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Spouse aggression, depression, and physical health: a multivariate longitudinal study of midlife couples

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Spouse aggression, depression, and physical health: a multivariate longitudinal study of midlife couples

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SPOUSE AGGRESSION, DEPRESSION, AND PHYSICAL HEALTH:
A MULTIVARIATE LONGITUDINAL STUDY OF MIDLIFE COUPLES

by

Katrina A. Vickerman

F
A Dissertation Presented to the
ACULT HOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
Y OF THE USC GRADUATE SC
In Partial Fulfillment of the
R equir egree
DOCTOR OF PHILOSOPHY
ements for the D
(PSYCHOLOGY)

August 2010

Copyright 2010 Katrina A. Vickerman
ii
Acknowledgements
Foremost, I would like to thank Gayla Margolin. Gayla has been a consistent
source of support, inspiration, and encouragement for me. Her guidance and
example have been invaluable parts of my education. I feel extremely fortunate to
have Gayla as a mentor.
I would also like to acknowledge and thank my committee members for their
contributions to my education and their thoughtful suggestions for this research.
Jack McArdle provided invaluable guidance for both this project and my master’s
thesis. His teaching, willingness to consult, and recommendations pushed me to
have a stronger understanding of statistics and to learn new techniques. Beth
Meyerowitz taught one of my favorite courses, Health Psychology, and played a
significant role in my growing interest in this area. I strongly respect Beth’s
thoughtfulness and standards. I greatly appreciate Jerry Davison’s sense of humor
and the levity he often brings to groups. Jerry is a true philosopher and pushes his
students to critically think about research. His knowledge of many disciplines and
the thoughtful connections he makes often provide a unique and thought‐provoking
perspective. John Brekke was also a delight to have on my committee—very
friendly, supportive, and helpful with perspectives from his areas of expertise.
This work came from a large longitudinal study that would not have been
possible without the many families who gave their time to participate year after
year, as well as the efforts of many graduate and undergraduate students. I would
like to thank fellow graduate students from the Family Studies Project, Drs. Michelle

iii
Ramos and Deborah Chien, soon‐to‐be Drs. Sarah Duman Serrano, Lauren Spies, and
Esti Iturralde, and collaborators Drs. Pamela Oliver and Elana Gordis. These women
make our lab a wonderfully warm and supportive place. I feel incredibly lucky to
work with them and to have them as friends. I also thank Elyse Guran and Diana
Bennett for their responsiveness to my many questions and requests as I finished
my dissertation from a distance. I would like to thank a number of my fellow
graduate students who have been important sources of support since our first day at
USC: Dr . Jennifer Dave, Drew Mullane, Kris Stevens, and Dr. Sara Smucker‐Barnwell.
I am grateful to my parents, Jack and Beverly Vickerman, for all of their love
and support as I’ve worked on this research and on my degree. Finally, I would like
to thank Dino Marshalonis for being my biggest supporter and for being wonderful.

iv
Table of ontents C

Acknowledgements

ii
List of Tables
ures

v
List of Fig

vi
v Abstract

hapter 1: Introduction
d Study
ii
C
The Propose

1
25
Chapter 2: Methods
ts   Participan
Procedures
  Measures
nalyses

Statistical A

28
28
31
32
43

Chapter 3: Results
  Descriptive Information
l Health and Demographic Variables
ion, and the Physical Health Composite: Hypothesis
Physica
Aggression, Depress
Testing
odels

Exploratory M
n

hapter 4: Discussio
lusions
48
48
55

56
66
C 84
  Conc

104
106 References

Appendices:
Appendix A. Domestic Conflict Index
‐ Revised
ty of Life ‐Brief

123
Appendix B. Symptom Checklist 90 129
Appendix C. World Health Organization Quali

134
Appendix D. Health Questionnaire 137
152 Appendix E. Alcohol and Drug Questionnaire
an Correction
ation tables for emotional and physical
Appendix F. Heckm
Appendix G. Correl
aggression models

154

156

v
List of Tables
Table 1: Sample Demographic Information and Differences Between
Couples Who Provided and Did Not Provide Wave 4 or 5
Physical Health Data on Wave 1 Measures

on ent
29
Table 2: Health index descriptions and item c

t 37
Table 3: Model Variable Descriptive Statistics

Table 4: Husband and Wife Spouse Total Aggression, Husband and Wife
Depression, and Wife Physical Health Variables: Pearson
51
52
Correlations and Spearman Correlations

Table 5: Husband and Wife Spouse Total Aggression, Husband and Wife
Depression, and Husband Physical Health Variables: Pearson

Correlations and Spearman Correlations

Table 6: Husband and Wife Physical Health Scales: Pearson and
53
Spearman Correlations

54
Table 7: Differences in health variables by ethnicity status


able 8: Unstandardized, Standardized, and Significance Levels for
56
59 T
Hypothesized Model in Figure 2

Table 9: Model Comparisons Evaluating Hypothesized Relationships

able 10: Unstandardized, Standardized, and Significance Levels for
61
64 T
Hypothesized Model with Heckman Correction

Table 11: Model Comparisons Evaluating Hypothesized Relationships in
Model with Heckman Correction

66

vi
L
General theoretical model
ist of Figures

Figure 1:

igure 2: Hypothesized path model for spouse total aggression, depression,
and physical health composite
26
58 F

igure 3: Path model for spouse total aggression, depression, and health
conditions index

F

igure 4: Path model for spouse total aggression, depression, and subclinical
symptoms index
68
F

igure 5: Path model for spouse total aggression, depression, and preventive
care index
69
F

igure 6: Path model for spouse total aggression, depression, and health
behaviors index
70
F

igure 7: Path model for spouse total aggression, depression, and physical
health quality of life index
71
F

igure 8: Path model for spouse emotional / physical aggression, depression,
and physical health composite
73
F

igure 9: Path model for spouse emotional / physical aggression, depression,
and health conditions index
76
F

igure 10: Path model for spouse emotional / physical aggression,
depression, and subclinical symptoms index
77
F

igure 11: Path model for spouse emotional / physical aggression,
depression, and preventive care index
78
F

igure 12: Path model for spouse emotional / physical aggression,
depression, and health behaviors index
79
F

igure 13: Path model for spouse emotional / physical aggression,
depression, and physical health quality of life index
80
F

81

vii
Abstract
This longitudinal study examined relationships for male and female intimate
partner aggression with depression and physical health, and indirect effects of
aggression on health via depressive symptoms for 119 midlife couples. Physical and
emotional aggression victimization and perpetration were examined; for 63% of
couples both spouses reported at least one act of aggression over a three year
period, for 9% only the husband was aggressive, for 12% only the wife was
aggressive, and for 16% no partner aggression was reported. Path modeling
revealed associations for husband total aggression with husband depression and
with a composite variable of wife physical health, which combined measures
assessing heath conditions, subclinical symptoms, preventive care behaviors, health
behaviors, and physical health quality of life. There was a non‐significant indirect
effect from husband total aggression to the husband physical health composite via
husband depression, which was significant in the model examining physical
aggression only. Husband and wife aggression were positively correlated with
increased wife depression and, although relationships between aggression and wife
depression did not reach significance in the path model, model fit comparisons
indicated these were important relationships in the model. Wife total aggression
was not associated with husband outcomes or wife physical health. Finally, wife
depression did not serve as a mediating variable between aggression and wife
physical health. Exploratory post‐hoc models examined emotional and physical
aggression separately, and the five individual physical health indices. Associations

viii
between husband total aggression and wife physical health were similar in
emotional aggression models, but were not present when only physical aggression
was examined. Several total or indirect effects between husband aggression and
husband physical health via husband depression were present in the emotional and
physical aggression models.   Despite rates of reciprocal partner aggression, male
aggression was associated with more negative outcomes and appeared to have a
different impact and meaning than female aggression did for these community
couples, who were generally experiencing less severe forms of relationship violence.
Differential pathways of impact for aggression victimization versus aggression
perpetration were discussed, as were avenues for future research and implications
for behavioral health and partner aggression interventions.

1
Chapter 1: Introduction
Approximately one in four (23.6%) women and 11.5% of men experience
intimate partner physical aggression at some point during their lives and 1.4% of
women and 0.7% of men report victimization by an intimate partner in the previous
twelve months (Brieding, Black, & Ryan, 2008). Yielding even higher estimates,
nationally representative samples of non‐treatment seeking community adults
(Straus & Gelles, 1990) and of two parent households (McDonald, Jouriles,
Ramisetty‐Mikler, Caetano, & Green, 2006) found that 16% and 21% of couples,
respectively, report physical aggression each year. These numbers show the
prevalence of intimate relationship aggression and the presence of interspousal
aggression, even in intact and relatively longer‐term relationships. Research has
demonstrated that intimate relationship aggression is related to negative mental
health outcomes for women (Carbone‐Lopez, Kruttschnitt, & Macmillan, 2006;
Carlson, McNutt, Choi, & Rose, 2002; Coker et al., 2002; Gelles & Straus, 1990;
Laffaye, Kennedy, & Stein, 2003). Mental health consequences for male recipients of
intimate aggression have been studied less frequently, but associations also have
been found (Carbone‐Lopez et al., 2006; Coker, Weston, Creson, Justice, & Blakeney,
2005; Taft et al, 2006). Despite a recent increase in research examining physical
health consequences from aggression beyond injury or global health perceptions,
more information is needed about the relationship between marital aggression and
non‐healthy life styles and chronic medical conditions. Understanding aggression
and the associated mental and physical health consequences for specific populations

2
is an identified research priority, necessary for improving treatment and prevention
efforts (American Psychological Association [APA], 1996; Centers for Disease
Control and Prevention [CDC], 2002; Plichta, 2004; World Health Organization
[WHO], 2002). Researchers have pointed to the importance of examining linkages
between aggression, mental health, and physical health, but few such multivariate
investigations have been conducted (Plichta, 2004; Resnick, Acierno, & Kilpatrick,
1997; Weaver & Resnick, 2004).
Aggression in Marital Relationships
Researchers have found it useful to distinguish between different forms of
aggression, which tend to be linked to different types of relationships more
generally (Delsol, Margolin, & John, 2003; Dixon & Brown, 2003; Holtzworth‐
Munroe & Stuart, 1994). Johnson (1995; Johnson & Ferraro, 2000) differentiated
between common couple violence (more minor and often bidirectional aggression
escalating from breakdowns in communication) and intimate terrorism (severe,
primarily male‐to‐female aggression involving attempts to frighten and control
one’s partner). While aggressive relationships characterized as intimate terrorism
have been found to have more severe consequences (Graham‐Kevan & Archer,
2003), studies have shown that lower levels of marital aggression (i.e., common
couple violence) also have negative consequences. Vivian & Langhinrichsen‐Rohling
(1994) found that a group of low level, mutually aggressive spouses was more
similar to couples in highly victimized groups on impact of aggression scores than
couples who were maritally distressed and not aggressive. This suggests that even

3
low levels of marital aggression are important to consider. Similarly, Cascardi,
Langhinrichsen, & Vivian (1992) found no differences between mildly and severely
aggressive groups on psychological impact or injury, suggesting that the presence of
any marital aggression may be a risk factor for health consequences, regardless of
the perceived severity.   These data point to the relevance of studying relationships
that may include less severe, lower level aggression. Since more than half of
volunteer, community spouses may have experienced physical intimate aggression
(Gordis, Margolin, & Vickerman, 2005; Vickerman & Margolin, 2008), more research
is needed to understand the consequences of such aggression for women and men.
Bidirectional Aggression
A repeating controversy in the study of intimate violence is whether
aggression toward men is a critical issue. Data examining the national occurrence of
intimate violence, which includes intimate violence outside of marriage, show that
women are victimized at greater rates than men (Tjaden & Thoennes, 2000).
However, data from couples currently living together show that approximately half
of physical intimate aggression is bidirectional and that females and males
perpetrate similar amounts of unilateral aggression (Cascardi et al., 1992; Margolin,
1987; Vivian & Langhinrichsen‐Rohling, 1994); analogous findings are shown in
dating and newlywed samples (Archer, 2000; Capaldi & Owen, 2001; Foshee, 1996;
O’Leary et al., 1989). For example, Margolin (1987) reported that, over the course
of a year, for 29% of couples both partners perpetrated aggression, for 11% only the
female partner perpetrated physical aggression, and for 9% only the male was

4
physically aggressive, whereas 52% of couples reported no physical partner
aggression. Similarly, in a nationally representative sample of young adults, half of
aggressive relationships were bidirectional, and females were the aggressor in 70%
of the unidirectional aggressive relationships (Whitaker, Haileyesus, Swahn, &
Saltzman, 2007). A meta‐analysis examining male and female use of aggression in
intimate relationships concluded that women used more physical aggression on
average, although the effect size for this difference was small and sexual violence
was not considered (Archer, 2000).
These notable rates of aggression perpetrated by both genders suggest that
considering both partners’ use of aggression is necessary to obtain a more complete
understanding of relationship aggression from an interactive and synergistic
perspective (Vivian & Langhinrichsen‐Rohling, 1994). Feld and Straus (1990) show
that wives’ aggression at time 1 significantly increased the probability of husbands
perpetrating severe aggression at time 2. Schumacher & Leonard (2005) also found
evidence for a reciprocal effect with husbands’ aggression predicting later wife
aggression. Swan and colleagues found that increased violence victimization
frequency increased the likelihood that women themselves were aggressors (Swan,
Gambone, Fields, Sullivan, & Snow, 2005). Finally, Temple, Weston, and Marshall
(2005) report that aggression was more severe and frequent for couples in
bidirectionally aggressive relationships with one partner as the primary aggressor
versus couples with only one violent partner or two equally violent partners.
Another study found that bidirectionally aggressive relationships have greater odds

5
of injury for both males and females compared to unidirectionally aggressive
relationships (Whitaker, Haileyesus, Swahn, & Saltzman, 2007).
Although intimate partner aggression may be perpetrated at similar rates in
some populations, this does not mean that an act of aggression by a male partner is
analogous to an act of aggression by a female partner. Given gender differences in
physical size, and, hence, the likelihood of more serious injury for women than men
(Jacobson, Gottman, Gortner, Berns, & Shortt, 1996; Straus & Gelles, 1996),
aggression in marriage is likely to have more serious physical and emotional
consequences for women than men. From his meta‐analysis of partner aggression
studies, Archer (2000) concluded that women were at greater risk of physical injury
than male recipients of partner aggression. Similarly, National Crime Victimization
Survey data show more women than men are injured and killed due to intimate
partner violence (Rennison, 2003), and, in United States emergency rooms, the
majority of injuries (82%) related to intimate partner violence are sustained by
women (Saltzman, Mahendra, Ikeda, & Ingram, 2005). In a study focusing on
bidirectional partner aggression, females sustained significantly more injuries in
relationships in which both spouses were aggressive, but the male was the primary
perpetrator. However, no gender differences in injuries or impact were found in
relationships in which partners were equally aggressive, in relationships in which
only one partner was aggressive, nor in relationships in which both spouses were
aggressive, but the female was the primary aggressor (Temple et al., 2005).

6
Emotional Aggression
Although research on the consequences of marital aggression often focuses
on physical aggression, women have reported that experiences of emotional
aggression can have a more negative psychological impact than physical aggression
(Follingstad, Brennan, Hause, Polek, & Rutledge, 1991) and can be distressing, even
in the absence of physical aggression (Henning & Klesges, 2003; Marshal, 1996).
Much research on emotional aggression has examined female victims; however,
studies including both women and men have not found consistent gender
differences (Coker et al., 2002; Foshee, 1996; Hamby & Sugarman, 1999; Hines &
Saudino, 2003; Kasian & Painter, 1992; O’Hearn & Davis, 1997; Swan & Snow, 2002).
Psychological aggression has also been found to moderate the impact of physical
partner aggression on women’s mental health; this moderating effect was not found
for males’ victimization and mental health (Beach et al., 2004). Emotional
aggression may provide a context in which physical aggression occurs, or a way to
maintain control even if physical aggression desists (Marshal, 1996; Quigley &
Leonard, 1996). Emotional aggression thus may intensify or sustain negative
consequences of marital aggression, even if physical aggression stops over time.
Longitudinal Course of Marital Aggression
Although past aggression is a useful predictor of future aggression, for many
couples partner aggression does not stably continue year to year nor does it escalate
over time (Aldarando, 1996; Capaldi, Shortt, & Crosby, 2003; O’Leary et al., 1989;
Schumacher & Leonard, 2005; Vickerman & Margolin, 2008). Male to female

7
physical aggression may desist from one time point to the next for 23‐50% of
priorly aggressive males (Feld & Straus, 1990; Gordis et al., 2005; Quigley &
Leonard, 1996; Vickerman & Margolin, 2008), while a smaller proportion of couples
may become aggressive even though they didn’t report aggression in a prior time
point (Gordis et al., 2005; Vickerman & Margolin, 2008).
Few longitudinal studies have examined emotional and physical aggression
or aggression by both partners. O’Leary et al. (1989) found that only 8% of men and
17% of women in newlywed couples were stably aggressive over three years. Ten
years later, spouses’ physical aggression had significantly decreased, regardless of
severity; however, psychological aggression did not significantly change (Fritz &
O’Leary, 2004). Jacobson et al. (1996) report that even if husbands reduce physical
aggression over time, emotional abuse may continue. Aldarondo (1996) found that
only husbands who were physically aggressive at year 1 and not years 2‐3
significantly reduced their emotional aggression, and husbands who were stably
physically aggressive had the highest levels of emotional aggression towards their
wives. Consideration of both spouses’ physical and emotional aggression over time
appears relevant in understanding the consequences of aggression. The instability
and fluctuating patterns of partner aggression call for a more thorough
consideration of aggression perpetration over time than offered by reports at a
single time point or attempts to classify couples as aggressive or non‐aggressive.
Finally, more information is needed on the health consequences of accumulated
levels of aggression to understand longer‐term effects.

8
Mental Health Consequences of Marital Violence: Depression
Multiple studies show a relationship between intimate aggression and
depressive symptoms for females (Carbone‐Lopez et al., 2006; Cascardi & O’Leary,
1992; Fergusson, Horwood, & Ridder, 2005; Golding, 1999; Haj‐Yahia, 2000; Loxton,
Schofield, & Hussain, 2006; O’Campo, Woods, Jones, Dienemann, & Campbell, 2006;
Stets & Straus, 1990; Temple et al., 2005; Vivian & Malone, 1997), and some studies
also show a relationship for males (Fergusson et al., 2005; Grandin, Lupri, &
Brinkerhoff, 1998; Vivian & Langhinrichsen‐Rohling, 1994). Increased severity and
frequency of physical aggression have been linked to more depressive symptoms
(Cascardi & O’Leary, 1992; Gleason, 1993; Golding, 1999). A large random digit dial
study in the northeastern United States found that women victimized by intimate
partner violence (IPV) in the last five years were 2.7 times more likely to report
severe depressive symptoms and women more remotely victimized still had a 1.6
times increased risk for severe depressive symptoms (Bonomi et al., 2006). In a
study with similar methodology, older men (age 55+) who had experienced physical
intimate partner violence had 2.8 and 3.1 times increased odds of minor and severe
depressive symptoms, respectively, and older men with psychological intimate
partner violence victimization were 2.6 times more likely to experience minor
depressive symptoms.   These relationships weren’t present for men under age 55
(Reid et al., 2008). In a large study of primarily African‐American men presenting
for emergency room care, compared to men with no intimate partner violence
exposure, men who had been victims only, perpetrators only, and both victims and

9
perpetrators of intimate partner violence had 2.92, 2.26, and 12.10 increased
prevalence ratios of moderate to severe depression, respectively, pointing to the
importance of examining bidirectionality in partner violence (Rhodes et al., 2009).
Depression has also been linked to being both the aggressor and victim in violent
relationships for women (Anderson, 2002; Grandin et al., 1998).
Both physical and emotional aggression have been correlated with
depression (Campbell, Kub, Belknap, & Templin, 1997; Haj‐Yahia, 2000; Nixon,
Resick, & Nishith, 2004) with some suggestion that emotional aggression may be a
stronger predictor of depression than physical aggression is (Coker et al., 2002;
Sackett & Saunders, 1999; Taft et al., 2006). To explain the stronger link sometimes
found between psychological, rather than physical, aggression and depression,
several aspects of psychological aggression have been highlighted, including its
pervasiveness, its overlooked importance, and its function of disrupting an
individual’s wellbeing and sense of self (Taft et al, 2006). Psychological aggression
also has been found to predict significantly increased severity of depression, even in
the absence of physical aggression, and to result in depression levels that were
statistically indistinguishable from those of women who were both physically and
psychologically abused (Pico‐Alfonso et al., 2006).
Some have argued for the presence of a reverse relationship between
psychiatric conditions and violence victimization; in other words, those with prior
psychiatric conditions are at an increased risk for later abusive relationships, which
would also explain the link between abuse and post‐abuse symptomatology.

10
However, in a longitudinal investigation, Ehrensaft, Moffitt, and Caspi (2006) found
that partner‐assaulted women had an increased risk of depression, even after
controlling for prior levels of psychopathology. In a second longitudinal study,
women who reported partner aggression victimization at a first assessment had
significantly higher depression scores five years later (Schei, Guthrie, Dennerstein, &
Alford, 2006). Quigley and Leonard (1996) provide evidence that desistance from
husband aggression over 3 years leads to decreases in wives’ depression, whereas
wives whose husbands did not desist increased in depressive symptoms. Romito,
Turan, & Marchi (2005) examined women’s experiences with past and current
interpersonal violence (including partner, family, acquaintance, and stranger
aggression) and concluded that women with both past and current aggression had
the highest odds of reporting current elevated levels of psychological distress,
followed by those reporting current but no past, those reporting past but no current
victimization, and women experiencing no interpersonal victimization. More
research is needed to examine the relationship between different types of intimate
aggression and depression in males and females over time, particularly with
community couples in relatively stable marital relationships.
Aggression and Health Outcomes
  Prior to the last five to ten years, studies examining health‐related
consequences of aggression focused predominantly on immediate injuries and
healthcare usage. Studies report that women, more than men, are likely to be
injured, receive medical treatment, be hospitalized, receive mental health treatment,

11
and take time off from work due to a partner’s aggressive behavior (Archer, 2000;
Breiding, Black, & Ryan, 2008; Cantos, Neidig, & O’Leary, 1994; Cascardi et al., 1992;
Foshee, 1996; Langhinrichsen‐Rohling et al., 1995; Tjaden & Thoennes, 1998, 2000).
Stets and Straus (1990) reported similarities between men and women in time
taken off work and number of days in bed in the last month, both of which were
higher for spouses in aggressive than non‐aggressive relationships. From an
economic impact perspective, a recent large‐scale telephone study of females in a
health maintenance organization (HMO) determined that women with a history of
intimate partner violence used more healthcare services than non‐IPV women for at
least five years following their last abuse incident. Partner victimized women were
estimated to have 19% higher healthcare costs annually. Assuming a 44%
prevalence rate of exposure to intimate partner violence, this translates into an
estimate of almost $20 million dollars excess cost for every 100,000 female HMO
members per year (Rivara et al, 2007). Brown, Finkelstein, & Murphy (2008)
estimate a $2.3 to 7.0 billion IPV‐related medical cost burden in just the first year
following victimization for women in the United States.
A growing number of investigations have focused on health implications of
intimate partner violence for women in specific health populations, samples
selected for aggression (i.e., women from domestic violence shelters), or in other
specific populations. Studies have shown that battered women are at increased risk
for chronic medical conditions and gastrointestinal problems (Drossman, Talley,
Leserman, Olden & Barreiro, 1995; Talley, Fett, & Zinsmeister, 1995); have more

12
surgical procedures (Leserman et al., 1996; Lown & Vega, 2001); have increased
odds of bone or joint problems, high blood pressure, and heart problems (Lown &
Vega, 2001); and show impaired immune functioning (Garcia‐Linares, Sanchez‐
Lorente, Coe, & Martinez, 2004). Females victimized by intimate partner violence
also report generally poorer health and an increased numbers of adverse symptoms
(Hurwitz, Gupta, Liu, Silverman, & Raj, 2006; Lown & Vega, 2001); increased pain
symptoms (Fisher & Regan, 2006), more non‐gastrointestinal somatic symptoms
(Leserman et al., 1996; Lown & Vega, 2001); and have more problems with sleep,
fatigue, and nightmares (Rasmussen, 2007). A systematic review of the impact of
physical partner aggression on women’s sexual health concluded that IPV is
consistently related to impaired sexual health, particularly sexual risk taking
behaviors, sexually transmitted infections, unwanted pregnancy and induced
abortions, and sexual dysfunction (Coker, 2007).
There has been a recent proliferation of larger generalizable samples,
nationally representative samples, and multi‐country studies examining
associations between partner aggression and health outcomes. These investigations
provide important prevalence estimates and generalizable data that could not be
garnered from previous studies, and have strengthened a number of gaps in this
literature. A large U.S. healthcare organization‐based study found that women with
a history of physical and/or sexual victimization were 2.8 times more likely to
report fair or poor health (versus good to excellent health) than women with no
victimization history (Bonomi et al., 2006). In a 15‐site international study

13
conducted by the WHO, women who had been physically or sexually abused by an
intimate partner had 1.6 greater odds of reporting poor or very poor health
compared to non‐victimized women, after controlling for demographic variables
(Garcia‐Moreno, Jansen, Ellsberg, Heise, & Watts, 2006), as well as increased odds of
mobility problems, problems completing daily activities, pain, memory loss,
dizziness, and vaginal discharge (Ellsberg, Jansen, Heise, Watts, & Garcia‐Moreno,
2008). Large investigations also have found intimate partner aggression is linked to
significantly increased odds of bone or joint problems, digestive problems, chronic
pain, high blood pressure or heart problems (Fisher & Regan, 2006), increased odds
of reporting a health problem requiring medical attention in the last year (Diop‐
Sidibe, Campbell, & Becker, 2006), increased odds of “poor” self‐rated health,
psychosomatic complaints, gynecological problems, and injuries (Neroien & Schei,
2008), increased risk for poor health, sexual dysfunction, and sexually transmitted
infections (Parish, Wang, Laumann, Pan, & Luo, 2004), increased prevalence of
asthma, migraine, kidney/urinary tract disease, pain and somatic symptoms, and
sleep problems (Eberhard‐Gran, Shei, & Eskild, 2007), and higher impairment than
national average levels in the domains of bodily pain, general health, physical
functio ). ning, and physical role limitations (Alsaker, Moen, Nortvedt, & Baste, 2006
Studies also have not found several aggression‐health links noted in other
studies. For example, in a large Norwegian study, high blood pressure, cancer,
cardiovascular disease, and gastrointestinal tract diseases did not occur at higher
rates for women exposed to physical or sexual violence in the previous year, and

14
fibromyalgia, diabetes, hyper/hypothyroidism, and muscular/skeletal system
diseases occurred at higher rates for women exposed to sexual violence, but not
women exposed to physical violence (Eberhard‐Gran, Shei, & Eskild, 2007). A
random sample of women in a large U.S. health plan showed links between prior
year IPV victimization and increased odds for chart diagnoses of acute respiratory
infection, some female reproductive problems, gastroesophageal reflux, abdominal
pain, urinary tract infections, sexually transmitted diseases, some musculoskeletal
problems, headaches, lacerations, and contusions. Increased odds were not found
for respiratory problems, obesity, sleep problems, neurologic syndromes,
musculoskeletal fractures/dislocations, irritable bowl syndrome, thyroid disease,
type 2 diabetes, allergies, and cardiovascular diseases (Bonomi, Anderson, Reid et
al., 2009).
In a number of investigations, women’s physical abuse also has been
associated with fewer healthy behaviors and more health compromising behaviors,
such as smoking, problem drinking, and illegal drug use (Ackerson, Kawachi,
Barbeau, & Subramanian, 2007; Bonomi et al, 2006; Carbone‐Lopez et al., 2006;
Kilpatrick, Acierno, Resnick, Saunders, & Best, 1997; Lemon, Verhoek‐Oftedahl, &
Donnely, 2002; Tomasulo and McNamara, 2007; Vest, Catlin, Chen, & Brownson,
2002), as well as decreased appetite and hypersomnia (Diez et al., 2009). Tomasulo
& McNamara (2007) found that, compared to non‐abused women, women with
abuse experiences had poorer scores on a questionnaire examining a range of health
behaviors.

15
Limited and at times conflicting data are available regarding IPV and
women’s preventive care behaviors. A number of studies have found that women
victimized by partner violence use healthcare resources at a higher rate (Tomasulo
& McNamara, 2007; Bonomi, Anderson, Rivara, & Thompson, 2009). In a statewide
study, physical and psychological IPV and non‐IPV women accessed medical care
and received clinical breast exams at the same rate, and physical IPV women
showed increased odds of receiving a regular PAP smear (Lemon, Verhoek‐Oftedahl,
& Donnelly, 2002). In another study, interpersonal physical violence exposure (not
limited to partner violence) was not linked to self‐reported use of preventive care
services; however, women’s safety concerns were linked to a decreased likelihood
of obtaining regular cervical cancer testing, clinical breast examinations, and
mammograms. No differences were found for cholesterol or blood pressure testing
(Cronholm & Bowman, 2009).
Fewer studies examining health outcomes have separately examined
emotional aggression. However, both emotional and physical intimate aggression
have been associated with the number and severity of health symptoms in abused
women (Follingstad et al., 1991). A study of community couples found that, after
controlling for physical aggression, psychological aggression victimization was
associated with higher reports of negative health symptoms for both men and
women. When physical aggression was examined, controlling for psychological
aggression, the link between aggression and health was no longer found (Taft et al,
2006).   Higher emotional aggression has also been associated with chronic disease

16
for women, but not for men (Coker et al., 2002). Both psychological and physical
aggression have been linked individually to increased odds of smoking, with the
highest rates among women who had experiences with both psychological and
physical abuse (Jun, Rich‐Edwards, Boynton‐Jarrett, & Wright, 2008). In a WHO
study in Japan, emotional abuse only and emotional abuse plus physical or sexual
violence led to an increased odds of reporting fair to very poor health compared to
no IPV women, but there were no significant differences between the two IPV‐
exposed groups. Women with emotional plus physical/sexual abuse experiences
showed higher numbers of adverse symptoms than emotional abuse only women,
and both groups were higher than non‐IPV women (Yoshihama, Horrocks, &
Kamano, 2009). Other studies have found that only increased co‐occurrence of
aggression types (psychological, physical, and sexual) and increased duration or
accumulation of exposure (greater than 1 year versus less than one year) lead to
significantly higher odds of chronic disease (Ruiz‐Perez, Plazaola‐Castano, & Rio‐
Lozano, 2007). In terms of healthcare dollars, compared to women who have not
experienced intimate partner violence, women experiencing only psychological
abuse have 13‐33% higher annual healthcare costs, whereas women experiencing
physical or sexual abuse (often in conjunction with psychological abuse) were found
to have 19‐42% higher annual healthcare costs (Bonomi, Anderson, Rivara, &
Thompson, 2009).
Research has focused primarily on the impact of male violence on women’s
health. The few investigations addressing health outcomes for men have shown

17
links with some health variables, but delivered mixed findings. Physical intimate
aggression has been associated with poorer health for both men and women
(Carbone‐Lopez et al., 2006; Coker et al., 2002; Parish et al., 2004), with the
associations appearing to be stronger for women than men (Carbone‐Lopez et al.,
2006). A study of males in a large healthcare system did not find links between
physical or psychological intimate partner violence victimization and general health
ratings, somatic symptoms, or a physical health component score (Reid et al., 2008).
In a college sample, male and female victims of IPV showed increased health risk
behaviors, including higher alcohol and drug abuse rates, and higher rates of driving
or riding with a driver under the influence of substances (Simons, Gwin, Brown, &
Gross, 2008). In a study examining intimate partner violence victimization and
perpetration, compared to men without IPV experiences, males who were both
perpetrators and victims had significantly increased prevalence of drug and alcohol
abuse, and smoking cigarettes, whereas male victims only had an increased
prevalence of smoking and male perpetrators did not differ from non‐IPV men
(Rhodes et al., 2009). Finally, in another study both male and female physical and
psychological aggression victimization was linked to poorer physical health, with no
significant interaction for gender. This study noted that a third of females and a
fourth of males self‐disclosed partner aggression perpetration as well, but this was
ot exa n mined in the analyses (Straus et al., 2009).
Related to the question of the bidirectionality of partner aggression is the
severity of violence. Some studies have shown increased risks only with aggression

18
accumulation (Ruiz‐Perez et al., 2007), and increased risk for current or recent
versus past aggression (Bonomi et al., 2006). Whereas other studies have examined
lifetime violence exposure and highlight continued impacts of past aggression or
accumulated aggression (Garcia‐Moreno et al., 2006). In two large surveys, dose‐
response relationships were found between aggression victimization and adverse
physical health, but the authors stressed that even “low‐severity” (“pushed or
grabbed” or “threatened to hurt you”) and “low magnitude” (experiencing physical
abuse “a few times” versus “many times”) abuse showed associations with poorer
health (McCauley, Kern, Kolodner, Derogatis, & Bass, 1998; Wijma, Samelius,
Wingren, & Wijma, 2007).
Much of the aggression and physical health research has relied on cross‐
sectional data and retrospective reporting, but a growing number of studies have
used longitudinal data or established temporal order between abuse and negative
health outcomes. In a five year study, Temple et al. (2005) found that women in
bidirectionally aggressive couples with a male primary perpetrator had lower
health optimism and reported lower health quality of life than women in nonviolent
or female‐only violent couples. In a longitudinal study of low‐income women,
chronic exposure to intimate partner violence predicted a higher number of chronic
health problem diagnoses, whereas current intimate violence victimization
predicted problems with employment (Staggs & Riger, 2005). In an Australian
population‐based cohort study, women reporting a history of IPV at an initial time
point reported lower levels of sexual health, a higher number of respiratory

19
problems, and a greater number of symptom complaints than non‐abused women at
a five‐year follow‐up assessment (Schei et al., 2006). In a one year follow‐up of
women who had left an abusive partner, no significant improvements were found in
physical health quality of life, which were below average at baseline, despite some
improvement in mental health and vitality domains (Alsaker, Moen, & Kristoffersen,
2008). Finally, another longitudinal investigation found that women with ongoing
abuse experiences (reported IPV at initial assessment and at follow‐up 9.5 months
later) reported an increased number of adverse physical symptoms at follow‐up,
whereas women with abuse only at time 1 showed no significant mean change in
symptoms and women with no abuse reported decreased symptoms at follow‐up
(Gerber, Wittenberg, Ganz, Williams, & McCloskey, 2007).
Studies focusing on physical health consequences of aggression have often
used clinical or medical samples and collapsed rape victims, physical aggression
victims, and/or victims of child abuse, but have not focused on the health effects of
marital aggression in long‐term relationships. Similarly, other studies have
examined relationships between domestic violence and health in samples selected
for presence or levels of aggression (i.e., samples of women seeking safety in
domestic violence shelters). There has been a recent increase in studies that
examine physical health correlates specifically for intimate partner aggression,
however a number of these investigations have relied on one general health
perception question (i.e., “How would you rate your overall health?”, with answer
choices ranging from poor to excellent) or presence of a list of chronic conditions. A

20
more nuanced examination of health and health behaviors is necessary to increase
knowledge about consequences of intimate partner violence. Finally, few
investigations have used longitudinal data or established temporal order between
partner aggression victimization and health symptoms or problems.
Aggression, Depression, and Health Outcomes
Depression and other mental health impacts may be more proximal
consequences of intimate aggression, which, over time, and even if recovered from,
may precipitate negative physical health problems. Relatedly, reviews have found
that marital functioning has both direct and indirect effects on health, with indirect
effects possibly accounted for through depression or health habits (Burman &
Margolin, 1992; Kiecolt‐Glaser & Newton, 2001). Depression has been directly
linked to negative health (Wells et al., 1989), with findings that even as depression
improves with treatment, physical symptoms may initially show some
improvement, but then plateau and persist (Greco, Eckert, & Kroenke, 2004). More
generally, accumulations of stress and chronically stressful life situations have been
connected to adverse health even more strongly than acute stressful life events, with
recent literature focusing on the mechanisms through which these stressful life
circumstances impact physical health (Tosevski & Milovancevic, 2006).
Researchers have called for investigations to identify mechanisms linking
intimate partner violence and physical health consequences and have proposed
theoretical models outlining potential mechanisms. Dutton et al. (2006) state that
the most important research on intimate partner violence in the past twenty years

21
contributed to our understanding of the physical and mental health consequences of
IPV. These authors suggest that the most important findings in the next decade will
focus on explaining the mechanisms accounting for the connection between
intimate partner violence and impaired physical health.   As part of this examination,
the authors propose that it will be necessary to examine differential outcomes and
pathways for women who have had different types of abuse experiences, citing
studies that have found a unique relationship between psychological abuse and
adverse health (e.g., Taft et al, 2006). Similarly, Cromer and Sachs‐Ericsson (2006)
suggest that the relationships between prior abuse and later physical health
impairments may not be direct, but instead mediated by victims’ reactions to the
abuse (e.g., PTSD). Cognitive variables, such as hostility, have also been proposed as
a potential link between abuse history and negative health outcomes (e.g.,
cardiovascular disease and metabolic syndrome) (Kendall‐Tacket, 2005). There
have been calls for more longitudinal investigations to clarify the links between
intimate partner aggression, mental health, and adverse physical outcomes (Woods,
2005), as well as calls for more longitudinal examinations evaluating health
conseq 05a). uences of aggression for both men and women (Holtzworth‐Munroe, 20
One of the most encompassing models detailing potential mechanisms
through which aggression may impact physical health was put forth by Resnick et al.
(1997). Their model suggests links between intimate partner violence and health
through acute injury, increased stress, and mental health problems. Increased
stress and mental health problems were then theorized to impact physical health

22
risk through impaired immune system functioning, increased health risk behaviors,
and inappropriate utilization of heath care. It was also suggested that acute physical
injury and problems can lead to more chronic physical injuries, which then lead to
health problems.
Despite the recent increase in empirical investigations of intimate partner
violence and physical health, few multivariate examinations of aggression, mental
health, and physical health have been conducted. Several studies have examined
multivariate links between partner aggression victimization, PTSD, and hormone
levels, indicators of immune functioning, or physical health symptoms (Woods et al.,
2005; Woods, Hall, Campbell, & Angott, 2008). There is some suggestion that PTSD
plays a particularly important role in the link between trauma exposure and health
for sexual assault victims (e.g., Clum, Calhoun, & Kimmerling, 2000; Dutton et al.,
2006; Golding, Cooper, & George, 1997). However, mechanisms may be different for
different populations. For example, rape victims seen in medical settings may be
particularly likely to have one acute trauma event, more likely to have been injured,
and have high rates of PTSD. In this type of population, PTSD may explain much of
the variance between trauma exposure and later impaired health. Similarly, partner
abuse classified as intimate terrorism may lead to increased risk for severe injury
and higher rates of classic PTSD symptoms. However, in longer‐term marital
relationships characterized by multiple incidents of lower level intimate partner
aggression or chronic versus acute trauma exposure, the classic constellation of
PTSD symptoms may be less fitting and different mental health factors may be more

23
relevant, particularly given that the “post” requirement of post‐traumatic stress
disorder is not relevant for women in ongoing aggressive relationships (Mechanic,
2004). Examining symptoms of depression may provide additional information on
the connection between partner violence exposure and impaired health.
Few multivariate investigations of partner aggression, depression, and
physical health exist. Perhaps the most relevant investigation examined data from a
community sample of women and found indirect effects of abuse‐related stress
through depression on an adverse health construct, which included a question
regarding general health perception and symptom severity ratings (Sutherland,
Bybee, & Sullivan, 2002). In a sample of female victims of intimate aggression seen
in medical clinics, depression accounted for a significant amount of variance in
health‐related quality of life (Laffaye, Kennedy, & Stein, 2003). Clum et al. (2000)
concluded that psychological reactions to sexual assault (i.e., depression and PTSD)
among college students at least partly account for the link between trauma history
and self‐reported health symptoms, as well as partly accounting for the link
between trauma history and global health perceptions. Hurwitz et al. (2006)
conducted qualitative interviews with small group of South Asian abused women in
the northeastern United States. These women described how abuse‐related
depression and anxiety negatively influenced their eating habits, sleep patterns,
energy, and other health‐related constructs.   Finally, studies have also indicated
that there may be direct effects of intimate partner violence on physical health aside
from potential indirect effects through mental health. In a sample of general

24
internal medicine patients, intimate partner violence was linked to increased
adverse chronic health symptoms after controlling for depression and PTSD
symptoms (Nicolaidis, Curry, McFarland, & Gerrity, 2004). Similarly, lifetime IPV
exposure also was linked to increased severity of physical symptoms after
controlling for depression, whereas this association was not found between
women’s childhood abuse histories and physical health (Nicolaidis, McFarland,
Curry, & Gerrity, 2009).
In summary, there has been a recent increase in the number of studies
specifically examining the link between intimate partner violence and physical
health outcomes. Many earlier studies focused on samples selected from particular
medical populations/settings (e.g., women with fibromyalgia or from
gastrointestinal clinics) or selected for women’s experiences with violence (e.g.,
from domestic violence shelters). Also, many studies have collapsed child abuse and
adult relationship aggression or collapsed multiple types of interpersonal
aggression (e.g., including stranger physical assault or rape). Despite the increase in
use of samples not selected for one of the key variables and larger, more
representative samples, few studies have examined mechanisms through which
intimate partner violence impacts health. Finally, many studies have been cross‐
sectional, used retrospective reports, and used very limited assessments of physical
health (e.g., one global question regarding perception of health being poor to
excellent). Research is needed with other samples, including ones involving men, to

25
examine further potential links between intimate partner aggression, mental health
symptoms, and physical health consequences.
T oposed Study
The proposed study examines emotional and physical aggression
perpetrated by husbands and wives over three years, depressive symptoms, and
physical health outcomes for both spouses approximately three years later. The
present study focuses on middle‐aged community couples, in relatively stable
relationships, who were not specifically selected for levels of aggression,
presentation for therapy, or specific medical problems or diagnoses. A volunteer
community sample is used to study the most common types of marital aggression in
couples who have long‐term marriages. This sample also allows for the assessment
of aggression perpetrated and received by both spouses. Since rates of intimate
aggression appear to peak in the early to mid twenties and then decline over the
lifespan (Fritz & O’Leary, 2004; Suitor, Pillemer, & Straus, 1990), findings from
young adult samples may not generalize to these middle‐aged couples. This sample
is ideal for evaluating the health consequences of accumulated levels of aggression
in long‐term intact marital relationships. Investigating intimate violence over the
lifespan, evaluating specific types of aggressive relationships, and examining health
consequences for these specific populations are identified research priorities (APS,
1996; CDC, 2002; WHO, 2002). A strength of this study is that both husbands and
wives report on their own and their spouse’s aggression. Despite moderate
reliability between spouses’ reports of aggression (Margolin, 1987; O’Brien, John,
he Pr

26
Margolin, & Erel, 1994; O’Leary & Arias, 1988), it is generally concluded that
researchers attain a more complete picture of relationship aggression with two
reporters.
The primary goal of this study is to evaluate how accumulated levels of
marital aggression affect mental health symptoms, specifically depressive
symptoms, and in turn, how depression impacts physical health outcomes (for
general theoretical model, see Figure 1.)

Figure 1. General theoretical model


Seven hypotheses are examined. The first three examine the effect of
accumulated partner aggression on each spouse’s depressive symptoms:
Hypothesis 1: Accumulated levels of aggression victimization will have direct
effects on depressive symptoms.
Hypothesis 2: Partner aggression victimization has stronger effects on wife’s,
than husband’s, depressive symptoms.
Hypothesis 3: Aggression victimization has a stronger influence, than
aggression perpetration, on depressive symptoms.

27
Paralleling hypotheses 1‐3, the second three hypotheses examine the effect of
accumulated partner aggression on each spouse’s physical health symptoms:
Hypothesis 4: Accumulated levels of aggression will have direct effects on
health outcomes for husbands and wives.
Hypothesis 5: Partner aggression victimization has a stronger effect on
health outcomes for wives than husbands.
Hypothesis 6: Spouse’s aggression victimization has a stronger influence,
ical health. than aggression perpetration, on spouse’s phys
The final hypothesis examines indirect effects:
Hypothesis 7: Aggression has an indirect effect on health outcomes through
depressive symptoms for husbands and wives.

28

Chapter 2: Methods
Participants
Participants for this study come from the Family Studies Project, a six wave
longitudinal project evaluating the effects of family conflict and community violence
on family processes and children’s functioning. The sample originally was recruited
through notices, advertisements, and word of mouth in the Los Angeles community.
Inclusion criteria for wave 1 required that: (a) each family unit included two parents
and a 9‐10 year old child, (b) both parents and the child had resided together at
least for the last three years, and (c) each family member could complete the
research protocol in English. The current study utilized husbands’ and wives’ data
from waves 1‐5.
One hundred nineteen families participated in the study at wave 1.
Demographic information for these families is reported in Table 1. Participants
were not asked separately about race and ethnicity in wave 1; therefore, this
information is reported together. The sample reflected the ethnic diversity of the
Los Angeles area, with the exception of a lower percentage of Hispanic/Latino
couples, likely related to the study requirement for couples to be able to complete
all materials in English. Ten percent of the sample was below the national poverty
level for family size at Wave 1.
Of the original 119 families, 102 families returned for wave 2, 103 returned
for wave 3, and 83 returned for wave 4. On average, there were M = 1.1 (SD = 0.3)

29
years between waves 1 and 2, M = 1.3 (SD = 0.3) years between waves 2 and 3, and
M = 2.70 (SD = .47) between waves 3 and 4. Wave 5 data collection is still in
progress. Wave 5 physical health data were used for eight wives and eight husbands
who either did not participate in wave 4 or who completed a subset of the
questionnaires in wave 4 but did not complete health data. In total, 90 couples
provided data on the Health Questionnaire (HQ) and the World Health Organization
uality of Life Interview‐brief version (WHOQOL‐bref) in wave 4 or 5. Of these 90 Q

Table 1. Sample Demographic Information and Differences Between Couples Who
Provided and Did Not Provi r 5 P easures de Wave 4 o
All Couples
(N=119)
hysical Health Data
Have Physical
Health Data
on Wave 1 M
(n = 90)
No Physical
Health Data
(n = 29)
Wave 1 Measures M SD M SD M SD
t‐
Ratio
Wife Age 38.50 5.90 38.85 6.02 37.42 5.44 ‐1.14
Husband Age 40.96 6.77 40.81 6.53 41.41 7.55 .42
Wife Year
Education
s 14.26 2.49
14.33 2.38 14.04 2.84 ‐.55
Husband
Education
14.13 2.50 14.37 2.41 13.38 2.69 ‐1.87
Family Income $66,900 $37,100 $68,700 $36,000 $61,400 $40,800 ‐.92
Number of
Children
2.82 1.47
2.68 1.39 3.28 1.62 1.93
Years Living
Together
13.69 4.76 13.98 4.91 1 2.79 4.19 ‐1.17
Years Married 11.55 6.03 12.20 5.80 9.52 6.36 ‐2.12*
Wife Phys. Aggr.
b
1.36 2.54 1.34 2.58 1.41 2.49 .13
Wife Emo. Aggr.
b
2.40 4.15 2.14 3.71 3.21 5.30 1.20
Husband Phys.
Aggr.
b
.73 1.82 .67 1.72 .93 2.10 .68
Husband Emo.
Aggr.
b
1.50 3.08 1.53 3.16 1.41 2.87 ‐.18

30
Table 1, Continued. Sample Demographic Information and Differences Between
Couples Who Provided and Did Not Provide Wave 4 or 5 Physical Health Data on Wave
1 Measures
All Couples
(N=119)
Have Physical
Health Data
(n = 90)
No Physical
Health Data
(n = 29)
Wave 1 Measures M SD M SD M SD
t‐
Ra tio
Wife Depression 1.56 .53 1.55 .51 1.57 .59 .14
Husb
Depression
and 1.35 .42
1.35 .33 1.34 .63 ‐.09
a
Wife
y Race/Ethnicit
% (n)
% (n) % (n ) χ
2
(3)
African Amer. 24.4% (29) 21.1% (19) 34.5% (10)
Caucasian 30.3% (36) 31.1% (28) 27.6%   (8)
Hispanic/Latina 29.4% (35) 31.1% (28) 24.1%   (7)
Other o
/multiracia
r mixed
l
16.0% (19) 16.7% (15) 13.8%   (4)
0.54
Husband
y Race/Ethnicit
% (n) % (n) % (n ) χ
2
(3)
African Amer. 24.4% (29) 20.0% (18) 3 7.9% (11)
Caucasian 31.9% (38) 33.3% (30) 27.6% (8)
Hispanic/
  Latino
26.9% (32)
28.9% (26) 20.7% (6)
Other or mixed

16.8% (20) 17.8% (16) 13.8% (4)
.28
/multiracial
a
Levene’s Test for Equality of Variances was significant. T‐ratio for equal variances not assumed reported.
b

hese variables are not normally distributed; Mann‐Whitney U non‐parametric analyses also non‐significant.
mo. Aggr. = Emotional Aggression. Phys. Aggr. = Physical Aggression. *p < .05
T
E

couples providing physical health data, 77 spouses completed both the HQ and
WHOQOL‐bref. For the remaining 13 couples, information was provided only by the
wife (five couples) or only by the husband (four couples), one of the two health
measures was missing for the husband (three couples), or one of the two health
measures was missing for the wife (one couple). Overall, 85 wives provided HQ

31
data and 86 wives completed WHOQOL‐bref data. Eighty‐three husbands provided
HQ data and 84 husbands completed WHOQOL‐bref data.
Eighty‐eight (73.9%) couples participated in the first three waves and
provided some physical health data in wave 4 (or wave 5), 12 (10.1%) couples
participated in three of the four time points, 7 (5.6%) families participated in two
time points, and 12 (10.1%) families were only seen at the first time point. Table 1
reports t‐tests comparing wave 1 demographic information, spouse aggression, and
depressive symptoms for families who provided health data in wave 4 or 5 versus
families who did not participate in those waves or did not provide physical health
data. Physical health data are not available from wave 1 for comparisons between
returning and non‐returning couples. Couples providing physical health data had
been married longer than couples who did not return in waves 4 or 5 (or who did
not provide health data). No other differences were found between returning and
non‐returning families on husbands’ or wives’ spouse aggression, on wave 1
depression scores, nor on other demographic variables.
Procedures
The present study utilized data from the first five waves of the Family Studies
Project. Spouses’ reports on partner aggression were obtained in waves 1‐3, reports
of depressive symptoms were obtained in wave 3, and reports of physical health
were obtained in waves 4 and/or 5.
During the first 4 laboratory visits, two graduate students explained
procedures and obtained consent to participate from both parents and assent from

32
the child. Families’ participation took three to four hours during waves 1‐4 and they
were compensated $100, $125, $150, and $175 at the first four waves, respectively.
Following the first four visits, families were asked to complete daily diaries for two
weeks, and were compensated an additional $50, $75, $90, and $90 for completing
these forms at waves 1‐4, respectively. For wave 5, husbands and wives participated
at home through online surveys, which took approximately two hours to complete,
and they were compensated $50 each for their participation. Husbands and wives
did not complete home data following their wave 5 procedures.
In waves 1‐4, family members answered paper and computer‐based
questionnaires in private, separated rooms. The revised Domestic Conflict
Inventory (DCI; waves 1‐3), the Symptom Checklist‐90 Revised (SCL‐90R; wave 3),
the Alcohol and Drug Questionnaires (ADQ; waves 4 and 5), the World Health
Organization Quality of Life Questionnaire‐ brief (WHOQOL‐bref; waves 4 and 5),
and a survey of physical health status and health‐related behaviors that was
compiled for this study, the Health Questionnaire (HQ; waves 4 and 5), were
administered during these procedures. Measures completed at multiple waves were
administered the same way at each time point.
Measures
Physical and Emotional Aggression.   At each wave, spouses completed the
revised Domestic Conflict Inventory (Margolin, Burman, John, & O’Brien, 2000). The
DCI is a 61‐item questionnaire about conflict and aggression used in intimate
relationships (see Appendix A). Both spouses reported about wife‐to‐husband and

33
husband‐to‐wife behaviors. The DCI includes items from the revised Conflict Tactics
Scale (Straus, Hamby, Boney‐McCoy, & Sugarman, 1996) plus additional items. At
wave 1, spouses were asked whether an item had ever occurred, and how many
times it occurred in the last year. At Waves 2‐3, spouses only reported on how
many times DCI items have occurred in the last year. Spouses selected a frequency
range for each DCI item resulting in a 0‐5 score: (0) none, (1) once per year, (2) 2‐5
times per year, (3) 6‐12 times per year, (4) 2‐4 times per month, and (5) more than
once per week. Husband and wife reports were combined by taking the maximum
reported behavior for each item, based on the assumption that individuals are more
likely to under‐report than over‐report aggression (Arias & Beach, 1987; Dutton &
Hemphill, 1992; Margolin, 1987).
For the revised DCI, internal consistency Cronbach alphas for couples’
reports of both spouses’ physical and emotional aggression ranged from .75 to .78.
This information is based on wave 1 data. For the original version of the DCI, two‐
week test‐retest reliability coefficients were .70 for husbands’ self‐reported physical
aggression, .90 for wives’ reports of husbands’ physical aggression, .82 for
husbands’ self‐reports of emotional aggression, and .81 for wives’ reports of
husbands’ emotional aggression (Burman, Margolin, & John, 1991). Test‐retest
information is not available for wives’ aggression or for the revised version of the
CI. D
There are 14 physical aggression items on the DCI: 3 assess minor aggression
(pushed, grabbed, or shoved; slapped; thrown object at spouse) and 11 assess more

34
severe acts of aggression (physically twisted arm; shaken; kicked, bit, or hit with
fist; hit or tried to hit with something; beat up; thrown or tried to throw bodily;
burned; choked or strangled; slammed against wall; threatened with a knife or gun;
used a knife or gun). Total physical aggression scores were calculated by summing
respondents’ maximum response (0 to 5) on the physical aggression items.
An emotional aggression score was composed from the following 11 items:
damaged a household item out of anger towards spouse; deliberately disposed of or
hid an important item of your spouse’s; purposely hurt spouse’s pet; purposely
damaged or destroyed spouse’s clothes, car, or other possessions; insulted or
shamed your spouse in front of others; told spouse he/she couldn’t go to work,
school, or other self‐improvement activities; tried to prevent spouse from
seeing/talking to family or friends; restricted your spouses’ use of the car or phone;
tried to turn family, friends, or children against spouse; frightened your spouse; and
revented your spouse from getting needed m p edical care.
Total and accumulated aggression. Total aggression scores were
computed by summing emotional and physical aggression scales at each time point.
Three accumulated aggression scores were computed for each spouse by taking the
mean of wave 1, 2, and 3 DCI scores for total aggression (Physical + Emotional), for
Physical Aggression, and for Emotional Aggression.   Each accumulated aggression
score thus reflected partner aggression across the first three waves of this study.
Accumulated aggression scores (total, physical, or emotional) were used for all of
the analyses.

35
Depressive Symptoms. In Wave 3, spouses completed the SCL‐90R
(Derogatis, 1983), a self‐report symptom inventory that has been standardized in
community samples (see Appendix B). Respondents rated each of the 90 items on a
five‐point scale (0 to 4), from ‘not at all’ to ‘extremely’. A 13‐item dimension of this
instrument assesses symptoms of depression (depression scale item numbers: 5, 14,
15, 20, 22, 26, 29, 30, 31, 32, 54, 71, 79). The depression scale has an internal
consistency alpha of .90 and test‐retest coefficient of .82. In addition, the SCL‐90R
depression scale is highly correlated with the Beck Depression Inventory‐II (.89)
(Steer, Ball, Ranieri, & Beck, 1997) and depression dimensions on the Wiggins (.75)
and the Middlesex Hospital Questionnaire (.73) (Derogatis, 1983). T‐scores, based
on published standardization data, were used for all analyses.
In wave 3, 102 wives and 100 husbands provided SCL‐90R data. An
additional two wives and three husbands participated in waves 2 and/or 4, but not
in wave 3. For these five spouses, their wave 2 or the mean of their wave 2 and
wave 4 SCL‐90R depression scale data were substituted for the mi a. ssing wave 3 dat
Health Compromising Behaviors and Health Outcomes. During waves 4
and 5, husbands and wives completed measures assessing their current health and
health‐compromising behaviors. Health behavior and health status were assessed
in five categories: (1) health status and chronic illnesses (e.g., cancer, hypertension),
(2) subclinical health symptoms (e.g., pain, headaches, fatigue, colds), (3) preventive
care (e.g., annual physical and dental check‐ups), (4) health behaviors (e.g., smoking,
drinking, nutrition, exercise, sleep), and (5) physical health quality of life (e.g.,

36
satisfaction with overall physical health and dimensions of health). Physical Health
Quality of Life was assessed using the physical health domain on the WHOQOL‐bref
(WHOQOL Group, 1998; see Appendix C). To assess dimensions 1‐4, four health
indices were created using data from a Health Questionnaire (HQ; see Appendix D)
compiled for this study and the Alcohol and Drug Questionnaire (see Appendix E),
consisting of the Alcohol Clinical Index (Skinner & Holt, 1987) and the CAGE
Questionnaire (Ewing, 1984; King, 1986). For all five health indices higher numbers
on the scales represent poorer health or health behaviors. Table 2 summarizes the
five health indices and provides examples of item content.
The WHOQOL‐bref, an abbreviated version of the WHOQOL‐100, uses 26
items to tap four domains: physical health, psychological, social relationships, and
environment. The Physical Health Quality of Life domain was used in the current
study and is highly correlated (.95) with WHOQOL‐100 physical health scale. For
the subscale, internal consistency coefficients range from .80‐.84 and test‐retest
reliability over a 2‐8 week period was .66. The WHOQOL‐bref successfully
discriminates between ill and well subjects (WHOQOL Group, 1998). The six
physical health domain items asked about daily interference or satisfaction related
to pain, needed medical treatment, energy, mobility, sleep, activities of daily living,
and capacity for work on a five‐point Likert‐type scale. Items were summed and
transformed to a 0‐100 scale. Transformed scores were reflected for this study so
that higher numbers indicate poorer health.

37
Table 2. Heal
x
th in ions and item conten dex descript t

Health Inde Description Item content/examples
Health
conditions
(25 items)
Count of health conditions or
diagnoses that respondent
first learned about in the last
two years
Coronary heart disease, heart
attack, high cholesterol,
hypertension, arthritis, asthma,
cancer, diabetes, allergies, liver
condition, sinusitis, thyroid
problems, weight problem, back or
neck problem, fracture or bone/
joint injury, hearing problem, etc
Subclinical
symptoms
(12 items)
Number of days in last three
months with impaired
physical wellness or
significant bodily discomfort
(pain, fatigue, poor physical
r flu health, and/or cold o
symptoms)
Days physical health not good, had
head/chest cold, stomach or
intestinal illness, flu or infection,
pain (neck, low back, facial,
headache, migraine, other), felt did
not get enough sleep, needed
stimulant because of fatigue
Preventiv
care
(7 items)
e Count of healthcare
utilization and preventive
care recommendations not
met
No medical or dental insurance,
postponing medical care or
prescriptions, no cholesterol check
last 5 years, not seen doctor or
dentist in last year
Health
behaviors
(14 items)
Count of health behavior
recommendations not met or
health risk behaviors engaged
in
Current smoker or tobacco user,
obese or overweight body mass
index, sleep, unhealthy weight
management, exercise, TV watching,
,

milk and fruit/vegetable servings
alcohol abuse or binging, drug use
Physical h
uality of
6 items)
ealth
life
Subjective well‐being or
satisfaction related to aspects
of physical health
Mobility, activities of daily living,
capacity for work, energy, pain,
access to medical treatment, sleep
q
(

The HQ utilized items adapted from the National Health Interview Survey
(National Center for Health Statistics [NCHS], 2004), California Health Interview
Survey (California Department of Health Services [CDHS], 2001, 2003), Behavioral
Risk Factor Surveillance System (CDC, 2004), Youth Risk Behavior Survey (CDC,
2005), National Health and Nutrition Examination Survey (NCHS, 2001), Medical
38
Expenditure Panel Survey (Agency for Healthcare Research and Quality [AHRQ],
2002), New‐Buss Questionnaire (Gidron, Davidson, & Ilia, 2001; 8 items from the
Buss‐Perry Aggression Questionnaire (Buss & Perry, 1992)), and RAND 36‐item
Health Survey (Hays, Sherbourne, & Mazel, 1993), as well as new questions
constructed for this study. Item origin is indicated on the questionnaire version in
Appendix D (this information was not included on the participant version of the
questionnaire). The HQ was piloted for clarity with a comparable population and
necessary a djustments were made prior to administration with the current sample.
Four physical health subscales were created from questions on the HQ. The
Health Conditions Index is a tally of reported health problems that started in the two
years prior to data reporting. Participants were asked whether they had ever been
told by a doctor or other health professional that they had a list of health conditions
or whether they ever had difficulty with certain health problems (see questions 8
and 9 on the HQ). Participants were presented with a list of 25 health problems or
conditions and were asked when they first learned of any reported problems.
Participants could also write in health conditions they had experienced; health
conditions that were relevant (e.g., not mental health problems such as depression)
and were not redundant with those already reported were added to the index tally.
Conditions or health problems were required to have started in the previous two
years to establish temporal order between spouse aggression and depression
reported in earlier waves and health problem onset. On average, there was a 2.7
year (SD = 0.47) delay between waves three and four of data collection. For women,

39
the most commonly reported health problems starting in the previous two years
were back or neck problems (28.2%), high cholesterol (14.1%), weight problem
(14.1%), hypertension (8.2%), hearing problems (5.9%), other health conditions
(8.2%), and other injuries (5.9%). The most common health problems starting in
the previous two years for men were high cholesterol (18.1%), back or neck
problem (14.5%), hypertension (10.8%), arthritis/rheumaticism (6.0%), and other
health conditions (10.8%). The remaining health conditions on the list were
reported by 5% or less of husbands and/or wives. Circulation problems (including
blood clots), epilepsy, and stroke were the only items on the list of 25 that were not
reported by any husbands or wives as starting in the prior two years.
The Subclinical Symptoms Index is a measure of daily discomfort and
symptom complaints. This index is a sum of the reported number of days over the
past three months that husbands and wives had physical health that was not good,
had a head or chest cold, had a stomach or intestinal illness, had the flu or an
infection, experienced pain (neck, low back, facial, headache, migraine, or other
pain), felt they did not get enough sleep, or felt they needed stimulants to stay
awake (see questions 2, 5, 6, 7, 10a‐f, 12, and 13 on the HQ). Questions about pain
were asked on a three‐month scale, whereas other questions were asked about the
prior 30 days. Questions regarding the prior 30 days were weighted by 3 when
summing the scale items. The alpha for the wives’ Subclinical Symptom Index is .69
and the alpha for the husbands’ Subclinical Symptom Index is .67. Deleting any one
of the items on this index would have lead to <.01 improvement in the alpha

40
coefficient for wives. Deleting any of the items would decrease the alpha coefficient
for husbands. These alpha coefficients are close to the conventional .70 guideline for
“acceptable” scale internal consistency. Given that this scale measured a number of
different symptom complaints that could be present in the absence of the
endorsement of other scale items, it is not surprising that these alpha coefficients
are not er.   high
The Preventive Care Index is a tally of participants’ non‐adherence to seven
positive healthcare practices. Participants received one point on the index if they
did not have health insurance, did not have dental insurance, had delayed needed
medical care, had delayed getting needed prescriptions, did not see a dentist in the
last year, did not see a doctor in the last year, or had not had their cholesterol
checked in the last five years. These seven items and definitions for dichotomizing
(e.g., cholesterol check in the last 5 years) were derived from the Chronic Disease
Indicators (CDI), which were developed through expert consensus to facilitate
uniform definitions for monitoring chronic disease risk factors and conditions. The
CDI definitions were the product of a collaboration between the Counsel of State and
Territorial Epidemiologists, the National Association of Chronic Disease Directors,
and the National Center for Chronic Disease Prevention and Health Promotion at the
Centers for Disease Control and Prevention (National Center for Chronic Disease
Prevention and Health Promotion, 2009a, 2009b). Similar to the other health
indices, higher scores represent poorer preventive care behavior.

41
The Health Behaviors Index included 14 items examining behaviors that have
been identified as indicators of chronic diseases and poor health, including poor
nutrition, poor sleep, physical inactivity, weight‐related problems, tobacco use, and
alcohol or drug abuse. Alcohol and drug use was reported on the ADQ and other
constructs were reported on the HQ. Similar to the preventive care index, one point
was given for each healthy behavior recommendation not adhered to or for each
health risk behavior. The 14 items on the health behaviors index included: *being a
current smoker (defined as having smoked at least 100 cigarettes in one’s lifetime
and currently smoking some days or everyday), currently using tobacco products
other than cigarettes, *being overweight (Body Mass Index ≥ 25), *being obese
(Body Mass Index ≥ 30), engaging in any unhealthy weight management behaviors
(fasting, using diet pills or laxatives, or vomiting to lose weight or keep from gaining
weight), sleeping less than 7 hours or more than nine hours per night, *consuming
less than 5 servings of fruits and vegetables per day, consuming less than 2 servings
of milk per day, *watching more than two hours of television per day, engaging in
less than 2.5 hours of moderate intensity exercise or 75 minutes of vigorous
intensity exercise per week, engaging in strengthening exercises less than 2 times
per week, *heavy alcohol consumption (defined as greater than seven drinks per
week for women and 14 drinks for men on average each week), *binge drinking
(defined as four or more drinks for women or five or more drinks for men per
occasion), and illicit drug use or prescription drug abuse.

42
The six asterisked items above are included in the National Center for
Chronic Disease Prevention and Health Promotion (2009a, 2009b) Chronic Disease
Indicators
1
. The aerobic and strengthening exercise dichotomizations above are
based on the U.S. Department of Health and Human Services (2008) Physical
Activity Guidelines for Americans. For this study, negative sleep health was defined
as less than seven hours or more than nine hours per night. Insufficient sleep or
sleep restriction has been linked to a number of neurocognitive problems and
negative physiologic changes that in turn increase risk for chronic diseases
(National Center on Sleep Disorders Research [NCSDR], 2003). Despite common
recommendations to obtain approximately eight hours of sleep per night, there is a
surprising dearth of strong research data guiding sleep recommendations. The
National Sleep Foundation (2009) recommends seven to nine hours for adults.
Epidemiological data have linked increases in mortality for individuals with
insufficient sleep, defined in different studies as less than six or less than seven
hours of sleep per night, and with longer than normal sleep times, defined as more
than nine hours of sleep per night (NCSDR, 2003). For this study, information was
only available on milk consumption and was not gathered on other dairy products.
Dietary recommendations suggest three or more servings of low‐fat milk or
equivalent diary products per day (U.S. Department of Health and Human Services,
2005). The cutoff of two or more servings of milk per day was used to include some

1
Hours of television viewing is a CDI specified for youth that is being used for adults in this
study.
43
representation of this health behavior. Use of tobacco products other than
cigarettes (National Institute of Drug Abuse, 2009), unhealthy weight management
behaviors (Becker, Grinspoon, Klibanski, & Herzog, 1999), and illicit drug use (Brick,
2008) w also included on the inde ere x due to linkages with negative physical health.
The Physical Health Composite Scale combined the 5 health indices described
above: (1) the health conditions index, (2) the subclinical symptoms index, (3) the
preventive care index, (4) the health behaviors index, and (5) the physical health
quality of life domain. Each of the indices was examined for outliers (>3 standard
deviations over the mean). Outliers were identified for both spouse’s health
condition and subclinical symptom indices, and the husband preventive care index
(1‐2 outliers per scale). These outliers were winsorized to not unduly impact
ranges of the indices. Winsorized variables for these scales were used in the
analyses. To construct the composite scale, each of the five indices was then divided
by its range to transform the indices to a 0‐1 scale. Finally, these five transformed
indices were summed to create the Physical Health Composite Scale with a potential
0‐5 range.
Statistical Analyses
Data were analyzed using path analysis, a type of Structural Equation
Modeling (SEM) that focuses on relationships among manifest variables. SEM is a
covariance‐based modeling technique. Analyses were completed using Mplus,
version 5.21 (Muthèn & Muthèn, 2007). Maximum likelihood estimation was used to
allow inclusion of cases with incomplete data.

44
Analyses were conducted in two steps. First, a confirmatory model evaluated
the study hypotheses regarding relationships between total accumulated spouse
aggression, depression, and the physical health composite variable. Second, a series
of exploratory, post‐hoc models were run to further examine the relationships
between couple physical and emotional aggression, depression, and the five physical
health indices. The exploratory models may assist in generating hypotheses for
future research and suggest construct relationships for replication in other samples.
Given the exploratory nature of these analyses, conclusions should be drawn with
caution.
In the post‐hoc analyses, the health conditions and preventive care indices
were identified as count variables due to the skewed distributional properties of
these variables. The subclinical symptoms and the health behaviors indices could
also be conceptualized as count variables; however, both of these indices were
analyzed as normally distributed continuous variables. The health behaviors index
adhered well to normality assumptions. The subclinical symptoms index is
positively skewed and a count of negative health days, but the large scale range
made it inappropriate for analysis as a count variable. This index was subjected to a
square root transformation to increase adherence to normality assumptions for the
SEM analyses.
For models not including count variables, chi‐square goodness‐of‐fit and root
mean square error of approximation (RMSEA) statistics were examined to evaluate
the strength of fit between the model and the data covariance matrix. For these fit

45
statistics, non‐significant chi‐squares (i.e., the hypothesis that the data fit the
modeled relationships is not rejected) and RMSEA values < .05 were considered
suggestive of “good” model fit (McDonald & Ho, 2002). Chi‐square difference tests
were used to compare alternative, nested models. Fit statistics are not available for
models with count variables. For these models, Wald tests and path significance
levels (alpha level at .05) were used to identify paths important to the model.
Missing Data Procedures. Given the longitudinal nature of this study and
the use of two reporters numerous missing data patterns were present. A number
of steps were taken to examine missingness and maximize the use of all available
data. As described above, couple aggression data were collected in waves 1‐3 (119,
102, and 103 families participated in those waves, respectively), depression data
were collected in wave 3 (103 participating families), and physical health data were
collected in waves 4 and 5 (90 couples provided physical health data).   Thus, 87%
of the original sample provided mental health data in wave 3 and 75.6% completed
physical health outcome measures.
Due to this missingness, the primary model was analyzed in two ways. First,
maximum likelihood estimation was used to allow inclusion of all available data
rather than only examining the couples with complete data on all measures (i.e.,
listwise deletion). This procedure produces unbiased parameter estimates for data
that are Missing At Random (MAR), meaning that data missingness may be a
function of other variables in the model, but may not be dependent on the variable
on which the data are missing (McDonald & Ho, 2002). Second, maximum

46
likelihood estimation was again used for the path analyses with the addition of a
Heckman Correction probability variable.
Heckman Correction. Although only one variable was identified to
distinguish between couples who provided and did not provide physical health data
in wave 4 or 5, it may not be appropriate to assume that non‐returners are Missing
At Random. The addition of the Heckman Correction to the path models improves
our ability to statistically account for differences between returners and non‐
returners during parameter estimation.
The Heckman Correction procedure takes place in two steps (Heckman,
1979). First, wave 1 data were used to create a probability for return variable via
saving the predicted probabilities produced in logistic regression analyses
predicting returner status (i.e., whether couples did or did not provide physical
health data in wave 4 or 5). This probability of return variable then was added as
one of the predictors of the primary model variables (i.e., aggression, depression,
and health variables) in the path models.
Ninety couples provided at least one report of physical health status at wave
4 or 5. A probability coefficient was estimated to predict completion of physical
health outcome data (n = 90 couples with health data; n = 29 couples with no health
data). Numerous logistic regression models were examined to identify the strongest
probability of return equation. With a constant as the only predictor in the
equation, 75.6% of couples’ returner status was correctly identified. Attempts to
predict returner status based on years since marriage, which was already identified

47
as differing among returning and non‐returning couples, did not improve correct
identification of returner status over the constant. To improve the utility of the
Heckman Correction probability factor, demographic variables and 33 additional
variables reported on in wave 1 were then examined. Appendix F lists the variables
examined and those used in the final logistic regression equation. Of these
variables, only one additional was found to be significantly different between the
two groups. Spouses’ number of moves in the previous 10 years, t(117) = 2.24, p =
.03, significantly differed between responders and non‐responders. Non‐returners
reported a higher number of previous moves on average. Backwards stepwise
deletion using the likelihood ratio produced the strongest Heckman Correction
variable with 94.2% of couples’ returner status correctly identified, Hosmer‐
Lemeshow goodness‐of fit χ
2
(8, N = 119)= 11.33, p = .18.
Multivariate Outliers. Model variables were examined for multivariate
outliers. Couples with a Mahalanobis distance significant at an alpha level of p <
.001 were identified as mulitivariate outliers and excluded from the analyses
(Tabachnick & Fidell, 2007). Two cases were identified as multivariate outliers for
the primary model, resulting in a final sample size of 117 for the analyses. For the
exploratory models, 1‐3 multivariate outliers were identified for each of the models
and excluded from the analyses.

48
Chapter 3: Results

Descriptive Information
Means, medians, standard deviations, and ranges for the model variables are
presented in Table 3. Several gender differences exist among the variables. Wife
total aggression, Wilcoxon signed‐rank Z = ‐2.62, p = .01, wife physical aggression,
Wilcoxon signed‐rank Z = ‐3.14, p = .002, and wife depression scores, t(102) = 2.52,
p = .01, were significantly higher than husbands’ corresponding scores. Wife
emotional aggression scores tend to be higher than husband emotional aggression,
but this difference is not statistically significant, Wilcoxon signed‐rank Z = ‐1.74, p =
.08. For 60% of couples both partners reported at least one act of emotional
aggression in waves 1‐3, for 13% only husbands were emotionally aggressive, for
12% only wives were emotionally aggressive, and no emotional aggression was
reported in 16% of couples. For physical aggression, in 24% of couples both spouse
were physically aggressive, for 8% only the husband was physically aggressive, for
19% only the wife was physically aggressive, and 49% of couples did not report any
physical aggression. Overall, in 63% of couples both spouses were aggressive, for
9% only husbands were aggressive, for 12% only wives were aggressive, and for
16% neither spouse engaged in physical or emotional aggression.
Husbands reported more negative health behaviors than wives, t(77) = ‐2.11,
p = .04. No other gender differences were present on the health indexes or on the
physical health composite variable. Correlations among aggression, depression, and

49
physical health variables are presented in Table 4 for wife physical health variables
and Table 5 for husband physical health variables. See Appendix G for correlation
tables including variables in emotional and physical aggression exploratory models.
Given the skewed nature of the aggression variables and a number of the health
indices (i.e., health conditions, subclinical symptoms, and preventive care),
Spearman’s rho correlations are presented in addition to Pearson correlations.
Multivariate outliers are not included in the correlation matrixes.
As shown in Tables 4 and 5, husband and wife aggression are strongly
correlated. Both husband and wife aggression are correlated with increased wife
depression. Husband aggression is correlated with increased husband depression.
Wife aggression is correlated with husband depression with the Pearson, but not
with the Spearman, correlation analysis. Given the non‐normal distribution of wife
aggression, it is more appropriate and conservative to rely on the Spearman
correlation results. Husband aggression is significantly, positively associated with
more impaired physical health for wives for the health composite and all of the
health indices, except wife health behaviors. Husband aggression is not significantly
related to wife health behaviors. Wife aggression is positively correlated with wife
physical health composite, subclinical symptoms, and health‐related quality of life
scales. For husbands’ physical health, both husband and wife aggression are
significantly, positively associated with poorer health for the health composite,
health conditions, and preventive care indices.

50
Table 6 displays correlations between wife and husband health variables.
Husband and wife behavior‐oriented health indices (i.e., preventive care and health
behaviors) displayed between‐spouse correlations and some between‐spouse,
cross‐index correlations. Neither spouse’s health conditions, subclinical symptoms,
nor physical health quality of life indices were correlated with the other spouse’s
ealth indices. h

51

T

able 3. Model Variable Descriptive Stat ics ist
Model Variables
N Mean SD Me an di Range
Wife Aggression ‐ total 119 3.69 6.76 1 0 ‐ 52.5
Husband Aggression ‐ total 119 2.75 5.92 1 0 – 52
Wife Emotional Aggression 119 2.52 4.23 .67 0 – 24
Husband Emotional Aggression 119 1.94 3.40 .6 7 0 ‐ 26.5
Wife Physical Aggression 119 1.17 3.11 0 0 – 29
Husband Physical Aggression 119 .81 2.78 0 0 ‐ 25.5
Wife Depression t‐score 104 52.86 9.44 53 33 ‐ 75
Husband Depression t‐score 1 03 50.03 10.91 52 37 – 82
Wife Physical Health Composite
a
85 1.65 .73 1.59 .32 ‐ 3.43
Husband Physical Health
Composite
a
83 1.59 .73 1 .49 .41 5 ‐ 3.4
Wife Health Conditions Index
b
85 1.16 1.18 1 0 ‐ 5
Husband Health Conditions Index
b
83 .90 1.22 1 0 ‐ 5
Wife Subclinical Health Symptoms
Index
b
85 104.20 91.70 81 0 – 381
Husband Subclinical Health
Symptoms Index
b
83 96.07 96.46 6 3 0 – 369
Wife Preventive Care Index 85 1.55 1.37 1 0 ‐ 5
Husband Preventive Care Index
b
83 1.52 1.34 1 0 – 5
Wife Health Behaviors Index 85 4.84 2.01 5 1 – 10
Husband Health Behaviors Index 83 5.36 1.94 5 2 – 9
Wife Physical Health Quality of Life
Index
86 50.87 15.37 46.43 25 ‐ 92.86
Husband Physical Health Quality of
Life Index
84 48.81 15.80 46.43 25 ‐ 100
a
Physical ealth composite variable includes index variables wit h

h winsorized outliers.
b
These variables have 1‐2 winsorized outliers.

52

Table 4. Husband and Wife Spouse Total Aggression, Husband and Wife Depression, and Wife Physical Health Variables: Pearson
Correlations (lower left triangle) and Spearman Correlations (upper right triangle)

Variables 1 2 3 4 5 6 7 8 9 10
1. Wife Aggression 1.00 .66
***
.27
**
.16 .31
**
.20 .32
**
.18 .10 .23
*
2. Husband Aggression .88
***
1.00 .27
**
.21
*
.40
***
.22
*
.33
**
.34
**
.05 .37
***
3. Wife Depression .26
**
.26
**
1.00 .39
***
.22
*
.06 .33
**
.08 .10 .28
**
4. Husband Depression .23
*
.31
**
.39
***
1.00 .03 ‐.18 .07 .06 .06 .15
5. Wife PH Composite .15 .31
**
.23
*
.14 1.00 .60
***
.69
***
.69
***
.38
***
.76
***
6. Wife Health Conditions .18 .26
*
.01 ‐.11 .58
***
1.00 .39
***
.23
*
‐.01 .33
**
7. Wife Subclinical Symptoms .12 .24 .29
**
.16 .71
***
.34
**
1.00 .34
**
.03 .52
***
8. Wife Preventive Care .13 .29
**
.06 .08 .70
***
.22
*
.28
*
1.00 .19 .44
***
9. Wife Health Behaviors .01 ‐.11 .10 .09 .36
***
‐.04 ‐.02 .18 1.00 .19
10. Wife PH Quality of Life .11 .29
**
.28
*
.23
*
.77
**
.29
**
.59
***
.41
**
.16 1.00
N 117 117 102 101 83 82 83 83 83 84
PH = Physical Health. Multivariate outliers excluded from correlation analyses. *p < .05.  **p < .01.  ***p < .001.

53

Table 5. Husband and Wife Spouse Total Aggression, Husband and Wife Depression, and Husband Physical Health Variables:
Pearson Correlations (lower left triangle) and Spearman Correlations (upper right triangle)

Variables 1 2 3 4 5 6 7 8 9 10
1. Wife Aggression 1.00 .66
***
.27
**
.16 .29
*
.35
***
.19 .23
*
.01 .22
2. Husband Aggression .88
***
1.00 .27
**
.21
*
.39
***
.32
**
.19 .39
***
.14 .19
3. Wife Depression .26
**
.26
**
1.00 .39
***
.11 .27
*
.02 .10 .16 ‐.06
4. Husband Depression .23
*
.31
**
.39
***
1.00 .30
**
.25
*
.30
**
.09 .19 .27
5. Husband PH Composite .19 .29
*
.15 .34
**
1.00 .50
***
.70
***
.67
***
.54
***
.67
***
6. Husband Health Conditions .33*
*
.25* .30
**
.28
*
.56
***
1.00 .29
*
.17 .14 .20
7. Husband Subclinical
Symptoms
.09 .23* .02 .25* .74
***
.26* 1.00 .26
*
.20 .53
***
8. Husband Preventive Care .17 .22* .04 .07 .64
***
.12 .31
**
1.00 .23
*
.25
*
9. Husband Health Behaviors ‐.04 .004 .15 .17 .50
***
.16 .14 .23 1.00 .21
10. Husband PH Quality of
Life
.17 .21 ‐.03 .39
***
.70
***
.20 .58
***
.26
*
.19 1.00
N 117 117 102 101 81 80 81 81 81 82
PH = Physical Health. Multivariate outliers excluded from correlation analyses.   *p < .05.  **p < .01.  ***p < .001.

54

Table 6. Husband and Wife Physical Health Scales: Pearson and Spearman Correlations

Variables Husband
PH
Composite
Husband
Health
Conditions
Husband
Subclinical
Symptoms
Husband
Preventive
Care
Husband
Health
Behaviors
Husband
PH
Quality of Life
Pearson Correlations:
Wife PH Composite .25
*
.18 ‐.13 .34
**
.21 .14
Wife Health Conditions .10 .15 ‐.11 .08 .17 ‐.01
Wife Subclinical
Symptoms
.10 .18 ‐.09 .13 ‐.02 .08
Wife Preventive Care .13 .06 ‐.15 .42
***
.02 .02
Wife Health Behaviors .30
**
.11 .05 .23
*
.37
***
.18
Wife PH Quality of Life .14 .09 ‐.10 .14 .18 .17
Spearman Correlations:
Wife PH Composite .16 .17 ‐.18 .33
**
.17 ‐.01
Wife Health Conditions .09 .17 ‐.16 .16 .15 ‐.05
Wife Subclinical
Symptoms
.10 .19 ‐.01 .21 ‐.03 ‐.001
Wife Preventive Care .13 .06 ‐.18 .42
***
.03 ‐.03
Wife Health Behaviors .32
**
.03 .09 .27
*
.40
***
.13
Wife PH Quality of Life .07 .06 ‐.15 .10 .17 .08
N=80 for correlations between Wife and Husband PH Quality of Life scales. N= 79 for correlations between Wife and Husband PH Quality of Life Scale and other health
scales. N = 78 for remaining correlations. PH = Physical Health. *p < .05.  **p < .01.  ***p < .001.
55
Physical Health and Demographic Variables
Relationships between the physical health variables, age, ethnicity, race,
income, education, and number of children were examined to identify demographic
variables important to include in the path models. All of the demographic variables
were reported on in the same wave as physical health, except for number of
children, which was only reported on in wave 1. Income was controlled for in
analyses examining ethnicity, race, and education to identify variables that provided
additional explanatory value. Wife age was significantly correlated with wife health
behaviors, r(83) = ‐.33, p = .002. Number of children was significantly correlated
with wife preventive care, r(83) = .26, p = .02. After controlling for income, wife
education was significantly correlated with wife health behaviors, r(81) = ‐.31, p =
.01, husband physical health composite scale, r(79) = ‐.25, p = .02, husband
subclinical symptoms, r(79) = ‐.24, p = .03, and husband health behaviors, r(79) = ‐
.30, p = .01. After controlling for income, husband education was significantly
correlated with wife health behaviors, r(81) = ‐.22, p = .04, wife physical health
quality of life, r(82) = ‐.22, p = .03, and husband health behaviors, r(79) = ‐.32, p =
.004. No significant relationships with race were found. After controlling for
income, a number of significant relationships between Hispanic/Latino(a) status
and health were present, as detailed in Table 7. Income and other demographic
variables significantly related to health were added to the path models to account
or these influences on physical health. f

56
T

able 7. Differences in health variables by ethnicity status (controlling for income)
Not
Hispanic/Latino(a) Hispanic/Latino(a)
Physical Health n M SD n M SD
F
(ethnicity)
Wife Variables:
Composite Scale
Health Cond
57
57
1.48
1.18
9
.67
1.31
8
27
27
1.96
1.11
13
.77
.89
100.66
8.56**
.06

itions
Subclinical
Symptoms
e
rs
57 0.56 5.23 27 4.22 4.30*
Preventive Car
Health Behavio
57
57
1.33
4.44
4
1.30
2.00
13
27
27
1.96
5.59
5
1.43
1.80
16
4.13*
6.90**
Quality of Life 57 7.62 .72 28 7.65 .80 8.49**

Husband Variables
itions
:
Composite Scale
Health Cond
51
51
1.43
.75
9
.65
1.13
9
31
31
1.84
1.19
10
.79
1.33
9
4
2
.42*
.22
Subclinical
Symptoms
e
rs
51 3.61 6.42 31 2.65 8.39 .09
Preventive Car
Health Behavio
fe
51
51
52
1.18
4.90
48.35
1.16
1.85
14.52
31
31
31
1.97
6.03
50.23
1.35
1.87
17.78
5.03*
5.12*
Quality of Li .09
**p<.01, *p<.05

Aggres sion, Depression, and the Physical Health Composite: Hypothesis Testing
Figure 2 depicts the hypothesized relationships between husband and wife
spouse aggression, depression, and physical health composite variables. Table 8
presents unstandardized and standardized coefficients for this model. Husband
aggression is significantly related to husband depression and wife physical health.
Husband depression has a significant direct effect on husband physical health.
There is an indirect effect from husband aggression to husband physical health via
husband depression that does not reach statistical significance, β = .14, S.E. = .08, p =
.08. Wife spouse aggression does not display significant effects on either spouses’
depression in the path model or on physical health variables.

57
Hypothesis 1, which predicted direct effects between aggression and
depression variables, was supported only for the link between husband aggression
and husband depression. Hypothesis 4, which predicted direct effects between
aggression and physical health, was supported only for the link between husband
aggression and wife physical health. No indirect effects from depression to physical
health via depression were significant (hypothesis 7).

58

Figure 2. Hypothesized path model for spouse total aggression (waves 13),
depression (wave 3), and physical health composite (waves 4 and 5) (Standardized
Solution)

χ
2
(2, N = 117) = .43, p(perfect) = .81; RMSEA = .00 (90% C.I = .00 ‐ .11), p(close) = .85.
Income, wife education, husband Hispanic/Latino status, and wife Hispanic/Latino status were included in the
model with paths from each of these variables to each of the primary model variables. These variables and
paths were not included in the above diagram for visual simplicity. H = Husband, W = Wife, Aggr. = Total
Aggression (Physical + Emotional), Depr. = Depression, PH = Physical Health, Educ. = Education, Inc. =
Household Income in $1000s (Years 4/5), H/L = Hispanic/Latino(a) Ethnic Status. Italicized path coefficients
for binary exogenous variables (i.e., Hispanic/latino(a) status) are interpreted as the change in y (outcome
variable) in y standard deviation units when the binary variable changes from zero to one. Other path
coefficients are interpreted as the change in y in y standard deviation units for a standard deviation change in x.
*p<.05, **p<.01, ***p<.001

59
Table 8. Unstandardized, Standardized, and Significance Levels for Hypothesized Model in Figure 2 (N = 117)

Parameter Estimate Unstandardized
(S.E.)
Critical
Ratio
p Standardized
a
(S.E.)
Critical
Ratio
P
Husb. Aggression Æ Wife Depression

.34   (.39) .86 .39 .19 (.22) .89 .37
Wife Aggression Æ Wife Depression .42   (.30) 1.41 .16 .27 (.19) 1.43 .15
Income   Wife Depression Æ Husb. Hispanic/Latino Æ Wife Depression
‐.01   (.02) ‐.23 .82 ‐.03 (.11) ‐.23 .82
Wife Education Wife Depression Æ Wife Hispanic/Latina   Wife Depression
.23   (.47) .49 .63 .05 (.11) .49 .63
1.68 (2.66) .63 .53 .17 (.26) .63 .53
Æ Husb. Aggression Æ Husb. Depression
1.85 (2.66) .70 .49 .18 (.26) .70 .49

1.01   (.43) 2.34 .02 .48 (.19) 2.59 .01
Wife Aggression Æ Husb. Depression .10   (.33) .29 .77 .05 (.18) .29 .77
Income Æ Husb. Depression ‐.01   (.02) ‐.21 .84 ‐.02 (.11) ‐.21 .84
Wife Education   Husb. Depression Æ Husb. Hispanic/Latino Æ Husb. Depression
‐.63   (.53) ‐1.18 .24 ‐.12 (.10) ‐1.19 .24
‐5.14 (2.95) ‐1.75 .08 ‐.42 (.23) ‐1.82 .07
Wife Hispanic/Latina   Husb. Depression Æ Husb. Aggression Æ Wife Physical Health
5.70 (2.96) 1.93 .054 .47 (.24) 1.96 .05

.08   (.04) 1.98 .05 .52 (.23) 2.31 .02
Wife Aggression Æ Wife Physical Health ‐.01   (.02) ‐.33 .74 ‐.06 (.19) ‐.33 .74
Wife Depression Æ Wife Physical Health .01   (.01) 1.32 .19 .12 (.10) 1.30 .20
Income Æ Wife Physical Health ‐.003 (.002) ‐1.74 .08 ‐.18 (.10) ‐1.75 .08
Wife Education   Wife Physical Health Æ Husb. Hispanic/Latino Æ Wife Physical Health
.02   (.04) .45 .65 .05 (.11) .45 .65
‐.01   (.21) ‐.05 .96 ‐.01 (.25) ‐.05 .96
Wife Hispanic/Latina   Wife Physical Health Æ Husb. Aggression Æ Husb. Physical Health
.42   (.20) 2.09 .04 .51 (.24) 2.16 .03
.02   (.03) .82 .41 .19 (.22) .84 .40
Wife Aggression Æ Husb. Physical Health .004 (.02) .16 .87 .03 (.20) .16 .87
Husb. Depression Æ Husb. Physical Health

Income Æ Husb. Physical Health
.02   (.01) 2.52 .01 .30 (.12) 2.54 .01
‐.001 (.001) ‐.71 .48 ‐.08 (.11) ‐.71 .48
Wife Education Æ Husb. Physical Health ‐.08   (.04) ‐2.21 .03 ‐.24 (.11) ‐2.24 .03

Table 8, Continued. Unstandardized, Standardized, and Significance Levels for Hypothesized Model in Figure 2 (N = 117)
60

Parameter Estimate Unstandardized
(S.E.)
Critical
Ratio
p Standardized
a
(S.E.)
Critical
Ratio
P
Husb. Hispanic/Latino Æ Husb. Physical
Health
.32   (.21) 1.52 .13 .42 (.28) 1.49 .14
Wife Hispanic/Latina Husb. Physical Health Æ Covariance Husb. & Wife Aggression
‐.18   (.21) ‐.85 .40 ‐.23 (.28) ‐.84 .40
33.37 (4.66) 7.17 <.001 .88 (.02) 43.98 <.001
Covariance Husb. & Wife Depression 30.89 (9.32) 3.31 .001 .35 (.09) 3.99 <.001
Covariance Husb. & Wife Physical Health .05   (.05) 1.12 .26 .13 (.12) 1.15 .25
Residual for Wife Depression 80.38 (11.26) 7.14 <.001 .78 (.12) 6.48 <.001
Residual for Husb. Depression 98.34 (13.83) 7.11 <.001 .66 (.12) 5.34 <.001
Residual for Wife Physical Health .42   (.07) 6.42 <.001 .60 (.15) 4.03 <.001
Residual for Husb. Physical Health .38   (.06) 6.36 <.001 .65 (.11) 6.03 <.001
Indirect Effects
Husb. Aggression   Husb. Depression Æ Æ   Husb. Physical Health
.02   (.01) 1.71 .09 .14 (.08) 1.76 .08
Note: χ
2
(2, N=117) = .43, p(perfect) = .81; RMSEA = .00 (90% Confidence Interval = .00 ‐ .11), p(close) = .85.
a
Standardized coefficients may be interpreted as the amount
of change in y in y standard deviation units, given a standard deviation change in x for all variables except binary variables. For binary variables (i.e., Husband or Wife
Hispanic/Latino(a) status), standardized coefficient represents the change in y in y standard deviation units given a change from zero to one in x. Household Income in
$1000s.
61
T

able 9. Model Comparisons Evaluating Hypothesized Rela nsh tio ips
Hypothesized Model χ
2
df p(perfect) χ
2
Δ
df
Δ
RMSEA
(90% C.I) p(close)
Full Model .43 2 .81 ‐‐ ‐‐ .00 (.00‐.11) .85
1a (HAg WDep@0) Æ
Æ
1.17
2.40
5.77
3 .76 .74
1
5.
1 .00 (.00‐.11) .83
1b (WAg WDep@0)
Æ 0)
3 .49 .97 1 .00 (.00‐.14) .61
1c (HAg HDep@
1d (WAg Æ HDep@0)
W
3
3
.12
.92
34*
.08
1
1
.09 (.00‐.20)
.00 (.00‐.06)
.22
.94 .51
2 (HAg Æ Dep &
WAg Æ HDep constrain =)
W

.61 3 .89 .18 1 .00 (.00‐.07) .93
3a (HAg Æ Dep &
WAg Æ WDep constrain =)
Æ ep constrain =)
.44 3 .93 .01 1 .00 (.00‐.05) .95
3b (WAg HDep &
HAg Æ HD
Æ
Æ
2.14 3 .54 1.71
3
1 .00 (.00‐.14) .66
4a (HAg WPH@0) 4.26 3 .35 .83 1 .00 (.00‐.18) .35
4b (WAg WPH@0)
Æ 0)
.54 3 .91 .11 1 .00 (.00‐.06) .94
4c (HAg HPH@
4d (WAg Æ HPH@0)
W
1.10
.45
3
3
.78
.93
.67
.02
1
1
.00 (.00‐.10)
.00 (.00‐.05)
.84
.95
5 (HAg Æ PH &
WAg Æ HPH constrain =)
W

2.81
2.62
3 .42 2.38
2
1 .00 (.00‐.15) .54
6a (HAg Æ PH &
WAg Æ WPH constrain =)
6
H
3 .45 .19 1 .00 (.00‐.15) .58
b (WAg Æ HPH &
Ag Æ HPH constrain =)
.61 3 .89 .18 1 .00 (.00‐.07) .93
HAg = Husband Aggression. WAg = Wife Aggression. HDep = Husband Depression. WDep = Wife Depression.
HPH = Husband Physical Health Composite. WPH = Wife Physical Health Composite. * p<.05

Table 9 displays model fit information for alternative models representing
hypotheses 1 thru 6. The null hypothesis that the effect of husband aggression on
wife depression is equal to the effect of wife aggression on husband depression was
not rejected (hypothesis 2). Similarly, the null hypothesis that husband aggression
has an equal effect on wife physical health as wife aggression has on husband
physical health could not be rejected (hypothesis 5). Finally, hypotheses 3 and 6,
which predicted that aggression victimization would have a stronger impact on
depression and physical health than aggression perpetration, also were not

62
supported. Although the path from husband aggression to wife physical health was
significant in the path model (hypothesis 4a), constraining this path to zero caused a
decrease in model fit that did not reach significance (p = .0503).
Paths from husband and wife aggression to wife depression were non‐
significant in the hypothesized model. However, constraining both of these paths to
zero led to a significant decrease in model fit, χ
2
change (2, N = 117) = 7.44, p = .02.
Constraining either path to zero individually caused the other path to become
significant. The strong association between husband and wife aggression makes it
difficult for these variables to explain unique variance in wife depression. Although
neither path was significant in the model, husband and wife aggression do appear to
be associated with wife depression based on this model fit comparison and
correlational findings.
Heckman Correction. Table 10 displays unstandardized and standardized
coefficients for the hypothesized model depicted in Figure 2 with the addition of the
Heckman Correction probability variable. The addition of the Heckman Correction
did not impact the pattern of relationships among the variables. Effect coefficients
changed minimally ( ≤ .04 for Bs and ≤ .03 for βs) for hypothesized relationships
between the primary model variables. Table 11 displays model fit information for
alternative models representing hypotheses 1 thru 6 for analyses including the
Heckman Correction. This table generally displays identical results to those
presented in Table 9. However, constraining the path from husband aggression to

63

wife physical health to zero (hypothesis 4a) resulted in a significant decrease in
model fit in the Heckman Correction model.

Table 10. Unstandardized, Standardized, and Significance Levels for Hypothesized Model with Heckman Correction (N = 117)
64

Parameter Estimate Unstandardized
(S.E.)
Critical
Ratio
p Standardized
a
(S.E.)
Critical
Ratio
P
Husb. Aggression Æ Wife Depression

.37   (.39) .96 .34 .21 (.21) 1.00 .32
Wife Aggression Æ Wife Depression .38   (.30) 1.28 .20 .24 (.18) 1.30 .20
Income   Wife Depression Æ Husb. Hispanic/Latino Æ Wife Depression
‐.003 (.02) ‐.16 .87 ‐.02 (.11) ‐.16 .87
Wife Education Wife Depression Æ Wife Hispanic/Latina Æ Wife Depression
.25   (.46) .53 .59 .06 (.10) .53 .59
2.27 (2.66) .85 .39 .22 (.26) .84 .40
1.77 (2.64) .67 .50 .17 (.25) .68 .50
Heckman Correction Wife Depression Æ Husb. Aggression Æ Husb. Depression
‐5.64 (3.83) ‐1.47 .14 ‐.17 (.11) ‐1.51 .13

1.02   (.43) 2.38 .02 .48 (.18) 2.64 .01
Wife Aggression Æ Husb. Depression .08   (.33) .24 .81 .04 (.17) .24 .81
Income Æ Husb. Depression ‐.01   (.02) ‐.20 .84 ‐.02 (.11) ‐.20 .84
Wife Education   Husb. Depression Æ Wife Hispanic/Latina Æ Husb. Depression
‐.62   (.53) ‐1.17 .24 ‐.12 (.10) ‐1.17 .24
Husb. Hispanic/Latino Æ Husb. Depression ‐4.90 (2.97) ‐1.65 .10 ‐.40 (.23) ‐1.70 .09
5.68 (2.95) 1.92 .06 .46 (.24) 1.95 .051
Heckman Correction Husb. Depression Æ Husb. Aggression Æ Wife Physical Health
‐2.42 (4.43) ‐.55 .59 ‐.06 (.11) ‐.55 .58

.08   (.04) 2.00 .05 .51 (.22) 2.30 .02
Wife Aggression Æ Wife Physical Health ‐.01   (.02) ‐.34 .73 ‐.06 (.18) ‐.34 .73
Wife Depression Æ Wife Physical Health .01   (.01) 1.14 .26 .11 (.09) 1.12 .26
Income Wife Physical Health Æ Husb. Hispanic/Latino Æ Wife Physical Health
‐.003 (.002) ‐1.75 .08 ‐.17 (.10) ‐1.75 .08
Wife Education   Wife Physical Health Æ Wife Hispanic/Latina Æ Wife Physical Health
.03   (.04) .72 .48 .08 (.11) .72 .47
.02   (.21) .11 .91 .03 (.24) .11 .91
.39   (.20) 1.94 .053 .46 (.23) 1.97 .05
Heckman Correction Wife Physical Health Æ Husb. Aggression Æ Husb. Physical Health
‐.60   (.44) ‐1.38 .17 ‐.22 (.15) ‐1.43 .15
.02   (.03) .81 .42 .18 (.21) .82 .41
Wife Aggression Æ Husb. Physical Health .01   (.02) .22 .83 .04 (.19) .22 .83
Husb. Depression Æ Husb. Physical Health

.02   (.01) 2.51 .01 .28 (.11) 2.50 .01

Table 10, Continued. Unstandardized, Standardized, and Significance Levels for Hypothesized Model with Heckman Correction
65
(N = 117)

Parameter Estimate Unstandardized
(S.E.)
Critical
Ratio
p Standardized
a
(S.E.)
Critical
Ratio
P
Income Æ Husb. Physical Health ‐.001 (.001) ‐.85 .40 ‐.09 (.10) ‐.85 .40
Wife Education Husb. Physical Health Æ Husb. Hispanic/Latino Æ Husb. Physical
Health
‐.09   (.04) ‐2.52 .01 ‐.27 (.10) ‐2.59 .01
.28   (.21) 1.34 .18 .36 (.27) 1.32 .19
Wife Hispanic/Latina Æ Husb. Physical Health ‐.14   (.21) ‐.69 .49 ‐.18 (.27) ‐.69 .49
Heckman Correction   Husb. Physical Health Æ Covariance Husb. & Wife Aggression
.80   (.41) 1.93 .054 .32 (.16) 2.05 .04
33.37 (4.65) 7.17 <.001 .88 (.02) 44.00 <.001
Covariance Husb. & Wife Depression 30.15 (9.20) 3.28 .001 .34 (.09) 3.93 <.001
Covariance Husb. & Wife Physical Health .06   (.05) 1.39 .16 .17 (.12) 1.45 .15
Residual for Wife Depression 78.68 (11.02) 7.14 <.001 .74 (.12) 6.02 <.001
Residual for Husb. Depression 98.00 (13.78) 7.11 <.001 .64 (.12) 5.19 <.001
Residual for Wife Physical Health .41   (.06) 6.42 <.001 .55 (.14) 3.84 <.001
Residual for Husb. Physical Health .37   (.06) 6.36 <.001 .60 (.10) 5.78 <.001
Indirect Effects
Husb. Aggression   Husb. Depression Æ Æ   Husb. Physical Health
.02   (.01) 1.73 .08 .14 (.08) 1.75 .08
Note: χ
2
(2, N = 117) = .22, p(perfect) = .90; RMSEA = .00 (90% Confidence Interval = .00 ‐ .08) , p(close) = .92.
a
Standardized coefficients may be interpreted as the
amount of change in y in y standard deviation units, given a standard deviation change in x for all variables except binary variables. For binary variables (i.e., Husband
or Wife Hispanic/Latino(a) status), standardized coefficient represents the change in y in y standard deviation units given a change from zero to one in x.

66
T
H

able 11. Model Comparisons Evaluating Hypothesized Relationships in Model with
eckman Correction
Hypothesized Model χ
2
df p(perfect) χ
2
Δ
df
Δ
RMSEA
(90% C.I) p(close)
Full Model .22 2 .90 ‐‐ ‐‐ .00 (.00‐.08) .92
1a (HAg WDep@0) Æ
Æ
1.15
1.85
5.73
3 .77 .93
1
5.
1 .00 (.00‐.11) .84
1b (WAg WDep@0)
Æ 0)
3 .60 .63 1 .00 (.00‐.13) .71
1c (HAg HDep@
1d (WAg Æ HDep@0)
W
3
3
.13
.96
51*
.06
1
1
.09 (.00‐.20)
.00 (.00‐.00)
.22
.98 .28
2 (HAg Æ Dep &
WAg Æ HDep constrain =)
W

.49 3 .92 .27 1 .00 (.00‐.05) .95
3a (HAg Æ Dep &
WAg Æ WDep constrain =)
Æ ep constrain =)
.22 3 .97 .00 1 .00 (.00‐.00) .98
3b (WAg HDep &
HAg Æ HD
Æ
Æ
2.05
4
3 .56 1.83
3.
1 .00 (.00‐.14) .67
4a (HAg WPH@0) .10 3 .25 88* 1 .06 (.00‐.18) .37
4b (WAg WPH@0)
Æ 0)
.34 3 .95 .12 1 .00 (.00‐.00) .97
4c (HAg HPH@
4d (WAg Æ HPH@0)
W
.87
.27
3
3
.83
.97
.65
.05
1
1
.00 (.00‐.09)
.00 (.00‐.00)
.88
.98
5 (HAg Æ PH &
WAg Æ HPH constrain =)
W

2.53
2.44
3 .47 2.31
2
1 .00 (.00‐.15) .59
6a (HAg Æ PH &
WAg Æ WPH constrain =)
6
H
3 .49 .22 1 .00 (.00‐.14) .60
b (WAg Æ HPH &
Ag Æ HPH constrain =)
.37 3 .95 .15 1 .00 (.00‐.02) .96
HAg = Husband Aggression. WAg = Wife Aggression. HDep = Husband Depression. WDep = Wife Depression.
HPH = Husband Physical Health Composite. WPH = Wife Physical Health Composite. * p<.05

Exploratory Models
To further examine relationships between aggression, depression, and
health, models for total aggression, depression, and the five individual health indices
are presented below. Additionally, models examining emotional and physical
aggression separately also are presented. These models are post‐hoc examinations
of the data. Any conclusions from these models should be viewed with caution.
However, exploration of these data may inform our understanding of the
relationships in the primary model and may provide hypothesis for examination in

67
future data sets. Standardized coefficients are presented for models with
continuous outcomes, and unstandardized coefficients are presented for the models
with outcome variables specified as count variables. Adding the Heckman
Correction to these models generally had minimal impact on parameter estimates
and did not change the pattern of results for the majority of the models. However,
the Heckman Correction did lead to several changes in the results. Heckman
correction findings are discussed below only if the addition of the Heckman
Correction impacted the pattern of results.
Total Aggression and the Five Health Indices. Figures 3‐7 depict models
for total aggression, depression, and the five health indices.

68

Figure 3. Path model for spouse total aggression, depression, and health conditions
index (Unstandardized Solution)

No fit indices available for models with count variables. N = 116.
Income was included in the model with paths from income to each of the primary model variables. These paths
ere not included in the above diagram for visual simplicity. H = Husband, W = Wife, Aggr. = Total Aggression
Physical + Emotional), Depr. = Depression, HC = Health Conditions, Inc. = Household Income in $1000s (Years
/5).   *p<.05, **p<.01, ***p<.001; † p<.05 in Heckman‐corrected model.
w
(
4

Health Conditions. Husband aggression had a direct effect on the wife
health condition index that did not reach statistical significance, p = .051. However,
with the addition of the Heckman Correction to this model, the direct effect from
husband aggression to wife health conditions was significant, B = .09, S.E. = .04, p =
.04. There were no significant effects on husband health conditions.

69

Figure 4. Path model for spouse total aggression , depression, and subclinical
symptoms index (Standardized Solution)

χ
2
(12 N = 117) = 1.11, p(perfect) = .58; RMSEA = .00 (90% C.I. = .00 ‐ .15), p(close) = .66.
Income, wife education, and wife Hispanic/Latino status were included in the model with paths from each of
these variables to each of the primary model variables. These variables and paths were not included in the
above diagram for visual simplicity. H = Husband, W = Wife, Aggr. = Total Aggression (Physical + Emotional),
Depr. = Depression, SC = Subclinical Symptoms, Educ. = Education, Inc. = Household Income in $1000s (Years
4/5), H/L = Hispanic/Latino(a) Ethnic Status. Italicized path coefficients for binary exogenous variables (i.e.,
Hispanic/latino(a) status) are interpreted as the change in y (outcome variable) in y standard deviation units
hen the binary variable changes from zero to one. Other path coefficients are interpreted as the change in y in
standard deviation units for a standard deviation change in x. *p<.05, **p<.01, ***p<.001; † p<.05 in Heckman‐
orrected model.
w
y
c

Subclinical Health Symptoms. There was a total effect between husband
aggression and wife subclinical symptoms that did not reach statistical significance,
β= .50, S.E. = .24, p = .06. There was also a total effect between husband aggression

70
and husband subclinical symptoms that did not reach significance, β= .46, S.E. = .23,
p = .052. The relationship between husband aggression and husband depression did
not reach significance, p = .051. However, this path was significant in the model
ith the Heckman Correction added, β= .42, S.E. = .19, p = .04. w

Figure 5. Path model for spouse total aggression, depression, and preventive care
index (Unstandardized Solution)

No fit indices available for models with count variables. N = 117.
Income, number of children, husband Hispanic/Latino, and wife Hispanic/Latina status were included in the
model with paths from each of these variables to each of the primary model variables. These variables and
paths were not included in the above diagram for visual simplicity. H = Husband, W = Wife, Aggr. = Total
Aggression (Physical + Emotional), Depr. = Depression, PC = Preventive Care, Inc. = Household Income in $1000s
(Years 4/5), H/L = Hispanic/Latino(a) Ethnic Status. *p<.05, **p<.01, ***p<.001

71
Preventive Care. Husband aggression had a direct effect on wife preventive
care that did not reach statistical significance, p = .06. There were no significant
effects on husband preventive care.

Figure 6. Path model for spouse total aggression, depression, and health behaviors
index (Standardized Solution)

χ
2
(2, N = 117) = .91, p(perfect) = .64; RMSEA = .00 (90% C.I. = .00 ‐ .15), p(close) = .71.
Income, husband education, wife education, wife age, husband Hispanic/Latino status, and wife Hispanic/Latina
status were included in the model with paths from each of these variables to each of the primary model
variables. These variables and paths were not included in the above diagram for visual simplicity. H = Husband,
W = Wife, Aggr. = Total Aggression (Physical + Emotional), Depr. = Depression, HB = Health Behaviors, Educ. =
Education, Inc. = Household Income in $1000s (Years 4/5), H/L = Hispanic/Latino(a) Ethnic Status. Italicized
path coefficients for binary exogenous variables (i.e., Hispanic/latino(a) status) are interpreted as the change in
y (outcome variable) in y standard deviation units when the binary variable changes from zero to one. Other
path coefficients are interpreted as the change in y in y standard deviation units for a standard deviation change
in x. *p<.05, **p<.01, ***p<.001

72
Health Behaviors. Husband aggression had a significant negative direct
effect on wife health behavior. There were no significant effects on husband health
ehavior. b
Physical Health Quality of Life. The hypothesized model with physical
health quality of life (PH QOL) as the health outcome displayed poor fit, χ
2
(2, N =
117) = 6.14, p(perfect) < .05; RMSEA = .13 (90% C.I. = .02 ‐ .26), p(close) = .09.
Adding a path from wife depression to husband PH QOL improved model fit (see
Figure 7). Husband aggression had a significant direct effect on wife PH QOL.
Husband depression had a significant direct effect on husband PH QOL and wife
depression had a significant negative direct effect on husband PH QOL. There was
an indirect effect from husband aggression to husband PH QOL via husband
depression that did not reach significance, β = .21, S.E. = .11, p = .07.

73

Figure 7. Path model for spouse total aggression, depression, and physical health quality
of life index (Standardized Solution)

χ
2
(1, N = 117) = .52, p(perfect) = .47; RMSEA = .00 (90% C.I. = .00 ‐ .22), p(close) = .53.
Income, husband education, and wife Hispanic/Latina status were included in the model with paths from each of
these variables to each of the primary model variables. These variables and paths were not included in the
above diagram for visual simplicity. H = Husband, W = Wife, Aggr. = Total Aggression (Physical + Emotional),
Depr. = Depression, QOL = Physical Health Quality of Life Index, Educ. = Education, Inc. = Household Income in
$1000s (Years 4/5), H/L = Hispanic/Latino(a) Ethnic Status. Italicized path coefficients for binary exogenous
variables (i.e., Hispanic/latino(a) status) are interpreted as the change in y (outcome variable) in y standard
deviation units when the binary variable changes from zero to one. Other path coefficients are interpreted as
the change in y in y standard deviation units for a standard deviation change in x. *p<.05, **p<.01, ***p<.001

Emotional Aggression and Health. Figures 8‐13 depict models for
emotional aggression, depression, and the physical health composite and five health
indices (analogous physical aggression models are shown below each of the

74
emotional aggression models in each figure). As with total aggression, husband
emotional aggression had a significant direct effect on husband depression in
several of the models. Neither spouse’s emotional aggression had a significant effect
on wife aggression. However, similar to total aggression, constraining paths from
husband and wife aggression to wife depression to zero led to a significant decrease
in model fit, χ
2
(2, N = 118)= 8.22, p = .02. Constraining at zero either one of the
effects from husband or wife emotional aggression to wife depression caused the
other effect to become significant.
Emotional aggression models produced the same pattern of results as the
total aggression models for the physical health composite scale and health behaviors
index.
Husband emotional aggression had a significant direct effect on wife health
conditions, as in the Heckman‐corrected total aggression model (see Figure 9).
Husband emotional aggression had a non‐significant effect, p = .06, on wife
depression; with the addition of the Heckman correction this effect was significant,
β = .60,

S.E. = .30, p = .04.
As shown in Figure 10, husband emotional aggression had a significant direct
effect on wife subclinical symptoms. Husband depression had a significant direct
effect on husband subclinical symptoms, and there was a significant total effect from
husband aggression to husband subclinical symptoms, β = .38, S.E. = .17, p = .03. The
relationship between husband emotional aggression and husband depression did
not reach statistical significance in this model, p = .06.
75
As shown in Figure 11, husband emotional aggression had a significant effect
on wife preventive care behaviors. The effect from wife emotional aggression to
husband preventive care was not significant, p = .18. However, in the Heckman‐
corrected model, this path was significant, B = .05, S.E. = .02, p = .02.
Finally, relationships with emotional aggression in the physical health quality
of life model (see Figure 12) were very similar to those in the total aggression
model. The effect from husband emotional aggression to husband depression was
non‐significant, β = .30, S.E. = .15, p = .06, but was significant with the addition of the
Heckman Correction, β = .31, S.E. = .15, p = .05.   The indirect effect from husband
emotional aggression to husband physical health quality of life via husband
depression did not reach significance, β = .15, S.E. = .09, p = .08, as was the case for
the total aggression model. Also, as with the total aggression model, the effect from
usband emotional aggression to wife physical health quality of life was significant. h

76
Figure 8. Trimmed path model for spouse emotional (top)/physical (bottom)
aggression, depression, and physical health composite (Standardized Solution)

χ
2
(2, N = 118) = .52, p(perfect) = .77; RMSEA = .00 (90% C.I. = .00 ‐ .12), p(close) = .82.

χ
2
(2, N = 117) = .11, p(perfect) = .95; RMSEA = .00 (90% C.I. = .00 ‐ .03), p(close) = .96.
Income, wife education, husband Hispanic/Latino status, and wife Hispanic/Latina status were included in the
model with paths from each of these variables to each of the primary model variables. These variables and
paths were not included in the above diagram for visual simplicity. H = Husband, W = Wife, EA = Emotional
Aggression, PA = Physical Aggression, Depr. = Depression, PH = Physical Health Composite Scale, Educ. =
Education, Inc. = Household Income in $1000s (Years 4/5), H/L = Hispanic/Latino(a) Ethnic Status. Italicized
path coefficients for binary exogenous variables (i.e., Hispanic/latino(a) status) are interpreted as the change in
y (outcome variable) in y standard deviation units when the binary variable changes from zero to one. Other
path coefficients are interpreted as the change in y in y standard deviation units for a standard deviation change
in x. *p<.05, **p<.01, ***p<.001

77
Figure 9. Trimmed path model for spouse emotional (top)/physical (bottom)
aggression, depression, and health conditions index (Unstandardized Solution)

No fit statistics are available for models with count outcomes. N = 118.

No fit statistics are available for models with count outcomes. N = 116.
Income was included in the model with paths from income to each of the primary model variables. These paths
were not included in the above diagram for visual simplicity. H = Husband, W = Wife, EA = Emotional
Aggression, PA = Physical Aggression, Depr. = Depression, PH = Physical Health Composite Scale, Inc. =
Household Income in $1000s (Years 4/5). *p<.05, **p<.01, ***p<.001; † p<.05 in Heckman‐corrected model.

78
Figure 10. Trimmed path model for spouse emotional (top)/physical (bottom)
aggression, depression, and subclinical symptoms index (Standardized Solution)

χ
2
(2, N = 118) = 1.11, p(perfect) = .57; RMSEA = .00 (90% C.I. = .00 ‐ .15), p(close) = .66.

χ
2
(2, N = 117) = .83, p(perfect) = .66; RMSEA = .00 (90% C.I. = .00 ‐ .14), p(close) = .73.
Income, wife education, and wife Hispanic/Latina status were included in the model with paths from each of
these variables to each of the primary model variables. These variables and paths were not included in the
above diagram for visual simplicity. H = Husband, W = Wife, EA = Emotional Aggression, PA = Physical
Aggression, Depr. = Depression, SC = Subclinical Symptoms, Educ. = Education, Inc. = Household Income in
$1000s (Years 4/5), H/L = Hispanic/Latino(a) Ethnic Status. Italicized path coefficients for binary exogenous
variables (i.e., Hispanic/Latino(a) status) are interpreted as the change in y (outcome variable) in y standard
deviation units when the binary variable changes from zero to one. Other path coefficients are interpreted as
the change in y in y standard deviation units for a standard deviation change in x. *p<.05, **p<.01, ***p<.001

79
Figure 11
Trimmed path model for spouse emotional (top)/physical (bottom) aggression,
depression, and preventive care index (Unstandardized Solution)

No fit indices available for models with count outcomes. N = 118.

No fit indices available for models with count outcomes. N = 116.
Income, number of children, husband Hispanic/Latino status, and wife Hispanic/Latina status were included in
the model with paths from each of these variables to each of the primary model variables. These variables and
paths were not included in the above diagram for visual simplicity. H = Husband, W = Wife, EA = Emotional
Aggression, PA = Physical Aggression, Depr. = Depression, PC = Preventive Care Index, Educ. = Education, Inc. =
Household Income in $1000s (Years 4/5), H/L = Hispanic/Latino(a) Ethnic Status. *p<.05, **p<.01, ***p<.001; †
p<.05 in Heckman‐corrected model.

80
Figure 12
Trimmed path model for spouse emotional (top)/physical (bottom) aggression,
depression, and health behaviors index (Standardized Solution)

χ
2
(2, N = 118) = .89, p(perfect) = .64; RMSEA = .00 (90% C.I. = .00 ‐ .14), p(close) = .72.

χ
2
(2, N = 117) = .71, p(perfect) = .70; RMSEA = .00 (90% C.I. = .00 ‐ .14), p(close) = .77.
Income, wife education, husband education, wife age, husband Hispanic/Latino status, and wife Hispanic/Latina
status were included in the model with paths from each of these variables to each of the primary model
variables. These variables and paths were not included in the above diagram for visual simplicity. H = Husband,
W = Wife, EA = Emotional Aggression, PA = Physical Aggression, Depr. = Depression, HB = Health Behaviors
Index, Educ. = Education, Inc. = Household Income in $1000s (Years 4/5), H/L = Hispanic/Latino(a) Ethnic
Status. Italicized path coefficients for binary exogenous variables (i.e., Hispanic/latino(a) status) are interpreted
as the change in y (outcome variable) in y SD units when the binary variable changes from zero to one. Other
path coefficients are interpreted as the change in y in y SD units for a SD change in x. *p<.05, **p<.01, ***p<.001

81
Figure 13
Trimmed path model for spouse emotional (top)/physical (bottom) aggression,
depression, and physical health quality of life index (Standardized Solution)

χ
2
(1, N = 118) = .81, p(perfect) = .37; RMSEA = .00 (90% C.I. = .00 ‐ .23), p(close) = .44.

χ
2
(1, N = 116) = 1.00, p(perfect) = .32; RMSEA = .00 (90% C.I. = .00 ‐ .25), p(close) = .39.
Income, husband education, and wife Hispanic/Latina status were included in the model with paths from each of
these variables to each of the primary model variables. These variables and paths were not included in the
above diagram for visual simplicity. H = Husband, W = Wife, EA = Emotional Aggression, PA = Physical
Aggression, Depr. = Depression, QOL = Physical Quality of Life Index, Educ. = Education, Inc. = Household Income
in $1000s (Years 4/5), H/L = Hispanic/Latino(a) Ethnic Status. Italicized path coefficients for binary exogenous
variables (i.e., Hispanic/latino(a) status) are interpreted as the change in y (outcome variable) in y SD units
when the binary variable changes from zero to one. Other path coefficients are interpreted as the change in y in
y SD units for a SD change in x. *p<.05, **p<.01, ***p<.001; † p<.05 in Heckman‐corrected model.

82
Physical Aggression and Health. Figure 8 depicts the modeled
relationships for physical aggression, depression, and the physical health composite
scale. There were no direct effects on wife physical health from aggression or
depression. There was a significant direct effect from husband depression to
husband physical health, and a significant indirect effect from husband aggression to
husband physical health via husband depression, β= .25, S.E. = .12, p = .05.
As shown in Figure 9, there were no significant effects on husband or wife
health conditions.
For subclinical symptoms (see Figure 10), wife depression had a direct effect
on wife subclinical symptoms and husband depression has a direct effect on
husband subclinical symptoms. There was a significant total effect from husband
physical aggression to husband subclinical symptoms, β = .65, S.E. = .25, p = .03. The
indirect effect from husband physical aggression to husband subclinical symptoms
via husband depression did not reach significance, β = .24, S.E. = .12, p = .06.
As shown in Figure 11, there is a direct effect from wife physical aggression
to husband preventive care.   The total effect from husband physical aggression to
husband preventive care was non‐significant, B = ‐.10, S.E. = .05, p = .053. Similarly,
in the Heckman‐corrected model, this total effect still was not significant, B = ‐.07,
S.E. = .05, p = .16.
There were no significant effects from physical aggression to wife health
behaviors (see Figure 12). The effect from husband physical aggression to husband

83
health behaviors was non‐significant in the non‐Heckman‐corrected, β = ‐.61, S.E. =
.30, p = .06, and Heckman‐corrected models, β = ‐.59, S.E. = .28, p = .053.
As shown in Figure 13, there are significant direct effects from wife
depression and husband depression to husband physical health quality of life.
There is a significant indirect effect from husband physical aggression to husband
PH QOL via husband depression, β = .34, S.E. = .15, p = .03, and a significant total
effect from husband physical aggression to husband PH QOL, β = .59, S.E. = .24, p =
.04. There are no significant effects from spouse physical aggression variables to
wife PH QOL.

84

Chapter 4: Discussion
Confirmatory Model Results
This study examined associations between husband and wife spouse
aggression, depression, and physical health constructs over four time points in a
longitudinal study of midlife couples who were not selected for levels of aggression,
specific health problems, presentation for therapy or medical treatment. The
partner aggression characteristic of these couples was generally lower severity,
particularly in terms of risk for injury (i.e., pushed, grabbed or shoved, or thrown an
object at spouse), and strongly correlated among husbands and wives.
Examination of relationships between partner aggression, depression, and
physical health status for these couples revealed a number of important effects. In
the primary model, as hypothesized, husband aggression perpetration was related
to husband depression. Also as hypothesized, husband aggression perpetration
during the first three waves of the study was significantly related to a composite
construct of wives’ physical health approximately two to three years later. There
was an indirect effect from husband aggression perpetration to husband physical
health via husband depression that did not reach significance in the total aggression
model. Wife aggression perpetration did not have significant paths to either
spouse’s depression or physical health. Finally, although there were not significant
paths from husband and wife aggression to wife depression, removing these paths
from the model significantly decreased model fit. Thus, there was some evidence for

85
husband and wife aggression being associated with wife depression. Given the
strong correlation between husband and wife aggression, it appeared that
attributing unique variance to one spouse’s aggression versus the other spouse’s
aggression was not possible, in terms of the relationship of these variables to wife
depression. Both husband and wife aggression were significantly, positively
associated with wife depression in the correlational results.
A number of hypothesized effects were not present or did not reach
statistical significance. Whereas both direct effects from aggression perpetration
and victimization to physical health and indirect effects via depression were
hypothesized, only husband aggression had a direct association with wife physical
health. The indirect effect from husband aggression on husband physical health via
husband depression did not reach significance. Wife aggression did not appear to
play a role in predicting the physical health composite constructs for either spouse,
and there was not an indirect effect of aggression victimization on wife physical
health via wife depression. Furthermore, it was hypothesized that aggression
victimization would have stronger associations than aggression perpetration with
depression and physical health outcomes for both spouses. It also was hypothesized
that husband aggression would have a stronger relationship with wife outcomes of
depression and physical health than wife aggression would with husband outcomes.
However, during model hypothesis testing analyses, there were no significant
differences in path magnitudes for aggression perpetration versus victimization and
for relative associations of husband aggression versus wife aggression on

86
depression and physical heath outcomes. Based on path coefficients and
significance levels, it appears that aggression victimization and perpetration have
equally important relationships with wife depression, but that husband aggression
perpetration has a stronger relationship with wife physical health. For husbands, it
appears that aggression perpetration has a stronger relationship with husband
depression than aggression victimization does, and that neither aggression
perpetration nor victimization has direct associations with husband physical health.
Finally, it appears that husband aggression has stronger relationships with wife
physical health than wife aggression has with husband physical health, and that
husband aggression has a stronger relationship with wife depression than wife
aggression has with husband depression. However, despite these differences in
significance levels of paths, statistically significant differences between path
coefficient magnitudes were not detected for the current sample. Given the pattern
of results, it is possible that there was insufficient power to detect differences
related to these hypotheses.
Exploratory Models
To further explore the associations identified in the confirmatory model, a
number of post‐hoc models were run to examine relationships with the five
individual health indices and the contributions of emotional and physical
aggression. Caution should be taken in interpreting these findings prior to
replication given the non‐confirmatory approach and the number of models
examined.

87
As with total aggression, husband physical aggression had significant
associations with husband depression in the physical health composite model and in
four of the five health index models. Husband emotional aggression was related to
husband depression in the composite model and in two of the five health index
models. This difference among the models could be attributed to different control
variables being included in the models depending on the health outcome analyzed,
and/or the count models having lower power. For both the emotional aggression
and physical aggression models, both husband and wife aggression did not have
significant direct effects on wife depression. However, based on correlational
results and model fit comparisons, it appeared that husband and wife aggression do
have associations with wife depression. The strong correlation between husband
and wife aggression may have not allowed for unique variance to be attributed to
one spouse’s use of aggression. In the literature, increased levels of depressive
symptoms for females victimized by partner aggression have been consistently
identified (e.g., Golding, 1999). Fewer studies have examined female aggression
perpetration, but several previous investigations have identified links between
wives’ use of aggression and wives’ depression as well (Anderson, 2000, Grandin et
al., 1998).
Exploratory Models: Individual Health Indices and Emotional Aggression
Findings
For models examining the individual health indices, husband total aggression
showed significant positive relationships (increases in aggression related to

88
increases in poor physical health) with the health conditions and physical health
quality of life indices for wives. Additionally, for the subclinical symptoms and
preventive care indices, there was some evidence for a relationship between
husband aggression and wife physical health, but these paths did not reach
statistical significance (ps < .06).  Husband aggression had a significant association
with wife health behaviors; however, this relationship was negative with increased
aggression being related to more positive health behaviors. There were no direct or
indirect effects from wife total aggression to any of the individual husband or wife
health indices. There was a non‐significant indirect effect from husband aggression
to husband health‐related quality of life via husband depression, p = .07, and a non‐
significant total effect from husband aggression to husband subclinical symptoms, p
= .06.
For models examining only accumulated emotional aggression rather than
total aggression, the results were largely the same as those found in the total
aggression models, except for subclinical symptoms and preventive care. The path
from husband emotional aggression to wife preventive care was significant (this
path had a p‐value = .06 in the total aggression model). There was also a significant
association between wife emotional aggression and husband preventive care
behaviors in the Heckman‐corrected model. For subclinical symptoms, the
association between husband emotional aggression and wife subclinical symptoms
was significant, and there was a significant total effect from husband emotional

89
aggression to husband subclinical symptoms (both of these paths also had p‐values
≤ .06 in the total aggression models).
These results coincided with findings in a number of previous studies,
particularly regarding links between husband aggression and wife health
conditions, subclinical symptoms, and physical health quality of life indices. Several
previous publications have supported the link found in this study between intimate
partner violence and adverse health, quantified as number of health conditions, for
women. This study did not have the sample size to examine risk for specific health
conditions, which has been the focus of several recent larger studies (e.g., Bonomi,
Anderson, Reid, et al., 2009). However, some researchers have suggested that, given
the range and breadth of physical health conditions with associations with violence
and the number of stress‐impacted health problems, the presence of multiple
conditions or increased symptoms may provide a better understanding of
victimization impacts than examining specific or particular clinical symptoms or
diagnoses (Nicolaidais et al., 2004). Notably, the present study focused on new
health conditions encountered after the last report of partner aggression. Methods
in few prior studies appeared to take into account the timing of onset for health
conditions in relation to aggression experiences. Effects from emotional aggression
victimization to the subclinical symptoms index for wives in the current study
correspond to previous research associating intimate partner violence and somatic
symptoms, including pain and fatigue, and poor health days. Similarly, a number of
studies have now supported links between aggression victimization and physical

90
health quality of life for women. A few studies have examined individual preventive
care behaviors and found no differences in healthcare usage or cholesterol
screening for women, and an increased odds of receiving a regular PAP smear
(Cronholm & Bowman, 2009; Lemon et al., 2002). Another study found increased
health care utilization (Tomasulo & McNamara, 2007), which is in line with studies
on the notable economic costs of IPV‐related healthcare usage (Brown et al., 2008;
Rivara et al., 2007). Reviews and theoretical models have posited inappropriate
healthcare utilization as an effect of intimate partner violence (Resnick et al., 1997).
The present study identified that emotional aggression victimization was associated
with meeting fewer health utilization guidelines, after taking into account
socioeconomic status variables.
In the present study, contrary to expectation, husband aggression was
connected to more positive health behaviors for women. Research examining
intimate partner violence and physical health behaviors has generally examined
individual behaviors, with some items on the current health behaviors index being
examined more frequently (e.g., alcohol abuse, drug abuse) than other behaviors on
the index (e.g., fruit and vegetable servings, servings of milk, unhealthy weight
management practices). This study attempted to gain a broader view of aggression
and depression associations with health behaviors by creating an index of health
behaviors based on dichotomizing health behavior data for individual items; thus
data were examined differently than in most previous studies that found the
opposite direction effect from partner aggression victimization to a number of

91
individual health behaviors (e.g., smoking, alcohol consumption, sleep). Tomasulo
and McNamara (2007) examined an index of 12 health behaviors, taking a more
similar approach to the current study, and found that aggression victimization was
related to more negative health behaviors for women. Their health index included a
number of different items than those examined in this study (e.g., wearing a seatbelt,
knowing current blood pressure, reading nutrition labels for fat content) and
included some items that would be conceptualized as part of the preventive care
index in this study (i.e., annual dental exam, knowing current cholesterol level,
performing monthly self‐breast exam). Further research is needed on methods for
gaining a more global perspective on individuals’ health behaviors.
The data do not provide a clear explanation for the unexpected, opposite‐
direction association between aggression victimization and wife health behaviors in
this study, but several hypotheses deserve consideration. Accumulated levels of
husband aggression were reported over a three‐year time period on average 2.7
years prior to reported health behaviors. Current health status of individuals in this
age group may more strongly influence their health behaviors. Individuals with
poorer health may have received medical counseling and have health‐related
motivations to improve their health behaviors. Individuals with better health may
put less attention towards the full range of or certain positive health behaviors (e.g.,
avoiding smoking, but still not exercising or eating recommended fruit and
vegetable servings). Given that husband aggression was related to new wife health
conditions, these new health condition diagnoses may have been accompanied by

92
medical advice to change certain behaviors. This advice may have led to changes in
behavior or a heightened awareness of what health behavior “should be”, which
could have increased social desirability in self‐reporting or created unintentional
bias in estimations of behavior. Alternatively, it is possible that current levels of
stress or aggression exposure influence current health behaviors in a different way,
given that behavior may fluctuate more than the other non‐behavior‐oriented health
indices. Another hypothesis is that individuals with ongoing stress, such as marital
aggression, may be more likely to take positive steps to moderate the impact of this
stress through positive health behaviors. Further study is needed to understand
partner aggression impacts on health behaviors, particularly because this is a
hypothesized mechanism through which one could improve health or moderate
impacts of aggression‐related stress. Finally, the relationship between husband
aggression and more positive health behaviors could reflect higher levels of anxiety
about appearance or faults perceived by spouse causing women to have higher
vigilance about health behaviors. Given the exploratory nature of this model and
counterintuitive findings, clearly more research is needed examining intimate
partner violence and a constellation of health behaviors.
Explor sion atory Models: Physical Aggression versus Total and Emotional Aggres
For models examining only physical aggression, there were a number of
differences from the total and emotional aggression models. Most notably, there
were no significant effects between husband physical aggression and wife physical
health; whereas, total aggression was associated with four of the health indices, and

93
emotional aggression had associations with all of the health indices. For physical
aggression, the indirect effect from husband aggression to the husband physical
health composite variable via husband depression was significant (this effect had p‐
values < .10 in the total and emotional aggression models).  There was a significant
indirect effect from husband aggression to husband health‐related quality of life via
husband depression, and a significant total effect from husband physical aggression
to husband subclinical symptoms, as well. Finally, in the physical aggression model,
as in the emotional aggression model, there was a significant direct effect from wife
aggression to husband preventive care. These were the only significant
relationships from wife aggression to any of the physical health constructs.
Examination of emotional and physical aggression in separate models
suggests that husband emotional aggression played a predominant role in the
relationships between husband aggression and wife health in the total aggression
models. However, associations between husband aggression and husband physical
health were significant only in physical aggression models (physical health
composite, subclinical symptoms, and physical health quality of life) and for
husband emotional aggression with husband subclinical symptoms. These findings
build on previous literature that has identified emotional aggression victimization
as potentially more important than physical aggression for impacts on females’
physical health (e.g., Taft et al., 2006), and contributes to the limited literature on
partner aggression and husband physical health. It is unclear whether the lower
levels of physical aggression characteristic of aggression in this sample led to the

94
non‐significant findings between physical aggression victimization and physical
health for women, a relationship which has been identified in a number of previous
studies, or if there was not sufficient power for these models to detect relationships.
Husband Aggression versus Wife Aggression and Outcome Relationships
Increased awareness of the bidirectionality of aggression for many couples in
community samples has led to discussions about the relative impacts of male versus
female aggression. This study adds to the burgeoning data about differential effects
and meaning for males’ use of aggression in intimate relationships versus females’
aggression (for discussion see Holtzworth‐Munroe, 2005a). Despite the high rates
of correspondence in aggression for this sample, important differences in the impact
of male versus female aggression were present. Only one significant relationship
was present between wife aggression perpetration and husband outcome measures
or wife physical health, specifically the associations between physical and emotional
wife aggression and husband preventive care behaviors.
The identified relationships between husband aggression and the wife
composite physical health construct, as well as a number of the individual health
indices, supports a growing literature examining physical health‐related impacts of
male partner aggression. The composite scales provide a broader examination of
health than has been employed in many studies, but falls in line with conclusions
reported in a range of samples representing a range of aggressive relationships. The
findings from this study correspond with several research studies highlighting the
presence of partner aggression effects on health even for “low‐severity” violence

95
(McCauley et al., 1998, Wijma et al., 2007). Given the decreased likelihood of “low‐
severity” violence impacting physical health due to IPV‐related physical injuries,
these studies underscore the presence of other mechanisms of impact, such as
indirect affective, behavioral, immunologic, and/or psychophysiological pathways
mediating these variables. Such mechanisms have been proposed in a number of
theoretical papers (e.g., Resnick, Acierno, & Kilpatrick, 1997).
In this study, we examined depression as one potential explanatory variable
for impacts of aggression on health. Depression was selected as a commonly
identified mental health sequela of relationship aggression that might be
particularly relevant for couples with intermittent and/or lower severity aggression
in predominately intact relationships. However, hypothesized indirect effects from
aggression victimization to physical health through depressive symptoms were not
found for women in this sample. Despite relationships between aggression
victimization and perpetration with wives’ depression, a significant relationship
between depression and the physical health composite was not identified for wives
in this study, thus limiting the possibility for depression to act as a mediating
explanatory variable. Relationships between depression and wife physical health
variables have been found in a number of studies (Clum et al., 2000; Laffaye et al.,
2003; Sutherland et al., 2002). Studies also have suggested that health behaviors
and depression may be more strongly linked concurrently rather than across time
(Simonsick, 1991). Similarly, it is possible that behaviors are more strongly linked
to concurrent aggression as well, which was not examined in this study due to the

96
focus on establishing temporal order between model variables and capitalizing on
the longitudinal data. It also is possible that given higher statistical power,
significant but small effects could have been identified. Or, it may be that different
relationships between aggression, depression, and physical health exist, such as
depression acting as a moderating variable. Finally, a more holistic examination of
mental health status (e.g., anxiety, etc.) could provide a better empirical test of
mental health status as a mechanism of impact on physical health for women.
Interestingly, husband depression did serve as a mediating variable for the
indirect effect between husband physical aggression perpetration and the husband
physical health composite. There are limited data on physical health impacts of
aggression perpetration for men. Husband physical aggression perpetration and
perpetration together with victimization have been linked with negative health
behaviors and increased risks for depression, and these impacts may be most
detrimental for men who are both perpetrators and victims (Rhodes et al., 2009). A
small number of other studies have focused on aggression victimization for men
with mixed findings regarding physical health impacts; however, it is unclear how
assessing experiences with partner aggression perpetration would have affected the
conclusions of these studies (e.g., Carbone‐Lopez et al, 2006; Reid et al., 2008). For
76% of the physically aggressive husbands in the current study, their wives were
also physically aggressive at some time during the three‐year period of aggression
assessment. Thus, a substantial proportion of husbands were both perpetrators and
victims of aggression.

97
As suggested by this model, affective or cognitive reactions to perpetrating
physical aggression, such as shame, sadness, or anger, could lead to depressive
symptoms, and in turn impair physical health for men. However, it would be
premature to assume relationships identified in this study are causal. There are a
number of possible explanations for the findings linking husband perpetration to
impaired husband physical health. Earlier levels of depression were not examined
in these models. It is possible that different relationships exist between the primary
variables, for example, earlier levels of depression could increase the likelihood that
a husband is aggressive, relate to future levels of depression, and be associated with
more negative health behaviors or changes in hormone or immune functioning,
which could then have an impact on physical health. Earlier studies have
established temporal order between aggression victimization and increases in
depression for women (e.g., Ehrensaft, Moffit, & Caspi, 2006; Quigley & Leonard,
1996), but this has not been examined for men or focused on for perpetration. A
meta‐analytic review identified depression as a risk factor for perpetrating
aggression for both men and women, but it was not clear that the directionality of
this effect was empirically examined in the reviewed studies either (Stith, Smith,
Penn, Ward, & Tritt, 2004). More research is needed examining these complex
relationships particularly taking into account perpetration and victimization
experiences. One variable with potential utility in this respect is hostility, which has
been linked to aggression perpetration (Stith et al., 2004), has shown interaction
effects with depression (Stewart, Janicki‐Deverts, Muldoon, & Kamarck, 2008), and

98
has been linked to impaired physical health (Miller, Smith, Turner, Guijarro, &
Hallet, 1996).
Differences in findings for husbands and wives raise questions of whether
there are different pathways between aggression and health for perpetration versus
victimization, different pathways for men and women, and/or possibly differential
strengths in pathways for bidirectionally versus unidirectionally aggressive couples.
This study did not examine group differences for bidirectionally aggressive versus
unidirectionally aggressive relationships. This line of research has yielded
interesting information about differential impacts of partner aggression in previous
investigations (e.g., Temple et al., 2005). For 63% of couples in the current study
both spouses used emotional or physical aggression over a three year time frame,
for 9% of couples only the husband was aggressive, for 12% only the wife was
aggressive, and for 16% neither spouse reported physical or emotional aggression.
For bidirectionally aggressive couples, whether one partner was the “primary”
perpetrator was not determined. It is possible that aggression has different
meanings for both the perpetrator and victim depending on whether one or both
spouses are aggressive and whether bidirectionally aggressive tactics are similar or
disproportionate, which in turn could change the shorter and longer‐term impacts
of aggressive behavior. However, many studies do not examine partner aggression
victimization and perpetration. Although there is much agreement in the literature
that husband aggression is likely to have more severe impacts on women, there is
some controversy on this topic. Dutton and Nicholls (2005) discussed confirmatory

99
biases in research that may be propagating this idea and limiting advances in
understanding relationship aggression. Holtzworth‐Munroe (2005b) stressed the
necessity for researchers to consider the ethical implications of their work, given
the misuses of data on female‐to‐male aggression (e.g., to fight funding for domestic
violence shelters), while also continuing with research to increase our limited
knowledge of female partner aggression (Holtzworth‐Munroe, 2005a). In the
current study, which examined perpetration and victimization for both partners,
male‐to‐female aggression appeared to have more serious impacts. By not
examining actions of both spouses, important implications for improving
interventions may be missed. For example, bidirectionally aggressive couples may
be at increased risk for injury, as has been suggested by several recent studies, due
to increased risk for escalations in physical interactions when both partners engage
(e.g., Whitaker et al., 2007). More research is needed to understand impacts of
aggression by males and females.
Additional Future Research and Implications for Interventions
Although depression proved to be an important mediating variable for
husbands in several of the physical aggression models, a broader conceptualization
of mental health in future studies may shed additional light on mechanisms linking
partner aggression and physical health, particularly for women. A number of
investigations have examined PTSD symptoms as a moderating or mediating
variable between partner aggression victimization and physical health for women
(e.g., Inslicht et al., 2006; Pico‐Alfonso, Garcia‐Linares, Celda‐Navarro, Herbert, &

100
Martinez, 2004; Woods et al, 2005). Given the lower‐level and likely non‐acute
aggression and ongoing nature of relationships in the present study, PTSD
symptoms were not hypothesized to be the most relevant mental health sequelae.
However, examination of PTSD‐like symptoms, and other sequelae of intimate
partner violence with empirical connections to physical health (e.g., anxiety; Strine,
Chapman, Kobau, & Balluz, 2005) could improve our understanding of mechanisms
through which partner aggression impacts physical health. It is also possible that
different mental health variables play a role in mediating or moderating
relationships with physical health and aggression perpetration versus aggression
victimization. Relatedly, examining protective factors such as social support or
positive health behaviors, which also could moderate some of the key relationships
in these models, would provide helpful information for guiding treatment
recommendations and intervention efforts.
Overall, relationships examined in this study, including demographic
variables, explained 40% of the variance in the health composite variable for wives
and 35% for husbands. Increased attention to aggression and related daily stress
factors may be an important consideration for medical providers counseling
patients about their physical healthcare and health behaviors. Individually tailored
analysis of factors impeding and promoting positive health, including intimate
partner aggression, could improve attempts at behavioral health change. Although
the United States Preventive Services Task Force (2004) has not recommended
universal screenings, a number of other organizations, including the American

101
Medical Association (2005), have advised that questions about family violence
should be included during routine history taking, chronic care management, and in
emergency settings. Healthcare providers’ increased awareness of the associations
between intimate partner violence and physical health could improve diagnostic
decision‐making and care delivery. The medical setting also provides an important
opportunity to offer resources and intervention (Plichta, 2007). Finally, in line with
the importance of examining relevant systems variables in health intervention
delivery, the significant association between husbands’ and wives’ health behaviors
in this study suggests that a systems approach could present ways to increase
success in behavior change efforts for individuals with a positive relationship with
their spouse as well.
Limitations and Strengths of the Present Study
There are a number of limitations that should be considered when
interpreting these results. This study focused on couples in relatively intact
relationships with a 9‐10 year old child at wave 1 of the study. Although this sample
provided information about the most common types of relationship aggression,
these results may not generalize to couples without children, couples with children
at different developmental stages, or individuals not in committed relationships.
Relatedly, this was a non‐random volunteer sample intended by design to examine
important relationships between variables, but not to provide prevalence estimates.
Second, although a number of significant relationships were identified among
variables, it is likely that this study was underpowered to identify smaller effect

102
sizes, particularly given the number of variables examined. It is possible that power
issues caused important relationships not to be identified in the results (i.e., type II
error false negatives). Third, although we established temporal order between
aggression, reports of depressive symptoms, and physical health, earlier levels of
health and depression were not examined. Further research is needed to rule out
the possibility of reciprocal or reversed relationships among the variables over time.
Third variables not included in the analytic models (e.g., other forms of
interpersonal victimization, marital dissatisfaction, hostility, etc.) also could further
explain or account for relationships identified in this study. Due to these factors,
none of the relationships or effects identified in this study can be assumed to be
causal. A fourth limitation is that, given the longitudinal approach, about 25% of
couples were lost to follow‐up for reporting on health outcomes. If couples who did
not return displayed different relationships between aggression and health, results
could be impacted. Although attrition is a problem for nearly all longitudinal
studies, we were not able to examine differences in physical health for returners
versus non‐returners because data were not collected on physical health in earlier
waves. We did use full information maximum likelihood estimation to allow
inclusion of all couples in the SEM analyses. Additionally, we employed avenues for
correcting estimates due to attrition using Heckman Correction procedures. Finally,
despite the nuanced examination of multiple health constructs in this study, health
scales were based on retrospective, self‐report data. Chart review for health
conditions, direct measurements for height and weight, and daily diary methods for

103
frequent and fluctuating health behaviors (i.e., diet, sleep, exercise) and subclinical
symptoms could have improved these measurements of physical health.
Despite these limitations, this study builds on the current literature in a
number of important ways. First, few longitudinal studies have been conducted
examining partner aggression and physical health. This study improves on previous
research by establishing temporal order between predictor and outcome variables,
including establishing temporal order between partner aggression and the onset of
health conditions. Cross‐sectional studies cannot determine if aggression or mental
health problems precede or follow impaired health or negative health behaviors.
Second, few studies have examined partner aggression perpetration and
victimization in relation to physical health, and none to our awareness have done so
in a multivariate context with mental health, despite theoretical models suggesting
links between these variables. The multivariate nature of this study proved
particularly important for our understanding of impacts of aggression perpetration
on husbands’ health. Third, few investigations have examined health for husbands
and wives within in the same couples. This approach may provide a more direct
route of comparison for impacts than comparing across studies with different
methodologies that have focused on only one gender’s experiences, particularly
because many of these studies have examined only victimization rather than
perpetration and victimization. Through this approach, different paths were
identified as important predictors of physical health for husbands versus wives.
Additionally, this study undertook a broad and in‐depth examination of reported

104
health, providing a different approach from other studies that have examined a
general health construct using a single global subjective rating of health (e.g., “poor”
to “good”), or have focused on only very specific aspects of health. Finally, this study
contributes to the limited data on impacts of lower severity violence and to the
literature on intimate partner violence and preventive care and health behaviors.
Conclusions
There has been an increase in research on and understanding of links
between spouse aggression and physical health. However, few studies examining
mechanisms for impacts on physical health have been conducted. The current study
contributes to the literature on multivariate relationships between spouse
aggression, mental, and physical health. As noted, there are many important
avenues for continued research in this area. The current study suggests that,
despite the bidirectionality of aggression in many of the participant couples,
husband aggression appeared to have a number of negative associations with both
spouses’ physical health, which was predominately not the case for aggression
perpetrated by wives. Additionally, husband emotional aggression appeared to be
particularly important in driving links between husband aggression and wife
physical health. Finally, husband depression was identified as a potential mediating
variable between husband aggression perpetration, and husband physical health in
several analyses. More research is needed to understand these relationships more
fully. Many of the couples in this study are married or have been living together for
a number of years and are raising children together. Even in this sample, which is

105
older on average than many samples examining partner aggression and likely has
experienced milder forms of partner violence (i.e., “common couple violence” rather
than “intimate terrorism”), important associations between aggression and
impaired physical health were found.   Given the proportion of couples exposed to at
least lower levels of relationship aggression, these findings and continued research
in this area have important implications for care delivery in medical settings and for
improving intervention efforts directed at health behaviors and at partner
ggression. a

106
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123

Appendix A. Domestic Conflict Index (Wave 1)

Domestic Conflict Index
Margolin, G., Burman, B., John, R. S., & O’ Brien, M. (1990)
University of Southern California

No matter how well a couple gets along, there are times when they disagree on major decisions, get annoyed about something the other person
does, or just have spats or fights because they’re in a bad mood, or tired, or for some other reason. People have many different ways of
expressing frustration, annoyance, or hostility with one another. Attached you will find a list of some things that you and your partner may have
done. You will find that some of these items apply, while others do not. Please be sure to consider all items, even if they seem extreme.

First, decide if this behavior has ever occurred (Section A). If the behavior has never occurred in the history of your relationship, circle “No”
under “Ever” and go on to the next question.

If the behavior has occured, indicate whether or not it happened in front of your child (Section B). Next, indicate how frequently this behavior
occurred within the last year (regardless of child’s presence) (Section C).

Section
A
Section
B
Section
C

From one year ago until today…
Have you: Ever?

In front of your
child?
0 per
year
1 per
year
2-5 per
year
6-12
per year
2-4 per
month
>1 per
week
1. screamed or yelled at your spouse No Yes No Maybe Yes
2. insulted or swore at your spouse No Yes No Maybe Yes
3. damaged a household item, or some part of your home,
out of anger towards your spouse
No Yes No Maybe Yes
4. withheld affection from your spouse No Yes No Maybe Yes
5. deliberately disposed of or hid an important item of your
spouse’s
No Yes No Maybe Yes
6. sulked or refused to talk about an issue No Yes No Maybe Yes
7. monitored your spouse’s time and made him or her
account for where he/she was
No Yes No Maybe Yes
8. made plans that left your spouse feeling excluded No Yes No Maybe Yes

124
Section
A
Section
B
Section
C

From one year ago until today…
Have you: Ever?

In front of your
child?
0 per
year
1 per
year
2-5 per
year
6-12
per year
2-4 per
month
>1 per
week
9. left your spouse and were unsure whether you were
going to return
No Yes No Maybe Yes
10. been angry if your spouse told you that you were using
too much alcohol or drugs
No Yes No Maybe Yes
11. been very upset if dinner, housework, or home repair
work was not done when you thought it should be
No Yes No Maybe Yes
12. done or said something to spite your spouse No Yes No Maybe Yes
13. been jealous and suspicious of your spouse’s friends No Yes No Maybe Yes
14. purposely hurt your spouse’s pet No Yes No Maybe Yes
15. purposely damaged or destroyed your spouse’s clothes,
car, and/or other personal possessions
No Yes No Maybe Yes
16. insulted or shamed your spouse in front of others No Yes No Maybe Yes
17. locked your spouse out of the house No Yes No Maybe Yes
18. told your spouse that he/she could not work, go to
school, or go to other self-improvement activities
No Yes No Maybe Yes
19. tried to prevent your spouse from seeing/talking to
family
or friends
No Yes No Maybe Yes
20. had an extramarital affair No Yes No Maybe Yes
21. restricted your spouse’s use of the car or telephone No Yes No Maybe Yes
22. made threats to leave the relationship No Yes No Maybe Yes
23. blamed your spouse for your problems No Yes No Maybe Yes
24. tried to turn family, friends, or children against your
spouse
No Yes No Maybe Yes
25. ordered your spouse around No Yes No Maybe Yes
26. been insensitive to your spouse’s feelings No Yes No Maybe Yes
27. frightened your spouse No Yes No Maybe Yes
28. treated your spouse like he/she was stupid No Yes No Maybe Yes
29. given your spouse the silent treatment/cold shoulder No Yes No Maybe Yes
30. criticized your spouse No Yes No Maybe Yes
31. called your spouse names No Yes No Maybe Yes

125
Section
A
Section
B
Section
C

From one year ago until today…
Have you: Ever?

In front of your
child?
0 per
year
1 per
year
2-5 per
year
6-12
per year
2-4 per
month
>1 per
week
32. stomped out of the room, house, or yard No Yes No Maybe Yes
33. stayed away from the house No Yes No Maybe Yes
34. ridiculed your spouse No Yes No Maybe Yes
35. physically twisted your spouse’s arm No Yes No Maybe Yes
36. threatened to hit your spouse or throw something at
him/her in anger
No Yes No Maybe Yes
37. pushed, grabbed, or shoved your spouse No Yes No Maybe Yes
38. slapped your spouse No Yes No Maybe Yes
39. physically forced sex on your spouse No Yes No Maybe Yes
40. burned your spouse No Yes No Maybe Yes
41. shaken your spouse No Yes No Maybe Yes
42. thrown, smashed, hit, or kicked something No Yes No Maybe Yes
43. prevented your spouse from getting medical care that
he/she needed
No Yes No Maybe Yes
44. thrown or tried to throw your spouse bodily No Yes No Maybe Yes
45. thrown an object at your spouse No Yes No Maybe Yes
46. choked or strangled your spouse No Yes No Maybe Yes
47. kicked, bit or hit your spouse with a fist No Yes No Maybe Yes
48. hit your spouse, or tried to hit your spouse, with
something
No Yes No Maybe Yes
49. beat up your spouse (multiple blows) No Yes No Maybe Yes
50. threatened your spouse with a knife or gun No Yes No Maybe Yes
51. used a knife or a gun on your spouse No Yes No Maybe Yes
52. used humiliation to make your spouse have sex No Yes No Maybe Yes
53. used threats to make your spouse have sex No Yes No Maybe Yes
54. coerced your spouse to engage in sexual practices
he/she did not want
No Yes No Maybe Yes
55. slammed your spouse against the wall No Yes No Maybe Yes
56. physically prevented your spouse from leaving an
argument or blocked his/her exit
No Yes No Maybe Yes
57. showed your spouse that you cared even though the No Yes No Maybe Yes

126
Section
A
Section
B
Section
C

From one year ago until today…
Have you: Ever?

In front of your
child?
0 per
year
1 per
year
2-5 per
year
6-12
per year
2-4 per
month
>1 per
week
two
of you disagreed
58. showed respect for your partner’s feelings about an
issue
No Yes No Maybe Yes
59. suggested a compromise to a disagreement No Yes No Maybe Yes
60. agreed to a solution your partner suggested No Yes No Maybe Yes
61. took responsibility for your part in a problem No Yes No Maybe Yes

In this section, you will answer the same types of questions about your spouse. Again, you will find that some of these items
apply, while others do not. Please be sure to consider all items, even if they seem extreme.
Section
A
Section
B
Section
C

From one year ago until today…
Has your spouse: Ever?

In front of your
child?
0 per
year
1 per
year
2-5 per
year
6-12 per
year
2-4 per
month
>1 per
week
1. screamed or yelled at you No Yes No Maybe Yes
2. insulted or swore at you No Yes No Maybe Yes
3. damaged a household item, or some part of your home,
out of anger towards you
No Yes No Maybe Yes
4. withheld affection from you No Yes No Maybe Yes
5. deliberately disposed of or hid an important item of yours No Yes No Maybe Yes
6. sulked or refused to talk about an issue No Yes No Maybe Yes
7. monitored your time and made you account for where
you were
No Yes No Maybe Yes
8. made plans that left you feeling excluded No Yes No Maybe Yes
9. left you and (you) were unsure whether he/she was going
to return
No Yes No Maybe Yes
10. been angry when you told him/her that he/she was using
too much alcohol or drugs
No Yes No Maybe Yes

127
Section
A
Section
B
Section
C

From one year ago until today…
Has your spouse: Ever?

In front of your
child?
0 per
year
1 per
year
2-5 per
year
6-12 per
year
2-4 per
month
>1 per
week
11. been very upset if dinner, housework, or home repair
work was not done when he/she thought it should be
No Yes No Maybe Yes
12. done or said something to you No Yes No Maybe Yes
13. been jealous and suspicious of your friends No Yes No Maybe Yes
14. purposely hurt your pet No Yes No Maybe Yes
15. purposely damaged or destroyed your clothes, car,
and/or other personal possessions
No Yes No Maybe Yes
16. insulted or shamed you in front of others No Yes No Maybe Yes
17. locked you out of the house No Yes No Maybe Yes
18. told you that you could not work, go to school, or go to
other self-improvement activities
No Yes No Maybe Yes
19. tried to prevent you from seeing/talking to family or
friends
No Yes No Maybe Yes
20. had an extramarital affair No Yes No Maybe Yes
21. restricted your use of the car or telephone No Yes No Maybe Yes
22. made threats to leave the relationship No Yes No Maybe Yes
23. blamed you for his/her problems No Yes No Maybe Yes
24. tried to turn family, friends, or children against you No Yes No Maybe Yes
25. ordered you around No Yes No Maybe Yes
26. been insensitive to your feelings No Yes No Maybe Yes
27. frightened you No Yes No Maybe Yes
28. treated you like you were stupid No Yes No Maybe Yes
29. given you the silent treatment/cold shoulder No Yes No Maybe Yes
30. criticized you No Yes No Maybe Yes
31. called you names No Yes No Maybe Yes
32. stomped out of the room, house, or yard No Yes No Maybe Yes
33. stayed away from the house No Yes No Maybe Yes
34. ridiculed you No Yes No Maybe Yes
35. physically twisted your arm No Yes No Maybe Yes
36. threatened to hit you, or throw something at you, in anger No Yes No Maybe Yes
37. pushed, grabbed, or shoved you No Yes No Maybe Yes

128
Section
A
Section
B
Section
C

From one year ago until today…
Has your spouse: Ever?

In front of your
child?
0 per
year
1 per
year
2-5 per
year
6-12 per
year
2-4 per
month
>1 per
week
38. slapped you No Yes No Maybe Yes
39. physically forced sex on you No Yes No Maybe Yes
40. burned you No Yes No Maybe Yes
41. shaken you No Yes No Maybe Yes
42. thrown, smashed, hit, or kicked something No Yes No Maybe Yes
43. prevented you from getting medical care that you needed No Yes No Maybe Yes
44. thrown, or tried to throw you, bodily No Yes No Maybe Yes
45. thrown an object at you No Yes No Maybe Yes
46. choked or strangled you No Yes No Maybe Yes
47. kicked, bit or hit you with a fist No Yes No Maybe Yes
48. hit you, or tried to hit you, with something No Yes No Maybe Yes
49. beat you up (multiple blows) No Yes No Maybe Yes
50. threatened you with a knife or gun No Yes No Maybe Yes
51. used a knife or a gun on you No Yes No Maybe Yes
52. used humiliation to make you have sex No Yes No Maybe Yes
53. used threats to make you have sex No Yes No Maybe Yes
54. coerced you to engage in sexual practices you did not
want
No Yes No Maybe Yes
55. slammed you against the wall No Yes No Maybe Yes
56. physically prevented you from leaving an argument or
blocked your exit
No Yes No Maybe Yes
57. showed you that he/she cared even though the two
of you disagreed
No Yes No Maybe Yes
58. showed respect for your feelings about an issue No Yes No Maybe Yes
59. suggested a compromise to a disagreement No Yes No Maybe Yes
60. agreed to a solution you suggested No Yes No Maybe Yes
61. took responsibility for his/her part in a problem No Yes No Maybe Yes

129
Appendix B. Symptom Checklist 90 Revised (Wave 3)
SCL-90-R

DIRECTIONS: Below is a list of problems that people sometimes have. Please mark the response that best describes how much
discomfort that problem has caused you during the past week, including today. Please do not skip any items.

Not at all A little bit Moderately Quite a bit Extremely
1. Headaches
2. Nervousness or shakiness inside
3. Repeated unpleasant thoughts that won't leave your mind
4. Faintness or dizziness
5. Loss of sexual interest or pleasure
6. Feeling critical of others
7. The idea that someone can control your thoughts
8. Feeling others are to blame for most of your troubles
9. Trouble remembering things
10. Worried about sloppiness or carelessness
11. Feeling easily annoyed or irritated
12. Pains in the heart or chest
13. Feeling afraid of open spaces or on the streets
14. Feeling low in energy or slowed down
15. Thoughts of ending your life
16. Hearing voices that other people do not hear
17. Trembling
18. Feeling that most people cannot be trusted

130

Not at all A little bit Moderately Quite a bit Extremely

19. Poor appetite
20. Crying easily
21. Feeling shy or uneasy with the opposite sex
22. Feeling of being trapped or caught
23. Suddenly scared for no reason
24. Temper outbursts that you could not control
25. Feeling afraid to go out of your house alone
26. Blaming yourself for things
27. Pains in lower back
28. Feeling blocked in getting things done
29. Feeling lonely
30. Feeling blue
31. Worrying too much about things
32. Feeling no interest in things
33. Feeling fearful
34. Your feelings being easily hurt
35. Other people being aware of your private thoughts
36. Feeling others do not understand you or are unsympathetic
37. Feeling that people are unfriendly or dislike you
38. Having to do things very slowly to ensure correctness
39. Heart pounding or racing
40. Nausea or upset stomach
41. Feeling inferior to others
42. Soreness of your muscles

131

Not at all A little bit Moderately Quite a bit Extremely

43. Feeling that you are being watched or talked about by others
44. Trouble falling asleep
45. Having to check and double-check what you do
46. Difficulty making decisions
47. Feeling afraid to travel on buses, subways, or trains
48. Trouble getting your breath
49. Hot or cold spells
50. Having to avoid certain things, places, or activities because
they frighten you

51. Your mind going blank
52. Numbness or tingling in parts of your body
53. A lump in your throat
54. Feeling hopeless about the future
55. Trouble concentrating
56. Feeling weak in parts of your body
57. Feeling tense or keyed-up
58. Heavy feeling in your arms or legs
59. Thoughts of death or dying
60. Overeating
61. Feeling uneasy when people are watching or talking about you
62. Having thoughts that are not your own
63. Having urges to beat, injure, or harm someone
64. Awakening in the early morning
65. Having to repeat the same actions such as touching,
counting or washing

132

Not at all A little bit Moderately Quite a bit Extremely

66. Sleep that is restless or disturbed
67. Having urges to break or smash things
68. Having ideas or beliefs that others do not share
69. Feeling very self-conscious with others
70. Feeling uneasy in crowds, such as shopping or at a movie
71. Feeling everything is an effort
72. Spells of terror or panic
73. Feeling uncomfortable about eating or drinking in public
74. Getting into frequent arguments
75. Feeling nervous when you are left alone
76. Others not giving you proper credit for your achievements
77. Feeling lonely even when you are with people
78. Feeling so restless you couldn’t sit still
79. Feelings of worthlessness
80. The feeling that something bad is going to happen to your
body

81. Shouting or throwing things
82. Feeling afraid that you will faint in public
83. Feeling that people will take advantage of you if you let
them

84. Having thoughts about sex that bother you a lot
85. The idea that you should be punished for your sins
86. Thoughts and images of a frightening nature
87. The idea that something serious is wrong with your body
88. Never feeling close to another person

133

Not at all A little bit Moderately Quite a bit Extremely
89. Feelings of guilt
90. The idea that something is wrong with your mind

134
Appendix C. World Health Organization Quality of Life – Brief (Wave 4)
WHOQOL-BREF

This assessment asks how you feel about your quality of life, health, or other areas of your life.
Please answer all the questions. If you are unsure about which response to give to a question,
please choose the one that appears most appropriate. This can often be your first response.

Please keep in mind your standards, hopes, pleasures and concerns. We ask that you think about
your life in the last two weeks. For example, thinking about the last two weeks, a question might
ask:

Do you get the kind of support
from others that you need?
Not at all

1
Not much

2
Moderately

3
A great deal

4
Completely

5

You should circle the number that best fits how much support you got from others over the last
two weeks. So you would circle the number 4 if you got a great deal of support from others. You
would circle number 1 if you did not get any of the support that you needed from others in the last
two weeks.

Please read each question, assess your feelings, and circle the number on the scale
for each question that gives the best answer for you.

Very Poor Poor Neither poor
nor good
Good Very good
How would you rate your quality
of life?
1.
1 2 3 4

5

Very
dissatisfied
Dissatisfied Neither
satisfied nor
dissatisfied
Satisfied Very
satisfied
2.
How satisfied are you with your
health?

1

2

3

4

5

The following questions ask about how much you have experienced certain things in the last two weeks.

Not at all A little A moderate
amount
Very
much
An extreme
amount
To what extent do you feel that
physical pain prevents you from
doing what you need to do?

1

2

3
3.
4

5
4.
How much do you need any
medical treatment to function in
your daily life?

1

2

3

4

5
5.
How much do you enjoy life?

1

2

3

4

5
6.
To what extent do you feel your
life to be meaningful?

1

2

3

4

5

135

Not at all A little A moderate
amount
Very
much
Extremely
7.
How well are you able to
concentrate?

1

2

3

4

5
8.
How safe do you feel in your daily
life?

1

2

3

4

5
9.
How healthy is your physical
environment?

1

2

3

4

5

The following questions ask about how completely you experience or were able to do certain things in the
last two weeks.

Not at all A little Moderately Mostly Completely
10.
Do you have enough energy for
everyday life?

1

2

3

4

5
11.
Are you able to accept your bodily
appearance?

1

2

3

4

5
12.
Have you enough money to meet
your needs?

1

2

3

4

5
13.
How available to you is the
information that you need in your
day-to-day life?

1

2

3

4

5
14.
To what extent do you have the
opportunity for leisure activities?

1

2

3

4

5

Very Poor Poor Neither poor
nor good
Good Very good
15.
How well are you able to get
around?

1

2

3

4

5

The following questions ask you to say how good or satisfied you have felt about various aspects of your
life over the last two weeks.

Very
dissatisfied
Dissatisfied Neither
satisfied nor
dissatisfied
Satisfied Very
satisfied
16.
How satisfied are you with your
sleep?

1

2

3

4

5
17.
How satisfied are you with your
ability to perform your daily living
activities?

1

2

3

4

5
18.
How satisfied are you with your
capacity for work?

1

2

3

4

5
19.
How satisfied are you with
yourself?

1

2

3

4

5
20.
How satisfied are you with your
personal relationships?

1

2

3

4

5
21.
How satisfied are you with your
sex life?

1

2

3

4

5
22.
How satisfied are you with the

136
support you get from your friends?
1 2 3 4 5
23.
How satisfied are you with the
conditions of your living place?

1

2

3

4

5
24.
How satisfied are you with your
access to health services?

1

2

3

4

5
25.
How satisfied are you with your
transport?

1

2

3

4

5
The following question refers to how often you have felt or experienced certain things in the last two
weeks.

Never Seldom Quite often Very Often Always
26.
How often do you have negative
feelings such as blue mood,
despair, anxiety, depression?

1

2

3

4

5

137
Appendix D. Health Questionnaire (Wave 4)
Health Questions by topic area 12.1.04

(1) Health status and chronic illnesses (e.g., cancer, hypertension)

(2) Sub-clinical health symptoms (e.g., pain, headaches, fatigue)

(3) Preventive care (e.g., annual physical and dental checkups, inoculations, men’s
and women’s health)

(4) Health risk behaviors (e.g., smoking, drinking, driving inattentively)

(5) Health promoting behaviors (e.g., nutrition, sleep, exercise)

Questions taken from: (after each question, question origin indicated using the following numbers)
[1] National Health Interview Survey (NCHS, 2004)
[2] National Health and Nutrition Examination Survey (NCHS, 2001)
[3] Youth Risk Behavior Survey (CDC, 2005)
[4] Behavioral Risk Factor Surveillance System (CDC, 2004)
[5] California Health Interview Survey (CDHS, 2001)
[5a] California Health Interview Survey (CDHS, 2003)
[6] Medical Expenditure Panel Survey (AHRQ, 2002)
[7] RAND 36-Item Health Survey (Hays, Sherbourne, & Mazel, 1993)
[8] New-Buss Questionnaire (Gidron, Davidson, & Ilia, 2001)
(consists of 8 items from Buss-Perry Aggression Questionnaire (Buss & Perry, 1992))
[9] Questions created for this study

****************************************************

(0) General

1. Please list all medications you are currently taking (including name, when started
taking medication, how frequently medication is taken, and what specific health problem
each medication is prescribed/used for.) Please record information directly from the
medicine’s label or instructions. Please list ALL medications; include use of antacids,
aspirin, cold and sinus products, etc.
[9]
Prescription/Medication
When started
taking
medication
(Month/Year)
How often taken?
(e.g., 1x/day, as
needed, etc.)
Prescribed/
Used for:
1.

2.

3.

138
4.

5.

6.

2. Now thinking about your physical health, which includes physical illness and injury,
for how many days during the PAST 30 DAYS was your physical health not good?
[2&4]

Enter number of days: __ __ days

3. Now thinking about your mental health, which includes stress, depression, and
problems with emotions, for how many days during the PAST 30 DAYS was your
mental health not good?
[2&4]

Enter number of days: __ __ days

4. During the PAST 30 DAYS, for about how many days did poor physical or mental
health keep you from doing your usual activities, such as self-care, work , or
recreation?
[2&4]

Enter number of days: __ __ days

5. During the PAST 3 MONTHS, for about how many days did you have a head or chest
cold?
[2-adapted]

Enter number of days: __ __ days

6. During the PAST 3 MONTHS, for about how many days did you have a stomach or
intestinal illness with vomiting or diarrhea?
[2-adapted]

Enter number of days: __ __ days

7. During the PAST 3 MONTHS, for about how many days did you have flu,
pneumonia, or ear infections?
[2-adapted]

Enter number of days: __ __ days

139

(1) Health status and chronic illnesses (e.g., cancer, hypertension)

8. Have you EVER been told by a doctor or other health professional that you had…
(please check and give details about all that apply)
[1]

When did you first learn of this
health problem?

Experienced
this health
problem in
the last
year?
Within
last 12
months
>1
yr-2
yrs
ago
>2 yrs
-5 yrs
ago
>5
yrs-10
yrs
ago
>1
0
yrs
ago
□ Angina (Angina Pectoris) Yes No
□ Coronary Heart Disease Yes No
□ Heart Attack (Myocardial
infarction)
Yes No

□ High cholesterol Yes No
□ Hypertension (high blood
pressure)
Yes No

□ Any other heart condition or
heart disease
Yes No

□ Arthritis /Rheumaticism Yes No
□ Asthma Yes No
□ Cancer or malignancy of any
kind
Kind of
Cancer:________________
Yes No

□ Circulation problem (including
blood clots)
Yes No

□ Chronic Bronchitis Yes No
□ Diabetes or sugar diabetes
(excluding during pregnancy)
Yes No

□ Emphysema Yes No
□ Epilepsy/Seizures Yes No
□ Hay fever / Allergies Yes No
□ Liver condition (any kind) Yes No
□ Sinusitis Yes No
□ Stroke Yes No
□ Thyroid problems
(hypothyroidism,
hyperthyroidism/Graves’
Disease)
Yes No

□ Ulcer (stomach, duodenal, or
peptic)
Yes No

□ Weak or failing kidneys (not Yes No

140
When did you first learn of this
health problem?

Experienced
this health
problem in
the last
year?
Within
last 12
months
>1
yr-2
yrs
ago
>2 yrs
-5 yrs
ago
>5
yrs-10
yrs
ago
>1
0
yrs
ago
including kidney stones, bladder
infection, or incontinence)
□ Weight problem: Yes No
□ Other health condition:
__________________________
___
Yes No

□ Other health condition:
__________________________
___
Yes No

9. Have you EVER had difficulty with any of the following conditions or health
problems…(please check and give details about all that apply)
[1]

When did you first learn of this
health problem?
Experienced
this problem
in the last
year?
Within
last 12
months
>1
yr-2
yrs
ago
>2 yrs
-5 yrs
ago
>5
yrs-10
yrs
ago
>1
0
yrs
ago
□ Back or neck problem Yes No
□ Fracture, bone/joint injury Yes No
□ Hearing Problem Yes No
□ Other
injury:__________________
Yes No

□ Other impairment/problem:
__________________________
__
Yes No

141

(2) Sub-clinical health symptoms (e.g., pain, headaches, fatigue, colds)
Pain & Headaches:
10. The following questions are about pain you may have experienced in the PAST
THREE MONTHS. Please refer to pain that LASTED A WHOLE DAY OR MORE.
Do not report aches and pains that are fleeting or minor.
[1&2-adapted answer choices]

a. During the PAST THREE MONTHS, for about how many days did you have
neck pain?
Enter number of days: __ __ days
b. During the PAST THREE MONTHS, for about how many days did you have low
back pain?
Enter number of days: __ __ days
c. During the PAST THREE MONTHS, for about how many days did you have
facial ache or pain in the jaw muscles or the joint in front of the ear?
Enter number of days: __ __ days
d. During the PAST THREE MONTHS, for about how many days did you have a
severe headache?
Enter number of days: __ __ days
e. During the PAST THREE MONTHS, for about how many days did you have a
migraine?
Enter number of days: __ __ days
f. During the PAST THREE MONTHS, for about how many days did you have a
any other types of pain (arms, legs, feet, etc.)?
Enter number of days: __ __ days

11. How much bodily pain have you had during the PAST 30 DAYS?
[7, #21]
(Circle One Number)
None…………….…………1
Very mild….…..…………..2
Mild………………………..3
Moderate...…...……………4
Severe…..…….…………...5
Very severe……..…….…...6

Fatigue:

12. During the PAST 30 DAYS, for about how many days have you felt you did not get
enough rest or sleep?
[4]

142
Enter number of days: __ __ days
Question also listed under #5 sleep.

13. During the PAST 30 DAYS, for about how many days have you felt that you needed
to drink coffee or take some other stimulant in order to stay awake because of
fatigue?
[9]
Enter number of days: __ __ days

14. Do you have enough energy for everyday life?
[WHO-BREF]

1 2 3 4 5
not at all completely

(3) Preventive care (e.g., annual physical and dental checkups, inoculations, men’s
and women’s health)

Insurance:

15. Do you have any kind of health coverage, including health insurance, prepaid plans
such as HMOs, or government plans such as Medicare?
[4]
□ Yes □ No

16. Do you now have any type of insurance that pays for all or part of your dental care?

[5a]
□ Yes □ No

Health care usage/preventive checkups:

17. During the past 12 months, how many times did you either delay or not get a
medicine that a doctor prescribed for you?
[5a-adapted]

□ Never □ 1 □ 2-3 □ 4-5 □ 6-7 □ 8-9 □ 10+

18. During the past 12 months, how many times did you delay or not get any other
medical care you felt you needed – such as seeing a doctor, a specialist or other
health professional?
[5a-adapted]

□ Never □ 1 □ 2-3 □ 4-5 □ 6-7 □ 8-9 □ 10+

19. About how long has it been since you last saw a dentist? Include all types of
dentists, such as orthodontists, oral surgeons, and all other dental specialists, as well
as dental hygienists.
[1]
□ 6 months or less
□ More than 6 months, but not more than 1 year ago
□ More than 1 year, but not more than 2 years ago
□ More than 2 years, but not more than 5 years ago
□ More than 5 years ago
□ Never

143
20. During the PAST 12 MONTHS, have you seen or talked to a mental health
professional such as a psychiatrist, psychologist, psychiatric nurse, or clinical social
worker about your own health?
[1]
□ Yes □ No

21. During the PAST 5 YEARS, how many times have you gone to the hospital
emergency room about your own health? (This includes emergency room visits that
resulted in hospital admission.)
[1-adapted]
□ 0 □ 1 □ 2-3 □ 4-5 □ 6-7 □ 8-9 □ 10-12 □ 13-15 □ 16+
For what reason (s)?_____________

22. During the PAST 12 MONTHS, how many times have you seen a doctor or other
health care professional about your own health at a DOCTOR'S OFFICE, A CLINIC,
OR SOME OTHER PLACE? (Do not include times you were hospitalized overnight,
visits to hospital emergency rooms, dental visits, or telephone calls.)
[1]
□ 0 □ 1 □ 2-3 □ 4-5 □ 6-7 □ 8-9 □ 10-12 □ 13-15 □ 16+

23. About how long has it been since you last saw or talked to a doctor or other health
care professional about your own health? (Include doctors seen while a patient in a
hospital.)
[1]
□ Never
□ 6 months or less
□ More than 6 months, but not more than 1 year ago
□ More than 1 year, but not more than 2 years ago
□ More than 2 years, but not more than 5 years ago
□ More than 5 years ago

Immunizations:

Women’s & men’s health:

The next questions are for women only. [If male, skip to question #27.]

24. A mammogram is an x-ray of each breast to look for breast cancer. Have you ever
had a mammogram?
[4]
□ Yes* □ No
*If Yes, how long has it been since you had your last mammogram?
□ Within the past year (anytime less than 12 months ago)
□ Within the past 2 years (1 year but less than 2 years ago)
□ Within the past 3 years (2 years but less than 3 years ago)
□ Within the past 5 years (3 years but less than 5 years ago)
□ 5 or more years ago

25. A clinical breast exam is when a doctor, nurse, or other health professional feels the
breasts for lumps. Have you ever had a clinical breast exam?
[4]
□ Yes* □ No

144
*If Yes, how long has it been since your last breast exam?
□ Within the past year (anytime less than 12 months ago)
□ Within the past 2 years (1 year but less than 2 years ago)
□ Within the past 3 years (2 years but less than 3 years ago)
□ Within the past 5 years (3 years but less than 5 years ago)
□ 5 or more years ago

26. A Pap test is a test for cancer of the cervix. Have you ever had a Pap test?
[4]

□ Yes* □ No
*If Yes, how long has it been since your last Pap test?
□ Within the past year (anytime less than 12 months ago)
□ Within the past 2 years (1 year but less than 2 years ago)
□ Within the past 3 years (2 years but less than 3 years ago)
□ Within the past 5 years (3 years but less than 5 years ago)
□ 5 or more years ago

The next questions are for men only. [If female, skip to question #29.]

27. A Prostate-Specific Antigen test, also called a PSA test, is a blood test used to check
men for prostate cancer. Have you ever had a PSA test?
[4]
□ Yes* □ No
*If Yes, how long has it been since your last PSA test?
□ Within the past year (anytime less than 12 months ago)
□ Within the past 2 years (1 year but less than 2 years ago)
□ Within the past 3 years (2 years but less than 3 years ago)
□ Within the past 5 years (3 years but less than 5 years ago)
□ 5 or more years ago

28. A digital rectal exam is an exam in which a doctor, nurse, or other health
professional places a gloved finger into the rectum to feel the size, shape, and
hardness of the prostate gland. Have you ever had a digital rectal exam?
[4]

□ Yes* □ No
*If Yes, how long has it been since your last digital rectal?
□ Within the past year (anytime less than 12 months ago)
□ Within the past 2 years (1 year but less than 2 years ago)
□ Within the past 3 years (2 years but less than 3 years ago)
□ Within the past 5 years (3 years but less than 5 years ago)
□ 5 or more years ago

29. Blood cholesterol is a fatty substance found in the blood. Have you ever had your
blood cholesterol checked?
[4]
□ Yes □ No
a. About how long has it been since you last had your blood cholesterol
checked?
[4]
□ Within the past year (anytime less than 12 months ago)
□ Within the past 2 years (1 year but less than 2 years ago)

145
□ With in the past 5 years (2 years but less than 5 years ago)
□ 5 or more years ago

(4) Health risk behaviors (e.g., smoking, drinking, driving inattentively, weight,
Anger)

*Drinking and drug use assessed with Alcohol & Drug Questionnaire.

Tobacco Use:
The following questions are about cigarette smoking.

30. Have you smoked at least 100 cigarettes in your ENTIRE LIFE?
[1]
□ Yes □ No

31. Do you NOW smoke cigarettes every day, some days, or not at all?
[1]
□ Every day
□ Some days
□ Not at all
*If answer ‘Not at all’ skip to 34

32. On how many of the PAST 30 DAYS did you smoke a cigarette?
[1]
Enter number: __ __ days
□ Not applicable

33. On average, when you smoked in the PAST 30 DAYS, how many cigarettes did you
smoke?
[1]

Enter number: ____ cigarettes
□ Not applicable

34. Have you ever used or tried any smokeless tobacco products such as chewing
tobacco or snuff?
[4]
□ Yes □ No

35. Do you currently use chewing tobacco or snuff every day, some days, or not at all?
[4]

□ Every day
□ Some days
□ Not at all

36. Do you currently use any tobacco products other than cigarettes, such as cigars,
pipes, bidis, kreteks, or any other tobacco product?
[4]
□ Yes □ No
[Note: Bidis are small, brown, hand-rolled cigarettes from India and other southeast Asian
countries. Kreteks are clove cigarettes made in Indonesia that contain clove extract and tobacco.]

146

Risky or inattentive driving behaviors:

37. How often do you wear a seat belt when driving in or riding in a car?
[3-adapted]
□ Never
□ Rarely
□ Sometimes
□ Most of the time
□ Always

38. During the PAST 30 DAYS, how many times did you ride in a car or other vehicle
driven by someone who had been drinking alcohol?
[3]
□ 0 times
□ 1 time
□ 2 or 3 times
□ 4 or 5 times
□ 6 or more times

39. During the PAST 30 DAYS, how many times did you drive a car or other vehicle
when you had been drinking alcohol?
[3]
□ 0 times
□ 1 time
□ 2 or 3 times
□ 4 or 5 times
□ 6 or more times

40. In the PAST 5 YEARS, how many speeding tickets or driving violations have
you been issued (not including parking tickets)?
[9]

Enter number: ____ tickets or violations

41. How many automobile accidents (including minor collisions) have you had in the
PAST 5 YEARS?
[9]
Enter number: ____ accidents

42. During the PAST 30 DAYS, how often did you find yourself driving inattentively
because you were distracted, angry, too tired, thinking about other things, or
worried about something?
[9]
□ 0 times
□ 1 time
□ 2 or 3 times
□ 4 or 5 times
□ 6 or more times

147
43. During the PAST 30 DAYS, how often did you find yourself cutting off or swearing
at other drivers because you were annoyed with or angry at them?
[9]
□ 0 times
□ 1 time
□ 2 or 3 times
□ 4 or 5 times
□ 6 or more times

Sun exposure:

44. This question is about sunburns, including any time that even a small part of your
skin was red or burned for more than 12 hours.
[4]
a. Have you had a sunburn within the PAST 12 MONTHS? □ Yes □ No
b. Including times when even a small part of your skin was red for more
than 12 hours, how many sunburns have you had within the PAST 12
MONTHS?
□ One
□ Two
□ Three
□ Four
□ Five
□ Six or more
□ I have not been sunburned in the past 12 months.

Weight:

These next questions are about your height and weight.

45. How tall are you without shoes?
[5a]
___ ft., ___ inches OR __ meters, __centimeters

46. How much do you weigh without shoes?
[5a]
____ pounds OR ___ kilograms

47. How much did you weigh at age 18?
[5a]
____ pounds OR ___ kilograms

48. How do you describe your weight?
[3]
□ Very underweight
□ Slightly underweight
□ About the right weight
□ Slightly overweight
□ Very overweight

49. Which of the following are you trying to do about your weight?
[3]
□ Lose weight
□ Gain weight

148
□ Stay the same weight
□ I am not trying to do anything about my weight

50. During the PAST 30 DAYS, on about how many days did you skip or miss meals,
either accidentally or on purpose (e.g., because you were too busy, forgot, or were
trying to lose weight)?
[9]

Enter number of days: __ __ days

51. During the PAST 30 DAYS, for about how many days did you go without eating
for 24 hours or more (also called fasting) to lose weight or keep from gaining
weight?
[3-adap]

Enter number of days: __ __ days

52. During the PAST 30 DAYS, for about how many days did you take any diet pills,
powders, or liquids without a doctor’s advice to lose weight or keep from gaining
weight? (Do not include meal replacement products such as Slim Fast.)
[3-adap]

Enter number of days: __ __ days

53. During the PAST 30 DAYS, for about how many days did you vomit or take
laxatives to lose weight or keep from gaining weight?
[3-adap]

Enter number of days: __ __ days

General risky behavior:

54. How much do you agree with this statement…
“I’m more likely to take risks than the average person.”
[6]

□ Disagree strongly
□ Disagree somewhat
□ Uncertain
□ Agree somewhat
□ Agree strongly

Hostility:

Answer each from 1 (not at all like me) to 5 (extremely like me)
[8]

not at all
like me

somewhat
like me

extremely
like me
55. My Friends say that I am somewhat
argumentative.
1 2 3 4 5
56. At times, I feel I have gotten a raw deal 1 2 3 4 5

149

not at all
like me

somewhat
like me

extremely
like me
out of life (had bad luck in life).
57. Sometimes, I fly off the handle (get very
upset or angry) for no good reason.
1 2 3 4 5
58. Given enough provocation, I may hit
another person.
1 2 3 4 5
59. I can’t help getting into arguments when
people disagree with me.
1 2 3 4 5
60. I have trouble controlling my temper. 1 2 3 4 5
61. I sometimes feel that people are laughing
at me behind my back.
1 2 3 4 5
62. If somebody hits me, I hit back. 1 2 3 4 5

(5) Health promoting behaviors (e.g., nutrition, sleep, exercise)

Sleep:

63. On average, how many hours of sleep do you get in a 24-hour period?
[1]

Enter number of hours: ___ hours
(Enter hours of sleep in whole numbers, rounding 30 minutes (1/2 hour) or more UP to
the next whole hour and dropping 29 or fewer minutes.)

64. During the PAST 30 DAYS, for about how many days have you felt you did not get
enough rest or sleep?
[4]
Enter number of days: __ __ days
Question also listed under #2 fatigue.

65. How satisfied are you with your sleep?
[WHO-BREF 16]

1 2 3 4 5
very neither very
dissatisfied satisfied

Nutrition/Diet:

These next questions are about the foods that you usually eat or drink. Please indicate
how often you eat or drink each one, for example, twice a week, three times a month, and
so forth. Remember, we are only interested in the foods you eat. Include all foods you
eat, both at home and away from home.

66. How many servings of vegetables do you usually eat? (Example: A serving of
vegetables at both lunch and dinner would be two servings.)
[4-adap]
____ servings per day, week, month (please circle one.)

150

67. How many servings of fruit do you usually eat?
[9]

____ servings per day, week, month (please circle one.)

68. How often do you eat non-nutritious snack foods (e.g., chips, candy, cookies)?
[9]
____ times per day, week, month (please circle one.)

For questions 69-72, consider a serving as 8 ounces or 1 cup.

69. How often do you drink milk? (Include milk used on cereal, etc.)
[9]
____ cup(s) per day, week, month (please circle one.)

70. How often do you drink coffee with caffeine?
[9]

____ cup(s) per day, week, month (please circle one.)

71. How often do you drink soft drinks/carbonated beverages with caffeine? (e.g., Diet
Coke, Coke, Pepsi, Mountain Dew, etc.)
[9]
____ cup(s) per day, week, month (please circle one.)

72. How often do you drink water?
[9]
____ cup(s) per day, week, month (please circle one.)

73. Over the PAST 30 DAYS, have you taken any vitamin, mineral, herbal, botanical, or
other dietary supplements?
[5 2001]
□ Yes □ No

74. On average, how many times per WEEK do you eat meals that were prepared in a
restaurant? (Please include eat-in restaurants, carry out restaurants, fast food restaurants,
and restaurants that deliver food to your house.)
[2]
Enter times per week: ____ □ Less than weekly □ Never

Exercise:

75. Over the PAST 30 DAYS, on average how many hours per day did you sit and watch
TV or videos (outside of work)?
[2]
□ less than 1 hr □ 1 hr □ 2 hrs □ 3 hrs □ 4 hrs □ 5 hrs □ 6+ hrs
□ Don’t watch TV or videos

76. Over the PAST 30 DAYS, on average how many hours per day did you use a
computer or play computer games (outside of work)?
[2]
□ less than 1 hr □ 1 hr □ 2 hrs □ 3 hrs □ 4 hrs □ 5 hrs □ 6+ hrs
□ Don’t use computer or play computer games (outside of work)

151
These next questions are about physical activities that you may do, including exercise,
sports, work, and physically active hobbies. Please include all activities you do,
including those in your free time or related to work or errands. Questions will move from
hard or vigorous activities to more moderate activities.

77. Over the PAST 30 DAYS, did you do any hard or vigorous activities for at least 10
minutes that caused HEAVY SWEATING OR LARGE INCREASES IN YOUR
BREATHING OR HEART RATE?
[1&5 2001-adap]
□ Yes* □ No
*If Yes, how many times per day, per week or per month did you do this
HARD or VIGOROUS activity over the PAST 30 DAYS?
____ times per day, week, month (please circle one.)
And on average, how long did you do these HARD or VIGOROUS
activities each time? ____ minutes

78. Over the PAST 30 DAYS, did you do any moderate activities for at least 10 minutes
that caused only LIGHT SWEATING OR A SLIGHT TO MODERATE INCREASE
IN BREATHING OR HEART RATE?
[1&5 2001-adap]
□ Yes* □ No
*If Yes, how many times per day, per week or per month did you do this
MODERATE activity over the PAST 30 DAYS?
____ times per day, week, month (please circle one.)
And on average, about how long did you do these MODERATE activities
each time? ____ minutes

79. Including anything you’ve already mentioned, did you do any physical activities
specifically designed as exercises to STRENGTHEN your muscles such as lifting
weights or other strength-building exercises over the PAST 30 DAYS?
[1&5 2001]
□ Yes* □ No
*If Yes, how many times per day, per week or per month did you do these
exercises over the PAST 30 DAYS?
____ times per day, week, month (please circle one.)

152
Appendix E. Alcohol and Drug Questionnaire (Wave 4)
Alcohol & Drug Questionnaire
1. In the past year, how often does your spouse consume
alcoholic beverages, that is, beer, wine or liquor?
Never
< 1 day
/month
1-3 days/
month
1-2 days/
week
3-4 days/
week
5-6 days/
week
Daily
2. When your spouse has alcohol, how many drinks does
she/he typically have?
1 2 3 4 5+

3. When your spouse has alcohol, what is the most drinks
she/he might have?
1 2 3 4 5+

4. In the past year, has your spouse had any problem with
alcohol?
No
Small
Problem
Large
problem

5. Currently does your spouse have any problem with
alcohol?
No
Small
Problem
Large
problem

6. In the past year, has anyone told your spouse that he/she
has a problem with alcohol?
No
Small
Problem
Large
problem

7. In the past year, how often did you consume alcoholic
beverages, that is, beer, wine or liquor?
Never
< 1 day
/month
1-3 days/
month
1-2 days/
week
3-4 days/
week
5-6 days/
week
Daily
8. When you have alcohol, how many drinks do you typically
drink?
1 2 3 4 5+

9. When you have alcohol, what is the most drinks you might
have?
1 2 3 4 5+

10. In the past year, have you had any problem with
alcohol?
No
Small
Problem
Large
problem

11. Currently, do you have any problem with alcohol? No
Small
Problem
Large
problem

12. In the past year, has anyone told you that you have a
problem with alcohol?
No
Small
Problem
Large
problem

153
Alcohol and Drug Questionnaire Page 2: CAGE
In the past year…

1. Have you felt that your spouse should cut down on his/her drinking? Yes No

2. Have people criticized your spouse’s drinking? Yes No

3. Do you think that your spouse has felt bad or guilty about his/her drinking? Yes No

4. Has your spouse had a drink the first thing in the morning to steady his/her Yes No
nerves or to get rid of a hangover?

5. Have you felt that you should cut down on your drinking? Yes No

6. Have people annoyed you by criticizing your drinking? Yes No

7. Have you felt bad or guilty about your drinking? Yes No

8. Have you had a drink first thing in the morning to steady your nerves Yes No
or to get rid of a hangover?
In the past year…
9. Has your spouse used drugs other than those required for medical reasons? Yes No
10. Has your spouse abused prescription drugs? Yes No
11. Have you used drugs other than those required for medical reasons? Yes No

12. Have you abused prescription drugs? Yes No
154
Appendix F. Heckman Correction
Table 1 . Variables included in Heckman Correction return probability estimating
quation e

Wave 1 Variables
a
B S.E. Wald df Sig. Exp(B)
Years married .38 .11 12.21 1 .00 1.46
Wife marital satisfaction
b
‐.08 .04 5.64 1 .02 .92
Wife anxiety
c
‐4.93 2.67 3.41 1 .07 .01
Wife global symptom index
c
6.94 2.83 6.04 1 .01 1034.94
Husband depression
c
‐9.70 3.62 7.19 1 .01 .00
Husband anxiety
c
‐5.61 2.70 4.31 1 .04 .004
Husband global symptom
index
c
26.49 8.06 10.80 1 .001 .00
Husband age ‐.17 .06 7.19 1 .01 .84
Number of children ‐1.53 .44 12.12 1 .001 .22
Husband # of times married 3.52 1.21 8.46 1 .004 33.68
Husband physical spouse
aggression
d
‐.93 .47 3.87 1 .05 .39
Wife physical spouse
aggression
d
.74 .30 6.03 1 .01 2.09
Wife emotional spouse
aggression
d
‐.53 .19 7.68 1 .01 .59
Husband emotional spouse
aggression
d
.65 .21 9.21 1 .002 1.91
Couple child’s biological
parents?
3.36 1.34 6.30 1 .01 28.87
Husband mental/physical
health problems count
e
‐1.00 .35 8.07 1 .004 .37
Wife Stress
f
‐.37 .10 13.00 1 .00 .69
Report of divorce or
g
‐3.62 1.30 7.80 1 .01 .03
separation

155
Table 1 , Continued. Variables included in Heckman Correction return probability
stimating equation e

Wave 1 Variables
a
B S.E. Wald df Sig. Exp(B)
Constant 8.05 5.85 1.90 1 .17 3141.91
a
The following variables were also examined for inclusion in the equation, but were excluded: whether husband
was born in the United States, whether wife was born in the United States, husband marital satisfaction
b
, income,
husband education, wife age, whether English is primary language spoken at home, wives’ number of previous
marriages, husband Michigan Alcohol Screening Test score (Selzer, 1971), wife Michigan Alcohol Screening Test
score, whether wife was employed wave 1, whether husband was employed at wave 1, wife mental/physical
problem count
e
, wife report of child’s problems (count of endorsed experienced with behavioral, mental, or
physical health problems, list of 22 items), husband report of child’s problems, wife Drug Abuse Screening Test
score (Gavin, Ross, & Skinner, 1989), husband Drug Abuse Screening Test score, number of friends living within
one mile (husband report), number of family living within one mile (husband report), number of moves
reported by husband and wife in last 10 years, Wife Hispanic/Latina status, Husband Hispanic/Latino status,.
Note that variables needed complete data to be considered for inclusion in Heckman Correction equations.
b
Measured by the Dyadic Adjustment Scale (Spanier, 1976).
c
Measures by the Symptom Checklist‐90‐Revised
(Derogatis, 1983).
d
Measured by the Domestic Conflict Index (Margolin, et al., 2000).
e
Measured by checklist of
13 mental and physical health problems (e.g., depression, thought disorder, high blood pressure, cancer, etc.)
f
Measured by stress ratings from Personal Background Questionnaire (sum of stress ratings for 10 topics plus
work stress ratings).
g
Divorce/separation reported during study (through wave 5), not at wave 1. This variable
may be inaccurate for families with complete loss of contact. Information based on last family contact

156
Appendix G. Correlation tables for emotional and physical aggression models
Table 1. Husband and Wife Spouse Emotional Aggression, Husband and Wife Depression, and Wife Physical Health Variables:
Pearson Correlations (lower left triangle) and Spearman Correlations (upper right triangle)

Variables 1 2 3 4 5 6 7 8 9 10
1. Wife Emotional Aggression 1.00 .58
***
.24
*
.13 .25
*
.22
*
.25
*
.12 .02 .17
2. Husband Emotional
Aggression
.75
***
1.00 .25
*
.17 .39
***
.23
*
.31
**
.34
**
.02 .33
**
3. Wife Depression .27
**
.27
**
1.00 .39
***
.21
*
.05 .
*
33
*
.08 .10 .28
**
4. Husband Depression .19 .27
**
.39
***
1.00 .02 ‐.21 .06 .06 .06 .17
5. Wife PH Composite .16 .40
***
.23
*
.13 1.00 .60
***
.69
***
.69
***
.38
***
.74
***
6. Wife Health Conditions .13 .29
**
.01 ‐.14 .58
***
1.00 .39
***
.21 .01 .30
**
7. Wife Subclinical Symptoms .13 .34
**
.29
**
.16 .71
***
.33
**
1.00 .34
**
.03 .51
***
8. Wife Preventive Care .14 .31
**
.06 .08 .70
***
.21 .28
**
1.00 .19 .42
***
9. Wife Health Behaviors ‐.02 ‐.13 .10 .08 .36
***
‐.03 ‐.02 .18 1.00 .19
10. Wife PH Quality of Life .12 .39
***
.28
**
.24
*
.76
***
.26
*
.59
***
.41
***
.15 1.00
N 118 118 103 102 84 84 84 84 84 85
PH = Physical Health. Multivariate outliers excluded from correlation analyses.   *p < .05.  **p < .01.  ***p < .001.

Table 2. Husband and Wife Spouse Emotional Aggression, Husband and Wife Depression, and Husband Physical Health Variables:
Pearson Correlations (lower left triangle), Spearman Correlations (upper right triangle), and Descriptive Statistics

Variables 1 2 3 4 5 6 7 8 9 10
1. Wife Emotional Aggression 1.00 .58
***
.24
*
.13 .25
*
.33
**
.12 .17 .02 .16
2. Husband Emotional
Aggression
.75
***
1.00 .25
*
.17 .37
***
.30
**
.16 .36
***
.15 .15
3. Wife Depression .27
**
.27
**
1.00 .39
***
.10 .26
*
.03 .09 .15 ‐.06
4. Husband Depression .19 .27
**
.39
**
1.00 .28
**
.22
*
.32
**
.06 .17 .28
**
5. Husband PH Composite .18 .27
*
.15 .34
**
1.00 .50
***
.69
***
.66
***
.54
***
.66
***
6. Husband Health Conditions .26
*
.22
*
.30
**
.27
**
.55
***
1.00 .27
*
.16 .16 .18
7. Husband Subclinical
Symptoms
.04 .21 .03 .26
*
.73
***
.25
*
1.00 .23
*
.17 .54
***
8. Husband Preventive Care .19 .20 .03 .04 .63
***
.11 .28
*
1.00 .26
*
.21
9. Husband Health Behaviors .02 .02 .15 .14 .50
***
.17 .12 .25
*
1.00 .17
10. Husband PH Quality of
Life
.09 .16 ‐.02 .40
***
.69
***
.20 .58
***
.23
*
.17 1.00
N 118 118 103 102 82 82 82 82 82 83

PH = Physical Health. Multivariate outliers excluded from correlation analyses. *p < .05.  **p < .01.  ***p < .001.

157

Table 3. Husband and Wife Spouse Physical Aggression, Husband and Wife Depression, and Wife Physical Health Variables:
Pearson Correlations (lower left triangle) and Spearman Correlations (upper right triangle)

Variables 1 2 3 4 5 6 7 8 9 10
1. Wife Physical Aggression 1.00 .57
***
.22
*
.10 .27
*
.10 .25
*
.25
*
.22
*
.09
2. Husband Physical
Aggression
.89
***
1.00 .12 .20
*
.17 .10 .14 .18 .06 .15
3. Wife Depression .14 .20
*
1.00 .39
*
1.00
**
.22 .09 .33
*
.07
*
.06 .10 .27
*
4. Husband Depression .05 .29
.10
**
.40
***
.02 ‐.17 .02 .08 .16
5. Wife PH Composite .15 .23
*
.14 1.00 .60
*
1.00
**
.69
***
.72
***
.38
*
‐.01
**
.76
***
6. Wife Health Conditions .13
.08
.09 .09 ‐.09 .60
***
.39
*
1.00
**
.27
*
.32
**
7. Wife Subclinical Symptoms .02 .29
.03
*
.16 .71
***
.36
*
.35
*
1.00
*
.03 .52
**
8. Wife Preventive Care .12 .13 .05 .72
***
.30
*
‐.04
.29
*
‐.02
*
.21 .42
*
.19
**
9. Wife Health Behaviors .15 .03 .10 .10 .36
***
.20 1.00
10. Wife PH Quality of Life ‐.04 .04 .27
*
.24
*
.76
***
.31
**
.59
***
.41
***
.16 1.00
N 117 117 102 101 80 79 80 79 80 82

PH = Physical Health. Multivariate outliers excluded from correlation analyses.   *p < .05.  **p < .01.  ***p < .001.

158

Table 4. Husband and Wife Spouse Physical Aggression, Husband and Wife Depression, and Husband Physical Health Variables:
Pearson Correlations (lower left triangle) and Spearman Correlations (upper right triangle)

Variables 1 2 3 4 5 6 7 8 9 10
1. Wife Physical Aggression 1.00 .57
***
.22
*
.10 .35
***
.27
*
.16 .42
***
.19 .23
*
2. Husband Physical
Aggression
.89
***
1.00 .12 .20
*
.31
*
.10
*
.15 .22
*
.03
.23
*
.07
.11 .24
*
3. Wife Depression .14 .20
*
1.00 .39
***
.28
*
.15 ‐.08
4. Husband Depression .05 .29
**
.40
***
1.00 .28
*
1.00
*
.25
*
.31
**
.02 .18 .27
*
5. Husband PH Composite .19 .29
*
.15 .34
**
.52
*
1.00
**
.69
***
.66
*
.19
**
.54
*
.16
**
.65
*
.19
**
6. Husband Health Conditions .21 .24
*
.31
*
.03
*
.28
**
.56
***
.28
*
1.00
7. Husband Subclinical
Symptoms
‐.004 .22
*
.26
*
.74
***
.25
*
.12
.21 .18 .54
*
.20
**
8. Husband Preventive Care .35
*
.08
**
.16 .01 .01 .63
***
.27
*
.12
1.00 .29
*
1.00 9. Husband Health Behaviors ‐.01 .15 .15 .50
***
.16 .29
*
.22
.16
10. Husband PH Quality of
Life
.16 .29
**
‐.04 .40
***
.68
***
.20 .58
***
.16 1.00
N 117 117 102 101 81 80 81 80 81 81
PH = Physical Health. Multivariate outliers excluded from correlation analyses.   *p < .05.  **p < .01.  ***p < .001.

159

Abstract (if available)

Abstract This longitudinal study examined relationships for male and female intimate partner aggression with depression and physical health, and indirect effects of aggression on health via depressive symptoms for 119 midlife couples. Physical and emotional aggression victimization and perpetration were examined

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