PLOS ONE RESEARCH ARTICLE Socioeconomic disparities in suicide: Causation or confounding? Vincent Lorant ID1*, Dharmi Kapadia2, Julian Perelman3, the DEMETRIQ study group¶ 1 Institute of Health and Society, UCLouvain, Brussels, Belgium, 2 Cathie Marsh Institute for Social Research, University of Manchester, Manchester, United Kingdom, 3 NOVA National School of Public Health, Public Health Research Centre, Universidade NOVA de Lisboa, Lisboa, Portugal ¶ Membership of the DEMETRIQ study group is provided in the Acknowledgments. * vincent.lorant@uclouvain.be a1111111111 a1111111111 a1111111111 Abstract a1111111111 a1111111111 Background Despite an overall reduction in suicide, educational disparities in suicide have not decreased over the last decade. The mechanisms behind educational disparities in suicide, however, remain unclear: low educational status may increase the risk of suicide (“causation”) or low OPEN ACCESS educational status and suicide may share confounders. This paper assesses whether edu- Citation: Lorant V, Kapadia D, Perelman J, the cational disparities in suicide (EDS) are more likely to be due to causation. DEMETRIQ study group (2021) Socioeconomic disparities in suicide: Causation or confounding? PLoS ONE 16(1): e0243895. https://doi.org/ Method 10.1371/journal.pone.0243895 The DEMETRIQ study collected and harmonized register-based data on mortality follow-up Editor: Astrid M. Kamperman, Erasmus Medical from forty population censuses from twelve European populations. More than 102,000 sui- Center, NETHERLANDS cides were registered over 392 million person-years. Three analyses were carried out. First, Received: February 10, 2020 we applied an instrumental variable approach that exploits changes in the legislation on Accepted: November 30, 2020 compulsory educational age to instrument educational status. Second, we analyzed EDS by age under the hypothesis that increasing EDS over the life cycle supports causation. Finally, Published: January 4, 2021 we compared EDS in men and women under the assumption that greater EDS in women Copyright: © 2021 Lorant et al. This is an open would support causation. access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and Findings reproduction in any medium, provided the original The instrumental variable analysis showed no evidence for causation between higher edu- author and source are credited. cation and suicide, for men or women. The life-cycle analysis showed that the decrease of Data Availability Statement: Access restrictions educational inequalities in suicide between the baseline 1991 period and the 2001 follow-up apply to the data of this study, for contractual and for legal reasons. The DEMETRIQ data set collected period was more pronounced and statistically significant in the first three younger age and combined data from national registers in groups. The gender analysis indicated that EDS were systematic and greater in men than in Finland, Sweden, Norway and Denmark, Scotland, women: the rate ratio of suicide for men with low level of education (RR = 2.51; 95% England and Wales, Belgium, Switzerland, Barcelona, Basque Country and Madrid, Turin, CI:2.44–2.58) was higher than the rate ratio in women (RR = 1.32; 95CI%:1.26–1.38). Poland, Hungary, Lithuania and Estonia. The original data can only be retrieved from the Interpretation National Statistics of each country, who owns the data. This has been the case as well with several Overall, there was little support for the causation hypothesis, suggesting that the association PLOSONE publications using the same dataset. between education and suicide is confounded. Educational inequalities in suicide should be PLOS ONE | https://doi.org/10.1371/journal.pone.0243895 January 4, 2021 1 / 14 PLOS ONE Socioeconomic disparities in suicide: causation or confounding? Aggregate data are available from Alaa Mahboub addressed in early life by early targeting of groups who struggle to complete their education from the IRSS (alaa.mahboub@uclouvain.be). and display higher risk of mental disorder or of mental health vulnerabilities. Funding: Vincent Lorant was in receipt of a FNRS grant number 2015/V 3/2/165 - IB/MAA - 10; The Demetriq project was supported by a grant (FP7- CP-FP no 278511) from the European Commission Research and Innovation Directorate General, as Introduction part of the “Developing methodologies to reduce disparities in the determinants of health” Worldwide, suicide accounts for 1.5% of all deaths and ranks as the fourth leading cause of (DEMETRIQ) project. The funders had no role in death in high-income countries [1]. Suicide is also socially patterned: it is more frequent in the study design, in the collection, analysis, and those who are not married [2], in the unemployed [3], and in lower socioeconomic groups [4]. interpretation of data, in the writing of the report, or The difference in suicide rates between socioeconomic groups (hereafter, socioeconomic dis- in the decision to submit the article for publication. parities in suicide) is an important topic of research for two reasons. Firstly, these disparities Competing interests: The authors have declared raise questions about the responsiveness of mental health care systems to the needs of the most that no competing interests exist. vulnerable groups. Secondly, despite an overall reduction in suicide, these disparities have not decreased over the last decade either in North America [5,6] or in Europe [7,8]. Socioeconomic disparities in suicide have been investigated in Asia [9–14], North America [5,6,15], Europe [8,16–19], and Australia and New Zealand [20–22]. In addition, two meta- analyses [14,23], one cross-comparative study of fourteen European countries [7], and one narrative review [4] have helped to take stock. In all but one of those studies, people in lower socioeconomic groups were found to be more likely to die by suicide than those in higher socioeconomic groups. Disparities were greatest for occupation-based socioeconomic status (SES), followed by education and, finally, income. The association between low socioeconomic status and suicide is generally more pronounced in men than in women. A Danish case-con- trol study found that suicide risk increased as income decreased (but the same was not true of wealth) and this relationship disappeared once psychiatric history was factored in [18]. Hence, there is a need to see how the risk of suicide is related to low socioeconomic status, controlling for key confounding factors. Among adults, suicide is an ultimate event and posterior to educational status. Formal edu- cation is completed early on in the life cycle and remains time-invariant thereafter. Accord- ingly, educational disparities in suicide are seen as indicative of a low level of education causing suicide either directly or indirectly through the well-known connection between socio- economic status and psychiatric disorder [24]. But this overlooks the omitted-variable bias: factors that affect both the risk of low educational attainment and the risk of psychiatric disor- der. Suicide is associated with a complex set of factors, which have been reviewed by others [25–27]. It certainly cannot be reduced to psychiatric disorder [28]. Some of these factors may affect both suicide risk factors and educational attainment in the general population: early psy- chiatric disorder [29,30], impulsiveness [31], childhood behavior [32], childhood adversity [33], and a low level of intelligence [34] are factors that decrease the chance of higher educa- tional achievement and increase the risk of later psychiatric disorder and, thus, of suicide (see S1 Table for a detailed description). Overall, the direct influence of low educational level on suicide remains a matter of contro- versy. To take on the challenge of assessing this topic, more insight is needed into the relation- ship between education and suicide. This paper attempts to address this question, using a theoretically informed approach. We designed three tests aimed at shedding light on the causal relationship between educational level and suicide. First, causation is investigated with a quasi- experimental approach, assessing how changes at the country-level of the legal upper age of compulsory education predict suicide mortality. Second, we analysed how educational inequalities in suicide evolve over age as causation predicts diverging health trajectories between educational groups over the life course. Third, under causation, we expect a steeper PLOS ONE | https://doi.org/10.1371/journal.pone.0243895 January 4, 2021 2 / 14 PLOS ONE Socioeconomic disparities in suicide: causation or confounding? gradient for women than for men because women generally have a lower educational level than men, are more exposed to economic hardship and poverty and benefit more from educa- tion than men [35–38]. We thus combined theory and empirical analysis of longitudinal data from twelve different populations and we applied these three tests to investigate the association between education and suicide. Together, these analyses throw light on the question of whether educational disparities in suicide are causal. In seeking an answer to this question, it is important to deliver on the need for an equity lens in suicide prevention [4]. Indeed, if these inequalities result from omitted-variable bias, then early intervention in relation to psychiatric history/vulnerability would make more sense. On the other hand, if a low level of education is a direct determinant of suicide then structural policies aimed at increasing educational opportunities throughout the life course would be needed. Materials and methods Design The research question precluded an experimental method and so we looked into observational data for effective signatures of the two hypotheses mentioned above: do the data plead for cau- sation or for confounding? We first used a quasi-experimental approach and performed two additional robustness analyses in order to investigate the causal link between education and suicide. These were then implemented with the longitudinal DEMETRIQ data. Data source The data came from the DEMETRIQ (“Developing Methodologies for Reducing Inequalities in the Determinants of Health”) database, which has been fully described elsewhere [7]. The denominator is composed of population censuses between 1990 and 2007 and linked at the individual level to mortality registers for an average of four years (see Table 1). For Spain-Bar- celona, Hungary, Poland, and Estonia the linkage was performed at the group level. For England and Wales, a 1% random sample (the Sample of Anonymized Records) of the popula- tion was included. Overall, more than 95% of deaths were successfully linked. The dataset included 12 populations from Northern, Southern, Eastern, and Western Europe: Austria, Bel- gium, Denmark, England and Wales, Estonia, Finland, Hungary, Italy (Turin Region), Nor- way, Poland, Spain (Madrid, Barcelona, and Basque regions), and Switzerland (Table 1). For Spain the data from three regions, Barcelona, the Basque region, and Madrid were merged. Italy includes only the region of Turin. The individuals were classified by sex and in 5-year age groups from 35 to 79. Education was harmonized across countries and classified into three groups: low level of education (International Standard Classification for Education–ISCED, 0 to 2, up to lower secondary), medium level of education (ISCED 3–4, upper secondary), and high level of education (ISCED 5+, tertiary education). Deaths were coded using ICD8, 9, or 10. Suicides were identified with the codes for ICD-8 (E950-E959), ICD-9 (E950-E959), and ICD-10 (X60-X84, Y87.0). The deaths included more than 100,000 suicides among 392 million person-years. For all population analyses, number of person-years and number of suicides were weighted so that each population had the same weight. Data analysis Two-stage regression (2SLS) is a quasi-experimental approach, which we used to identify pre- dictors of educational status that are unlikely to be associated with confounders. Here, we first looked for instrumental variables and found that changes in the legal upper age of compulsory PLOS ONE | https://doi.org/10.1371/journal.pone.0243895 January 4, 2021 3 / 14 PLOS ONE Socioeconomic disparities in suicide: causation or confounding? Table 1. Number of person-years and number of suicides per population and census, DEMETRIQ study from twelve European populations, 1991–2001. Population Census Follow-up time (y) Number of person-years No. of suicides Austria 1991 1 3,696,932 1,043 2001 1 4,248,221 994 Belgium 1991 5 21,308,219 6,030 2004 1 10,593,107 2,720 Denmark 1991 4 12,194,456 3,910 1996 4 12,607,023 2,710 2001 4 13,247,779 2,361 England and Wales 1991 5 1,211,333 95 1996 5 1,181,362 78 2001 5 1,280,994 91 2006 3 938,240 65 Estonia 1987 4 3,609,145 1,379 1998 4 3,435,255 1,471 Finland 1990 5 12,729,941 4,824 1995 5 12,418,614 3,948 2000 5 13,999,113 3,870 2005 5 13,447,352 3,340 Hungary 1988 3 20,576,688 12,531 1999 3 21,031,348 9,374 Italy-Turin 1991 5 2,518,551 323 1996 5 2,217,765 233 2001 5 2,460,183 234 2006 4 1,822,737 154 Norway 1990 5 8,033,047 1,470 1995 6 8,181,245 1,251 2001 5 8,956,862 1,277 2006 3 4,889,983 688 Poland 1991 2 41,567,370 9,871 2001 2 42,980,313 10,478 Spain (3 regions) 1992 4 4,290,318 368 1996 3 9,230,787 605 1997 4 4,146,288 365 2001 4 10,292,666 693 2002 4 4,347,257 399 2007 3 3,537,654 358 Switzerland 1990 5 13,714,409 4,130 1995 5 13,264,927 3,684 2000 5 14,208,708 3,423 2005 3 8,306,439 1,925 Total 392,722,631 102,763 https://doi.org/10.1371/journal.pone.0243895.t001 education could be an instrument of individual educational status, an approach that had been used by others [39–42]. We surveyed educational reforms in the DEMETRIQ countries and found that twelve countries had carried out educational reforms: one of these (Belgium) occurred too early to be captured in our dataset (see supplementary tables) and one (Finland) occurred too late. We then checked whether these reforms could be a good instrument: using graphs, we identified discontinuity in the distribution of those with a high level of education as PLOS ONE | https://doi.org/10.1371/journal.pone.0243895 January 4, 2021 4 / 14 PLOS ONE Socioeconomic disparities in suicide: causation or confounding? a response to the reforms and we excluded countries where the reform was not associated with a statistically significant increase in the percentage of individuals with medium or high levels of education after the reform (Austria, Denmark, and Finland). The S2 Table describes the educational reform per country, together with the sources of information and the effect of the reform on the percentage of individuals with a medium level of education. S1 Fig displays the change in the educational level following the pivotal year of the education reform. We were left with eight countries in which 54.4% of person-years were exposed to the reform and 45.6% were not. We ran probit models of high education level predicted by country, sex, age, and dummies indicating when the age of compulsory education was increased. The predicted value of a high educational level was then computed and was retained for the second-stage analysis. Endogeneity of high educational level was also tested with the Durbin-Wu-Hausman (DWH) test. Two-stage least square regressions were performed with suicide mortality rate as the dependent variable and the predicted educational level as an instrumental variable for individ- ual education, in addition to other covariates. Separate analyses were run for men and women. In addition, two complementary analyses were performed according to age and to gender. The causation theory of cumulative disadvantage predicts diverging health trajectories between educational groups over a lifetime [43,44]. Under cumulative disadvantage, disparities in suicide would increase because educational status brings benefit at each stage of the life cycle, thus leading to increasing differences between the different educational groups. Alterna- tively, health trajectories between educational groups will converge in later life cycles: this is because, at each stage of the life cycle, suicide removes a vulnerable subgroup among those with less education, rendering more similar the composition of the different educational groups regarding these confounding factors. We thus modeled the number of suicides per person-year with a Poisson regression using educational group, age, and the interaction of education and age, controlling for the census period, sex, and country as dummies. Having a college degree, however, means different things in younger age groups than in older age groups. To control for this cohort effect, we included the age-specific relative rank of each educational group as an additional control. Comparing suicide inequalities across different age groups does not, however, disentangle cohort from age effects. As we were able to include at least with at least two repeated follow- ups per age group for several populations, we were able to construct a pseudo-panel at the group level as proposed by Deaton and others [45,46]. We constructed baseline groups accord- ing to education (low, middle, high), gender, birth cohort of five years at the first period of ref- erence (1990/91). Each baseline group was then matched with the second period, by aging each baseline group according to the time span between the first census and the second census (10 years). Because we counted with age group of 5 years, we retained only countries for which we had at least two censuses 10 years apart. For this analysis, we retained Denmark, Finland, and Norway because the data covered the whole country, for a longer period, and had better suicide coding. We ran a Poisson regression, and rate ratios were computed for each educa- tional group, age, and period (baseline census and follow-up census), controlling for country, gender, and age at baseline. Pooled analyses were weighted so that each population-period had the same weight. Our third analysis relied on the gendered difference in socioeconomic disparities in suicide. As explained above, the relationship between socioeconomic status, suicide, and the confound- ers differs both in terms of sign and magnitude for men and women (see Fig 1). Women have generally had a lower educational level than men and they are more exposed to economic hardship and poverty [35–37]. In addition, the economic gain from education is higher for women than for men [38]. Accordingly, the causal relationship between education and suicide (a and c1� b2, Fig 1) is expected to be more negative for women than for men. As far as the PLOS ONE | https://doi.org/10.1371/journal.pone.0243895 January 4, 2021 5 / 14 PLOS ONE Socioeconomic disparities in suicide: causation or confounding? Fig 1. Theoretical model of educational disparities in suicide, with unobserved and observed variables in the DEMETRIQ dataset. https://doi.org/10.1371/journal.pone.0243895.g001 confounding factors are concerned, psychiatric disorders in childhood are more prevalent in boys than in girls [29,30]; impulsiveness, a key trigger of suicide, is more frequent in men; there are no clear gender differences in childhood adversity, with the exception of sexual abuse, which is more frequently experienced by girls [47–49]. Early psychiatric disorder in childhood or adolescence has been investigated across sex groups: Costello 2003 and Merikan- gas 2010 found that boys were more likely to have a psychiatric disorder than girls. Boys and girls differ in the type of disorder: conduct or behavioral disorder are more frequent in boys, whereas depression is more frequent in girls [29,30]. Hence, these confounding factors may be considered slightly more frequent in boys than in girls: this implies that the arrow (e, in Fig 1) is either negative or close to zero. As a conclusion, we expect women, as compared to men, to be more vulnerable to causation (because of d < 0 and because c1 is higher in absolute value for women than for men) but less vulnerable to confounding effects (e is either < 0 or !0). From a statistical point of view, our analysis rests on testing the interaction of educational sta- tus and gender in relation to the number of suicides per person-year using Poisson regressions, for each country and for the pooled dataset (weighted analysis with countries as dummies). Each hypothesis is associated with different expectations: causation is supported by a nega- tive effect of instrumented education on suicide in the 2SLS. Causation predicts a diverging trend in educational disparities in suicide; causation leads to a steeper gradient for women than for men. Together, these analyses throw light on the question of whether educational dis- parities in suicide are more likely to be causal or not. All analyses were carried out with STATA 15.1 and SAS 9.4. Results Quasi-experimental approach Results of the 2SLS are displayed in Table 2 for the first stage (upper panel) and for the second stage (lower panel). A high level of education was more likely when the legal upper age limit for compulsory education was increased; it was more frequent in some countries (i.e. PLOS ONE | https://doi.org/10.1371/journal.pone.0243895 January 4, 2021 6 / 14 PLOS ONE Socioeconomic disparities in suicide: causation or confounding? Table 2. Two-stage least square estimates, DEMETRIQ study of twelve European populations, 1991–2001. Both genders Men Women Coefficient (SE) Coefficient (SE) Coefficient (SE) Covariate Predictor of medium or high level of education: first-stage probit estimate Change in upper age limit for compulsory education (dummy) 0.181��� 0.123��� 0.244��� (0.000236) (0.000346) (0.000325) Women (ref = men) -0.0974��� (0.000150) Age (y.) -0.0223��� -0.0166��� -0.0270��� (9.21e-06) (1.37e-05) (1.26e-05) Intercept 1.499��� 1.487��� 1.415��� (0.000737) (0.00110) (0.00101) F-test of Weak instrument 12.69��� 10.23��� 11.12��� Predictors of suicide mortality: second-stage estimates Medium or high education level -0.297(-1.896, 1.302) 0.515(-0.982, 2.012) -0.419(-1.756, 0.918) (0.816) (0.764) (0.682) Women (ref = men) -1.135��� (0.139) Intercept -7.880��� -8.503��� -8.856��� (0.619) (0.569) (0.544) N 272,906,066 129,203,487 143,702,579 ¶Robust standard errors in parentheses ��� P < 0.01 �� P < 0.05 � P < 0.1. ‡Controlled for 5y age groups and country dummies. https://doi.org/10.1371/journal.pone.0243895.t002 Switzerland and Norway) than others; it was higher at a younger age. Interestingly, the change in the upper age limit for compulsory education was associated with a greater increase in the proportion with a high level of education among women (Beta = 0.244) than among men (Beta = 0.124). The McFadden pseudo-R2 were 0.16 for men and 0.14 for women; the robust test of weak instrument was rejected (F(2,9) = 12.7, p = 0.0029) for both gender groups (Men: 10.23, p<0.01; Women: 11.12, p<0.01). Exogeneity of education was rejected with a DWH chi-square of endogeneity of 11.88 (P � 0.001) for men and 55.63 (P � 0.001) for women. In the second stage (Table 2, lower panel), suicide mortality was not significantly associated with a high level of education, for either men or women. Suicide was lower among women than among men and lower in southern countries than in eastern countries. The same results were found with a medium level of education. These estimates were performed on countries (Belgium, England and Wales, Estonia, Hun- gary, Italy, Norway, Poland, Spain, and Switzerland) with a positive effect of the instrument in the first-stage equation. Three countries had a negative effect and were thus excluded: Austria, Denmark, and Finland. Educational disparities in suicide by age Across all age groups, the risk of suicide among those with the lowest level of education, com- pared to the most highly educated, was 1.61 (95%CI:1.53, 1.70) at baseline and decreased to 1.46 (95%CI: 1.38, 1.55) ten years later, a decrease which was statistically significant PLOS ONE | https://doi.org/10.1371/journal.pone.0243895 January 4, 2021 7 / 14 PLOS ONE Socioeconomic disparities in suicide: causation or confounding? Fig 2. Educational disparities in suicide across age groups and period: Rate ratio of suicide, pooled and weighted Poisson regression analysis of Denmark, Finland, and Norway, 1991–2001. https://doi.org/10.1371/journal.pone.0243895.g002 (Chi = 6.07, p = 0.014). Fig 2 displays the pooled rate ratio (RR) of suicide for each age and period: the decrease of educational inequalities in suicide between the baseline 1991 period and the 2001 follow-up period was more pronounced and statistically significant in the first three younger age groups. For example, among those aged 35–39, inequalities decreased from 2.79 to 2.10 between 1991 and 2001. Educational disparities in suicide for men and women The educational disparities in suicide for men (M) and women (F) are displayed in Fig 3. In the pooled analysis, the risk of suicide for women with a low level of education compared to those with a high level was 1.32 (95CI%:1.26, 1.38); in men, this ratio was higher (2.51; 95% CI:2.44, 2.58). In all countries except two (England-Wales and Estonia), educational disparity was statistically significantly higher in men than in women (see last column of S3 Table). Discussion Main findings This paper contributes novel information on the association between education and suicide. The instrumental variable showed that group-level predictors of a high level of education were PLOS ONE | https://doi.org/10.1371/journal.pone.0243895 January 4, 2021 8 / 14 PLOS ONE Socioeconomic disparities in suicide: causation or confounding? Fig 3. Educational disparities in suicide per population and gender (F = Women, M = Men): Pooled and weighted results and population-specific risk ratio of suicide from the Poisson regressions, DEMETRIQ study from twelve European populations, 1991– 2001. https://doi.org/10.1371/journal.pone.0243895.g003 not associated with suicide. In addition, educational disparities in suicide decreased with age, thus not supporting causation. This general finding should, however, be nuanced, as dispari- ties in suicide were larger between 55 and 65 years. As these disparities were more systematic and marked for men than for women, causation was again less likely. Overall, this paper found little support for a causal relationship between education and suicide. Interpretation Several reviews have looked anew at the social determinants of suicide and at the debate about which models are relevant [4,50,51]. From a psychiatry perspective, two models compete as far as depression is concerned, one in which psychosocial factors are determinants of both depres- sion and suicide, the other in which depression affects both psychosocial factors and suicide. In their review of current empirical evidence related to suicide prevention, Hegerl and Heinz [52] found more support for the latter than for the former, lending support to our conclusions. Our results are equally consistent with previous empirical studies. Our instrumental analy- sis compares well with another study that investigated municipal differences in relation to rais- ing the upper age limit for compulsory education by one year between 1949 and 1962 in Sweden. To the best of our knowledge, that was the only instrumental variable approach to provide cause-specific mortality results, including suicide and intentional self-harm. It found PLOS ONE | https://doi.org/10.1371/journal.pone.0243895 January 4, 2021 9 / 14 PLOS ONE Socioeconomic disparities in suicide: causation or confounding? no effect for all-causes mortality and no effect for suicide/intentional self-harm in either men or women [40]. Besides the Danish register study, a recent case-control study from Finland points to the same conclusions. The Finnish study found a reverse gradient, with suicide occurring slightly more frequently among those with a high level of education than among those with a low level, once depression severity and other clinical features were accounted for [52]. Limitations The DEMETRIQ dataset lacked information related to the possible confounders. The literature provides some insights, which are summarized in S1 Table, in which we have excluded factors posterior to education (i.e. unemployment and marital status) [3]. Candidates for omitted-var- iable bias include: (a) childhood or adolescent psychiatric disorder, (b) latent factors such as impulsiveness and intelligence [34], and (c) childhood adversity. All these variables have been found to increase both the risk of suicide and poor educational achievement. The instrumental variable approach had some limitations: we had categories of education and not completed years of education; thus, our estimate is possibly a lower bound. Finally, for some countries, raising the upper age limit for compulsory education was a poor instrument of education status. In addition, education is a time-invariant marker of socioeconomic status. It has the advan- tage of being insensitive to later changes in psychiatric condition but, as a consequence, does not capture the full range of socioeconomic opportunities such as income, which may show a different pattern for the two hypotheses tested here [53]. The underreporting of suicide in reg- isters is another limitation. Although suicide is certainly underreported in some countries, a previous sensitivity analysis showed that the magnitude of educational disparities in suicide was only weakly affected by underreporting when considering countries with more reliable data or when including deaths categorized as “injuries–unknown whether intentional” as covert suicide [54,55]. As far as the life-course analysis was concerned, it could not do justice to the dynamic rela- tionships involved in these disparities [56]. The mechanisms driving the association between education and mental health are different across the life course and also involve inter-genera- tional processes [57,58]. The decreasing educational inequalities in suicide with age might also be the result of the differential role that education plays in different life stages. Education is an important dimension of social stratification in young adults, but may be less relevant in older age where wealth and housing tenure are more important. Also, educational disparities in sui- cide may be lower in women in part because suicide is much less frequent among women than among men or because the relationship between education and suicide is different in men and women. So there may be a limit to the attempt to separate the gender gradient in suicide from the educational gradient in suicide. Yet, even in countries where educational disparities in sui- cide were more pronounced (i.e. eastern European countries), disparities for men always exceeded disparities for women. Finally, this study was performed with European populations, where, on the whole, income inequality is rather low and health care coverage is quite exten- sive compared to other continents. Conclusions The higher risk of suicide in less educated individuals may be due to early-life factors reducing educational opportunities and increasing mental health vulnerabilities. Paying more attention to young men who are struggling to complete their educational track and who have mental health vulnerabilities should become a priority in order to tackle educational inequalities in suicide. PLOS ONE | https://doi.org/10.1371/journal.pone.0243895 January 4, 2021 10 / 14 PLOS ONE Socioeconomic disparities in suicide: causation or confounding? Supporting information S1 Fig. Percentage of those with a high level of education in the population by number of years before/after the educational reform, per country. (TIF) S1 Table. Factors affecting the risk of suicide and low educational level: A brief overview of the literature. (DOCX) S2 Table. Changes in compulsory schooling legislation. ¶ Effect of exposure to the reform in the following logit equation: medium high level of education = age group + Census year + Sex + exposure to the reform. (DOCX) S3 Table. Results of Test 2, educational disparities in suicide by gender and population, DEMETRIQ study from twelve European populations, 1991–2001. ¶ All estimates are con- trolled for sex, 5y. age group, and year of the census. Results for all countries are weighted and controlled by country dummies. (DOCX) Acknowledgments The authors are grateful to the Institute of Health and Society and the Cathie Marsh Institute for the opportunity to present and discuss the paper. A special thanks to the following persons: Bram Vanhoutte, James Nazroo, Wendy Olsen, Tarani Chandola, Pierre-Olivier Robert, Pablo Nicaise, and Sandy Tubeuf. The authors acknowledge the role of the DEMETRIQ study group in designing, collecting, and harmonizing the data used in this study: Carme Borrell, Maica Rodrı́guez-Sanz,Ramune Kalediene, Mall Leinsalu, Enrique Regidor, Bogdan Wojtyniak, Bjørn Heine Strand, Matthias Bopp, and Johan Mackenbach. Author Contributions Conceptualization: Vincent Lorant, Dharmi Kapadia, Julian Perelman. Formal analysis: Vincent Lorant, Julian Perelman. Investigation: Vincent Lorant. Methodology: Vincent Lorant, Dharmi Kapadia. Software: Vincent Lorant, Julian Perelman. Supervision: Vincent Lorant, Dharmi Kapadia. Validation: Vincent Lorant, Dharmi Kapadia, Julian Perelman. Visualization: Vincent Lorant. Writing – original draft: Vincent Lorant. Writing – review & editing: Vincent Lorant, Dharmi Kapadia, Julian Perelman. References 1. 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