Neighborhood-Level Predictors of Sexual Violence Across Intimate Partner and Non-Intimate Partner Relationships: A Case

Abstract

Ample research explores individual factors associated with sexual violence, yet individual, dyadic, and environmental influences on intimate partner sexual violence (IPSV) occurring in the larger context of non-intimate partner violence (NIPSV) remain relatively unexplored. The current study aimed to determine the extent to which county-level indicators in combination with individual and dyadic factors are associated with sexual violence across relationship types. Reported IPSV and NIPSV cases were obtained from the Tennessee Bureau of Investigation’s (TBI) online incident-based reporting system. County-level variables indicative of neighborhood physical disorder, violent crime, income inequality, firearm prevalence, and community alcohol use patterns were retrieved from the online resource County Health Rankings and Roadmaps. Using a nested case–control design, we determined significant sexual violence risk within younger cohorts and across relationship types, finding three significant county-level factors: 1) income inequality, 2) rate of firearm fatalities, and 3) percentage of female residents. Suggested prevention and intervention efforts include targeting younger age groups for IPSV and NIPSV education, developing resources for a range of relational partners, improving legal access and law enforcement training for reporting, and continued examination of the role of firearms.

Keywords

Intimate partner sexual violence non-intimate partner sexual violence sexual violence intimate partner violence environmental predictors

Sexual violence occurs across settings, contexts, and relational types. This may include sexual abuse or assault in marital or dating relationships, non-romantic acquaintances, and stranger encounters, as well as incidents of poly-victimization (e.g., multiple forms of abuse in one relationship) or involving persons who are too intoxicated or otherwise lack capacity to consent (Dartnall, & Jewkes, 2013). Recent data indicate that current intimate partners are the most common victims of sexual violence (e.g., dating or marital partnership; Smith et al., 2018), followed by non-intimate partners (acquaintance and strangers; Smith et al., 2018), though acquaintance rape is estimated to be 60–80% of all reported sexual assaults (Lopez et al., 2019).

Thus, differences between correlates of intimate partner sexual violence (IPSV; e.g., marital and dating relationships) and non-intimate partner sexual violence (NIPSV; e.g., acquaintance and stranger relationships) merit unique attention, as IPSV shares characteristics of intimate partner violence (IPV) generally, but the ecological and dyadic influences may differ depending on the relationship type, and overlapping features of IPSV and NIPSV remain relatively understudied. In the current study, we intend to explore relationship- and community-level factors to better understand the complexities of sexual violence across relationship types and the implications for effective prevention and intervention practices.

Through a socio-ecological lens, ISPV and NIPSV are associated with varying risks at individual, relationship, community, and societal levels (World Health Organization [WHO], 2012). At the individual level, for example, correlates of sexual violence against women may include social isolation, history of maltreatment, and youthful age. Relationship-level factors like conflict, threat of separation or divorce, and relationship instability may play a role. Community-level factors may include gender and social inequality in the local community, attitudes tolerant of violence toward women, and limited support available for women and families. Societal-level factors like social and cultural norms that glorify violence and promote inequality for women or marginalized groups additionally contribute. Identified within the empirical literature are a range of correlates and predictors associated with IPSV and NIPSV, including those involving survivors and perpetrators at the individual level, those at the relationship or dyadic level, considerations at the contextual or situational level, and finally, those that may influence sexual violence at the community or systems level.

Individual-Level Correlates of IPSV and NIPSV

Specific factors unique to IPSV perpetration compared to general IPV include a history of violence and criminality (Sparks et al., 2020), prior history of maltreatment and mental health problems (Frye et al., 2014; Sparks et al., 2020), lower education, inconsistent employment (Coker et al., 2000; Smith et al., 2002; Sparks et al., 2020), and history of violence in family of origin and current relationships (Coker et al., 2000; Frye et al., 2014; Sparks et al., 2020). Sexual entitlement (Bergen & Bukovec, 2006; Tarzia, 2020), hostility, and difficulties with sexual and self-regulation, (Sparks et al., 2020), and the use of weapons (Krienert & Walsh, 2018) have also been noted as specific factors related to IPSV.

Findings related to the role of drug and alcohol use among perpetrators of IPSV vary. Alcohol use by survivors and/or perpetrators is purportedly associated with at least half of all intimate partner sexual assaults (Abbey, 2002). While regular alcohol and drug abuse among perpetrators of IPSV is sometimes reported as common (Bergen & Bukovec, 2006), others have indicated no strong relationship with IPSV occurrence (Smith et al., 2002), or that only some features of drug and alcohol use may be relevant, such as degree of hazardous drinking (Shorey et al., 2015), influence of dyadic factors (Krienert & Walsh, 2018), or problematic drug versus alcohol use (Sparks et al., 2020). Others have noted that alcohol use may activate or facilitate aggressive and impulsive responding in perpetrators of IPV and IPSV due to its disinhibiting effects (Tharp et al., 2013), perhaps driving inconsistent conclusions regarding the role of alcohol or other drug use in IPSV.

With regard to individual correlates associated with survivors of IPSV, gender is perhaps the strongest, in that women experience IPSV 20–40 times more frequently than do men (Breiding et al., 2015). Other correlates among survivors are similar to those characterizing perpetrators, including history of violence in the home of origin (Frye et al., 2014), prior sexual and violent victimization (Tarzia, 2020), alcohol and drug abuse (Frye et al., 2014), and lower age, income, and educational level (Tarzia, 2020). Further, there are differential risks or correlates associated with different forms of IPSV. For example, women who were sexually assaulted by their partners were more likely to share children with that partner than women who reported non-assaultive but sexually abusive IPSV behaviors (Messing et al., 2014).

There are similarities between the individual correlates of IPSV and NIPSV, but with some exceptions. Younger ages of both perpetrator and survivor may be a strong correlate, as 38% of acquaintance rape victims are 14–17 years old, and the average age of all reported acquaintance rapes in adolescent and college victims is 18.5 years (Lopez et al., 2019). Similarly, the overall lifetime prevalence of rape is lower for men (1 in 71 men vs. 1 in 5 women), yet half of sexual assaults against men involve either acquaintances (52%) or strangers (15.1%), with the majority under the age of 25 (Brecklin, & Ullman, 2010). Those who perpetrate sexual offenses against acquaintances share some characteristics in common with those who perpetrate against intimate partners, including an exaggerated sense of entitlement and lack of guilt, remorse, or empathy (Chancellor, 2012). Also, male perpetrators of intimate partner homicide, sexual-related homicide, and homicide against older women demonstrate similar patterns of serious antisocial and criminal behavior (Dobash & Dobash, 2015).

The most significant difference between NIPSV and IPSV may be the role of alcohol or drugs at the time of the assault. Evidence suggests that the majority of rapes facilitated by alcohol or other drugs are perpetrated by acquaintances (Kilpatrick et al., 2007). Intimate partners often have a sexual history lesser influenced by intoxication, and the use of intoxicants to facilitate partner compliance may be more likely in dating or acquaintance relationships compared to marital relationships (Krienert, & Walsh, 2018).

This confluence of individual-level correlates highlights the overlap between IPSV, NIPSV, and IPV. Features of prior violence and sexually abusive behavior, experiences of victimization and violence within the home of origin, isolation and negative relationship experiences, potential role of alcohol and drug abuse, and other indicators that may suggest difficulties with anger and self-regulatory ability largely characterize individual-level variables associated with sexual violence perpetration. However, these individual variables may be differentially associated with other levels of the system, including dyadic or relationship variables as well.

Relationship or Dyadic-Level Correlates of IPSV and NIPSV

Relationship or dyadic-level factors reflect qualities of the relationship itself or interactions between the partners in a relationship. A number of these factors have been identified, both independently as correlates of IPSV and NIPSV, and also in combination with other, individual-level factors. First, some evidence suggests that those in marital compared to dating and acquaintance relationships are at greater risk of IPSV, as well as increased violence or serious harm. IPSV incidents typically are characterized by more violent penetrative assaults (Krienert & Walsh, 2018) than are those in acquaintance intimate partnerships. Similarly, married couples indicate more aggressive forms of violence (e.g., assault, rape, and homicide), while acquaintances and dating couples are more likely to engage in simple assaults, intimidation, and stalking (Bagwell-Gray et al., 2015).

Characteristics of sexual assault survivors who present to the emergency room mirror these patterns. Victims of abuse from spousal relationships typically present with more severe physical impairments and sexually related, identifiable bruises and lacerations, whereas survivors of violence in dating and acquaintance relationships are more likely to exhibit facial lacerations and non-sexual bodily bruising (Logan et al., 2007). Such findings are consistent with Shotland’s (1985) theoretical perspectives on sexual assault in dating relationships, such that there are differences in the degree of anticipated sexual intimacy in differing stages of the relationship, and dyadic and situational factors play a larger role in more established sexual partnerships.

Further, IPSV can and does occur in isolation, but it often co-occurs with other forms of relationship violence, as 28–68% of women reporting IPV additionally report instances of IPSV, with co-occurring physical and sexual assault commonly noted in women reporting multiple forms of IPV (Smith et al., 2002; Tarzia, 2020). In an examination of perpetrators of IPSV, just over half reported incidents of IPSV, with additional reports of multiple forms of violence in a given relationship (Bergen & Bukovec, 2006). Importantly, survivors of IPSV describe qualitative differences between the experiences of sexual relationship violence and either physical or emotional abuse, more frequently citing humiliation and betrayal of trust associated with sexual assault by a partner and decreased likelihood of reporting IPSV (Easteal & Mc-Ormond-Plummer, 2006). On the other hand, NIPSV typically involves singular cases of sexual violence, but in some early partnerships that are not fully established, such as acquaintances who do not consider themselves as “dating,” survivors also report co-occurring rates of other forms of IPV (World Health Organization, 2013.

Another dyadic factor that appears to characterize incidents of IPSV is a history of problems or discord within the relationship (Sparks et al., 2020), including threats or stalking behaviors (Messing et al., 2014) and co-occurring non-sexual violence (i.e., IPV; Smith et al., 2002; Tarzia, 2020). With regard to specific forms of IPSV, women who share children with their partner are more likely to experience forcible rape as opposed to sexual abuse (e.g., condom nonuse or coerced (but not forced) sexual activity; Messing et al., 2014), though this likely overlaps with findings that married or longer-term partners are more likely to experience penetrative incidents of IPSV. Finally, in one study comparing IPV, IPSV, and NIPSV, it was noted that perpetrators and survivors in IPSV incidents were more similar in age than those involved in NIPSV (Jung et al., 2020).

Community-Level Correlates of IPSV and NIPSV

Despite recognition that community, societal, and cultural influences exist related to the occurrence of IPSV (WHO, 2012), very little empirical evidence exists documenting community-level influences (Breidling et al., 2017; Campbell et al., 2009; LeSeur, 2020; Tarzia, 2020). One examination specific to IPSV found that urban neighborhood-level indicators of IPV and IPSV risk were largely insignificant, though ethnic heterogeneity within the immediate neighborhood reduced the risk of IPSV, while neighborhood-level collective efficacy actually increased the occurrence of IPSV (Frye et al., 2014). Thus, many questions remain regarding the influence of community factors in the perpetration of IPSV. More commonly, research exists describing community-level factors associated with the broader occurrence of IPV. For example, rates of gun ownership and increased rates of IPV within the home have been consistently correlated (Glass et al., 2008). Likewise, community violence is commonly associated with increased rates of IPV (Lauritsen & Shaum, 2004; Jain et al., 2010; Reed et al., 2009; Smith et al., 2018), as are other indicators of neighborhood disadvantage (e.g., poverty and resource deprivation) and social disorganization (Valentine et al., 2019). It is not yet fully understood how these factors related to general IPV may be determinants of IPSV.

Only several studies exist exploring the ecological influences of NIPSV (Pazzani, 2007). Lauritsen and Schaum (2004) identified several factors associated with NIPSV, including living in a central city location, income inequality, and neighborhood violence. The U.S. county level subscription rates to Guns and Ammo were positively associated with acquaintance rape, and both income and age were negatively associated with both stranger and acquaintance rape, but women specifically living in the Southern U.S. were less likely to be assaulted by a stranger. While the ecological influences of acquaintance rape are relatively unexplored, there is a larger body of research examining stranger rape (Greathouse et al., 2015, for a review; Sampson & Lauritsen, 1994). Ceccato, Li, and Haining (2019) indicated several significant neighborhood-level predictors of stranger rape, including city areas with a high concentration of alcohol outlets, residential turnover, burglary and theft, large female residential populations, and endorsement of fear leaving their residence.

Current Study

While individual and dyadic influences of IPSV and NIPSV are relatively well explored, environmental correlates of sexual violence across relationship dyads remain understudied. The purpose of the current study is to determine the extent to which intimate and non-intimate relationships differ and understand which neighborhood-level indicators, in combination with individual and dyadic factors, are associated with IPSV and NIPSV. Variables indicative of neighborhood physical disorder, violent crime, and community alcohol use patterns and individual- and dyadic-level factors, such as survivor age and the type of the relationship at the time of the assault, were used. Our research hypotheses were as follows:

1. Empirical evidence related to IPV, IPSV, and NIPSV has consistently indicated elevated risk among younger individuals, and that more severe forms of sexual violence occur among married partners. We expect similar patterns to emerge in comparison with matched IPV controls.

2. A number of specific variables linked to community factors, including evidence of excessive drinking, alcohol availability, violent crime, gun ownership, and high unemployment, will be more uniquely associated with IPSV and NIPSV than matched incidents of non-sexual IPV.

Method

Sample

Child and adult IPSV, NIPSV, and partner simple assault cases (N = 15,737) were retrieved from the Tennessee Bureau of Investigation’s (TBI) Online Incident Based Reporting System (TIBRS) for purposes of secondary data analysis. Tennessee’s law enforcement department reports crime information from all 95 counties and once reviewed for accuracy by the TBI, data are made available to the public. Data retrieved from the TIBRS were classified by TBI and reporting agencies as “domestic violence,” defined as “violent or aggressive behavior within the home or towards a family member, often involving the violent abuse of a spouse or partner.” For purposes of conducting a nested case–control design, data were separated into cases and controls. Retrieved cases of IPSV and NIPSV included forcible rape, forcible sodomy, forcible fondling, and sexual assault w/an object while the IPV controls included simple assault (see Appendix A for further definitions). The IPV controls accounted for the majority of assaults overall, while forcible rape was the most common sexual assault type within the cases, followed by forcible fondling forcible sodomy and sexual assault w/an object. The majority of the survivors were in acquaintance relationships at the time of the assault followed by dating and spousal relationships. Survivors were White (65.0%; n = 10,354), Black (34.3%; n = 5463), Asian (.6%; n = 91), and American Indian or Alaska Native (0%; n = 6) (see Table 1).

Table 1.

Assault Types by Age Range and Relationship Type, N = 15,737.

	Forcible Rape	Forcible Sodomy	Forcible Fondling	Sexual Assault W/Object	Simple Assault
Age range
<18	335 (23.7%)	87 (36.9%)	284 (29.5%)	36 (26.5%)	3350 (25.4%)
18–24	421 (29.8%)	55 (23.3%)	192 (19.9%)	23 (16.9%)	3416 (25.9%)
25–34	279 (19.7%)	35 (14.8%)	191 (19.8%)	35 (25.7%)	2671 (20.3%)
35–44	211 (14.9%)	30 (12.7%)	129 (13.4%)	23 16.9%)	1941 (14.7%)
45–54	118 (8.4%)	18 (7.65)	89 (9.2%)	11 (8.1%)	1110 (8.4%)
55–64	38 (2.7%)	6 (2.5%)	61 (6.3%)	5 (3.7%)	537 (4.1%)
Relationship type
Acquaintance	804 (12.7%)	148 (2.3%)	617 (9.7%)	79 (1.2%)	4701 (36.6%)
Dating	244 (3.8%)	18 (0.3%)	57 (0.9%)	22 (0.3%)	6047 (94.7%)
Spousal	89 (5.95)	10 (0.7%)	32 (2.1%)	6 (0.4%)	1366 (10.6%)
Stranger	264 (20.2%)	48 (3.75)	233 (17.85)	23 (1.8%)	740 (5.8%)

In 2018, Tennessee’s overall crime rate was 651.5 incidents per 100,000 persons, well above the national rate of 394 per 100,000 (TBI, 2019). Specifically, there were 498 (7.4 per 100,000) reported homicides, 2821 forcible rapes (41.7 per 100,000), and 31,717 cases of aggravated assault (468.5 per 100,000). Of those, 20% of the total homicides (n = 98), 24% of the forcible rapes (n = 668), and 35% of the aggravated assaults (n = 10,985) were reported as IPV related incidents (TBI, 2019). Both controls (57.5%; n = 7584) and cases (56.6%; n = 1552) originated from counties that were predominantly urban (i.e., with only 3–11% of the county area designated as rural). A large majority of both controls (43.5%; n = 5733) and cases (42.9%; n = 1177) were living in areas with high rates of violent crime, while both the cases and controls resided predominantly in areas with non-excessive drinking (56.9%; n = 4209) (see Table 2 for more information pertaining the ecological variables).

Table 2.

Correlations Between Ecological Predictors and Dyadic Variables.

	Alcohol Outlet	Euclidian	Excessive Drinking	Unem-Ployment	Income Inequality	Violent Crime	Firearm Fatalities	% Female	% Rural	Firearm Permits	IPSV	Simple Assault	Relationship Type
Alcohol outlet
Euclidian	.99*
Excessive drinking	−.32*	−.34*
Unemployment	.28*	.31*	−.83*
Income	−.38*	−.36*	−.56*	.53*
Violent crime	−.72*	−.70*	−.08*	.13*	.64*
Firearm fatalities	−.69*	−.67*	−.19*	.24*	.72*	.94*
% female	−.62*	−.60*	−.28*	.15*	.68*	.75*	.75*
% rural	.93*	.93*	−.26*	.28*	−.41*	−.71*	−.71*	−.63*
Firearm permits	.81*	.81*	−.52*	.39*	−.22*	−.73*	−.62*	−.46*	.80*
IPSV	−.00	.00	.00	.00	−.00	.01	.01	.01	.00	−.00
Simple assault	−.01	−.01	.01	−.01	−.00	.00	.01	.00	−.01	−.00	−.64*
Relationship type	−.08*	−.08*	−.10*	.07*	.14*	.14*	.15*	.16*	−.11*	−.06*	.18*	−.25*
Age	.00	−.00	.03*	−.03*	−.01	−.02*	−.02*	−.03*	−.00	−.00	.01	.00	−.44*
Mean	−	2.09	.80	−.73	.36	2.00	464.47	51.59	20.10	.08	−	−	−
SD	−	1.26	1.55	.84	1.12	1.99	422.28	.76	22.42	.02	−	−	−

Note. *p < .05.

Procedures

Dependent Variables (Cases)

The categorical dependent variables retrieved from the TBI crime dataset included four types of sexual violence (i.e., forcible rape, sexual assault with an object, forcible fondling, and forcible sodomy), with reports of simple assault used for matched IPV controls (see Appendix A for further information).

Independent Variables

Within the same TBI dataset, categorical independent variables included age range, (under 18, 18–24, 25–34, 35–44, 45–54, 55–64, and 65 and over), gender, race, Tennessee county (n = 95), and the type of relationship the perpetrator and victim were in at the time of the assault: IPSV included boyfriend/girlfriend; ex-boyfriend/girlfriend, spouse, ex-spouse, common-law spouse, and NIPSV included stranger, acquaintance, friend, employee, employer, or neighbor. It is important to note that these designations were made by TBI or reporting law enforcement agencies.

Additional continuous independent predictor variables were predominantly retrieved from the County Health Rankings and Roadmaps System (Stöckl et al., 2014), firearm information from the Department of Safety and Homeland Security (2019), and alcohol outlet density retrieved from other scholars (Lu et al., 2018). These variables included the following county-level information: alcohol outlet density, approximate Euclidian distance (i.e., similar measure to alcohol outlet density), excessive drinking, unemployment, income inequality, violent crime, rate of firearm fatalities, firearm permits per county, percentage female residents, and percentage rurality (see Appendix A for variable definitions and Table 2 for descriptive statistics related to county-level variables).

Using a nested case–control design, we matched cases of the four types of either IPSV or NIPSV (n = 2749), including forcible rape (n = 1413), forcible sodomy (n = 236), forcible fondling (n = 964), and sexual assault with an object (n = 136), to IPV simple assault controls (n = 13,179). Each case of sexual violence was matched to five control cases, matched at random on county, gender, age, and race. For sexual violence cases that had no remaining simple assault case matches, they were matched to cases in similar counties based on the County Health Rankings and Roadmaps System Ranking Information (2019). This system ranks counties on overall health outcomes, length of life, quality of life, health behaviors, clinical care, social and economic factors, and the physical environment. Each sexual violence category demonstrated adequate match rates: forcible rape (90.0%), sexual assault with an object (75.9%), forcible sodomy (89.1%), and forcible fondling (62.3%), with a total overall match rate of 77.6%. The lowest match rate was found for White females under the age of 18 across all counties. Sexual violence cases without matched controls were excluded from further analysis.

Analytic Plan

Data were cleaned using KuKu Tools for Excel Version 3.04. All analyses were conducted using SPSS Version 26. Data were first recoded due to unequal sample sizes within the age range and relationship type variables. Relationship types were recoded into four groups (1 = Spousal; 2 = Dating; 3 = Stranger; 4 = Acquaintance) and all age ranges above 64 were removed. Point-biserial correlations (bivariate correlations) were calculated to determine the strength of the associations between all continuous-level variables and the IPSV and non-IPSV binary variables (see Table 2). Regarding Hypothesis 1, multiple Chi Square analyses were performed and effect sizes calculated (Cramer’s V; Table 3). Subsequently, a series of binary logistic regressions further explored age and relationship type for all four types of sexual violence (Table 4). For Hypothesis 2, the differences in sexual violence exposure prevalence between matched sets with the addition of the continuous neighborhood-level predictor variables were estimated using the backward stepwise logistic regression procedure to calculate odds ratios (ORs) and their 95% confidence intervals (Table 5).

Table 3.

Pearson’s Chi Square and Cramer’s V of Sexual Assaults, Age Range, and Relationship.

	Pearson’s Chi Square	Cramer’s V	Sig.
Forcible rape
Spousal	7.48	.03	.006
BF/GF	573.15	.26	<.001*
Stranger	397.72	.22	<.001*
Acquaintance	250.76	.17	<.001*
Under 18	.63	.01	.426
18–24	.13	.00	.715
25–34	.05	.00	.819
35–44	.14	.00	.705
44–55	.01	.00	.919
55–64	.04	.00	.836
Forcible sodomy
Spousal	13.87	.10	<.001*
BF/GF	45.91	.19	<.001*
Stranger	1.66	.04	.197
Acquaintance	54.76	.21	<.001*
Under 18	.21	.01	.645
18–24	.03	.01	.867
25–34	.10	.01	.758
35–44	.06	.01	.803
44–55	.26	.01	.608
55–64	.21	.01	.644
Forcible fondling
Spousal	50.46	.01	<.001*
BF/GF	436.58	.28	<.001*
Stranger	418.82	.28	<.001*
Acquaintance	175.52	.18	<.001*
Under 18	1.76	.02	.185
18–24	.46	.01	.500
25–34	.29	.01	.590
35–44	.04	.00	.842
44–55	.09	.00	.761
55–64	.25	.01	.617
Sexual assault W/an object
Spousal	6.76	.01	.009
BF/GF	30.99	.21	<.001*
Stranger	9.08	−.11	.003
Acquaintance	27.50	.11	<.001*
Under 18	.68	.03	.409
18–24	.10	.01	.750
25–34	.10	.01	.758
35–44	.08	.01	.784
44–55	.05	.01	.832
55–64	.05	.01	.819

Note. * Sig at p <.05.

Table 4.

Logistic Regression of Sexual Assault Types, Age Range, and Relationship Type.

Forcible Rape	B	Se	Wald	Sig.	Exp(B)	95% CI
Age range
<18	.53	.20	7.19	.007*	1.703	[1.154–2.513]
18–24	−.16	.10	2.67	.102*	.851	[.701–1.033]
25–34	−.16	.07	5.91	.015*	.849	[.744–.969]
35–44	−.16	.05	9.37	.002*	854	[.771–.945]
45–54	−.13	.04	8.92	.002*	.854	[.771–.945]
55–64	−.09	.03	7.91	.007*	.915	[.858–.976]
Relationship type
Spousal	2.40	.22	122.33	<.001*	10.982	[7.182–16.791]
Dating	3.15	.20	243.43	<.001*	23.387	[15.740–34.750]
Stranger	.19	.21	.86	.353	1.210	[.809–1.811]
Acquaintance	1.09	.19	32.80	<.001*	2.962	[2.043–4.296]
Forcible sodomy
Age range
<18	.38	.49	.60	.438	1.459	[.561–3.9793]
18–24	−.00	.25	.00	.994	.998	[.612–1.627]
25–34	−.28	.17	2.56	.109	.758	[.540–1.064]
35–44	−.16	.13	1.46	.226	.854	[.661–1.103]
45–54	−2.13	.11	3.49	.062	.808	[.646–1.010]
55–64	−.06	.08	.60	.438	.939	[.801–1.101]
Relationship type
Spousal	3.21	.57	32.38	<.001*	24.839	[8.214–75.110]
Dating	3.50	.54	41.55	<.001*	33.179	[11.440–96.228]
Stranger	1.48	.51	8.45	.004*	4.376	[1.617–11.840]
Acquaintance	.98	.47	4.27	.039*	2.650	[1.051–6.682]
Forcible fondling
Age range
<18	.47	.17	7.67	.006*	1.605	[1.148–2.243]
18–24	−.15	.09	2.60	.107	.864	[.724–1.032]
25–34	−.08	.06	1.72	.190	.924	[.821–1.040]
35–44	−.24	.05	22.88	<.001*	.789	[.715–.869]
45–54	−.13	.04	9.34	.002*	.881	[.812–.956]
55–64	−.08	.03	7.67	.006*	.924	[.874–.977]
Relationship
Spousal	3.16	.23	194.40	<.001*	23.594	[15.130–36.793]
Dating	4.01	.21	361.90	<.001*	54.908	[36–342-82.959]
Stranger	.19	.18	1.12	.290	1.209	[.851–1.718]
Acquaintance	1.04	.16	43.40	<.001*	2.840	[2.082–3.874]
Sexual Assault W/an object
Age range
<18	−.07	.55	.02	.901	.934	[.320–2.724]
18–24	.03	.30	.01	.924	1.028	[.585–1.806]
25–34	−.10	.18	.29	.589	.906	[.633–1.296]
35–44	−.18	.14	1.55	.213	.837	[.632–1.107]
45–54	−.15	.13	1.45	.229	.859	[.671–1.100]
55–64	.011	.09	.02	.901	1.011	[.846–1.209]
Relationship
Spousal	3.01	.67	20.29	<.001*	20.186	[5.460–74.633]
Dating	2.85	.55	25.52	<.001*	17.305	[5.725–52.314]
Stranger	.86	.57	2.27	.132	2.363	[.773–7.225]
Acquaintance	1.22	.52	5.56	.018*	3.376	[1.228–9.279]

Note. * Sig at p <.05.

Table 5.

Backward Stepwise Regression Analyses of IPSV Cases, Relationship Type, and Neighborhood-Level Predictors.

	B	SE	Wald	Sig.	Exp(B)	95% CI
Forcible rape
Spousal	.83	.12	46.61	<.001	2.300	[1.811–2.921]
Dating	1.76	.08	481.91	<.001	5.830	[4.981–6.823]
Stranger	−1.14	.10	140.17	<.001	.320	[.265–.387]
Acquaintance	−1.81	.39	21.09	<.001	.164	[.076–.354]
Excessive drinking	−.14	.03	17.93	<.001	.874	[.821–.930]
Income inequality	−.11	.05	4.87	.027	.893	[.808–.987]
Firearm fatalities	.00	.00	14.98	.001	1.001	[1.000–1.001]
Rurality	.−.01	.00	5.76	.016	.994	[.990–.999]
Forcible sodomy
Stranger	−1.47	.25	34.76	<.001	.230	[.141–.375]
Acquaintance	−1.69	.21	63.66	<.001	.185	[.122–.280]
Percentage female	.05	.00	212.72	<.001	1.055	[1.048–1.063]
Forcible fondling
Spousal	1.73	.18	95.65	<.001	5.639	[3.987–7.976]
Dating	2.49	.14	301.00	<.001	12.093	[9.125–16.027]
Stranger	−1.34	.11	151.18	<.001	.262	[.211–.324]
Excessive drinking	−.15	.05	9.83	.002	.862	[.785–.946]
Unemployment	−.21	.08	7.17	.007	.815	[.701–.946]
Firearm permits	−13.18	2.00	43.72	<.001	.002	[.005.−.112]
Sexual assault W/an object
Stranger	−1.69	.32	27.92	<.001	.184	[.098–.345]
Acquaintance	−1.70	.25	45.58	<.001	.183	[.112–.300]
Income inequality	.21	.09	4.90	.027	1.231	[1.024–1.480]
Percentage female	.05	.00	157.53	<.001	1.052	[1.043–1.060]

Note. Significant variables (p <.05) included from the final iteration of the backward stepwise regression model.

Results

To ascertain significant differences between offense type (i.e., forcible rape, forcible fondling, forcible sodomy, and sexual assault w/an object), age range, and relationship types, we conducted multiple Pearson chi-square analyses and evaluated the associated Cramer’s V effect sizes (Cohen, 1983). There was not a statistically significant association between offense types and age range, but all relationship types demonstrated a significant association with the four sexual violence categories. Boyfriend/girlfriend relationships repeatedly demonstrated the largest effect sizes for each sexual offense (see Table 3 for further information).

Four binary logistic regression models were used to examine the associations between relationship type and age range on the four sexual violence categories (Table 4). Dating, spousal relationships, and those under 18 demonstrated the highest odds ratio’s for each assault category, with risk decreasing with age.

A binary logistic regression model examining the association between relationship type and age range on forcible rape cases versus IPV controls was significant, χ² (9, N = 8289) = 4944.793, p < .001, Nagelkerke’s R² = .599. All relationships besides stranger were significant. Those in dating, spousal, and acquaintance relationships experienced a greater likelihood of partner forcible rape than simple assault, with the highest likelihood observed in dating relationships. Those under 18 demonstrated a higher likelihood of forcible rape compared to simple assault, while those above 18 demonstrated a decreased likelihood.

The regression model examining forcible sodomy cases in the context of relationship type and age range was significant, χ² (9, N =1299) = 725.726, p < .001, Nagelkerke’s R² = .571. Dating and spousal relationships demonstrated the highest likelihood of experiencing forcible sodomy compared to simple assault, but no age ranges were significantly more likely to experience this type of sexual assault.

The regression model examining forcible fondling was also significant, χ² (9, N =5501) = 3548.400, p < .001, Nagelkerke’s R² = .634. All relationships types were significantly more likely to experience forcible sodomy compared to simple assault, with dating relationships and those under the age of 18 demonstrating the highest likelihood.

With regard to sexual assaults with an object, the resulting regression model was significant, χ² (9, N =723) = 374.521, p < .001, Nagelkerke’s R² = .539. All relationships were significant, with survivors in spousal and dating relationships the most likely to experience sexual assault with an object compared to simple assault. Age ranges were not significant.

A combination of dyadic risk factors in conjunction with neighborhood-level factors predicted elevated IPSV risk. Separate models were analyzed for each form of sexual assault (see Table 5 for further details on each analysis).

A binary logistic regression model examining the association between relationship type and community-level predictors on forcible rape cases versus controls was significant, χ² (7, N = 8351) = 904.630, p < .001, McFadden R² = .103, Nagelkerke’s R² = .172. Relationship type did significantly vary, as those in spousal and dating relationships experienced a greater likelihood of intimate partner forcible rape than simple assault. Several ecological factors were significantly associated with a decreased likelihood of experiencing forcible rape in comparison with simple assault, including excessive drinking, income inequality, and rurality. In contrast, the rate of firearm fatalities increased the odds of forcible rape when compared with matched controls.

The regression model examining forcible sodomy cases in the context of relationship type and community predictors was significant, χ² (15, N =1329) = 703.129, p < .001, McFadden R² =.411, Nagelkerke’s R²= .548. Those in either stranger or acquaintance partnerships were less likely to experience forcible sodomy than simple assault. Of neighborhood-level predictors, only the percentage of women in a given county was significant.

The regression model examining forcible fondling was significant, χ² (6, N =5590) =908.971, p < .001, McFadden R² = .150, Nagelkerke’s R² = .250. Three dyadic relationship variables were significant in the final model. An increased likelihood of forcible sodomy was associated with spousal and dating relationships, whereas decreased likelihood was associated with stranger partnerships. Of community-level predictors, excessive drinking, unemployment, and rate of firearm permits were significant but indicated a lower likelihood of experiencing forcible fondling as compared to simple intimate partner assault.

With regard to sexual assaults with an object, the resulting regression model was significant, χ² (3, N =738) = 59.013, p < .001, McFadden R²²= .084, Nagelkerke’s R² = .136. Both stranger and acquaintance intimate relationships were significant in the final model, with survivors in these relationship types less likely to experience sexual assault with an object than simple assault. Income inequality and percentage of women in the county increased the likelihood of experiencing this assault type.

Discussion

The current study aimed to replicate previous findings that younger cohorts demonstrate the highest rates of sexual violence, to explore the differences between relationship type (IPSV and NIPSV), and to evaluate the association with community-level factors. Drawing on data from a large sample of reported incidents of sexual assault, we determined significant sexual violence prevalence within younger cohorts, but surprising findings regarding relationship type and community-level factors emerged.

Consistent with previous literature (Black et al., 2011; Tarzia, 2020) the majority who experienced sexual violence were under the age of 24. This may be because younger couples evidence greater sexual violence risk, including engaging in related risk behaviors (e.g., substance abuse, criminal activity, and early pregnancies), troubled peer and parental relationships, poor educational outcomes, and childhood violence exposure (National Institute of Justice, 2018). Additionally, general and sexual violence perpetration tends to decrease over time (Farrington, 2017; Hanson et al., 2018).

Lower rates of sexual violence in older cohorts may also reflect limited reporting of sexual victimization. Sexual violence remains the most underreported of all violent crimes (Carbone-Lopez et al., 2016) and is more so in the context of IPSV (Martin et al., 2007). Older individuals experience IPSV at similar rates to younger cohorts but report less often (Bows, 2018; Nobels et al., 2020) due to fear of reprisal, high investment in the partnership, elderly health barriers, and lack of confidence in the criminal justice system (Taylor & Gassner, 2010).

Similarly, our findings highlight an important distinction between age and forms of sexual violence. While forcible rape was mainly reported by those over 18, other forms of sexual assault occurred in younger cohorts. Forcible rape is more likely in marital relationships (Krienert & Walsh, 2018), which could explain age effects, and other forms of sexual violence may be attributable to teen-dating assaults or sexual offenses against children in the home. Prior research has demonstrated similar patterns in which minors represented the majority of victims of forcible fondling, forcible sodomy, and sexual assault with an object, while fewer than half were victims of forcible rape (Snyder, 2000). These rates in youth under 18 may reflect actual differences in victimization, though it may also reflect the influence of mandatory reporting of sexual crimes against children and barriers to reporting for adult survivors (e.g., Rape, Abuse, and Incest National Network [RAINN], 2016).

Those in marital relationships are consistently at the highest risk for IPSV (Krienert, & Walsh, 2018; Tarzia, 2020), but some have also identified significant risk in dating relationships (Bhochhibhoya et al., 2019; Wegner et al., 2014). The current analyses confirmed that both spousal and dating relationships accounted for significant IPSV risk, but spousal risk was less than expected. This may be attributable to spousal reporting barriers including enhanced intimacy, fear of violent reprisal, financial concerns or fear of blame or judgment by the police (Johnson, 2017; Tingley, 2018). Additionally, higher reported cases within dating relationships may be explained by their youthful age which, as previously noted, significantly increases risk for IPSV.

Other relationship types also demonstrated significant risk of sexual violence. The majority of total NIPSV incidents occurred within acquaintance relationships, indicating that sexual violence does not only occur within the context of longer-term partners. These findings are consistent with previous research indicating that sexual assaults are most commonly perpetrated by acquaintances (Truman & Langton, 2015). Partners who have experienced sexual assaults are more likely to report when committed by those less known to them (Wolitzky-Taylor et al., 2011), suggesting that the further the relational distance between survivor and perpetrator, the more likely they are to report (Felson & Pare, 2005).

High rates of documented NIPSV may also be explained by the improper classification of relationship type when the original police report was filed. It is unclear how the survivor was asked about relationship status or if law enforcement responders assess this themselves. For the small percentage of cases that are reported, police use their discretion to determine how each case will be classified for possible investigation (Johnson, 2017). Existing stereotypes regarding IPV incidents may shape law enforcement agents’ decision-making.

With regard to community-level factors, we hypothesized that multiple variables would influence rates of IPSV and NIPSV, but here only three significant county-level factors emerged: 1) income inequality, 2) rate of firearm fatalities, and 3) percentage of female residents. Consistent with the current findings, income inequality, low socioeconomic status (SES), and lack of employment are all associated with higher levels of sexual assault (Breidling et al., 2017). The National Crime Victimization Survey (Warnken, & Lauritsen, 2019) indicates that survivors with a household income below federal poverty level were 12 times more likely to experience sexual assault. In addition to income inequality, individuals may face increased risk in areas with high rates of firearm fatalities. Both the presence of a firearm in the home and community-level firearm fatalities influence rates of sexual assault (Hudak et al., 2020). This may indicate community social disorganization (Konkel et al., 2019), where neighborhood cohesion and informal social control are disrupted and increase the likelihood of sexual and violent crime. In areas with high rates of firearm fatalities, firearms may be more accessible and used as forms of intimidation or control in IPSV incidents (Sorenson & Wiebe, 2004). While relatively unexplored, fewer women within a given community may influence rates of sexual victimization. Cross-cultural research indicates that uneven sex ratios within a population may be associated with social instability, higher rates of IPV, increased violent competition, and self-reported male sexual assault against women (Diamond-Smith & Rudolph, 2018; Hesketh, 2011). More research is needed to understand this variable in the context of IPSV and NIPSV in the U.S.

Recommendations for Prevention and Intervention

Here, those at highest risk of IPSV and NIPSV were younger, including persons not yet 18. Current prevention efforts primarily engage college-aged individuals (Laughon et al., 2020), and IPSV and NIPSV is typically subsumed under broader IPV or sexual violence education. Additional interventions that aim to prevent or reduce IPSV among youth aged 12–24 years may include early intervention programs across settings (i.e., the home, middle schools, high schools, and college campuses) that describe the characteristics of healthy partnerships and warning signs and consequences. For those particularly at risk for gender-based violence, engaging influential adults and peers may mitigate problematic behavior. This includes appointing men and boys as allies in prevention (e.g., boys in athletic teams to promote healthy social norms) and promoting family-based programs involving caregivers to enhance awareness of risks and signs of IPSV (National Coalition Against Domestic Violence, 2015). Additional strategies may include disseminating information in middle and secondary school settings that include resources for anonymous reporting for those who may be facing IPSV or NIPSV.

Further, many current interventions focus on individuals who are already in abusive relationships and are tailored to IPSV (e.g., dating/spousal relationships; Okasako-Schmucker et al., 2019). These interventions include removing the survivor from the violent situation, providing financial resources, enhancing social support (e.g., provision of an advocate), providing alternative housing, and addressing safety measures. While these practices may be necessary for those in established relationships, others may require different resources. Those in NIPSV relationships may desire assistance securing a protective order, guidance for informing family members, and information on how to report the abuse while protecting the survivor from retaliation. This may not only aid intervention efforts but also improve reporting rates for NIPSV and increase the reach of available services (Freed et al., 2017).

A related concern for intervention is the low reporting rate of IPSV. Survivors may not report due to the feeling that the assault is a personal matter, a desire to protect the offender, believing the crime was minor or unimportant, fear of reprisal, or doubt in the efficacy of responding law enforcement agents (Johnson, 2017). The New York State Office for the Prevention of Domestic Violence (2020) initiated an anonymous reporting system not involving legal personnel that instead appoints an advocate to communicate with the survivor. The survivor may feel safer speaking with this advocate instead of calling law enforcement to their home and facing possible retaliation from their partner.

Also, since it remains unclear as to how relationship type is classified upon reporting an IPSV or NIPSV incident, law enforcement may benefit from additional training pertaining to proper screening for previous abuse (e.g., type of force involved, presence of a firearm) and the length of time spent in the relationship. Furthermore, training in and consistent use of structured risk assessments such as The Lethality Assessment Program (LAP) and the Domestic Violence High-Risk Team (DVHRT) mode (Messing et al., 2020) can potentially identify repeat offenders at the time of police contact. Through a clearer understanding of risks at the time a report is filed, resources can be allocated more appropriately. Other reform policies include instilling procedural justice (e.g., compassionate responses), proper classification and assessment of the report, and additional training pertaining to the nuances of IPV, IPSV, and NIPSV (Johnson, 2017).

Regarding the surrounding environment, income inequality and firearm ownership may be two of the most important community level-factors pertinent to sexual violence. It is well documented that those born into low SES are more likely to witness partner violence and experience abuse themselves later (National Institute of Justice, 2018). Breaking this generational cycle may prove difficult, but some programs do provide survivors with financial resources if they seek to leave the abusive relationship and need assistance (e.g., Crime Victim Compensation, RAINN, 2016).

Certain factors such as IPV myths, poverty, low SES, and unemployment may lead to biased reporting. To begin, IPV myths such as victim blaming (e.g., the victim should simply leave the abusive relationship), hysterical victims (i.e., victim noncooperation; Twis et al., 2018), and impoverished areas demonstrating a “culture of violence” (i.e., those living in these areas are less deserving of help; are known to influence law enforcement decision making. This includes officer frustration when returning to a previous IPV call, minimizing the severity of abuse, not utilizing formalized risk assessment tools (Ballucci et al., 2017), and providing fewer services (Twis et al., 2018).

Law enforcement response to IPV may be similar regardless of a survivor’s background characteristics, but some studies indicate differential response to IPV based on socioeconomic status, racial, and/or immigrant status (Robinson & Chandek 2000). While this is bidirectionally related to help-seeking behaviors (Waller et al., 2021), law enforcement may be less responsive to IPV calls in impoverished areas (Gezinski, 2020). They may demonstrate reluctance to attend to calls in high-violence areas due to safety concerns and may face limited departmental staffing in economically disadvantaged communities (Grotpeter et al., 2009). Practitioners and researchers can utilize these data to be better prepared to identify sexual violence across relationship types and offer services for those across a range of socioeconomic strata. Specifically, when IPV advocates accompany law enforcement when making arrests, survivors are more likely to characterize the interaction positively, feel more empowered, report feeling more in control, and ultimately view the intervention as more effective, regardless of their socioeconomic characteristics (Caettano, 2010). Additionally, ubiquitous risk assessment and consultation in primary care settings may target disadvantaged individuals and mitigate the progression of sexual violence.

Regarding firearms, several U.S. federal and state policies have attempted to reduce the negative impacts of firearms on IPV (Goodyear et al., 2019) but do not always include IPSV and NIPSV within their legislation. In Tennessee, where these data were derived, firearm restrictions are especially lenient and do not require firearm registration, limit the number of firearms owned, or allow local governments to regulate firearms associated with higher assault and murder rates (CDC, 2019). While ample research documents increased rates of IPV when a firearm is present, it remains unclear how a firearm is used within the context of sexual violence, and this represents a clear need for empirical study. Additional community-level research is needed to understand why higher firearm fatalities are related to increased occurrences of IPSV and NIPSV.

Limitations

The current study is not without limitations. Due to the nature of using secondary data, we were unable to determine the temporal length of the relationships, past relationship status, frequency of sexual violence within the relationships, and person-level historical factors (e.g., substance abuse history, employment status, and education). These details would have enhanced our understanding of the associations between age cohort, relationship type, and the types of IPSV and NIPSV. Moreover, in incidents involving those under 18, it remains unclear if these assaults were acts perpetrated by family members, sexual assaults against children, or reports of teen dating violence. Ideally, actual law enforcement records would provide clarity in these cases. Several studies indicate that archival data recorded by government agencies, like police officers or frontline workers, are characterized by inaccuracies (Bonomi et al., 2014; Tewksbury 2002). It is possible that officers did not consistently record information when responding to partner calls and may have underestimated the nature of the violence when receiving the call. Additionally, due to the low rates of IPSV and NIPSV assaults reportedly involving LGBTQ partners, we were unable to draw conclusions specific to this population.

Several of the sexual assault variables had relatively small sample sizes and were highly correlated, limiting statistical inferences due to Hessian matrix abnormalities. This was remedied by collapsing categories into fewer groups, and using a nested case–control design, but a larger sample size would have improved these irregularities. Moreover, a large proportion of the reported assaults came from large, metropolitan counties, and controlling for population size may have illustrated additional findings from smaller, rural communities.

Conclusions

Sexual violence occurs across a range of relationship types and age ranges, and significant deleterious effects for survivors are well-documented. We confirmed that younger individuals were more likely to experience IPSV and NIPSV, but also highlighted an important distinction between age range and risk of various forms of sexual violence. While IPSV was relatively common, non-married partners, especially acquaintances, demonstrated higher rates of NIPSV than expected, while spousal relationships demonstrated less than hypothesized. These findings indicate that intervention and prevention efforts should be tailored toward all relationship types, not just those with close relational distance patterns. Additionally, environmental factors like income inequality and the presence of firearms were significant factors that influenced sexual violence. Prevention and intervention efforts should target younger age groups, provide resources to all partners regardless of their relational distance, improve legal access and law enforcement training, and continue to examine the role of firearms in IPSV and NIPSV.

Footnotes

Acknowledgments

The authors take responsibility for the integrity of the data, the accuracy of the data analyses, and have made every effort to avoid inflating statistically significant results.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Valérie Savoie

Appendix

Variable	From:
IPSV/Simple assault	TIBRS	“Violent or aggressive behavior within the home or towards a family member, often involving the violent abuse of a spouse or partner.”
Forcible rape (§39-13-503)	TIBRS	Unlawful sexual penetration in any of the following circumstances: a) Force or coercion is used to accomplish the act; b) sexual penetration is accomplished without the consent of the victim; and c) the perpetrator knows or has reason to know at the time of the penetration that the victim did not consent.
Forcible Sodomy (§39-13-501(6))	TIBRS	Sexual intercourse, cunnilingus, fellatio, anal intercourse, or any other intrusion, however slight, of any part of a person’s body or of any object into the genital or anal openings of the victim’s, the perpetrator’s, or any other person’s body.
Forcible fondling (§ 39-13-501-39-13-511)	TIBRS	Touching of the private body parts of another person for the purpose of sexual gratification, forcibly and/or against that person’s will. It may also occur without force or against that person’s will where the victim is incapable of giving consent.
Sexual assault W/an object (§39-13-501(6))	TIBRS	To use an object or instrument to unlawfully penetrate, however slightly, the genital or anal opening of the body of another person, without the consent of the victim. Includes instances where the victim is incapable of giving consent because of his/her age or because of his/her temporary or permanent mental or physical incapacity.
Simple assault (IPV Controls)	TIBRS	The TBI dataset categorized only simple assaults that occurred as a domestic violence altercation. Simple assaults that were not classified as domestic violence were not included.
Simple assault (IPV Controls)	TIBRS	An unlawful physical attack by one person upon another where neither the offender has a weapon, nor the victim suffers obvious severe or aggravated bodily injury involving apparent broken bones, loss of teeth, possible internal injury, severe laceration, or loss of consciousness.
Alcohol outlet density	CHRRS	The number of physical locations in which alcoholic beverages are available for purchase per county area.
Euclidian distance	Lu, Zhang, Holt, Kanny, and Croft, (2013)	The county level population weighted distance (PWD) from on-premise alcohol outlets which is a similar measure to alcohol outlet density.
Excessive drinking	CHRRS	The percentage of a county’s adult population that reports binge or heavy drinking.
Unemployment	CHRRS	The percentage of the county’s civilian labor force, ages 16 and older, that is unemployed but seeking work.
Income inequality	CHRRS	The ratio of household income at the 80th percentile to that at the 20th percentile, i.e., when the incomes of all households in a county are listed from highest to lowest, the 80th percentile is the level of income at which only 20% of households have higher incomes, and the 20th percentile is the level of income at which only 20% of households have lower incomes. A higher inequality ratio indicates greater division between the top and bottom ends of the income spectrum.
Violent crime	CHRRS	The number of violent crimes reported per 100,000 population. Rates measure the number of events (i.e., deaths, births, etc.) in a given time period (generally one or more years) divided by the average number of people at risk during that period.
Firearm permits	Department of Safety and Homeland Security (2019)	Number of handgun permits per county and then divided by population per county to determine county rate.
Firearm fatalities	CHRRS	The number of deaths due to firearms in a county per 100,000 population.
% female	CHRRS	Percent of the county population that is female.
% rural	CHRRS	Percent of the county population that resides within a rural area.

Note. Assault category definitions derived from Tennessee statues (Tennessee Bureau of Investigation, 2019) and definitions provided by the TIBRS. CHRRS = County Health Rankings and Roadmaps System. TIBRS: Tennessee’s Online Incident Based Reporting System.

References

Abbey

. (2002). Alcohol-related sexual assault: A common problem among college students. Journal of Studies on Alcohol and Addiction, 14, 118–128. https://doi.org/fpj9

Bagwell-Gray

M. E.

Messing

J. T.

Baldwin-White

(2015). Intimate partner sexual violence: A review of terms, definitions, and prevalence. Trauma, Violence & Abuse, 16(3), 316–335. https://doi.org/f7gqmc

Ballucci

Gill

Campbell

M. A.

(2017). The power of attitude: The role of police culture and receptivity of risk assessment tools in IPV calls. Policing: A Journal of Policy and Practice, 11(3), 242–257. https://doi.org/gjk2bh

Bergen

R. K.

Bukovec

(2006). Men and intimate partner rape: Characteristics of men who sexually abuse their partner. Journal of Interpersonal Violence, 21(10), 1375–1384. https://doi.org/fmzh3c

Bhochhibhoya

Maness

S. B.

Cheney

Larson

(2019). Risk factors for sexual violence among college students in dating relationships: An ecological approach. Journal of Interpersonal Violence, 36(15-16), 202–16. https://doi.org/fpkb

Black

Basile

Breiding

Smith

Walters

Merrick

Stevens

(2011). National intimate partner and sexual violence survey: 2010 summary reports centers for disease control and prevention. https://doi.org/fpkd

Bonomi

A. E.

Trabert

Anderson

M. L.

Kernic

M. A.

Holt

V. L.

(2014). Intimate partner violence and neighborhood income: A longitudinal analysis. Violence Against Women, 20(1), 42–58. https://doi.org/gk75

Bows

(2018). Sexual violence against older people: A review of the empirical literature. Trauma, Violence & Abuse, 19(5), 567–583. https://doi.org/ggxbb5

Brecklin

L. R.

Ullman

S. E.

(2010). The roles of victim and offender substance use in sexual assault outcomes. Journal of Interpersonal Violence, 25(8), 1503–1522. https://doi.org/cpdq44

10.

Breiding

M. J.

Smith

S. G.

Basile

K. C.

Walters

M. L.

Chen

Merrick

M. T.

(2015). Prevalence and characteristics of sexual violence, stalking, and intimate partner violence victimization—National Intimate Partner and Sexual Violence Survey, United States, 2011. American Journal of Public Health, 105(4), e11–e12. https://doi.org/fpkc

11.

Breidling

M. J.

Basile

K. C.

Klevens

Smith

S. G.

(2017). Economic insecurity and intimate partner and sexual violence victimization. American Journal of Preventive Medicine, 53(4), 457–464. https://doi.org/gckhb7

12.

Campbell

Dworkin

Cabral

(2009). An ecological model of the impact of sexual assault on women's mental health. Trauma, Violence, & Abuse, 10(3), 225–246. https://doi.org/bhdcs3

13.

Carbone-Lopez

Slocum

L. A.

Kruttschnitt

(2016). “Police wouldn’t give you no help” female offenders on reporting sexual assault to police. Violence Against Women, 22(3), 366–396. https://doi.org/f79qsk

14.

Ceccato

Haining

(2019). The ecology of outdoor rape: The case of Stockholm, Sweden. European Journal of Criminology, 16(2), 210–236. https://doi.org/gd8tmh

15.

Chancellor

A. S.

(2012). Investigating sexual assault cases. Jones & Bartlett Publishers. https://doi.org/gk76

16.

Cohen

(1983). The cost of dichotomization. Applied Psychological Measurement, 7(3), 249–253. https://doi.org/cp28jq

17.

Coker

A. L.

Smith

P. H.

McKeown

R. E.

King

M. J.

(2000). Frequency and correlates of intimate partner violence by type: physical, sexual, and psychological battering. American Journal of Public Health, 90(4), 553. https://doi.org/cmd782

18.

County Health Rankings and Roadmaps System (2019). How healthy is your county? County health rankings. University of Wisconsin Population Health Institute. Retrieved from: http://www.countyhealthrankings.org/homepage

19.

Dartnall

Jewkes

(2013). Sexual violence against women: The scope of the problem. Best Practice & Research Clinical Obstetrics & Gynecology, 27(1), 3–13. https://doi.org/f4pggb

20.

Diamond-Smith

Rudolph

(2018). The association between uneven sex ratios and violence: Evidence from 6 Asian countries. PLoS One, 13(6), e0197516. https://doi.org/gdnjr5

21.

Dobash

R. E.

Dobash

(2015). When men murder women. Oxford University Press.

22.

Easteal

L. P.

Mc-Ormond-Plummer

(2006). Real rape, al pain: Help for women sexually assaulted by male partners. Melbourne, VIC, Australia: Hybrid Publishers. https://doi.org/ffs2h9.

23.

Farrington

D. P.

(Ed.). (2017). Integrated developmental and life-course theories of offending. Routledge. https://doi.org/fpmb

24.

Felson

R. B.

Pare

(2005). The reporting of domestic violence and sexual assault by non- strangers to the police. Journal of Marriage and Family, 67, 597–610. https://doi.org/dshw3x

25.

Freed

Palmer

Minchala

Levy

Ristenpart

Dell

(2017). Digital technologies and intimate partner violence: A qualitative analysis with multiple stakeholders. Human and Computer Interaction 46, 26–38. https://doi.org/gfvhkn

26.

Frye

Blaney

Cerdá

Vlahov

Galea

Ompad

D. C.

(2014). Neighborhood characteristics and sexual intimate partner violence against women among low-income, drug-involved New York City residents: Results from the IMPACT studies. Violence Against Women, 20(7), 799–824. https://doi.org/fpkf

27.

Gezinski

L. B.

(2020). “It’s kind of hit and miss with them”: A qualitative investigation of police response to intimate partner violence in a mandatory arrest state. Journal of Family Violence, 1-13. https://doi.org/gk77.

28.

Glass

Laughon

Rutto

Bevacqua

Campbell

J. C.

(2008). Young adult intimate partner feticide: An exploratory study. Homicide Studies, 12(2), 177–218. https://doi.org/fm9d7n

29.

Goodyear

Rodriguez

Glik

(2019). The role of firearms in intimate partner violence: Policy and research considerations. Journal of Public Health Policy, 41, 1–11. https://doi.org/fpkg

30.

Greathouse

S. M.

Saunders

J. M.

Matthews

Keller

K. M.

Miller

L. L.

(2015). A review of the literature on sexual assault perpetrator characteristics and behaviors: Rand Corporation.

31.

Grotpeter

Menard

Gianola

(2009). Intimate partner violence: Justice system response and public health service utilization in a national sample. PsychExtra Dataset. https://doi.org/gk78

32.

Hanson

R. K.

Harris

A. J.

Letourneau

Helmus

L. M.

Thornton

(2018). Reductions in risk based on time offense-free in the community: Once a sexual offender, not always a sexual offender. Psychology, Public Policy, and Law, 24(1), 48. https://doi.org/gc2n57

33.

Hesketh

. (2011). Selecting sex: The effect of preferring sons. Early Human Development. 87(11), 759–761. https://doi.org/drtbrp

34.

Hudak

Corry

Schwimmer

Rupp

(2020). Firearm-facilitated sexual assault: Using emergency department data to provide a novel perspective of the problem. Violence and Gender, 7(1), 33–36. https://doi.org/fpkh

35.

Jain

Buka

S. L.

Subramanian

S. V.

Molnar

B. E.

(2010). Neighborhood predictors of dating violence victimization and perpetration in young adulthood: A multilevel study. American Journal of Public Health, 100(9), 1737–1744. https://doi.org/dphq6h

36.

Johnson

(2017). Why doesn't she just report it? Apprehensions and contradictions for women who report sexual violence to the police. Canadian Journal of Women and the Law, 29(1), 36–59. https://doi.org/fpkj

37.

Jung

Faitakis

Cheema

(2020). A comparative profile of intimate partner sexual violence. Journal of Sexual Aggression, 27, 1–11. https://doi.org/fpkk

38.

Kilpatrick

D. G.

Resnick

H. S.

Ruggiero

K. J.

Conoscenti

L. M.

McCauley

(2007). Drug-facilitated, incapacitated, and forcible rape: A national studyNational Criminal Justice Reference Service. https://doi.org/gk8b

39.

Konkel

R. H.

Hafemeister

A. J.

Daigle

L. E.

(2019). The effects of risky places, motivated offenders, and social disorganization on sexual victimization: A microgeographic-and neighborhood-level examination. Journal of Interpersonal Violence, 36, 17–18. https://doi.org/fpkn

40.

Krienert

J. L.

Walsh

J. A.

(2018). An examination of intimate partner sexual violence: Comparing marital and nonmarital incidents employing NIBRS data, 2008–2012. Partner Abuse, 9(1), 41–57. https://doi.org/fpkm

41.

Laughon

Bloom

Amar

A. F.

Debnam

(2020). Conceptualizing an approach to secondary prevention of relationship violence among college students. Journal of American College Health, 1-8. https://doi.org/ghqq8b.

42.

Lauritsen

J. L.

Schaum

R. J.

(2004). The social ecology of violence against women. Criminology, 42(2), 323–357. https://doi.org/cmtqtg

43.

LeSeur

(2020). An international study of the contextual effects of gender inequality on intimate partner sexual violence against women students. Feminist Criminology, 15(1), 97–118. https://doi.org/fpmd

44.

Logan

T. K.

Cole

Capillo

(2007). Differential characteristics of intimate partner, acquaintance, and stranger rape survivors examined by a Sexual Assault Nurse Examiner (SANE). Journal of Interpersonal Violence, 22(8), 1066–1076. https://doi.org/dqqmss

45.

Lopez

E. C.

Koss

M. P.

Kennon

(2019). Acquaintance rape. The Encyclopedia of Women and crime, 1-8. https://doi.org/gk79.

46.

Zhang

Holt

J. B.

Kanny

Croft

J. B.

(2018). Quantifying spatial accessibility in public health practice and research: An application to on-premise alcohol outlets, United States, 2013. International Journal of Health Geographics, 17(1), 23. https://doi.org/gdtrzn

47.

Martin

S. L.

Young

S. K.

Billings

D. L.

Bross

C. C.

(2007). Health care-based interventions for women who have experienced sexual violence: A review of the literature. Trauma, Violence & Abuse, 8(1), 3–18. https://doi.org/drcd7s

48.

Messing

J. T.

Campbell

Dunne

Dubus

(2020). Development and testing of the Danger Assessment for Law Enforcement (DA-LE). Social Work Research, 44(3), 143-156. https://doi.org/fpkv.

49.

Messing

J. T.

Thaller

Bagwell

(2014). Factors related to sexual abuse and forced sex in a sample of women experiencing police-involved intimate partner violence. Health & Social Work, 39(3), 181–191. https://doi.org/f6c3z6

50.

National Coalition Against Domestic Violence (2015). Domestic violence. Retrieved from: https://assets.speakcdn.com/assets/2497/domestic_violence.pdf

51.

National Institute of Justice (2018). Risk factors in pre-and mid-adolescence may help predict dating violence in young adulthood. US Department of Justice, Office of Justice Programs, and the United States of America.

52.

Nobels

Vandeviver

Beaulieu

Cismaru Inescu

Nisen

Van Den Noortgate

Vander Beken

Lemmens

Keygnaert

(2020). “Too grey to be true?” Sexual violence in older adults: A critical interpretive synthesis of evidence. International Journal of Environmental Research and Public Health, 17(11), 4117. https://doi.org/fpkt

53.

Office for the Prevention of Domestic Violence (2020). Retrieved from: https://opdv.ny.gov/

54.

Okasako-Schmucker

D. L.

Cole

K. H.

Finnie

R. K.

Basile

K. C.

DeGue

Niolon

P. H.

(2019). Using a community preventive services task force recommendation to prevent and reduce intimate partner violence and sexual violence. Journal of Women’s Health, 28(10), 1335–1337. https://doi.org/fpkw

55.

Pazzani

L. M.

(2007). The factors affecting sexual assaults committed by strangers and acquaintances. Violence against Women, 13(7), 717–749. https://doi.org/b3zs4r

56.

Rape, Abuse, and Incest National Network (RAINN) . (2016). Retrieved from https://www.rainn.org/statistics

57.

Reed

Silverman

J. G.

Welles

S. L.

Santana

M. C.

Missmer

S. A.

Raj

(2009). Associations between perceptions and involvement in neighborhood violence and intimate partner violence perpetration among urban, African American men. Journal of Community Health, 34(4), 328–335. https://doi.org/cwvsj8

58.

Robinson

A. L.

Chandek

M. S.

(2000). The domestic violence arrest decision: Examining demographic, attitudinal, and situational variables. Crime & Delinquency, 46(1), 18–37. https://doi.org/bqmn3v

59.

Sampson & Lauritsen . (1994). National Research Council. Understanding and Preventing Violence, Volume 3: Social Influences. Washington, DC: The National Academies Press. https://doi.org/10.17226/4421.

60.

Shorey

R. C.

Brasfield

Zapor

Febres

Stuart

G. L.

(2015). The relation between alcohol use and psychological, physical, and sexual dating violence perpetration among male college students. Violence Against Women, 21(2), 151–164. https://doi.org/f6zkbm

61.

Shotland

R. L.

(1985). A preliminary model of some causes of date rape. Academic Psychology Bulletin, 7, 187–200. https://doi.org/br5pbm

62.

Smith

P. H.

Thornton

G. E.

DeVellis

Earp

Coker

A. L.

(2002). A population-based study of the prevalence and distinctiveness of battering, physical assault, and sexual assault in intimate relationships. Violence Against Women, 8(10), 1208–1232. https://doi.org/fpk2

63.

Smith

S. G.

Zhang

Basile

K. C.

Merrick

M. T.

Wang

Kresnow

M. J.

Chen

(2018). The national intimate partner and sexual violence survey: 2015 data brief– updated release. National Center for Injury Prevention and Control, Centers for Disease Control and Prevention.

64.

Snyder

H. N.

(2000). Sexual assault of young children as reported to law enforcement: Victim, incident, and offender characteristics. National Center for Juvenile Justice. https://doi.org/fpk3

65.

Sorenson

S. B.

Wiebe

D. J.

(2004). Weapons in the lives of battered women. American Journal of Public Health, 94(8), 1412–1417. https://doi.org/cgxk4n

66.

Sparks

Wielinga

Jung

Olver

(2020). Recidivism risk and criminogenic needs of individuals who perpetrated intimate partner sexual violence offenses. Sexual Offending Theory Risk and Prevention, 15(1), e3713. https://doi.org/fpk4.

67.

Stöckl

March

Pallitto

Garcia-Moreno

(2014). Intimate partner violence among adolescents and young women: Prevalence and associated factors in nine countries: A cross-sectional study. BMC Public Health, 14(1), 1-14. https://doi.org/f6fjb8.

68.

Tarzia

(2020). Toward an ecological understanding of intimate partner sexual violence. Journal of Interpersonal Violence, 1. https://doi.org/fpk5.

69.

Taylor

S. C.

Gassner

(2010). Stemming the flow: Challenges for policing adult sexual assault with regard to attrition rates and under‐reporting of sexual offences. Police Practice and Research, 11(3), 240–255. https://doi.org/dnm2zw

70.

Tennessee Incident Based Reporting System (2019). Crime insight. Tennessee Bureau of Investigation. Retrieved from: https://crimeinsight.tbi.tn.gov/tops/

71.

Tewksbury

(2002). Validity and utility of the Kentucky sex offender registry. Federal. Probation, 66, 21. https://doi.org/bqjj93

72.

Tharp

A. T.

Schumacher

J. A.

Samper

R. E.

McLeish

A. C.

Coffey

S. F.

(2013). Relative importance of emotional dysregulation, hostility, and impulsiveness in predicting intimate partner violence perpetrated by men in alcohol treatment. Psychology of Women Quarterly, 37(1), 51–60. https://doi.org/fpk6

73.

Tingley

J. C.

(2018). Family and intimate partner homicide: A descriptive analysis of the characteristics and circumstances surrounding family and intimate partner homicide in Virginia, 2015. Virginia Department of Health. Retrieved from: www.vdh.virginia.gov/medExam/fipvhs-reports-publications.htm

74.

Titan Business Unit (2019). Handgun carry permit statistics calendar year 2018. Department of Safety and Homeland Security.

75.

Truman

J. L.

Langton

(2015). Criminal victimization, 2014. National Criminal Justice Reference Service. Bureau of Justice and Statistics.

76.

Twis

M. K.

Nguyen

A. P.

Nordberg

(2018). Intimate partner violence myths in police reports: a directed content analysis. Violence and Victims, 33(2), 351–367. https://doi.org/gdcjcv

77.

Valentine

C. L.

Stults

B. J.

Hasbrouck

(2019). The nonlinear effect of informal social control on repeat intimate partner violence victimization. Journal of Interpersonal Violence, 34(13), 2723–2748. https://doi.org/fpmh

78.

Waller

B. Y.

Harris

Quinn

C. R.

(2021). Caught in the crossroad: An intersectional examination of African American women intimate partner violence survivors’ help seeking. Trauma, Violence, & Abuse, 1524838021991303. https://doi.org/gk8c

79.

Warnken

Lauritsen

(2019). Who experiences violent victimization and who accesses services? Findings from the national crime victimization survey for expanding our reach. Center for Victim Research Repository.

80.

Wegner

Pierce

Abbey

(2014). Relationship type and sexual precedence: The associations with characteristics of sexual assault and perpetrators and incidents. Violence against Women, 20(11), 1360–1382. https://doi.org/f6nw9s

81.

Wolitzky-Taylor

K. B.

Resnick

H. S.

McCauley

J. L.

Amstadter

A. B.

Kilpatrick

D. G.

Ruggiero

K. J.

(2011). Is reporting of rape on the rise? A comparison of women with reported versus unreported rape experiences in the National Women’s Study- Replication. Journal of Interpersonal Violence, 26(4), 807–832. https://doi.org/b5j7rx

82.

World Health Organization . (2012). Understanding and addressing violence against women: Intimate partner violence (No. WHO/RHR/12.36). World Health Organization.

83.

World Health Organization . (2013). Global and regional estimates of violence against women: Prevalence and health effects of intimate partner violence and non-partner sexual violence. World Health Organization.

Neighborhood-Level Predictors of Sexual Violence Across Intimate Partner and Non-Intimate Partner Relationships: A Case–Control Study

Abstract

Keywords

Individual-Level Correlates of IPSV and NIPSV

Relationship or Dyadic-Level Correlates of IPSV and NIPSV

Community-Level Correlates of IPSV and NIPSV

Current Study

Method

Sample

Procedures

Dependent Variables (Cases)

Independent Variables

Analytic Plan

Results

Discussion

Recommendations for Prevention and Intervention

Limitations

Conclusions

Footnotes

Acknowledgments

Declaration of Conflicting Interests

Funding

ORCID iD

Appendix

References