Distinct scars: unique effects of physical and sexual abuse on mental health outcomes in a gender-specific substance use disorder sample in Brazil from 1998 to 2024
Institute of Psychiatry, Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro, Brazil
Statistics Departament, Institute of Mathematics, Universidade de São Paulo, São Paulo, Brazil
Laboratory of Psychiatric Neuroimaging (LIM 21), Departament of Psychiatry, Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
Abstract
Objectives
(1) To compare sociodemographic characteristics, psychopathology, and substance use patterns among women diagnosed with substance use disorder (SUD) who experienced physical abuse (PA), sexual abuse (SA), or both (PSA); (2) to describe ages of onset; (3) to evaluate the impact of PA, SA, and their interaction on clinical outcomes.
Methods
Observational retrospective study with patients from PROMUD (Drug Dependent Women Treatment Center) in Brazil. Questionnaires at admission assessed sociodemographics, history of SA and PA, substance use, and psychopathology. t-tests and chi-squared tests were used for descriptive statistics. Logistic and linear regressions estimated associations between clinical outcomes and history of SA or PA in crude and adjusted models. The PA–SA interaction was tested.
Results
401 patients were included (1999–2024). Both SA and PA were associated with greater socioeconomic vulnerability and higher non-heterosexual orientation. SA often began in early childhood, PA more often in adolescence. PA was associated with higher odds of cocaine/crack as the main substance of dependence (OR = 2.7, p < 0.001) and lifetime physical aggression (OR = 1.9, p = 0.018). SA was linked to lifetime suicidal ideation (OR = 2.8, p < 0.01) and use of other substances (OR = 2.0, p = 0.041). No significant PA*SA interaction was found.
Conclusions
SA was associated with internalizing patterns, such as suicidal ideation and cannabis/sedative use, whereas PA was linked to externalizing patterns, including physical aggression and cocaine/crack use. These effects were independent, underscoring the need to assess both in women with SUD and to develop gender-sensitive, trauma-informed interventions, particularly where resources are limited.
Supplementary Information
The online version contains supplementary material available at 10.1007/s00737-026-01702-5.
Untitled section
Keywords: Women’s mental health, Substance use disorder, Physical abuse, Sexual abuse, Violence against women and girls, Gender-based violence, Gender-sensitive care, Brazil
Highlights
- Women with history of abuse faced greater social and economic challenges.
- Sexual abuse independently linked to suicidal thoughts and cannabis or sedative dependence.
- Physical abuse independently linked to aggression and cocaine/crack dependence.
- Abuse often happened before age 10, with long-term impacts.
- Findings support gender-sensitive, trauma-informed addiction care.
Supplementary Information
The online version contains supplementary material available at 10.1007/s00737-026-01702-5.
Article notes
Untitled section
Received 2025 Aug 12; Accepted 2026 Apr 7; Issue date 2026.
Introduction
Violence Against Women and Girls (VAWG) is an overarching legal–public health category, that encompasses multiple acts, threats and coercive patterns that result in suffering to women (Falb et al. 2025). VAWG can be defined as any act of gender-based violence that results in, or is likely to result in, physical, sexual or psychological harm or suffering to women, including threats of such acts, coercion or arbitrary deprivation of liberty (Ellsberg et al. 2015). In research and clinical settings, such events are commonly assessed through histories of interpersonal abuse, which refer to patterned behaviors within relationships, such as physical abuse (PA), sexual abuse (SA), or psychological abuse (Watts and Zimmerman 2002).
Physical abuse (PA) and sexual abuse (SA) are major determinants of health, contributing substantially to disease burden across the life course (Spencer et al. 2023). Childhood, adolescence and early adulthood prove to be critical periods of heightened vulnerability. Adverse childhood experiences (ACEs), which include abuse and neglect occurring primarily before the age of 18, are important risk factors for mental health disorders (Daníelsdóttir et al. 2024). ACEs disrupt brain development involved in emotional regulation, stress response and executive function, especially during critical periods (Nelson et al. 2025). While traditional ACE frameworks emphasize a limited range of childhood adversities, expanded models also consider socioeconomic vulnerability, exposure to family violence, and household substance use exposure (Finkelhor et al. 2013). ACEs also have an impact on risk on the development of substance use disorders (SUDs), particularly in women (Martin et al. 2023), and females with SUDs report higher rates of ACE, such as PA, SA and neglect (Fletcher 2021; Carr et al. 2023).
There is evidence that women who have experienced childhood SA alone, compared to PA alone, have higher odds of alcohol dependence, and both are individually associated with increased risk of SUDs (Simpson and Miller 2002; Anne Lown et al. 2011). Moreover, studies show that having experienced both PA and SA has a cumulative effect on the risk of SUDs, and is associated with a greater addiction severity, which initiates at an earlier age, and escalates faster (Charak et al. 2015; Lotzin et al. 2019). Exposure to abuse during adulthood is also a significant risk factor, particularly among women, and longitudinal evidence suggests it independently predicts development of SUDs, even after controlling for antecedent substance disorders (Ahmadabadi et al. 2019).
Data regarding VAWG is most likely underestimated and has significant variation by region and context due to a myriad of reasons, including historical and cultural norms which may compromise data collection practices, underreporting due to stigma and fear, and methodological challenges (Palermo et al. 2014; Vahedi et al. 2023; Schredl et al. 2025). Low- and middle-income countries (LMICs) generally have higher prevalence of VAWG (Coll et al. 2020). These regions often face economic insecurity, gender inequitable norms, high levels of societal stigma, discriminatory family laws, and inadequate support services (Heise and Fulu 2015). In Brazil, a systematic review found that 20% of Brazilian women suffered physical violence in their lifetime, and one tenth in the previous year (Nakamura et al. 2023).
Nevertheless, despite evidence linking PA and SA to SUDs, the literature still lacks findings regarding the unique and independent contribution of each exposure to SUD risk and clinical presentation, particularly in clinical samples, independent of the timing of abuse across the life course. Due to the frequent co-occurrence of PA and SA, most studies either aggregate exposures or fail to estimate mutually adjusted effects, limiting inference about whether PA and SA have distinct, independent effects. Although community-based evidence suggests unique effects of PA and SA on psychopathology (Adams et al. 2018), comparable analyses in clinical samples with confirmed SUDs, particularly those adopting a gendered lens, remain scarce. Clinically relevant outcomes. like suicidality and aggressivity. are of particular interest in this context. Moreover, this evidence gap is particularly pronounced in LMICs, where women’s addiction services are often under-resourced and long-running clinical cohorts are less frequently studied.
Therefore, this study seeks to further elucidate the interplay of VAWG and SUD by analysing data from a sample of women receiving treatment for SUD in Brazil. The aims were threefold:
- To compare sociodemographic characteristics, psychopathology, and substance use patterns among women who experienced PA, SA or both;
- To identify the age of onset of SA and PA and examine whether the age distributions differ;
- To evaluate the unique effect of PA, SA and their interaction on substance choice and clinical outcomes.
Methods
Study setting and design & sample
This observational study was conducted with patients admitted to the Drug Dependent Women Treatment Center (PROMUD) at the Institute of Psychiatry of the Hospital das Clínicas, Faculty of Medicine, University of São Paulo (IPqHCFMUSP), between 1996 and 2024. Treatment at PROMUD follows a standardized protocol which includes psychiatric care, nutritional consultations, and group psychotherapy for all patients (Leal et al. 2024; Bacchi et al. 2025). Patients were recruited if they met the inclusion and exclusion criteria of the service through a structured interview at the time of admission.
Participants were recruited from patients who voluntarily sought treatment at PROMUD. The inclusion criteria for the study were: (1) a confirmed diagnosis of SUD by a psychiatrist, according to DSM-IV or DSM-5 criteria, as applicable at the time of assessment; (2) completion of a comprehensive questionnaire administered at enrollment; and (3) informed consent obtained from the patient to participate in the study. The exclusion criterion was the absence of any responses to the specific questions regarding the history of SA or PA. All of the patients treated at PROMUD have a confirmed diagnosis of SUD by a licensed psychiatrist. No patient admitted to the service openly refused to participate in the study, but participants often missed assessments.
Variables
Data collection was carried out through questionnaires administered at the time of admission, carried out by trained mental health professionals ensuring standardization and accuracy of the information. After the initial psychiatric interview, the main substance of dependence was determined, and posteriorly categorized into Alcohol, Cocaine/Crack, Other. The “Other” category was collapsed due to the small sample size of the individual categories, and is composed of the substances: cannabis, amphetamines, sedatives, ketamine, opioids and LSD. The questionnaire comprises sociodemographic, clinical, psychiatric and substance related questions. The semi-structured interview ASI-5 was applied from 1998 to 2005 and ASI-6 from 2006 to 2024.
The sociodemographic variables collected included age, race/ethnicity (categorized as white, black, yellow, and indigenous), education level (categorized incomplete primary school, completed primary school, completed middle school, and completed university education), occupational status (categorized as retired, employed or unemployed), marital status (partnered or not partnered), sexual orientation (heterosexual, homosexual, or bisexual and others), and financial self-sufficiency and income level (categorized as monthly income greater than one minimum wage or less than one minimum wage). Participants were assessed whether they had ever experienced suicidal thoughts or attempts, as well as any history of hetero-aggression or self-harm.
Information regarding SA was obtained through the following questions: “Did you experience any type of sexual abuse during childhood or adolescence?” and the ASI question “Have you ever been sexually assaulted/abused by someone you knew?“, while information regarding PA was obtained through the following question: “Have you ever been physically assaulted/abused by someone you knew?“. Patients who reported having experienced SA at any of these questions were allocated to the “SA” group, patients who reported having experienced PA at any of these questions were allocated to the “PA” group, patients who experienced both types of abuse were allocated to the “SA and PA” group, while those who denied any history of abuse were allocated to the “No abuse” group. The ages of onset of these abuses were assessed by the question “How old were you when this happened for the first time?”, following both the questions of SA and PA.
Statistical analyses
Analyses were performed using R software version 4.2. For our first aim, The four groups (No Abuse / SA / PA / SA and PA) were compared. To compare the means of continuous variables across the groups, we performed an ANOVA. For categorical variables, a Chi-square test (χ²) was used. The level of statistical significance was set at p < 0.05. For our second aim Kernel Density Estimates for the age distribution at onset of SA and PA were plotted and a Kolmogorov-Smirnov test was used to evaluate differences between distributions.
For our third aim, linear regression betas and 95% confidence intervals (95% CI) were estimated for the associations between history of sexual abuse (SA) or physical abuse (PA) and the age at which the patient entered PROMUD. Logistic regressions were used to estimate odds ratios and 95% confidence intervals for the associations between a history of SA or PA and various clinical outcomes. We first built a crude model for each outcome, including only SA and PA as predictors. Subsequently, we built an adjusted model, including sex, educational level, and year of admission as covariates. Year of admission was included as a covariate to account for secular trends over the cohort’s three-decade span, including changes in diagnostic frameworks for substance use disorders (DSM-IV to DSM-5, shifts in violence reporting practices (Lima et al. 2025) and greater public and clinical awareness (Palermo et al. 2014), and changes in drug-use patterns over time (Malta et al. 2021).
All models were also tested for an interaction between SA and PA; The models with interaction had the following formula: Outcome ~ PA * SA + confounders. However, these interactions were not statistically significant and thus not included in the final reported models. A detailed breakdown of the interaction terms and their p-values can be found in Table S2 and S3.
Item-level missingness in sociodemographic and clinical variables was assumed to be Missing at Random (MAR), as missingness was plausibly related to observed factors such as year of admission, educational level, and interview version, all of which were accounted for.
Multicollinearity was assessed using Variance Inflation Factors (VIF), with all values below 3 indicating stable standard errors in the models with no interactions. When interaction terms are added, VIF values are naturally much higher. Dispersion and outlier tests were conducted using simulation-based diagnostics via the DHARMa package, suggesting no assumption violations (Tables S4 and S5).
Ethics statement
The study was approved by the Research Ethics Committee of the Institute of Psychiatry of the Hospital das Clínicas, Faculty of Medicine, University of São Paulo (IPqHCFMUSP). All participants signed the Informed Consent Form (ICF) prior to inclusion in the study. The authors assert that all procedures in this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008.
Results
From the initial sample of 854 patients, 200 were excluded because the ASI questionnaire was applied only from 1998 on, and 253 were excluded due to missing data on PA or SA. Therefore, 401 patients were included, according to history of abuse: no abuse (NA, n = 135; 33.6%), physical abuse (PA, n = 92; 22.9%), sexual abuse (SA, n = 71; 17.7%), and both physical and sexual abuse (PSA, n = 103; 25.6%). Mean age at admission differed significantly between groups (p = 0.026), being highest in the NA group. Additionally, the year of admission to PROMUD differed significantly (p = 0.002), with a predominance of NA between 1998 and 2006 (46.7%) and a predominance of patients with a history of some type of abuse between 2014 and 2024 (ranging from 23.9% to 45.6%). A significant difference in sexual orientation (p = 0.012) was observed, with higher rates of bisexuality in abuse groups (9.6%–21.2%) compared to NA (4.2%), and lower prevalence of heterosexuality in the abuse groups (Table 1). Self-reported income insufficiency was also significantly associated with abuse history (p = 0.002), reported by 64.7% to 74.2% in abuse groups compared to 45.8% in the NA group, indicating higher socioeconomic vulnerability in those with abuse experiences. Additionally, a significant association was observed between monthly income and a history of abuse (p = 0.018). Among patients with reported abuse, 33.3% to 51.4% reported receiving more than one minimum wage per month, whereas 64.5% of patients without a history of abuse reported earning more than one minimum wage per month. (Table 1).
| Characteristic | No abuse (N = 135) | Physical abuse (N = 92) | Sexual abuse (N = 71) | Sexual and physical abuse (N = 103) | P-value | Missing (%) |
|---|---|---|---|---|---|---|
| Age at entry (mean ± SD) | 42.79 ± 11.99 | 39.22 ± 12.31 | 38.79 ± 11.75 | 38.71 ± 12.04 | 0.026 | 0% |
| Year of admission to PROMUD | 0.002 | |||||
| From 1998 to 2006 | 63 (46.7%) | 34 (37%) | 26 (37.1%) | 27 (26.2%) | ||
| From 2006 to 2014 | 38 (28.1%) | 36 (39.1%) | 16 (22.9%) | 29 (28.2%) | ||
| From 2014 to 2024 | 34 (25.2%) | 22 (23.9%) | 28 (40%) | 47 (45.6%) | ||
| Race (%) | 0.329 | 1% | ||||
| Yellow | 3 (2.3%) | 0 (0.0%) | 2 (2.8%) | 1 (1.0%) | ||
| White | 101 (75.9%) | 61 (67.0%) | 54 (76.1%) | 71 (69.6%) | ||
| Indigenous | 0 (0.0%) | 1 (1.1%) | 0 (0.0%) | 0 (0.0%) | ||
| Black | 29 (21.8%) | 29 (31.9%) | 15 (21.1%) | 30 (29.4%) | ||
| Answered “no partner” for marital status (%) | 90 (67.7%) | 65 (70.7%) | 45 (69.2%) | 82 (80.4%) | 0.163 | 2.2% |
| Sexual Orientation (%) | 0.012 | 13.2% | ||||
| Bisexual and others | 5 (4.2%) | 7 (9.6%) | 14 (21.2%) | 11 (12.1%) | ||
| Heterosexual | 106 (89.8%) | 57 (78.1%) | 46 (69.7%) | 71 (78.0%) | ||
| Homosexual | 7 (5.9%) | 9 (12.3%) | 6 (9.1%) | 9 (9.9%) | ||
| Financial self-sufficiency (%) | 45 (54.2%) | 16 (25.8%) | 12 (35.3%) | 26 (31.0%) | 0.002 | 34.4% |
| Income greater minimum wage (%) | 49 (64.5%) | 29 (46.8%) | 11 (33.3%) | 38 (51.4%) | 0.018 | 38.9% |
| Occupational status (%) | 0.398 | 8.5% | ||||
| Retired | 8 (6.6%) | 5 (6.1%) | 8 (11.6%) | 6 (6.3%) | ||
| Unemployed | 57 (47.1%) | 45 (54.9%) | 38 (55.1%) | 43 (45.3%) | ||
| Employed | 56 (46.3%) | 32 (39.0%) | 23 (33.3%) | 46 (48.4%) | ||
| Education Level (%) | 0.467 | 4.7% | ||||
| Incomplete primary | 16 (12.2%) | 10 (11.1%) | 10 (15.4%) | 15 (15.6%) | ||
| Complete primary | 14 (10.7%) | 12 (13.3%) | 14 (21.5%) | 14 (14.6%) | ||
| Complete primary | 62 (47.3%) | 46 (51.1%) | 31 (47.7%) | 44 (45.8%) | ||
| Complete university education | 39 (29.8%) | 22 (24.4%) | 10 (15.4%) | 23 (24.0%) | ||
| Main substance (%) | < 0.001 | 2.7% | ||||
| Alcohol | 95 (71.4%) | 45 (51.7%) | 40 (57.1%) | 44 (44.0%) | ||
| Other | 18 (13.5%) | 8 (9.2%) | 13 (18.6%) | 17 (17.0%) | ||
| Cocaine and crack | 20 (15.0%) | 34 (39.1%) | 17 (24.3%) | 39 (39.0%) | ||
| Age of onset of alcohol use (mean ± SD) | 19.96 ± 10.18 | 18.63 ± 8.07 | 17.71 ± 8.67 | 16.96 ± 7.72 | 0.091 | 11.2% |
| Previous treatment for alcohol (%) | 40 (50.6%) | 24 (48.0%) | 20 (50.0%) | 27 (41.5%) | 0.719 | 41.6% |
| Previous treatment for other substance (%) | 31 (40.8%) | 24 (47.1%) | 26 (54.2%) | 39 (54.2%) | 0.335 | 38.4% |
| SADD Score (mean ± SD) | 18.77 ± 11.86 | 17.37 ± 10.91 | 19.42 ± 12.41 | 18.99 ± 12.75 | 0.814 | 30.7% |
| Lifetime suicidal ideation (%) | 32 (37.2%) | 36 (56.2%) | 24 (70.6%) | 58 (70.7%) | < 0.001 | 33.7% |
| Lifetime suicide attempt (%) | 21 (32.8%) | 20 (44.4%) | 22 (51.2%) | 33 (50.0%) | 0.164 | 45.6% |
| Lifetime physical aggression (%) | 24 (28.9%) | 28 (43.8%) | 13 (37.1%) | 43 (51.8%) | 0.024 | 33.9% |
No significant differences were found regarding race, marital status, education, employment, income, age at alcohol use onset, prior treatment, or secondary alcohol dependence. However, a significant difference was found for the primary substance of dependence (p < 0.001), with cocaine/crack more prevalent in PA (39.1%), SA (24.3%), and PSA (39%) than in NA (15%). Lifetime suicidal ideation was significantly more frequent (p < 0.001) in PA (56.2%), SA (70.6%), and PSA (70.7%) compared to NA (37.2%). Reports of lifetime physical aggression were also significantly higher in abuse groups (p = 0.024), especially in PSA (51.8%) versus NA (28.9%) (Table 1).
Kernel Density Estimates showing the age distribution at onset of sexual and physical violence. Dashed lines indicate quartiles. A Kolmogorov-Smirnov test rejected the null hypothesis of equality of these two distributions (p < 0.001), indicating a statistically significant difference in the age profiles of sexual versus physical violence onset.
Sample distribution of the number of abuse reports by patient arrival treatment period, stratified by abuse type, with a notable increase in simultaneous sexual and physical abuse over time.
Estimates for interaction of sexual and physical abuse as predictors for multiple outcomes, and p values showing that none was significant.
Forest Plot of the effect of sexual abuse or physical on different outcomes. First, crude effects were established, afterwards, a model adjusted by race, education level and year of treatment. This model did not consider interaction terms between sexual abuse and physical abuse.
For the regression analyses, the first model tested the interaction between SA and PA; no significant interaction term was found for any outcome (Table 2; complete results in Table S1). We then proceeded to the model without interaction terms. Regarding the outcome “age at admission”, no significant effect was found. For the outcome “use of cocaine/crack relative to alcohol as the primary substance of abuse,” a significant association was observed with PA (p < 0.001, adjusted OR = 2.7). SA was significantly associated with Other Substances ( p = 0.041, adjusted OR = 2.0 ) (Fig. 3; complete results in Table S2).
| Outcome variable | Model scenario | Physical: sexual abuse interaction estimate | P-value |
|---|---|---|---|
| Age at Admission | Crude | 3.5 | 0.15 |
| Age at Admission | Adjusted | 3.8 | 0.14 |
| Lifetime suicide attempt | Crude | -0.5 | 0.33 |
| Lifetime suicide attempt | Adjusted | -0.6 | 0.27 |
| Lifetime suicidal ideation | Crude | -0.8 | 0.17 |
| Lifetime suicidal ideation | Adjusted | -0.8 | 0.17 |
| Lifetime physical aggression | Crude | 0.0 | 0.92 |
| Lifetime physical aggression | Adjusted | 0.2 | 0.73 |
| Main substance - other | Crude | 0.2 | 0.70 |
| Main substance - cocaine/crack | Crude | -0.5 | 0.27 |
| Main substance - other | Adjusted | 0.4 | 0.58 |
| Main substance - cocaine/crack | Adjusted | -0.8 | 0.12 |
PA was associated with higher odds of “lifetime history of physical aggression,” (adjusted OR = 1.9). Regarding suicidal ideation, SA showed a strong positive association (adjusted OR = 2.8). PA was also significantly associated in the adjusted model (p = 0.028), although with a lower magnitude (OR = 1.9). Finally, for the outcome “lifetime suicide attempt”, no significant effect was found.
Compared with non-responders, responders were older at entry (40.21 ± 12.13 vs. 37.49 ± 12.54 years; p = 0.002) and differed by admission period (p = 0.002), with higher income above the minimum wage (51.8% vs. 36.7%; p = 0.012), employment (51.8% vs. 33.0%; p = 0.003), and education (p < 0.001), while race (p = 0.796), marital status (p = 0.163), main substance (p = 0.067), and clinical variables (all p > 0.05) were similar. These results can be seen in the Table S3.
Discussion
For our first aim we compared sociodemographic characteristics, psychopathology, and substance use patterns among women who experienced PA, SA or both. Two thirds of the sample had suffered at least one type of abuse. Women exposed to abusive experiences, particularly those in the PSA group, have higher socioeconomic vulnerability, including being unemployed and self-declaring financially insufficient. These findings are consistent with robust evidence that VAWG poses higher risk for adverse economic outcomes (Sauber and O’Brien 2020; Domond et al. 2023). We found that women with a history of at least one type of abuse were more likely to identify as non-heterosexual. The role of sexual orientation and its relationship with abuse is a complex issue, and there seem to be higher rates of child abuse among non-heterosexual individuals (Koeppel and Bouffard 2014). Women enrolled in the program between 2013 and 2024 presented higher abuse rates, especially SA. There is evidence of increased SA reporting in Brazil in the last decades, which likely reflects both greater awareness and improved reporting mechanisms, rather than a true rise in incidence (Gaspar and Pereira 2018).
Our second aim was to analyze and compare the age of onset of SA and PA. Half of the SAs occurred firstly before 10 years, and half of PAs occurred firstly before 15 years. Such findings are in line with clinical and community samples in LMIC, where first SA typically occurred between 6 and 12 years old (Rueda et al. 2021). In the context of SUDs, childhood abuses are associated with greater severity, earlier initiation of drug use and psychiatric comorbidities (Valério et al. 2022; Rakovski et al. 2024). Among women with SUD, physical abuse frequently begins during early developmental periods and is strongly associated with earlier initiation of substance use and greater clinical severity, especially when accompanied by comorbid PTSD (Lansford et al. 2010; Lotzin et al. 2019).
Adverse Childhood Events (ACEs), including PA and SA, impact the developing brain and social cognition (O’Hare et al. 2023) and are implicated in genetic, epigenetic, cultural, and psychosocial mechanisms (Donovan et al. 2024). When addressing substance use, the impact becomes increasingly complex and bidirectional. Exposure to traumatic events can induce stress, fear and isolation and, on the other hand, women with severe mental health issues are at a higher risk of experiencing violent victimization (Hyde et al. 2008; Khalifeh and Dean 2010).
For our third aim, we evaluated the impact of PA, SA, and their interaction on clinical and behavioral outcomes. Women who suffered SA were approximately three times as likely to have had suicidal ideation during their lifetime, suggesting a significantly high predisposition to psychological suffering and suicidal thoughts. Patients with a history of PA were also linked to higher rates of suicidal ideation, although with a less pronounced effect.
ACEs present both direct and indirect effects on suicidality (Kim et al. 2021). Epidemiological studies and meta-analyses demonstrate an association between childhood SA and a 2.5–3-fold increase in the odds of suicidal ideation and attempts in both youth and adults (Angelakis et al. 2020; Dworkin et al. 2022). There is also evidence of a smaller, 2-fold increased risk for these outcomes, among those who suffered PA (Visioli et al. 2023). In women, suicidal thoughts may originate from stigma and neglect, whether in childhood or later, during sociocultural integration. Social determinants may perpetuate suicidality among vulnerable populations (Na et al. 2025). Sexually abused women have elevated internalizing symptoms, such as depression and PTSD (Yang et al. 2023; Hamel et al. 2024), which could mediate relationships between ACEs and later risk behaviours, such as SUD (Villar et al. 2024).
PA was associated with an increased chance of physical aggression during lifetime. Victims of PA may present violent behaviours during their lifetime (Stouthamer-Loeber et al. 2001), especially during adolescence (Smith and Thornberry 1995). The sentence “Violence begets violence” has been studied since the end of the last century (Widom 1989). Children who have been physically abused present higher risks of continuity of violent behaviours towards their own children later in life (Freisthler et al. 2017). PA is generally associated with externalizing symptoms and behaviours (Aksoy et al. 2022; Hamel et al. 2024). The use of cocaine is also associated with externalizing traits (Vorspan et al. 2020), and individuals who use cocaine have an increased chance of both suffering and perpetrating PA (Lee et al. 1997; Kadri et al. 2025). Our findings support this complex dynamic, once women in our sample that suffered PA are more prone to be mainly cocaine users.
We did not find interaction between PA and SA as predictors, which most likely means they act independently, in a cumulative but not interacting manner, neither attenuating nor exacerbating each other as exposures. We hereby posit that these two direct risk factors should be assessed and independently accounted for in clinical settings.
Strengths
To our knowledge, this was the first study to examine unique effects of physical and sexual as predictors of psychopathology in a clinical sample of women with SUD.
This study has data from women spanning 26 years and is to our knowledge the largest of such clinical samples in Brazil. Additionally, a gender-specific center offers a unique opportunity to gain insights into a historically underrepresented population. Therefore, the findings of our study may have broader relevance and applicability to similar contexts, particularly in other LMICs.
Limitations
The limitations of the study must be stated. PTSD prevalence and association with SUD were not accounted for in our sample, despite its role as a possible mediator between victimization and the severity of various types of SUDs. Another limitation of our study lies in the patients’ understanding of what constitutes an abusive situation. It is undeniable that throughout the analyzed period, there have been tangible societal and cultural shifts which may, in turn, influence reporting of abuse.
Furthermore, the present study relies on self-report data, which may incur recall bias, which is particularly important for reporting past traumatic events. Sociodemographic characteristics of our sample, including a predominance of higher education levels than Brazilian average, higher income, and white race/ethnicity, may hinder the external validity of our findings.
Additionally, we could not adjust for some contextual factors that may influence both exposure to violence and clinical outcomes, including social support, family support, and family history of mental health disorders.
Conclusion
The present study provides evidence of the associations between SA, PA, and adverse clinical outcomes in women with SUD. Both SA and PA were correlated with greater socioeconomic vulnerability and frequently occurred early in life. SA was associated with internalizing patterns, such as suicidal ideation and use of substances like cannabis and sedatives, and PA was associated with externalizing patterns, like physical aggression and cocaine or crack use. The independence of the effects of PA and SA suggests that these events should be carefully assessed and interpreted in a clinical setting, to further develop gender-sensitive and trauma-informed tailored care.
Supplementary Information
Below is the link to the electronic supplementary material.
Funding
The Article Processing Charge (APC) for the publication of this research was funded by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) (ROR identifier: 00x0ma614). All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript.
Data availability
No datasets were generated or analysed during the current study.
Declarations
Competing interests
The authors declare no competing interests.
Footnotes
Footnote Group
References
Untitled section
References
- Adams J, Mrug S, Knight DC (2018) Characteristics of child physical and sexual abuse as predictors of psychopathology. Child Abuse Negl 86:167–177. 10.1016/j.chiabu.2018.09.019
- Ahmadabadi Z, Najman JM, Williams GM, Clavarino AM, d’Abbs P, Smirnov A (2019) Intimate partner violence in emerging adulthood and subsequent substance use disorders: findings from a longitudinal study. Addiction 114:1264–1273. 10.1111/add.14592
- Aksoy D, Favre CA, Janousch C, Ertanir B (2022) Internalizing and externalizing symptoms in adolescents with and without experiences of physical parental violence, a latent profile analysis on violence resilience. Front Psychol 13. 10.3389/fpsyg.2022.824543
- Angelakis I, Austin JL, Gooding P (2020) Association of childhood maltreatment with suicide behaviors among young people: A systematic review and meta-analysis. JAMA Netw Open 3:e2012563. 10.1001/jamanetworkopen.2020.12563
- Anne Lown E, Nayak MB, Korcha RA, Greenfield TK (2011) Child physical and sexual abuse: A comprehensive look at alcohol consumption patterns, consequences, and dependence from the national alcohol survey. Alcohol Clin Exp Res 35:317–325. 10.1111/j.1530-0277.2010.01347.x
- Bacchi PS, Carezzato F, di Santi T, Suen P, Silveira F, Takeuchi T, Marczyk J, Trinca RT, Torres RS, Brasiliano S, Hochgraf P (2025) Expanding gender-sensitive and equitable substance use care models: treatment retention analysis of the women’s drug dependent treatment program (PROMUD) replication in psychosocial units in Brazil. Arch Womens Ment Health. 10.1007/s00737-025-01601-1
- Carr MM, Ellis JD, Saules KK, Ledgerwood DM (2023) Childhood adversity, addiction severity, and comorbidity among patients receiving opioid use disorder treatment. J Nerv Ment Dis 211:150–156. 10.1097/nmd.0000000000001581
- Charak R, Koot HM, Dvorak RD, Elklit A, Elhai JD (2015) Unique versus cumulative effects of physical and sexual assault on patterns of adolescent substance use. Psychiatry Res 230:763–769. 10.1016/j.psychres.2015.11.014
- Coll CVN, Ewerling F, García-Moreno C, Hellwig F, Barros AJD (2020) Intimate partner violence in 46 low-income and middle-income countries: an appraisal of the most vulnerable groups of women using national health surveys. BMJ Glob Health 5:e002208. 10.1136/bmjgh-2019-002208
- Daníelsdóttir HB, Aspelund T, Shen Q, Halldorsdottir T, Jakobsdóttir J, Song H, Lu D, Kuja-Halkola R, Larsson H, Fall K, Magnusson PKE, Fang F, Bergstedt J, Valdimarsdóttir UA (2024) Adverse childhood experiences and adult mental health outcomes. JAMA Psychiatry 81:586. 10.1001/jamapsychiatry.2024.0039
- Domond P, Orri M, Vergunst F, Bouchard S, Findlay L, Kohen D, Hébert M, Vitaro F, Tremblay RE, Geoffroy M-C, Côté S (2023) Childhood abuse, intimate partner violence in young adulthood, and welfare receipt by midlife. Pediatrics 151. 10.1542/peds.2022-057379
- Donovan A, Assari S, Grella C, Shaheen M, Richter L, Friedman TC (2024) Neuroendocrine mechanisms in the links between early life stress, affect, and youth substance use: A conceptual model for the study of sex and gender differences. Front Neuroendocrinol 73:101121. 10.1016/j.yfrne.2024.101121
- Dworkin ER, DeCou CR, Fitzpatrick S (2022) Associations between sexual assault and suicidal thoughts and behavior: A meta-analysis. Psychol Trauma 14:1208–1211. 10.1037/tra0000570
- Ellsberg M, Arango DJ, Morton M, Gennari F, Kiplesund S, Contreras M, Watts C (2015) Prevention of violence against women and girls: what does the evidence say? Lancet 385:1555–1566. 10.1016/S0140-6736(14)61703-7
- Falb K, Peterman A, Nordås R, Field A, Porat R, Stark L (2025) Violence against women and girls research: Leveraging gains across disciplines. Proc Natl Acad Sci U S A 122:e2404557122. 10.1073/pnas.2404557122
- Finkelhor D, Shattuck A, Turner H, Hamby S (2013) Improving the adverse childhood experiences study scale. JAMA Pediatr 167:70–75. 10.1001/jamapediatrics.2013.420
- Fletcher K (2021) A systematic review of the relationship between child sexual abuse and substance use issues. J Child Sex Abus 30:258–277. 10.1080/10538712.2020.1801937
- Freisthler B, Wolf JP, Wiegmann W, Kepple NJ (2017) Drug use, the drug environment, and child physical abuse and neglect. Child Maltreat 22:245–255. 10.1177/1077559517711042
- Gaspar RS, Pereira MUL (2018) [Trends in reporting of sexual violence in Brazil from 2009 to 2013]. Cad Saude Publica 34:e00172617. 10.1590/0102-311X00172617
- Hamel C, Rodrigue C, Clermont C, Hébert M, Paquette L, Dion J (2024) Alexithymia as a mediator of the associations between child maltreatment and internalizing and externalizing behaviors in adolescence. Sci Rep 14. 10.1038/s41598-024-56909-2
- Heise L, Fulu E (2015) What works to prevent violence against women and girls evidence reviews. Paper 1: state of the field of violence against women and girls
- Hyde JS, Mezulis AH, Abramson LY (2008) The ABCs of depression: integrating affective, biological, and cognitive models to explain the emergence of the gender difference in depression. Psychol Rev 115:291–313. 10.1037/0033-295X.115.2.291
- Kadri A, Clergue-Duval V, Lambert C, Atger L, Chouchana M, de Chazeron I, Questel F, Laporte C, Brousse G, Vorspan F, Vicard-Olagne M (2025) Is cocaine use associated with intimate partner violence in patients from addiction centers? Subst Use Misuse 60:1577–1582. 10.1080/10826084.2025.2506144
- Khalifeh H, Dean K (2010) Gender and violence against people with severe mental illness. Int Rev Psychiatry 22:535–546. 10.3109/09540261.2010.506185
- Kim G, Shin J, Kim J-W (2021) The mediating role of internalizing and externalizing symptoms in the relationship between childhood trauma and suicidality among adolescents: a structural equation model. Child Adolesc Psychiatry Ment Health 15:79. 10.1186/s13034-021-00434-x
- Koeppel MDH, Bouffard L (2014) Sexual orientation, child abuse, and intimate partner violence victimization. Violence Vict 29:436–450. 10.1891/0886-6708.vv-d-12-00169
- Lansford JE, Dodge KA, Pettit GS, Bates JE (2010) Does physical abuse in early childhood predict substance use in adolescence and early adulthood? Child Maltreat 15:190–194. 10.1177/1077559509352359
- Leal G, Studart I, Figueiredo CPM, di Santi T, Suen P, Brasiliano S, Hochgraf PB, Bacchi PS (2024) Case report: Additional grounds for tighter regulation? A case series of five women with zolpidem dependence from a Brazilian women-specific substance use disorder outpatient service. Front Psychiatry 15:1456148. 10.3389/fpsyt.2024.1456148
- Lee WV, Gottheil E, Sterling RC, Weinstein SP, Serota RD (1997) Characteristics of cocaine-addicted individuals who abuse their partners. J Subst Abuse Treat 14:367–371. 10.1016/s0740-5472(97)00011-1
- Lima GCC, dos Passos CM, Pinheiro ALS, Ribeiro ÍJS, Maia EG (2025) Temporal trend and epidemiological profile of notifications of violence against women in Brazil: 2014–2023. Epidemiol Serv Saude 34. 10.1590/s2237-96222025v34e20240475.en
- Lotzin A, Grundmann J, Hiller P, Pawils S, Schäfer I (2019) Profiles of childhood trauma in women with substance use disorders and comorbid posttraumatic stress disorders. Front Psychiatry 10:674. 10.3389/fpsyt.2019.00674
- Malta DC, Silva AG da, Prates EJS, Alves FTA, Cristo EB, Machado ÍE (2021) Convergence in alcohol abuse in Brazilian capitals between genders, 2006 to 2019: what population surveys show. Rev Bras Epidemiol 24:e210022. 10.1590/1980-549720210022.supl.1
- Martin EL, Neelon B, Brady KT, Guille C, Baker NL, Ramakrishnan V, Gray KM, Saladin ME, McRae-Clark AL (2023) Differential prevalence of Adverse Childhood Experiences (ACEs) by gender and substance used in individuals with cannabis, cocaine, opioid, and tobacco use disorders. Am J Drug Alcohol Abuse 49:190–198. 10.1080/00952990.2023.2171301
- Na PJ, Shin J, Kwak HR, Lee J, Jester DJ, Bandara P, Kim JY, Moutier CY, Pietrzak RH, Oquendo MA, Jeste DV (2025) Social determinants of health and suicide-related outcomes: A review of meta-analyses. JAMA Psychiatry 82:337–346. 10.1001/jamapsychiatry.2024.4241
- Nakamura IB, Silva MT, Garcia LP, Galvao TF (2023) Prevalence of physical violence against Brazilian women: Systematic review and meta-analysis. Trauma Violence Abuse 24:329–339. 10.1177/15248380211029410
- Nelson CA, Sullivan EF, Valdes V (2025) Early adversity alters brain architecture and increases susceptibility to mental health disorders. Nat Rev Neurosci. 10.1038/s41583-025-00948-9
- O’Hare K, Watkeys O, Whitten T, Dean K, Laurens KR, Harris F, Carr VJ, Green MJ (2023) Cumulative environmental risk in early life is associated with mental disorders in childhood. Psychol Med 53:4762–4771. 10.1017/S0033291722001702
- Palermo T, Bleck J, Peterman A (2014) Tip of the iceberg: Reporting and gender-based violence in developing countries. Am J Epidemiol 179:602–612. 10.1093/aje/kwt295
- Rakovski C, Lalli M, Gu J, Hobson M, Wollenhaupt-Aguiar B, Minuzzi L, Kapczinski F, de Azevedo Cardoso T, Frey BN (2024) Childhood maltreatment as a predictor of substance use/misuse among youth: A systematic review and meta-analysis. Neurosci Biobehav Rev 166:105873. 10.1016/j.neubiorev.2024.105873
- Rueda P, Ferragut M, Cerezo MV, Ortiz-Tallo M (2021) Child sexual abuse in Mexican women: Type of experience, age, perpetrator, and disclosure. Int J Environ Res Public Health 18:6931. 10.3390/ijerph18136931
- Sauber EW, O’Brien KM (2020) Multiple losses: The psychological and economic well-being of survivors of intimate partner violence. J Interpers Violence 35:3054–3078. 10.1177/0886260517706760
- Schredl C, Lipinsky A, Humbert AL (2025) You can’t see what you don’t measure! A scoping review of measurements of gender-based violence, its determinants and consequences in academia. PLoS ONE 20:e0317872. 10.1371/journal.pone.0317872
- Simpson TL, Miller WR (2002) Concomitance between childhood sexual and physical abuse and substance use problems. Clin Psychol Rev 22:27–77. 10.1016/s0272-7358(00)00088-x
- Smith C, Thornberry TP (1995) The relationship between childhood maltreatment and adolescent involvement in delinquency. Criminology 33:451–481. 10.1111/j.1745-9125.1995.tb01186.x
- Spencer CN, Khalil M, Herbert M, Aravkin AY, Arrieta A, Baeza MJ, Bustreo F, Cagney J, Calderon-Anyosa RJC, Carr S, Chandan JK, Coll CVN, de Andrade FMD, de Andrade GN, Debure AN, Flor LS, Hammond B, Hay SI, Knaul FN, Lim RQH, McLaughlin SA, Minhas S, Mohr JK, Mullany EC, Murray CJL, O’Connell EM, Patwardhan V, Reinach S, Scott D, Sorenson RJD, Stein C, Stöckl H, Twalibu A, Vasconcelos N, Zheng P, Metheny N, Chandan JS, Gakidou E (2023) Health effects associated with exposure to intimate partner violence against women and childhood sexual abuse: a burden of proof study. Nat Med 29:3243–3258. 10.1038/s41591-023-02629-5
- Stouthamer-Loeber M, Loeber R, Homish DL, Wei E (2001) Maltreatment of boys and the development of disruptive and delinquent behavior. Dev Psychopathol 13:941–955. 10.1017/s0954579401004102
- Vahedi L, Qushua N, Seff I, Doering M, Stoll C, Bartels SA, Stark L (2023) Methodological and ethical implications of using remote data collection tools to measure sexual and reproductive health and gender-based violence outcomes among women and girls in humanitarian and fragile settings: A mixed methods systematic review of peer-reviewed research. Trauma Violence Abuse 24:2498–2529. 10.1177/15248380221097439
- Valério ID, Soares ALG, Menezes AMB, Wehrmeister FC, Gonçalves H (2022) Child maltreatment and substances use throughout adolescence and adulthood: Data from a Brazilian Birth Cohort. Child Abuse Negl 131:105766. 10.1016/j.chiabu.2022.105766
- Villar MG, Fava NM, Zucker RA, Trucco EM (2024) Internalizing pathways to adolescent substance use from adverse childhood experiences. Int J Environ Res Public Health 21. 10.3390/ijerph21111408
- Visioli C, Tondo L, Miola A, Pinna M, Contu M, Baldessarini RJ (2023) Early sexual or physical abuse in female and male mood disorder patients. J Psychiatr Res 167:125–131. 10.1016/j.jpsychires.2023.10.015
- Vorspan F, de Witt P, Zerdazi E-H, Karsinti E, Ksouda K, Icick R, Bellivier F, Marie N, Brousse G, Bloch V (2020) Chronic exposure to cocaine is associated with persistent behavioral disturbances. A cross-sectional dimensional study in outpatients with multiple substance use disorders. Psychopharmacology 237:3399–3407. 10.1007/s00213-020-05620-x
- Watts C, Zimmerman C (2002) Violence against women: global scope and magnitude. Lancet 359:1232–1237. 10.1016/S0140-6736(02)08221-1
- Widom CS (1989) Does violence beget violence? A critical examination of the literature. Psychol Bull 106:3–28. 10.1037/0033-2909.106.1.3
- Yang L, Jia F-F, Lu X-Y, Jia C-X (2023) Internalizing and externalizing problems mediate the relationship between maltreatment and self-harm among UK adolescents. J Affect Disord 333:240–248. 10.1016/j.jad.2023.04.046
Associated Data
Supplementary Materials
Data Availability Statement
No datasets were generated or analysed during the current study.