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. 2023 Apr 10;16(4):1109–1117. doi: 10.1007/s40653-023-00543-z

Adverse Childhood Experiences and ADHD Symptoms Among French College Students

Ashlyn Schwartz 1,2,✉, Cédric Galera 1,3, Hala Kerbage 4,5, Ilaria Montagni 1, Christophe Tzourio 1
PMCID: PMC10689313  PMID: 38045835

Abstract

To examine the relationship between adverse childhood experiences (ACEs) and Attention-deficit Hyperactivity Disorder (ADHD) among college students. We investigated the association between ACEs and ADHD symptoms among French college students enrolled in the i-Share cohort using multivariate logistic regression models. The sample comprised of 1062 participants with a mean age of 20.3 (SD = 2.3) of which 30.6% had no ACEs exposure, 29.6% had 1 ACE, 19.2% had 2 ACEs, and 20.6% had ≥ 3 ACEs. After controlling for potential confounders, every increase in ACE exposure heightened the risk of ADHD symptoms with the respective adjusted Odds Ratios and 95% confidence intervals: 1 ACE: 2.1 (0.7–6.3) / 2 ACEs: 4.5 (2.6–12.8)/ ≥ 3 ACEs: 5.2 (1.8–14.8). Estimates for ADHD symptoms were higher with sexual abuse, emotional and physical neglect, and bullying. Findings suggest that ACEs heighten the risk for developing ADHD symptoms among college students and bear important implications for prevention and clinical practice.

Keywords: Adverse childhood experiences, Attention-deficit Hyperactivity Disorder, College students, Risk factors, Toxic stress, Stress outcomes

Introduction

Attention-deficit Hyperactivity Disorder (ADHD) is a disabling condition affecting 2–8% of college students that frequently persists into emerging adulthood (DuPaul et al., 2009). Many aspects of ADHD inhibit academic success, as students with ADHD are at risk of failing or not completing college education (Frazier et al., 2007; Weyandt et al., 2013). ADHD is frequently associated with other psychiatric comorbidities (e.g., anxiety, depression, substance use disorders) and neurodevelopmental conditions (e.g., learning disabilities), which further impact academic functioning and lead to poor social, economic and health outcomes (Faraone et al., 2000; Jensen & Steinhausen, 2015; Reiff & Tippins, 2004).

While ADHD isn’t adequately explained by one risk factor, genetic factors largely contribute to ADHD (Thapar & Cooper, 2016), with twin studies demonstrating heritability estimates over 70% (Thapar et al., 2013). Several prenatal environmental risk factors are associated with ADHD risk, including low birthweight, prematurity, and pre- and post-natal lead exposure (Sciberras et al., 2017). Environmental exposures can alter biology (e.g., brain structure, epigenetics), demonstrating an interplay between environment and genetics that may augment ADHD risk (Thapar et al., 2013). Psychosocial risk, such as low SES (Russell et al., 2016) or family adversity are correlated with ADHD (Thapar & Cooper, 2016) and may be casual if the exposure was very severe and experienced at an early age (Rutter et al., 2007).

Consequently, adverse childhood experiences (ACES) have been a recent focus of interest. Defined as highly stressful events that occur during childhood, ACEs typically describe the cumulative exposure to neglect, abuse, and household dysfunction (Felitti et al., 1998). ACEs are common among the pediatric and adult population (Crouch et al., 2019; Merrick et al., 2018) and among college students, with up to 76.2% of the latter reporting having at least one ACE (Schwartz et al., 2022). Typically, ACEs cluster, whereby having an increased ACE score is associated with worse health outcomes in adulthood (Lee et al., 2021). ACEs are linked with a wide range of negative health consequences, including increased likelihood of injury, chronic disease, and risky behaviors, and poorer mental and maternal health, education, occupation, and income (CDC, 2019; Park et al., 2021).

The available literature on the relationship between ACEs and ADHD report a greater prevalence of ACEs among people with ADHD, as well as a significant graded relationship between the number of accumulated ACEs and ADHD symptoms and severity (Briscoe-Smith & Hinshaw, 2006; Crouch et al., 2021; Ford et al., 2000; Fuller-Thomson & Lewis, 2015; Fuller-Thomson et al., 2014; Hunt et al., 2017; Jimenez et al., 2017; Ouyang et al., 2008; Zarei et al., 2021). The mechanism underlying this association is hypothesized to be related to the impact of toxic stress on brain development affecting cerebral regions involved in ADHD manifestations, such as impulsivity and emotional dysregulation (Brown et al., 2017; Lugo-Candelas et al., 2021).

It’s important to note that the reverse association may also be true: childhood ADHD symptoms may increase risk of experiencing ACEs. Childhood ADHD symptom presentation, such as poor emotional regulation, impuslivity, or hyperactivity may increase the risk of ACEs through increased family conflict (Harold et al., 2013). Both longitudinal and treatment studies have demonstrated negative or challenged parent–child relationships as a consequence of childhood ADHD symptoms (Harold et al., 2013; Lifford et al., 2009). In a longitudinal study controlling for initial ACEs and child disruptive beahvioral disorders, child ADHD diagnosis predicted subsequent risk for ACEs, confering the most risk for intimate partner violence, parental substance use, and parental incarceration (Lugo-Candelas et al., 2021). While the directionality between ADHD symptoms and ACEs remains uncertain, comorbidity between ACEs and ADHD among university students presents similar clinical considerations.

The majority of available studies investigating the association between ACEs and ADHD symptoms have been conducted in children and adolescents. To our knowledge, only one study has investigated the link between ACEs and ADHD in college students (Windle et al., 2018). Yet the college years period is crucial in terms of later evolution especially in people with ADHD who are more prone to academic failure due to their learning difficulties and executive functioning problems (Dorr & Armstrong, 2019). Understanding the early contributors to ADHD is particularly useful for identifying subgroups of people with ADHD that could benefit from specific interventions. Thus, measuring a wide variety of ACEs, such as abuse, neglect, peer bullying, as well as household dysfunction (e.g., parental mental health and substance use disorders, divorce) (Barnes et al., 2020; Marie-Mitchell et al., 2019) is particularly relevant to have an accurate picture of which ACEs are more contributive to later ADHD symptoms.

To fill these gaps, we have conducted the present study relying on a French college student sample. Our objective was to evaluate the association between ACEs and ADHD among college students, while examining the cumulative exposure of ACEs and the respective contributions of different ACE types.

Methods

Study Population

This study used data from the internet-based Students Health Research Enterprise (i-Share), a prospective French cohort with annual online follow-up questionnaires. Launched in 2013, i-Share evaluates the well-being and health status of university students, including information on ACEs, mental health, substance use, risk behaviors, and socio-demographic factors. To be eligible to participate, students must be enrolled at a university or higher education institution in France, be 18 years or older, and able to read and understand French. Two steps were taken for inclusion in the study, including registering on the website (www.i-share.fr) and completing the baseline questionnaire. Our study utilized data from the baseline questionnaire collected between September 2018 and October 2021. This study was approved by the National Commission for Information Technology and Liberties (CNIL) [DR-2013–019].

Measures

Individual Adverse Childhood Experiences (ACEs)

To analyze the most comprehensive set of ACEs possible from the baseline questionnaire and in line with other ACE instruments (Bethell et al., 2017), we created nine dichotomous (referent = no adverse childhood experience) measures of self-reported adverse experiences occurring before age 18, defined as: emotional abuse (adult caregiver ridiculed/criticized child often or child often had the feeling they had been mistreated emotionally by caregiver); physical abuse (child had ever been beaten by an adult caregiver to the point of having bruises or having to see a doctor or child often had the feeling that they were physically abused by adult caregiver); sexual abuse (adult caregiver ever touched, fondled child sexually or adult caregiver ever threated to hurt child or to lie in order to touch or have sex with child); emotional neglect (adult caregiver often ignored child or made them understand they did not matter or child often had the feeling that the adult caregiver did not want them to be born); physical neglect (child’s basic needs were often overlooked or there was rarely someone there to take care or protect child); parental divorce (parents divorced or separated at or before 18 years of age); parental substance use (either parent often had a problematic alcohol use or had alcohol use disorder or had a drug problem); parental mental illness (child’s mother or father had problems with anxiety or depression); and bullying (child was often the victim of harassment by other children).

Cumulative ACEs

We summed nine dichotomous adverse experiences to create an ordinal ACE score with a range of 0 to 3 + ACEs (due to having limited data in the higher range). Analyses included only cases with no missing data for all nine individual adverse experiences (n = 1174).

Attention-deficit Hyperactivity Disorder (ADHD)

In the baseline questionnaire, the 6-item version of The World Health Organization standardized screening tool: Adult Self Report Scale (ASRS v1.1) was used to assess ADHD symptoms (R. C. Kessler et al., 2005). This questionnaire has demonstrated good reliability and validity for assessing ADHD symptoms among college students (Gray et al., 2014). The ASRS asks about behavior over the 6 previous months, whereby items 1–4 assess inattention symptoms and items 5–6 assess hyperactivity/impulsivity symptoms. A five-point Likert scale is utilized [0 = never often, 4 = very often] where a summary score is calculated (0–24). Higher scores are linked with an increased risk of presenting an ADHD diagnosis. ASRS screening strata of 0–17 and 18–24 were used for clinically relevant ADHD cut off scores (Kessler et al., 2007a). The 6 items are as follows: 1) How often do you have trouble wrapping up the final details of a project once the challenging parts have been done? 2) How often do you have difficulty getting things in order when you have to do a task that requires organization? 3) How often do you have problems remembering appointments or obligations? 4) When you have a task that requires a lot of thought, how often do you avoid or delay getting started? 5) How often do you fidget or squirm with your hands or feet when you have to sit down for a long time? 6) How often do you feel overly active and compelled to do things, like you were driven by a motor? Participants had to respond to all 6 questions to be included in the study.

Co-variates

The covariates included were potential confounders of the relationship between ACEs and ADHD collected at baseline. Socio-demographic characteristics included: sex (male or female), year in university courses (≤ 2 years or > 2 years), socio-economic status during adolescence (low or moderate/high), lifetime tobacco consumption (yes, no), lifetime illicit drug use (yes, no), and lifetime cannabis use (yes, no). In addition, participants were asked if they had a previous history of depression or anxiety disorders diagnosed by a physician (yes, no).

Statistical Analyses

First, we described the study sample and compared baseline characteristics between participants with and without ACEs with chi-square tests. Second, we investigated the crude associations between cumulative ACEs, individual ACEs, sociodemographic characteristics, and ADHD symptoms by using logistic regression models. Third, we adjusted for sex, adolescent SES, year in university courses, depression and anxiety diagnoses, and substance use variables to the existing models with a multivariate regression. The best model fit was confirmed by having the larger area under the curve and a Hosmer and Lemeshow Test ≥ 0.05. Several sensitivity analyses were run to confirm the relation between cumulative ACEs and ADHD symptoms; including 1) a linear regression analysis between cumulative ACEs and ADHD symptoms score, 2) utilizing different cut off values for ADHD scale (0–13) (14–17) (18–24), and 3) analyzing the relation between ACEs and depression and anxiety diagnoses (control outcomes). SAS Enterprise Guide (version 8.3) was used to conduct the analyses.

Results

A total of 1,174 students completed questions within the baseline questionnaire on ACEs. Among them, 1062 had no missing data on ADHD status, making them eligible for the present study (Fig. 1).

Fig. 1.

Fig. 1

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Flowchart of i-Share Participants

Participant Characteristics

The sample comprised 1062 participants with a mean age of 20.3 (SD = 2.3). Across the entire sample, 30.6% of students had an ACE score of zero, 29.6% had an ACE score of 1, 19.2% had an ACE score of 2, and 20.6% had an ACE score of three or more. The most reported ACEs were parental mental illness (38.3%), divorce (32.5%), and bullying (18.5%), followed by emotional neglect (14.6%), emotional abuse (12.8%), sexual abuse (11.6%), physical abuse (10.8%), parental substance misuse (9.1%), and physical neglect (6.7%). Most participants were females (81.4%) and had a moderate to high SES during adolescence (88.3%). Among the sample, 5.13% had ADHD symptoms (ntotal = 57; nfemales = 43; nmales = 14). Concerning mental health diagnoses, 12.4% had a depression diagnosis and 14.1% had an anxiety diagnosis. Regarding lifetime substance use, about half had used cannabis (52.2%) or tobacco (41.8%), and a smaller percentage had used illicit drugs (excluding cannabis; 14.1%). Persons with ADHD symptoms were significantly more likely to have a depression diagnosis (Χ2(1) = 18.7, p < 0.0001) or an anxiety diagnosis (Χ2(1) = 8.4, p = 0.0038).

Table 1 depicts baseline characteristics of the sample according to ACE status. In bivariate analyses, students with ACEs exposure had a higher likelihood of having ADHD symptoms (6.7% vs. 1.5%). Students with ACEs were statistically significantly more likely to have a lower SES during adolescence, have a depression or anxiety diagnosis, and have used cannabis, illicit drugs, or tobacco during their lifetime.

Table 1.

Demographic Characteristics by ACE status

Variable Level No ACEs ACEs Chi-square
N % N % p-value
Sex Female 282 79.7 660 82.2 0.3078
Male 72 20.3 143 17.8
SES Adolescence Moderate-high 286 80.8 579 72.1 0.0017
Low 68 19.2 224 27.9
Year in University Courses  ≤ 2 years 129 38.1 334 43.7 0.2949
 > 2 years 210 61.9 429 56.2
Depression Diagnosis No 333 94.1 630 78.5  < .0001
Yes 21 5.9 173 21.5
Anxiety Diagnosis No 328 92.7 637 79.3  < .0001
Yes 26 7.3 166 20.7
ADHD Symptoms No 333 98.5 719 93.3 0.0003
Yes 5 1.5 52 6.7
Lifetime Tobacco use No 204 64.1 411 55.7 0.0105
Yes 114 35.9 327 44.3
Lifetime Illicit Drug use No 283 89.3 621 84.5 0.0406
Yes 34 10.7 114 15.5
Lifetime Cannabis use No 174 55.2 327 44.7 0.0017
Yes 141 44.8 405 55.3
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Cumulative ACEs

In unadjusted analysis, students with two ACEs or three or more ACEs were five times and seven times more likely to have ADHD symptoms, respectively, compared to peers without ACEs exposure (Table 2). Cumulative associations between ACEs and ADHD symptoms remained in multivariate analyses. There was a trend (p < 0.0001) whereby adjusted odds ratios were elevated in those with 1 ACE and greatest in those with 3 + ACEs. Thus, compared to college students with no ACE exposure, those with three or more ACEs were five times as likely to report ADHD symptoms (aOR: 5.2; 95% CI: 1.8–14.8). Risk factors for ADHD symptoms in our analytic sample emerged, including having a depression diagnosis (aOR: 2.2; 95% CI: 1.1–4.3). While not significant, males had a trend of having increased risk of ADHD symptoms (aOR: 1.9; 95% CI: 1.0–3.7).

Table 2.

Unadjusted and adjusted associations of ACEs and sociodemographic covariates with ADHD Symptoms

Unadjusted Adjusted*
Variable Level OR 95% CI aOR 95% CI
ACEs ACEs 0 1.0 - - 1.0 - -
ACEs 1 2.6 0.9 7.4 2.1 0.7 6.3
ACEs 2 5.3 1.9 14.6 4.5 1.6 12.8
ACEs 3 +  7.7 2.9 20.6 5.2 1.8 14.8
Sex Male 1.0 - - 1.0 - -
Female 0.7 0.4 1.3 0.5 0.3 1.0
SES Adolescence Low 1.0 - - 1.0 - -
Moderate-High 0.5 0.3 1.1 0.7 0.4 1.5
Year in University Courses  ≤ 2 years 1.0 - - 1.0 - -
 > 2 years 0.5 0.3 1.1 0.7 0.3 1.5
Depression No 1.0 - - 1.0 - -
Yes 3.4 2.0 6.0 2.2 1.1 4.3
Anxiety No 1.0 - - 1.0 - -
Yes 2.3 1.3 4.1 1.2 0.6 2.5
Cannabis use No 1.0 - - 1.0 - -
Yes 1.2 0.7 2.0 1.0 0.5 2.0
Tobacco use No 1.0 - - 1.0 - -
Yes 1.1 0.7 2.0 1.0 0.5 2.0
Illicit drug use No 1.0 - - 1.0 - -
Yes 1.1 0.5 2.3 0.8 0.3 1.8
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*Models adjusted for sex, adolescent SES, year in university courses, depression diagnosis, anxiety diagnosis, lifetime cannabis use, lifetime tobacco use, and lifetime illicit drug use

Three sensitivity analyses were run to confirm these results. Having three or more ACEs was associated with increased likelihood of having mild ADHD symptoms (ASRS value = 14–17) (aOR: 1.6; 95% CI: 0.9–2.8) and increased ADHD symptoms (ASRS value ≥ 18) (aOR: 2.2; 95% CI: 0.9–4.9). Further, ACEs were significantly associated with increased ADHD symptoms (p < 0.0001; R2 = 0.09). Lastly, having three or more ACEs significantly increased the likelihood of a depression diagnosis (aOR: 4.9; 95% CI: 2.7–9.1; p < 0.0001) or anxiety diagnosis (aOR: 3.7; 95% CI 2.1–7.2; p < 0.0001), after adjusting for sociodemographic, mental health, and substance use variables.

ACE Type

In adjusted models of the ACE type and ADHD symptoms, most ACE types demonstrated a consistent pattern of higher odds of ADHD symptoms (Fig. 2). When analyzing the relation between ACE type and ADHD symptoms, the estimates were higher for sexual abuse (aOR: 2.3; 95% CI: 1.1, 4.7), emotional neglect (aOR: 2.5; 95% CI: 1.3, 4.8), physical neglect (aOR: 2.5; 95% CI: 1.1, 5.4), and bullying (aOR: 2.5; 95% CI: 1.3, 4.5).

Fig. 2.

Fig. 2

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ACE Type and ADHD Symptoms. All models present OR and 95% CI and are adjusted for sex, adolescent SES, year in university courses, ADHD, depression diagnosis, anxiety diagnosis, lifetime cannabis use, lifetime tobacco use, and lifetime illicit drug use

Discussion

This study investigated the association of cumulative ACEs and ACE type with ADHD symptoms in French college students. Our findings indicate that French college students with ADHD symptoms are more likely to have experienced ACEs compared to their counterparts and any level of ACEs exposure was associated with an increased risk of ADHD symptoms. In addition, our study shows a dose–response relationship between ACEs and ADHD, whereby as ACEs exposure increases, the risk of having ADHD symptoms is heightened. The association between ACE type and ADHD symptoms seems to be stronger among French college students who have experienced sexual abuse, emotional neglect, physical neglect, and bullying.

These findings suggest that ACEs heighten risk of ADHD symptoms among college students. While this association has been previously described in one study among college students in the United States (Windle et al., 2018), this is the first study to report the link between ACEs and ADHD symptoms among college students residing in Europe. Our analysis indicates a dose–response relationship between ACEs and ADHD, thus confirming previous studies in the area (Briscoe-Smith & Hinshaw, 2006; Crouch et al., 2021; Fuller-Thomson & Lewis, 2015; Windle et al., 2018). Moreover, while individual studies have documented the link between adult ADHD symptoms after physical and sexual abuse (Fuller-Thomson & Lewis, 2015; Fuller-Thomson et al., 2014), few studies have examined as wide of a range of ACE exposures as this paper presents among adults.

Our study describes the association between ACEs and ADHD symptoms among French college students. From a life-course perspective, emerging adulthood is a crucial developmental period that prepares individuals for middle and older adulthood (Arnett, 2007; Elder et al., 2003). Emerging adults face many challenges, including transitions into new social environments, academic pressures, beginning the workforce, and finding a life partner (Arnett et al., 2014). Further, the onset of mental health challenges peak during emerging adulthood (Kessler et al., 2007b), increasing risk of co-occurring problems. Since adult ADHD is correlated with a range of negative consequences, including poorer health and socioeconomic (SES) outcomes, peer, and family conflicts, as well as behavioral problems (Ebejer et al., 2012; Fayyad et al., 2007; Kessler. et al., 2006), it can further complicate the young adulthood period.

Given the relationship between ACEs exposure and ADHD symptoms, enhanced screening efforts for ACEs among college students with ADHD symptom presentation should be an important consideration at universities. These efforts would enhance evaluation, diagnosis, management, and delivery of care (Brown et al., 2017). Professionals who work with college students with ADHD or mental health challenges should consider the role of ACEs before developing their treatment plans and be prepared to discuss these sensitive topics (Goddard, 2021; Oral et al., 2016). As our analyses indicated ACEs exposure may overlap with co-occurring ADHD symptoms, depression, and anxiety, a classical treatment of ADHD alone might not be sufficient to address the effects of ACEs. In this regard, there is a need to increase access to therapies specifically designed to target ACEs.

Even more importantly, our findings highlight the importance of identifying and screening for ACEs among the pediatric population as a major public health need with implications for adulthood. Considering risk factors at early stages and screening in pediatric and primary care settings provides an opportunity for early identification, and intervention while preventing the development of ADHD. Primary care is the best setting for ACE screening because of the regular intervals of interaction with children and their families (Barnes et al., 2020; Marie-Mitchell et al., 2019). Several questionnaires have been developed in the pediatric setting to screen and assess for ACEs, despite limitations regarding their use and psychometric reliability (McLennan et al., 2020), which points to the need for further understanding of the nature of ACEs and their impact for a better screening (Finkelhor, 2018).

Limitations and Future Directions

This study has several strengths, including adjustment on a wide range of potential confounding factors and the use of a validated, age-appropriate ADHD behavioral assessment. Nonetheless, some limitations should be considered. First, the sample was non-representative of the general French student population and a few risk factors for ADHD were underrepresented, including male sex and low SES. Although an overrepresentation of females is typiqual in population studies based on voluntary participation (Glass et al., 2015), this limits the generalizability of our findings and the external validity of the frequencies observed in the sample. However, this potential bias has a limited influence on the study associations between ACEs and ADHD. Second, the ASRS assesses ADHD symptoms and is not a clinical diagnosis. Yet, the ASRS has been validated for college populations, has clinically relevant cutoff scores (Kessler et al., 2007a), and three sensitivity analyses confirmed these results. Third, other overwhelmingly stressful experiences were not included in our ACEs assessment, but should be considered as possible ACEs due to the evidence for their impact on child development and health, such as severe economic hardship, parental intimate partner violence, parental incarceration, chronic disabilities, exposure to war and migration (especially among non-French students that come from low and middle income countries), and racial discrimination (Ellis et al., 2008; Evans & Kim, 2007; Kazak et al., 2006; Thabet et al., 2004).

The reverse association between ADHD and ACEs – ADHD leading to ACEs – should also be considered since children with ADHD who are impulsive and lack self-regulation are more likely to be bullied or experience harsh parental attitudes (Lugo-Candelas et al., 2021). Given the developmental nature of ADHD, an adult ADHD diagnosis by an age-appropriate ADHD behavioral assessment such as the one we used in this study indicates a childhood ADHD diagnosis. Therefore, the use of retrospective ACE self-reports prevents us from determining a definite temporal sequence that would enable us to determine whether ADHD symptoms were present before or after the occurrence of ACEs. The clinical implication however of the comorbidity between ACEs and ADHD and their treatment in the college years would be similar in both cases.

In conclusion, findings suggest that college students with ACEs exposure have heightened risk of ADHD symptoms and certain ACE types (sexual abuse, emotional neglect, physical neglect, and bullying) may contribute greater risk. More longitudinal research is needed to understand the temporality of the association between ACEs and ADHD symptoms to best identify factors to improve intervention and prevention efforts.

Acknowledgements

The authors are indebted to the participants of the i-Share project for their commitment and cooperation and to the entire i-Share staff for their expert contribution and assistance.

Authors’ Contribution

Conceptualization: Ashlyn Schwartz, Cédric Galera, Ilaria Montagni, Christophe Tzourio; Methodology: Ashlyn Schwartz, Hala Kerbage, Cédric Galera, Ilaria Montagni, Christophe Tzourio; Formal analysis and investigation: Ashlyn Schwartz; Writing—original draft preparation: Ashlyn Schwartz; Writing—review and editing: Ashlyn Schwartz, Hala Kerbage, Cédric Galera, Ilaria Montagni, Christophe Tzourio; Funding acquisition: Ashlyn Schwartz, Christophe Tzourio; Resources: Ashlyn Schwartz, Hala Kerbage, Christophe Tzourio; Supervision: Cédric Galera, Hala Kerbage, Ilaria Montagni, Christophe Tzourio. All authors read and approved the final manuscript.

Funding

This study was supported by a Fulbright-University of Bordeaux grant through the Franco-American Fulbright Commission. Additionally, the i-Share team is currently supported by an unrestricted grant of the Nouvelle-Aquitaine Regional Council (Conseil Régional Nouvelle-Aquitaine, grant N°4370420). It has also received grants from the Nouvelle-Aquitaine Regional Health Agency (Agence Régionale de Santé Nouvelle-Aquitaine, grant N°6066R-8), Public Health France (Santé Publique France, grant N°19DPPP023-0), and The National Institute against cancer INCa (grant N°INCa_11502). The funding bodies were neither involved in the study design, or in the collection, analysis, or interpretation of the data.

Data Availability

Database for the i-Share cohort can be made available upon reasoned request.

Declarations

Ethics Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed Consent

Informed consent was obtained from all participants included in the study.

Conflict of Interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Database for the i-Share cohort can be made available upon reasoned request.

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