFS, by using complex survey design to produce nationally representative estimates of flourishing and its domains, provides an opportunity to explore linkages with completed suicide mortality. Our findings corroborate previous large USA based longitudinal analyses including the Health Professionals Follow-up Study [31] (n=34 901, age range=40-75, follow up=24 years) and the Nurses Health Study [32] (n=72 607, age range=46-71, follow up=18 years) which found that high levels of social integration was associated with a 2 \u0026ndash; 3 times lower risk of completed suicide in males and females.\u003c/p\u003e\n\u003cp\u003eThe limited prior evidence linking meaning/purpose or close social relationships with completed suicide has meant that such constructs are rarely considered in suicide prevention frameworks. This is perhaps surprising, given that meaning/purpose are thought to play a central role in addressing the \u0026apos;existential vacuum\u0026apos; that can lead to vulnerabilities (e.g., hopelessness) that heighten risk of suicide [33] . When more people within a given population perceive their lives as meaningful or having purpose, fewer may be at risk of experiencing emptiness or despair that tend to precede suicidal thoughts and behaviors [34]. In their expert review, Tureki et al (2019) [35] outline a number of primary prevention strategies (e.g. restricting access to means, media strategies for better reporting, and suicide awareness campaigns), but none deal with considerations of population flourishing, sense of meaning, or social relationships. Similarly, the USA Health and Human Services (HHS) National Strategy for Suicide Prevention[36]\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003enominates a range of strategies, with only a cursory mention of social relationships and no discussion of meaning or purpose. Both the quality and number of close social relationships in the USA were found to be declining in a 2023 US Surgeon General\u0026rsquo;s Report on the epidemic of loneliness, [37] and younger generations show lower trust of and involvement in institutions that have been previously associated with a sense of meaning and purpose (e.g. national civic institutions, religious organisations and family) [38]. Our study raises the possibility that both common measures of wellbeing (e.g. life satisfaction or happiness) and national frameworks may be missing factors that may be especially crucial to suicide prevention.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhile national levels of meaning/purpose and close relationships were understandably associated with suicide, it was surprising the other putatively important flourishing domains were not. These results should be considered with caution given that the sample size of 22 countries may lack the power to detect associations of a smaller effect size. However, consistent with a previous larger study [10] (n = 122 countries), we found that national-level self-rated happiness/life satisfaction was not associated with suicide rates. Previous studies have postulated that in nations where more value is placed on individual happiness and wellbeing [9], when an individual lacks such an sense of happiness life becomes relatively more intolerable, potentially \u0026ldquo;unliveable\u0026rdquo; and has a higher risk of suicide.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTurkey was an statistical outlier with regard to suicide and Japan with regard to depression. The analyses including all countries had a smaller effect sizes. Pritchard \u003cem\u003eet al\u003c/em\u003e. (2020) [25] has identified that Turkey has an anomalous low rate of suicide mortality and higher rates of accidental and undetermined cause of death, likely reflecting an underreporting due to cultural taboos and relatively under-developed mental health infrastructure. \u0026nbsp;Similarly, rates of depressive disorder are known to be significantly underreported in Japan, due to factors including mental illness stigmatised as \u0026ldquo;weakness\u0026rdquo; and a preference for handling problems privately [39]. With more reliably collected and reported data and a greater number of countries the relationships between suicide and flourishing may be strengthened.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStrengths and Limitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStrengths of this study include the use of large, representative data sources, sensitivity analyses, and multiple adjacent outcomes to corroborate findings. Limitations include restriction of the small sample to 22 countries, which limits generalisability, statistical power, and the ability to comprehensively adjust for covariates in analyses. There are a range of covariates that have not been included in the analysis, including universal healthcare coverage/access to mental health care, national rates of substance abuse and rates of religiosity. The analyses concern cross-sectional group-averaged associations and can be interpreted predictively, but not causally. The temporal sequence between the timing the 1\u0026ndash;2-year difference in timing of estimation of exposures and outcomes limits the interpretation of directionality of effects. However, given the relative persistence of national suicide trends over such a short period [1], the associations are unlikely to be radically different with precisely contemporaneous data collection. The GBD data should also be understood with its limitations, with some national estimates of suicide modelled or adjusted heavily due to limited reporting or data in those countries (e.g. South Africa, India), potentially introducing measurement error.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, this study found that the flourishing index was associated with suicide mortality and intentional self-harm, with the domains of meaning/purpose and relationships being the most strongly associated. Further research is needed examining the effect of flourishing longitudinally, at the level of the individual, and within the context of public health interventions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cspan\u003eAll participants provided informed consent to participate.\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data used is available. The full dataset and example R code used are available as part of the Supplementary Materials.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to acknowledge the work of all the Human Flourishing Study Team core teams at Baylor University, Gallup and Harvard University.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMJL was responsible for conceptualisation, data curation, formal analysis, investigation, methodology, project administration, validation, and writing the original draft.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eXS, AR, JS, PBM, CL, RC, and TJV were responsible for the development of the methodology and reviewing/editing iterations of the draft.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMJL was funded by the Higher Education Training Institute (HETI) NSW Special Training Award during the development of this research. The Global Flourishing Study was supported by funding from the John Templeton Foundation (grant no. 61665, T.J.V.), Templeton Religion Trust (no. 1308, T.J.V.), Templeton World Charity Foundation (no. 0605, T.J.V.), Well-Being for Planet Earth Foundation, Fetzer Institute (no. 4354, T.J.V.), Well Being Trust, Paul L. Foster Family Foundation and the David and Carol Myers Foundation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTJV reports consulting fees from Gloo Inc., along with shared revenue received by Harvard University in its license agreement with Gloo according to the University IP policy.\u003c/p\u003e\n\u003cp\u003eCL is on the Clinical Advisory Board for Douglas Pharmaceuticals and Sigmastim and has received fees for the following: Janssen Cilag advisory board, Medical Director of Neurostimulation and Interventional Psychiatry at Ramsay Health Care.\u003c/p\u003e\n\u003cp\u003ePBM has received remuneration from Janssen (Australia) and Sanofi (Hangzhou) for lectures or advisory board membership within the past 3 years.\u003c/p\u003e\n\u003cp\u003eAll other authors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalytic code availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePre-registration of this project is available here https://osf.io/2wa4g. The data had been viewed prior to pre-registration of this exploratory analysis. Example R Code is available with this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSupplementary Material is available including Supplementary Methods, Supplementary Tables 1 \u0026ndash; 5 and Supplementary Figures 1 and 2.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGBD 2021 Suicide Collaborators. Global, regional, and national burden of suicide, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet Public Heal. 2025;10:e189\u0026ndash;e202.\u003c/li\u003e\n\u003cli\u003eTurecki G, Brent DA. Suicide and suicidal behaviour. Lancet. 2016;387:1227\u0026ndash;1239.\u003c/li\u003e\n\u003cli\u003eCurtin SC, Warner M, Hedegaard H. Increase in Suicide in the United States, 1999-2014. NCHS Data Brief. 2016:1\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eRadhakrishnan R, Andrade C. Suicide: An Indian perspective. Indian J Psychiatry. 2012;54:304\u0026ndash;319.\u003c/li\u003e\n\u003cli\u003eChang S-S, Stuckler D, Yip P, Gunnell D. Impact of 2008 global economic crisis on suicide: time trend study in 54 countries. BMJ Br Med J. 2013;347:f5239.\u003c/li\u003e\n\u003cli\u003eLawrence RE, Oquendo MA, Stanley B. Religion and Suicide Risk: A Systematic Review. Arch Suicide Res Off J Int Acad Suicide Res. 2016;20:1\u0026ndash;21.\u003c/li\u003e\n\u003cli\u003eVanderWeele TJ, Li S, Tsai AC, Kawachi I. Association Between Religious Service Attendance and Lower Suicide Rates Among US Women. JAMA Psychiatry. 2016;73:845\u0026ndash;851.\u003c/li\u003e\n\u003cli\u003eRosmarin DH, Koenig HG. Handbook of spirituality, religion, and mental health. 2nd ed. Cambridge, MA, US: Academic Press; 2020.\u003c/li\u003e\n\u003cli\u003eDaly MC, Oswald AJ, Wilson D, Wu S. Dark contrasts: The paradox of high rates of suicide in happy places. J Econ Behav Organ. 2011;80:435\u0026ndash;442.\u003c/li\u003e\n\u003cli\u003eHsu C-Y, Chang S-S, Gunnell D. Suicide and Happiness: The Association Between Two Potential Sustainable Development Goal Indicators for Mental Health. J Clin Psychiatry. 2020;81.\u003c/li\u003e\n\u003cli\u003eFranklin JC, Ribeiro JD, Fox KR, Bentley KH, Kleiman EM, Huang X, et al. Risk factors for suicidal thoughts and behaviors: A meta-analysis of 50 years of research. Psychol Bull. 2017;143:187\u0026ndash;232.\u003c/li\u003e\n\u003cli\u003eVanderWeele TJ, Johnson BR, Bialowolski PT, Bonhag R, Bradshaw M, Breedlove T, et al. The Global Flourishing Study: Study Profile and Initial Results on Flourishing. Nat Ment Heal. 2025;3:636\u0026ndash;653.\u003c/li\u003e\n\u003cli\u003ePadgett RN, Cowden RG, Chattopadhyay M, Han Y, Honohan J, Ritter Z, et al. Survey sampling design in wave 1 of the Global Flourishing Study. Eur J Epidemiol. 2025;40:391\u0026ndash;406.\u003c/li\u003e\n\u003cli\u003eRitter Z, Srinivasan R, Han Y, Chattopadhyay M, Honohan J, Johnson B, et al. Global Flourishing Study methodology. Gall Inc. 2024. https://osf.io/k2s7u. Accessed 11 August 2025.\u003c/li\u003e\n\u003cli\u003eCrabtree S, English C, Johnson B, Ritter Z, VanderWeele T. Global Flourishing Study: Questionnaire Development report. Gall Inc. 2021. https://osf.io/y3t6m. Accessed 11 August 2025.\u003c/li\u003e\n\u003cli\u003eLomas T, Bradshaw M, Case B, Cowden RG, Crabtree S, English C, et al. The development of the Global Flourishing Study questionnaire: charting the evolution of a new 109-item inventory of human flourishing. BMC Glob Public Heal. 2025;3:30.\u003c/li\u003e\n\u003cli\u003ePadgett RN, Bradshaw M, Chen Y, Cowden RG, Jang SJ, Kim ES, et al. Analytic methodology for childhood predictor analyses for wave 1 of the Global Flourishing Study. BMC Glob Public Heal. 2025;3:29.\u003c/li\u003e\n\u003cli\u003eSterne JAC, White IR, Carlin JB, Spratt M, Royston P, Kenward MG, et al. Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. BMJ. 2009;338:b2393.\u003c/li\u003e\n\u003cli\u003ePadgett RN, Bradshaw M, Chen Y, Jang SJ, Shiba K, Johnson BR, et al. Global Flourishing Study Wave 1 Statistical Analyses Code. OSF. 2024.\u003c/li\u003e\n\u003cli\u003eLumley T. Analysis of complex survey samples. J Stat Softw. 2004;9:1\u0026ndash;19.\u003c/li\u003e\n\u003cli\u003eGBD 2021 Causes of Death Collaborators. Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet (London, England). 2024;403:2100\u0026ndash;2132.\u003c/li\u003e\n\u003cli\u003eWorld Health Organisation (WHO). Suicide worldwide in 2021: Global Health Estimates. Glob Heal Estim. 2025. https://apps.who.int/iris/rest/bitstreams/1350975/retrieve%0Ahttps://www.who.int/publications-detail-redirect/9789240026643. Accessed 11 August 2025.\u003c/li\u003e\n\u003cli\u003eHay SI, Ong KL, Santomauro DF, A B, Aalipour MA, Aalruz H, et al. Burden of 375 diseases and injuries, risk-attributable burden of 88 risk factors, and healthy life expectancy in 204 countries and territories, including 660 subnational locations, 1990 - 2023: a systematic analysis for the Global Burden of Disease Study . Lancet. 2025;406:1873\u0026ndash;1922.\u003c/li\u003e\n\u003cli\u003eGlobal Burden of Disease Collaborative Network. Global Burden of Disease Study 2023 (GBD 2023) Results. Inst Heal Metrics Eval. 2025. https://vizhub.healthdata.org/gbd-results/. Accessed 18 December 2025.\u003c/li\u003e\n\u003cli\u003ePritchard C, Iqbal W, Dray R. Undetermined and accidental mortality rates as possible sources of underreported suicides: population-based study comparing Islamic countries and traditionally religious Western countries. BJPsych Open. 2020;6:e56.\u003c/li\u003e\n\u003cli\u003eXie L, Tang L, Liu Y, Dong Z. Global burden and trends of self-harm from 1990 to 2021, with predictions to 2050. Front Public Heal. 2025:1\u0026ndash;12.\u003c/li\u003e\n\u003cli\u003eRong J, Wang X, Cheng P, Li D, Zhao D. Global, regional and national burden of depressive disorders and attributable risk factors, from 1990 to 2021: results from the 2021 Global Burden of Disease study. Br J Psychiatry. 2025:1\u0026ndash;10.\u003c/li\u003e\n\u003cli\u003eChen X-D, Li F, Zuo H, Zhu F. Trends in Prevalent Cases and Disability-Adjusted Life-Years of Depressive Disorders Worldwide: Findings From the Global Burden of Disease Study From 1990 to 2021. Depress Anxiety. 2025;2025:5553491.\u003c/li\u003e\n\u003cli\u003eLi S, Luo H, Huang F, Wang Y, Siu Fai Yip P. Associations between meaning in life and suicidal ideation in young people: A systematic review and meta-analysis. Child Youth Serv Rev. 2024;158:107477.\u003c/li\u003e\n\u003cli\u003eMotillon-Toudic C, Walter M, S\u0026eacute;guin M, Carrier J-D, Berrouiguet S, Lemey C. Social isolation and suicide risk: Literature review and perspectives. Eur Psychiatry. 2022;65:e65.\u003c/li\u003e\n\u003cli\u003eTsai AC, Lucas M, Sania A, Kim D, Kawachi I. Social integration and suicide mortality among men: 24-year cohort study of U.S. health professionals. Ann Intern Med. 2014;161:85\u0026ndash;95.\u003c/li\u003e\n\u003cli\u003eTsai AC, Lucas M, Kawachi I. Association Between Social Integration and Suicide Among Women in the United States. JAMA Psychiatry. 2015;72:987\u0026ndash;993.\u003c/li\u003e\n\u003cli\u003eFrankl VE. Man\u0026rsquo;s search for meaning: An introduction to logotherapy, 4th ed. Man\u0026rsquo;s Search Mean An Introd to Logother 4th Ed. 1992:196.\u003c/li\u003e\n\u003cli\u003eKleiman EM, Beaver JK. A meaningful life is worth living: Meaning in life as a suicide resiliency factor. Psychiatry Res. 2013;210:934\u0026ndash;939.\u003c/li\u003e\n\u003cli\u003eTurecki G, Brent DA, Gunnell D, O\u0026rsquo;Connor RC, Oquendo MA, Pirkis J, et al. Suicide and suicide risk. Nat Rev Dis Prim. 2019;5:74.\u003c/li\u003e\n\u003cli\u003eU.S. Department of Health and Human Services (HHS). National Strategy for Suicide Prevention. Washington, DC; 2024.\u003c/li\u003e\n\u003cli\u003eMurthy VH. Our epidemic of loneliness and isolation: the U.S. surgeon general\u0026rsquo;s advisory on the healing effects of social connection and community. Off US Surg Gen. 2023:1\u0026ndash;82.\u003c/li\u003e\n\u003cli\u003ePew Research Centre. Where Americans Find Meaning in Life. Reports. 2018. https://www.pewresearch.org/religion/2018/11/20/where-americans-find-meaning-in-life/. Accessed 27 July 2025.\u003c/li\u003e\n\u003cli\u003eKanehara A, Umeda M, Kawakami N. Barriers to mental health care in Japan: Results from the World Mental Health Japan Survey. Psychiatry Clin Neurosci. 2015;69:523\u0026ndash;533.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1:\u003c/strong\u003e The underlying measures contributing to the flourishing index. Each response is rated from 1 \u0026ndash; 10. The domains are computed taking the average of two questions and the flourishing index is computed taking the average of the 6 domains. Taken from VanderWeele et al (2025) - Each question or statement is evaluated 0\u0026ndash;10. Anchors are Q1 (0, not satisfied at all,; 10, completely satisfied); Q2 (0, extremely unhappy; 10, extremely happy); Q3 and Q4 (0, poor; 10, excellent); Q5 (0, not at all worthwhile; 10, completely worthwhile); Q6, Q9 and Q10 (0, strongly disagree; 10, strongly agree); Q7 and Q8 (0, not true of me; 10, completely true of me); Q11 and Q12 (0, worry all of the time; 10, do not ever worry).\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"558\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDomain\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 412px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuestion/statement\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eD1. Happiness and life satisfaction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 412px;\"\u003e\n \u003cp\u003eQ1. Overall, how satisfied are you with life as a whole these days?\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eD1. Happiness and life satisfaction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 412px;\"\u003e\n \u003cp\u003eQ2. In general, how happy or unhappy do you usually feel?\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eD2. Mental and physical health\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 412px;\"\u003e\n \u003cp\u003eQ3. In general, how would you rate your physical health?\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eD2. Mental and physical health\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 412px;\"\u003e\n \u003cp\u003eQ4. How would you rate your overall mental health?\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eD3. Meaning and Purpose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 412px;\"\u003e\n \u003cp\u003eQ5. Overall, to what extent do you feel the things you do in your life are worthwhile?\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eD3. Meaning and Purpose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 412px;\"\u003e\n \u003cp\u003eQ6. I understand my purpose in life.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eD4. Character and Virtue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 412px;\"\u003e\n \u003cp\u003eQ7. I always act to promote good in all circumstances, even in difficult and challenging situations.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eD4. Character and Virtue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 412px;\"\u003e\n \u003cp\u003eQ8. I am always able to give up some happiness now for greater happiness later.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eD5. Close social relationships\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 412px;\"\u003e\n \u003cp\u003eQ9. I am content with my friendships and relationships.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eD5. Close social relationships\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 412px;\"\u003e\n \u003cp\u003eQ10. My relationships are as satisfying as I would want them to be.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eD6. Financial/material stability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 412px;\"\u003e\n \u003cp\u003eQ11. How often do you worry about being able to meet normal monthly living expenses?\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eD6. Financial/material stability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 412px;\"\u003e\n \u003cp\u003eQ12. How often do you worry about safety, food or housing?\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u0026nbsp;\u003c/strong\u003eSummary of generalised linear models examining the relationship between the flourishing index and suicide mortality rates using both a simple age-adjusted model and stepwise regression models in the total population and stratified by sex and age groups with the outlier country Turkey removed. Flourishing index and flourishing domains were accounted for complex sampling design using primary sampling units, strata and annual weights so that estimates were nationally representative. Stepwise backwards regression models considered covariates of national GDP per capita, average temperatures, average years of education, sociodemographic index (SDI), population density and numbers of guns owned per 100 persons as covariates. \u0026nbsp;Details on included covariates for each analyses can be found in Supplementary Table 2.\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge-adjusted model\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 246px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStepwise model\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eB (95%CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBeta\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eB (95%CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBeta\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFlourishing Index, Total Population\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e-5.2 (-8.9, -1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 42px;\"\u003e\n \u003cp\u003e-0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0142*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-4.6 (-7.8, -1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0104*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 567px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFlourishing Index, Subgroups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e-3.6 (-5.8, -1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 42px;\"\u003e\n \u003cp\u003e-0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0056**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-3.2 (-5.1, -1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e-6.2 (-12.4, -0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 42px;\"\u003e\n \u003cp\u003e-0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.0606\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-4.4 (-9.8, 1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.1336\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e18 \u0026ndash; 29\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e-3.7 (-7.3, -0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 42px;\"\u003e\n \u003cp\u003e-0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.0503\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-3.3 (-6.5, -0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.0625\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e30 \u0026ndash; 49\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e-5.1 (-10.1, -0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 42px;\"\u003e\n \u003cp\u003e-0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.0632\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-5.5 (-9.6, -1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0183*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e50 \u0026ndash; 69\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e-7.7 (-13.8, -1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 42px;\"\u003e\n \u003cp\u003e-0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0229*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-7.7 (-13.4, -2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0152*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e70+\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e-19.6 (-33.7, -5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 42px;\"\u003e\n \u003cp\u003e-0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0139*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-10.2 (-27.1, 6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.253\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 567px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFlourishing domains, Total population\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHappiness/Life Satisfaction\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e-2.2 (-5.6, 1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 42px;\"\u003e\n \u003cp\u003e-0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.2321\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-1.9 (-5.2, 1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.2894\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhysical and Mental Health\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e-2.5 (-6.4, 1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e-0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.2297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-2.7 (-6, 0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.1356\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMeaning/Purpose\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e-4.6 (-7.3, -1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 42px;\"\u003e\n \u003cp\u003e-0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0047**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-4.3 (-6.8, -1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.004**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacter/Virtue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e-3.1 (-6.4, 0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 42px;\"\u003e\n \u003cp\u003e-0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.0788\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-2.4 (-4.9, 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.0634\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClose social relationships\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e-4.8 (-8, -1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 42px;\"\u003e\n \u003cp\u003e-0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0088**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-4 (-6.9, -1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0173*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFinancial/Material Stability\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e-0.4 (-2.1, 1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 42px;\"\u003e\n \u003cp\u003e-0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.6232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-1.1 (-3, 0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.2943\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003ep\u0026lt;0.05*\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ep\u0026lt;0.01**\u003c/strong\u003e\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"social-psychiatry-and-psychiatric-epidemiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"sppe","sideBox":"Learn more about [Social Psychiatry and Psychiatric Epidemiology](http://link.springer.com/journal/127)","snPcode":"127","submissionUrl":"https://submission.nature.com/new-submission/127/3","title":"Social Psychiatry and Psychiatric Epidemiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Suicide, Flourishing, Meaning, Purpose, Relationships, Happiness","lastPublishedDoi":"10.21203/rs.3.rs-8487304/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8487304/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSuicide rates continue to increase in many nations despite awareness and prevention campaigns. While economic factors, substance abuse and availability of means have been associated with suicide rates, much of the population-level variability remains unexplained. To assess the association between national-level flourishing index scores, flourishing subdomains and age-standardised suicide mortality rates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study used national-level, cross-sectional data from\u003cstrong\u003e \u003c/strong\u003eGlobal Flourishing Study (GFS) and the Global Burden of Disease (GBD) Study (2021). Generalised linear models were used to assess the relationships between the exposures and outcomes. The exposures included the \u003cstrong\u003eflourishing index and flourishing domain scores (happiness/life satisfaction, mental/physical health, meaning/purpose, character/virtue, close social relationships, and financial/material stability). \u003c/strong\u003eThe primary outcome was suicide mortality (GBD 2021).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere were 202,838 participants included in the GFS from 22 countries nations that differed widely by socioeconomic status, cultural background, and religious tradition. In the main age-adjusted analysis, national flourishing index scores were inversely associated with the GBD estimates of suicide mortality (B=-5.2; 95%CI[-8.9, -1.4]). The two flourishing domains associated with suicide mortality were meaning/purpose (B=-4.6; 95%CI[-7.3, -1.8]) and close social relationships (B=-4.8; 95%CI[-8, -1.6]), with little evidence of associations found with the other four domains.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMeasures of flourishing may be more closely associated with suicide mortality than previously used measures of wellbeing. Flourishing, particularly in domains of meaning/purpose and close social relationships, should be considered in further research of causal factors and in national frameworks for suicide prevention.\u003c/p\u003e","manuscriptTitle":"Human flourishing and suicide: A national-level analysis with 22 countries","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-09 06:36:05","doi":"10.21203/rs.3.rs-8487304/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-13T16:10:03+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-08T04:06:34+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-04T16:04:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"105282045070215267938379116331336471621","date":"2026-04-20T17:54:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"4127142949114671735171770156009533797","date":"2026-04-20T14:33:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"234421500986498324533840406392317718160","date":"2026-04-19T08:39:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"241790811750966639786746680232779746224","date":"2026-04-17T16:07:32+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-17T08:22:03+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-03T10:39:34+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-03T06:31:58+00:00","index":"","fulltext":""},{"type":"submitted","content":"Social Psychiatry and Psychiatric Epidemiology","date":"2025-12-31T07:44:03+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"social-psychiatry-and-psychiatric-epidemiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"sppe","sideBox":"Learn more about [Social Psychiatry and Psychiatric Epidemiology](http://link.springer.com/journal/127)","snPcode":"127","submissionUrl":"https://submission.nature.com/new-submission/127/3","title":"Social Psychiatry and Psychiatric Epidemiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"d695a7a2-1e94-4a1e-b5ec-d15689c61121","owner":[],"postedDate":"January 9th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-13T16:10:03+00:00","index":26,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-08T04:06:34+00:00","index":25,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-04T16:04:32+00:00","index":24,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-17T08:38:42+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-09 06:36:05","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8487304","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8487304","identity":"rs-8487304","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}