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Traumatology Intimate Partner Violence Among Service Members and Veterans: Differences by Sex and Rurality David L. Albright, Justin McDaniel, Kelli Godfrey, Catherine Carlson, Kari L. Fletcher, and Kate Hendricks Thomas Online First Publication, January 2, 2020. http://dx.doi.org/10.1037/trm0000236
CITATION Albright, D. L., McDaniel, J., Godfrey, K., Carlson, C., Fletcher, K. L., & Thomas, K. H. (2020, January 2). Intimate Partner Violence Among Service Members and Veterans: Differences by Sex and Rurality. Traumatology. Advance online publication. http://dx.doi.org/10.1037/trm0000236
Intimate Partner Violence Among Service Members and Veterans: Differences by Sex and Rurality
David L. Albright University of Alabama
Justin McDaniel Southern Illinois University
Kelli Godfrey and Catherine Carlson University of Alabama
Kari L. Fletcher University of St. Thomas
Kate Hendricks Thomas George Mason University
Among military service members and veterans (SMVs), factors unique to military service may contribute to an elevated risk of experiencing intimate partner violence (IPV) victimization. Although rurality has been established as a risk factor for IPV, differences in IPV victimization by rural– urban dwelling location, SMV status, and sex have not been explored. The purpose of this study was to estimate the rate of IPV victimization in rural and urban areas in the United States by SMV status and sex. We obtained Behavioral Risk Factor Surveillance System data (BRFSS; n � 18,755); fit a mixed-effects, multilevel generalized linear model to the data for IPV victimization; and linked the model to U.S. Census Bureau population count data. We generated predicted estimates of IPV for SMVs and civilians separately by sex in rural and urban areas. The direct IPV victimization prevalence rate for the entire BRFSS sample was 16.90%. Substantial variation in model-based IPV prevalence was observed across subgroups. Female SMVs (rural � 23.54%, 95% confidence interval [CI] [17.33, 30.02]; urban � 23.34%, 95% CI [17.48, 30.17]) had higher IPV victimization rates than female civilians (rural � 14.55%, 95% CI [13.06, 16.37]; urban � 14.50%, 95% CI [13.19, 16.34]), whereas male civilians (rural � 8.06%, 95% CI [7.19, 9.08]; urban � 8.02%, 95% CI [7.27, 9.02]) had higher IPV victimization rates than male SMVs (rural � 7.21%, 95% CI [6.03, 8.47]; urban � 7.17%, 95% CI [6.00, 8.41]). Programming for preventing and assisting in recovering from IPV exposure should target rural-dwelling female SMVs.
Keywords: intimate partner violence, veterans, rural
Intimate partner violence (IPV) includes physical violence, sex- ual violence, stalking, and psychological aggression perpetrated by a current or former intimate partner (Breiding, Basile, Smith, Black, & Mahendra, 2015). Approximately one in four women and one in 10 men have experienced IPV in their lifetime (Smith et al., 2018). Negative physical and mental health consequences of IPV impact both victims of violence as well as their families (Breiding, Black, & Ryan, 2008). Physical health consequences of IPV in- clude gynecological problems, sleep disturbance, chronic health issues, increased risk of sexual transmitted infections, injury, and
death (Breiding et al., 2008). Mental health consequences of IPV can include depression, anxiety, posttraumatic stress disorder (PTSD), substance use disorders, bipolar disorder, and panic dis- order (Eshelman & Levendosky, 2012). Children exposed to IPV may experience behavioral and emotional problems and are at an increased risk of experiencing child maltreatment (Huth-Bocks & Hughes, 2008).
Age, gender, race and ethnicity, socioeconomic status, and geographic location are among several risk factors that may be predictors of IPV (Capaldi, Knoble, Shortt, & Kim, 2012). Al- though both men and women are impacted by IPV, women are more susceptible to and more often experience negative conse- quences resulting from IPV (Capaldi et al., 2012). Members of minority race/ethnicities are at higher risks for IPV (Capaldi et al., 2012). Socioeconomic status, which includes education level, em- ployment status, and income level, is a risk factor for IPV and is often an issue prevalent in rural areas (Capaldi et al., 2012). A growing body of evidence suggests that residential location can have an impact on the risk of experiencing or witnessing IPV (Edwards, 2015). Living in rural areas may increase the risk for more chronic and severe IPV, including intimate partner homicide, and reduced access to IPV services (Edwards, 2015). Rural areas
X David L. Albright, School of Social Work, University of Alabama; X Justin McDaniel, Department of Public Health, Southern Illinois University; X Kelli Godfrey and X Catherine Carlson, School of Social Work, University of Alabama; Kari L. Fletcher, School of Social Work, University of St. Thomas; Kate Hendricks Thomas, Department of Global and Community Health, George Mason University.
Correspondence concerning this article should be addressed to David L. Albright, School of Social Work, University of Alabama, Box 870314, Tuscaloosa, AL 35487. E-mail: [email protected]
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Traumatology © 2020 American Psychological Association 2020, Vol. 1, No. 999, 000 ISSN: 1085-9373 http://dx.doi.org/10.1037/trm0000236
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have limited access to physical and mental health care, as well as high rates of poverty; all of which are risk factors for IPV (Davi- dov et al., 2017; Dudgeon & Evanson, 2014). Peek-Asa et al.’s (2011) study of women living in Iowa showed that (a) IPV prev- alence was higher in rural areas than in urban areas (22.50% vs. 15.50%) and (b) approximately one in four women living in rural areas lived more than 40 miles from the nearest IPV victimization program or service, compared with less than 1.00% of women living in urban areas.
Veterans’ vulnerability to experiencing IPV may be com- pounded owing to both military culture and PTSD, which often accompanies combat deployment (Taft et al., 2009). Estimates of IPV victimization prevalence among service members and veter- ans (SMVs) range from 13.30% to 47.00% (Gierisch et al., 2013). Military culture’s prescribed organizational structures and rigid standards—its mission, duty, and loyalty spanning all branches vary from the culture of most civilian workplaces—may exacer- bate psychosocial problems within military intimate relationships (Redmond et al., 2015). Women’s increasing presence within the military (Thomas, McDaniel, Albright, Fletcher, & Haring, 2018) in tandem with their experiences of premilitary trauma, military sexual trauma, PTSD, and higher rates of IPV more broadly have brought increased recognition of IPV within the Veterans Health Administration (Gerber, Iverson, Dichter, Klap, & Latta, 2014). Previous research shows that persons diagnosed with PTSD are more likely to experience IPV, and veterans exposed to combat are more likely to experience PTSD symptoms (Taft et al., 2012). A study of male veterans suggested that those with PTSD were more likely to experience and perpetrate IPV that results in injury compared with those without PTSD (Teten, Sherman, & Han, 2009). Further, impacts of trauma from military service in combi- nation with subsequent experiences of IPV may increase negative mental health outcomes (Thomas, Haring, McDaniel, Fletcher, & Albright, 2017).
Community-based interventions have shown effectiveness in breaking cycles of family violence, including preventing and stop- ping future occurrences of IPV (Cronholm, Fogarty, Ambuel, & Harrison, 2011). To understand the needs of communities and establish effective community-based interventions, it is important to establish local area estimates of IPV (Cronholm et al., 2011).
In this study, we draw from the subcultural deviance theory (Braithwaite, 1989) to form our primary aim. According to Weisheit and Wells (1996), the subcultural deviance theory
asserts that the effectiveness of sanctions in controlling deviant/ criminal behavior depends on the social networks, attachments, and settings within which the controls are administrated, along with the contextual meaning of the sanctions for offenders as community members. These factors determine whether punishment is disintegra- tive or reintegrative, as well as which form of punishment will be more effective. The sanctioning/control processes that work one way in loosely connected urban settings . . . will work differently in “communitarian” settings . . . as found in many rural communities. (p. 387)
As such, perpetration of IPV may be carried out differently in rural and urban settings; thus, the prevalence of IPV may differ by rural–urban area. Although rurality has been established as a risk factor for IPV, little is known about how sex and SMV status might also contribute to IPV risk within rural areas. As such, the
purpose of this study is to estimate the prevalence of IPV in rural and urban areas by SMV status and sex, to guide the development of geographically targeted services for IPV victimization.
Method
Study Design
To estimate IPV prevalence among SMVs living in rural and urban areas, small area estimation (SAE) using a mixed-effects, multilevel regression approach was carried out. Data for the pre- dictive model calculated in the present study were retrieved from the 2007 Behavioral Risk Factor Surveillance System (BRFSS), which is the most recently administrated survey with publicly available data that contains both IPV victimization experiences and geocodes below the state level. Survey participants who re- sponded in the affirmative to the following question were consid- ered SMVs: “Have you ever served on active duty in the United States Armed Forces, either in the regular military or in a National Guard or military reserve unit (yes or no)?”
The following fixed-effects independent variables were in- cluded in the SAE predictive model: sex (male, code � 0; female, code � 1), age (18–64, code � 0; 65 or older, code � 1), race (White, code � 1; non-White � 0), and SMV status (no � 0, yes � 1). We also included an interaction term in the model for SMV status and sex. Fixed-effects variable categories were se- lected to match U.S. Census Bureau population count categories, explained momentarily. The urban–rural status of a participant’s county of residence—nested within their state of residence—was included as a random-effect covariate in the SAE predictive model to account for contextual effects.
The following questions—which were asked to 18,755 individ- uals living in Hawaii, Nebraska, Virginia, and West Virginia— related to lifetime physical and sexual IPV victimization were used to create a single dependent variable: (a) Has an intimate partner ever threatened you with physical violence? This includes threat- ening to hit, slap, push, kick, or hurt you in any way; (b) Has an intimate partner ever attempted physical violence against you? This includes times when they tried to hit, slap, push, kick, or otherwise hurt you, but they were not able to; (c) Has an intimate partner ever hit, slapped, pushed, kicked, or hurt you in any way? and (d) Have you ever experienced any unwanted sex by a current or former intimate partner? If respondents answered in the affir- mative to any of the aforementioned questions, they were coded as having experienced IPV.
Data Analysis
Demographic data for the study are presented in Table 1. A mixed-effects generalized linear model with a logit link was cal- culated to determine the relationship between IPV victimization and its four covariates (i.e., age, sex, race, and SMV status), as well as a geographically referenced random variance component (i.e., rural–urban status codes nested within states). BRFSS survey weights were used in the analysis to account for the complex sampling design. Beta coefficients from the model were used to calculate the probability of experiencing IPV for each study par- ticipant.
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Linking the Predictive Model With Census Data
To estimate IPV prevalence among SMVs in rural and urban areas, population count data for SMVs and civilians in 2007 were obtained from the U.S. Census Bureau for each state’s rural and urban counties. The data set obtained from the Census Bureau consisted of aggregate population counts for rural and urban areas, stratified by age (18–64 or 65�), sex (male or female), race (White or non-White), and SMV status (no or yes).
The aggregate Census Bureau data were converted into individ- ual demographic profiles based on the independent variables from the mixed-effects generalized linear model. As the data from the Census Bureau were stratified along four dimensions, each cell was converted into the appropriate number of individuals with the four-dimensional profile of the cell. The predicted prevalence rate of IPV for a subgroup within a rural or urban area was calculated by summing the products of the probabilities and population counts and dividing by the population count. We present preva- lence rates in the form of percentage with a 95% CI.
Results
The unadjusted observed prevalence of overall IPV victimiza- tion in the entire BRFSS sample was 16.90%. Our analysis showed that, in the entire BRFSS sample, 13.30% had ever been hit, slapped, pushed, kicked, or hurt by an intimate partner; 11.40% reported that their partner had attempted physical violence against them; 12.20% reported that their partner had threatened physical violence against them; and 5.90% reported that they had experi- enced unwanted sex from a partner. Results of our SAE predictive model for IPV are shown in Table 2. After adjustment for rural– urban area of residence, results showed that women and individ- uals younger than 65 years were less likely to experience IPV than men and individuals 65 years old or older. Furthermore, although the main effect of SMV status was not statistically significant in the model, an interaction term for SMV status and sex was statis- tically significant (B � 0.74, p � .001).
Small area estimates of IPV victimization prevalence among SMVs and civilians are shown in Table 3. The average SAE-based IPV prevalence rate for the entire sample was 13.31%. In general, rural areas had higher IPV prevalence than urban areas. Specifi- cally, female SMVs (rural � 23.54%; urban � 23.34%) had higher IPV victimization rates than women without any military experi- ence (rural � 14.55%; urban � 14.50%), whereas men without
any military experience (rural � 8.06%; urban � 8.02%) had higher IPV victimization rates than male SMVs (rural � 7.21%; urban � 7.17%).
Implications
The primary aim of this study was to determine IPV victimiza- tion prevalence rates among SMVs and civilians in rural and urbans areas by sex. Results of this study showed that IPV vic- timization was slightly higher in rural areas than in urban areas. Furthermore, our results showed that the relationship between SMV status and IPV victimization varied by sex. In particular, whereas female SMVs had higher IPV victimization rates than women without any military experience, men without any military experience had higher IPV victimization rates than male SMVs.
Although our results extend the IPV victimization literature by providing SMV and sex-specific IPV prevalence rates in rural and urban areas, some of our findings are consistent with the literature on IPV. In particular, our results are in agreement with Peek-Asa et al.’s (2011) study of women in Iowa, which showed that IPV prevalence in rural areas was higher than in urban areas (22.50% vs. 15.50%). These findings add to the literature on the subcultural deviance theory, especially as it applies to rural and urban crime victimization (Braithwaite, 1989). Furthermore, Gibbs, Jewkes, Willan, and Washington’s study (2018) showed that IPV victim- ization prevalence was more common among women than among men—a sex-based difference that was observed in this study. Finally, Albright et al.’s (2019) study showed that IPV, as mea- sured by emotional abuse and physical abuse perpetrated by an intimate partner, was more common among military veterans than individuals with no military experience—an outcome that was also observed in this study.
IPV prevention and recovery services for female veterans living in rural areas are needed. Some research has suggested that victim advocacy telephone hotlines for IPV may be one way of helping women initiate recovery from IPV victimization (Miller, Jordan, Levenson, & Silverman, 2010), especially in rural areas given that physical locations for IPV services may be geographically distal (Peek-Asa et al., 2011). Another study—conducted in Alabama— showed that IPV victimization among women was more common
Table 2 Regression Coefficients for Fixed Effects and Variance Components in the Multilevel, Mixed-Effects Generalized Linear Model of IPV Victimization
Variable B SE p value
Female 0.69 0.06 �.001 Aged 65� years �1.35 0.09 �.001 White 0.08 0.06 .17 SMV �0.12 0.09 .16 SMV � Sex 0.74 0.09 �.001 Intercept �2.03 0.06 �.001 Variance component
Observations 18,755 Groups 8 Variance Rural � State 0.01
Note. IPV � intimate partner violence; SMV � service member or veteran.
Table 1 Demographic Characteristics of the Study Sample by Service Member or Veteran Status
SMV (n � 2,872)
Civilian (n � 15,883)
Variable Category n % n %
Sex Male 2,628 91.50 4,688 29.50 Female 244 8.50 11,195 70.50
Age 18–64 1,683 58.60 12,268 77.20 65� 1,189 41.40 3,615 22.80
Race Non-White 740 25.80 4,447 28.00 White 2,132 74.20 11,436 72.00
Note. SMV � service member or veteran.
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3INTIMATE PARTNER VIOLENCE
among those with a history of alcohol abuse (Li et al., 2010). Programs that integrate behavioral health services in primary care settings, such as screening, brief intervention, and referral to treatment programs (Bernstein et al., 2007), should consider ap- pending an IPV victimization screening survey to existing alcohol abuse screening surveys in an effort to identify and treat women with a recent history of IPV victimization.
Some limitations accompanied the analysis of data and inter- pretation of results in this study. First, this study was cross- sectional; thus, we were unable to make causal inferences about the relationship between rurality, SMV status, sex, and IPV vic- timization. Second, given the sensitive nature of the IPV-related survey questions in the BRFSS, it is possible that our estimates underestimate the actual prevalence of IPV. Third, our data were limited to rural and urban areas in four states (i.e., states that elected to include the optional IPV BRFSS module in 2007); thus, we caution against the generalization of the results of this study to the entire United States. Future research should build on the health geography literature being established for the veteran population, specifically (McDaniel & Klesges, 2019; McDaniel, Albright, et al., 2019; McDaniel et al., 2018; McDaniel, Mayer, et al., 2019; Thomas et al., 2019). Fourth, our analysis was limited to data from the 2007 BRFSS data set, which is the most recently released georeferenced (i.e., at the substate level) and publicly available data on IPV victimization among SMVs.
Summary
This study contributes to the relatively small body of literature on IPV perpetrated against SMVs, especially within rural and urban areas of the United States. Our use of SAE assisted in the development of accurate estimates of IPV in substate areas, par- ticularly among SMVs who are at a higher risk for IPV victim- ization. We offer five main programming/future research recom- mendations: (a) increase screening across health-care settings, (b) further develop prevention and outreach efforts, (c) expand ser- vices offered within rural counties, (d) continue to research types of IPV and deepen provider knowledge and ability to address IPV, and (e) support those at risk and/or who have experienced IPV across health-care settings.
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Table 3 Comparisons of Predicted IPV Victimization Rates by SMV Status, Sex, and Rural–Urban Dwelling Status
Military service status
Female Male
Urban Rural Urban Rural
SMV 23.34 [17.48, 30.17] 23.54 [17.33, 30.02] 7.17 [6.00, 8.41] 7.21 [6.03, 8.47] Civilian 14.50 [13.19, 16.34] 14.55 [13.06, 16.37] 8.02 [7.27, 9.02] 8.06 [7.19, 9.08]
Note. IPV � intimate partner violence; SMV � service member or veteran. Predicted IPV victimization rates were obtained via small area estimation.
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Received August 2, 2019 Revision received October 29, 2019
Accepted December 2, 2019 �
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5INTIMATE PARTNER VIOLENCE
