Journal of Affective Disorders 152-154 (2014) 434–440

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Research report

Lifetime major depression and comorbid disorders among current-era women veterans John F. Curry a,b,c,n, Nicki Aubuchon-Endsley a,d, Mira Brancu a,b,c, Jennifer J. Runnals a,b,c, VA Mid-Atlantic MIRECC Women Veterans Research Workgroup b, VA Mid-Atlantic MIRECC Registry Workgroup b, John A. Fairbank a,b,c a

Durham VA Medical Center, Durham, NC 27705, USA Mid-Atlantic Region VA Mental Illness Research, Education and Clinical Center (VISN 6 MIRECC), Durham, NC 27705, USA c Duke University Medical Center, Durham, NC 27705, USA d Brown University, Warren Alpert Medical School, Providence, RI 02912, USA b

art ic l e i nf o

a b s t r a c t

Article history: Received 20 September 2013 Accepted 8 October 2013 Available online 16 October 2013

Background: Most research on women veterans' mental health has focused on postraumatic stress disorder (PTSD) or reactions to military sexual trauma. Although depression is also a frequent diagnosis among women veterans, little is known about its characteristics, including comorbid conditions and patterns of disorder onset. We investigated lifetime diagnoses of major depressive disorder (MDD) and comorbid conditions in a primarily treatment-seeking research sample of male and female veterans to determine frequency of lifetime MDD, comorbid disorders and their temporal onset. Method: The 1700 veterans (346 women; 1354 men) completed diagnostic interviews as participants in a research registry. Rates of and gender differences in lifetime MDD and comorbid conditions (PTSD, other anxiety disorders, substance use and eating disorders) were calculated. We assessed the percentage of cases in which MDD preceded the comorbid condition (primary onset MDD). Results: Lifetime MDD was frequent in this sample, and significantly more common in women (46.5%) than in men (36.3%). Gender differences in comorbidity were found for anxiety and eating disorders (more common in women); and for alcohol and nicotine use disorders (more common in men). However, primary onset MDD was no more common among women than among men, and was in neither case the predominant pattern of comorbid lifetime disorder onset. Limitations: The sample is not representative of all veterans, and lifetime diagnoses were based on retrospective recall. Conclusions: MDD usually follows the onset of other comorbid disorders among women veterans, indicating the need to assess for earlier lifetime disorders in veterans with MDD. Published by Elsevier B.V.

Keywords: Women veterans Depression Comorbidity Gender differences

1. Introduction Most research literature on women veterans' mental health relates to posttraumatic stress disorder (PTSD) or reactions to military sexual trauma (MST; Goldzweig et al., 2006). However, depression is also a frequent diagnosis among women veterans. For example, Maguen et al. (2010) found that, among 329,049 veterans of Iraq or Afghanistan who were seeking health care in the Veterans Health Administration, 23% of the 40,701 women had diagnoses of depressive disorders, and the frequency of depression was significantly higher among women

n Corresponding author at: Durham Veterans Administration Medical Center, Mid-Atlantic Region VA Mental Illness Research, Education and Clinical Center (VISN 6 MIRECC), Building 5, 508 Fulton Street, Durham, NC 27705, USA. Tel.: þ 1 919 619 8245; fax: þ1 919 681 1600. E-mail addresses: [email protected], [email protected] (J.F. Curry).

0165-0327/$ - see front matter Published by Elsevier B.V. http://dx.doi.org/10.1016/j.jad.2013.10.012

than among men. Similarly, Seal et al. (2009) reported that depressive disorders had the second highest (after PTSD) increase in prevalence between 2002 and 2008 among Iraq/Afghanistan war veterans enrolled in Veterans Affairs (VA) health care, and was also more common among women than men. Despite the prevalence of depression among women veterans, little is known about related features such as comorbid conditions and patterns of diagnostic onset. The above studies (Maguen et al., 2010; Seal et al., 2009) demonstrated that the presence of two or more psychiatric disorders is frequent among veterans seeking health care. In one study, 20% of both men and women had more than one psychiatric diagnosis (Maguen et al., 2010). In the other, over half of those with one diagnosis had two or more (Seal et al., 2009). Nonetheless, these studies were limited to the clinical diagnoses in the medical charts. They did not include formal assessment of diagnostic criteria based on semi-structured interviews evaluating

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the range of possible comorbid conditions. Moreover, they did not report specific combinations of comorbid disorders. Smaller studies with women veterans serving prior to the current conflicts in Iraq and Afghanistan found that psychiatric comorbidity was likely to be common in treatment-seeking settings. For example, Bader et al. (2001) screened for mental illness at a VA Women's Health Clinic, and found that 45% of 209 women likely had a psychiatric disorder, with 22% likely to have two or more disorders. However, specific comorbid combinations were not reported. Grubaugh et al. (2006) did use formal diagnostic interviews with a pre-Afghanistan/Iraq war sample of 187 women veterans (average age approximately 50 years) seeking primary care. In their sample 44% of the women evidenced a psychiatric disorder, with 24% meeting criteria for two or more disorders. Twenty-nine percent had current major depressive disorder (MDD), and 44.1% had lifetime MDD. Two-thirds of the women with current MDD had an additional psychiatric disorder. However, specific combinations of comorbid disorders were again not reported. Based on primarily male pre-Iraq/Afghanistan era samples of veterans, the disorders most likely to be comorbid with depressive disorders appear to be PTSD, substance use disorders, and other anxiety disorders. In formerly deployed veterans of the First Gulf War (88% male), those with current depressive disorders had high rates of comorbid anxiety disorders (51.5%, including 27.3% with PTSD), and substance use disorders (13.6%). A similar pattern was found using lifetime, rather than current diagnoses (Black et al., 2004). In a large sample of pre-Afghanistan/Iraq veterans (93% male) 69% of those diagnosed with PTSD also had MDD (Magruder et al., 2005). Although there are relatively fewer studies examining depression and non-PTSD anxiety disorder comorbidity in women veterans, a recent study (Sambamoorthi et al., 2010) utilizing a sample of women veterans with cardiovascular disease, hypertension or diabetes (63% over age 49; 69% White) demonstrated a 20% rate of comorbidity between depressive disorders and non-PTSD anxiety disorders. Comorbid substance use disorders occurred at the same frequency, followed by PTSD at 11%. Davis et al. (2003) screened for psychiatric and substance use disorders in a sample of over 1000 women veterans of the World War II through First Gulf War eras. They found that PTSD and MDD were the most likely mental health disorders, with 33% and 20% of the sample, respectively, screening positive for these disorders. Misuse of substances (alcohol, illicit drugs, or nicotine) occurred in approximately 60% of the women with likely PTSD or MDD. Other specific combinations of psychiatric comorbidity were not reported. Earlier work had also indicated that heavy smoking was associated with elevated depression symptoms in women veterans from eras prior to the First Gulf War (Whitlock et al., 1995). While it is important to better understand the co-occurrence rates of mental health disorders among current-era women veterans, equally important is increased knowledge of the temporal association of MDD and other psychiatric or substance use disorders. Across the course of development, episodes of depression can precede, follow, or be concurrent with episodes of other disorders (Niciu et al., 2009; Pittman et al., 2012). In a recent longitudinal investigation of male Israeli veterans (Ginzburg et al., 2010), PTSD symptoms significantly predicted the emergence of later depression, anxiety, and comorbid depression and anxiety. However, the reverse was not true, suggesting that PTSD was the primary onset disorder which may have led to or increased the risk for subsequent depression and other anxiety disorders. Understanding such patterns and sequences of comorbid disorder onset over time has implications for secondary prevention and treatment (Swendsen et al., 2010). Optimally, effective treatment of a primary onset disorder may serve a protective function against the emergence of a later disorder. Importantly, the frequency of psychiatric conditions that are co-morbid with depression, as well as patterns in temporal onset

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may differ by gender. Women with MDD appear more likely to have comorbid anxiety disorders and less likely to have comorbid alcohol use disorders than men with MDD (Verhagen, et al., 2008). Moreover, given that onset of MDD is significantly more frequent in girls than in boys after the age of 14 (Wade et al., 2002) it seems likely that female veterans would report higher rates of lifetime MDD, and earlier average age of MDD onset than male veterans. In summary, depression among women veterans who served in the Iraq and Afghanistan era is relatively understudied. There is need for more information on the frequency of MDD, itself, of the conditions co-morbid with MDD, such as PTSD, non-PTSD anxiety disorders, and substance use disorders, and of the temporal onset of these conditions. We investigated the frequency of lifetime MDD and comorbid disorders and their patterns of temporal onset in a sample of current-era veterans, comparing women and men. Consistent with prior work we hypothesized that women would have a higher frequency of lifetime MDD than men. We further hypothesized that there would be gender differences in the patterns of comorbidity of disorders with MDD, and in the temporal relationship of comorbid disorders with MDD. We predicted that lifetime MDD would be more likely to precede the onset of comorbid disorders among women than among men.

2. Method 2.1. Participants Measures in this study were collected as part of the VA MidAtlantic Mental Illness Research, Education, and Clinical Center (VISN 6 MIRECC) multi-site registry of volunteer US military veterans, active duty personnel, and reserve forces (National Guardsmen and Reservist) members who had served since September 11, 2001 in support of the Iraq/Afghanistan era conflicts. Data collection of interviews and demographic questionnaires included in this crosssectional cohort study occurred between June 2005 and May 2012 and the current study is a secondary analysis of this previously collected data. From the total of 1808 participants in the registry who were administered a Structured Clinical Interview for DSM-IV Diagnoses (SCID-I) as of May, 2012, we excluded those with a lifetime diagnosis of any psychotic disorder or any major depressive episode that was part of a disorder other than MDD (bipolar disorder, substance-induced mood disorder, mood disorder directly due to a medical condition), and those with missing or discrepant data. A total of 1700 participants were included in the current study. Lifetime diagnostic data were available for all 1700 participants across all diagnoses except lifetime nicotine dependence, where data were available for 1551 subjects. 2.2. Procedures The institutional review board at each of the four collaborating sites approved the protocol prior to initiating the study. All participants were given a verbal description of the protocol prior to signing a written informed consent. Participants had been recruited and referred from a variety of sources, including fliers, advertisements, VA clinic referrals, and invitational letters using the Dillman (2000) system of subject recruitment. Most of the participants were treatment-seeking veterans registered with a VA hospital as a health care recipient. 2.3. Measures 2.3.1. Demographic information Demographic data were gathered for all participants, including gender; age; race/ethnicity (White non-Hispanic, African-American

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non-Hispanic, or Other, including Hispanic); marital status (married/remarried, widowed/separated/divorced, or never married); current employment status (full time, part time, or unemployed/ retired); and years of formal education. Structured Clinical Interview for DSM-IV-TR Axis-I Disorders/ Provider form (SCID-I/P, First et al., 1994): The SCID-I/P is a semi-structured interview for determining DSM-IV Axis I diagnoses. The SCID gathers information about current and lifetime disorders, including year and ages of onset though retrospective recall of past experiences. Clinical interviewers are trained to compare information given regarding onset of disorders and clarify with subjects in order to obtain internally consistent information regarding their retrospective recall. The SCID has been found to be both clinically sensitive and reliable (Keane and Barlow, 2002), with good to excellent inter-rater reliability for current and lifetime diagnoses (Lobbestael et al., 2011; Rogers, 2001; Williams et al., 1992). SCID interviewers in the current project completed an extensive training program that included rating SCID training videos, observing and being observed conducting at least one live interview by an experienced SCID study interviewer, receiving ongoing consultation, and participating in bi-weekly reliability meetings. The interviewers (n ¼22) demonstrated excellent mean inter-rater concordance for current Axis I diagnosis (Fleiss' kappa ¼.94), including MDD and PTSD (Fleiss' kappa ¼1.00 for both). Similarly, there was excellent mean inter-rater concordance on lifetime diagnoses (k ¼.94), including MDD (k ¼.88) and PTSD (k¼ 1.00).

2.4. Data Analyses All data analyses were performed using SPSS, version 21. Analyses of psychiatric disorders were based on data gathered from the SCID.

2.4.1. Gender differences in demographic variables First, the full sample was described, both combined and separately by gender, in terms of age, race, education, marital status, and employment status (see Table 1). The significance of gender differences in these demographic variables was examined by independent samples t-tests for semi-continuous variables (age, years of education) or Chi-square tests of association for categorical variables (race, marital status, and employment status).

2.4.2. Prevalence of, and gender differences in, lifetime disorders We calculated the prevalence rates of lifetime diagnoses, as assessed by the SCID, for the following disorders: major depressive disorder (MDD-L); posttraumatic stress disorder (PTSD-L); other anxiety disorders (ANX-L: panic disorder, agoraphobia without panic disorder, specific phobia, social phobia, obsessive–compulsive disorder, or generalized anxiety disorder), alcohol use disorders (AUD-L: abuse or dependence), cannabis use disorders (CANN-L: abuse or dependence), nicotine dependence (ND-L), and eating disorders (EAT-L: anorexia nervosa, bulimia nervosa, and binge-eating disorder). Gender differences in rates were tested for significance. 2.4.3. Gender differences among veterans with MDD-L We next compared only those men and women with MDD-L on demographic variables, and lifetime comorbid disorders. 2.4.4. Sequence of lifetime disorder onset The sequence of onset, gathered systematically through structured and standardized SCID interview questions, of MDD-L and comorbid lifetime diagnoses was coded (i.e., lifetime MDD onset at least one year before comorbid disorder onset [primary MDD]; lifetime MDD and comorbid disorder onset within one year of each other, or lifetime MDD onset at least one year after comorbid disorder). Because our hypothesis was that women would be more likely than men to have primary onset MDD-L we then compared primary onset MDD-L to MDD-L that was either concurrent with or subsequent to comorbid disorders [both considered nonprimary onset MDD].

3. Results The registry sample included 1700 current-era veterans (1354 men; 346 women). Characteristics of the sample are included in Table 1. The sample of women included a significantly greater percentage of African American participants and a lower percentage of White participants, compared to the sample of men (χ2(2) ¼46.73, po .0001). Women were significantly less likely than men to be currently or formerly married (χ2(2)¼ 94.01, po .0001). Whereas equal percentages of men and women were not working, employed women were more likely than men to be working part-time (χ2(2)¼ 7.90, p ¼.019).

Table 1 Demographic characteristics of registry veterans. Combined sample

Age Years of education Ethnicity: White African American Other Missing Marital status: Married Formerly married Never married Missing Employment: Not working Part-time Full-time Missing

Women

Men

N/n

Mean (SD)

n

Mean (SD)

n

Mean (SD)

1700 1679

37.48 (10.11) 13.43 (3.52)

346 340

36.88 (9.75) 13.80 (3.55)

1354 1339

37.64 (10.20) 13.34 (3.51)

702 822 166 10 1697 931 390 376 3

91 222 30

% 26.5 64.7 8.7

611 600 136

% 45.4 44.5 10.1

109 116 119

31.7 33.7 34.6

822 274 257

60.8 20.3 19.0

561 170 961 8

115 48 181

33.4 14.0 52.6

446 122 780

33.1 9.1 57.9

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Of the 1700 participants, 652 (38.4%) had a diagnosis of MDD at some point during their lifetime (MDD-L). MDD-L was significantly more common among women veterans than among men (46.5% versus 36.3%; χ2(1) ¼12.29, p o.001). It was also associated with being of other than White or African American race (χ2(2) ¼6.83, p ¼.033), with having been formerly married (widowed/separated/ divorced) (χ2(2) ¼7.74, p ¼.021), and with not being currently employed (χ2(2)¼70.21, p o.001). Rates of lifetime diagnoses within the entire study sample, along with gender differences in rates of these disorders, are shown in Table 2. With the exception of PTSD-L, which characterized 37.6% of the registry sample, all lifetime diagnoses differed significantly by gender. In addition to MDD-L, both ANX-L and EAT-L were more common among women, whereas AUD-L, CANN-L, and ND-L were more common among men. We then investigated gender differences among veterans with MDD-L. Women with MDD-L did not differ from men with MDD-L on age at time of SCID assessment or years of education. Women reported a mean age at onset of first MDD episode of 28.50 years (SD ¼ 11.41), which did not differ significantly from that reported by men [M¼ 29.54; SD ¼9.71, t(459) ¼.95, p ¼.344]. Compared to men with MDD-L, women were more likely to be AfricanAmerican and less likely to be White (χ2(2) ¼17.88, p o.001); more likely to be in part-time than full-time employment (χ2(2)¼ 12.54, p ¼.002); and more likely to have never married or to be formerly married than to be currently married (χ2(2)¼ 47.60, p o.0001). The gender differences in ethnicity and in marital status, however, were not restricted to veterans with MDD-L, as they also characterized registry participants without MDD-L. Among the latter group, there were significantly more African–American and fewer White women compared to men (χ2(2)¼ 30.33, p o.0001). Likewise, women without MDD-L were significantly more likely than men without MDD-L to have never married or to be formerly married than to be currently married (χ2(2) ¼46.41, p o.0001). By contrast, the gender difference in full-time versus part-time employment that characterized veterans with MDD-L was not found in veterans without MDD-L (χ2(2)¼.49, p¼ .784). We next analyzed gender differences in the prevalence of comorbid lifetime diagnoses among men and women with MDDL. Comparison of rates of disorders in Table 2 and Table 3 indicates that rates of each disorder were higher among veterans with MDD-L than for the sample as a whole, and that the gender differences in comorbid disorders in most cases mirrored those for the whole sample, consistent with our first hypothesis. Men with

Women

n

%

n

%

n

%

652 639 229 623 154 291 26

38.4 37.6 13.5 36.6 9.1 18.8 1.5

161 127 72 77 9 36 16

46.5 36.7 20.9 22.3 5.5 11.7 4.6

491 512 157 546 135 255 10

36.3 37.9 11.6 40.3 10.0 20.5 7

po .01. p o.001. nnn p o .0001. nn

Table 3 Prevalence of lifetime comorbid disorders in female and male veterans with MDD-L.

PTSD-L ANX-L AUD-L CANN-L ND-L EAT-L

χ2

Women (n¼ 161)

Men (n ¼491)

n

%

n

%

98 49 50 13 24 14

60.9 30.4 31.1 8.1 17.3 8.7

326 85 284 65 136 7

66.4 17.3 57.8 13.2 30.3 1.4

1.63 12.78nn 34.82nnn 3.07 9.09n 20.56nnn

Note: MDD-L ¼ lifetime major depressive disorder; PTSD-L ¼ lifetime post-traumatic stress disorder; ANX-L ¼ lifetime non-PTSD anxiety disorder; AUD-L¼ lifetime alcohol use disorder; CANN-L ¼lifetime cannabis use disorder; ND-L ¼lifetime nicotine dependence; EAT-L ¼lifetime eating disorder. n

p o .01. po .001. po .0001.

nn

nnn

χ2

Combined sample

Men

PTSD-L 12.29nn 00.16 20.18nnn 38.76nnn 6.71n 12.62nn 27.57nnn

Note: MDD-L ¼ lifetime major depressive disorder; PTSD-L ¼lifetime post-traumatic stress disorder; ANX-L ¼ lifetime non-PTSD anxiety disorder; AUD-L ¼lifetime alcohol use disorder; CANN-L ¼ lifetime cannabis use disorder; ND-L ¼ lifetime nicotine dependence; EAT-L ¼ lifetime eating disorder. n

MDD-L were significantly more likely than women with MDD-L to have comorbid AUD-L or ND-L, with over half of depressed men but less than one-third of depressed women demonstrating comorbid AUD-L. However, whereas men in the full study sample were more likely than women to have CANN-L, men and women with MDD-L did not significantly differ in their rates of this comorbid disorder. There was no gender difference in PTSD-L among those with MDD-L, with both genders evidencing high rates (66.4% for depressed men and 60.9% for depressed women). Women with MDD-L were more likely than men with MDD-L to have comorbid ANX-L (30.4% versus 17.3% (X2(1)¼ 12.79, p ¼.0003), or EAT-L (8.7% versus 1.4% (X2(1) ¼20.56, p o.0001). Next, we explored possible gender differences in the sequence of onset of comorbid MDD-L and other lifetime disorders. Results are shown in Table 4. A primary MDD-L, as defined above, was consistently less prevalent than non-primary MDD-L. Rates of primary MDD-L ranged from a low of 10.7% among men with comorbid NIC-L to just over 30% among men or women with comorbid AUD-L. Contrary to our hypotheses, in no instance were there any significant gender differences in the pattern of onset of MDD-L and a comorbid disorder. Finally, in an exploratory effort to determine whether women were more likely than men to have earlier onset of less complex

Table 4 Frequency of primary onset major depressive disorder among male and female veterans with lifetime comorbid disorders.

Table 2 Prevalence of lifetime disorders in registry sample.

MDD-L PTSD-L ANX-L AUD-L CANN-L ND-L EAT-L

437

AUD-L CANN-L ANX-L ND-L

Primary MDD-L Other MDD-L Primary MDD-L Other MDD-L Primary MDD-L Other MDD-L Primary MDD-L Other MDD-L Primary MDD-L Other MDD-L

Men

%

Women

%

51 155 61 132 6 15 15 39 11 92

24.8 75.2 31.2 68.4 28.6 71.4 27.8 72.2 10.7 89.3

18 48 11 23 1 4 6 27 1 14

27.3 72.7 32.4 67.7 20.0 80.0 18.2 81.9 6.7 93.3

χ2(1)

p

.17

.683

.01

.933 NA

1.03

.310 NA

Note: MDD-L ¼ lifetime major depressive disorder; AUD-L ¼lifetime alcohol use disorder; CANN-L¼ lifetime cannabis use disorder; ANX-L ¼ lifetime anxiety disorder; ND-L ¼ lifetime nicotine dependence; Primary MDD-L ¼ MDD-L onset at least one year before onset of comorbid lifetime disorder; Other MDD-L ¼MDD-L onset within one year of, or subsequent to, onset of comorbid disorder. NA ¼statistical test not applicable due to low n.

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presentations of MDD-L, we explored gender differences in age of onset of MDD-L among veterans without the two most common comorbid conditions, PTSD-L or AUD-L. There was no gender difference in age of depression onset among veterans without comorbid PTSD-L (for men M ¼30.36; SD ¼ 8.83) versus M ¼31.31 (SD ¼ 11.77) for women; t(62.43) ¼ .494, p ¼.623). However, men with no history of AUD-L had a later age of MDD-L onset than women without AUD-L (M ¼31.94; SD ¼9.51) for men versus M¼ 28.51 (SD ¼11.82) for women; t(125.274) ¼2.17, p ¼.032.

4. Discussion We investigated depression in a large sample of Iraq and Afghanistan era veterans, comparing women and men on frequency of MDD-L, other lifetime disorders comorbid with MDD-L, and sequences of comorbid disorder onset. Overall the frequency of lifetime depression in this sample of veterans was high and as hypothesized, was relatively higher among women: almost half of women and slightly over a third of men met criteria for depression. Our hypothesis that frequency of comorbid lifetime disorders would differ by gender was partially supported. Among veterans with MDD-L, comorbid lifetime alcohol and nicotine disorders, but not cannabis disorders, were significantly more prevalent among men. This is consistent with prior work showing similar gender differences in rates of alcohol use disorders among veterans (Maguen et al., 2010). Our final hypothesis, that there would be more women than men for whom MDD-L preceded comorbid disorders, was not supported, nor was the age of onset for depression younger for women veterans as has been seen in non-veteran clinical samples (Marcus et al., 2005). 4.1. Prevalence of depression The rates of MDD-L in our sample (38.4% overall; 46.5% for women and 36.3% for men) exceed those found in a recent major epidemiological survey of American adults. In the National Comorbidity Survey Replication (NCS-R), the overall lifetime rate of MDD for adults ages 18 to 64 was 18.3%, with 22.1% of women and 14.4% of men meeting criteria for the diagnosis (Kessler et al., 2012). The MDD-L rates in our registry sample are similar to those in treatment-seeking samples of adults, including rates of 36.1% for women and 23.3% for men in a primary care setting (Rowe et al., 1995), but they are lower than rates found in some psychiatric outpatient studies, where even current MDD can characterize over 40% of participants (Mitchell et al., 2009). Our rates also exceed those seen in a study of veterans of the First Gulf War (Black et al., 2004) where 32% met criteria for a lifetime depressive disorder; with MDD-L, specifically, characterizing 25% of the predominantly male sample. However, that study was not based on a treatmentseeking sample. Moreover, a recent meta-analysis of MDD among (non-treatment-seeking) U.S. military active duty personnel reported current MDD rates of 12.0% among currently deployed and 13.1% among formerly deployed personnel. Estimated lifetime MDD rate in this study was 16.2% (Gadermann et al., 2012) The relatively high rates of MDD-L found in our sample likely reflects the fact that most participants who enrolled in the registry study were also enrolled in primary or specialized health care services at one of the participating Veterans Affairs Medical Centers. 4.2. Gender differences in depression rate As predicted, MDD-L was more frequent in women than in men. In fact, MDD-L was the most frequent lifetime diagnosis among women in our sample, characterizing 46.5% of women participants. Kessler (2003) has reviewed epidemiological studies

that consistently indicate that depression is much more common among women than among men and is the leading cause of disability worldwide among women. Unlike their non-depressed counterparts in our sample, women with MDD-L were more likely than men with MDD-L to be employed part-time rather than fulltime. The correlational design of our study precludes causal inferences, and the reasons for part-time employment are not known, but this finding raises the question of whether MDD-L among women veterans is associated with decreased employment. Along these lines, a major European epidemiological study found that, among depressed adults, women were significantly less likely than men to be in paid employment (Angst et al., 2002). 4.3. Gender differences in comorbidity The rates of comorbid lifetime disorders among those with MDD-L showed predicted gender differences, with anxiety and eating disorders more common in women with MDD-L, and alcohol and nicotine use disorders more common among men with MDD-L. It is notable that almost one-third of women with MDD-L also had a non-PTSD anxiety disorder (ANX-L). Anxiety complicates the treatment of major depression, leading to lower depression remission rates and longer time to remission (Fava et al., 2008). Although AUD-L was more common among men than among women with MDD-L, the rate of AUD-L in women veterans was as high as their rate of ANX-L. These findings underscore the importance of assessing and treating comorbid AUD in depressed women veterans. Nunes and Levin (2004) found that MDD treatment can have a significant effect in adults with depression and AUD although reducing the depression is unlikely to improve the AUD, suggesting both conditions require treatment. Among the full sample and among veterans with lifetime MDD the frequency of comorbid PTSD-L was similar and very high (460%) for men and women. These rates are consistent with those reported by Magruder et al. (2005), who studied comorbid current MDD among those with current PTSD. Previous work on PTSD has shown greater rates of PTSD in women than in men within the general population (Kessler et al., 2012) but higher rates in male than in female veterans (Maguen et al., 2010), which may be due in part to combat-related trauma exposure that is unique to male veteran versus male civilian samples. In fact, Vogt et al. (2011) found no gender difference in PTSD symptoms among veterans after exposure to combat was taken into account. 4.4. Sequence of depression onset Perhaps the most surprising findings in the present study were that the sequence of onset of comorbid lifetime disorders did not differ by gender. Because women experience depression more frequently than men (beginning around age 14), we expected that there would be a higher percentage of women veterans reporting MDD-L that preceded comorbid lifetime disorders. Instead, we found that primary onset MDD-L was in every instance less common than non-primary onset MDD-L, regardless of the comorbid lifetime condition. In addition, there were no gender differences in onset sequences, nor was there a gender difference in age of onset of first depressive episode. The latter finding is consistent with that of a large European study of primary care patients with depression (Maier et al., 1999), but differs from findings of a large American depression treatment study, in which women had earlier age of first depression episode onset than men (Marcus et al., 2005). A possible explanation for the lack of gender difference in temporal onset patterns of depression among veterans may be attributable to selection bias in that women choosing military service may be less likely to have a history of adolescent or young adult depression than non-veteran women. The only

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sub-group for whom we found that lifetime depression occurred earlier among women than among men was those depressed veterans without comorbid alcohol use disorders. It is possible that AUD raises the risk for onset of MDD or that early onset MDD raises the risk for AUD among men. Additional research is needed to evaluate these speculative explanations.

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presents with MDD, treatment can more effectively target the comorbid condition. Given the relevance of this information for understanding the etiology, maintenance, and effective/appropriate treatment of mental health conditions among male and female veterans, more work is needed that addresses the prevalence, co-morbidity, and time-course of onset of disorders.

4.5. Limitations Strengths of this study include a large sample size and the use of a standardized and validated measure of DSM-IV psychiatric diagnoses, which represents a methodological advance over other studies of veterans from the Iraq/Afghanistan era, especially women veterans. One limitation is that data are cross-sectional thus precluding causal inference. For example, among veterans with MDD-L and PTSD-L, in approximately three-quarters of the cases, the PTSD preceded onset of MDD. It is unknown whether this preceding condition (PTSD) might have caused or worsened the later onset depression. A second limitation is that diagnoses were based on subject's retrospective recall. Interviewers were trained to compare onset of all diagnoses and symptoms during the course of the SCID interviews as well as length of time elapsed between diagnoses as this information would have implications for final diagnoses (e.g., DSM-IV criteria for certain remission specifiers require specific timelines that had to be established during the interview). This likely improved the internal consistency of the data provided by the subjects, but is not a perfect substitute for longitudinal studies of course of illness. Finally, the sample consisted of mostly treatment-seeking veterans and therefore, the results cannot be generalized to all veterans. 4.6. Summary, implications and future directions The current findings show that across gender, rates of MDD-L among Iraq and Afghanistan-era veterans, most of whom were enrolled into VA care, are high, that MDD-L is often co-morbid with other significant lifetime mental health conditions, and that onset of MDD-L most often follows onset of the co-morbid mental health condition. Some of these co-morbid conditions, such as alcohol use disorders or eating disorders, differ between male and female veterans whereas others, such as PTSD, do not. While this pattern of depression following a preceding disorder is similar for men and women, importantly, and as expected, female veterans have higher rates of depression than male veterans. Two important implications can be drawn from this work. First, as the number of women in military service and thus veteran status increases, it will be critical to screen for and recognize MDD among women veterans. Second, given the likelihood of preceding onset of a separate mental health condition (for both male and female veterans), detection of depression symptoms should signal clinicians to assess for other likely preceding mental health conditions such as PTSD and AUD. While it is not possible to conclude from this data that the preceding condition is causing or maintaining the depression, prior work suggests that treatment of a preceding condition is substantially complicated by comorbid depression. For example, treatment of substance dependence, is rendered less effective by comorbid depression (Samet et al., 2013) and depressed individuals are more likely to drop out of treatment for PTSD (Bryant et al., 2003). It is likely important, then, for successful treatment to disentangle sequence of disorders in order to engage veterans in appropriate and effective interventions. Identifying primary-onset conditions early, perhaps during military service, will aid in the reduction of symptoms and the speed of treatment effectiveness post-military service. Similarly, when providers screen for possible comorbid diagnoses when a veteran

Role of funding source This research was supported by the US Department of Veterans Affairs Office of Mental Health Services grant to the VISN 6 MIRECC. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the funding agency.

Conflict of interest Dr. Curry receives grant funding from Pfizer and from Forest Pharmaceuticals. No other authors have any conflicts of interest.

Acknowledgements The VA Mid-Atlantic MIRECC Women Veterans Workgroup includes the following contributors: Beckham, Jean C Calhoun, Patrick Mann-Wrobel, Monica Robbins, Allison Strauss, Jennifer Swinkels, Cindy Van Voorhees, Elizabeth

PhD PhD PhD PhD PhD PhD PhD

DURVAMC, DURVAMC, DURVAMC, DURVAMC DURVAMC, DURVAMC, DURVAMC,

Duke University Medical Center Duke University Medical Center Duke University Medical Center Duke University Medical Center Duke University Medical Center Duke University Medical Center

The VA Mid-Atlantic MIRECC Registry Workgroup includes the following contributors: Beckham, Jean PhD DURVAMC, Duke University Medical Center Calhoun, Patrick S PhD DURVAMC, Duke University Medical Center Elbogen, Eric B PhD DURVAMC, University of North Carolina Fairbank, John A PhD DURVAMC, Duke University Medical Center Green, Kimberly T. MS DURVAMC, Duke University Medical Center Hoerle, Jeffrey M MS DURVAMC Hurley, Robin MD Salisbury (SBY) VAMC, Wake Forest University, Baylor College of Medicine Ingle, Sarah Kudler, Harold Marx, Christine E. McDonald, Scott D Moore, Scott Morey, Rajendra Pickett, Treven Taber, Katherine H Tupler, Larry A Wagner, H. Ryan Weiner, Richard Yoash-Gantz, Ruth

PhD MD MD, MS PhD

Hampton VAMC DURVAMC, Duke University Medical Center DURVAMC, Duke University Medical Center Richmond (R) VAMC, Virginia Commonwealth University MD, PhD DURVAMC, Duke University Medical Center MD, MS DURVAMC, Duke University Medical Center PsyD RVAMC, Virginia Commonwealth University PhD SBYVAMC, Virginia College of Osteopathic Medicine, Baylor College of Medicine PhD PhD MD, PhD PsyD

DURVAMC, Duke University Medical Center DURVAMC, Duke University Medical Center DURVAMC, Duke University Medical Center SBYVAMC, Wake Forest University

References Angst, J., Gamma, A., Gastpar, M., Lepine, J.-P., Mendlewicz, J., Tylee, A., 2002. Gender differences in depression: epidemiological findings from the European DEPRES I and II studies. Eur. Arch. Psychiatry Clin. Neurosci. 252, 201–209. Bader, G., Ragsdale, K.G., Franchina, J.J., 2001. Screening for mental illness in a Veterans Affairs women's health clinic. Psychiatr. Serv. 52 (11), 1521–1522, http://dx.doi.org/10.1176/appi.ps.52.11.1521. Black, D.W., Carney, C.P., Forman-Hoffman, V.L., Letuchy, E., Peloso, P., Woolson, R.F., Doebbeling, B.N., 2004. Depression in Veterans of the first Gulf War and comparable military controls. Ann. Clin. Psychiatry 16 (2), 53–61, http://dx. doi.org/10.1080/10401230490452645. Bryant, R.A., Moulds, M.L., Guthrie, R.M., Dang, S.T., Nixon, R.D.V., 2003. Imaginal exposure alone and imaginal exposure with cognitive restructuring in treatment of posttraumatic stress disorder. J. Consult. Clin. Psychol. 71, 706–712, http://dx.doi.org/10.1037/0022-006X.71.4.706. Davis, T.M., Bush, K.R., Kivlahan, D.R., Dobie, D.J., Bradley, K.A., 2003. Screening for substance abuse and psychiatric disorders among women patients in a VA Health Care System. Psychiatr. Serv. 54 (2), 214–218, http://dx.doi.org/10.1176/ appi.ps.54.2.214. Dillman, D., 2000. Mail and Telephone Surveys: The Tailored Design Method. John Wiley and Sons, New York. Fava, M., Rush, A.J., Alpert, J.E., Balasubramani, G.K., Wisniewski, S.R., Carmin, C.N., biggs, M.M., Zisook, S., Leuchter, A., Howland, R., Warden, D., Trivedi, M.H., 2008. Difference in treatment outcome in outpatients with anxious versus

440

J.F. Curry et al. / Journal of Affective Disorders 152-154 (2014) 434–440

nonanxious depression: a STARnD report. Am. J. Psychiatry 165, 342–351, http://dx. doi.org/10.1176/appi.ajp2007.06111868. First, M., Spitzer, R., Gibbon, M., Williams, J., 1994. Structured Clinical Interview for Axis I DSM-IV Disorders. Biometrics Research Department, New York. (Version 2.0. New York). Gadermann, A.M., Engel, C.C., Naifeh, J.A., Nock, M.K., Petukhova, M., Santiago, P.N., Wu, B., Zaslavsky, A.M., Kessler, R.C., 2012. Prevalence of DSM-IV major depression among U.S. Military personnel: meta-analysis and simulation. Mil. Med. 177, 47–59. Ginzburg, K., Ein-Dor, T., Solomon, Z., 2010. Comorbidity of posttraumatic stress disorder, anxiety and depression: a 20-year longitudinal study of war veterans. J. Affect. Disord. 123 (1–3), 249–257, http://dx.doi.org/10.1016/j.jad.2009.08.006. Goldzweig, C.L., Balekian, T.M., Rolon, C., Yano, E.M., Shekelle, P.G., 2006. The state of women veterans' health research: results of a systematic literature review. J. Gen. Intern. Med. 21 (3), S82–S92. Grubaugh, A.L., Monnier, J., Magruder, K.M., Knapp, R.G., Frueh, B.C., 2006. Female Veterans seeking medical care at Veterans Affairs primary care clinics: psychiatric and medical illness burden and service use. Women Health 43 (3), 41–62, http://dx.doi.org/10.1300/J013v43n03-03. Keane, T.M., Barlow, D.H., 2002. Posttraumatic stress disorder. In: Barlow, D.H. (Ed.), Anxiety and its Disorders: The Nature and Treatment of Anxiety and Panic. Guilford Press, New York, pp. 418–453. Kessler, R.C., 2003. Epidemiology of women and depression. J. Affect. Disord. 74, 5–13, http://dx.doi.org/10.1016/S0165-0327(02)00426-3. Kessler, R.C., Petukhova, M., Sampson, N.A., Zaslavsky, A.M., Wittchen, H.-U., 2012. Twelve-month and lifetime prevalence and lifetime morbid risk of anxiety and mood disorders in the United States. Int. J. Methods Psychiatr. Res. 21, 169–184, http://dx.doi.org/10.1002/mpr.1359. Lobbestael, J., Leurgans, M., Arntz, A., 2011. Inter rater reliability of the Structured Clinical Interview for DSM IV Axis I disorders (SCID I) and Axis II disorders (SCID II). Clin. Psychol. Psychother. 18, 75–79, http://dx.doi.org/10.1002/ cpp.693. Maguen, S.R., LiBosch, J.O., Marmar, C.R., Seal, K.H., 2010. Gender differences in mental health diagnoses among Iraq and Afghanistan veterans enrolled in Veterans Affairs health care. Am. J. Public Health 100, 2450–2456, http://dx.doi. org/10.2105/AJPH.2009.166165. Magruder, K.M., Frueh, B.C., Knapp, R.G., Davis, L., Hamner, M.B., Martin, R.H., Gold, P.B., Arana, G.W., 2005. Prevalence of posttraumatic stress disorder in Veterans Affairs primary care clinics. Gen. Hosp. Psychiatry 27, 167–179, http://dx.doi.org/10.1016/j. genhosppsych.2004.11.001. Maier, W., Gansicke, M., Gater, R., Rezaki, M., Tiemens, B., Urzua, R.F., 1999. Gender differences in the prevalence of depression: a survey in primary care. J. Affect. Disord. 53, 241–252, http://dx.doi.org/10.1016/S0165-0327(98)00131-1. Marcus, S.M., Young, E.A., Kerber, K.B., Kornstein, S., Farabaugh, A.H., Mitchell, J., Wisniewski, S.R., Balasubramanif, G.K., Trivedi, M.H., Rush, A.J., 2005. Gender differences in depression: findings from the STARnD study. J. Affect. Disord. 87, 141–150, http://dx.doi.org/10.1016/j.jad.2004.09.008. Mitchell, A.J., McGlinchey, J.B., Young, D., Chelminski, I., Zimmerman, M., 2009. Accuracy of specific symptoms in the diagnosis of major depressive disorder in psychiatric out-patients: data from the MIDAS project. Psychol. Med. 39, 1107–1116, http://dx.doi.org/10.1017/S0033291708004674.

Niciu, M.J., Chan, G., Gelernter, J., Arias, A.J., Douglas, K., Weiss, R., anton, R.F., Farrer, L., Cubells, J.F., Kranzler, H.R., 2009. Subtypes of major depression in substance dependence. Addiction 104 (10), 1700–1709, http://dx.doi.org/10.1111/j.13600443.2009.02672.x. Nunes, E.V., Levin, F.R., 2004. Treatment of depression in patients with alcohol or other drug dependence: a meta-analysis. JAMA 291, 1887–1896, http://dx.doi. org/10.1001/jama.291.15.1887. Pittman, J., Goldsmith, A., Lemmer, J., Kilmer, M., Baker, D., 2012. Post-traumatic stress disorder, depression, and health-related quality of life in OEF/OIF veterans. Qual. Life Res. 21 (1), 99–103, http://dx.doi.org/10.1007/s11136-0119918-3. Rogers, R., 2001. Structured Clinical Interview for DSM–IV Disorders (SCID) and other Axis I interviews. Handbook of Diagnostic and Structured Interviewing. Guilford Press, New York, New York. Rowe, M.G., Fleming, M.F., Barry, K.L., Manwell, L.B., Kropp, S., 1995. Correlates of depression in primary care. J. Fam. Pract. 41, 551–558. Sambamoorthi, U., Shen, C., Findley, P., Frayne, S., Banerjea, R., 2010. Depression treatment patterns among women veterans with cardiovascular conditions or diabetes. World Psychiatry 9, 177–182. Samet, S., Fenton, M.C., Nunes, E., Greenstein, E., Aharonovich, E., Hasin, D., 2013. Effects of independent and substance-induced major depressive disorder on remission and relapse of alcohol, cocaine and heroin dependence. Addiction 108, 115–123, http://dx.doi.org/10.1111/j.1360-0443.2012.04010.x. Seal, K.H., Metzler, T.J., Gima, K.S., Bertenthal, D., Maguen, S., Marmar, C.R., 2009. Trends and risk factors for mental health diagnoses among Iraq and Afghanistan Veterans using Department of Veterans Affairs health care, 2002–2008. Am. Public Health 99 (9), 1651–1658, http://dx.doi.org/10.2105/AJPH.2008.150284. Swendsen, J., Conway, K.P., Degenhardt, L., Glantz, M., Jin, R., Merikangas, K.R., Sampson, N., Kessler, R.C., 2010. Mental disorders as risk factors for substance use, abuse and dependence: results from the 10-year follow-up of the National Comorbidity Survey. Addiction 105, 1117–1128, http://dx.doi.org/10.1111/j.13600443.2010.02902.x. Verhagen, M., van der Meij, A., Franke, B., Vollebergh, W., de Graaf, R., Buitelaar, J., Janzing, J.G., 2008. Familiality of major depressive disorder and gender differences in comorbidity. Acta Psychiatr. Scand. 118, 130–138, http://dx.doi. org/10.1111/j.1600-0447.2008.01186.x. Vogt, D., Vaughn, R., Glickman, M.E., Schultz, M., Drainoni, M.-L., Elwy, R., Eisen, S., 2011. Gender differences in combat-related stressors and their association with postdeployment mental health in a nationally representative sample of U.S. OEF/OIF veterans. J. Abnorm. Psychol. 120, 797–806, http://dx.doi.org/10.1037/ a0023452. (10.1037/a0023452.supp (Supplemental). Wade, T.J., Cairney, J., Pevalin, D.J., 2002. Emergence of gender differences in depression during adolescence: national panel results from three countries. J. Am. Acad. Child Adolesc. Psychiatry 41, 190–198, http://dx.doi.org/10.1097/ 00004583-200202000-00013. Whitlock, E.P., Ferry, L.H., Burchette, R.J., Abbey, D., 1995. Smoking characteristics of female veterans. Addict. Behav. 20, 409–426, http://dx.doi.org/10.1016/03064603(95)00011-Z. Williams, J.B., Gibbon, M., First, M.B., Spitzer, R.L., et al., 1992. The Structured Clinical Interview for DSM-III—R (SCID): II. Multisite test-retest reliability. Arch. Gen. Psychiatry 49, 630–636, http://dx.doi.org/10.1001/archpsyc.1992.01820080038006.

Lifetime major depression and comorbid disorders among current-era women veterans.

Most research on women veterans' mental health has focused on postraumatic stress disorder (PTSD) or reactions to military sexual trauma. Although dep...
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