Abstract
Three dopamine genes (DAT1, DRD2, and DRD4) have been associated with interpersonal delinquency, aggression, and violence when individuals experience adverse environmental exposures. Guided by the catalyst model of aggression, risk alleles identified in previous studies were hypothesized to be associated with intimate partner violence (IPV) perpetration in the presence of financial stressors, a possible environmental trigger. This hypothesis was tested using weighted, clustered logistic regression with data from The National Longitudinal Study of Adolescent to Adult Health. The direct effects DAT1, DRD2, and DRD4 on IPV perpetration, and the interaction of DAT1, DRD2, and DRD4 and financial stressors on IPV perpetration were assessed. Due to cell size, only white men and women were included in this analysis. Increasing number of financial stressors was associated with increased odds of IPV perpetration, regardless of DAT1, DRD2, and DRD4 alleles. As predicted, increasing number of financial stressors was more strongly associated with IPV perpetration among individuals with high risk DAT1 alleles, than individuals with low risk alleles. However, this relationship was inverted for DRD2. Although there was still a significantly interaction between DRD2 and financial stressors, individuals with low risk alleles had higher odds of IPV perpetration in the presence of financial stressors. A similar, non-significant relationship was found for DRD4. These findings indicate that these genes may interact differently with environmental exposures and types of violent behavior. Additionally, the findings may, if replicated, suggest dopamine plays a different role in IPV perpetration compared with other forms of aggression and violence.
Keywords: intimate partner violence, perpetration, DAT1, DRD2, DRD4, dopamine
Intimate partner violence (IPV) has significant implications for the mental, physical, and economic well-being of men and women. Approximately 5% of men and women in the United States experience physical IPV victimization each year (Black et al., 2011). Beyond the trauma and injury associated with physical violence victimization (Wu, Huff, & Bhandari, 2010), many men and women experience lasting physical and mental health issues (Afifi, Henriksen, Asmundson, & Sareen, 2012; Beydoun, Beydoun, Kaufman, Lo, & Zonderman, 2012; Devries et al., 2014; Okuda et al., 2011; Trevillion, Oram, Feder, & Howard, 2012; Vives-Cases, Ruiz-Cantero, Escribà-Agüir, & Miralles, 2011; Weiss, Duke, & Sullivan, 2014). Despite the high prevalence of IPV and the significant health consequences, a small proportion of the IPV literature examines risk and protective factors or prevention strategies for perpetrators. The limited understanding of factors contributing to IPV perpetration limits the development of effective intervention and prevention activities for perpetrators (Bell & Naugle, 2008; Eckhardt, Murphy, Black, & Suhr, 2006).
From the existing literature, it is clear the etiology of IPV perpetration is multifactorial and complex (Bell & Naugle, 2008). Individual personal characteristics may interact with physical and social experiences throughout life to shape the propensity to perpetrate IPV (Bell & Naugle, 2008). Although there are several etiological frameworks for IPV, existing frameworks often oversimplify the antecedents to IPV and fail to account for recent findings in the field of violence research (Bell & Naugle, 2008), including potential genetic contributions. The potential genetic contribution to IPV perpetration, especially in light of growing evidence on the role of genetic factors in the perpetration of other forms of aggression (Barnes & Jacobs, 2013; Beaver, Gibson, DeLisi, Vaughn, & Wright, 2011; T. J. Chen et al., 2005; Ferguson, 2010; Ferguson & Beaver, 2009; Ferguson, Ivory, & Beaver, 2013; Guo, Roettger, & Shih, 2007; Vaske, Boisvert, & Wright, 2012), is of growing interest to the field of violence research and has the potential to contribute to the understanding of the etiology of IPV perpetration.
Based on a comprehensive literature review, four studies of genetic factors for IPV perpetration were identified (Stuart et al., 2014). Two of the four studies used a twin design, which compares the similarities and differences between pairs of monozygotic and dizygotic twins to determine the relative contribution of genetic and environmental factors (Meaney, 2010). These studies were not able to identify specific genes or the interaction between those genes and the environment to predict violence (Meaney, 2010). However, the studies found genetic factors explained up to 54% of the variance in IPV perpetration, which supported the hypothesis that genetic factors contribute to IPV perpetration (Barnes, TenEyck, Boutwell, & Beaver, 2013; Hines & Saudino, 2004). There have also been two studies of the contribution of specific genes to IPV perpetration (Stuart et al., 2014). In a small study of men with hazardous alcohol behaviors in batterer intervention programs, the Monoamine Oxidase A (MAOA) gene and the serotonin transporter gene (SLC6A4) were significantly associated with more frequent IPV perpetration (Stuart et al., 2014). However, this study did not include any non-perpetrating control participants, so the generalizability of this study to the population was unclear. The second study examined the interaction between alcohol use and a cumulative genetic risk scale created by summing the number of individual alleles associated with higher risk of impulsivity as a result of dopamine processing (Foshee et al., 2015). This study found evidence that the association between the genetic risk scale and adolescent dating violence was significantly different depending participants’ alcohol use (Foshee et al., 2015). Together, these findings provided further support for the genetic contributions to IPV perpetration, at least in the presence of environment risk factors.
Genetic Polymorphisms
Although many genetic polymorphisms have been examined as potential contributors to violence perpetration, three dopaminergic genes (DAT1, DRD2, and DRD4) emerged as particularly promising. Research has found that these genes play a role in the processing of dopamine (Anselme, 2013), a neurotransmitter with significant influence on motivation and learning (Anselme, 2013; Wassum, Ostlund, Balleine, & Maidment, 2011). Additionally, variations in dopamine processing have been found to modulate the relationship between exposure to stressors and stress responses (Valenti, Gill, & Grace, 2012). In studies of the functional implications of these genes, DAT1 influenced the dopamine reuptake process in the presynaptic neuron (Fuke et al., 2001), and the 10-repeat allele was associated with changes to the rate of dopamine reuptake in the synapse and increased violence perpetration in young men (T. J. Chen et al., 2007; Guo et al., 2007). Carrying a 10R/10R genotype (two 10-repeat DAT1 alleles) was associated with lower levels of self-control (Li & Lee, 2012; Wright, Schnupp, Beaver, Delisi, & Vaughn, 2012) and deficits associated with impulse control, including attention, cognitive flexibility, and planning (Cornish et al., 2005).
Two dopamine receptor genes (DRD2, DRD4) have also been shown to be associated with violence perpetration (Beaver et al., 2007). As a result of fewer D2 dopamine receptors (Pohjalainen et al., 1998), the DRD2 A-1 allele was associated with increased susceptibility to environmental triggers (Bakermans-Kranenburg & van Ijzendoorn, 2011), elevated response to stressful situations (Berman & Noble, 1997), and an increased propensity for violence perpetration (Beaver, Gibson, Jennings, & Ward, 2009; Beaver et al., 2007; Guo et al., 2007). Similar to DRD2, DRD4 was associated with the availability of D4 dopamine receptors (Beaver et al., 2007). In interactions with the environment, the presence of a single 7-repeat allele was associated with reduced response to dopamine (Asghari et al., 1995), poor impulse control (Bakermans-Kranenburg & van Ijzendoorn, 2011), and increased odds of violence perpetration (Beaver et al., 2007; Dmitrieva, Chen, Greenberger, Ogunseitan, & Ding, 2011).
Environmental Exposures
Stress, defined as an interaction between individuals and their environment which results in the perception that the situation exceeds resources and compromises well-being (Lazarus & Folkman, 1984), has been associated with IPV perpetration across the lifespan (Cano & Vivian, 2001; Capaldi, Knoble, Shortt, & Kim, 2012; Mason & Smithey, 2012; Roberts, McLaughlin, Conron, & Koenen, 2011). Stressors, defined as the specific environmental trigger of the stress response (Selye, 1950), have received less attention in the literature as a potential antecedent to IPV perpetration, although specific forms of stressors, such as relationship conflict, have been consistently shown to be an antecedent to IPV perpetration (Byun, 2012; Elkins, Moore, McNulty, Kivisto, & Handsel, 2013; Langhinrichsen-Rohling, McCullars, & Misra, 2012; Shortt, Capaldi, Kim, & Tiberio, 2013; Whitaker, 2013).
Financial stressors, one potential environmental trigger of IPV (Byun, 2012; Neff, Holamon, & Schluter, 1995; Slep, Foran, Heyman, & Snarr, 2010; Schwab-Reese, Peek-Asa, & Parker, 2016), have been reported as stressful to both individual partners and the couple as a dyad (Mason & Smithey, 2012) Several studies of females have found an association between financial stress and IPV victimization (Golden, Perreira, & Durrance, 2013; Khalifeh, Hargreaves, Howard, & Birdthistle, 2013; Matjasko, Niolon, & Valle, 2013). However the associations of financial stressors and IPV were less consistent. In one study, increasing perceptions of financial stress were significantly associated with IPV victimization, but potential financial stressors, such as income to needs ratio, were not associated with IPV victimization (Benson, Fox, DeMaris, & Van Wyk, 2003). Another recent study found financial stressors, such as nonpayment of housing or food insecurity, were significantly associated with increased odds of IPV perpetration among both men and women (Schwab-Reese, Peek-Asa, & Parker, 2016), which may provide preliminary support for the association between financial stressors and IPV perpetration.
Understanding the multifactorial etiology of IPV perpetration is an important foundation for the development and implementation of effective IPV prevention and intervention programs (Bell & Naugle, 2008). Given the dearth of literature on the relationships of specific polymorphisms to IPV perpetration, the purpose of this analysis was to contribute to the understanding of the etiology of IPV perpetration through increased understanding of the interaction between three dopaminergic genes and adulthood financial stressors.
Method
Study population.
Data from the The National Longitudinal Study of Adolescent to Adult Health (Add Health) was used for this analysis. Between 1994 and 1995, over 90,000 students completed an in-school questionnaire. From the in-school sample, a subset of 20,745 adolescents participated in a prospective cohort study from 1995 to 2008 that included four waves of data collection (Harris KM, 2009). Of the original 20,745 participants, 15,701 participants completed data collection during Wave IV, which occurred when participants were 24 to 32 years old (Harris KM, 2009). Further information on the Add Health Study is available elsewhere (Harris KM, 2009).
Measures.
Outcome.
Participants reported intimate partner violence (IPV) perpetration during Wave IV (2008–2009) (Harris KM, 2009). Participants reported, “How often (have/did) you (slapped/slap), hit, or (kicked/kick) [partner’s initials]?” (Harris KM, 2009). Response options included, “Never”, “This has not happened in past year, but happened before then,” and specific numbers of times it occurred in the past year (Harris KM, 2009). Participants were coded as perpetrators if they reported slapping, hitting, or kicking their partner at least once in the prior year, and as non-perpetrators if they did not report these actions in the prior year.
Exposure.
The research team collected genetic data for all participants who consented. Further detailed information on the protocol, equipment, genotyping, and data cleaning for each gene is available elsewhere (Harris, Halpern, Smolen, & Haberstick, 2006; Smolen et al., 2013). For this analysis, each allele of DAT1, DRD2, and DRD4 was categorized as empirically associated with violence perpetration (“risk gene”) or not (“non-risk gene”) based on prior literature on the functional differences and associations with violence perpetration. For DAT1, the 10-repeat allele was coded as high risk and the 9-repeat allele as low risk (T. J. Chen et al., 2007; Guo et al., 2007). Individuals with the 11-repeat (n=4), 3-repeat (n=39), 7-repeat (n=53), and 8-repeat (n=181) were excluded from the DAT1 analysis because the functional implications of these alleles were unclear (Barnes & Jacobs, 2013). For DRD2, the A1 allele was coded as high risk and the A2 allele as low risk (Beaver et al., 2009; Beaver et al., 2007; Guo et al., 2007; Pohjalainen et al., 1998). For DRD4, the 7-repeat allele and 8-repeat allele were coded as high risk and the 2-repeat, 3.39-repeat, 3-repeat, 4-repeat, 5-repeat, and 6-repeat alleles as low risk (Beaver et al., 2007; Dmitrieva et al., 2011). Based on the literature, each pairs of alleles was categorized as high risk if there was at least one high risk DRD2 or DRD4 allele and two high risk DAT1 alleles (Thibodeau, Cicchetti, & Rogosch, 2015).
Interacting variable.
During Wave IV, participants reported if they had experienced each of the following six financial stressors during the prior twelve months: without phone service due to financial reasons; didn’t pay the full amount of the rent or mortgage due to financial reasons; evicted from housing for nonpayment; didn’t pay full amount of a gas, electricity, or oil bill due to financial reasons; gas or electric service turned off or oil company wouldn’t delivery because of nonpayment; worried that food would run out before there was money to buy more (Harris KM, 2009). As was consistent with prior literature (Halliday Hardie & Lucas, 2010), the total number of stressors reported by each participant was summed with scores ranging from zero to six
Statistical analysis.
In accordance with guidelines provided by the Add Health study research team, all analyses were weighted and clustered to account for the complex survey design. Distributions of polymorphisms differed by race, so all analyses were stratified by race. Given the relative rarity of combinations of the risk alleles, financial stressors, and IPV perpetration, the analysis was limited to white individuals due to insufficient sample size among the remaining racial/ethnic groups.
Univariate analysis was used to estimate the mean number of financial stressors, and the number of high risk genes. Weighted, clustered simple logistic regression models were used to examine relationship between financial stressors, high risk genes, and IPV perpetration and weighted, clustered logistic regression models including main effects of each of the dopaminergic genes and financial stressors, and interaction effect of the two variables to estimate the odds of perpetrating physical IPV for each combination of exposure compared to having neither exposure and the odds of perpetrating IPV associated with financial stressors comparing participants in the same dopaminergic risk category. Finally, the predicted probability of perpetrating IPV by each level of financial stressor and risk allele was calculated.
To be eligible for this analysis, participants must have been in a romantic relationship during the past twelve months, answered questions on the exposure, interaction, and outcome variables, and completed genotyping. Participants who were not in a relationship during the past twelve months were excluded because their reports of IPV perpetration occurred more than twelve months prior to the interview. Since financial stressors were measured during the prior year, it would have been temporally ambiguous to include participants who reported relationship experiences that occurred prior to the timeframe for financial stressors.
Of the nearly 16,000 participants who completed Wave IV data collection, approximately 11,500 were included in this analysis. Most of the excluded participants (~3,320) did not have a romantic partner in the prior twelve months so could not report experiences with IPV. The remaining participants (~900) were excluded due to missing data for IPV perpetration, financial stressors, or other covariates. However, participants were not removed from the dataset. As directed by the Add Health research team, the weights for these participants were set to 0.000001, which included the participants in the weighting process but did not include them in the estimates produced by the model (P. Chen & Chantala, 2014).
Results
Financials stressors, polymorphisms, and perpetration of IPV.
The mean number of financial stressors was 0.5 (95%CI:0.4–0.5) (Table 1). Approximately three-quarters (77.5%, 95%CI:75.8–79.2) reported no financial stressors in the past year. Approximately 16.0% (95%CI:14.3–17.8) reported one financial stressor and 6.5% (95%CI:5.0–7.9) reported more than one financial stressor. As the number of financial stressors increased, the odds of perpetrating IPV increased 1.34 times (95%CI:1.26–1.44). More than half had two DAT1 risk alleles (55.7%, 95%CI:53.9–57.58) and approximately one-third had one DRD2 (38.1%, 95%CI:36.7–39.5) or DRD4 (37.0%, 95%CI:35.8–38.3) risk allele. None of the risk alleles were directly associated with IPV perpetration.
Table 1.
Estimated percent and 95% confidence intervals financial stressors and dopamine genes, and their associations with IPV perpetration among white men and women
| Mean (95% CI) | Association with IPVa | |
|---|---|---|
|
| ||
| Financial Stressors b | 0.5 (0.4–0.5) | 1.34 (1.26–1.44) |
|
| ||
| Estimated Proportion (95%CI)c | Association with IPVa | |
|
| ||
| DAT1 | ||
| 2 risk alleles | 55.7 (53.9–57.5) | 0.95 (0.75–1.21) |
| 0 or 1 risk alleles | 44.3 (42.5–46.1) | Ref |
| DRD2 | ||
| 1 or 2 risk alleles | 38.1 (36.7–39.5) | 1.05 (0.81–1.38) |
| 0 risk alleles | 61.9 (60.5–63.3) | Ref |
| DRD4 | ||
| 1 or 2 risk alleles | 37.0 (35.8–38.3) | 1.05 (0.80–1.38) |
| 0 risk alleles | 63.0 (61.7–64.2) | Ref |
Crude odds ratio and 95%CI predicting IPV perpetration
Total number of financial stressors ranging from 0 to 6
Estimated column percent and 95%CI;
Interaction of polymorphisms and financial stressors.
Increased financial stressors significantly increased the odds of perpetrating IPV across all genes and allele categorizations, when compared with individuals with no financial stressors and no risk alleles (Table 2). However, the magnitude of the increase varied across allele categorizations. Individuals with two DAT1 risk alleles and six financial stressors had 10.07 times (95%CI:5.07–20.03) higher odds of perpetration compared with individuals with no risk alleles and no financial stressors. Among individuals with zero or one DAT1 risk allele, the increase in the odds associated with a greater number of financial stressors was smaller (OR:5.11; 95%CI:2.68–9.74). As the number of financial stressors increased, the probability of perpetration (Figure 1) was significantly higher among individuals with two DAT1 risk alleles, compared with individuals with no or one DAT1 risk allele (interaction p-value=.05). This significant interaction indicated that the presence of financial stressors significantly moderated the relationship between DAT1 alleles and IPV perpetration.
Table 2.
Associations between perpetrating physical intimate partner violence and the interaction of dopaminergic polymorphism and financial stressors among white men and women
| High Exposure OR (95%CI)a |
Low Exposure OR (95%CI)b |
OR (95%CI) for exposure to violence within strata of genec | |
|---|---|---|---|
|
| |||
| Financial Stressors | |||
|
| |||
| DAT1 | |||
| 2 risk alleles | 10.07 (5.07–20.03) | 0.86 (0.64–1.15) | 11.73 (5.54–24.83) |
| 0 or 1 risk alleles | 5.11 (2.68–9.74) | Ref | |
| DRD2 | |||
| 1 or 2 risk alleles | 4.40 (2.00–9.68) | 1.30 (0.96–1.76) | 3.39 (1.49–7.72) |
| 0 risk alleles | 12.23 (5.69–26.25) | Ref | |
| DRD4 | |||
| 1 or 2 risk alleles | 5.96 (2.56–13.89) | 1.16 (0.85–1.60) | 5.12 (1.97–13.28) |
| 0 risk alleles | 9.95 (5.04–19.65) | Ref | |
Defined as highest level of possible exposure (i.e., all financial stressors)
Defined as lowest level of possible exposure (i.e., no financial stressors)
Comparion of high exposure to low exposure among individuals with same level of risk alleles
Figure 1.

Predicted probability of perpetrating physical IPV, by polymorphism and financial stressor.
In contrast, individuals with one or two DRD2 risk alleles and six financial stressors had 4.40 (95%CI:2.00–9.68) times higher odds of perpetrating IPV compared with individuals with no DRD2 risk alleles and no financial stressors. This increase in the odds of perpetration associated with financial stressors was significantly less (interaction p-value=.02) than among individuals with no risk alleles (OR:12.23; 95%CI: 5.69–26.25). Although both groups experienced significantly increased probability of perpetration as number of financial stressors increased, the probability of perpetration was significantly higher among individuals with no DRD2 risk alleles compared with individuals with one or two DRD2 risk alleles (Figure 1). Thus, the presence of financial stressors significantly moderated the relationship between DRD2 risk alleles and financial stressors, although in the opposite direction as the DAT1 moderation. The results of the models of DRD4 were similar, however, there was not a significant interaction between financial stressors and DRD4.
Discussion
These findings contributed to the small body of literature on genetic contributions to IPV perpetration (Stuart et al., 2014) and suggested that the etiology of IPV perpetration is complex and multifactorial. Although having DAT1 risk alleles increased the probability of perpetrating IPV as number of financial stressors increased, the associations between DRD2 and DRD4 with financial stressors did not support the initial hypothesis. In fact, having DRD2 risk alleles was associated with significantly smaller increases in the probability of IPV perpetration, compared with peers with without DRD2 risk alleles. Although financial stressors significantly increased the probability of perpetrating IPV, the presence of DRD4 risk alleles did not significantly influence that relationship. The results did not indicate that DAT1, DRD2, and DRD4 polymorphisms were significantly associated with IPV perpetration, at least in the absence of environmental experiences. Any contribution of dopaminergic polymorphisms was likely the result of their interaction with the environment and their influence on other factors (e.g., differential response to stress) (Stuart et al., 2014). At a minimum, the findings suggested the interactions between dopamine genes and exposure to stressors were better predictors of IPV perpetration compared with dopamine genes alone.
These analyses contributed to the understanding of the specific genetic polymorphisms to IPV perpetration, which, to our knowledge, had only been examined by two previous studies(Stuart et al., 2014). In the initial study of specific genes, the Monoamine Oxidase A (MAOA) gene and the serotonin transporter gene (SLC6A4) were associated with more frequent IPV perpetration (Stuart et al., 2014). In contrast, the results of this analyses suggested that the dopaminergic genes under consideration do not directly contribute to IPV perpetration. The second study examined the interaction between alcohol use and dopamine genes (Foshee et al., 2015). Similar to this study, this analyses suggested the interaction between genes and environmental experiences, such as financial stressors, was a better predictor of IPV perpetration than genes alone. This gene and environment interaction was consistent with prior findings on contributions of genes to other forms of aggression (Barnes & Jacobs, 2013). In prior research, the association between violence perpetration and a higher number of risk alleles was dependent upon harmful environmental experiences, such as neighborhood disadvantage (Barnes & Jacobs, 2013). However, this relationship was found only for men and not for women (Barnes & Jacobs, 2013) and this study found no significant differences by gender. These results may have implications for the development of IPV prevention and intervention activities, but additional research will be necessary to clarify the role of genetic and environmental interactions. However, financial stressors significantly increased the odds of IPV perpetration, regardless of polymorphism, so interventions to reduce financial stressors may benefit all individuals, regardless of genetic factors.
It is crucial to carefully interpret the results of these analyses, particularly in light of the limitations. There were two limitations associated with gene by environment analysis of complex behavioral outcomes. First, the gene by environment analysis of complex behaviors was based on probabilistic methods and was not able to identify specific functional implications associated with the polymorphisms (Meaney, 2010). As a result, this type of study was unable to determine a causal relationship between dopaminergic polymorphisms and IPV perpetration (Meaney, 2010). Second, this analysis was not able to account for epigenetic differences, which may mitigate the effects of specific polymorphisms by altering transcription (Essex et al., 2013).
There were also some limitations associated with the study design. As a secondary data analysis, the possible variables were limited to those collected by the study investigators. Several potentially important variables, including child maltreatment and exposure to parental intimate partner violence, were not available in the data. In addition, these results depended upon perpetrator self-report, which may differ from victim report (Renner, Schwab-Reese, Peek-Asa, & Ramirez, In press). Additionally, these analyses were at the level of the individual, rather than at the event-level. Exposure to financial stressors may change over time so an analysis at the event-level would have been able to determine the specific levels of exposure at the time of perpetration. For example, a recent study asked participants to keep daily diaries of their affect and their experiences with their partners (Elkins et al., 2013). By tracking affect every day, these researchers were better able to determine the temporal association between affect and IPV. However, this type of data was expensive to collect, time consuming for both participants and researchers, and subject to high costs. Finally, this analysis was not able to account for whether IPV perpetration occurring during the relationship or after a relationship ended. Additionally, individuals who were not in a partnership during the past twelve months may have continued to perpetrate against former partners, but that perpetration was not captured in the current data structure. The termination of relationships has been identified as a high risk period for IPV perpetration (Saftlas et al., 2010), so it may be important to understand how the relationships of stressors and genes influence IPV among former partners.
Despite these limitations, these findings may have important implications for future IPV research and practice. A better understanding of the interactions between genes and the environment may result in more effective intervention and prevention activities that can be tailored to the individual and those at highest risk for perpetration. Ultimately, pharmacological or behavioral intervention may be tailored to individuals based on their composition of genetic and environmental risk factors.
Acknowledgments
This research was funded by a pilot project through the University of Iowa Injury Prevention Research Center. This research uses data from Add Health, a program project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill, and funded by grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from 23 other federal agencies and foundations. Special acknowledgment is due Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Information on how to obtain the Add Health data files is available on the Add Health website (http://www.cpc.unc.edu/addhealth). No direct support was received from grant P01-HD31921 for this analysis. Special thanks to Marizen Ramirez, Sato Ashida, and Carri Casteel for their feedback on earlier drafts of the manuscript.
Footnotes
This is the peer reviewed version of the following article: Schwab-Reese LM, Parker EA, Peek-Asa C. The Interaction of Dopamine Genes and Financial Stressors to Predict Adulthood Intimate Partner Violence Perpetration. J Interpers Violence. 2020 Mar;35(5–6):1251–1268. doi: 10.1177/0886260517696841. Epub 2017 Mar 9. PMID: 29294665., which has been published in final form at 10.1177/0886260517696841. This article may be used for non-commercial purposes in accordance with Sage Journal Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Sage Jouranl or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Sage Journal’s version of record and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Sage Journal must be prohibited.
References
- Afifi TO, Henriksen CA, Asmundson GJ, & Sareen J (2012). Victimization and perpetration of intimate partner violence and substance use disorders in a nationally representative sample. The journal of Nervous and Mental Disease, 200(8), 684–691. [DOI] [PubMed] [Google Scholar]
- Anselme P (2013). Dopamine, motivation, and the evolutionary significance of gambling-like behaviour. Behavioural Brain Research, 256, 1–4. [DOI] [PubMed] [Google Scholar]
- Asghari V, Sanyal S, Buchwaldt S, Paterson A, Jovanovic V, & Van Tol HH (1995). Modulation of intracellular cyclic AMP levels by different human dopamine D4 receptor variants. Journal of Neurochemistry, 65(3), 1157–1165. [DOI] [PubMed] [Google Scholar]
- Bakermans-Kranenburg MJ, & van Ijzendoorn MH (2011). Differential susceptibility to rearing environment depending on dopamine-related genes: New evidence and a meta-analysis. Development and Psychopathology, 23(01), 39–52. [DOI] [PubMed] [Google Scholar]
- Barnes J, & Jacobs BA (2013). Genetic Risk for Violent Behavior and Environmental Exposure to Disadvantage and Violent Crime The Case for Gene–Environment Interaction. Journal of Interpersonal Violence, 28(1), 92–120. [DOI] [PubMed] [Google Scholar]
- Barnes J, TenEyck M, Boutwell BB, & Beaver KM (2013). Indicators of domestic/intimate partner violence are structured by genetic and nonshared environmental influences. Journal of Psychiatric Research, 47(3), 371–376. [DOI] [PubMed] [Google Scholar]
- Beaver KM, Gibson CL, DeLisi M, Vaughn MG, & Wright JP (2011). The interaction between neighborhood disadvantage and genetic factors in the prediction of antisocial outcomes. Youth Violence and Juvenile Justice, 1541204011422085. [Google Scholar]
- Beaver KM, Gibson CL, Jennings WG, & Ward JT (2009). A gene X environment interaction between DRD2 and religiosity in the prediction of adolescent delinquent involvement in a sample of males. Biodemography and Social Biology, 55(1), 71–81. [DOI] [PubMed] [Google Scholar]
- Beaver KM, Wright JP, DeLisi M, Walsh A, Vaughn MG, Boisvert D, & Vaske J (2007). A gene× gene interaction between DRD2 and DRD4 is associated with conduct disorder and antisocial behavior in males. Behavioral and Brain Functions, 3(30), 1186–1193. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Bell KM, & Naugle AE (2008). Intimate partner violence theoretical considerations: Moving towards a contextual framework. Clinical Psychology Review, 28(7), 1096–1107. [DOI] [PubMed] [Google Scholar]
- Benson ML, Fox GL, DeMaris A, & Van Wyk J (2003). Neighborhood disadvantage, individual economic distress and violence against women in intimate relationships. Journal of Quantitative Criminology, 19(3), 207–235. [Google Scholar]
- Berman SM, & Noble EP (1997). The D2 dopamine receptor (DRD2) gene and family stress; interactive effects on cognitive functions in children. Behavior Genetics, 27(1), 33–43. [DOI] [PubMed] [Google Scholar]
- Beydoun HA, Beydoun MA, Kaufman JS, Lo B, & Zonderman AB (2012). Intimate partner violence against adult women and its association with major depressive disorder, depressive symptoms and postpartum depression: a systematic review and meta-analysis. Social Science & Medicine, 75(6), 959–975. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Black M, Basile K, Breiding M, Smith S, Walthers S, Merrick M, & al e. (2011). The National Intimate Partner and Sexual Violence Survey (NISVS): 2010 Summary Report. Atlanta, GA: [Google Scholar]
- Byun S. h. (2012). What happens before intimate partner violence? Distal and proximal antecedents. Journal of Family Violence, 27(8), 783–799. [Google Scholar]
- Cano A, & Vivian D (2001). Life stressors and husband-to-wife violence. Aggression and Violent Behavior, 6(5), 459–480. [Google Scholar]
- Capaldi DM, Knoble NB, Shortt JW, & Kim HK (2012). A systematic review of risk factors for intimate partner violence. Partner Abuse, 3(2), 231. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Chen P, & Chantala K (2014). Guidelines for analyzing add health data. Retrieved from http://www.cpc.unc.edu/projects/addhealth/data/guides/wt-guidelines.pdf
- Chen TJ, Blum K, Mathews D, Fisher L, Schnautz N, Braverman ER, Schoolfield J, Downs MW, Blum SH, Mengucci J, Meshkin B, Arcuri V, Bajaj N, Wait RL, & Comings DE (2007). Preliminary association of both the Dopamine D2 Receptor (DRD2)[Taq1 A1 Allele] and the Dopamine Transporter (DAT1)[480 bp Allele] genes with pathological aggressive behavior, a clinical subtype of Reward Deficiency Syndrome (RDS) in adolescents. Gene Therapy & Molecular Biologyl, 11, 93–112. [Google Scholar]
- Chen TJ, Blum K, Mathews D, Fisher L, Schnautz N, Braverman ER, Schoolfield J, Downs BW, & Comings DE (2005). Are dopaminergic genes involved in a predisposition to pathological aggression?: Hypothesizing the importance of “super normal controls” in psychiatricgenetic research of complex behavioral disorders. Medical Hypotheses, 65(4), 703–707. [DOI] [PubMed] [Google Scholar]
- Cornish KM, Manly T, Savage R, Swanson J, Morisano D, Butler N, Grant G, Cross G, Bentley L, & Hollis C (2005). Association of the dopamine transporter (DAT1) 10/10-repeat genotype with ADHD symptoms and response inhibition in a general population sample. Molecular Psychiatry, 10(7), 686–698. [DOI] [PubMed] [Google Scholar]
- Devries KM, Child JC, Bacchus LJ, Mak J, Falder G, Graham K, Watts C, & Heise L (2014). Intimate partner violence victimization and alcohol consumption in women: a systematic review and meta‐analysis. Addiction, 109(3), 379–391. [DOI] [PubMed] [Google Scholar]
- Dmitrieva J, Chen C, Greenberger E, Ogunseitan O, & Ding Y-C (2011). Gender-specific expression of the DRD4 gene on adolescent delinquency, anger and thrill seeking. Social Cognitive and Affective Neuroscience, 6(1), 82–89. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Eckhardt CI, Murphy C, Black D, & Suhr L (2006). Intervention programs for perpetrators of intimate partner violence: Conclusions from a clinical research perspective. Public Health Reports, 121(4), 369. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Elkins SR, Moore TM, McNulty JK, Kivisto AJ, & Handsel VA (2013). Electronic diary assessment of the temporal association between proximal anger and intimate partner violence perpetration. Psychology of Violence, 3(1), 100. [Google Scholar]
- Essex MJ, Thomas Boyce W, Hertzman C, Lam LL, Armstrong JM, Neumann S, & Kobor MS (2013). Epigenetic vestiges of early developmental adversity: childhood stress exposure and DNA methylation in adolescence. Child Sevelopment, 84(1), 58–75. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Ferguson CJ (2010). Genetic contributions to antisocial personality and behavior: A meta-analytic review from an evolutionary perspective. The Journal of Social Psychology, 150(2), 160–180. [DOI] [PubMed] [Google Scholar]
- Ferguson CJ, & Beaver KM (2009). Natural born killers: The genetic origins of extreme violence. Aggression and Violent Behavior, 14(5), 286–294. [Google Scholar]
- Ferguson CJ, Ivory JD, & Beaver KM (2013). Genetic, maternal, school, intelligence, and media use predictors of adult criminality: A longitudinal test of the catalyst model in adolescence through early adulthood. Journal of Aggression, Maltreatment & Trauma, 22(5), 447–460. [Google Scholar]
- Foshee VA, Benefield TS, Puvanesarajah S, Reyes HLM, Haberstick BC, Smolen A, Ennett ET, &Suchindran C (2015). Self‐regulatory failure and the perpetration of adolescent dating violence: Examining an alcohol use by gene explanation. Aggressive behavior, 41(2), 189–203. [DOI] [PubMed] [Google Scholar]
- Fuke S, Suo S, Takahashi N, Koike H, Sasagawa N, & Ishiura S (2001). The VNTR polymorphism of the human dopamine transporter (DAT1) gene affects gene expression. The Pharmacogenomics Journal, 1(2), 152–156. [DOI] [PubMed] [Google Scholar]
- Golden SD, Perreira KM, & Durrance CP (2013). Troubled times, troubled relationships: how economic resources, gender beliefs, and neighborhood disadvantage influence intimate partner violence. Journal of Interpersonal Violence, DOI: 0886260512471083. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Guo G, Roettger ME, & Shih JC (2007). Contributions of the DAT1 and DRD2 genes to serious and violent delinquency among adolescents and young adults. Human Genetics, 121(1), 125–136. [DOI] [PubMed] [Google Scholar]
- Halliday Hardie J, & Lucas A (2010). Economic factors and relationship quality among young couples: Comparing cohabitation and marriage. Journal of Marriage and Family, 72(5), 1141–1154. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Harris KM, Halpern CT, Smolen A, & Haberstick BC (2006). The national longitudinal study of adolescent health (Add Health) twin data. Twin Research and Human Genetics, 9(06), 988–997. [DOI] [PubMed] [Google Scholar]
- Harris KM HC, Whitsel E, Hussey J, Tabor, & Entzel P (2009). The National Longitudinal Study of Adolescent Health: Research Design. Retrieved from http://www.cpc.unc.edu/projects/addhealth/design
- Hines DA, & Saudino KJ (2004). Genetic and environmental influences on intimate partner aggression: A preliminary study. Violence and Victims, 19(6), 701–718. [DOI] [PubMed] [Google Scholar]
- Khalifeh H, Hargreaves J, Howard LM, & Birdthistle I (2013). Intimate partner violence and socioeconomic deprivation in England: findings from a national cross-sectional survey. American Journal of Public Health, 103(3), 462–472. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Langhinrichsen-Rohling J, McCullars A, & Misra TA (2012). Motivations for men and women’s intimate partner violence perpetration: A comprehensive review. Partner Abuse, 3(4), 429–468. [Google Scholar]
- Lazarus R, & Folkman S (1984). The stress concept in the life sciences. Stress, Sppraisal and Coping, 1–21. [Google Scholar]
- Li JJ, & Lee SS (2012). Interaction of dopamine transporter (DAT1) genotype and maltreatment for ADHD: a latent class analysis. Journal of Child Psychology and Psychiatry, 53(9), 997–1005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Mason B, & Smithey M (2012). The effects of academic and interpersonal stress on dating violence among college students a test of classical strain theory. Journal of Interpersonal Violence, 27(5), 974–986. [DOI] [PubMed] [Google Scholar]
- Matjasko JL, Niolon PH, & Valle LA (2013). The role of economic factors and economic support in preventing and escaping from intimate partner violence. Journal of Policy Analysis and Management, 32(1), 122–128. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Meaney MJ (2010). Epigenetics and the biological definition of gene× environment interactions. Child Development, 81(1), 41–79. [DOI] [PubMed] [Google Scholar]
- Neff JA, Holamon B, & Schluter TD (1995). Spousal violence among Anglos, Blacks, and Mexican Americans: The role of demographic variables, psychosocial predictors, and alcohol consumption. Journal of Family Violence, 10(1), 1–21. [Google Scholar]
- Okuda M, Olfson M, Hasin D, Grant BF, Lin K-H, & Blanco C (2011). Mental health of victims of intimate partner violence: Results from a national epidemiologic survey. Psychiatric Services, 62(8), 959–962. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Pohjalainen T, Rinne J, Någren K, Lehikoinen P, Anttila K, Syvälahti E, & Hietala J (1998). The A1 allele of the human D2 dopamine receptor gene predicts low D2 receptor availability in healthy volunteers. Molecular Psychiatry, 3(3), 256–260. [DOI] [PubMed] [Google Scholar]
- Renner LM, Schwab-Reese L, Peek-Asa C, & Ramirez M (In press). Reporting patterns of unidirectional and bidirectional verbal aggression and physical violence among rural couples. Journal of Family Violence. [Google Scholar]
- Roberts AL, McLaughlin KA, Conron KJ, & Koenen KC (2011). Adulthood stressors, history of childhood adversity, and risk of perpetration of intimate partner violence. American journal of Preventive Medicine, 40(2), 128–138. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Saftlas AF, Wallis AB, Shochet T, Harland KK, Dickey P, & Peek-Asa C (2010). Prevalence of intimate partner violence among an abortion clinic population. American Journal of Public Health, 100(8), 1412–1415. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Schwab-Reese LM, Peek-Asa C, & Parker E (2016). Associations of financial stressors and physical intimate partner violence perpetration. Injury Epidemiology, 3(1), 1–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Selye H (1950). Stress and the general adaptation syndrome. British Medical Journal, 1(4667), 1383. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Shortt JW, Capaldi DM, Kim HK, & Tiberio SS (2013). The interplay between interpersonal stress and psychological intimate partner violence over time for young at-risk couples. Journal of Youth and Adolescence, 42(4), 619–632. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Slep AMS, Foran HM, Heyman RE, & Snarr JD (2010). Unique risk and protective factors for partner aggression in a large scale Air Force survey. Journal of Community Health, 35(4), 375–383. [DOI] [PubMed] [Google Scholar]
- Smolen A, Witsel E, Tabor J, Killeya-Jones L, Cuthbertson C, Hussey J, Halpern CT, & Harris K (2013). Add Health Wave IV Documentation Report: Candidate Genes. Retrieved from http://www.cpc.unc.edu/projects/addhealth/data/guides/DNA_documentation.pdf
- Stuart GL, McGeary JE, Shorey RC, Knopik VS, Beaucage K, & Temple JR (2014). Genetic associations with intimate partner violence in a sample of hazardous drinking men in batterer intervention programs. Violence Against Women, 20(4), 385–400. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Thibodeau EL, Cicchetti D, & Rogosch FA (2015). Child maltreatment, impulsivity, and antisocial behavior in African American children: moderation effects from a cumulative dopaminergic gene index. Development and Psychopathology, 27(4pt2), 1621–1636. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Trevillion K, Oram S, Feder G, & Howard LM (2012). Experiences of domestic violence and mental disorders: a systematic review and meta-analysis. PLoS One, 7(12), e51740. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Valenti O, Gill KM, & Grace AA (2012). Different stressors produce excitation or inhibition of mesolimbic dopamine neuron activity: response alteration by stress pre‐exposure. European Journal of Neuroscience, 35(8), 1312–1321. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Vaske J, Boisvert D, & Wright JP (2012). Genetic and environmental contributions to the relationship between violent victimization and criminal behavior. Journal of Interpersonal Violence, DOI:0886260512441254. [DOI] [PubMed] [Google Scholar]
- Vives-Cases C, Ruiz-Cantero MT, Escribà-Agüir V, & Miralles JJ (2011). The effect of intimate partner violence and other forms of violence against women on health. Journal of Public Health, 33(1), 15–21. [DOI] [PubMed] [Google Scholar]
- Wassum KM, Ostlund SB, Balleine BW, & Maidment NT (2011). Differential dependence of Pavlovian incentive motivation and instrumental incentive learning processes on dopamine signaling. Learning & Memory, 18(7), 475–483. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Weiss NH, Duke AA, & Sullivan TP (2014). Evidence for a curvilinear dose-response relationship between avoidance coping and drug use problems among women who experience intimate partner violence. Anxiety, Stress, & Coping, 27(6), 722–732. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Whitaker MP (2013). Motivational Attributions About Intimate Partner Violence Among Male and Female Perpetrators. Journal of Interpersonal Violence, 0886260513505211. [DOI] [PubMed] [Google Scholar]
- Wright JP, Schnupp R, Beaver KM, Delisi M, & Vaughn M (2012). Genes, maternal negativity, and self-control: Evidence of a gene× environment interaction. Youth Violence and Juvenile Justice, 1541204011429315. [Google Scholar]
- Wu V, Huff H, & Bhandari M (2010). Pattern of physical injury associated with intimate partner violence in women presenting to the emergency department: a systematic review and meta-analysis. Trauma, Violence, & Abuse, 11(2), 71–82. [DOI] [PubMed] [Google Scholar]
