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Risk Factors for Femicide in Abusive Relationships: Results From a Multisite Case Control Study

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This 11-city study sought to identify risk factors for femicide in abusive relationships. Proxies of 220 intimate partner femicide victims identified from police or medical examiner records were interviewed, along with 343 abused control women. Preincident risk factors associated in multivariate analyses with increased risk of intimate partner femicide included perpetrator's access to a gun and previous threat with a weapon, perpetrator's stepchild in the home, and estrangement, especially from a controlling partner. Never living together and prior domestic violence arrest were associated with lowered risks. Significant incident factors included the victim having left for another partner and the perpetrator's use of a gun. Other significant bivariate-level risks included stalking, forced sex, and abuse during pregnancy. There are identifiable risk factors for intimate partner femicides.
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July 2003, Vol 93, No. 7 | American Journal of Public Health Campbell et al. | Peer Reviewed | Research and Practice | 1089
RESEARCH AND PRACTICE
Objectives. This 11-city study sought to identify risk factors for femicide in abusive
relationships.
Methods. Proxies of 220 intimate partner femicide victims identified from police or
medical examiner records were interviewed, along with 343 abused control women.
Results. Preincident risk factors associated in multivariate analyses with increased
risk of intimate partner femicide included perpetrator’s access to a gun and previous
threat with a weapon, perpetrator’s stepchild in the home, and estrangement, espe-
cially from a controlling partner. Never living together and prior domestic violence ar-
rest were associated with lowered risks. Significant incident factors included the vic-
tim having left for another partner and the perpetrator’s use of a gun. Other significant
bivariate-level risks included stalking, forced sex, and abuse during pregnancy.
Conclusions. There are identifiable risk factors for intimate partner femicides. (Am J
Public Health. 2003;93:1089–1097)
Risk Factors for Femicide in Abusive Relationships:
Results From a Multisite Case Control Study
| Jacquelyn C. Campbell, PhD, RN, Daniel Webster, ScD, MPH, Jane Koziol-McLain, PhD, RN, Carolyn Block, PhD, Doris Campbell, PhD, RN, Mary Ann
Curry, PhD, RN, Faye Gary, PhD, RN, Nancy Glass, PhD, MPH, RN, Judith McFarlane, PhD, RN, Carolyn Sachs, MD, MPH, Phyllis Sharps, PhD, RN,
Yvonne Ulrich, PhD, RN, Susan A. Wilt, DrPH, Jennifer Manganello, PhD, MPH, Xiao Xu, PhD, RN, Janet Schollenberger, MHS, Victoria Frye, MPH,
and Kathryn Laughon, MPH
Femicide Cases
All consecutive femicide police or med-
ical examiner records from 1994 through
2000 at each site were examined to assess
victim–perpetrator relationships. Cases were
eligible if the perpetrator was a current or
former intimate partner and the case was
designated as “closed” by the police (suicide
by the perpetrator, arrest, or adjudication,
depending on the jurisdiction). Records were
abstracted for data specific to the homicide.
At least 2 potential proxy informants, indi-
viduals knowledgeable about the victim’s re-
lationship with the perpetrator, were identi-
fied from the records. The proxy who, in the
investigator’s judgment, was the most knowl-
edgeable source was then sent a letter ex-
plaining the study and including researcher
contact information. If no communication was
initiated by the proxy, study personnel at-
tempted telephone or (in the few cases in
which no telephone contact was possible) per-
sonal contact.
If the first proxy was not knowledgeable
about details of the relationship, she or he
was asked to identify another willing potential
proxy informant. When a knowledgeable
proxy was found, informed consent was ob-
tained. In 373 of the 545 (68%) total femi-
cide cases abstracted, a knowledgeable proxy
was identified and located. In 82% (307/
373) of these cases, proxies agreed to partici-
pate. Two exclusion criteria, age (18–50
years) and no previous abuse by the femicide
perpetrator, resulted in the elimination of 87
additional cases (28.3% of 307 cases), with
59 (19.2% of 307 cases) eliminated solely as
a result of the latter criterion.
Researchers and doctoral students experi-
enced in working with victims of domestic vi-
olence conducted telephone or in-person in-
terviews in English or Spanish; interviews
were 60 to 90 minutes in duration. Both
proxies and abused control women were ex-
cluded if they could speak neither English
nor Spanish.
Abused Control Women
Stratified random-digit dialing (up to 6 at-
tempts per number) was used to select
women aged 18 to 50 years who had been
involved “romantically or sexually” in a rela-
tionship at some time in the past 2 years in
the same cities in which the femicides oc-
curred. A woman was considered “abused” if
she had been physically assaulted or threat-
ened with a weapon by a current or former
intimate partner during the past 2 years; we
Femicide, the homicide of women, is the lead-
ing cause of death in the United States among
young African American women aged 15 to
45 years and the seventh leading cause of
premature death among women overall.
1
American women are killed by intimate part-
ners (husbands, lovers, ex-husbands, or ex-
lovers) more often than by any other type of
perpetrator.
2–4
Intimate partner homicide ac-
counts for approximately 40% to 50% of US
femicides but a relatively small proportion of
male homicides (5.9%).
1,5–10
The percentage
of intimate partner homicides involving male
victims decreased between 1976 and 1996,
whereas the percentage of female victims in-
creased, from 54% to 72%.
4
The majority (67%–80%) of intimate part-
ner homicides involve physical abuse of the
female by the male before the murder, no
matter which partner is killed.
1,2,6,11–13
There-
fore, one of the major ways to decrease inti-
mate partner homicide is to identify and in-
tervene with battered women at risk. The
objective of this study was to specify the risk
factors for intimate partner femicide among
women in violent relationships with the aim
of preventing this form of mortality.
METHODS
An 11-city case–control design was used;
femicide victims were cases (n =220), and
randomly identified abused women residing
in the same metropolitan area were control
women (n=343). Co-investigators at each site
collaborated with domestic violence advo-
cacy, law enforcement, and medical examiner
offices in implementing the study. Sampling
quotas for cases and control women in each
city were proportionately calculated so that
the cities with the highest annual femicide
rates included the largest number of cases
and control women.
American Journal of Public Health | July 2003, Vol 93, No. 71090 | Research and Practice | Peer Reviewed | Campbell et al.
RESEARCH AND PRACTICE
identified episodes of abuse with a modified
version of the Conflict Tactics Scale with
stalking items added.
11 , 14
English- and Spanish-speaking telephone
interviewers employed by an experienced
telephone survey firm completed sensitivity
and safety protocol training.
15
A total of 4746
women met the age and relationship criteria
and were read the consent statement. Among
these women, 3637 (76.6%) agreed to partic-
ipate, 356 (9.8%) of whom had been physi-
cally abused or threatened with a weapon by
a current or recent intimate partner. Thirteen
abused control women were excluded from
the analysis because they reported that the
injuries from their most severe incident of
abuse were so severe that they thought they
could have died.
Risk Factor Survey Instrument
The interview included previously tested
instruments, such as the Danger Assess-
ment,
16 , 17
and gathered information on demo-
graphic and relationship characteristics, in-
cluding type, frequency, and severity of
violence, psychological abuse, and harass-
ment; alcohol and drug use; and weapon
availability. The Danger Assessment had
been translated to and validated in Spanish in
earlier research; the remainder of the survey
wastranslated and back-translated by our
Spanish-speaking interviewers and by project
staff in Houston, Los Angeles, and New York.
A factor analysis of the risk items was used in
constructing scales measuring partners’ con-
trolling and stalking behaviors. Each scale
was internally consistent (α=.83 and .75,
respectively).
Data Analysis
Logistic regression was used to estimate
the independent associations between each
of the hypothesized risk factors and the risk
of intimate partner femicide. Because the im-
portance of certain risk factors may not be
detected when their effects are mediated by
more proximal risk factors, we sequentially
added blocks of conceptually similar explana-
tory variables along a risk factor continuum
ranging from most distal (demographic char-
acteristics of perpetrators and victims) to
most proximal (e.g., weapon used in the femi-
cide or most serious abuse incident). Vari-
ables not significantly associated with femi-
cide risk were dropped from subsequent
models. Model coefficients were exponenti-
ated so that they could be interpreted as ad-
justed odds ratios (ORs).
RESULTS
Demographic, background, and relation-
ship variables that differentiated case women
from control women in bivariate analyses are
presented in Tables 1 and 2. Table 3 displays
findings from the series of logistic regression
models. The strongest sociodemographic risk
factor (model 1) for intimate partner femicide
was the abuser’s lack of employment (ad-
justed OR = 5.09; 95% confidence interval
[CI] = 2.74, 9.45). Instances in which the
abuser had a college education (vs a high
school education) were protective against
femicide (adjusted OR = 0.31; 95% CI = 0.12,
0.80), as were instances in which the abuser
had a college degree and was unemployed
but looking for work. Race/ethnicity of
abusers and victims was not independently
associated with intimate partner femicide risk
after control for other demographic factors.
When additional individual-level risk fac-
tors for homicide were added to the model
(model 2), both abuser’s access to a firearm
(adjusted OR = 7.59; 95% CI =3.85, 14.99)
and abuser’s use of illicit drugs (adjusted
OR=4.76; 95% CI = 2.19, 10.34) were
strongly associated with intimate partner
femicide, although the abuser’s excessive use
of alcohol was not. Although the abuser’s ac-
cess to a firearm increased femicide risk, vic-
tims’ risk of being killed by their intimate
partner was lower when they lived apart from
the abuser and had sole access to a firearm
(adjusted OR = 0.22). Neither alcohol abuse
nor drug use by the victim was independently
associated with her risk of being killed.
Relationship variables were added in
model 3. Never having lived with the abusive
partner significantly lowered women’s risk of
femicide (OR = 0.39; 95% CI = 0.16, 0.97).
Having been separated from an abusive part-
ner after living together was associated with a
higher risk of femicide (adjusted OR = 3.64;
95% CI = 1.71, 7.78), as was having ever left
or having asked the partner to leave (adjusted
OR=3.19; 95% CI = 1.70, 6.02). Having a
child living in the home who was not the abu-
sive partner’s biological child more than dou-
bled the risk of femicide (adjusted OR = 2.23;
95% CI = 1.13, 4.39). Addition of the rela-
tionship variables resulted in victims’ sole ac-
cess to a firearm no longer being statistically
significant and substantially reduced the ef-
fects of abuser’s drug use.
Variables related to abusive partners’ con-
trolling behaviors and verbal aggression were
added in model 4. The effects of a highly
controlling abuser were modified by whether
the abuser and victim separated after living
together. The risk of intimate partner femi-
cide was increased 9-fold by the combination
of a highly controlling abuser and the cou-
ple’s separation after living together (adjusted
OR=8.98; 95% CI = 3.25, 24.83). Femicide
risk was increased to a lesser degree when
the abuser was highly controlling but the cou-
ple had not separated (adjusted OR= 2.90;
95% CI = 1.41, 5.97) and when the couple
had separated after living together but the
abuser was not highly controlling (adjusted
OR=3.10; 95% CI = 1.20, 8.05).
Threatening behaviors and stalking were
added in model 5. Abusers’ previous threats
with a weapon (adjusted OR= 4.08; 95%
CI=1.91, 8.72) and threats to kill (adjusted
OR=2.60; 95% CI = 1.24, 5.42) were associ-
ated with substantially higher risks for femi-
cide. After control for threatening behaviors,
there were no significant independent effects
of abusers’ drug use (OR = 1.64; 95% CI =
0.88, 3.04). The effects of high control with
separation (adjusted OR= 4.07; 95% CI=
1.33, 12.4) and access to guns (adjusted
OR=5.44; 95% CI = 2.89, 10.22), although
substantially reduced, remained strong.
Stalking and threats to harm children and
other family members were not indepen-
dently associated with intimate partner femi-
cide risk after variables had been entered in
the first models. When variables related to
previous physical abuse were included in
model 6, previous arrest of the abuser for do-
mestic violence was associated with a de-
creased risk of intimate partner femicide (ad-
justed OR = 0.34; 95% CI= 0.16, 0.73). The
association between abusers’ use of forced
sex on victims and increased intimate partner
femicide risks approached statistical signifi-
cance (adjusted OR = 1.87; 95% CI = 0.97,
3.63; P<.07).
July 2003, Vol 93, No. 7 | American Journal of Public Health Campbell et al. | Peer Reviewed | Research and Practice | 1091
RESEARCH AND PRACTICE
TABLE 1—Sociodemographic Characteristics of Victims and Perpetrators and General Risk
Factors for Homicide, by Group
Victims Perpetrators
Nonfatal Nonfatal
Physical Abuse Homicide Physical Abuse Homicide
(n = 343) (n = 220) P (n = 343) (n = 220) P
Sociodemographic variables
Age, y, mean ± SD 30.1 ± 8.6 31.4 ± 7.7 .081 31.2 ± 9.2 34.2 ± 8.7 <.001
Don’t know/refused/missing 0 0 4 22
Race/ethnicity, No. (%) <.001 <.001
Black/African American 70 (20.6) 104 (47.3) 83 (24.3) 107 (48.9)
White 157 (46.3) 53 (24.1) 153 (44.7) 49 (22.4)
Latino/Hispanic 82 (24.2) 53 (24.1) 80 (23.4) 58 (26.5)
Other 30 (8.9) 10 (4.5) 26 (7.6) 5 (2.3)
Don’t know/refused/missing 4 0 1 1
Education, No. (%) <.001 <.001
Less than high school 61 (17.9) 71 (33.2) 92 (28.0) 70 (48.9)
High school 73 (21.5) 59 (27.5) 91 (27.7) 47 (32.9)
Some college/trade school 109 (32.1) 68 (31.8) 58 (17.7) 17 (11.9)
College/trade school 97 (28.5) 16 (7.5) 87 (26.5) 9 (6.3)
Don’t know/refused/missing 3 6 15 77
Employment, No. (%) <.001 <.001
Full-time 179 (52.2) 114 (51.8) 229 (68.2) 84 (39.6)
Part-time 70 (20.4) 31 (14.1) 39 (11.6) 20 (9.5)
Unemployed, seeking job 40 (11.7) 12 (5.5) 25 (7.4) 13 (6.1)
Unemployed, not seeking job 54 (15.7) 63 (28.6) 43 (12.8) 95 (44.8)
Don’t know/refused/missing 0 0 7 8
Income (annual household), $, .005
No. (%)
Less than 10 000 67 (21.7) 25 (18.8)
10 000–19 999 49 (15.9) 32 (24.1)
20 000–29 999 43 (13.9) 20 (15.0)
30 000–39 999 41 (13.3) 29 (21.8)
40 000 or more 109 (35.3) 27 (20.3)
Don’t know/refused/missing 34 87
General violence/homicide risk variables
Threatened/attempted suicide .091 .149
Yes 33 (9.6) 12 (5.6) 68 (20.1) 45 (25.0)
Don’t know/refused/missing 0 6 4 40
Problem alcohol drinker, No. (%) < .001 < .001
Yes 27 (7.9) 36 (19.1) 106 (30.9) 105 (52.0)
Don’t know/refused/missing 0 32 0 18
Illicit drug use, No. (%) .002 <.001
Yes 49 (14.3) 48 (25.3) 101 (30.4) 123 (65.4)
Don’t know/refused/missing 1 30 11 32
Access to a firearm,
a
No. (%) .996 <.001
Yes 17 (5.0) 10 (5.0) 82 (23.9) 143(65.0)
Don’t know/refused/missing 2 19 0 0
Continued
Incident-level variables were added in
model 7. Abuser’s use of a gun in the worst
incident of abuse was associated with a 41-
fold increase in risk of femicide after control
for other risk factors, this effect apparently
mediating the effects of abuser’s access to a
gun, which was no longer significant. How-
ever, previous threats with a weapon contin-
ued to be associated with increased femicide
risks (OR = 4.41; 95% CI = 1.76, 11.06).
When the worst incident of abuse was
triggered by the victim’s having left the
abuser for another partner or by the abuser’s
jealousy, there was a nearly 5-fold increase
in femicide risk (adjusted OR = 4.91; 95%
CI=2.42, 9.96). When the incident was trig-
gered by the victim’s having left the abuser
for any other reason, femicide risks were
also significantly increased (adjusted OR =
4.04; 95% CI = 1.80, 9.06). These incident-
level effects appear to mediate those related
to highly controlling abusers and separation
after cohabitation.
Each of the models included in Table 3
demonstrated an adequate fit according to
Hosmer–Lemeshow
18
goodness-of-fit tests.
Model 6 correctly predicted the case status of
73% of the cases and 93% of the control
women. Model 7 correctly predicted the case
status of 81% of the cases and 95% of the
control women.
DISCUSSION
Seventy-nine percent (220/279) of the
femicide victims aged 18 to 50 years and
70% of the 307 total femicide cases were
physically abused before their deaths by the
same intimate partner who killed them, in
comparison with 10% of the pool of eligible
control women. Thus, our first premise, that
physical violence against the victim is the pri-
mary risk factor for intimate partner femicide,
was upheld. The purpose of this study, how-
ever, was to determine the risk factors that,
over and above previous intimate partner vio-
lence, are associated with femicide within a
sample of battered women. Our analysis
demonstrated that a combination of the most
commonly identified risk factors for homicide,
in conjunction with characteristics specific to
violent intimate relationships, predicted inti-
mate partner femicide risks.
American Journal of Public Health | July 2003, Vol 93, No. 71092 | Research and Practice | Peer Reviewed | Campbell et al.
RESEARCH AND PRACTICE
TABLE 1—Continued
Arrest for violent crime, No. (%) <.001
Yes 38 (11.5) 43 (21.8)
Don’t know/refused/missing 12 23
Note. The referent time periods for all risk variables were the year previous to the most abusive event for abused control
women and the year previous to the femicide for femicide victims.
a
For abused women, gun access was defined as a woman’s sole access to a firearm on the basis of her living apart from her
partner and reporting having a gun in the home; gun access for partner was based on reports of his personal ownership of a
firearm or living in a household with a firearm.
The model-building strategy we used al-
lowed for consideration of different levels of
prevention and the degree to which intimate
partner femicides could be prevented by strat-
egies directed at risk factors for homicide in
general. For example, our analysis and those
of others suggest that increasing employment
opportunities, preventing substance abuse,
and restricting abusers’ access to guns can po-
tentially reduce both overall rates of homicide
and rates of intimate partner femicide.
In comparing our femicide perpetrators
with other abusive men, we found that unem-
ployment was the most important demo-
graphic risk factor for acts of intimate partner
femicide. In fact, abuser’s lack of employment
was the only demographic risk factor that sig-
nificantly predicted femicide risks after we
controlled for a comprehensive list of more
proximate risk factors, increasing risks 4-fold
relative to the case of employed abusers
(model 6). Unemployment appears to under-
lie increased risks often attributed to race/
ethnicity, as has been found and reported in
other analyses related to violence.
19 , 2 0
The present results revealed that traits of
perpetrators thought to be characteristic of vi-
olent criminals in general
21
tended to be no
more characteristic of femicide perpetrators
than of other batterers. For instance, in con-
trast to results of previous research compar-
ing abusers and nonabusers,
22
our regression
analyses showed that arrests for other crimes
did not differentiate femicide perpetrators
from perpetrators of intimate partner vio-
lence. After controlling for other risk factors,
prior arrest for domestic violence actually de-
creased the risk for femicide, suggesting that
arrest of abusers protects against future inti-
mate partner femicide risks. Perpetrator drug
abuse significantly increased the risk of inti-
mate partner femicide, but only before the ef-
fects of previous threats and abuse were
added. Drug abuse, therefore, was associated
with patterns of intimate partner abuse that
increase femicide risks.
Our iterative model-building strategy also
allowed us to observe whether the effects of
more proximate risk factors mediate the ef-
fects of more distal factors in a manner con-
sistent with theory. For example, the 8-fold in-
crease in intimate partner femicide risk
associated with abusers’ access to firearms at-
tenuated to a 5-fold increase when character-
istics of the abuse were considered, including
previous threats with a weapon on the part of
the abuser. This suggests that abusers who
possess guns tend to inflict the most severe
abuse.
However, consistent with other re-
search,
3,23,15,24,25
gun availability still had sub-
stantial independent effects that increased
homicide risks. As expected, these effects
were due to gun-owning abusers’ much
greater likelihood of using a gun in the worst
incident of abuse, in some cases, the actual
femicide. The substantial increase in lethality
associated with using a firearm was consistent
with the findings of other research assessing
weapon lethality. A victim’s access to a gun
could plausibly reduce her risk of being
killed, at least if she does not live with the
abuser. A small percentage (5%) of both case
and control women lived apart from the
abuser and owned a gun, however, and there
was no clear evidence of protective effects.
Previous arrests for domestic violence was
protective against intimate partner femicide
in both of the final models. In most of the
cities where data were collected, there is a
coordinated community response to domes-
tic violence. Under optimal conditions, such
responses include adequate and swift adjudi-
cation, close supervision of parole outcomes
through periodic court reviews or specialized
probation programs, ongoing risk manage-
ment for arrested perpetrators and ongoing
safety planning for victims, and close super-
vision involving sanctions for batterers who
drop out of mandated intervention pro-
grams.
26
Under these kinds of conditions,
arrest can indeed be protective against do-
mestic violence escalating to lethality.
Two relationship variables remained signif-
icant throughout the models. Consistent with
earlier research,
27,28
instances in which a
child of the victim by a previous partner was
living in the home increased the risk of inti-
mate partner femicide. Situations in which
the victim and abuser had never lived to-
gether were protective, validating safety ad-
vice that battered women have offered to
other battered women in interview studies.
29
Women who separated from their abusive
partners after cohabitation experienced in-
creased risk of femicide, particularly when
the abuser was highly controlling. Other stud-
ies have revealed the same risks posed by es-
trangement,
30,31
but ours further explicates
the findings by identifying highly controlling
male partners as presenting the most danger
in this situation. At the incident level, we
found that batterers were significantly more
likely to perpetrate homicide if their partner
was leaving them for a different partner.
The bivariate analysis supported earlier ev-
idence that certain characteristics of intimate
partner violence are associated with intimate
partner femicide, including stalking, strangula-
tion, forced sex, abuse during pregnancy, a
pattern of escalating severity and frequency
of physical violence, perpetrator suicidality,
perception of danger on the part of the vic-
tim, and child abuse.
15 ,16,20,32–37
However,
these risk factors, with the exception of forced
sex, were not associated with intimate partner
femicide risk in the multivariate analysis.
Many of these characteristics of abuse are as-
sociated with previous threats with a weapon
and previous threats to kill the victim, factors
that more closely predict intimate partner
femicide risks.
This investigation is one of the few studies
of intimate partner femicide to include a
control population and, to our knowledge,
July 2003, Vol 93, No. 7 | American Journal of Public Health Campbell et al. | Peer Reviewed | Research and Practice | 1093
RESEARCH AND PRACTICE
TABLE 2—Relationship Dynamics, Threatening Behavior, and Abuse Characteristics
Abused Control Homicide Victims
Women (n= 343) (n = 220) P
Relationship variables
Age difference, y, mean ± SD 1.1 ± 5.7 2.9 ± 6.4 .001
Length of relationship, No. (%) .023
1 month or less 5 (1.5) 0
1 month to 1 year 94 (27.5) 44 (20.0)
1 or more years 243 (71.0) 176 (80.0)
Don’t know/refused/missing 1 0
Relationship partner, No. (%) .005
Husband 101 (29.7) 85 (39.0)
Boyfriend 86 (25.3) 65 (29.8)
Ex-husband 36 (10.6) 20 (9.2)
Ex-boyfriend 117 (34.4) 48 (22.0)
Don’t know/refused/missing 3 2
Separated, No. (%) <.001
Yes 117 (34.9) 101 (55.2)
Don’t know/refused/missing 8 37
Cohabitation, No. (%) <.001
Yes 174 (50.7) 81 (45.0)
In the past year, but not currently 39 (11.4) 68 (37.8)
Previously, but not in the past year 11 (3.2) 11 (6.1)
Never 118 (34.7) 20 (11.1)
Don’t know/refused/missing 1 40
Biological child(ren) of victim and partner living in the
household, No. (%) .034
Yes 98 (28.6) 73 (37.4)
Don’t know/refused/missing 0 25
Biological child(ren) of victim, and not of partner, living
in the household, No. (%) <.001
Yes 60 (17.5) 82 (38.7)
Don’t know/refused/missing 0 8
Relationship abuse dynamics
Partner controlling behaviors (score > 3), No. (%) <.001
Yes 84 (24.5) 145 (65.9)
Partner called victim names to put her down, No. (%) <.001
Yes 164 (47.8) 151 (77.8)
Don’t know/refused/missing 0 26
General violence/homicide risk variables
Partner violent outside home, No. (%) <.001
Yes 116 (35.5) 102 (55.7)
Don’t know/refused/missing 16 37
Partner threatened to kill woman, No. (%) <.001
Yes 50 (14.6) 142 (73.6)
Don’t know/refused/missing 1 27
Partner threatened to kill family, No. (%) <.001
Yes 26 (7.6) 72 (33.8)
Don’t know/refused/missing 0 7
Continued
the first to examine the connection between
relationship variables and specific demo-
graphic characteristics of victims and perpe-
trators. Perhaps the most important limita-
tion of the study is its necessary reliance on
proxy respondents for data regarding hy-
pothesized risk factors for intimate partner
femicide cases. Because we obtained data
from control women directly, rather than
from a proxy, observed differences between
case and control women may have been
wholly or partly attributable to differences in
accuracy of reporting between victims and
their proxies. To examine this issue, we con-
ducted a small pilot study comparing re-
sponses of victims of attempted femicide and
responses of their proxy respondents and
found good agreement between summed
Danger Assessment scores from the 2
sources of information. Furthermore, there
was no clear tendency for proxies to under-
report or overreport victims’ exposure to
specific risk factors relative to the self-
reports of victims themselves.
35
It is also possible that some of the women
who were excluded from this analysis be-
cause of no record of previous physical vio-
lence were in fact being abused, unknown to
the proxy. However, we found fairly good
correspondence with police records of previ-
ous domestic violence, and, if anything, we
found more knowledge of previous physical
abuse among proxies than among police. A
related limitation is the relatively large pro-
portion of “don’t know” responses from prox-
ies regarding certain hypothesized risk fac-
tors of a more personal nature (e.g., forced
sex). Our decision to treat these “don’t know”
responses as representing absence of the “ex-
posure” produced conservative biases in our
estimates of relationships with intimate part-
ner femicide risks. Therefore, we may have
inappropriately failed to reject the null hy-
pothesis in the case of some of these vari-
ables with large amounts of missing data and
near-significant associations with intimate
partner femicide risk.
Another limitation was that we excluded
women who did not reside in large urban
areas (other than Wichita, Kan) and control
group women who did not have telephones.
We also failed to keep records of exactly
which proxy interviews (estimated to be less
American Journal of Public Health | July 2003, Vol 93, No. 71094 | Research and Practice | Peer Reviewed | Campbell et al.
RESEARCH AND PRACTICE
TABLE 2—Continued
Partner threatened woman with a weapon, No. (%) <.001
Yes 16 (4.7) 110 (55.3)
Don’t know/refused/missing 0 21
Partner threatened to harm children, No. (%) <.001
Yes4 (1.2) 36 (18.5)
Don’t know/refused/missing 7 25
Stalking behavior (score > 3), No. (%) <.001
Yes 21 (6.1) 47 (21.4)
Don’t know/refused/missing 0 0
Characteristics of physical violence
Increase in frequency, No. (%) <.001
Yes 88 (25.7) 109 (59.9)
Don’t know/refused/missing 5 38
Increase in severity, No. (%) <.001
Yes 70 (20.4) 105 (64.4)
Don’t know/refused/missing 5 57
Partner tried to choke (strangle) woman, No. (%) <.001
Yes 34 (9.9) 84 (56.4)
Don’t know/refused/missing 1 71
Forced sex, No. (%) <.001
Yes 51 (14.9) 84 (57.1)
Don’t know/refused/missing 1 73
Abused during pregnancy (ever), No. (%) <.001
Yes 24 (7.0) 49 (25.8)
No or never been pregnant 319 (93.0) 141 (74.2)
Don’t know/refused/missing 0 30
Partner arrest previously for domestic violence, No. (%) .003
Yes 46 (13.9) 50 (25.6%)
Don’t know/refused/missing 12 25
Incident-level variables
Gun used, No. (%) <.001
Yes3 (0.9) 84 (38.2)
Partner used alcohol or drugs, No. (%) <.001
Yes 123 (34.6) 133 (60.5)
Victim used alcohol or drugs, No. (%) <.001
Yes 44 (12.4) 53 (24.1)
Order of protection, No. (%) <.001
Yes 16 (4.7) 54 (24.5)
Trigger: jealousy, No. (%) <.001
Yes 52 (17.1) 85 (38.6)
No or don’t know 291 (82.9) 135 (61.4)
Trigger: woman leaving, No. (%) <.001
Yes 32 (10.5) 72 (32.7)
No or don’t know 311 (89.5) 148 (67.3)
Trigger: woman has new relationship, No. (%) <.001
Yes7 (2.0) 26 (11.8)
No or don’t know 336 (98.0) 194 (88.2)
Note. Unless otherwise noted, the referent time periods for risk variables were the year previous to the most abusive event for
abused control women and the year previous to the femicide for femicide victims.
than 10% of the total) were conducted in
person rather than by telephone, and thus
we cannot evaluate the effects of this source
of bias. Finally, we have no way to compare
the control women who participated with
those who did not, and women living in the
most dangerous situations may have been
less likely to participate as control women. If
so, true exposure to the risk factors of inter-
est among women involved in abusive inti-
mate relationships may be greater than our
control data suggest, thus inflating our esti-
mates of increased risks associated with
these exposures.
CONCLUSIONS
In light of our findings, it is important to
consider the role medical professionals might
play in identifying women at high risk of inti-
mate partner femicide. The variables that re-
mained significant in model 6 are those most
important for identifying abused women at
risk for femicide in the health care system
and elsewhere, whereas those that were sig-
nificant in model 7 are particularly important
in prevention of the lethal incident itself.
When women are identified as abused in
medical settings, it is important to assess per-
petrators’ access to guns and to warn women
of the risk guns present. This is especially
true in the case of women who have been
threatened with a gun or another weapon
and in conditions of estrangement. Under fed-
eral law, individuals who have been con-
victed of domestic violence or who are sub-
ject to a restraining order are barred from
owning firearms. Judges issuing orders of pro-
tection in cases of intimate partner violence
should consider the heightened risk of lethal
violence associated with abusers’ access to
firearms.
Often, battered women like the idea of a
health care professional notifying the police
for them; however, with the exception of Cal-
ifornia, states do not require health care pro-
fessionals to report to the criminal justice sys-
tem unless there is evidence of a felony
assault or an injury from an assault.
38–40
In
states other than California, the professional
can offer to call the police, but the woman
should have the final say, in that she can
best assess any increased danger that might
July 2003, Vol 93, No. 7 | American Journal of Public Health Campbell et al. | Peer Reviewed | Research and Practice | 1095
RESEARCH AND PRACTICE
TABLE 3—Hypothesized Risk Factors for Intimate Partner Femicide Among Women Involved
in a Physically Abusive Intimate Relationship Within the Past 2 Years: Adjusted Odds Ratios
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7
Abuser age 1.10*** 1.08*** NS
Abuser race/ethnicity NS
Abuser education (reference group:
high school graduates)
Less than high school 1.40 NS
Some college 0.72 NS
College 0.31* NS
Abuser job status (reference group:
employed full time)
Employed part time 1.61 NS NS NS NS NS NS
Unemployed, seeking job 1.34 NS NS NS NS NS NS
Unemployed, not seeking job 5.09*** 6.27*** 4.00*** 3.24*** 4.28*** 4.42*** 4.35*
Victim age NS
Victim race/ethnicity NS
Victim education (reference group:
high school graduates)
Less than high school 1.61 NS NS NS
Some college 0.87 NS NS NS
College 0.31** 0.15* 0.28* NS
Victim job status (reference group:
employed full time)
Employed part time 0.95 NS NS
Unemployed, seeking job 0.13*** 0.25* NS
Unemployed, not seeking job 0.99 NS NS
General risk factors for homicide
Abuser problem drinker NS
Abuser used illicit drugs 4.76*** 2.19* 1.88* NS NS
Abuser mental health NS
Abuser threatened suicide NS
Abuser hurt pet NS
Abuser access to gun 7.59*** 9.21*** 8.28*** 5.44*** 5.38*** NS
Abuser arrest for violent crime NS
Victim problem drinker NS
Victim used illicit drugs NS
Victim sole access to gun 0.22* NS NS NS NS NS
Relationship variables
Married NS
Divorced NS
Time in relationship NS
Cohabitation (reference: living
together during entire past
year)
Living together less than 1 year NS
Previously lived together, 3.64**
separated at time of
incident
Never lived together 0.39** 0.30** 0.36* 0.34** 0.31**
Continued
result from the police being notified. An ex-
cellent resource for referral, shelter, and in-
formation is the National Domestic Violence
Hotline (1-800-799-SAFE).
If a woman confides that she is planning to
leave her abuser, it is critical to warn her not
to confront him personally with her decision.
Instead, she needs to leave when he is not
present and leave a note or call him later. It is
also clear that extremely controlling abusers
are particularly dangerous under conditions
of estrangement. A question such as “Does
your partner try to control all of your daily
activities?” (from the Danger Assessment
15
)
can quickly assess this extreme need for con-
trol. Health care professionals can also expe-
ditiously assess whether the perpetrator is un-
employed, whether stepchildren are present
in the home, and whether the perpetrator has
threatened to kill the victim. Under these con-
ditions of extreme danger, it is incumbent on
health care professionals to be extremely as-
sertive with abused women about their risk of
homicide and their need for shelter.
41
About the Authors
Jacquelyn C. Campbell, Phyllis Sharps, and Kathryn
Laughon are with the School of Nursing, Johns Hopkins
University, Baltimore, Md. Daniel Webster, Jennifer
Manganello, and Janet Schollenberger are with the
Bloomberg School of Public Health, Johns Hopkins Uni-
versity. Jane Koziol-McLain is with the School of Nursing,
Auckland University of Technology, Auckland, New
Zealand. Carolyn Rebecca Block is with the Illinois Crim-
inal Justice Information Authority, Chicago. Doris Camp-
bell is with the College of Medicine, University of South
Florida, Tampa. Mary Ann Curry and Nancy Glass are
with the School of Nursing, Oregon Health Sciences Uni-
versity, Portland. Faye Gary is with the College of Nurs-
ing, University of Florida, Gainesville. Judith McFarlane
is with the School of Nursing, Texas Women’s University,
Houston. Carolyn Sachs is with the School of Medicine,
University of California Los Angeles. Yvonne Ulrich is
with the School of Nursing, University of Washington,
Seattle. Susan A. Wilt is with the New York City Depart-
ment of Health. Xiao Xu is with Covance Inc, Washing-
ton, DC. Victoria A. Frye is with St. Luke’s Medical Cen-
ter, New York City.
Requests for reprints should be sent to Jacquelyn C.
Campbell, PhD, RN, Johns Hopkins University, School of
Nursing, 525 N Wolfe St, #436, Baltimore, MD 21205-
2110 (e-mail: jcampbell@son.jhmi.edu).
This article was accepted September 23, 2002.
Contributors
J. C. Campbell designed the study and wrote most of
the introductory and Discussion sections. D. Webster
analyzed the data, wrote most of the Results section,
and contributed to the Methods and Discussion sec-
tions. J. Koziol-McLain wrote the Methods section, con-
American Journal of Public Health | July 2003, Vol 93, No. 71096 | Research and Practice | Peer Reviewed | Campbell et al.
RESEARCH AND PRACTICE
TABLE 3—Continued
Victim left or asked abuser to leave 3.20** 2.40** NS
Victim–abuser had biological child NS
Victim had child by a previous 2.23** 1.70 1.94* 2.44** 2.35*
partner in home
Abuser–victim age difference NS
Abuser control of victim, verbal
aggression
Calls names NS
Not high control and separated 3.10* 3.36* 3.64* 3.10*
after living together
High control and not separated 2.90** 2.09* 2.08* 2.40*
after living together
High control and separated after 8.98*** 4.07* 5.52** 3.43*
living together
Abuser threats and stalking
Threatened to harm children NS
Threatened to harm family NS
Threatened victim with weapon 4.08*** 3.38*** 4.41*
Threatened to kill victim 2.60** 3.22** NS
Stalking NS
Physical abuse before worst incident
Abuse increasing in frequency NS
and severity
Choked (strangled) NS
Forced sex 1.87 NS
Abused when pregnant NS
Previous arrest for domestic 0.34** 0.31*
violence
Incident-level risk factors
Abuser used alcohol or drugs NS
Victim used alcohol or drugs NS
Abuser used gun 41.38**
Trigger: jealousy/victim left for 4.91***
other relationship
Trigger: victim left abuser for 4.04***
other reasons
Note. NS = nonsignificant.
*P < .05; **P < .01; ***P < .001.
tributed to the Results section, and prepared the tables.
J. Manganello contributed to the data analysis and Re-
sults sections. All other authors collected data, con-
tributed to the introductory and Discussion sections,
and reviewed the article.
Acknowledgments
This research was supported by joint funding from the
National Institute on Alcohol Abuse and Alcoholism,
the National Institute on Drug Abuse, the National In-
stitute of Mental Health, the National Institutes on
Aging, the Centers for Disease Control and Prevention,
and the National Institute of Justice (grant R01 # DA/
AA11156).
We would like to thank our advocacy, criminal jus-
tice, and medical examiner collaborators at each of the
sites, along with the women and family members who
told their stories. We also thank Arthur Kellerman,
MD, for his wise consultation and original ideas. Fi-
nally, we thank the staff of the Data Stat Survey Re-
search Firm and Jo Ellen Stinchcomb, Nadiyah John-
son, and the many other assistants and students for all
of their work.
Human Participant Protection
Institutional review board approval was obtained from
each study site. Informed consent was obtained by tele-
phone from all participants who were interviewed.
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