alcohol and domestic violence essay

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November 7, 2020 By Kristina Robb-Dover

The Destructive Link Between Alcohol Abuse and Domestic Violence

The links between alcohol and domestic violence are complex and not always well understood. While there is a lot of talk about  alcohol and the effects of drinking too much alcohol on the body and mind, there’s less talk about its ties to domestic violence. Indeed, alcohol abuse and domestic violence do seem to be inextricably linked, and while alcohol use may not necessarily “cause” domestic violence, alcohol can be a factor in increased aggression.

With the enormous pressures on families locked down during the COVID-19 pandemic and incidences of substance abuse and mental health issues skyrocketing, understanding what percentage of alcohol abuse is domestic violence-related or the reverse is eye-opening. The truth is that both alcohol use—(particularly alcohol abuse, addiction, and alcoholism)—and domestic violence are often escalating situations posing risks and dangers to all involved.

Understanding Alcohol’s Influence on Self-Control/Aggression

Much is known through research about how alcohol influences an individual’s self-control and aggressive tendencies. The common perception that drinking loosens inhibitions is accurate, as alcohol is a sedative that dulls adherence to rules and helps mask shyness and insecurities, which may lead to the drinker doing and saying things they otherwise wouldn’t.

Binge or heavy drinking causes a serious erosion in self-control that in some people can manifest as aggressive actions at the least provocation. Cases of alcohol and sexual assault after excessive drinking, most notably  college drinking  and sexual assault, are not uncommon.

According to the  National Coalition Against Domestic Violence , 10 million people each year suffer physical abuse at the hand of an intimate partner. Furthermore, domestic violence hotlines across the U.S. receive some 20,000 calls daily. The World Health Organization estimates that 55 percent of perpetrators of domestic violence drank alcohol before the assault . The 2010 National Intimate Partner and Domestic Violence Survey found that 48.4 and 48.8 percent of women and men, respectively, suffered psychological aggression by an intimate partner in their lifetime. Also, more than one woman in three in the U.S. has experienced physical violence, stalking, or rape by an intimate partner during their lifetime.

Domestic Violence Is Serious and Must be Addressed

Domestic violence occurs in many different forms. It does not always include physical abuse, at least not initially. Domestic violence includes:

• Physical abuse – including hitting, shoving, slapping, punching, kicking, forcing someone to have alcohol or drugs, physically restraining an individual, and aggravated assault (assault with a weapon).
• Emotional abuse – including threatening physical or sexual violence, displaying extreme jealousy, possessiveness, intimidation, degrading the other person’s comments and beliefs, or being disrespectful of them, preventing a partner from seeing friends or insisting on social isolation, blaming the other individual for their problems, and hiding or withholding forms of communication.
• Sexual abuse – including forced intercourse, sexual activity that follows an incident of physical abuse, sexual acts that are coerced, and threats of infidelity.
• Verbal abuse – including public humiliation, putdowns, yelling, name-calling, and criticizing another person’s beliefs, actions, and appearance.
• Economic abuse – including preventing someone from going to a job, taking away access to family finances, controlling behavior by withholding money, destroying personal property, or selling possessions and property without the other person’s consent.

Domestic Violence Fueled by Alcohol Abuse

A study published in the  International Journal of Environmental Research and Public Health   found high percentages of women who abused alcohol reporting histories of abuse: 88 percent reported physical abuse, 89 percent reported emotional abuse, and 76 percent reported sexual abuse. In the study, women said the abuse predominantly occurred during childhood (35, 33, and 20 percent, respectively).

With such traumatic histories of abuse and witnessing or being victimized by parents who may have been alcoholics or suffered from other forms of drug abuse, these women often found it difficult to break patterns of dysfunctional behavior and a tendency to seek out partners who were themselves drinkers or abusers. Thus, alcohol use and domestic violence may well play out in future generations, unless the cycle is stopped through intervention, treatment, perhaps legal recourse.

What are the Dangers Involved?

When one partner exerts coercive control over another and engages in repeated physical, emotional, and sexual abuse of that individual, numerous dangers exist, including unintended pregnancies, sexual diseases, HIV/AIDS, hospitalizations, even death. Children in the family who may witness parental drinking and domestic violence or intimate partner violence are likely to be themselves traumatized and may, according to research, go on to become abusers and heavy drinkers in adulthood.

For victims of domestic violence, turning to  alcohol as a means of coping  is cited across numerous studies. While ineffective and doing nothing to change the situation, alcohol use helps to mask, at least temporarily, some of the stresses, fears, and insecurities inherent in abusive relationships. Unfortunately, reliance on alcohol can lead to alcohol dependence and addiction, as well as worsening the family dynamic, endangering adults and children in this toxic atmosphere.

Suggestions for How to Remedy the Situation

If you are committing violence, seek help immediately.

The situation is not going to get better on its own. While you may profusely apologize following violent episodes and vow never to repeat such behavior, the fact is that domestic violence worsens over time without help. It takes a great deal of courage to face the truth and to be willing to get professional help to overcome behavior that falls under the category of domestic violence. If you drink and commit violence against loved ones and family members, you are destroying lives needlessly. Surely this isn’t something you want to do. Take steps to find help so you can overcome problems with alcohol and address any tendencies to be overly aggressive toward and threatening or controlling others you’re close to.

If You are Receiving or Near Someone Who May be Capable of DV, Seek Immediate Help

You don’t have to suffer alone or think it’s impossible to get out of the excessive control and power exerted over you by the perpetrator of domestic violence. This may be a spouse, partner, sibling, parent, adult child, or an extended family member living in the same house that is putting you in increasing danger, escalating threats, intimidation, stalking, harassment, usurping your freedom, and stepping up control over everything you do.

While seeking the advice and counsel of a psychiatrist, member of the clergy, a marriage counselor, or other professional help is a good idea, many of these individuals are not trained to specifically deal with domestic violence. As such, while you can get advice from them, it’s probably to your benefit to contact the local domestic violence service provider or call or access the domestic violence hotline online. If a local hotline isn’t available, contact the National Domestic Violence Hotline at 1-800-799-SAFE.

It may be that you’re close to someone whom you suspect or know is a victim of domestic violence or see the trajectory of explosive outbursts and patterns of behavior associated with domestic violence and believe the partner or individual is capable of committing violence against your friend. They are in desperate need of help and could potentially be able to avoid serious harm if you offer to assist on a confidential and inconspicuous basis.

The best approach is to provide non-judgmental support while simultaneously encouraging that friend to seek professional help. Be willing to listen, be sympathetic, and point them to available community services. These include domestic violence advocates that are accessible through local domestic violence hotlines and crisis centers. If the friend decides to leave, have them get in touch with domestic violence shelters or the local domestic violence hotline, or the National Domestic Violence Hotline at 1-800-799-SAFE. If the situation is currently violent, contact the police without delay. Time is critical for help to intervene when domestic violence erupts into a physical assault.

First Step for the Alcoholic: Seek Help

If there’s an alcoholic in the family, getting help for that individual should be a high priority. Yet the alcoholic will likely be resistant to seeking help and this may not be something family members can convince them to do. Still, self-protection for each member of the family is vitally important. You must do all you can to protect yourself, even if that means planning a safe exit from the home environment to escape repeated or potential domestic violence fueled by alcohol or other substance use, abuse, and addiction. Alcohol and domestic violence, once both reach a noticeable stage, demand action on the part of whoever can intervene.

Getting into an alcohol and drug rehab program, going into  detox , and following up with counseling, therapies, and treatments tailored to meet the alcoholic’s needs is the most important next step. Finding a treatment center that can also address issues of domestic violence with appropriate treatments, counseling and therapies is also vitally important. For those who have had problems with alcohol and sexual assault, including the victims of such abuse, treatment, family therapy, couples counseling,  women’s programs , and support groups can provide ongoing help.

If you are worried about alcohol and domestic violence in your family,  call or contact FHE Health  to learn about  alcohol addiction treatment programs and resources that may be available.

About Kristina Robb-Dover

Kristina Robb-Dover is a content manager and writer with extensive editing and writing experience... read more

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Intimate partner violence, substance use, and health comorbidities among women: A narrative review

Jacqueline b. mehr.

1 School of Environmental and Biological Sciences, Rutgers University – New Brunswick, New Brunswick, NJ, United States

Esther R. Bennett

2 School of Social Work, Rutgers University - New Brunswick, New Brunswick, NJ, United States

Julianne L. Price

3 Department of Kinesiology and Health, Rutgers University - New Brunswick, New Brunswick, NJ, United States

4 Center of Alcohol and Substance Use Studies, Graduate School of Applied and Professional Psychology, Rutgers University - New Brunswick, New Brunswick, NJ, United States

Nicola L. de Souza

5 School of Graduate Studies, Biomedical Sciences, Rutgers Biomedical and Health Sciences, Newark, NJ, United States

6 Department of Rehabilitation and Movement Sciences, School of Health Professions, Rutgers Biomedical and Health Sciences, Newark, NJ, United States

7 Department of Rehabilitation and Human Performance, Icahn School of Medicine at Mount Sinai, New York, NY, United States

Jennifer F. Buckman

Elisabeth a. wilde.

8 Department of Neurology, School of Medicine, The University of Utah, Salt Lake City, UT, United States

9 George E. Wahlen, VA Salt Lake City Healthcare System, Research Care Line, Salt Lake City, UT, United States

David F. Tate

Amy d. marshall.

10 Department of Psychology, College of the Liberal Arts, The Pennsylvania State University, State College, PA, United States

Kristen Dams-O'Connor

11 Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States

Carrie Esopenko

Exposure to intimate partner violence (IPV), including physical, sexual, and psychological violence, aggression, and/or stalking, impacts overall health and can have lasting mental and physical health consequences. Substance misuse is common among individuals exposed to IPV, and IPV-exposed women (IPV-EW) are at-risk for transitioning from substance misuse to substance use disorder (SUD) and demonstrate greater SUD symptom severity; this too can have lasting mental and physical health consequences. Moreover, brain injury is highly prevalent in IPV-EW and is also associated with risk of substance misuse and SUD. Substance misuse, mental health diagnoses, and brain injury, which are highly comorbid, can increase risk of revictimization. Determining the interaction between these factors on the health outcomes and quality of life of IPV-EW remains a critical need. This narrative review uses a multidisciplinary perspective to foster further discussion and research in this area by examining how substance use patterns can cloud identification of and treatment for brain injury and IPV. We draw on past research and the knowledge of our multidisciplinary team of researchers to provide recommendations to facilitate access to resources and treatment strategies and highlight intervention strategies capable of addressing the varied and complex needs of IPV-EW.

1. Introduction

It is estimated that one in three women worldwide experiences physical and/or sexual violence from an intimate partner ( Devries et al., 2013 ; Breiding et al., 2014 ; WHO, 2021 ). Intimate partner violence-exposed women (IPV-EW) frequently experience negative psychological ( Campbell, 2002 ; Afifi et al., 2009 ; Fletcher, 2010 ; Okuda et al., 2011 ; Brignone et al., 2018 ; Iovine-Wong et al., 2019 ) and physiological ( Campbell, 2002 ; Wuest et al., 2008 , 2010 ; Kwako et al., 2011 ) symptoms, as well as comorbidities such as depression, anxiety, posttraumatic stress disorder (PTSD; Dardis et al., 2021 ), and suicidal ideation ( Alhusen et al., 2015 ; Brignone et al., 2018 ; Iovine-Wong et al., 2019 ; Rasmussen et al., 2021 ). Substance misuse is also seen after IPV exposure in women ( Testa et al., 2003 ; Pallatino et al., 2019 ; Ogden et al., 2022 ). Furthermore, the physical and sexual trauma that often occurs in IPV increases the risk for bodily injuries that can result in chronic pain, as well as head, neck, and/or facial injuries that can cause traumatic brain injury (TBI) or acquired hypoxic–ischemic brain injury as a result of non-fatal strangulation (NFS) or other forms of impeded breathing ( Wilbur et al., 2001 ; Valera and Berenbaum, 2003 ; Wuest et al., 2008 ; St Ivany and Schminkey, 2016 ; Campbell et al., 2022 ; Walker et al., 2022 ) 1 . Large independent literatures have identified interrelationships between IPV exposure history and mental health diagnoses, chronic pain, brain injury, substance misuse, and substance use disorder (SUD; Merkel et al., 2017 ; Voon et al., 2018 ; Lutgendorf, 2019 ; Stone and Rothman, 2019 ; Campbell et al., 2022 ; Haag et al., 2022 ; Ogden et al., 2022 ; Oram et al., 2022 ); yet, few studies have attempted to piece together the complex interactions between these variables in a manner that supports frontline clinical strategies that more holistically bolster the quality of life for IPV-EW.

This narrative review begins this process by providing a broad framework for understanding substance use and misuse in IPV-EW to researchers and frontline clinicians. IPV and mental health comorbidities have been thoroughly discussed in the literature ( Campbell, 2002 ; Afifi et al., 2009 ; Okuda et al., 2011 ; Brignone et al., 2018 ), and the varied and complex interplay of these factors on risk of substance misuse and SUD warrants a targeted discussion. Despite the elevated risk for substance misuse and SUD associated with IPV, the causal pathways from IPV to SUD and the interaction between IPV exposure and comorbid mental health diagnoses, pain, and brain injury is not clearly understood. This dearth of research exploring mediating factors in the relationship between IPV and SUD interferes with the development of new treatment targets and improvement of clinical outcomes for IPV-EW. Moreover, it perpetuates common stigmas associated with substance misuse, including the identification of substance users as intractable, “difficult” to treat, and even incurable.

2. The relationship of substance use and IPV exposure

Substance misuse is defined as substance use at high doses or in inappropriate situations. SUD is a diagnosable illness that arises following prolonged substance misuse and that significantly alters health and daily functioning ( Campbell, 2002 ; McLellan, 2017 ). Substance misuse in IPV-EW has been reported as a means of coping with the physical and emotional pain ( Smith et al., 2012 ; Simonelli et al., 2014 ; Gezinski et al., 2021 ). Self-medication, defined in the general population as using alcohol, recreational drugs with analgesic properties, and prescription opioids to treat pain ( Alford et al., 2016 ; Cil et al., 2019 ; Rogozea et al., 2020 ), can accelerate the progression from substance use to SUD ( Timko et al., 2005 ; Lehavot et al., 2014 ; Hogarth et al., 2019 ); however, the use of psychoactive substances as self-medication is not specific to the IPV community - it is a common pathway to addiction across populations. Moreover, similar to research in other fields that links heavy and frequent use of psychoactive substances to risk of violence and assault, substance misuse and SUD has been shown to also place IPV-EW at an increased risk for future IPV victimization ( Kingery et al., 1992 ; Kilpatrick et al., 1997 ; Cunningham et al., 2009 ).

IPV exposure in women may increase the occurrence of risky substance use behaviors. For example, frequent patterns of heavy or binge drinking episodes ( Testa and Leonard, 2001 ; Martino et al., 2005 ; Weinsheimer et al., 2005 ; Hink et al., 2015 ; Ullman and Sigurvinsdottir, 2015 ) and drinking and driving ( Hanson, 2010 ) have been observed. Elevated rates of illicit substance use ( El-Bassel et al., 2005 ; Gilbert et al., 2012 ; Hink et al., 2015 ), misuse of prescription medications ( Smith et al., 2012 ; Hall et al., 2016 ), and needle sharing for intravenous substance use ( Braitstein et al., 2003 ; Wagner et al., 2009 ) have also been reported in women exposed to physical or sexual violence relative to non IPV-EW. These risky behaviors contribute to general poor health and increased mortality, even in circumstances where they do not reach criteria for a SUD diagnosis ( Patel et al., 2016 ; Dwyer-Lindgren et al., 2018 ; Gjersing and Bretteville-Jensen, 2018 ). For instance, intravenous substance use increases the risk for contracting highly communicable diseases like hepatitis C and human immunodeficiency virus (HIV) as well as other infections ( Lake and Kennedy, 2016 ). In addition, misuse of prescription medications and illicit substances is associated with greater risk of chronic illnesses like pulmonary complications and liver failure ( Baltarowich et al., 2018 ; Nanayakkara and McNamara, 2021 ).

Diagnostic criteria of SUD are stronger correlates of IPV than consumption patterns alone ( Cafferky et al., 2018 ). IPV-EW are more likely than non IPV-EW to transition from misuse to SUD and have greater SUD symptom severity ( Liebschutz et al., 2002 ; La Flair et al., 2012 ; Hobkirk et al., 2015 ). Estimates of 24%–75% ( Paone et al., 1992 ; El-Bassel et al., 2000 ; Beijer et al., 2018 ) of women report lifetime IPV exposure at SUD treatment intake. Similarly, the prevalence of SUD in IPV-EW is greater than in the general population ( Schneider et al., 2009 ; Smith et al., 2012 ; Stone and Rothman, 2019 ). In one study, half of women presenting to a shelter after IPV exposure report recent alcohol use, almost all of whom met criteria for alcohol use disorder (AUD; Poole et al., 2008 ). An overrepresentation of IPV-EW in substance use treatment facilities, and vice versa, is one indication that an optimal time to intervene for both IPV and SUD may be when women seek help for either IPV or SUD ( Bennett and O’Brien, 2007 ; Macy and Goodbourn, 2012 ).

Treatment-seeking samples, however, are not always representative of the population. Self-selection occurs as treatment-seekers are limited to those who are willing and able to attain medical help. Large scale community-based studies may therefore better describe rates of SUD and IPV in the general population. Although the prevalence of co-occurring SUD and IPV are lower in the community than treatment seeking samples, the associative patterns between the two remain strong ( Afifi et al., 2009 , 2012 ). Even when controlling for a number of sociodemographic variables and psychiatric comorbidities, women in community samples who report exposure to IPV have a greater occurrence of substance misuse and SUD than those without IPV exposure ( Afifi et al., 2012 ; La Flair et al., 2012 ; Salom et al., 2015 ). Interestingly, though, the SUD and IPV associations are often substance-specific and vary by the type of violence exposure, as will be explained in the following sections.

2.1. The IPV-SUD temporal relationship

The temporal relationship between IPV and SUD can be difficult to parse as IPV exposure and substance use often occur concurrently ( Caetano et al., 2000 ; Nowotny and Graves, 2013 ; Simonelli et al., 2014 ), and retrospective substance use can be difficult to confirm. Most findings describe either cross-sectional or single-time point data, as opposed to time-dependent relationships ( Testa and Leonard, 2001 ; Weinsheimer et al., 2005 ; Hanson, 2010 ; Smith et al., 2012 ; Hink et al., 2015 ; Ullman and Sigurvinsdottir, 2015 ; Hohman et al., 2017 ), although a handful of longitudinal and metanalytic studies have suggested that IPV more often precedes the onset of substance misuse/SUD ( Kilpatrick et al., 1997 ; Testa et al., 2003 ; El-Bassel et al., 2005 ; Carbone-López et al., 2006 ; Devries et al., 2014 ; Øverup et al., 2015 ). While some research indicates that current misuse of alcohol ( Devries et al., 2014 ) and other drugs ( Kilpatrick et al., 1997 ; Moore et al., 2008 ) is associated with future IPV, the current review will focus on substance use patterns that emerge after experiencing IPV ( El-Bassel et al., 2005 ).

2.2. Types and patterns of substance use following IPV

Alcohol is arguably the most commonly used psychoactive substance among IPV-EW ( El-Bassel et al., 2003 ; Finney, 2004 ; Afifi et al., 2012 ; Kraanen et al., 2014 ), unsurprising as it is also the most commonly used psychoactive substance in the world ( Peacock et al., 2018 ). Alcohol has acute analgesic properties ( Neddenriep et al., 2019 ; Boissoneault et al., 2020 ), making it a particularly frequent target of misuse among individuals experiencing physical pain. In-lab alcohol administration paradigms have shown a dose–response relationship between increased blood alcohol content (BAC) and decreased pain intensity, but only once BAC surpasses the legal limit (0.08%; Thompson et al., 2017 ). This suggests that the use of alcohol as an analgesic requires repeated high doses, a pattern of use that increases the odds of developing AUD ( Patrick et al., 2021 ). Testa et al. (2003) and Øverup et al. (2015) both found a high incidence of heavy/problem drinking episodes in the 1–2 year period following IPV exposure in IPV-EW relative to individuals who did not report exposure to IPV. This was supported by a 2014 meta-analysis that reported a positive association between IPV exposure and subsequent alcohol use in IPV-EW ( Devries et al., 2014 ) although the authors emphasized the need for more multi-wave longitudinal projects due to heterogeneity of measurement and the lack of control for confounds including partner’s alcohol consumption. These studies point to the importance of considering alcohol misuse in the context of pain self-management, particularly in women who may be less likely or able to seek medical treatment for injuries sustained as the result of an IPV-related assault. Reframing alcohol use through this lens may help clinical treatment providers to restructure alcohol-related conversations to reduce stigma and shame.

Among IPV-EW who are able and seek medical care, opiates are prescribed at a staggering rate - up to four times higher than in the general population ( Stene et al., 2012 ; Stone and Rothman, 2019 ). Although prescription medication use can serve to manage physical pain due to physical abuse ( Poole et al., 2008 ; Cole and Logan, 2010 ; Hemsing et al., 2016 ; Stone and Rothman, 2019 ; Williams et al., 2020 ), there is a lack of support for long term opiate management of pain, as chronic opiate use decreases pain tolerance ( Compton, 1994 ; Younger et al., 2008 ) and increases risk of physical dependence ( Compton et al., 2003 ; Raith and Hochhaus, 2004 ). Further, a prospective medical chart review found that women reporting IPV exposure had higher prescription rates than the general population for opiates and benzodiazepines ( Stene et al., 2012 ), both of which have high addiction potential and can be very dangerous when taken together ( Gudin et al., 2013 ; Afzal and Kiyatkin, 2019 ). Over-prescription also can drive a transition from prescription opiate to illicit opiate use, like heroin, among treatment-seeking individuals in the general population ( Hoffman et al., 2017 ; Volkow et al., 2019 ) and non-prescription opiate use has been documented among some IPV-EW ( Stone and Rothman, 2019 ; Williams et al., 2020 ) and as a consequence of IPV exposure ( El-Bassel et al., 2005 ).

Consistent with alcohol and opiate use patterns, cannabis use disorder is also more prevalent among IPV-EW than in the general population ( El-Bassel et al., 2000 ; Gilbert et al., 2012 ; Smith et al., 2012 ). While cannabis has been touted as effective for pain management ( Russo et al., 2007 ; Hill et al., 2017 ), clinical evidence remains limited, and some argue that cannabis use is more commonly used to cope with psychological as opposed to physical trauma in people exposed to IPV ( El-Bassel et al., 2011 ; Reingle et al., 2012 ) and a general population of young adults ( Bonn-Miller et al., 2008 ). Cannabis use for stress/coping purposes can increase risk of developing SUD ( Hyman and Sinha, 2009 ) and may be accompanied by a perpetuation of depressive and anxiety disorders and suicidal ideation in adolescents ( Copeland et al., 2013 ). Given the risk for mental health symptoms, such as depression and PTSD, among IPV-EW, and the prevalence of cannabis use in this population, research is needed to explore how cannabis interacts to either exacerbate or ameliorate mental health symptoms ( Haney and Evins, 2016 ; Lowe et al., 2019 ). Moreover, cannabis use should be considered in context of polysubstance use patterns that can arise from mixing recreational and prescription psychoactive substances. Such multi-drug patterns can exacerbate unsafe and unhealthy behavioral repertoires that can increase risk for revictimization and worsening overall physical and mental health. Thus, although national approval of medicinal and recreational cannabis use is growing, the risk for misuse and dependence in IPV-EW should not be ignored.

IPV-EW have indicated that their substance use can serve as a coping mechanism for the physical, as well as emotional pain of trauma exposure ( Øverup et al., 2015 ; Gezinski et al., 2021 ). Alcohol and recreational substance use in women is also impacted by partner behavior ( Owens et al., 2013 ; Derrick et al., 2019 ). In IPV-EW, some perpetrators may coerce or force IPV survivors to use addictive substances ( Warsaw and Tinnon, 2018 ). Added to that is the increased accessibility to addictive prescription medications due to the high likelihood for emergency room visits in this population because of injuries experienced ( Kothari and Rhodes, 2006 ; Rhodes et al., 2011 ; Hemsing et al., 2016 ). While reports suggest that a primary driver of substance use in IPV-EW is self-medication, the possibility that both IPV perpetrators and the medical community may exacerbate this behavior warrants significant consideration. Substance users remain highly stigmatized in our society and clinical treatment providers are urged to account for these external factors in the complex needs of IPV-EW.

3. Factors affecting the relationship between IPV exposure and substance use

3.1. sociodemographics.

Age, education, race, and socioeconomic status are established factors in the risk for IPV exposure ( Smith et al., 2018 ). Racial and ethnic minorities experience disproportionate rates of rape, physical violence, or stalking by an intimate partner ( CDC, 2017 ), and over 80% of Indigenous women in the United States have experienced IPV, stalking, or sexual violence ( National Institute of Justice, 2016 ; Rosay, 2016 ). Racial discrimination produces increased risk for IPV exposure ( Cho et al., 2014 ) and developing mental health issues after violence exposure ( Voth Schrag, 2017 ). Individuals with disabilities also experience higher rates of IPV ( Hughes et al., 2011 ; Plummer and Findley, 2012 ; García-Cuéllar et al., 2022 ) and face additional barriers to help-seeking ( Plummer and Findley, 2012 ). Similarly, racial discrimination increases the risk for developing a SUD ( Yoo et al., 2010 ; Otiniano Verissimo et al., 2014 ; Pro et al., 2018 ; Matsuzaka and Knapp, 2020 ), and racial and ethnic minority groups experience more severe consequences related to SUDs including treatment disparities, criminal justice involvement, morbidity, mortality, and violence ( Boyd et al., 2003 ; Smedley et al., 2003 ; Iguchi et al., 2005 ; Amaro et al., 2006 ; Mennis and Stahler, 2016 ; Matsuzaka and Knapp, 2020 ). Moreover, structural bias in the media has promulgated stereotypes about SUDs as a personal deficit specific to people of color, which again influences access to, and the quality of SUD treatment provided to minority groups ( Matsuzaka and Knapp, 2020 ).

Poverty and poor economic conditions are both a risk for and consequence of IPV exposure ( CDC, 2019 ; Fernandes-Alcantara, 2019 ). Socioeconomic mobility can be restricted through physical and psychological trauma by preventing educational attainment and causing job instability; 64% of IPV-EW report that violence exposure hindered their ability to work ( McLean and Bocinski, 2017 ). Likewise, income inequalities can be perpetuated through substance use related stigma in discriminatory employment and housing practices ( Earnshaw, 2020 ). Gender inequality in education, employment, and income further adds to this burden ( Niolon et al., 2017 ), as does overcrowding, high unemployment rates, neighborhood disadvantage, and low social resource capital ( Niolon et al., 2017 ; CDC, 2019 ). Moreover, because IPV exposure results in various physical and mental health needs, health care utilization costs are often high and many victims pay for services out of pocket or incur medical debt ( McLean and Bocinski, 2017 ). Economic barriers also negatively impact access to quality SUD treatment ( Matsuzaka and Knapp, 2020 ; CDC, 2022 ) and often delay treatment seeking due to lack of health insurance and/or reliable transportation ( Schmidt et al., 2007 ; Matsuzaka and Knapp, 2020 ; CDC, 2022 ). This delay in treatment seeking can impact the severity of substance misuse issues and the progression to SUD ( Lewis et al., 2018 ; Matsuzaka and Knapp, 2020 ). Finally, it is noteworthy that adverse childhood experiences (ACEs) including childhood physical and sexual abuse, adversity, and a family history of (or witness to) IPV are associated with increased risk for IPV exposure in adulthood as well as increased risk for substance use ( LeTendre and Reed, 2017 ; CDC, 2018 ; Currie and Tough, 2021 ; Leza et al., 2021 ). For frontline care providers, it is important to consider the intersecting effects of sociodemographics on IPV and substance use risk, particularly as such factors affect the breadth and quality of treatment strategies that are accessible to certain populations. These considerations can inform decisions regarding wraparound care and connection to resources.

3.2. Mental health

Exposure to IPV is associated with increased risk for onset of mental health disorders, with incidence rates highest for depression, anxiety, PTSD, and mood disorders ( Okuda et al., 2011 ; Ahmadabadi et al., 2020 ; Chandan et al., 2020 ; Mazza et al., 2021 ). Likewise, SUD demonstrates high comorbidity with mental health conditions and psychiatric disorders ( Grant et al., 2015 , 2016 ). Moreover a diagnosis of depression has been associated with subsequent alcohol misuse in IPV-EW ( La Flair et al., 2012 ). Additionally, in IPV-EW recruited from shelter populations and community samples, 60%–90% meet diagnostic criteria for PTSD ( Golding, 1999 ; Dutton et al., 2005 , 2006 ; Woods et al., 2008 ; Nathanson et al., 2012 ), and show greater symptom severity than trauma-exposed women who have not experienced IPV ( Pico-Alfonso, 2005 ; Sullivan and Holt, 2008 ; Woods et al., 2008 ). In parallel, nearly half of women who develop PTSD following exposure to IPV also develop comorbid SUD ( Najavits et al., 2004 ; Sullivan and Holt, 2008 ; Sullivan et al., 2012 ; Najavits and Hien, 2013 ). Women with a history of physical IPV and comorbid PTSD were nearly 15 times more likely to have days in which they use both alcohol and drugs than IPV-EW without PTSD ( Sullivan et al., 2016 ; McKee and Hilton, 2019 ). Not surprisingly, the use of alcohol and other drugs to cope with the mental health symptoms following IPV exposure can exacerbate mental health disorders, increase symptom severity, and perpetuate maladaptive coping ( Poole et al., 2008 ; Sullivan et al., 2012 ; Ullman and Sigurvinsdottir, 2015 ; Stoicescu et al., 2019 ). This sets a potentially cyclical relationship between IPV exposure, substance misuse, and mental health problems, which must be considered in all clinical contexts to reduce the potential for worsening mental health outcomes and the risk for revictimization ( Gearon and Bellack, 1999 ; Tol et al., 2019 ).

3.3. Brain injury and substance use

To-date, IPV-related brain injuries have been vastly understudied, yet the rates of partner-inflicted head trauma and probable brain injury among IPV-EW are estimated to be extremely high. For example, studies suggest that anywhere from 30% to 92% of participants report at least one episode of abuse with either exposure to head or neck trauma and/or probable brain injury ( Jackson et al., 2002 ; Valera and Berenbaum, 2003 ; St Ivany and Schminkey, 2016 ; Valera and Kucyi, 2017 ; Esopenko et al., 2021 ; Campbell et al., 2022 ). Another recent scoping review found that the prevalence of head trauma is between 19% and 100% across studies, with the large range being due to varied definitions of head trauma and brain injury as well as varied participant inclusion characteristics (e.g., inclusion of only participants with injuries to the head; Haag et al., 2022 ).

Repetitive exposure to head trauma is also of significant concern as at least 50% of individuals within these samples report multiple episodes of head, neck, and facial trauma ( Wilbur et al., 2001 ; St Ivany and Schminkey, 2016 ; Valera and Kucyi, 2017 ; Zieman et al., 2017 ). Imporantly, each head, neck, and/or facial trauma that occurs as a result of physical and sexual violence in IPV has the potential to result in a brain injury ( Capizzi et al., 2020 ; Esopenko et al., 2021 ; Meyer et al., 2021 ; Saleem et al., 2021 ). IPV-related TBI can occur due to being punched, kicked, thrown, hit with an object, or shaken, all of which can result in focal and/or diffuse axonal injury ( Sheridan and Nash, 2007 ; Valera et al., 2019 ). NFS, suffocation, and other forms of impeded breathing occurring as a result of IPV can cause hypoxic–ischemic brain injuries from a lack of, or decrease in, oxygen to the brain ( Jackson et al., 2002 ; Valera and Berenbaum, 2003 ; Kwako et al., 2011 ; Haag et al., 2022 ; Valera et al., 2022 ). With so many avenues for brain trauma, it is probably unsurprising that estimates suggest that approximately 23 million people are living with IPV-related brain injury in the United States alone ( St Ivany and Schminkey, 2016 ).

In the general population, there is some evidence that substance use increases following brain injury, but other factors, such as premorbid substance use, injury severity, and age at time of injury also affect this relationship ( Ponsford et al., 2007 ; Pagulayan et al., 2016 ; Kennedy et al., 2017 ; Merkel et al., 2017 ; Shiwalkar et al., 2017 ; Schindler et al., 2021 ). Moreover, the high prevalence of IPV-related head trauma and probable brain injuries, coupled with other factors discussed above (e.g., comorbid mental health symptoms), likely increases the risk of SUD ( Oliverio et al., 2020 ; Oakley et al., 2021 ). For example, one study of female veterans who all screened positive for TBI found that only the women who also reported a lifetime history of IPV had a SUD diagnosis ( Iverson et al., 2020 ). In the general population, the neural changes and resulting cognitive and psychological impairments occurring after TBI are strong predictors of substance use, misuse, and development of SUD ( Graham and Cardon, 2008 ; Weil et al., 2016 ; Beaulieu-Bonneau et al., 2018 ; Olsen and Corrigan, 2021 ), and contribute to poorer treatment outcomes ( Corrigan and Deutschle, 2008 ; Graham and Cardon, 2008 ). However, the cause-and-effect relationship between TBI and substance use is complex and hard to parse as substance use is both a risk factor for, and sequelae of, TBI ( Nikoo et al., 2017 ; Eskander et al., 2020 ). Nonetheless, there is evidence that brain injury often remains undiagnosed among IPV-EW, as substance misuse and mental health issues mask brain injury symptoms, thereby precluding effective assessment and treatment for brain injury ( Banks, 2007 ; Haag et al., 2022 ). Undiagnosed brain injury has far-reaching mental and physical health consequences, and failure to identify brain injury in the clinical context could prove detrimental to the long-term outcomes of IPV-EW, by impeding delivery of adequate and effective therapies. ( Comper et al., 2005 ). It also can perpetuate stigmas associated with SUD, such as patients being “difficult” and the disease as being intractable.

4. Facilitating substance use intervention strategies for IPV-EW

4.1. acknowledging barriers to care.

The combined exposure to IPV and SUD creates barriers (i.e., women with SUDs being denied shelter admission) that inhibit access to treatment for either IPV or SUD ( Logan and Walker, 2004 ; Humphreys et al., 2005 ; Klostermann, 2006 ; Macy and Goodbourn, 2012 ). Standard trauma-informed frameworks are not always sufficient to treat the complex needs of IPV survivors who are also coping with substance use problems ( Macy and Goodbourn, 2012 ; Capezza et al., 2015 ), and SUD treatment facilities rarely screen for IPV exposure ( Bennett and Lawson, 1994 ; Collins et al., 1997 ; Logan et al., 2002 ). Another consideration is encouragement or coercion by partners to continue drug use ( Gilbert et al., 2001 ; Simonelli et al., 2014 ; USDHHS, 2020 ). For instance, partner opposition to SUD treatment entry poses a barrier to recovery ( Amaro and Hardy-Fanta, 1995 ; USDHHS, 2020 ), and IPV perpetrators may keep substances around the home and pressure or force their partner to use substances ( USDHHS, 2020 ). Additionally, brain injury-related cognitive and neurobehavioral impairments can make it harder for those with brain injury and IPV exposure to gain access to, stick with, and benefit from standard treatments for SUD ( Vungkhanching et al., 2007 ; Olson-Madden et al., 2012 ). These barriers , in general SUD samples, have been shown to undermine the likelihood of SUD treatment success ( Bates et al., 2006 , 2013 ). Thus, the creation and implementation of treatment options that include cognitive and neurobehavioral support remain urgently needed.

4.2. Screening

Given that mental health diagnoses, including SUD, increase the risk of continued and future victimization ( Gearon and Bellack, 1999 ; Friedman and Loue, 2007 ), it would be beneficial for all emergency departments and mental health facilities to screen for history of IPV, and associated comorbidities, particularly exposure to head, neck, and facial trauma and probable brain injury, in anyone seeking treatment for these conditions ( Waalen et al., 2000 ; Clark et al., 2008 ; Rabin et al., 2009 ; Radcliffe and Gilchrist, 2016 ; Gilchrist and Hegarty, 2017 ; Iverson et al., 2020 ). Likewise, screening for IPV and brain injury in substance use treatment programs is also needed as efficacy is significantly reduced in IPV-EW who are not receiving care and resources related to violence exposure ( Capezza et al., 2015 ). Similarly, screening for SUD in anyone seeking IPV treatment and shelter services not only increases the safety of IPV populations, as research shows SUD is linked with re-victimization, but will also provide timely SUD treatment ( Kilpatrick et al., 1997 ; Capaldi et al., 2012 ; Simmons et al., 2014 , 2017 ; McKee and Hilton, 2019 ). Free, validated self-report tools, such as the Alcohol Use Disorders Identification Test (AUDIT; Saunders et al., 1993 ), the Drug Abuse Screening Test (DAST-10; Skinner, 1982 ; Bohn et al., 1991 ), and the Alcohol, Smoking, and Substance Use Involvement Screening Test (ASSIST; Humeniuk et al., 2010 ) are readily available and can be used to quickly assess alcohol and substance misuse. Health care agencies could also serve a greater number of IPV-EW who need SUD treatment, but who may lack health insurance coverage and/or are financially dependent on an IPV perpetrator ( Clark et al., 2008 ; Foster et al., 2010 ; Priester et al., 2016 ), by including an assessment of financial need to ensure access to services regardless of financial limitations ( Hageman and George, 2018 ). Screening processes may best be facilitated by social work staff trained in resource facilitation and could increase the likelihood that basic needs are also met ( Macy et al., 2013 ). Lastly, key stakeholders, including domestic violence and SUD agencies could further improve outcomes by screening and referring IPV-EW for brain injury-related services, as cognitive deficits resulting from brain injury can make a survivor’s physical and emotional healing more difficult ( Iverson and Pogoda, 2015 ; Haag et al., 2022 ) and, more generally, SUD treatment less efficacious.

4.3. CBT-based interventions

Intervention research shows support for cognitive-behavioral therapies (CBT) as most effective for targeting PTSD, depression, emotional well-being, and substance misuse in IPV groups ( Eckhardt et al., 2013 ; Arroyo et al., 2017 ). A systematic review and meta-analysis found that CBT-based interventions specifically tailored for the unique needs of IPV survivors resulted in the largest effect sizes for outcomes such as PTSD, depression, and self-esteem with moderate effect size decreases in substance use outcomes ( Arroyo et al., 2017 ). Other recent research demonstrates the efficacy of CBT with interventions such as Helping to Overcome PTSD through Empowerment [HOPE] ( Johnson and Zlotnick, 2009 ). This CBT-based HOPE intervention was developed specifically for IPV-EW who were also residing in a shelter and was shown to reduce the likelihood for revictimization. Cognitive Trauma Therapy for Battered Women (CTT-BW) is another intervention developed to address trauma history, exposure to abuse and abuser reminders, as well as monitoring of negative self-talk and cognitive therapy for guilt ( Kubany et al., 2004 ). CTT-BW showed significant reductions in PTSD and depressive symptoms among IPV-EW that were maintained at 6-month follow-up ( Kubany et al., 2004 ).

4.4. Concurrent IPV/SUD treatment

There is evidence that concurrent IPV services and substance use treatment may be a more effective approach than treating IPV or SUD on their own ( Capezza and Najavits, 2012 ; Macy and Goodbourn, 2012 ; Capezza et al., 2015 ). For example, one treatment strategy designed to address both trauma symptoms and SUD, known as Seeking Safety, has been efficacious in reducing SUD and PTSD symptoms ( Najavits, 2007 ) and has been recommended for use with IPV groups ( Cohen et al., 2013 ; McKee and Hilton, 2019 ). By utilizing one facility with the same team of treatment personnel, coordination is efficient, cost-effective, and there is a greater likelihood that individuals will attend, complete, and benefit from the program ( Mueser et al., 2003 ; Poole et al., 2008 ; Murphy and Ting, 2010 ; Capezza et al., 2015 ; McKee and Hilton, 2019 ).

4.5. Teaching and strengthening resilience

A crucial consideration for substance use treatment programs for IPV-EW is resilience, a process of positive adaptation despite adverse conditions ( Crann and Barata, 2016 ; Tsirigotis and Łuczak, 2018 ; Rollero and Speranza, 2020 ; Gonzalez-Mendez and Hamby, 2021 ). Resilience is a skill set that promotes beneficial responses to avoid negative outcomes and reduce harmful effects on physical and psychological functioning ( Luthar et al., 2000 ; Humphreys, 2003 ; Gonzalez-Mendez and Hamby, 2021 ). Among IPV-EW, higher resilience has been consistently correlated with lower levels of PTSD, depression, anxiety, psychological distress, and risk for substance use ( Humphreys, 2003 ; Anderson et al., 2012 ; Gonçalves and Matos, 2020 ). Interventions that can both teach and strengthen resilience have been shown to improve IPV-EW’s confidence, independence, power, and positive social relationships, all of which contribute positive outcomes ( Humphreys, 2003 ; Decker et al., 2020 ). Research has shown that IPV-EW who employ strategies such as physical activity, creativity, spirituality, introspection, and optimism are more likely to demonstrate greater resilience, positive adaptation, self-efficacy, and healing from abuse ( Drumm et al., 2014 ; López-Fuentes and Calvete, 2015 ). Similarly, interventions that empower IPV-EW to access and use their strengths (e.g., social resources, help-seeking behaviors, assertiveness, problem-solving skills) enable survivors to respond to partner violence and related sequelae with healthier behavioral strategies, ultimately resulting in a decreased risk for substance use problems ( Luthar et al., 2000 ; Humphreys, 2003 ; Sani and Pereira, 2020 ).

Several studies have documented that an increase in resilience is associated with decreased substance use and SUD recovery ( Elm et al., 2016 ; McKinley and Theall, 2021 ; Yamashita et al., 2021 ). In fact, one study demonstrated that women with greater resilience, defined as a strong sense of self, an awareness of the abuse, a knowledge of resources, and a future hope, showed more awareness of how their abuser’s and their own substance use contributed to the maintenance of the abusive relationship ( Werner-Wilson et al., 2000 ). This increased awareness is a crucial factor needed for ending the potentially cyclical nature of substance use in IPV ( Gutierres and Van Puymbroeck, 2006 ). In addition, increased resilience is associated with healthier and safer decision making in IPV-EW which supports efforts to reduce risk for revictimization ( McFarlane et al., 1997 ; Humphreys, 2003 ; Decker et al., 2020 ; Schaefer et al., 2021 ). The ability of resilience to reduce physical and psychological distress, while improving overall health, could make it a key target for recovery from SUD ( Gorvine et al., 2021 ). Teaching and strengthening resilience could provide a positive, empowering, and healthy alternative for IPV-EW to obtain relief from the physical pain and psychological trauma symptoms that may be underlying the use of alcohol and other drugs ( Hernandez and Mendoza, 2011 ; Gorvine et al., 2021 ). With prior research demonstrating the power of resilience to reduce substance use and misuse, future research is necessary to expand the potential for SUD prevention in IPV using the resilience framework ( Gorvine et al., 2021 ; Yamashita et al., 2021 ).

5. Conclusion

The complex and cyclical relationship between IPV exposure and substance misuse warrants significantly more research and clinical attention, particularly considering that both demonstrate complex interactions with with highly comorbid factors, such as mental health problems and brain injury. Critical next steps include cross-fertilization of ideas, theories, and data from fields such as social work, psychology, neuroscience, addiction, and women’s health. This review presents evidence for an elevated risk for misuse of recreational and prescription substances in this population, but emphasizes a need for clinicians to reframe perspectives on this use to improve outcomes for all IPV-EW. Clinicians are urged to consider substance use in light of physical and emotional pain that often results from violence exposure, and take care to screen for SUDs prior to prescribing potentially addictive medications. Mental health disorders and IPV-related brain injuries are additional factors for clinicians to consider. It is only when substance use, mental health, and brain health are considered together that IPV-EW will gain access to optimal treatment strategies. In the absence of such comprehensive screening, IPV-EW may appear unable or unwilling to affect meaningful change to improve their quality of life, thereby perpetuating the stigma and bias that remains deeply entrenched against IPV survivors and substance users.

The suggested clinical approach, derived from the evidence reviewed, is for concurrent treatment of IPV and SUD, with added infrastructure for mental health and cognitive support to facilitate treatment seeking, treatment gains, and long-term quality of life - both in terms of violence exposure and substance use. Clinicians treating those with IPV should consider SUD, mental health diagnoses, and cognitive impairments in terms of clinical presentation and severity. Likewise, those providing SUD treatment should assess for IPV exposure as well as mental and brain health, as this may strongly alter the optimal treatment path ( WHO, 2013 ). It is acknowledged, however, that such comprehensive screenings are time and resource intensive, and may not be feasible in all contexts. Yet, even for those with limited time and resources, such as emergency department health care providers and shelter workers, building knowledge of these comorbidities is essential for improving outcomes for IPV-EW. Future research should be directed at probing the interplay of SUD, brain injury, mental health, and IPV, as well as testing which screening and recovery protocols provide the best treatment outcomes in IPV-EW experiencing SUD across different contexts.

Author contributions

CE, JB, EW, DT, AM, and KD-O’C were involved in manuscript conceptualization. JM, EB, CE, and JB wrote the initial paper draft. JP and NS provided editorial and conceptual feedback. All authors contributed to the article and approved the submitted version.

CE, EW, and DT are supported by the National Institutes of Neurological Disorders and Stroke [R01NS115957]. DT is also supported by the and the National Institute of Neurological Disorders and Stroke [R01NS122184; R61NS120249]. JB is supported by a NIH/NIAAA K-award [K02AA025123]. JP is supported through the NIH postdoctoral fellowship training program [T32AA028254]. KD-O’C is supported by the National Institute on Disability, Independent Living, and Rehabilitation [90DPTB0009] and the International Alzheimer’s and Related Dementias Research Portfolio [1RF1NS115268].

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

1 Brain injury will be used as an umbrella term for IPV-related TBI and/or hypoxic–ischemic brain injury (described in section 3.3).

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Alcohol, Aggression, and Violence: From Public Health to Neuroscience

Affiliations.

• 1 National Forensic Sciences University, Gandhinagar, India.
• 2 Centre for Research in Psychology and Human Well-Being, Faculty of Social Sciences and Humanities, Universiti Kebangsaan Malaysia, Bangi, Malaysia.
• 3 Department of Pharmacology, Faculty of Medicine, Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur, Malaysia.
• 4 Department of Family Medicine, Faculty of Medicine, Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur, Malaysia.
• 5 Neuropharmacology Research Laboratory, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Subang Jaya, Malaysia.
• 6 Department of Physiology, Faculty of Medicine, Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur, Malaysia.
• PMID: 35002823
• PMCID: PMC8729263
• DOI: 10.3389/fpsyg.2021.699726

Alcohol has been associated with violent crimes and domestic violence across many nations. Various etiological factors were linked to chronic alcohol use and violence including psychiatric comorbidities of perpetrators such as personality disorders, mood disorders, and intermittent explosive disorders. Aggression is the precursor of violence and individuals prone to aggressive behaviors are more likely to commit impulsive violent crimes, especially under the influence of alcohol. Findings from brain studies indicate long-term alcohol consumption induced morphological changes in brain regions involved in self-control, decision-making, and emotional processing. In line with this, the inherent dopaminergic and serotonergic anomalies seen in aggressive individuals increase their susceptibility to commit violent crimes when alcohol present in their system. In relation to this, this article intends to investigate the influence of alcohol on aggression with sociopsychological and neuroscientific perspectives by looking into comorbidity of personality or mood disorders, state of the mind during alcohol consumption, types of beverages, environmental trigger, neurochemical changes, and gender differences that influence individual responses to alcohol intake and susceptibility to intoxicated aggression.

Keywords: aggression; alcohol; brain; domestic; public health; serotonin; violence; violent.

Copyright © 2021 Sontate, Rahim Kamaluddin, Naina Mohamed, Mohamed, Shaikh, Kamal and Kumar.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Article Contents

Introduction, correlations and typologies, complex interdependencies, group 1 exemplar. victim was never substance dependent, group 2 exemplar. victim was desisting from substance use, group 3 exemplar. victim was substance dependent, discussion and conclusion.

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The Dynamics of Domestic Abuse and Drug and Alcohol Dependency

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David Gadd, Juliet Henderson, Polly Radcliffe, Danielle Stephens-Lewis, Amy Johnson, Gail Gilchrist, The Dynamics of Domestic Abuse and Drug and Alcohol Dependency, The British Journal of Criminology , Volume 59, Issue 5, September 2019, Pages 1035–1053, https://doi.org/10.1093/bjc/azz011

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This article elucidates the dynamics that occur in relationships where there have been both substance use and domestic abuse. It draws interpretively on in-depth qualitative interviews with male perpetrators and their current and former partners. These interviews were undertaken for the National Institute for Health Research-funded ADVANCE programme. The article’s analysis highlights the diverse ways in which domestic abuse by substance-using male partners is compounded for women who have never been substance dependent, women who have formerly been substance dependent and women who are currently substance dependent. The criminological implications of the competing models of change deployed in drug treatment and domestic violence intervention are discussed alongside the policy and practice challenges entailed in reconciling them within intervention contexts where specialist service provision has been scaled back and victims navigate pressures to stay with perpetrators while they undergo treatment alongside the threat of sanction should they seek protection from the police and courts.

The 2019 Domestic Abuse Bill proposes to establish a statutory definition of domestic abuse that includes ‘controlling, coercive, threatening behaviour, violence or abuse’ encompassing ‘psychological, physical, sexual, economic and emotional forms of abuse’ ( HM Government, 2019 : 5). It proposes to widen the scope of Domestic Abuse Protection Orders so that suspected perpetrators of domestic abuse can be compelled to attend ‘drug or alcohol treatment’, as well as ‘behavioural change’ programmes by the family courts (if petitioned by victims or other relevant third parties, such as non-governmental organizations) and magistrates courts (where the police would normally petition) (ibid. Explanatory Note Clause 3: 128). It is proposed that compliance with such orders will be secured in part through electronic monitoring. Breaches of such orders will be a criminal offence, punishable by up to ‘five years’ imprisonment, unlimited fine or both’ (ibid. 30).

The Bill is informed by a prolonged consultation in which over 3,200 responses were received by government and expert opinion—primarily from organizations representing victims and survivors of domestic abuse and stalking—was submitted to two Home Affairs Committees ( House of Commons, 2018 ). Cross-party support for the Bill was secured: as politicians registered the volume of domestic abuse cases raised with them by constituents; amidst news that the daughter of an MP had committed suicide following a relationship in which she suffered psychological—but not physical—torment that caused her to fear that she was mentally ill ( Elgot, 2018 ); and during a campaign by David Challen to enable his mother to appeal her conviction for murdering his coercively controlling father ( Moore, 2018 ). In strengthening the prohibition of ‘coercive control’ ( Home Office, 2015 : 2)—a concept advanced by Stark (2007 : i) to explain ‘how men entrap women in personal life’ through ‘intimate terrorism’—the Bill can be read as a logical extension of three decades of Conservative party policy that conceives the criminalization of a dangerous minority of men who abuse ‘very vulnerable women and girls’ to be a key part of the solution to domestic abuse ( Heidensohn, 1995 ; Gadd, 2012 ). But this Bill was conceived within a more nuanced policy agenda than its predecessors. In the initial consultation document Transforming the Response to Domestic Abuse, which sought views on a raft of new measures, the then-Home Secretary, Amber Rudd, and Justice Secretary, David Gauke, called for policy that (1) recognizes that both ‘women and men are victims of domestic abuse’, though ‘a disproportionate number of victims are women, especially in the most severe cases’ ( HM Government, 2018 : 3); (2) ‘actively empowers victims, communities and professionals to confront and challenge’ domestic abuse; and (3) reduces regional variation in the quality of ‘services to help victims’ and ‘punish and rehabilitate offenders’ (ibid, our emphases). This receptivity to the rehabilitative ambitions of health and social care professionals derived principally from the findings of domestic homicide and serious case reviews (ibid, p21), which reveal the pertinence of a ‘toxic trio’ of domestic abuse, mental health issues and drug and alcohol problems in cases where women or children are killed ( Brandon et al., 2010 ; Robinson et al., 2018 ), and how substance use features in around half of intimate partners homicides in the United Kingdom ( Home Office, 2016 ). Transforming the Response to Domestic Abuse followed suit, highlighting the ‘complex needs’ of those living with ‘drug and alcohol misuse, offending, mental illness and poverty’ ( HM Government, 2018 : 10); domestic abuse ‘victims’ with ‘problematic drug use’ (p24); ‘survivors… who have children on child protection plans’ (p28); ‘women at risk of having their children removed’ (p28); ‘female offenders’ who have also ‘experienced domestic abuse’ (p31); and male ‘perpetrators’, who are too often depicted in terms of the ‘stereotype’ of a ‘drunk… who… loses control and assaults their partner’ (p11). Such ‘simplistic’ depictions were debunked for failing to ‘reflect… the complex reality and lived experience of victims’ and impervious to the ‘dynamics of power and control which are present in many abusive relationships’ (ibid. pp11 and 12). They had previously been challenged by official drugs policy that committed to supporting the disproportionate number of ‘intimate partner violence’ victims and perpetrators accessing substance misuse services ( HM Government, 2017 ).

This article responds to this call to redress the dynamics of power that occur in relationships where substance use and domestic abuse co-occur. We contribute to such an understanding through the presentation of three couple dyads—each comprising a male perpetrator and his female partner—interviewed in-depth for the UK National Institute for Health Research funded Advancing theory and treatment approaches for males in substance use treatment who perpetrate intimate partner violence (ADVANCE) programme 1 . Our conclusion returns to the challenges the 2019 Domestic Abuse Bill poses to policy, practice and criminological theorizing.

Evidence for the relationship between domestic abuse and drug and alcohol intoxication is plentiful in crime surveys but tends to focus, peculiarly, on the behaviour of victims more often than offenders. For example, the 2016 Crime Survey for England and Wales revealed that ‘adults aged between 16 and 59 who had taken illicit drugs in the last year’ were three times more likely to report ‘being a victim of partner abuse’ than those who had not done so ( ONS, 2016 : 25). However, using illicit drugs does not invite assault and the identification of such ‘risk factors’ in the absence of explanation of their relevance accentuates the victim-blaming some perpetrators deploy to control their victims ( Gadd et al., 2014 ). The international evidence reveals that men, but not women, tend to perpetrate more severe assaults when they have been drinking ( Graham et al., 2011 ; Reno et al., 2010 ). Women are more vulnerable to assault when they too are intoxicated, but this is at least partly because those living with abusers are less diligent at pursuing safety strategies when they have been drinking ( Iverson et al., 2013 ). Substance use features in around half of all UK domestic homicides. Since 2011, substance use has been detected among domestic homicide perpetrators more than four times as often as it has among those killed by them ( Home Office, 2016 )

In sum, the relationship between substance use and domestic abuse is not straightforward. Moreover, Different substances have different pharmacological properties. They are used in variable quantities and combinations fostering a range of effects—including docility as much as aggression—that are contingent upon the user’s experience of them, prehistory of use, mood and the context in which the consumption takes place ( Zinberg, 1984 ; Gilchrist et al., 2019 ). Laboratory research reveals that those with low levels of inhibition, empathy and self-regulation and elevated levels of sensitivity to threats and insults (‘instigative cues’) are more prone to violence when they have consumed alcohol up to four hours ahead of a perceived threat or ‘provocation’ ( Leonard and Quiqley, 2017 ). Cocaine consumption can induce similar reactions. Like cannabinoids and opiates—the effects of which are rarely studied in the context of aggression or violence—cocaine can also alleviate anxiety and exacerbate underlying problems with depression, paranoia and hallucinations ( Sacks et al., 2009 ). Consequently, regular use of such drugs, like the consumption of excessive alcohol, can impinge upon mental well-being and intimacy, generating indirect and belated relationships between victimization and substance use that extend far beyond periods of intoxication.

Feminist scholarship on domestic abuse has tended not to engage with the pharmacological impacts of substance use and has focussed instead on how some abusive men retain power over women by attributing their violence to intoxication, by insisting that their drinking caused them to act out of character, or by denying any memory of assaults perpetrated when intoxicated ( Hearn, 1998 ; MacKay, 1996 ). Evaluations of interventions for perpetrators have thus needed to be alert to the ways in which substance use is invoked to minimize violence. Women’s accounts of victimization have had to take precedence over men’s self-reported offending as measure of changes given the potential for such minimization ( Dobash et al., 1999 ). But as Stark’s (2007) review of officially reported ‘intimate terrorism’ cases illustrates, substance can also be implicated in the perpetration of ‘coercive control’ and victims’ responses to it. His analyses reveal that some victims do self-medicate to manage the depression the daily anticipation of violence engenders and that some perpetrators control victims by increasing their dependence on substances before restricting their access to them. Finally, Stark highlights that some women who have been terrorized over many years take matters into their own hands after the law has failed to protect them, mounting grievous attacks on perpetrators when they are too intoxicated to retaliate.

Typological research on men’s domestic abuse perpetration has also addressed the role of drugs and alcohol anecdotally. For example, Holtzworth-Munroe and Stuart (1994) suggest that there are three distinct types of male domestic abuse perpetrator, one of which—the ‘antisocial batterer’—is defined by their dependence on drugs and alcohol, engagement in crime and paternalistic values. The other two groups, they propose, include ‘family only batterers’ who are seemingly ‘normal’ men who are violent at home and conventional in their sexism; and ‘emotionally dysphoric batterers’ with clinically diagnosable ‘borderline personality disorders’ who tend to be overtly misogynistic, especially when their relationships are failing, or they distrust the fidelity of their partners. Yet, what the relationship is between substance use and violence for the antisocial batterer remains untheorized in Holzworth and colleagues’ tests of their typology ( Holtzworth-Munroe et al., 2000 ). This is despite clinical evidence suggesting that drug use and violence co-occur most among men with diagnosed mental health issues, poor concentration and problems understanding and remembering their pasts ( Sacks et al., 2009 ). In relation to ‘family only’ perpetrators, Johnson et al. (2014 : 65) suggest that this group is more likely to be involved in ‘situational couple’ and ‘separation-instigated’ violence that is more ‘gender-symmetrical’, and derivative of arguments over domestic matters, finances, childcare or ‘objections to the other partner’s excessive drinking’ that evolve into ‘fights’. For this subgroup of ‘family only perpetrators’, the link between alcohol consumption and domestic abuse may have more to do with everyday conflicts than personality traits, though the difference between them and intimate terrorists can be overdrawn ( Gadd and Corr, 2017 ). Sociologically speaking, control ‘is a continuum. Everyone controls their partner to some extent’ ( Johnson, 2008 : 87), begging the question as to when and why the desire to control becomes pertinent.

Answers to this question can be found in the few qualitative studies that explore how drugs and alcohol feature in the relationships of couples living with domestic abuse. These reveal that some perpetrators pose greater risks to their partners, not when they are high, but when they are irritable, withdrawing or are struggling to finance alcohol or drug purchases ( Gilchrist et al., 2019 ). One exemplar is Hydén’s (1994) study of middle-class Swedish couples reported to the police for domestic abuse. Follow-up interviews with 20 couples where alcohol consumption was noted by the police revealed that, although drunkenness and its expense were the source of many arguments that led to violence, social drinking, especially at parties, was also what held some relationships together. Afterwards, some couples reconciled on the basis that it was the alcohol that caused the conflict. They asserted that the perpetrator was normally a ‘good person’ who could be helped. Men who had caused injuries when intoxicated often claimed they could only recall feeling hurt—sometimes in ways that reminded them of painful experiences in their pasts—by female partners who criticized them or acted aggressively towards them and not the assaults they themselves had perpetrated.

Evidence of the relevance of emotional pain can also be found in Motz’s (2014) case analyses of couples in therapy. This reveals how some women who had been abused or neglected as children attempted to cope with feelings of vulnerability ‘through the creation of highly dependent relationships with men who… offer… protection, and through getting into states of mind where these feelings can be pushed away… through drugs or alcohol’ (p69). Motz depicts the emotionally impoverished lives of abusive men with whom some drug-using women cohabit, many of whom feared abandonment because of experiences of abuse, neglect or institutional care. Some of these men had ‘little capacity to tolerate emotional intimacy’ (p93) and thus found it ‘impossible to relate’ to their families or sexual partners unless ‘high on drugs’ (p93). Over time, Motz suggests, these couples became ‘doubly dangerous’, leaving their children uncared for when intoxicated, withdrawing or fighting, and unable to ‘come together safely’ in an emotionally connected way to ‘manage and contain distress’ afterwards (p158). ‘Toxic couples’, Motz argues, deny their own dependencies and instead project them onto each other, leading them to view their partners as more out of control than they are. For some men such projection amounted to ‘a fantasized attempt at creating a state of invulnerability and absolute control’ (ibid) when their own lives are in disarray.

Evidence of this kind of ‘splitting’—where good and bad, safe and dangerous, vulnerable and invulnerable, qualities in the self or other are imagined as irreconcilably polarized—upon which such projective processes rely, can also be found in Gilbert and colleagues’ (2001) focus-group study of women enrolled in North American methadone programmes. Participants described how altercations materialized rapidly when high on crack cocaine or when drunk, as intoxication induced paranoid sexual jealousy that led to hostile accusations by men who became like ‘Jekyll and Hyde’. When withdrawing from heroin, some men attacked their partners for failing to provide money for drugs, some women cited ‘irritability’ as explanations for their own use of violence towards their partners when intoxicated or withdrawing, meanwhile others emphasized that drunkenness intensified their male partners’ criticism of them for failing to fulfill household tasks. Some women described engaging in prostitution to raise money for drugs as evidence of their love and care for male partners. When the women subsequently refused to raise funds in this way or sought support from professionals to reduce their own drug use, some male perpetrators threatened further violence whereas others encouraged them to relapse back onto heroin or crack, thus entrapping stigmatized and socially isolated women in relationships with them.

In what follows, we expand the argument for a more relationally sensitive analysis of the dynamics of power that pertain in the lives of couples where domestic abuse towards a partner occurs alongside substance use. Such analyses, we argue, need to be attuned to the gendered power dynamics of drug use and domestic abuse: dynamics that may be reciprocal even while unequal; financial, emotional and pharmacological; involve violence that is perceived as ‘situational’ by one partner and ‘coercively controlling’ by the other; and recalled as involving movements between intimacy and distance among the exchange of insults and assaults, craving for drink and drugs, intoxication and withdrawal. We seek to illustrate these points by drawing on dyad interviews—with male perpetrators in treatment for substance use problems together with their current and former female partners—undertaken for the ADVANCE programme.

The ADVANCE programme seeks to develop and test an integrated intimate partner violence and substance use group intervention that will reduce intimate partner abuse perpetrated by men receiving substance misuse treatment. We report here on the programme’s preparatory workstream. This involved interviewing male domestic abuse perpetrators receiving treatment for substance use and their current or former partners about their relationships and support needs. Adult men were recruited from six community-based substance use treatment services in London and the West Midlands. The treatment services were for people who regarded themselves as ‘substance dependent’, typically because they regarded their drug and alcohol usage as ‘compulsive’, necessary to deal with problems, taking up a lot of time and energy, costing more than they could legitimately afford, and/or very difficult to stop 2 .

Seventy men were screened for lifetime domestic abuse against a partner. Men who currently had court orders preventing contact with their (ex)partners were excluded. Forty-seven of the 70 men screened were eligible, and 37 of these 47 men were then interviewed. Male interviewees were asked to provide contact details of their current or former female partners, and in 14 cases these women were interviewed. All participants were advised that there were limits to the confidentiality that could be afforded where unaddressed risks of harm and safeguarding issues were disclosed. Women and men were always interviewed by different researchers to ensure no information was inadvertently shared between participants. Participants were paid £20 to compensate for their time.

Interviews were undertaken using reflective techniques derived from the Free Association Narrative Interview Method ( Hollway and Jefferson, 2000 ), with participants being supported through active listening to tell the stories of their drug use, relationships, domestic abuse and intervention experiences. Digital recordings of the interviews were transcribed verbatim and transcriptions were checked twice for errors. Timelines were created to track the sequence of events through the life of each participant. Case studies were then written-up as ‘pen portraits’, which sought to capture the complexity revealed in each interview, including apparent contradictions, avoidances and implausible claims. In the 14 cases where both partners were interviewed, men’s and women’s accounts were compared with each other. Although all of the perpetrators interviewed could have been coded as ‘antisocial’ in Holtzworth-Munroe’s (2000) terms, given their drug use and criminal histories, such categorization would oversimplify matters. All but two of the men depicted their violence as situational and/or a product of some form of mutual combat, whereas all but one of their partners depicted coercively controlling abuse, to which around half the women responded with some degree of violent resistance. In terms of their drug use, the 14 men who were interviewed with their partners appeared to be broadly comparable with the other 23 whose partners were not interviewed ( Table 1 ). The majority used heroin with other illicit substances, notably crack cocaine and/or powder cocaine, though some also mixed benzodiazepines with alcohol. Nine out of the 14 were also heavy drinkers. Five of the 14 men also described medical or psychological diagnosis consistent with emotional dysphoria. Eight males disclosed perpetrating violence that was extra-familial in addition to their abuse of partners. Contact with children had, at some point or other, been restricted for all the men in the study.

Self-reported substance use within the sample

Given the high degree of similarity among the men on key variables, we explored if more meaningful distinctions could be drawn by distinguishing the dyads in terms of whether victims had ever used drugs and, if they had, whether they were desisting from substance use or still using. Only four of the women described themselves as substance dependent at the time of the interviews. Five had never been substance dependent, and another five were desisting from substance use, either having become completely abstinent from using or having only had temporary relapses. A three-fold distinction could thus be drawn across the dyads that revealed some important variations in terms of how domestic abuse and substance use manifested themselves.

Group 1. Victim had never been substance dependent ( n = 5)

Within the sample, there were five couples where the female partner had never been substance dependent, though all the women interviewed drank alcohol socially, and one smoked cannabis occasionally. Women in this group had almost no involvement in crime. Four of these women had never been separated from their children, but one woman had children who had been required to live with their grandfather as she would not leave her abusive partner. These non-substance dependent women were typically confused as to why relationships that had started out well had suddenly deteriorated; why their partners engaged in unexplained and peculiar behaviours; and why they had accused them of unfounded infidelities while lying about their own substance use and/or the criminal activity that generally supported it.

Group 2. Victim was desisting from substance use ( n = 5)

Within the sample, there were five couples where the female partner had abstained from using drugs or alcohol, having previously been substance dependent. None of these women had criminal convictions. The stories these desisting women told tended to be of intimacy lost. Sharing feelings and traumas that motivated drug use, and about what made it difficult to give up, had generated understanding and closeness when they had first met their partners. Conflicts had then developed when the men resumed drug use or drinking whereas the women were trying to reduce their own or abstain. Only two of the women in this group had children of their own. In both cases, these women had raised their own children, but with some intermittent professional oversight.

Group 3. Victim was substance dependent ( n = 4)

Within the sample, there were four couples where both the male perpetrator and the female victim were both currently substance dependent. All the women in this group used crack cocaine and heroin to varying degrees. Though they sometimes mentioned love, they often explained their persistence with relationships that had become abusive in terms of daily needs for protection, somewhere to live and the sharing of drugs. The women in this group had much more frequent and entrenched patterns of criminal involvement than the other 10 in the sample. Their criminal involvement activities included shoplifting, petty frauds and prostitution to finance their drug use, typically with encouragement from male partners who relied, to some extent, upon the income the women generated. All four women in this group had been separated from their children when these children were young, though two women had re-established relationships with their children in adulthood.

In what follows, we present one couple from each of these groups to further illustrate the different power dynamics that can pertain in relationships where domestic abuse and substance use co-occur. Italics are used to highlight points where the participants emphasized a relationship between substance use and domestic abuse.

Wayne (early thirties) and Rhian (late twenties) met while she was managing a pub where he drank, sometimes ‘heavily’, during the ‘daytime’. She had never cohabited with a partner before, but he already had a child with another woman and had served at least six prison sentences, two for ‘kidnap’ of his own child. By Rhian’s account, when they first met three years before, the relationship ‘progressed really quickly’: ‘within a couple of weeks’ Wayne was staying in her flat. By Wayne’s account, he and Rhian visited the grave of his grandfather before spending the night together. After that, Wayne said, he ‘couldn’t get rid’ of Rhian: he ‘loved her to bits’ and their relationship was ‘proper good’ for 18 months until he began to ‘blag’ money from her to buy heroin. Rhian’s account, by contrast, was recollected more as an unfolding nightmare, in which she did not know why Wayne was being so controlling until after their baby was born when he revealed he was getting treatment for heroin dependency.

Rhian recalled that Wayne first assaulted her within a couple of months of moving in. After a drink with friends and not knowing that she was already pregnant, Rhian felt ill and went to bed. When Wayne returned home, he became ‘very argumentative’, ‘coming right’ in her ‘face’, accusing her, without foundation, of sleeping with someone else. Rhian wanted to end the relationship then, but Wayne was profusely apologetic, convincing her to keep the baby and get their ‘own place’, explaining his life was ‘empty’ before they met. Wayne provided a detailed account of the emptiness he felt. His mother, who was separated from his father, had worked nights in a pub, leaving her children ‘home alone’ to run ‘wild’. In her absence, Wayne began smoking ‘weed’ regularly. He had ‘weird thoughts’ and would pick fights with anybody , feeling no ‘remorse’ afterwards. Wayne’s mother sought help but did not receive any. Instead, Wayne became abusive to her, ‘calling her a slag’, threatening to hit her when she took his brother’s side, and constantly ‘smashing her house up’. Invited by his cousin to ‘smoke’ heroin to ‘forget’ his grief’ after his grandmother’s funeral, Wayne claimed his clandestine usage escalated from there, Rhian erroneously assuming he was cheating on her, doing nothing to ‘help’ him come to terms with his loss, and causing him to cheat on her. As a ‘druggie’, Wayne said, he became unable to show Rhian ‘affection’ or ‘love anybody’ , including himself.

Wayne’s accusations of infidelity caused Rhian much distress while his behaviour became more erratic and threatening, ‘his jaw… going and his eyes’ being ‘wired’ . He smashed Rhian’s phone because he was ‘convinced’ that he had ‘seen someone’s name’ on the screen. Though their relationship was ‘over’ during most of her pregnancy, Rhian ‘literally couldn’t go anywhere’ without Wayne constantly ‘phoning’ and ‘texting’ her, questioning her about what money she had spent, and sometimes barricading her in the house until she asked his mother to come and get him. After a nurse overheard Wayne discussing drugs on his phone during one of the few antenatal appointments he attended, Rhian took the opportunity to ask him what it was about because she was concerned that social services would see a child protection risk for her baby. Wayne responded by calling Rhian a ‘sick’ ‘liar’ and insisted that it was she, not drugs, that was ‘driving’ him ‘crazy’ .

Wayne apologized after their son was born and claimed that holding the baby inspired him to ‘change’. He and Rhian then took, what she recalled was, a ‘perfect’ family holiday together in which he explained that he had been prescribed Subutex (buprenorphine), a semi-synthetic opioid used to treat heroin dependence . Wanting her son to be raised by two parents, Rhian agreed to let Wayne move back in, but when his drug use resumed, he became ‘physically aggressive again’ . Rhian recounted three occasions when Wayne throttled her, once asking her to put the baby in another room so the child would not see, and on another occasion putting a knife to Rhian’s throat and rationalizing, ‘You’re killing me… So, I should … make it look like you killed yourself’. Sometimes Wayne would speed off, with their baby in the back of the car, in a hurry to buy drugs. Other times, he locked Rhian in the flat for days because he suspected she was ‘cheating’ and feared she would leave him. The violence only ceased, Rhian said, when Wayne called the police on himself after pinning her down and grabbing her by the neck. Rhian said she was pressurized by the police to make a statement against Wayne, but that the case was withdrawn when he made a fraudulent counter-accusation and a friend of his posted content on Rhian’s Facebook page, as if by her, purportedly confessing. Wayne, by contrast, only recalled one assault explaining they ‘didn’t argue a lot’ partly because his ‘mind wasn’t there’ . He admitted driving off with the baby because he was in a ‘rush’ to get drugs but insisted the argument occurred only on his return when Rhian, who thought ‘she was more powerful than everybody else’, punched him ‘in the chest’ to stop him leaving again. In response, Wayne claimed, he had ‘moved’ Rhian by the ‘face’ because she ‘wouldn’t let’ him leave and was ‘kicking’ his ‘legs’ and because he knew he ‘would have ended up battering’ her as he did not always know what he was doing when ‘on heroin’ . Wayne was thus surprised to later be awoken by ‘two police officers’ who arrested him, but relieved when the courts concluded that Rhian had lied, and pleased that, post the break-up, he had been able to access some support for the mental health problems that had been troubling him since his childhood.

Mitchel (early fifties) and June (mid-forties) were in a relationship for over 15 years. They met while in residential rehabilitation for heroin dependence when they both were ‘emotionally raw’. Mitchel felt the ‘deepest love’ for June when they met. June thought she had ‘met her soulmate’: an ‘affectionate’ man with whom she had much ‘empathy’ given his ‘horrendous’ experiences of ‘child abuse’; a man who helped her overcome the death of her son’s (also heroin-using) father. As a teenager, Mitchel too had found ‘comfort’ in heroin use after he was sexually abused by his brother and his brother’s friends while their mother, was out ‘trying to find somebody to love her’ . As a child, June was repeatedly coerced into having sex by a man who threatened to report her to social services for caring for her siblings while her mother received hospital treatment. June said that as a university student, she lacked the social skills to say ‘no’ when she was introduced to heroin. When she became pregnant, she weaned herself off it but relapsed when her mother accused her of inviting the sexual abuse she was subjected to as a child. Having taken heroin to ‘bury’ the ‘hurt’ this accusation inflicted, June self-referred into drug rehabilitation for two years so she could raise her son in an environment in which her desistance from drugs was effectively managed . From Mitchel’s perspective, problems in their relationship emerged after they left the residential rehabilitation. June, he said, was ‘damaged goods’: ‘although the love was there’ she was ‘frigid’. He pursued sex with a woman called Rose and hoped that ‘the three of’ them ‘could love each other’, introducing both women to crack cocaine to facilitate this. But, according to Mitchel, the ‘resentments grew’, until June became pregnant and began ‘hounding’ him to commit to her, even though she knew he ‘loved’ Rose ‘more’, trapping him, paradoxically, in a sexless relationship by becoming pregnant. Owing money to a crack cocaine dealer, Mitchel said, he and June fled to his mother’s house for a ‘fresh start’, during which they could cease using drugs and get their own place.

June, by contrast, made no mention of a polyamorous relationship and said that she had remained ‘clean’ of drugs for a decade after leaving the rehabilitation centre while Mitchel’s drug use resumed . Thereafter, she said, Mitchel would constantly ‘put’ her ‘down and compare’ her to another woman. She said that while the heroin would ‘subdue’ Mitchel, when drunk he became ‘aggressive and arrogant, looking for a problem’ . This abusiveness heightened during her pregnancy; a time when she felt increasingly ‘isolated’ and ‘insecure’. The ‘fresh start’ she had been promised never materialized though this was partly because she started drinking heavily, blurring the line between his ‘put downs’ and her responses to them . Drinking, June said, helped her tolerate Mitchel’s ‘screaming’, but sometimes he was determined to escalate arguments, once pouring a bucket of water over her while in bed. When Mitchell returned from university, where his relationship with Rose had resumed, June said he ‘was drinking pints of vodka’ as well as using heroin while undertaking odd jobs for cash, and that she would come home from work to find him ‘asleep’ in front of ‘a plate full of heroin and needles’ while the children played unsupervised . June said that when she ‘confronted’ Mitchel, he ‘cleared’ out her bank account, leaving her reliant on money borrowed from her mother to provide food for the family. Feeling ‘depressed’, ‘trapped’ and defeated’, June began using heroin again.

Mitchel made no mention of these incidents but said June had become domineering about domestic matters when he returned from university. ‘ Violence’ became their ‘means’ of ‘communication’ at this time with him threatening to hit her ‘back’ when she ‘lashed out’. June explained that she had once hit Mitchel in retaliation, whacking him ‘with a folder’ when he lent her car to an unqualified driver and the police questioned her about it. Mitchel responded, she said, by ‘kicking’ her ‘from the head up’, breaking her jaw, causing her unforgettable pain. June said she lay on top of her son to protect him when Mitchel went ‘ballistic’ because the boy had failed to clear up the kitchen after making his own lunch. June conceded that she ‘hit’ Mitchel ‘right back’. Mitchel said he regretted hitting June ‘like a man’, clarifying that normally he would ‘just’ hit her back with an ‘open hand slap’, but that on this occasion she ‘came at’ him, creating an ‘explosion’ before having a ‘breakdown’, perplexingly ‘terrified’ of him.

The police attended but arrested neither of them as they had both been drinking . So, June said, she tried to leave for a friend’s house with the children and eyes that were too swollen to open, but Mitchel kicked and beat her again. After a period in hospital, June said June contacted a drugs and alcohol dependency team who put her on a methadone programme, but Mitchel started taking the methadone because he feared he would lose the house and his children if June recovered. June’s version was that she only succeeded in leaving Mitchel after she awoke to find him ‘forcing’ tablets down her ‘throat’, to make it look as if she had killed herself by overdose. Mitchel made no mention of this attempted murder but explained how bitter he was that June secured a court order that prohibited him from seeing the children merely because he had made the ‘ mistake’ of buying a very large ‘bag’ of heroin and despite always having done the hoovering and cooking ‘for them’.

Joe (mid-thirties) and Kate (late twenties) had been together for six years. A week after having met in the streets and gone out for a drink , Kate arrived at Joe’s house with just a suitcase and never left. Kate had been sexually assaulted both as a child and as a teenager and was estranged from her family. Joe, whose parents were both deceased, was sexually abused while in care and was estranged from his siblings. Kate’s children lived exclusively with her previous partner, their father, because of Kate’s alcoholism. Joe had been a heavy drinker since his molestation and had served multiple prison sentences: two for attacking men he had seen ‘touch up’ women without their consent and one for assaulting Kate. All but one of Joe’s many previous relationships had involved violence, some grievous and directed at him, but for which he had often been arrested, leading him to the conclusion that ‘it is really sexist out there’: ‘there’s one rule for blokes and one rule for women’.

Despite being ‘frightened of men’, Kate initially found Joe ‘really nice’. She said he ‘spoilt’ her and did ‘sweet’ things, taking her to restaurants and bringing her flowers. They both emphasized that they had loved each other, though Kate said she struggled to ‘handle’ Joe’s attention and was sometimes ‘mouthy’ and ‘hateful’ towards him when drunk, merely to elicit a different ‘reaction’ . From Joe’s perspective, however, ‘every argument’ was ‘about drugs and money’ . He understood that Kate was using drugs —something she barely disclosed in her interview—‘ to block out the pain’ of her past, but the drug use had affected their sex life , while chronic pancreatitis had left her with ‘only… a few years left to live’. Joe did not like Kate ‘clipping’ —‘robbing’ men she deceived into believing they would have sex with her—to fund their drug use and wanted her to steal from supermarkets instead. He said he worried that Kate would be raped or killed by men she had clipped and that he had lost teeth defending her from men she had tricked. Joe admitted being ‘jealous’ and afraid that Kate was ‘cheating on’ on him, though he knew she was not ‘a slag’ despite ‘acting’ like ‘one’. Joe considered himself to be no longer ‘alcohol reliant’, having given up spirits, but claimed that he became ‘addicted’ to heroin a year ago, trying it to show Kate he could ‘understand’ what it was like for her . Heroin withdrawal had been the real ‘devil’ for Joe, leaving him unable to ‘walk’ at times, ‘depressed’ and vulnerable to a descending ‘red mist’ that he claimed rendered his temper uncontrollable . Joe commenced a Subutex prescription during his most recent prison sentence which, since his release, he had shared with Kate to ‘make sure that she ain’t sick’ (i.e., suffering withdrawal symptoms), sometimes also using heroin or crack cocaine in addition to his prescription.

From Kate’s perspective, however, Joe’s protectiveness could be ‘suffocating’. She explained that although Joe initially ‘understood’ how her childhood experiences of the sexual violence affected her, his capacity for understanding was now contingent on whether she had sex with him. He now treated her like a ‘child’ and ‘as his’ property and feared he ‘could kill’ her in an ‘accidental angry’ moment. When coming down from being high or drunk, Joe was often ‘controlling’ and could ‘switch very easily with anyone’. Kate explained that previously, when Joe had been smoking crack, he assaulted a ‘pervert’ who had touched Kate ‘in an inappropriate way’. After he had finished assaulting the ‘pervert’ Joe proceeded to strangle and batter Kate, breaking some of her ribs. Hence, Kate avoided doing anything ‘sudden’ that would make Joe ‘paranoid’, despite having invited him to ‘just fucking kill’ her rather than keep ‘terrifying’ her. After ‘days’ of ‘not sleeping and just drinking’, Joe tried to provoke an argument . When Kate walked away, he mimed ‘putting bullets’ in her head, so she ‘pushed him away’ and he ‘punched’ her. While Joe was in prison for this assault, Kate twice attempted suicide. She continued to blame herself for his violence and drank alcohol ‘to feel happy’ while questioning whether it was ‘really’ her ‘fault’ that Joe was so ‘messed up’, as he has claimed. Joe, by contrast, claimed Kate had hit him ‘over the head with a hammer’ because he ‘wouldn’t buy her drugs’ and explained that the assault on her, for which he went to prison, occurred after she ‘slapped’ him ‘round the head’ because he did not ‘have… money for drugs’. It was unfortunate, he said, that the police drove past just as he was hitting ‘her back’ in ‘self-defence’. Though Kate said she ‘loves’ Joe ‘to death’ she doubted whether the ‘damage’ to their relationship could be ‘mended’. He , by contrast, was desperate ‘to get her clean’, as he imagined this would enable him to get his own ‘life back’. Joe assumed that if Kate became sober enough to see her children again, it would save his relationship with her from ‘ruin’.

In this article, we have presented three relationship scenarios where domestic abuse pertained alongside drug or alcohol dependency. These relationships diverged primarily in terms of the female partners’ histories of drug and alcohol consumption as all men were in treatment for substance dependence. All three men—like the majority of those interviewed in the ADVANCE project—considered ‘drugs’, their own and/or their partner’s use of them to have damaged or ruined their relationships. Their depictions of violence as ‘isolated incidents’ in which they were only partially culpable were consistent with perpetrators’ accounts more generally ( Stark, 2007 ; Women’s Aid, 2018 ; Gilchrist et al., 2019 ). Wayne, Mitchel and Joe all described discrete, regrettable and unplanned assaults that derived from everyday conflicts over alcohol and drug use, financial pressures, sexual jealousies and domestic chores: conflicts that were sometimes accentuated by being intoxicated. Nevertheless, the stories these men told suggested that their need to control became increasingly acute when their relationships were in crisis, when they had secrets to keep, when they felt dependent on drugs or alcohol, were afraid of losing their minds, their partners and their children, when money was scarce, and when homelessness and criminalization were distinct possibilities. As these men projected this sense of being in disarray onto their partners, the women began to feel like they were being driven crazy, in part because they did not have full knowledge of the drug and alcohol use that was consuming the men’s time and minds. As the women began to question what was happening, the men’s attempts to coercively control became more dangerous and desperate, e.g., in the refusal to let partners leave their homes or in their efforts to tempt or coerce the women into consuming drugs. Despite their unhappiness, these men, like their partners, often lacked the emotional strength and economic resources required to separate ( Walby and Towers, 2018 ). Instead, the men often blamed discrete incidents of violence, as they construed them, on drugs and/or money-related issues that could be fixed if they entered treatment and their partners were prepared to fight for the relationship, for the sake of children whose well-being had not been paramount (to the men) previously.

By contrast, Rhian, June and Kate, described steadily accumulating patterns of abuse, forgiven initially as promises of fresh starts, either in new places or after drug treatment, were made. The women’s reasons for enduring domestic abuse or for giving the men another chance began with this hope for change but often mutated as they encountered the financial and emotional difficulties of leaving homes, the prospect of losing their children (forever in Kate’s case) and the concomitant risk of criminalization when the men threatened to report them for hitting back or for using drugs. Hence, the reasons these women stayed were complexly configured around drug and alcohol use. Wayne’s abusive behaviour had proved confusing to Rhian, who knew only that he was a heavy drinker until his heroin use was confirmed after their baby was born. Then, as someone with little experience of either drugs or relationships, Rhian was persuaded to give Wayne another chance while he sought drug treatment, assuming mistakenly that this would redress his violence. June, by contrast, had some empathy with Mitchel, having relapsed with heroin herself and recognizing that her own drinking contributed to their arguments. June had been persuaded that moving might facilitate a fresh start, without drug use. However, when June sought opioid substitution treatment for herself, Mitchel found a new way of controlling her, diminishing her capacity to leave by controlling her access to her prescription and then trying to administer an overdose. The challenges for Kate were different again. She had a long history of heavy alcohol consumption and illicit drug use, the latter of which Joe had joined in with, compounding their mutual dependence on shoplifting and pseudo-sex work to maintain their supplies. Joe construed his heroin use as an attempt to empathize with Kate, though it appeared that he persisted with drug treatment partly because it legitimized his management of her drug use. Joe hoped he would get his ‘life back’ if he could facilitate a reconciliation between Kate and her children. In the interim, Kate suffered grievous violence, while living in Joe’s home: violence that was construed as part of the protection he afforded her against men she had clipped.

For the women in these relationships, criminal justice intervention was often greeted with trepidation, for it rarely provided the protection it promised. Instead, they had often concluded that it was simpler to suffer difficulties within their relationships, attribute violence to drugs use and attribute drug use to earlier traumas, of which there were many in our participants’ lives. For June and Kate, the pains of child abuse, mental health problems and bereavement were partly responsible for the solace they had sought in alcohol and heroin consumption, as well as in their relationships with men. However, as their drug and alcohol usage became complicated by domestic abuse, a range of different strategies were pursued by each couple, typically to avoid attracting the attention of social services or the police. These strategies included taking prescribed medications to minimize their need to commit crime to fund illicit drug use (Joe), moving away while also severing ties with friends and family (Mitchel, June), switching substances (Mitchel, Joe), pursuing relationships with others who use illicit drugs to avoid feeling ‘trapped’ (Mitchel, Kate), consuming drugs or alcohol to cope with the aftermath of conflict (Wayne, Mitchel and June), engaging in crime together (Joe, Kate) and tacitly encouraging partners to participate in drug use (Mitchel, Joe), compounding the risks faced by women who wished to abstain or keep their use moderate. Although drug and alcohol use could increase sociability and enhance feelings of closeness between partners, the fear of dependency also induced feelings of worthlessness—evidenced most vociferously in Wayne’s belief that he could not love anyone and the paranoid accusations this engendered, but also hinted at in Joe’s jealousy and Mitchel’s infidelity.

These cases reveal how the projective dynamics that impart blame, often through men’s claims that their female partners are ‘driving’ them ‘mad’, are easily facilitated by the nuances of sexism and reinforced by the perennial threat of violence. These dynamics were compounded as drinking and drug use generated financial pressures, which intensified conflicts that left the women, as well as some of the men, feeling that their partners regarded sustaining their substance use as more important than their relationship, avoiding criminalization and social services intervention, and the threats posed by those from whom money and drugs had been borrowed or defrauded.

For time-pressured police officers, social workers and magistrates faced with partial evidence and counterclaims, discerning the ‘truth’ of who had done what to whom in which circumstances would have been particularly difficult. Evidently, some abusive men tell highly convoluted stories to exonerate themselves. But some women who are the primary victims in such relationships do not and cannot always tell the whole truth either, not only because they fear further violence and abuse but also because of the stigma of their own drinking and drug use, the fear of child protection proceedings being instigated and the risk of being incriminated by perpetrators they have hit in self-defence or retaliated against ( Wolf et al., 2003 ; Felson and Paul-Phillipe, 2005 ). What is under-acknowledged in many serious cases of domestic abuse is that both perpetrators and victims often share in the shame associated with being abused as adults and children, of failing to protect their own children, anticipate their partner’s needs, having hit back, gotten drunk or engaged in illicit drug use.

Like many of the men in the ADVANCE programme study, the perpetrators we have depicted here dealt with feelings of trauma and grief from their pasts through drug use and by scaring their partners in ways that the women experienced as acutely controlling. While frequently terrifying, such behaviour was not only instrumental and controlling but also expressive of how painful some aspects of their pasts were and how unwilling they were to concede their dependency on both substances and partners who provided care, funds, a place to live and the support needed to maintain precarious relationships with children. Similar experiences of child abuse, mental health problems and drug dependency were sometimes part of the story of intimacy that held these couples together despite grievous domestic abuse. Then, when the risk of criminalization or estrangement presented, men who were coercively controlling sometimes used such prehistories against their partners by threatening to expose them for raising children in contexts that were unsafe. Hence, the ‘madness’ that the women in these relationships often felt was not simply symptomatic of their own mental health problems but projected onto them by men who had become desperate to impose their own versions of reality.

This imposition of the perpetrator’s reality sometimes became more forceful when the criminal justice system intervened. The risk of ‘legal systems abuse’ occurs when perpetrators adept at coercive control harness the powers of the police or the courts to further intimidate their partners ( Douglas, 2018 ). It has, to some extent, been be amplified by the advent of gender-neutral policy, which recognizes that men can be victims too, alongside incident-focussed approaches to policing that direct attention to what has just happened—such as a man being hit—rather than the history of the relationship—such as a woman being terrified or controlled by the same man over a prolonged period ( Walklate et al., 2018 ). The 2019 Domestic Abuse Bill attempts to counter this risk by prohibiting perpetrators from cross-examining victims in the family courts and providing greater recognition of the impact of the ways in which economic abuse makes it harder for many victims to leave. But compelling alcohol and drug-using perpetrators to receive treatment may introduce unforeseen possibilities for coercive use of the law. Some women will consider themselves too culpable to seek support and will ultimately be let down within a criminal justice process calibrated to identify the perpetrator of assaults at the scene and/or whether they were intoxicated, and hence be easily blindsided by the mutualizing discourses some serial offenders offer in their defence ( Tolmie, 2018 ). Others will stay under the misapprehension that the domestic abuse will cease once treatment for substance use begins. This is an unlikely outcome, though intervention is nonetheless worthwhile. There is tentative evidence to suggest that reducing drinking among perpetrators can diminish resort to violence ( Wilson et al., 2014 ) and that opiate substitution treatment can help alleviate dependence on illicitly purchased drugs and acquisitive crime and improve mental, physical and sexual health among heroin-dependent polydrug users ( Gossop et al., 2000 ; Strang et al., 2010 ; MacArthur et al., 2014 ). But, although treatment interventions can reduce the harms of substance use, where drug and alcohol use and domestic abuse co-occur, treatment needs to be part of a range of measures that include support in changes in thinking and modes of relating, securing the housing and economic resources couples need to be able to contemplate living apart, the support and empowerment of survivors, the safeguarding of children and professional help with mental health problems. These skilled forms of intervention are critical to deescalating the dynamics that sustain substance use in the lives of people enduring the worst forms of domestic abuse but are often in short supply.

By contrast, the evidence that domestic abuse perpetrator programmes—as currently commissioned by the UK government—‘work’ remains mixed ( Vigurs et al., 2017 ). Although the best interventions risk encouraging men who have been physically violent to adopt more emotionally abusive tactics ( Kelly and Westmarland, 2016 ), the UK’s Probation Inspectorate is doubtful as to whether the private Community Rehabilitation Companies currently delivering such interventions provide adequate practice in terms of safeguarding victims and their children ( House of Commons, 2018 ). Both the domestic abuse and substance use treatment sectors in the United Kingdom have suffered sustained funding cuts over the last 10 years ( Women’s Aid, 2016 ; ACMD, 2017 ), often secured through the non-renewal of local procurement contracts via competitive tendering processes that favour cheaper and less specialist provision. One danger with compelling drug or alcohol treatment is that it will place clinicians and health practitioners in the ethically compromising position of having to report those who relapse, together with those whose prescriptions have proved insufficient, or who have decided that they would be better trying to reduce their substance use gradually, to the courts where they may face further criminalization ( Seddon, 2007 ; Werb et al., 2016 ).

More generally, models of treatment for alcohol and drug use that acknowledge that ‘relapse’ is common are hard to reconcile with domestic abuse policy founded on compliance with court orders that insist upon ‘zero tolerance’ of reoffending ( Benitez et al., 2010 ). Criminalizing responses are rarely challenged in domestic abuse policy, where academic research has tended to extol the benefits of naming ‘perpetrators’ as such and victims, though sometimes recognized as ‘survivors’, are usually cast as their opposites. Such an approach runs contrary to academic conventions in substance use research where a concerted effort has been used to avoid stigmatizing terminology that reduces individuals’ identities to their drug consumption ( Broyles et al., 2014 ).

Hence, acknowledgement of complexities in the power dynamics of domestic abuse that co-occurs with drug, alcohol and mental health problems raises acute challenges, not only for the delivery of policy that attempts to reconcile safety, justice and rehabilitation but also for academics who have framed the problem of domestic abuse primarily as one of either gender or psychology. Not only do criminologists need to reconceptualize domestic abuse more dynamically but they must also ask why some men choose to secure control in coercive ways when so many other aspects of their lives appear out of control. There is a need to recognize how the interdependencies—including the prospect of economic abuse—involved in intimate relationships are intensified by poverty, stigma, co-dependency, child abuse and neglect, poor mental health and the fear of police and social services intervention. In theory and in practice, we must ensure that shorthand explanations derivative of personality disorders do not obscure what can be learnt from the more complex descriptions both survivors and perpetrators can offer of their relationships. Policymakers need also to ensure that evaluations of treatment options for substance-using perpetrators extend beyond the longstanding fixation with acquisitive crime to include measures that take stock of their impact on children and partners, whether current and former, and to recognize that establishing effective practice will require the reestablishment of expertize and service provision that is increasingly scarce.

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• Published: 26 August 2024

Parental domestic violence and abuse, mental ill-health, and substance misuse and the impact on child mental health: a secondary data analysis using the UK Millennium Cohort Study

• Kate Allen   ORCID: orcid.org/0000-0002-0870-7209 1 ,
• G. J. Melendez-Torres   ORCID: orcid.org/0000-0002-9823-4790 1 ,
• Tamsin Ford   ORCID: orcid.org/0000-0001-5295-4904 2 ,
• Chris Bonell   ORCID: orcid.org/0000-0002-6253-6498 3 &
• Vashti Berry   ORCID: orcid.org/0000-0001-6438-3731 1  

BMC Public Health volume  24 , Article number:  2310 ( 2024 ) Cite this article

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Metrics details

Parental domestic violence and abuse (DVA), mental ill-health (MH), and substance misuse (SU) can have a negative impact on both parents and children. However, it remains unclear if and how parental DVA, MH, and SU cluster and the impacts this clustering might have. We examined how parental DVA, MH, and SU cluster during early childhood, the demographic/contextual profiles of these clusters, and how these clusters relate to child MH trajectories.

We examined data from 15,377 families in the UK Millennium Cohort Study. We used: (1) latent class analysis to create groups differentially exposed to parental DVA, MH, and SU at age three; (2) latent growth curve modelling to create latent trajectories of child MH from ages 3–17; and (3) a case-weight approach to relate latent classes to child MH trajectories.

We identified three latent classes: high-frequency alcohol use (11.9%), elevated adversity (3.5%), and low-level adversity (84.6%). Children in the elevated adversity class had higher probabilities of being from low-socioeconomic backgrounds and having White, younger parents. Children exposed to elevated adversity displayed worse MH at age three (intercept = 2.274; p  < 0.001) compared the low-level adversity (intercept = 2.228; p  < 0.001) and high-frequency alcohol use class (intercept = 2.068; p  < 0.001). However, latent growth factors (linear and quadratic terms) of child MH did not differ by latent class.

Conclusions

Parental DVA, MH, and SU cluster during early childhood and this has a negative impact on children’s MH at age three, leading to similar levels of poor MH across time. Intervening early to prevent the initial deterioration, using a syndemic-approach is essential.

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Parental domestic violence and abuse (DVA), mental ill-health (MH), and substance misuse (SU; including alcohol and drug use) are prevalent public health problems both in the UK [ 1 , 2 , 3 ] and worldwide [ 4 , 5 , 6 , 7 ] and are considered to be three of several adverse childhood experiences (ACEs). When considered in combination, an estimated 3.6% of UK children are living in households where all three of parental DVA, MH, and SU are present [ 8 ]. This is a conservative estimate, with epidemiological studies, qualitative accounts, and referrals to specialist helplines indicating that each of these three ACEs have been exacerbated by COVID-19 government-related restrictions [ 9 ]. Unsurprisingly, parental DVA, MH, and SU can have a negative impact on parenting capacity, child internalising and externalising behaviour, and a range of child health outcomes across the life course [ 10 ], with each of parental DVA, MH, and SU being associated with increased risk of child maltreatment [ 11 , 12 ]. Furthermore, evidence suggests these ACEs tend to be intergenerational, with those who experience parental DVA, MH, and SU during childhood being at increased risk of developing problems with violence, MH, and SU themselves, later on in life [ 13 ].

Families experiencing these three ACEs are likely to be at increased risk of harm, with evidence suggesting that each of these public health problems are likely to modify the risk of the other occurring [ 14 , 15 , 16 ]. Consequently, improving the ways in which we prevent and respond to parental DVA, MH, and SU is a policy and practice priority within the UK [ 17 , 18 , 19 ]. Although families may experience these issues in combination, commissioning and service provision for DVA, MH, and SU have remained historically siloed, resulting in difficulties providing integrated support [ 20 ]. Moreover, we lack effective evidence-based interventions for these difficulties in combination [ 21 ]. Developing an effective response requires an understanding of how these ACEs cluster, the demographic/contextual profiles of these clusters, and whether clustering impacts child outcomes.

Few studies have considered this, with research to date focusing on each of these ACEs in isolation or cumulatively alongside other ACEs which ignores potential synergistic relationships and effects interventions may need to target [ 22 , 23 ]. Where recent studies have considered how ACEs cluster, findings remained limited or mixed. For example, when considering a whole range of ACEs (e.g., child maltreatment, parental DVA, parental MH, parental SU, parental separation/divorce, parental convictions, death of close family members etc.) there is mixed evidence to suggest parental DVA, MH, and SU form a prominent cluster (e.g. [ 24 , 25 , 26 ], When focusing on parental DVA, MH, and SU specifically, a recent systematic review identified only three studies [ 27 , 28 , 29 ] that had explored the relationship between these three ACEs and the impact they might have on child abuse and behavioural outcomes [ 30 ]. This research has also tended to focus on high-risk samples, retrospective reports, or maternal experiences of DVA, MH, and SU rather than experiences within the whole family context. Taking a family systems perspective, these ACEs are likely to impact children regardless of who is experiencing them.

To address this gap, Adjei et al. [ 31 ] considered how parental DVA, MH, alcohol use, and poverty cluster across 9-months to 14-years of age and how these clustered-trajectories might relate to child outcomes at age 14. Using prospective data from the UK Millennium Cohort Study (MCS), they identified six clustered-trajectories including: (1) “no adversities” , (2) “persistent poverty” , (3) “persistent MH” , (4) “persistent alcohol use” , (5) “persistent DVA” , (6) “persistent poverty and MH” . Group membership in the “persistent poverty and MH” trajectory was related to the most negative socioemotional, cognitive disability, drug experimentation, and obesity outcomes at age 14, suggesting important targets for future intervention. Although providing a valuable insight into how ACE trajectories co-occur, it tells us little about how adversity clusters during potentially sensitive time-periods in a child’s development. While the evidence base is still developing, there is some evidence to suggest that experiencing ACEs during early childhood (as opposed to late childhood or adolescence) is more likely to have negative impacts on a child across their life course when considering specific outcomes [ 32 , 33 ]. Furthermore, policy and practice often prioritise this period of child development as a crucial time for prevention and early intervention [ 34 ]. Exploring how parental DVA, MH, and SU cluster during such time points will help further advance our understanding of ACE clusters whilst informing our timing of intervention efforts [ 32 ]. To our knowledge, no studies have yet considered this.

Drawing on our recent systematic review [ 21 ] and literature from the individual fields of DVA, MH, and SU [ 35 , 36 , 37 , 38 , 39 ], important demographic and contextual characteristics that are likely to relate to the co-occurrence of parental DVA, MH, and SU include socio-demographic characteristics such as parental age, ethnicity, education/qualifications, household income, number of children, and housing tenure. However, our understanding of how these characteristics might relate to specific patterning of parental DVA, MH, and SU remains limited. Exploring the demographic and contextual profiles of families experiencing specific clusters of parental DVA, MH, and SU during early childhood is essential to help inform the development of preventive interventions (both in terms of who preventive interventions for clustered parental DVA, MH, and SU might seek to target and how preventive interventions might need to be tailored), as well as inform policymakers. Furthermore, it could help elucidate avenues for future research, helping us to develop a more nuanced understanding of the co-occurrence of parental DVA, MH, and SU.

We examined how parental DVA, MH, and SU cluster during early childhood, the demographic/contextual profiles of these clusters, and how these clusters might relate to child trajectories of MH over time. We focus on trajectories of child MH because child MH problems can lead to a range of negative outcomes later on in life including poor academic attainment, interpersonal difficulties, substance use, and physical health problems [ 40 ] and therefore, intervening early is essential. Overall, our work seeks to clarify who an intervention for parental DVA, MH, and SU should target, as well as whether clustered risk impacts children’s MH trajectories.

Study design

We conducted a latent variable mixture modelling analysis using data from the MCS; a freely accessible cohort study of ~ 19,000 UK children born between September 2000–January 2002 [ 41 ]. MCS cohort children were identified for recruitment via UK government child benefit records and eligible if they were living in the UK at 9-months of age. Oversampling of hard-to-reach groups resulted in a nationally representative sample [ 41 ]. MCS collected data on cohort children, and their families, in seven sweeps including when the child was; (1) 9-months-old; (2) 3-years-old; (3) 5-years-old; (4) 7-years-old; (5) 11-years-old; (6) 14-years-old; and (7) 17-years-old. Our study utilises exposure variables collected from main respondents (most often mothers/mother figures) and resident partner respondents (most often fathers/father figures) at age three and child outcome variables at ages 3–17. Most data were collected during home visits via face-to-face interview or self-completion [ 42 , 43 , 44 ]. Child outcome data at age 17 were also collected outside of home visits via self-completion [ 42 ]. We excluded multiple births from our study due to lack of independence. This left 15,377 cohort children and families who had provided at least some data at age three.

Our study was granted ethical approval from the University of Exeter College of Medicine and Health Ethics Committee (number: 489638). The protocol can be found on the Open Science Framework ( https://osf.io/c6tbh/ ).

Exposure: latent clusters of parental DVA, MH, alcohol use, and drug use

Latent clusters were created using binary manifest indicators representing the presence/absence of parental DVA, MH, alcohol use, and drug use at age three, derived using data from main and partner respondents (see Table  1 for overview and Supplementary Appendix S1 , Additional file 1 for rationale). This was the earliest that data were available from main and partner respondents on all variables of interest.

Outcome: latent trajectories of child MH

Our outcome variables were latent intercept and growth factors of parent-reported SDQ total difficulties (SDQ-TD) scores (Supplementary Appendix S1 , Additional file 1) measured at ages 3–17. The SDQ is a 25-item measure of child behaviour which includes five subscales addressing emotional symptoms, conduct problems, hyperactivity/inattention, peer relationship problems and prosocial behaviour. Respondents respond to 25-items on a three-point Likert scale (‘not true’, ‘somewhat true’, or ‘certainly true’). Scores from the first four subscales are summed to create a ‘total difficulties’ score ranging from 0–40, with higher scores indicating greater difficulties [ 45 ]. The SDQ was completed by the main respondent from ages 3–14, and main or partner respondents at age 17 [ 42 , 43 , 44 ].

Demographic and contextual variables

Demographic and contextual variables included: child sex measured at age 9-months, and number of children in the household, main and partner respondent age at birth of cohort child, ethnicity, and highest qualification, family income (banded), OECD poverty level, and housing tenure measured at age three. Where the latter were unavailable at age three, data were fed forward from age 9-months.

Statistical analysis

All descriptive analyses, data transformations, and multiple imputations were conducted in STATA. Main analyses were conducted in Mplus Version 8.7 [ 46 ] (see https://osf.io/c6tbh/ for our main analyses Mplus code) and pooled pairwise chi-squared tests were conducted in R using the ‘micombine.chisquared’ function (see https://www.rdocumentation.org/packages/miceadds/versions/3.17-44/topics/micombine.chisquare ).

Multiple imputation

We multiply imputed missing exposure and outcome variables using fully conditional specifications, with canonical regressions for exposures and predictive mean matching for outcomes given the left-leaning skew of SDQ-TD distributions [ 47 ]. We assumed data were missing at random and used multiple imputation by chained equations (MICE) to impute 35 datasets based on the highest fraction of missing information. All variables used within the analysis, as well as interactions between household-level DVA, MH, alcohol use, and drug use (including DVA*MH, DVA*alcohol use, DVA*drug use, MH*alcohol use, MH*drug use, and alcohol use*drug use), were included in the imputation. Interactions between household-level DVA, MH, alcohol use and drug use were included using the ‘just another variable’ approach [ 45 ]. This step was essential to ensure that the imputation model was congruent with the analysis method (i.e., LCA; [ 45 ]).

Complete case exposure data and multiply imputed data produced similar results and, therefore, the latter are reported from this point onwards (see Supplementary Appendix S2 Tables S2.1 – S2.4 and S3 Tables S3.1 – S3.5 , Additional file 1 for missing data patterns and complete case exposure data analyses).

Main analyses

First, we created our exposure variable by estimating latent class models using manifest indicators of parental DVA (0 = no, 1 = yes), MH (0 = no, 1 = yes), alcohol use (0 = no, 1 = yes), and drug use (0 = no, 1 = yes) derived using data from age three. We estimated two-, three-, and four-class models. Several criteria were used to assess model fit including scaled relative entropy (0–1, higher entropy scores indicating greater classification certainty), Bayesian Information Criterion (BIC), Akaike Information Criterion (AIC) (lower BIC/AIC scores indicating better fit between the model and observed data), homogeneity in item-response probabilities (indicating the degree of latent class separation), VLMR LRT p -value (indicating whether the k model is a better fit to the k-1 model), and interpretability [ 48 , 49 ]. We re-ran the most appropriate model using the bootstrap likelihood-ratio test (BLRT) to confirm the optimal number of classes [ 49 ]. We labelled the resultant latent classes through discussion, taking into account both item-response probabilities and interpretability/theoretical sense-making.

Second, we examined class-specific demographic/contextual profiles using the three-step approach. This involves: (1) estimating the LCA model; (2) retaining information about most likely latent class membership and latent class posterior distributions; and (3) using this information about membership uncertainty to regress latent classes onto demographic/contextual variables in a multinominal regression framework [ 50 ]. The three-step procedure in Mplus provides probabilities of demographic/contextual characteristics conditional on membership in a particular latent class [ 50 ]. We also report results from pooled pairwise chi-squared tests to indicate whether there are statistically significant differences in the covariate distributions between each latent class.

Third, we fitted a latent growth curve model (LGM) to SDQ-TD scores measured at ages 3–17. Measurement at age three was set as the intercept. We log-transformed the SDQ-TD scores prior to analysis due to a left-leaning skew in the data. We examined intercept-only, linear, and quadratic forms of the LGM and judged model fit using chi-squared (scores > 0.05 indicating good model fit), RSMEA (scores < 0.05 indicating good model fit), CFI and TFLI (scores > 0.95 indicating good model fit), and BIC and AIC scores.

Finally, we related the LCA-derived latent classes to the intercepts, linear, and quadratic terms of the LGM previously estimated. We did this using the case-weight approach whereby: (1) the LCA is estimated; (2) estimated posterior class probabilities are saved as weight variables; and (3) the LGM is estimated for each latent class using case-weight information retained from step two [ 51 ]. Latent-class-specific LGM parameters were compared with the original LGM estimated in step four and with one another using Wald chi-squared tests.

Supplementary Appendix S1 , Additional file 1 provides a graphical representation of the main analyses.

Figure  1 illustrates the flow of participants through the study. At child age three, 9.8% ( n  = 1,507) of families reported parental DVA, 4.3% ( n  = 661) reported poor parental MH, 12.8% ( n  = 1,968) reported parental alcohol use, and 9.7% ( n  = 1,492) reported parental drug use (Table  2 ). Mean SDQ-TD scores across sweeps ranged from 7.5 (SE = 0.04) to 9.8 (SE = 0.04).

Participant flow through study

Latent class analysis

We estimated two, three, and four-class latent class models using complete case exposure data (Supplementary Appendix S3 , Additional file 1). The three-class model provided the best fit in terms of entropy (0.74), AIC, and c-BIC, as well as demonstrating clearer class separation and theoretical sense in classes as compared to the two- and four-class models (Table  3 ). The three-class solution also displayed a significant VLMR p -value. Both the two-class and four-class solutions displayed low levels of entropy (0.57 and 0.37, respectively), and the four-class solution also suffered from low classification accuracy and unclear class separation, complicating interpretation. Although the two-class model displayed a lower BIC score than the three-class solution, the difference between the two was minimal (< 9.0) (Table  3 ).

Given the judged fit of the three-class model, we ran a BLRT to confirm the model fit, which was significant ( p  < 0.001), so the three-class model was selected and re-run using the imputed data (see Table  3 , ‘final model’). Based on the item-response probabilities for DVA, MH, alcohol use, and drug use in each latent class within the imputed data (Table  4 ), we labelled the latent classes as follows:

Class 1: High-frequency alcohol use

This class comprised 11.9% of families, who reported drinking alcohol 5–6 times per week or everyday (100%). Families in this class were unlikely to be experiencing DVA (8.6%), MH (0.7%), or drug use (11.5%).

Class 2: Elevated adversity

This class was the smallest class (3.5%). Families were more likely to be experiencing DVA (47.2%), MH (16.5%), or drug use (43.8%) as compared to the other two classes. They were also more likely to be experiencing high-frequency alcohol use (21.5%) as compared to the low-level adversity class.

Class 3: Low-level adversity

This class was the largest class (84.6%). Families in this class displayed low levels of DVA (5.6%), MH (3.3%), alcohol use (2.5%), and drug use (5.5%).

Demographic/contextual profiles of latent classes

Latent-class-specific demographic/contextual profiles are presented in Table  5 , along with details of the pooled chi-squared tests between each latent class for the multiply imputed data.

Child sex did not significantly differ by latent class.

Number of children in household

The high-frequency alcohol use class displayed significantly higher probabilities of having two children in the household and lower probabilities of having one, four, or five or more, as compared to the other two classes.

Main and partner respondent age at birth

Main and partner respondents in the elevated adversity class had higher probabilities of being younger, whereas those in the high-frequency alcohol use class had higher probabilities of being older. Most main and partner respondents in the low-level adversity class were aged between 26 and 35 years.

Main and partner respondent ethnicity

Main respondents in the elevated adversity class had higher probabilities of being White and lower probabilities of being in an Ethnic Minority group as compared to the low-level adversity class. When compared to the high-frequency alcohol use class, main respondents in the elevated adversity class had lower probabilities of being White and higher probabilities of being in an Ethnic Minority group. For partner respondents, there were higher probabilities of being White in the high-frequency alcohol use class as compared to the low-level adversity and elevated adversity class. Consequently, there were higher probabilities of partner respondents being in an Ethnic Minority group in the low-level adversity class as compared to the multiple-adversity and high-frequency alcohol use class.

Main and partner respondent qualifications

Main and partner respondents in the high-frequency alcohol use class had higher probabilities of continuing their education beyond secondary school (i.e., beyond age 16) compared to those in the elevated adversity class who had higher probabilities of having no qualifications or GCSEs only. Main and partner respondents in the low-level adversity class were more mixed. There were no significant differences between main respondent qualifications in the elevated adversity class as compared to the low-level adversity class.

Joint annual income

Respondents in the elevated adversity class had higher probabilities of having a lower joint annual income as compared to the high-frequency alcohol use class and the low-level adversity class.

Almost all respondents in the high-frequency alcohol use class were above the poverty line whereas almost half of respondents in the elevated adversity class were below the poverty line. For the low-level adversity class, families had higher probabilities of being above the poverty line.

Housing tenure

Most respondents in the high-frequency alcohol use class owned their own house as did most respondents in the low-level adversity class, although to a lesser extent. The elevated adversity class displayed higher probabilities of renting from the local authority or a housing association and renting privately as compared to the other two classes.

Relation to child mental health

Table  2 shows the estimated mean SDQ-TD scores at each timepoint. For the overall, unconditional model, the quadratic terms provided the best model fit (RMSEA = 0.116, CFI = 0.910, χ2 (df12) = 2492.3, p  < 0.001; Table  6 ). The mean intercept for the log-transformed SDQ-TD score was 2.163 ( p  < 0.001), the mean linear slope was −0.057 ( p  < 0.001), and the mean quadratic slope was 0.003 ( p  < 0.001). Children’s MH gradually improved from 3 to 11 years at which point MH began to gradually deteriorate from 11 to 17 years. There was significant variability in the intercept, linear slope, and quadratic slope indicating children’s MH differed in terms of the intercept and change across time.

Given known gender differences in MH, we added child sex as a time-invariant covariate in a conditional model of child MH trajectories. This conditional model appeared to provide a marginally better fit as compared to the unconditional model (RMSEA = 0.105, CFI = 0.913, χ2 (df15) = 2545.436, p  < 0.001; Table  6 ), although the fit indices were still not optimal. There was a significant effect of child sex on the mean intercept, linear slope, and quadratic slope. Figure  2 displays the growth trajectories for boys and girls, separately, along with the marginal mean predictions for boys and girls at specific sensitive ages (min, median, max). Girls were more likely to have a better mean intercept SDQ-TD score than boys (estimate = -0.114; p  < 0.001). Boys’ MH gradually improved from 3 to 14 years after which they plateaued, with a slight increase at 17 years (linear slope estimate = -0.047, p  < 0.001; quadratic slope estimate = 0.002, p  < 0.001). Girls’ MH was marked by a steeper improvement in scores from 3 to 11 years, at which point MH gradually began to deteriorate (linear slope estimate = -0.021; p  < 0.001; quadratic slope estimate = 0.002; p  < 0.001).

Growth curves for boys and girls (multiply imputed data)

Finally, we examined latent-class-specific child MH trajectories controlling for child sex (Table  6 ; Fig.  3 ). Latent-class-specific trajectories followed a similar growth pattern (as indicated by similar linear and quadratic slope estimates for each latent class). However, the intercepts significantly differed between latent classes (Table  6 ; Supplementary Appendix S4 , Additional file 1). Children in the elevated adversity class displayed the highest SDQ-TD scores at age three (intercept = 2.274; p  < 0.001), followed by the low-level adversity (intercept = 2.228; p  < 0.001), and high-frequency alcohol class (intercept = 2.068; p  < 0.001). All three latent-class-specific trajectories demonstrated significant variability in intercepts, linear slopes, and quadratic slopes, indicating children’s MH within each latent class differed in terms of the intercept and change across time.

Latent-class-specific growth curves for boys and girls (multiply imputed data)

We examined how parental DVA, MH, alcohol use, and drug use cluster during early childhood in the MCS, the demographic/contextual profiles of these clusters, and how these clusters relate to children’s MH trajectories. We identified three latent clusters: high-frequency alcohol use , elevated adversity , and low-level adversity . These clusters were related to distinct demographic/contextual profiles and child MH profiles.

At child age three, 3.5% of families were experiencing elevated adversity which concurs with studies estimating the prevalence of parental DVA, MH, and SU in the UK and extends previous individual/cumulative ACE work [ 8 ]. Our elevated adversity cluster was similar to that identified in a sample of families referred to statutory Children’s Social Care in England and general population studies where lifetime DVA, MH, and SU cluster alongside other ACEs [ 26 , 28 ]. However, it is one of few to find parental DVA, MH, and SU cluster as a triad alone. This may be due to differences in the time point examined, our consideration of both main and partner responses, or our inclusion of parental drug use which features clearly in our elevated adversity class but has been excluded from other studies [ 31 ]. The item-response probabilities of parental MH in this cluster were notably low, which is interesting given the established bi-directional relationship between MH and DVA/SU and predominance of MH as an ACE in other studies [ 16 , 26 , 31 , 52 ]. We used a cut-off point for poor MH to reflect clinical caseness which may explain this finding. Equally, general population studies may not be capturing data from families experiencing the greatest challenges.

Families in the elevated adversity class tended to be White (although to a lesser extent than the high frequency alcohol use class), younger parents from low-socioeconomic backgrounds, highlighting key potential demographic/contextual targets for future intervention. We did not include poverty in our ACE cluster given that prevention and early intervention in relation to poverty and DVA, MH, and SU have different policy and practice implications. Poverty is often considered a social policy issue while DVA, MH, and SU are considered health and social care practice concerns. However, our study emphasises that poverty cannot be ignored when considering clustered parental DVA, MH, and SU; almost half of families experiencing this cluster fell below the poverty line. While being mindful not to conflate the two [ 53 ], there is a clear link between poverty and individual/cumulative ACEs as well as clustered adversity [ 26 , 54 ]. Thus, interventions aiming to prevent/reduce clustered ACEs should actively target economic risk factors, as well as individual/family-level risk factors. Interventions for parental DVA, MH, and SU often target low-income families or areas but rarely directly address poverty, even though socioeconomic support alone has been shown to reduce the prevalence of ACEs [ 55 ]. Future work would benefit from reframing ACE clusters as syndemic issues; not only examining how ACEs cluster or amplify one another but also exploring population-level social, economic, environmental, and political determinants which may be amenable to policy/system-level intervention [ 56 ].

The fact that our elevated adversity class was associated with worse child MH at age three (and subsequently, across time) serves to validate the policy focus on parental DVA, MH, and SU where this has been previously questioned [ 30 ]. Intervening early to support children and families with complex needs may minimise the potential disadvantage children face in terms of their MH. Early years education settings are likely to be useful sites for prevention of child MH problems. Future research should explore whether the impact of parental DVA, MH, and SU can be detected even earlier in a child’s development, as well elucidating the causal pathway between these clustered ACEs and child MH. This should be guided by frameworks such as Family Stress Theory which also consider the role poverty might play [ 57 ].

Unsurprisingly, there were high levels of variability in our latent-class-specific trajectories of child MH, which may be influenced by mediators/moderators, severity, or persistence of clustered-risk. Future work should examine: (1) more nuanced, differential latent trajectories associated with exposure to clustered parental DVA, MH, and SU and associated risk and protective factors, and (2) whether changes or stability in latent class membership over time might be associated with differential child MH outcomes.

Our study benefits from several strengths, including the use of a large nationally representative sample, prospective measurement of parental DVA, MH, and SU, consistent measurement of child MH, and pre-registered analysis plans. However, we need to consider its limitations. First, our measurement of parental DVA was restricted to a single-item on physical violence, the only available variable as with many large cohort studies. DVA can include physical, sexual, emotional, controlling or coercive, and economic abuse, all of which are essential to consider given the impact they can have on families [ 18 ]. Second, our measure of alcohol use was limited to frequency, as in other studies [ 31 ]. Although indicative of problematic use, our study suggests this is a poor ACE measure. Considering the quantity of alcohol use and impact on daily living would be preferable. Third, we were unable to consider severity of DVA, MH, and SU which may influence the impact on child outcomes [ 32 ]. Fourth, measures of DVA, MH, and SU relied on self-report which could be prone to social-desirability bias. This may be particularly pertinent for ethnic minority groups due to cultural stigma associated with DVA, MH, or SU. However, the prevalence of these issues appeared similar to other studies and, situated in the context of other questions, social-desirability bias is likely to explain a small amount of variance in responses [ 58 ]. Fifth, both our exposure variables and outcome variables rely on parent-reported measures, increasing the risk of information bias. Finally, while the fit indices of our overall and conditional LGM were sufficient, they were not optimal, meaning there is room for improvement to enhance the robustness and replicability of the model findings.

Improving support for families who experience co-occurring parental DVA, MH, and SU is a key priority for policy and practice. Our study validates this focus, finding that parental DVA, MH, and SU cluster during early child development and can have a negative and persistent impact on children’s MH as young as three-years of age. Our findings suggest preventing and responding to this clustered risk requires an early, multi-faceted response that addresses all these ACEs in combination as well as the socio-economic determinants that drive them.

Data availability

This study uses data from the MCS. MCS data can be found and accessed via the UK Data Service: https://ukdataservice.ac.uk/ .

Abbreviations

Akaike information criterion

Adverse childhood experience

Bayesian information criterion

Bootstrap likelihood-ratio test

Sample size adjusted Bayesian information criterion

• Domestic violence and abuse

Latent growth curve model

Millennium Cohort Study

• Mental ill-health

Multiple imputation by chained equations

Organisation for Economic Co-operation and Development

Strengths and Difficulties Questionnaire

Strengths and Difficulties Questionnaire Total Difficulties Score

• Substance misuse

Vuong-Lo-Mendell-Rubin adjusted likelihood-ratio test

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Acknowledgements

We would like to thank all the Millennium Cohort Study (MCS) children and families and the MCS research team for their involvement in the MCS as well as the UCL Centre for Longitudinal Studies and UK Data service for providing access to the MCS data. We would also like to thank Professor Obi Ukoumunne for his support with the multiple imputation and Dr Abby Russell and Dr Helen Eke for their support with the ethics application.

This report is independent research funded by a National Institute for Health and Care Research (NIHR) Applied Research Collaboration South West Peninsula (PenARC) awarded to VB as primary supervisor/PI and held as a PhD studentship by KA. The views expressed in this publication are those of the author(s) and not necessarily those of the National Institute for Health and Care Research or the Department of Health and Social Care. The MCS is funded by the UK Economic and Social Research Council.

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KA was responsible for the conceptualisation and design of the study, applying for ethics, conducting the formal analysis of the data, interpreting the data, preparing a first draft of the manuscript, making revisions, and submitting the manuscript for publication. All co-authors (GJMT, TF, CB, VB) made substantial contributions to the conceptualisation and design of the study, the interpretation of the data, and commenting on the first draft of the manuscript. In addition, GJMT also contributed to the formal analysis of the data, supporting with the conduct of latent variable mixture modelling. All authors (KA, GJMT, TF, CB, VB) have approved the submitted version and have agreed both to be personally accountable for the author’s own contributions and to ensure that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature.

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Allen, K., Melendez-Torres, G.J., Ford, T. et al. Parental domestic violence and abuse, mental ill-health, and substance misuse and the impact on child mental health: a secondary data analysis using the UK Millennium Cohort Study. BMC Public Health 24 , 2310 (2024). https://doi.org/10.1186/s12889-024-19694-1

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