# Moderating effects of self-defined sexual orientation on the relation between social factors and depressive symptoms or suicidal ideation among French young adults

Junko Kose, Camille Davisse-Paturet, Anne Pastorello, Laurence Meyer, Maria Melchior, Cécile Vuillermoz, Alexandra Rouquette, Josiane Warszawski, Nathalie Bajos, Guillaume Bagein, et al.

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Junko Kose, Camille Davisse-Paturet, Anne Pastorello, Laurence Meyer, Maria Melchior, et al. Moderating effects of self-defined sexual orientation on the relation between social factors and depressive symptoms or suicidal ideation among French young adults. Social Psychiatry and Psychiatric Epidemiology, 2025, 10.1007/s00127-025-02951-y. hal-05137580

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# Moderating effects of self-defined sexual orientation on the relation between social factors and depressive symptoms or suicidal ideation among French young adults

Junko Kose<fnref n="1" /> · Camille Davisse-Paturet<fnref n="2" /> · Anne Pastorello<fnref n="1" /> · Laurence Meyer<fnref n="1" />,<fnref n="3" /> · Maria Melchior<fnref n="2" /> · Cécile Vuillermoz<fnref n="1" /> · Alexandra Rouquette<fnref n="1" />,<fnref n="3" />

Received: 23 October 2024 / Accepted: 9 June 2025

© The Author(s) 2025

## Abstract

**Purpose** Disparities in mental health across sexual orientation groups and among young adults have long been discussed. The aim of this cross-sectional study was to investigate the moderating effects of sexual orientation on the associations between social factors and depressive symptoms as well as suicidal ideation in young adults.

**Methods** The study included 6,337 participants aged 18–25y in 2022 from the French EpiCov cohort. The outcome variables were depressive symptoms and suicidal ideation. Poisson regressions with robust error variance were performed to investigate the associations between social factors and outcomes according to sexual orientation (lesbian, gay, bisexual, other, or not defining themselves according to their sexuality: sexual minority (SM); heterosexual or not wishing to answer: Not belonging to SM (NSM)).

**Results** The prevalence of depressive symptoms and suicidal ideation was higher in the SM than in the NSM group. Regarding depressive symptoms, significant moderating effects of sexual orientation were observed for female vs male sex (NSM: adjusted Prevalence Ratio (aPR) 1.58[1.28–1.95], SM: aPR 1.03[0.78–1.36]) and age category 22–25y vs 18-21y (NSM: aPR 1.32[1.05–1.67], SM: aPR 0.78[0.59–1.03]). Regarding suicidal ideation, significant moderating effect was observed for not being vs being in a relationship (NSM: aPR 1.55[1.14–2.12], SM: aPR 0.82[0.59–1.13]).

**Conclusion** In this study conducted in 2022, well-known social risk factors of mental problems do not explain the higher prevalence of depressive symptoms and suicidal ideation among young SM group. Further studies are needed to understand the specific challenges faced by these young people.

**Keywords** Depressive symptoms · Epidemiology · Sexual orientation · Social factors · Suicidal ideation · Young adults

The complete list of collaborators of the EpiCov study can be found

**Terminology rules throughout the manuscript regarding members of the LGBTQI+ community:** the terms used in each cited paper are referred to using quotation marks. In all other parts of the manuscript (analyses, general context), the terms “sexual minority” are used.”.

in the acknowledgments section.

<footnote>Junko Kose
junko.kose@inserm.fr</footnote>

<footnote n="1">¹ Université Paris-Saclay, Inserm, Université Versailles Saint-Quentin (UVSQ), Centre d'Epidémiologie et de Santé Publique (CESP), Paris, France</footnote>

<footnote n="2">² Social Epidemiology Research Team, Institut Pierre Louis d'Epidémiologie Et de Santé Publique (IPLESP), Université, InsermParis, Sorbonne, France</footnote>

<footnote n="3">³ Epidemiology and Public Health Department, Assistance Publique-Hôpitaux de Paris Université Paris-Saclay, Le Kremlin-Bicêtre, France</footnote>
## Abbreviations

<table><tr><td>CATIs</td><td>Computer-Assisted Telephone Interviews</td></tr><tr><td>CAWIs</td><td>Self-Computer-Assisted Web Interviews</td></tr><tr><td>EpiCov</td><td>Epidemiology et Conditions de vie sous le COVID-19</td></tr><tr><td>ICD</td><td>International Classification of Diseases</td></tr><tr><td>IR</td><td>Interaction Ratio</td></tr><tr><td>INSEE</td><td>National Institute for Statistics and Economic Studies</td></tr><tr><td>LGBTQI+</td><td>Lesbian, Gay, Bisexual, Transgender, Queer, Intersex, and inclusive of individuals who identify as part of sexual and gender diverse communities</td></tr><tr><td>NSM</td><td>Not belonging to Sexual Minority</td></tr><tr><td>PHQ-9</td><td>9 Items of the Patient Health Questionnaire</td></tr><tr><td>PR</td><td>Prevalence Ratio</td></tr><tr><td>SM</td><td>Sexual Minority</td></tr></table>

## Introduction

Individuals identifying within the sexual minority community (individuals who identify as part of sexual orientation diverse communities) have long faced higher risks of mental health conditions and suicidal thoughts and behaviors than their heterosexual counterparts [1–3]. In 1995 for gay men and in 2003 for lesbian, gay, and bisexual people, Ilan Meyer described a conceptual framework for understanding this higher risk, called “Minority stress theory” [4, 5]. The framework includes proximal stress (internal vigilance and concern about discrimination, internalized stigmatization about sexuality, and concealment or disclosure of sexual orientation) and distal stress (stress due to interpersonal relationships, such as experiences of rejection or discrimination by others) [4, 5]. In that sense, the stress faced by the sexual minority community should be considered not only as an individual attitude, but also as a consequence of the social and political climate toward this community [6]. Indeed, following a joint statement by the United Nations agencies in 2015 to condemn violence and discrimination against LGBTQI+ people (lesbian, gay, bisexual, transgender, queer, intersex, and inclusive of individuals who identify as part of sexual and gender diverse communities), the United Nations Secretariat adopted in 2024 a strategy to protect them from violence and discrimination [7]. While there is ongoing progress to support the rights of members of this community worldwide, same-sex relationships remain a crime in many countries, and decriminalization or moving sexual orientation out of the psychiatric field are relatively recent in other countries. For example, the American Psychiatric Association included the diagnosis of “homosexuality” in the Diagnostic and Statistical Manual

until 1974 [8]. Regarding the World Health Organization, although “homosexuality” has been removed from the International Classification of Diseases (ICD) since 1992, the International Classification of Diseases (ICD)-10 still included “Psychological and behavioral disorders associated with sexual development and orientation” suggesting mental disorders uniquely linked to sexual orientation [9]. This category was removed from the ICD-11, which officially entered into force in 2022. In France, discriminatory laws regarding the age of consent for sexual intercourse (15 years for the opposite sex and 18 years for the same sex) had existed, and “homosexuality” could be grounds for termination of a residential lease until 1982 [10]. The civil solidarity pact (Pacte civil de solidarité: PACS) for same-sex couples was approved in 1999, however, it did not permit joint adoptions by same-sex couples [11]. Marriage for same-sex couples, which allows for joint adoption by same-sex married couples, was approved in 2013 (Law n°2013–404). These transitions may lead to generational differences in the associations between sexual orientation and mental health [12]. As regards societal attitude towards the sexual minority community, French interministerial delegation mobilized against hate reported that since 2016, anti-LGBT+ crimes and misdemeanors have increased by 129% and 115% of increase for ‘anti-LGBT+’ contraventions [16]. The majority of recorded anti-LGBT+ crimes affected young people under the age of 30 [16]. In addition, mental disorders account for a greater percentage of the overall burden of diseases in young adults in European high-income countries [13]: among them, depressive disorders are the first leading cause of Disability Adjusted Life Years [14]. Likewise, suicide and “intentional self-harm” is the second leading cause of death in young people in Europe [15]. Continuous assessment of these associations in younger generations is therefore important to inform and adapt public health strategies to the challenges actually faced by these new generations.

In general, mental health conditions result from a complex interplay of social, psychological, and biological factors. For instance, female sex, low income, low socioeconomic status, being single, being from ethnical minorities, and stigmatization have been suggested as risk factors for mental health problems [17–19]. Regarding the sexual minority community, studies have also reported that young age, female sex, low educational attainment, not being in a relationship, and not feeling accepted by others could heightened the risk of depressive symptoms and/or suicidality in this community [20–22]. It should be noted that these studies were conducted using convenient study samples from members of the sexual minority community, which can generate selection bias and do not allow us to investigate whether these factors explain their high risk for
depression and suicidality compared to those not belonging
to this community.

Previous studies have explored the moderating effect of
sexual orientation on the associations between various social
factors and depressive symptoms and suicidal thoughts.
Indeed, belonging to the sexual minority community has
been reported to have strong correlations with both social
factors such as discrimination and stigmatization in the
family and public contexts [23] and mental health problems
[1-3]. The results from previous studies on the moderation
effects of sexual orientation suggest that the associations
between depressive symptoms or suicidal thoughts and low
income, living inner cities, and educational attainment were
greater among people belonging to the sexual minority com-
munity than among their heterosexual counterparts [24-26].
These studies were conducted in a nationally representative
sample of US female elderly using data measured in 2015
[25], in a nationally and regionally representative sample of
8,455 UK adults using data measured in 2008-2013 [26],
and in a nationally representative sample of 35,230 US
adults using data measured in 2004-2005 [24], respectively.
On the other hand, other studies have suggested that vic-
timization, bullying, social support, and childhood gender
nonconformity have weaker associations with depressive
symptoms or suicidality in participant defined as sexual
minority community than in their heterosexual counter-
parts [27-30]. These findings were obtained in a sample of
3,062 Chinese high school students using data measured
in 2018 [28], in a sample of 75,344 US adolescents using
data measured in 2009-2011 [27], in a national represen-
tative sample of 4,121 US elderly using data measured in
2005-2015 [30], and in a sample of 10,655 US adolescents
to young adults using data in measured 2007-2010 [29],
respectively. Regarding other social factors, representa-
tive household surveys of English adults (N=10,443) in
2007 and 2014 reported no interaction between gender and
sexual orientation on the association with suicidality [31].
Likewise, a Canadian study in a nationally representative
sample of 169,091 adults using data in 2007-2017 reported
no interaction between sexual orientation and rurality on
suicidal behaviors [32]. Overall, the moderating effects of
sexual orientation on the associations between social factors
and mental health are inconclusive and depends on studied
factors, population, geographical context, and period. That
may be due to the fact that the effect of sexual orientation
on mental health depend greatly on the social and politi-
cal climate toward sexual minority community [6]. Hence,
a comprehensive study of this target population using recent
data is necessary.

In France, the latest data on mental health according to
sexual orientation were collected before the COVID-19 pan-
demic. A French study of a nationally representative sample

aged 18–69 y in 2012–2019 reported that having same-sex
partners was associated with an increased risk of depres-
sive symptoms and suicide attempts [33]. Another French
national survey conducted in 2017 among adults 18–75 y
revealed that lesbian, gay, and bisexual participants had
increased odds of depression, suicide thoughts and attempts
compared to heterosexual individuals. This study also
reported that 25.4% of the associations were explained by
physical or verbal victimization [34], indicating that almost
75% of the associations could be due to other factors. Inves-
tigating the moderating effect of sexual orientation on the
associations between known social risk factors and depres-
sive symptoms or suicidal thoughts could help understand
how such factors explain disparities in mental health across
sexual orientation groups.

In this context, the aim of the present study was to inves-
tigate whether sexual orientation moderate the associations
between various social factors and depressive symptoms
as well as suicidal ideation, after verifying the associations
between sexual orientation and each outcome, using a recent
and large sample of young adults from the French general
population, to understand the challenges faced by this new
generation of emerging adults.

**Materials and methods**

Study population

The EpiCov (French acronym for “*Epidemiologie et conditions de vie sous le COVID-19*”) French cohort was initiated in 2020, randomly selecting 371,000 participants aged≥15 y in 2020, living in mainland France or in three overseas territories (Martinique, Guadeloupe, and Reunion) from the national tax database (96.4% coverage). The sampling frame was designed to overrepresent underprivileged populations to ensure sufficient statistical power to study social inequalities. People living in medical retirement homes or prisons were not invited to participate in the study [35]. Four waves of data collection were conducted and the present cross-sectional analysis is principally based on the fourth wave, which took place between September 12 and December 5, 2022. Self-computer-assisted web interviews (CAWIs) or computer-assisted telephone interviews (CATIs) was randomly assigned to each participant to collect the data. At the fourth wave, a total of 84,492 participants completed the questionnaire; among them, we included participants aged 18–25 y in 2022 in this study.

All participants provided informed consent to participate
in the EpiCov study, which received approval from an ethics
committee (Comité de Protection des Personnes Sud Médi-
terranée III 2020-A01191-38) and from France's National
Data Protection Agency (*Commission Nationale Informa-
tique et Libertés*, CNIL, MLD/MFI/AR205138).

Data collection

All information described below was based on data col-
lected during the fourth wave in September–December
2022, where not specified.

Moderator: self-defined sexual orientation

Self-defined sexual orientation data were collected using the
following question: currently, you define yourself as 1) het-
erosexual, 2) homosexual, gay or lesbian (people who have
sexual relations with people of the same sex), 3) bisexual
(people who have sexual relations with people of the same
or opposite sex), 4) you don't define yourself by your sexu-
ality, 5) other, 6) you do not wish to answer. Importantly,
this question was only asked to adult participants who
reported not living with a partner at the fourth wave. The
authors of the present work decided not to derive the defi-
nition of sexual orientation from the sex of the partner for
participants living with a partner, to avoid misclassification
bias. For example, a person can self-identify as bisexual and
be currently living with a same-sex partner. The analyses
were therefore restricted to participants who answered the
question on self-defined sexual orientation, thus who were
living without partners. Participants defining themselves as
homosexual, bisexual, other, or not defining themselves by
their sexuality were categorized into the Sexual Minority
(SM) group in the present study. Thus, participants who
defined themselves as heterosexual or not wishing to answer
were categorized into the Not belonging to Sexual Minor-
ity (NSM; reference group). Participants who reported not
defining themselves by their sexuality were grouped with
those who reported being homosexual, bisexual, and other
as they shared the same distributions of sociodemographic
and health characteristics. Likewise, participants report-
ing not wishing to answer were grouped with participants
reporting being heterosexual, given similarity of their
sociodemographic and health-related characteristics. Nota-
bly, the prevalence of depressive symptoms and suicidal ide-
ation was low in those who did not wish to response to the
question on sexual orientation. The distribution of sociode-
mographic and health characteristics according to detailed
sexual orientation is presented in Supplementary Table S1.

Outcomes: depressive symptoms and suicidal ideation

Depressive symptoms within 15 days before the response
date were assessed using the 9 items of the Patient Health

Questionnaire (PHQ-9) [36]. Score ranges from 0 to 27 and a score≥10 was considered as having moderate to severe depressive symptoms (yes/no) [37]. This cut-off score was the most used score in PHQ-9 validation studies and optimal for detecting major depressive disorder [37]. Suicidal ideation was assessed using the following question: “In the last 12 months, have you thought about killing yourself by suicide (yes/no)?”.

Exposures: social factors

On the basis of prior evidence, the following well-known
social factors associated with depressive symptoms and sui-
cidality [38, 39] were selected: sex (female vs male, data
from the National Institute for Statistics and Economic Stud-
ies: INSEE), age category (22–25 vs 18–21 y), educational
attainment (≤high school vs>high school), employment
status (not being employed vs being employed), perceived
financial difficulties (yes vs no), being in a relationship (no
vs yes), and living alone (yes vs no). The urban density of
living area in 2018 (rural=reference; intermediate; high or
Paris area) was obtained from INSEE. We also included
self-reported history of discrimination in the last 5 years
(yes vs no). The questions and response modalities are pre-
sented in Supplementary Table S2.

Covariates

Covariates included the presence of self-reported chronic
health conditions or disabilities and a history of mental dis-
order diagnosis, which are not expected to influence some
exposures but are associated with both the moderator and
outcomes. We also included the questionnaire type (CAWIs;
CATIs) of the fourth wave to account for potential desirabil-
ity bias due to the survey mode. The questions and response
modalities are presented in Supplementary Table S2.

Statistical analyses

We excluded participants with missing data on outcomes
and/or sexual orientation, which are the main variables of
interest in the present study. Thus, a total of 6,337 partici-
pants aged 18–25 y was included in the analyses (Fig. 1).
The comparison of characteristics between the included and
excluded participants is presented in Supplementary Table
S3. Briefly, the included participants were more likely to be
male, 22–25 y, have suicidal ideation, and less likely to have
depressive symptoms than those excluded from the analy-
ses. The characteristics of the included participants are pre-
sented in the full analyzed sample and according to sexual
orientation (Table 1), depressive symptoms (Supplementary
Table S4), and suicidal ideation (Supplementary Table S5).
<figure><img src="image_2.png" /><figcaption>Fig. 1 Flowchart of participants</figcaption></figure>

As preliminary analyses, the multiplicative interaction between sexual orientation (moderator) and each social factor (exposure) on the association with each outcome was tested using Poisson regression models with robust error variance [40] to identify interaction terms that would be included in the main model (p<0.2, described below). The

Poisson regression model with robust error variable allows to estimate prevalence ratio, which can address issues of overestimation of associations estimated by Odds Ratios in logistic regression while also being more straightforward to interpret [41]. Each model was run, including all exposures, questionnaire type, and an interaction term between sexual
orientation and each exposure. The results for each model are presented using a common exposure reference group (no risk factor and NSM group) to present the adjusted Prevalence Ratio (aPR) of each category according to social factors and sexual orientation, as recommended by Vander-Weele et al. [42] (Supplementary Figure S1 and S2). This presentation allows us to examine adjusted associations between sexual orientation and each outcome that cannot be observed in stratified analyses by sexual orientation (i.e., main analyses, see below).

For the main analyses, we first run a Poisson regression model with robust error variance for each outcome including all exposures, thus mutually adjusted, questionnaire type, and interaction terms between sexual orientation and exposures having $p<0.2$ in the preliminary analyses to obtain adjusted Interaction Ratio (IR). IR is calculated by dividing the observed joint effect of the moderator and exposure by the multiplication of their independent effects, which correspond to the exponentiate of beta coefficient of interaction term in regression models [42]. When the moderator and exposure increase the risk of outcome, an $IR>1$ indicates a positive multiplicative interaction (observed joint effect is greater than expected), while an $IR<1$ indicates a negative multiplicative interaction (observed joint effect is smaller than expected). When the IR is equal to 1, there is no multiplicative interaction [42]. Afterwards, we ran a Poisson regression model with robust error variance for each outcome, including all exposures and questionnaire type, stratified by sexual orientation to obtain aPR for each exposure according to sexual orientation (Fig. 2 and 3).

In the sensitivity analyses, we repeated the procedure described above by adding chronic health conditions and a history of mental disorder diagnosis as covariates to the main model in order to take into account their potential effect on the associations between social factors and depressive symptoms or suicidal ideation (Supplementary Figure S3–S6). An additional sensitivity analysis was conducted excluding participant who did not wish to report their sexual orientation to consider potential differences from participants who reported a heterosexual orientation (Supplementary Figure S7–S10). For the preliminary, main, and sensitivity analyses, social factors and/or covariates with missing values were imputed by Multivariate Imputation by Chained Equations assuming that data were missing at random (10 imputation sets: 10.8% in the study sample had missing data on at least one social factor) [43].

Data management was performed using SAS v9.4. Missing value imputation, descriptive, bivariate, and regression analyses were performed using R 4.0. Study weights were applied to descriptive, bivariate, and regression analyses to account for EpiCov's survey design and non-participation bias (detailed elsewhere [44]). In brief, survey weights

were based on demographic and socioeconomic indicators obtained from the FIDELI database and EpiCov previous waves that may be relevant to response probabilities. The margins were also adjusted for general population based on census data and population projections. All tests were two-sided and $p<0.05$ was considered as evidence for statistical significance.

# Results

## Characteristics of the participants

Among 6,337 participants of the fourth wave of the EpiCov study, aged 18–25 y with available data on sexual orientation and both study outcomes, 11.0 [10.1–12.1] % belonged to the SM group, and 15.1 [14.0–16.3] % and 7.4 [6.7–8.2] % presented depressive symptoms and suicidal ideation, respectively. 45.6 [43.9–47.3] % were female and 38.4 [36.8–39.9] % had an educational attainment higher than high school. Participants in the SM group were more likely to be women, live alone, experience discrimination, have chronic health conditions, and have been diagnosed with mental disorders than their counterparts. They were more likely to experience depressive symptoms (33.9 [29.6–38.4] %) and suicidal ideation (23.0 [19.5–26.8] %) than those in the NSM group (12.8 [11.6–14.0] % and 5.5 [4.77–6.28] %, respectively) (Table 1). Likewise, participants in the SM group had increased aPRs for depressive symptoms and suicidal ideation compared to the reference group (no risk factor and NSM group) in all models (Supplementary Figure S1 and S2).

## Moderating effects of sexual orientation on the associations between social factors, depressive symptoms, and suicidal ideation

For depressive symptoms, significant negative interactions (observed joint effect is smaller than expected) were observed between sexual orientation and female sex (IR 0.64 [0.46–0.91]) and 22–25 y age category (IR 0.62 [0.44–0.86]) (Fig. 2). Accordingly, in the Poisson regression model stratified by sexual orientation, female individuals in the NSM group had a higher prevalence of depressive symptoms than their male counterpart (aPR: 1.58 [1.28–1.95]), whereas no significant difference in prevalence was observed between sexes in the SM group (PR: 1.03 [0.78–1.36]) (Fig. 2). Likewise, individuals in the NSM group aged 22–25 y had a higher prevalence of depressive symptoms than their 18–21 y counterparts (PR: 1.32 [1.05–1.67]), whereas no significant difference in prevalence was observed between the age groups in the SM group (0.78
<table><caption>**Table 1** Characteristics of participants aged 18–25y in the full analyzed sample and according to sexual orientation (N=6,337; EpiCov study in 2022; not imputed)</caption><thead><tr><th>Characteristic</th><th>Full sample,<br>N=6,337<sup>1</sup></th><th>95% CI<sup>2</sup></th><th>NSM group,<br>N=5,594<sup>1</sup></th><th>95% CI<sup>2</sup></th><th>SM group, N=743<sup>1</sup></th><th>95% CI<sup>2</sup></th><th>p-value<sup>3</sup></th></tr></thead><tbody><tr><td>Depressive symptoms during last 15 days</td><td></td><td></td><td></td><td></td><td></td><td></td><td>&lt;0.001</td></tr><tr><td>Yes</td><td>15.1% (958)</td><td>14.0%, 16.3%</td><td>12.8% (697)</td><td>11.6%, 14.0%</td><td>33.9% (261)</td><td>29.6%, 38.4%</td><td></td></tr><tr><td>Suicidal ideation during last 12 months</td><td></td><td></td><td></td><td></td><td></td><td></td><td>&lt;0.001</td></tr><tr><td>Yes</td><td>7.4%<br>(511)</td><td>6.65%, 8.23%</td><td>5.5% (318)</td><td>4.77%, 6.28%</td><td>23.0% (193)</td><td>19.5%, 26.8%</td><td></td></tr><tr><td>Sex</td><td></td><td></td><td></td><td></td><td></td><td></td><td>&lt;0.001</td></tr><tr><td>Female</td><td>45.6% (3,149)</td><td>43.9%, 47.3%</td><td>44.1% (2,693)</td><td>42.3%, 46.0%</td><td>57.0% (456)</td><td>51.7%, 62.1%</td><td></td></tr><tr><td>Age category</td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.738</td></tr><tr><td>18–21 y</td><td>46.2% (2,757)</td><td>44.5%, 47.9%</td><td>46.3% (2,436)</td><td>44.5%, 48.1%</td><td>45.4% (321)</td><td>40.5%, 50.4%</td><td></td></tr><tr><td>22–25 y</td><td>53.8% (3,580)</td><td>52.1%, 55.5%</td><td>53.7% (3,158)</td><td>51.9%, 55.5%</td><td>54.6% (422)</td><td>49.6%, 59.5%</td><td></td></tr><tr><td>Educational attainment higher than high school</td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.986</td></tr><tr><td>Yes</td><td>38.4% (2,663)</td><td>36.8%, 39.9%</td><td>38.4% (2,356)</td><td>36.7%, 40.0%</td><td>38.3% (307)</td><td>33.9%, 43.0%</td><td></td></tr><tr><td>Being employed</td><td></td><td></td><td></td><td></td><td></td><td></td><td>&lt;0.001</td></tr><tr><td>Yes</td><td>29.0% (1,655)</td><td>27.5%, 30.6%</td><td>30.0% (1,514)</td><td>28.3%, 31.7%</td><td>21.5% (141)</td><td>17.8%, 25.7%</td><td></td></tr><tr><td>Perceived financial difficulties</td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.155</td></tr><tr><td>Yes</td><td>12.1% (681)</td><td>10.9%, 13.3%</td><td>11.8% (584)</td><td>10.6%, 13.1%</td><td>14.3% (97)</td><td>11.2%, 18.1%</td><td></td></tr><tr><td>In a relationship</td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.603</td></tr><tr><td>Yes</td><td>25.4% (1,772)</td><td>24.1%, 26.8%</td><td>25.5% (1,576)</td><td>24.1%, 27.0%</td><td>24.4% (196)</td><td>20.8%, 28.5%</td><td></td></tr><tr><td>Living alone</td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.004</td></tr><tr><td>Yes</td><td>26.9% (1,804)</td><td>25.5%, 28.4%</td><td>26.2% (1,558)</td><td>24.7%, 27.7%</td><td>33.0% (246)</td><td>28.6%, 37.7%</td><td></td></tr><tr><td>Urban density</td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.683</td></tr><tr><td>Rural</td><td>23.4% (1,552)</td><td>22.0%, 24.8%</td><td>23.5% (1,396)</td><td>22.1%, 25.1%</td><td>22.3% (156)</td><td>18.3%, 27.0%</td><td></td></tr><tr><td>Intermediate</td><td>60.2% (3,894)</td><td>58.6%, 61.9%</td><td>60.3% (3,412)</td><td>58.5%, 62.0%</td><td>59.7% (482)</td><td>54.6%, 64.7%</td><td></td></tr><tr><td>High—Paris area</td><td>16.4% (891)</td><td>15.1%, 17.8%</td><td>16.2% (786)</td><td>14.8%, 17.6%</td><td>17.9% (105)</td><td>13.9%, 22.9%</td><td></td></tr><tr><td>Experience of discrimination in the last 5 y</td><td></td><td></td><td></td><td></td><td></td><td></td><td>&lt;0.001</td></tr><tr><td>Yes</td><td>20.9% (1,346)</td><td>19.6%, 22.3%</td><td>19.5% (1,089)</td><td>18.1%, 20.9%</td><td>32.7% (257)</td><td>28.5%, 37.2%</td><td></td></tr><tr><td>Chronic somatic or mental conditions</td><td></td><td></td><td></td><td></td><td></td><td></td><td>&lt;0.001</td></tr><tr><td>Yes</td><td>24.6% (1,539)</td><td>23.2%, 26.1%</td><td>23.6% (1,292)</td><td>22.2%, 25.2%</td><td>32.7% (247)</td><td>28.2%, 37.6%</td><td></td></tr><tr><td>History of mental disorders diagnosis</td><td></td><td></td><td></td><td></td><td></td><td></td><td>&lt;0.001</td></tr><tr><td>Yes</td><td>7.5% (533)</td><td>6.76%, 8.40%</td><td>6.0% (365)</td><td>5.23%, 6.78%</td><td>20.2% (168)</td><td>16.7%, 24.3%</td><td></td></tr><tr><td>Web questionnaire type</td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.016</td></tr><tr><td>Yes</td><td>70.8% (4,592)</td><td>69.2%, 72.3%</td><td>70.1% (4,011)</td><td>68.5%, 71.7%</td><td>76.1% (581)</td><td>71.6%, 80.1%</td><td></td></tr></tbody></table>

Sex, educational attainment, being employed, perceived financial difficulties, living alone, experience of discrimination, chronic somatic and mental conditions, history of mental disorders diagnosis contained 545, 2, 1, 24, 8, 9, 76, and 2 missing values, respectively

NSM: Not belonging to Sexual Minority, SM: Sexual Minority

[0.59–1.03]). Regarding suicidal ideation, we observed significant negative interactions (observed joint effect is smaller than expected) between sexual orientation and not being in relationship (IR 0.52 [0.33–0.81]) (Fig. 3). In the Poisson regression stratified by sexual orientation, individuals not being in a relationship in the NSM group had a higher prevalence of suicidal ideation than those being in a relationship (aPR: 1.55 [1.14–2.12]), whereas no significant difference in prevalence was observed according to relationship status in the SM group (aPR 0.82 [0.59–1.13]) (Fig. 3). No positive interactions were detected.

## Sensitivity analyses

In the sensitivity analyses, which adjusted for chronic health conditions and a history of diagnosed mental disorders, as well as for those excluding participants who did not wish to report their sexual orientation, similar results to those from the main analyses were obtained. Nonetheless, some interactions that were borderline significant in the main analyses became significant in the sensitivity analyses (Supplementary Figure S5, S6, S9, and S10).

<footnote n="1">¹ Weighted % (n (unweighted))</footnote>

<footnote n="2">² CI=Confidence Interval</footnote>

<footnote n="3">³ chi-squared test with Rao & Scott's second-order correction (NSM vs SM)</footnote>
<table><caption>**Fig. 2** Associations between social factors and depressive symptoms according to sexual orientation (N=6,337 aged 18–25y; EpiCov study in 2022; weighted and pooled)</caption><thead><tr><th>Factor</th><th>n case/N total</th><th>PR(CI95%)</th><th>p value</th><th>Prevalence ratio</th></tr></thead><tbody><tr><td>Sex at birth</td><td>IR</td><td>0.64 (0.46 – 0.91)</td><td>0.012</td><td></td></tr><tr><td>Male:NSM</td><td>194/2401</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Female:NSM</td><td>434/2693</td><td>1.58 (1.28 – 1.95)</td><td>&lt;0.001</td><td>●</td></tr><tr><td>Male:SM</td><td>75/242</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Female:SM</td><td>169/456</td><td>1.03 (0.78 – 1.36)</td><td>0.819</td><td>●</td></tr><tr><td>Age category</td><td>IR</td><td>0.62 (0.44 – 0.86)</td><td>0.004</td><td></td></tr><tr><td>18 – 21 y:NSM</td><td>378/3158</td><td>1.00</td><td></td><td>●</td></tr><tr><td>22 – 25 y:NSM</td><td>319/2436</td><td>1.32 (1.05 – 1.67)</td><td>0.020</td><td>●</td></tr><tr><td>18 – 21 y:SM</td><td>163/422</td><td>1.00</td><td></td><td>●</td></tr><tr><td>22 – 25 y:SM</td><td>98/321</td><td>0.78 (0.59 – 1.03)</td><td>0.084</td><td>●</td></tr><tr><td>Educational attainment</td><td>IR</td><td>NS</td><td></td><td></td></tr><tr><td>Higher than bac:NSM</td><td>297/2356</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Bac and lower:NSM</td><td>400/3236</td><td>1.12 (0.90 – 1.39)</td><td>0.329</td><td>●</td></tr><tr><td>Higher than bac:SM</td><td>96/307</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Bac and lower:SM</td><td>165/436</td><td>1.11 (0.83 – 1.48)</td><td>0.474</td><td>●</td></tr><tr><td>Employment status</td><td>IR</td><td>NS</td><td></td><td></td></tr><tr><td>Being employed:NSM</td><td>135/1514</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Not being employed:NSM</td><td>562/4079</td><td>1.66 (1.27 – 2.18)</td><td>&lt;0.001</td><td>●</td></tr><tr><td>Being employed:SM</td><td>38/141</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Not being employed:SM</td><td>223/602</td><td>1.15 (0.81 – 1.64)</td><td>0.420</td><td>●</td></tr><tr><td>Perceived financial difficulties</td><td>IR</td><td>NS</td><td></td><td></td></tr><tr><td>No:NSM</td><td>553/4990</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Yes:NSM</td><td>143/584</td><td>1.70 (1.35 – 2.14)</td><td>&lt;0.001</td><td>●</td></tr><tr><td>No:SM</td><td>203/642</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Yes:SM</td><td>56/97</td><td>1.54 (1.14 – 2.06)</td><td>0.004</td><td>●</td></tr><tr><td>In relationship</td><td>IR</td><td>NS</td><td></td><td></td></tr><tr><td>Yes:NSM</td><td>208/1576</td><td>1.00</td><td></td><td>●</td></tr><tr><td>No:NSM</td><td>489/4018</td><td>1.05 (0.86 – 1.30)</td><td>0.623</td><td>●</td></tr><tr><td>Yes:SM</td><td>75/196</td><td>1.00</td><td></td><td>●</td></tr><tr><td>No:SM</td><td>186/547</td><td>0.94 (0.72 – 1.22)</td><td>0.629</td><td>●</td></tr><tr><td>Living alone</td><td>IR</td><td>0.80 (0.58 – 1.11)</td><td>0.179</td><td></td></tr><tr><td>No:NSM</td><td>452/4030</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Yes:NSM</td><td>244/1558</td><td>1.37 (1.12 – 1.67)</td><td>0.002</td><td>●</td></tr><tr><td>No:SM</td><td>178/495</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Yes:SM</td><td>82/246</td><td>1.06 (0.80 – 1.39)</td><td>0.702</td><td>●</td></tr><tr><td>Urban density</td><td>IR</td><td>NS</td><td></td><td></td></tr><tr><td>Rural:NSM</td><td>159/1396</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Intermediate:NSM</td><td>438/3412</td><td>0.96 (0.76 – 1.21)</td><td>0.712</td><td>●</td></tr><tr><td>Rural:SM</td><td>53/156</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Intermediate:SM</td><td>168/482</td><td>1.05 (0.77 – 1.44)</td><td>0.739</td><td>●</td></tr><tr><td>Urban density</td><td>IR</td><td>NS</td><td></td><td></td></tr><tr><td>Rural:NSM</td><td>159/1396</td><td>1.00</td><td></td><td>●</td></tr><tr><td>High-Paris:NSM</td><td>100/786</td><td>1.08 (0.79 – 1.49)</td><td>0.631</td><td>●</td></tr><tr><td>Rural:SM</td><td>53/156</td><td>1.00</td><td></td><td>●</td></tr><tr><td>High-Paris:SM</td><td>40/105</td><td>1.02 (0.66 – 1.58)</td><td>0.927</td><td>●</td></tr><tr><td>Discrimination</td><td>IR</td><td>0.78 (0.57 – 1.06)</td><td>0.112</td><td></td></tr><tr><td>No:NSM</td><td>417/4496</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Yes:NSM</td><td>279/1089</td><td>2.40 (1.96 – 2.94)</td><td>&lt;0.001</td><td>●</td></tr><tr><td>No:SM</td><td>128/486</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Yes:SM</td><td>133/257</td><td>1.88 (1.46 – 2.43)</td><td>&lt;0.001</td><td>●</td></tr></tbody><tfoot><tr><td colspan="5">PR: Prevalence ratio, CI: Confidence interval, NS: Interaction test non significatif in preliminary analysis<br>NSM: Not belonging to sexual minority, IR: Interaction ratio, SM: Sexual minority</td></tr></tfoot></table>
<table><caption>**Fig. 3** Associations between social factors and suicidal ideation according to sexual orientation (N=6,337 aged 18–25y; EpiCov study in 2022; weighted and pooled)</caption><thead><tr><th>Factor</th><th>n case/N total</th><th>PR(CI95%)</th><th>p value</th><th>Prevalence ratio</th></tr></thead><tbody><tr><td>Sex at birth</td><td>IR</td><td></td><td>NS</td><td></td></tr><tr><td>Male:NSM</td><td>107/2401</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Female:NSM</td><td>190/2693</td><td>1.36 (1.01 – 1.82)</td><td>0.043</td><td>●</td></tr><tr><td>Male:SM</td><td>56/242</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Female:SM</td><td>124/456</td><td>1.17 (0.82 – 1.67)</td><td>0.382</td><td>●</td></tr><tr><td>Age category</td><td>IR</td><td></td><td>NS</td><td></td></tr><tr><td>18 – 21 y:NSM</td><td>169/3158</td><td>1.00</td><td></td><td>●</td></tr><tr><td>22 – 25 y:NSM</td><td>149/2436</td><td>1.37 (0.97 – 1.93)</td><td>0.078</td><td>●</td></tr><tr><td>18 – 21 y:SM</td><td>108/422</td><td>1.00</td><td></td><td>●</td></tr><tr><td>22 – 25 y:SM</td><td>85/321</td><td>1.07 (0.77 – 1.47)</td><td>0.698</td><td>●</td></tr><tr><td>Educational attainment</td><td>IR</td><td></td><td>NS</td><td></td></tr><tr><td>Higher than bac:NSM</td><td>132/2356</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Bac and lower:NSM</td><td>186/3236</td><td>1.28 (0.93 – 1.76)</td><td>0.124</td><td>●</td></tr><tr><td>Higher than bac:SM</td><td>74/307</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Bac and lower:SM</td><td>119/436</td><td>1.04 (0.75 – 1.44)</td><td>0.811</td><td>●</td></tr><tr><td>Employment status</td><td>IR</td><td>0.62 (0.36 – 1.07)</td><td>0.085</td><td></td></tr><tr><td>Being employed:NSM</td><td>62/1514</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Not being employed:NSM</td><td>256/4079</td><td>1.89 (1.29 – 2.79)</td><td>0.001</td><td>●</td></tr><tr><td>Being employed:SM</td><td>31/141</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Not being employed:SM</td><td>162/602</td><td>1.17 (0.78 – 1.76)</td><td>0.445</td><td>●</td></tr><tr><td>Perceived financial difficulties</td><td>IR</td><td>0.60 (0.35 – 1.02)</td><td>0.058</td><td></td></tr><tr><td>No:NSM</td><td>257/4990</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Yes:NSM</td><td>61/584</td><td>1.55 (1.08 – 2.22)</td><td>0.018</td><td>●</td></tr><tr><td>No:SM</td><td>161/642</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Yes:SM</td><td>31/97</td><td>0.91 (0.61 – 1.36)</td><td>0.639</td><td>●</td></tr><tr><td>In relationship</td><td>IR</td><td>0.52 (0.33 – 0.81)</td><td>0.004</td><td></td></tr><tr><td>Yes:NSM</td><td>71/1576</td><td>1.00</td><td></td><td>●</td></tr><tr><td>No:NSM</td><td>247/4018</td><td>1.55 (1.14 – 2.12)</td><td>0.005</td><td>●</td></tr><tr><td>Yes:SM</td><td>58/196</td><td>1.00</td><td></td><td>●</td></tr><tr><td>No:SM</td><td>135/547</td><td>0.82 (0.59 – 1.13)</td><td>0.221</td><td>●</td></tr><tr><td>Living alone</td><td>IR</td><td>0.64 (0.41 – 1.01)</td><td>0.057</td><td></td></tr><tr><td>No:NSM</td><td>206/4030</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Yes:NSM</td><td>111/1558</td><td>1.55 (1.13 – 2.11)</td><td>0.006</td><td>●</td></tr><tr><td>No:SM</td><td>132/495</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Yes:SM</td><td>61/246</td><td>0.96 (0.68 – 1.34)</td><td>0.797</td><td>●</td></tr><tr><td>Urban density</td><td>IR</td><td></td><td>NS</td><td></td></tr><tr><td>Rural:NSM</td><td>61/1396</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Intermediate:NSM</td><td>205/3412</td><td>1.17 (0.82 – 1.67)</td><td>0.380</td><td>●</td></tr><tr><td>Rural:SM</td><td>42/156</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Intermediate:SM</td><td>122/482</td><td>1.06 (0.72 – 1.56)</td><td>0.780</td><td>●</td></tr><tr><td>Urban density</td><td>IR</td><td></td><td>NS</td><td></td></tr><tr><td>Rural:NSM</td><td>61/1396</td><td>1.00</td><td></td><td>●</td></tr><tr><td>High-Paris:NSM</td><td>52/786</td><td>1.41 (0.91 – 2.20)</td><td>0.124</td><td>●</td></tr><tr><td>Rural:SM</td><td>42/156</td><td>1.00</td><td></td><td>●</td></tr><tr><td>High-Paris:SM</td><td>29/105</td><td>0.88 (0.51 – 1.50)</td><td>0.634</td><td>●</td></tr><tr><td>Discrimination</td><td>IR</td><td>0.75 (0.49 – 1.15)</td><td>0.187</td><td></td></tr><tr><td>No:NSM</td><td>179/4496</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Yes:NSM</td><td>137/1089</td><td>2.62 (1.97 – 3.49)</td><td>&lt;0.001</td><td>●</td></tr><tr><td>No:SM</td><td>97/486</td><td>1.00</td><td></td><td>●</td></tr><tr><td>Yes:SM</td><td>96/257</td><td>1.99 (1.46 – 2.72)</td><td>&lt;0.001</td><td>●</td></tr></tbody><tfoot><tr><td colspan="5">PR: Prevalence ratio, CI: Confidence interval, NS: Interaction test non significatif in preliminary analysis<br>NSM: Not belonging to sexual minority, IR: Interaction ratio, SM: Sexual minority</td></tr><tr><td colspan="5">0.6 1 1.6 2.7</td></tr></tfoot></table>
Discussion

In line with previous findings, in this recent French pop-
ulation-based study, young adults defining themselves as
lesbian, gay, bisexual, other, or not defining themselves
by their sexual orientation were more likely to suffer from
depressive symptoms and suicidal ideation than youth iden-
tifying as heterosexual or preferring not to answer. How-
ever, some known social risk factors for mental health were
found to be associated with depressive symptoms or suicidal
ideation only in young adults who identified as heterosexual
or preferring not to answer, thus not explaining the higher
risk observed in lesbian, gay, bisexual, and not self-defining
young adults. Therefore, depression and suicidal ideation
may be explained by specific underlying mechanisms in
these young adults.

Our results suggest that participants with female sex
(vs male participants) and those aged 22–25 y in 2022 (vs
those aged 18–21 y) had a higher prevalence of depressive
symptoms only in the NSM group, not in the SM group.
To the best of our knowledge, no study has explored the
moderating effects of sexual orientation on the associa-
tions between sex and depression. However, various stud-
ies have explored the moderating effects of sex on the
associations between sexual orientation and mental health,
with inconsistent results. A French study with a nationally
representative sample reported that the risk of depression
associated with having same-sex partners is higher in men
than in women [33]. Another French national survey indi-
cated that the association between being homosexual and
depressive symptoms may be greater in women than in
men, and that the association between being bisexual and
depressive symptoms was smaller in women than in men
[34]. However, a nationally representative Swedish study
examining associations between sexual orientation and
depression diagnosis by gender observed that being homo-
sexual had a smaller association with lifetime diagnostic of
depression in women than in men, while being bisexual had
greater association in women than in men [45]. With respect
to age, a prior study in a sample from the general popula-
tion reported a U-shaped relationship between psychologi-
cal well-being and age, with the lowest levels of well-being
around ages 45–54y, which is consistent with our results
observed in the NSM group [46]. Although this association
was not observed in the SM group in our study, a system-
atic review on the prevalence of major depressive disorders
among LGBTQI+people, including 48 articles comprising
4,616,903 individuals, suggested that age was positively
associated with a higher prevalence [47]. Our results need
to be confirmed by future studies, given that we identified
no study investigating the moderating effects of sexual
orientation on the association between age and depressive

symptoms in young adults. Regarding suicidal ideation, our results suggested that single young adults had a higher prevalence of suicidal ideation than those in a relationship in the NSM group, but not in the SM group. Although we observed no study on the moderating effects of sexual orientation on the association between relationship status and suicidal ideation, a study with a sample of 232 college students from the Philippines reported that being in a relationship may be a risk factor for anxiety and depression among non-heterosexual students, while it was a protective factor among heterosexual students [48]. Our results suggest that being single may not be a risk factor for suicidal ideation among people who define themselves as lesbian, gay, bisexual, other, or not defining themselves by their sexuality. Indeed, disclosure of a sexual minority could be a stressful event, which impact negatively on their mental health [5, 49]. Overall, the modification effects of sexual orientation on the associations between social factors and depressive symptoms/suicidal ideation depend on the study samples, studied variables, period, and how variables are modeled [24–30]. Along with the fact that we identified no study on the moderating effects of sexual orientation observed in the present study, our findings need to be confirmed by future studies using similar study samples and social factors.

In the sensitivity analyses with additional adjustment for chronic health conditions and history of diagnosed mental disorders, we additionally observed moderating effects of sexual orientation on employment status, living in high-population density areas, and discrimination. This may be attributed to the fact that aPR values decreased only in the SM group but not in the NSM group in the sensitivity analyses. Thus, chronic health conditions and a history of mental disorders diagnosis could have important effects on the relationship between these social factors and depressive symptoms and/or suicidal ideation in the SM group, but not in the NSM group. Regarding participants’ experience of discrimination, while those who experienced discrimination had a higher prevalence of depressive symptoms and suicidal ideation than those who did not experience discrimination in both the NSM and the SM groups, the associations between discrimination and outcomes were smaller in the SM group compared to the NSM group. Prior studies have indeed reported that the effects of victimization, bullying, or discrimination for depressive symptoms and suicidal ideation/thoughts were smaller in those belonging to the sexual minority community than who do not in samples of adolescents, high school, and university students [27, 28, 50, 51], which is consistent with our findings. Regarding the sensitivity analyses excluding participants who did not wish to report their sexual orientation, although results for employment status (depressive symptoms) and for perceived financial difficulties (suicidal ideation) became statistically
significant, the values of IR were similar to those of main
analyses. Furthermore, we observed no other statistical
change from main analyses, which indicates that there are
no statistical differences in modification effect of sexual ori-
entation between the sensitivity and main analyses.

Although participants belonging to the SM group were
more likely to report depressive symptoms and suicidal ide-
ation than those in the NSM group, we observed no social
factors having a greater association with depressive symp-
toms or suicidal ideation in the SM group than in the NSM
group. Therefore, unmeasured factors that could not be
explored in this study, may mainly contribute to the elevated
prevalence of depressive symptoms and suicidal ideation, as
described in the minority stress theory [4, 5]. Indeed, prior
studies have reported higher levels of internalized stigma,
stigma awareness, perceived stigma, and lower levels of
perceived safety in sexual minority populations than in their
heterosexual counterparts [49]. Concealment and disclosure
of sexuality may also have harmful effects on their mental
health [5, 49]. In addition, because of the long history of
labelling ‘homosexuality’ in international and national dis-
ease classification frameworks, which can be stigmatizing,
people belonging to sexual minorities are less likely to seek
help because of the potential negative attitudes of health ser-
vice providers [52]. Thus, they may be less likely to receive
psychiatric treatment. Furthermore, although same-sex mar-
riage has been permitted since 2013 in France, structural
stigma, defined as cultural norms and institutional policies
at the social level that constrain opportunities, resources,
and well-being, may still be present in today’s society [6,
49]. Finally, a new field is emerging in twin and sibling
studies using Cholesky's ACE model, which investigates
childhood factors (genetic, shared environmental, and non-
shared environmental factors) in relation to sexual orienta-
tion, depressive symptoms, and suicide attempts [53, 54].
These studies suggested that the increased risk of depres-
sion associated with same-sex marriage was partially due to
genetic factors among women [54] and that the covariance
of genetic factors between sexual orientation and depressive
symptoms was greatest at high levels of childhood gender
nonconformity, whereas that of environmental effects was
greatest at low levels of childhood gender nonconformity
[53].

Limitations and strengths

The limitations of the present study should be noted. First,
the question on sexual orientation in the EpiCov cohort was
only asked to adult participants not living with a partner,
and we decided not to use information on the sex of partner
to avoid misclassification bias. Therefore, the results of the

present study cannot be generalized to young people liv-
ing with a partner. However, it should be noted that 81.6%
of EpiCov participants aged 18–25y were included in the
present analyses. Second, the cross-sectional study design
prevents causal inference. Future longitudinal studies could
elucidate the chronology of the associations. Third, catego-
rization of continuous variables (e.g., PHQ-9 score, age)
may lead to information loss. Finally, because of a meth-
odological constraint regarding number of participants, we
grouped diverse categories of sexual orientation in a sin-
gle group (i.e., SM group), which may oversimplify their
diverse experiences. Despite these limitations, this study
has several important strengths. To our knowledge, this is
the first large-scale epidemiological study to investigate the
moderating effects of sexual orientation on the associations
between on various social factors, depressive symptoms,
and suicidal ideation in young adults. Data were collected
in 2022; thus, the results represent the recent situation in
France. The observed moderating effects and associations
were controlled for the main sociodemographic and health-
related risk factors of depression and suicidality. Finally,
EpiCov participants were randomly selected from a national
tax database covering more than 96% of the general popula-
tion living in France, and data were weighted to account for
non-response, thus reducing potential selection bias.

Conclusions

This study suggests that in 2022, young adults who identi-
fied as lesbian, gay, bisexual, other, or not defining them-
selves by their sexual orientation are still more likely to
experience depressive symptoms and suicidal ideation than
their counterparts. However, well-known social risk fac-
tors for mental health conditions do not appear to explain
this higher prevalence. This work advocates for continu-
ously assessing factors related to mental health according
to sexual orientation, as well-known factors can become
irrelevant in an ever-evolving context. New generations of
young adults might face different types of adversity than
their predecessors, some of which affect the mental health
of all people and others of which affect the mental health of
specific subgroups. Keeping up with these shared and spe-
cific factors is necessary to implement effective and inclu-
sive mental health policies.

**Supplementary Information** The online version contains
supplementary material available at https://doi.org/10.1007/s00127-0
25-02951-y.

**Acknowledgements** We sincerely thank all the participants in the Epi-
CoV study. We thank Dr. Nathalie Bajos for her contribution to concep-
tualization and methodology of the study. We also thank the INSERM
staff, including, in particular, Carmen Calandra, Karim Ammour,
Jean-Marc Boivent, Jean-Marie Gagliolo, Frédérique Le Saulnier, and Frédéric Robergeau, who worked with considerable dedication and commitment to make it possible to develop, in record time, and to maintain all regulatory, budgetary, technical, and logistical aspects of the EpiCov study. We thank the staff of Santé publique France, and especially Lucie Duchesne, who played a major role in organization and quality assurance for the seroprevalence component of the EpiCov study. We thank the staff of DREES and INSEE, for their collaboration in the implementation of the study, methodological input, sample selection, and the complex development of weights to correct for non-response. We thank the Ipsos staff, including Christophe David and Valérie Blineau in particular, for their major contribution to the quality of data collection. *The EPICOV study group: Josiane Warszawski and Nathalie Bajos (joint principal investigators), Guillaume Bagein, François Beck, Emilie Counil, Florence Jusot, Nathalie Lydié, Claude Martin, Laurence Meyer, Philippe Raynaud, Alexandra Rouquette, Ariane Pailhé, Delphine Rahib, Patrick Sillard, Alexis Spire. Josiane Warszawski, Nathalie Bajos, Guillaume Bagein, François Beck, Emilie Counil, Florence Jusot, Nathalie Lydié, Claude Martin, Laurence Meyer, Philippe Raynaud, Alexandra Rouquette, Ariane Pailhé, Delphine Rahib, Patrick Sillard, Alexis Spire*

**Author contributions** JK conceptualization, methodology, formal analysis, writing – original draft, visualization, project administration; CDP conceptualization, methodology, writing – review and editing, supervision, project administration; AP writing – review and editing; LM methodology, investigation, resources, writing – review and editing, funding acquisition; MM writing – review and editing; CV writing – review and editing; AR conceptualization, methodology, investigation, resources, supervision, project administration, writing – review and editing, funding acquisition; EpiCov study group investigation, data curation.

**Funding** Open access funding provided by Université Paris-Saclay. This research was supported by the Institut National de la Santé et de la Recherche Médicale (INSERM), the French Ministry for Research, Direction de la Recherche, des Etudes, de l'Evaluation et des Statistiques (DREES), the French Ministry for Health, and the Région Ile de France. This project also received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement 101016167 ORCHESTRA (Connecting European Cohorts to Increase Common and Effective Response to SARS-CoV-2 Pandemic) (Pr Meyer), which contributed to the scientific development and allowed us to fund part of the data management.

**Data Availability** The non-aggregated individual data cannot be shared publicly because of European Regulation 2016/679. Nonetheless, these data can be made available after submission to approval of French Ethics and Regulatory Committee procedure (Comité du Secret Statistique, CESREES and CNIL). The EpiCov dataset is available for research purposes on CASD (https://www.casd.eu/).

Declaration

**Conflict of interest** The authors declare no competing interest.

**Ethics statement** The studies involving human participants were reviewed and approved by Comité de Protection des Personnes Sud Méditerranée III 2020- A0119138 and France's National Data Protection Agency (Commission Nationale Informatique et Libertés, CNIL, MLD/MFI/AR205138). The patients/participants provided their written informed consent to participate in this study.

**Open Access** This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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