Prospective Examination of Early Associations ... - Wiley Online Library

Journal of Traumatic Stress February 2018, 31, 102–113

Prospective Examination of Early Associations of Iraq War Zone Deployment, Combat Severity, and Posttraumatic Stress Disorder with New Incident Medical Diagnoses Kevin Brailey,1,2 Mary Alice Mills,1,2 Brian P. Marx,3,2 Susan P. Proctor,4,5,6 Karen H. Seal,7,8 Avron Spiro III,9,10,2 Erin W. Ulloa,11,12 and Jennifer J. Vasterling1,2 1

Psychology Service, VA Boston Healthcare System, Boston, Massachusetts, USA Department of Psychiatry, Boston University School of Medicine, Boston, Massachusetts, USA 3 National Center for PTSD, VA Boston Healthcare System, Boston, Massachusetts, USA 4 Military Performance Division, U.S. Army Research Institute of Environmental Medicine, Natick, Massachusetts, USA 5 Research Service, VA Boston Healthcare System, Boston, Massachusetts, USA 6 Department of Environmental Health, Boston University School of Public Health, Boston, Massachusetts, USA 7 San Francisco VA Health Care System, San Francisco, California, USA 8 Departments of Medicine and Psychiatry, University of California San Francisco, San Francisco, California, USA 9 Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA 10 Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts, USA 11 Behavioral Health Service, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania, USA 12 Department of Psychiatry, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, USA 2

War zone deployment and posttraumatic stress disorder (PTSD) have been associated with morbidity and mortality decades later. Less is known about the associations between these variables and the early emergence of medical disorders in war zone veterans. This prospective study of 862 U.S. Army soldiers (n = 569 deployed; n = 293 nondeployed) examined: (a) associations between Iraq War deployment status (deployed vs. nondeployed) and new medical diagnoses that emerged within six months after return from Iraq among all participants; and (b) associations between combat severity and PTSD symptoms, and new postdeployment medical diagnoses that emerged within 12 months after return from Iraq within deployed participants. New medical diagnoses were abstracted from diagnostic codes associated with clinical outpatient visits recorded within the Department of Defense Standard Ambulatory Data Record database. Combat severity was measured with the Combat Experiences module of the Deployment Risk and Resilience Inventory, and postdeployment posttraumatic stress disorder symptom severity was measured using the PTSD Checklist–Civilian. Neither deployment nor combat severity was associated with new medical diagnoses. However, among deployed soldiers, more severe PTSD symptoms were associated with increased risk for a new medical disorder diagnosis; every 10-point increase in PTSD symptoms increased odds of a new diagnosis by nearly 20% (odds ratio = 1.20). Results suggest that PTSD symptoms are associated with early morbidity in Iraq War veterans.

Multiple studies with veterans of different military conflicts have documented a clear link between war zone deployment and subsequent development of physical health problems, including increased risk for self-reported circulatory, digestive, musculoskeletal, endocrine-nutritional-metabolic, nervous system, respiratory, and dermatological diseases (Boscarino, 2006; Crum-Cianflone et al., 2014; Decoufl´e, Holmgreen, Boyie, & Stroup, 1992; Elder, Shanahan, & Clipp, 1997; Hotopf et al., 2006; Ishøy et al., 1999; Jankowsky et al., 2011; Kline et al.,

Funding was provided by the U.S. Army Medical Research and Materiel Command (DAMD 17-03-0020) and Department of Veterans Affairs (VA) Clinical Sciences Research and Development. The primary funding organizations had no role in the scientific aspects of the study or the preparation of the manuscript. The manuscript underwent scientific and administrative review within the U.S. Army Research Institute of Environmental Medicine. The views expressed in this article are those of the authors and do not reflect the official policy or position of the Department of the Army or Department of Veterans Affairs. We are grateful for input provided by Drs. Laura Grande, Christopher Harte, Colleen Jackson, Lewina Lee, and Anica Pless Kaiser. Finally, we thank the soldiers for volunteering their time to participate in the study and for their military service. Correspondence concerning this article should be addressed to Kevin Brailey, VA Boston Healthcare System, 150 S. Huntington Ave. (116B), Boston, MA 02130. E-mail: [email protected]

Published 2018. This article is a U.S. Government work and is in the public domain in the USA. View this article online at wileyonlinelibrary.com DOI: 10.1002/jts.22264

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Deployment, Combat, PTSD, and Medical Diagnoses

2010; Smith, Wong, et al., 2009; Wolfe et al., 1999). Initial studies involving service members who have been deployed to Iraq and Afghanistan found cross-sectional associations between posttraumatic stress disorder (PTSD) and self-reported health problems (Hoge, Terhakopian, Castro, Messer, & Engel, 2007; Jakupcak, Luterek, Hunt, Conybeare, & McFall, 2008), along with medical diagnoses of hypertension, circulatory, digestive, nervous, musculoskeletal, and pain disorders, and signs of ill-defined disease (Andersen, Wade, Possemato, & Ouimette, 2010; Cohen, Marmar, Ren, Bertenthal, & Seal, 2009; Helmer et al., 2009). With the deployment of over 2.7 million personnel since September 2001, the importance of understanding deployment-related factors that lead to such problems has emerged as a major public health concern. War zone deployment may adversely affect health by both direct and indirect mechanisms. Deployment may directly affect the physical health of deployed troops via the inherent environmental, physical, and psychological stresses of combat severity (Crum-Cianflone et al., 2014; Jankowsky et al., 2011; O’Toole, Catts, Outram, Pierse, & Cockburn, 2009; Pizarro, Silver, & Prause, 2006; Schnurr, Spiro, & Paris, 2000; Smith, Wong, et al., 2009). Alternatively, the association between combat deployment (the stressor) and physical health outcomes may be mediated by PTSD and other stress-related psychological symptoms (Andersen et al., 2010; Boscarino, 2006; Boscarino, 2008; Cohen et al., 2009; Frayne et al., 2011; Helmer, et al., 2009; Hoge et al., 2007; Jakupcak et al., 2008; Jankowsky et al., 2011; Kline et al., 2010; Wolfe et al., 1999). Although there is empirical support for both hypotheses, common methodological features have created gaps in knowledge. Some studies examining war zone stress have not examined PTSD symptoms as a potential mediator of the association between stress and physical health problems (Elder, Shanahan, & Clipp, 1997; Ishøy et al., 1999; Pizarro, Silver, & Prause, 2006). Those studies that have examined PTSD have often focused exclusively on longer-term outcomes, measured years later (Andersen et al., 2010; Boscarino, 2006; Boscarino, 2008; Kline et al., 2010; Kubzansky, Koenen, Spiro, Vokonas, & Sparrow, 2007; O’Toole et al., 2009; Pizarro, Silver, & Prause, 2006; Schnurr, Spiro, & Paris, 2000), with the exception of Smith, Leardmann, Smith, Jacobsen, and Ryan (2009), which was a large population-based hospitalization study that indicated increased hospitalizations in the first year after deployment compared with a nondeployed sample. Further, many studies have been cross-sectional (Boscarino, 2006; Frayne et al., 2011; Hoge et al., 2007; Hotopf et al., 2006; Ishøy et al., 1999; Jakupcak et al., 2008; Kline et al., 2010; O’Toole et al., 2009; Pizarro, Silver, & Prause, 2006; Wolfe et al., 1999) or began longitudinal assessment only after return from deployment and did not take into account predeployment health (Andersen et al., 2010; Boscarino, 2008; Cohen et al., 2009; Kubzansky et al., 2007; Schnurr, Spiro, & Paris, 2000). Finally, studies that have included prospective, baseline assessment of health have relied predominantly on

subjective, self-reported symptom complaints (Boyko et al., 2010; Granado et al., 2009; Jankowsky et al., 2011; Smith, Wong et al., 2009) that are potentially vulnerable to reporting biases, or have validated self-report with only a subset of study participants (Crum-Cianflone et al., 2014; Jones et al., 2011). This study addressed gaps in knowledge by prospectively measuring short-term physical health outcomes using clinical encounter visit diagnoses in a sample of U.S Army soldiers who had either been recently deployed to Iraq or were nondeployed. Within the deployed sample, we examined risk factors specific to war zone service, including associations between physical health outcomes and both stress exposure, as indexed by self-reported combat severity, and stress-related psychological symptoms, as indexed by PTSD symptom severity. The current study had two objectives: (a) to determine whether deployed and nondeployed service members differed in documented new-onset medical conditions that emerged within six months postdeployment, and (b) to examine associations between postdeployment PTSD symptoms and new-onset medical conditions that emerged within 12 months postdeployment. We hypothesized that deployed soldiers would have higher rates of new-onset incident health conditions postdeployment, as measured by their utilization of military-mandated medical care in the measurement intervals before and after deployment, than soldiers comparable in military characteristics who did not deploy, and that, among deployed soldiers, the increase in new-onset health conditions would be explained in part by the greater severity of combat experiences and in particular by PTSD symptom severity. Consistent with prior research on the recent combat operations in Iraq and Afghanistan (Andersen et al., 2010), which found PTSD to be most strongly associated with disorders of the nervous system and musculoskeletal system, we expected that disorders of these types would be most strongly associated with PTSD symptoms. Given the high reporting rates among Iraq and Afghanistan conflict veterans of exposure to blasts and other events potentially resulting in mild traumatic brain injury (TBI), and the potential association between TBI events (e.g., being thrown from a vehicle) and certain nervous system and musculoskeletal disorders (e.g., migraine and joint disorders, respectively), we also included self-reported deployment TBI in the analyses as an independent variable.

Method Participants and Procedure To examine the effects of deployment on physical health diagnoses (Objective 1), we compared new-onset International Classification of Diseases (9th rev., clinical modification; ICD9-CM) outpatient diagnostic codes in two groups of regular active duty U.S. Army soldiers with comparable military characteristics: (1) those who had been predominantly deployed for standard (i.e., 12-month) tours to Iraq during the study period and (2) those who had not been deploy during the study

Journal of Traumatic Stress DOI 10.1002/jts. Published on behalf of the International Society for Traumatic Stress Studies.

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period. To examine the potential effects of deployment-related factors on physical health diagnoses (Objective 2), we examined associations between self-reported combat severity during deployment and postdeployment PTSD symptom severity with new onset physical health diagnoses in participants who had been deployed. The analytic sample was drawn from 1,363 regular active duty U.S. Army soldiers enrolled in the Neurocognition Deployment Health Study (NDHS). Detailed sampling, recruitment, and consent procedures for the NDHS are described elsewhere (Vasterling et al., 2006). In brief, NDHS participants were sampled at the battalion unit level, with battalions selected to capture heterogeneous deployment experiences, occupational specialties, and location assignments within the war zone. Primary assessment data were collected in person at active duty military installations by civilian examiners. Data were gathered from soldiers who served between April 2003 and June 2005. Participant deployments (12 months in duration) occurred within the period of October 2003 through December 2004. No participant had previous Iraq conflict service before the start of this study. Reporting of previous deployment (Table 1) included service in the Persian Gulf War of 1991, peacekeeping in Kosovo, and, for only a very few soldiers, brief deployment to Afghanistan prior to 2003. Deployed soldiers were assessed prior to deployment to Iraq (Time 1, between April and December 2003) and again following their return (Time 2, between January and May 2005). Nondeployed soldiers were tested over analogous timeframes. Deployed soldiers reported significant exposure to combat, even when serving in support roles (Vasterling et al., 2006). The study timeline is depicted in Figure 1. For comparisons between deployed and nondeployed soldiers (Objective 1), we included NDHS participants who were in regular active duty status for at least six months prior and subsequent to their deployment (and for comparable durations for participants who did not deploy). A 6-month interval before and after deployment reflected the maximum possible observation period common across both deployed and nondeployed participants, recognizing that many participants classified as nondeployed for this study deployed within several months following their second study assessment. Of the 1,130 soldiers who met these criteria, 1,040 (92.0%) provided written release to access electronic health data bases; six were excluded because they were deployment-ready at Time 1 but did not deploy. Of the remaining 1,034 NDHS participants, 172 were not available for assessment at Time 2, leading to a final sample of 862 soldiers (n = 569 deployed; n = 293 nondeployed). The most common reason for loss to follow-up at the second NDHS assessment was that participants were no longer with the same military units (n = 136). Other reasons included: on leave/training (n = 24), declined to participate (n = 6), and deceased (n = 3). Deployed participants for whom deployment dates were available and who completed their 12 month tour (n = 554) were assessed for PTSD symptoms an average of

60.06 (SD = 29.00; median = 43) days prior to deployment and 75.77 (SD = 30.24; median = 76) days after returning from deployment. For deployed participants, because a longer, 12-month preand postdeployment healthcare utilization period was available for most participants (n = 507), clinical encounter data from this longer span were gathered. Thus, to evaluate the potential effects of deployment factors on physical health diagnoses (Objective 2), we excluded those deployed participants who were not in regular active duty status for at least 12 months prior and subsequent to their deployment (n = 62). Table 1 depicts comparisons of the baseline sample characteristics of study participants who were included in Objective 1 (effects of deployment on physical health diagnoses) analyses (“participants”) with those not included in the analytic sample (“nonparticipants”). Participants, relative to nonparticipants, were more likely to be male, have an enlisted rank, have not had prior deployments in the 1990s and early 2000s, smoke tobacco, and endorse less severe PTSD symptoms at baseline. Sample characteristics of deployed and nondeployed participants at baseline assessment can be found in Table 2. Deployed and nondeployed participants did not differ on demographic or contextual variables with the exception that deployed partcipants were more likely to self-identify as ethnic minorities than participants who did not deploy. Deployed participants reported moderate combat severity, and 10.6% reported having been wounded or injured in combat. There were no significant differences between deployed and nondeployed participants in the likelihood of screening positive for PTSD. However, at Time 2, deployed participants reported significantly more severe PTSD symptoms than those who had not been deployed. For all participants, human subjects approvals were obtained from human subjects research review boards of the Army, Tulane University Health Sciences Center, and the Department of Veterans Affairs. All participants provided written informed consent prior to participation.

Measures Medical outcomes. Medical outcomes were identified via outpatient diagnostic codes from the Standard Ambulatory Data Record database, obtained from the Department of Defense Patient Administration Systems and Biostatistics Activity. For analyses involving both deployed and nondeployed participants (Objective 1), the primary outcome (i.e., an encounter classified as a new diagnosis of an ICD9-CM disorder in one or more of eight categories) was defined by the presence of a diagnostic code in any of the first four diagnostic code positions recorded for each clinic visit in the 6 months postdeployment, and the absence of that code in the 6 months prior to deployment (or comparable period for nondeployed participants). A diagnosis/condition/symptom was coded as present if at least one visit associated with the diagnostic code occurred during the identified health observation timeframes.


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Table 1 Demographic and Contextual Sample Characteristics at Baseline Assessment Time 2 Participants (n = 862) Variable Age (years) Ethnicity minority Women Education (years) Years in Army Enlisted rank (enlisted) Previous operational deployment Married Hours of sleep per night (past week) Alcoholic drinks consumed per week (past month) Current cigarette smoker Reported taking prescribed or over the counter medication (past 48 hr) Reporting taking prescribed psychoactive or anticonvulsant medications (past 48 hr) Reported developmental disorder Reported psychiatric disorder Reported past alcohol use disorder Reported prior head injury with loss of consciousness > 15 min Reported other neuromedical disorder PCL summary score PTSD screening case

M

SD

24.8

4.9

69 12.5 3.9

n

%

347

40.3

8.0 1.3 3.8

29.4

M

SD

24.3

4.5

12.5 3.5 844 91 396

5.9 4.8

Time 2 Nonparticipants (n = 172)

5.9 9.0

%

p

75 27

43.9 15.7

.002

165 15 78

95.9 18.5 45.6

1.4 3.4

97.9 11.1 45.9

1.3 12.3

n

1.3 13.9

410 284

47.6 32.9

70 64

40.9 37.2

16

1.9

5

2.9

116 57 38 53

13.6 6.7 4.5 6.2

20 16 9 11

11.7 9.5 5.3 6.5

24

2.8

7

4.9

24

14.0

12.7

32.1 82

.050

14.5

9.6

.026

Note. PCL = PTSD Checklist; PTSD = posttraumatic stress disorder.

For Objective 2 (examination of the potential effects of deployment-related factors on physical health diagnoses), identical definitions were used within 12-month timeframes pre- and postdeployment. We examined seven diagnostic categories: endocrine, nervous system, circulatory, respiratory, digestive, dermatological, and musculoskeletal, along with an eighth category of signs/symptoms/ill-defined conditions

(e.g., dizziness, insomnia not elsewhere classified). Specific conditions within each category are given in Appendix 1. A summary variable labeled “any medical diagnosis” was created to reflect the presence of a diagnosis in any diagnostic category excluding signs/symptoms/ill-defined conditions. Diagnostic code selection was informed by prior research examining stress-related health outcomes (Andersen et al.,

12 Month Predeployment Test 2

Test 1

6 Month Predeployment

12 Month Postdeployment 12 Month Deployment Period

6 Month Predeployment

Objective 1 – Comparison of deployed v. nondeployed participants: 6 month pre/postdeployment health data monitoring periods. Objective 2 – Examination of factors among deployed participants only: 12 month pre/postdeployment health data monitoring periods.

Figure 1. Study timeline. Journal of Traumatic Stress DOI 10.1002/jts. Published on behalf of the International Society for Traumatic Stress Studies.

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Table 2 Demographic and Contextual Sample Characteristics of Nondeployed and Deployed Participants at Time 1, and Deployment-Related Variables at Time 2 Nondeployed (n = 293) Variable Age (years) Self-reported ethnic minority Caucasian African-American Hispanic American Asian American Other Women Married Education, years Rank, enlisted Junior enlisted (E1-E4) Noncommissioned officers (E5-E9) Officers (commissioned or warrant) Current smoker Alcoholic drinks/week in past month, Hours sleep/night in past week PTSD presumptive diagnosis (strict-Hoge), Time 1 PCL summary score, Time 1 DRRI Combat Experiences Wounded or injured in combat PTSD presumptive diagnosis (strict-Hoge), Time 2 PCL summary score, Time 2

M

SD

24.95

4.95

n

Deployed (n = 569) %

M

SD

24.77

4.87

34.7 65.3 14.4 8.6 4.5 7.2 9.6 46.8 12.56

1.39

12.40

12.39

5.94

1.20

.016

2.4

1.8

13.16

13.14

43.2 56.8 15.3 13.9 3.3 10.7 7.2 45.5 98.2 74.9 23.4

49.6 8.45

12.25

5.84

1.31

29.33 18.99

32.78

13.58

ns ns ns ns

ns ns

8.8

ns ns

15.9 12.3

ns NA NA ns

12.55 10.60

10.7 29.48

p

1.28

11.0 29.67

%

97.3 74.4 22.9

43.7 8.28

n

0.001

Note. N = 862. DRRI = Deployment Risk and Resilience Inventory; PCL = PTSD Checklist; PTSD = posttraumatic stress disorder.

2010; Helmer et al., 2009; Schnurr, Spiro, & Paris, 2000) but also included conditions reflecting inadequate self-care practices (e.g., gingivitis, hemorrhoids) and nonspecific physical complaints previously described following military deployment (e.g., tinnitus, fatigue; Cook, Stegner, & Ellingson, 2010). We did not include injury-related diagnostic categories (e.g. TBI), as we were most interested in health conditions that did not directly indicate a specific physical trauma or injury. Deployment-related variables. Demographic and military information was queried via interview and written surveys at Time 1 and verified by service records. At Time 2, a version of the Combat Experiences module of the Deployment Risk and Resilience Inventory (DRRI; King, King, Vogt, Knight, & Samper, 2006) modified to solicit frequency-based responses

provided a continuous measure of combat severity. The DRRI is a modular inventory with robust psychometric properties that was developed after the Gulf War to capture events common to contemporary war-zone deployment. It has demonstrated good discrimination between low- and high-combat groups in validation studies (Cronbach’s α = .85; King et al., 2006). At both Times 1 and 2, PTSD symptom severity was assessed using the PTSD Checklist, Civilian version (PCL-C; Weathers, Huska, & Keane, 1991; Ruggiero, Del Ben, Scotti, & Rabalais, 2003), a 17-item checklist that queries for the frequency of each of the Diagnostic and Statistical Manual for Mental Disorders (4th ed.; DSM-IV; American Psychiatric Association [APA], 1994) PTSD diagnostic symptoms (Cronbach’s α = .94; Ruggiero et al., 2003). Presumptive PTSD diagnosis was derived from the PCL-C using methods described by Hoge and colleagues (2007). Incidence of TBI was assessed with a


107


constructed structured interview using methods summarized elsewhere (Vasterling et al., 2012). Data Analysis All data analyses were conducted using SPSS version 20. Time 2 participants and nonparticipants (e.g., those who did not complete a Time 2 assessment, other exclusions) were compared on demographic, military, behavioral and psychological variables using t tests for continuous variables and chi-square tests for categorical variables. Within participants, there was no missing data for the variables reported in this study. Deployed and nondeployed participants were compared on the same variables. We used logistic regression to examine the effects of deployment on health outcomes: any new medical problem (including signs and symptoms) and any specific new medical diagnosis from the eight a priori diagnostic categories. Multivariate logistic regression models were repeated using each individual disease category as an outcome. To address Objective 2 (i.e., effects of combat severity and PTSD symptom severity on health diagnosis outcomes), we used multiple logistic regression with simultaneous entry of all covariates. To examine the association between health outcomes and clinically meaningful increments in PTSD symptom severity, we also repeated the model using 10-point increments on the PCL-C as the unit of prediction to examine PCL-C associations with each outcome (Street, Gradus, Vogt, Giasson, & Resick, 2013). Logistic regression models in which medical outcomes were predicted by either deployment status or, within deployed subjects, by PTSD symptoms and/or combat severity, were adjusted for age, sex, race, education level, and self-reported deployment TBI.

Results In both unadjusted and adjusted analyses, deployment was not significantly associated with a new diagnosis in any specific category of physical illness, odds ratios [ORs] = 0.43 to 1.73, all ps = .061 to .879; or with the combined category of any new medical diagnosis, OR = 0.75, 95% CI [0.54-1.04, p = .080 (Table 3). As shown in Table 4, combat severity was not significantly associated with new medical diagnoses in adjusted or unadjusted models, either for any new diagnosis or for any specific category of disorder. However, after adjustment for age, sex, race, education, deployment TBI, and combat severity, each 1point PCL score increase was associated with a 1.7% increase in the odds of a new medical diagnosis, or an 18.4% increase in the odds of a new medical diagnosis per 10-point PCL score increase. The majority of risk for new medical diagnosis associated with PTSD symptoms reflected new diagnoses of nervous system and musculoskeletal disorders; an increase of 10 points on the PCL was associated with a 45.2% increase in the odds of a new nervous system diagnosis, OR = 1.45, 95% CI [1.07, 1.97], p = .017; and a 19.5% increase in the odds of a new

musculoskeletal diagnosis, OR = 1.20, 95% CI [1.02, 1.40], p = .027. Appendix 1 lists the specific diagnoses subsumed within each diagnostic category. Post hoc inspection of the specific outpatient visit ICD-9 codes included in these analyses indicates that the three most common diagnoses for the nervous system category were “other disorders of ear” (n = 9, 1.8%), “visual disturbances” (n = 6, 1.2%), and “migraines” (n = 3, 0.6%), whereas the three most common musculoskeletal diagnoses were painassociated disorders: “other and unspecified disorders of joint” (n = 46, 9.2%), “other and unspecified disorders of back” (n = 33, 6.6%), and “other disorders of soft tissues” (n = 27, 5.4%). Power features of logistic regression are such that the required sample size to establish a significant result increases as base rate declines and, naturally, as effect size decreases. An a priori power analysis (i.e., computed for a required sample size specifying alpha, power, R2 among covariates, and effect size) indicated that for any medical diagnosis (.259 overall base rate), using a one-tailed test, a small effect size (OR = 1.3), Cronbach’s alpha value of .05, power of .8, and the R2 found among covariates (.016), the required sample size is 485, well below the sample size we used in our analysis. Power was also very good for many of the specific diagnostic categories we tested. Thus, power was acceptable for higher frequency disorders even with small effect sizes (i.e., small odds ratios), but decreased for lower-occurrence issues. So, for circulatory problems, which was the outcome with the lowest base rate (.013), the equivalent required sample size for a small effect size was 6,899. Discussion In this study of active duty Army soldiers, we examined prospective associations between Iraq war zone deployment (vs. nondeployment) with new-onset medical diagnoses in the 6-month interval following deployment (Objective 1), and associations between combat severity and PTSD with new medical diagnoses in the 12 months following deployment (Objective 2). We found no significant associations between deployment or combat severity and new-onset medical diagnoses; however, postdeployment PTSD symptom severity was associated with any new medical diagnosis, and with new-onset nervous system and musculoskeletal disorders. The clinical significance of these associations became evident when we considered clinically meaningful (i.e., 10-point) increments in PTSD symptom severity. The findings regarding the increased risk of medical diagnoses as a function of PTSD symptom severity are noteworthy for several reasons. First, the outcomes were diagnoses rendered by a medical professional, rather than self-reported somatic symptoms or conditions. As such, the extent to which subjective interpretations or inaccurate reporting might have accounted for associations between PTSD symptom severity and medical is attenuated. Secondly, the sample consisted of fairly young, otherwise healthy individuals (mean age = 24 years)


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Table 3 Unadjusted Incidence and Adjusted Odds of Newly Reported Diagnoses, 6-Months Postdeployment, by Deployment Status Unadjusted Incidence

Medical Diagnosis Any medical diagnosis Endocrine Nervous System Circulatory Respiratory Digestive Dermatological Musculoskeletal Signs/symptoms

Deployment Status

Nondeployed (n = 293) (%)

Deployed (n = 569) (%)

Adjusteda OR

29.4 1.7 3.8 1.4 2.4 2.7 3.8 19.5 6.8

24.1 2.6 1.8 1.2 3.5 2.8 3.2 14.8 10.7

0.75 1.73 0.43 0.89 1.54 0.94 0.88 0.72 1.67

95% CI [0.54, 1.04] [0.61, 4.85] [0.18, 1.04] [0.26, 3.11] [0.64, 3.72] [0.39, 2.24] [0.40, 1.94] [0.49, 1.06] [0.97, 2.85]

Note. OR = odds ratio. a Data are adjusted for age at Time 2, sex, race (white vs. non-white), and education at Time 2.

who had recently returned from deployment, which suggests that increased risk for medical diagnoses can develop rapidly. The lack of significant associations between deployment and new diagnoses stands in contrast to some previous research that found associations between deployment, self-reported health problems and functional status (Ishøy et al., 1999; Kline, et al., 2010). The discrepancy between our findings and those of previous studies may reflect the fact that we examined cliniciandiagnosed medical disorders that were rendered at clinical encounter visits, which presumably yield a more comprehensive and objective evaluation. Also, in this study, analyses that examined medical outcomes as a function of deployment only captured those diagnoses that developed within the six months following deployment, a notably shorter time period than those utilized in prior research. Our findings, however, are consistent with other studies that found that stress-related psychopathology (as a consequence of deployment) is more strongly associated with morbidity than is deployment more broadly (Boyko et al., 2010; CrumCianflone et al., 2014; Granado et al., 2009; Jankowsky et al., 2011; Schnurr, Spiro, & Paris, 2000; Smith et al., 2008; Smith, Wingard, et al., 2009; Wolfe et al., 1999). Our results are also consistent with prior research that indicated that PTSD diagnosis was cross-sectionally associated with a near doubling of risk for nervous system and musculoskeletal disorders after an average of 17.3 months from the initial contact young veterans of recent Iraq and Afghanistan military operations made with the VA medical system (Andersen et al., 2013). Indeed, for a 10-point increase in PTSD symptoms, we found increased odds of 45% and 20% for nervous system and musculoskeletal diagnoses, respectively. Mechanisms for the association between PTSD and risk for nervous system disorders are well documented. Posttraumatic stress disorder is known to disrupt central nervous system

functioning, as reflected by abnormalities in hormonal and other neuroregulatory factors such as catecholaminergic dysregulation, alterations to hypothalamic-pituitary-adrenal (HPA) axis functioning, and other neurohormonal abnormalities (Pitman et al., 2012). Mechanisms by which PTSD might increase the risk for musculoskeletal disorders are less well understood, but include a variety of models that focus on the well-documented connection between PTSD and chronic pain (Seal et al., 2012), shared presence of avoidance coping and attentional biases that could exacerbate and maintain both disorders (Otis, Keane, & Kerns, 2003) and shared neurobiological and neuroanatomical features (Scioli-Salter et al., 2015). This study was the first to prospectively assess potential short-term health effects of deployment, combat severity, and PTSD simultaneously in a sizable sample using clinician encounter visit diagnoses of multiple categories of medical disorders. Despite significant methodological strengths, the study should be interpreted in light of its limitations. We used a selfreport inventory to assess PTSD symptom severity. However, the use of PTSD screening instruments has been widely used in the research of PTSD-related health outcomes (Edmondson et al., 2012) and the PCL-C was developed specifically as a continuous measure, which allowed us to examine PTSD symptom severity, rather than PTSD diagnosis alone. Other than TBI, we did not adjust our analyses for physical injuries, which may have attenuated the association of PTSD to new-onset disorder. Our focus on PTSD also does not eliminate possible associations between other mental health disorders, such as depression, and new-onset medical diagnoses. However, given the high comorbidity between depression and PTSD in veterans and significant symptom overlap between the two, and the complexities involved in attempting to differentiate between distinct etiologies for similar symptoms, the relative contribution of depression and PTSD to outcomes would be difficult to


41.0 6.3 4.0 4.0 5.7 6.1 5.9 25.7 20.8

1.00 1.00 1.02 0.98 1.01 1.00 0.99 1.01 1.02

AOR [0.99, 1.02] [0.97, 1.03] [0.97, 1.06] [0.93, 1.03] [0.98, 1.05] [0.97, 1.04] [0.96, 1.03] [0.99, 1.03] [1.00, 1.04]

95% CI

95% CI [1.00, 1.03] [0.99, 1.04] [1.01, 1.07] [0.96, 1.03] [0.99, 1.04] [0.98, 1.03] [0.98, 1.03] [1.00, 1.03] [1.00, 1.03]

AOR 1.02* 1.01 1.04* 0.99 1.02 1.00 1.00 1.02* 1.01

Time 2 PCLa

1.02* 1.01 1.04* 1.00 1.02 1.00 1.01 1.02* 1.01

AOR

[1.00, 1.03] [0.98, 1.04] [1.00, 1.07 [0.96, 1.04] [0.99, 1.04] [0.98, 1.03] [0.98, 1.04] [1.00, 1.03] [0.99, 1.02]

95% CI

Time 2 PCLb

1.18* 1.14 1.45* 1.01 1.16 1.02 1.04 1.20* 1.08

AOR

[1.03, 1.37] [0.86, 1.49] [1.07, 1.97] [0.67, 1.52] [0.89, 1.52] [0.77, 1.34] [0.78, 1.40] [1.02, 1.40] [0.92, 1.28]

95% CI

Time 2 PCL OR, per 10 pointsb,c

Note. N = 507. OR = odds ratio; AOR = adjusted odds ratio; PCL = Posttraumatic Stress Disorder (PTSD) Checklist. a Adjusted for age at Time 2, sex, race (White vs. non-White), mild traumatic brain injury (mTBI), and education at Time 2. b Adjusted for age at Time 2, sex, race (White vs. non-White), mTBI, education at time 2, and combat severity. c Estimates correspond to a 10-point increase on the PCL. * p < .05

Any medical diagnosis Endocrine Nervous system Circulatory Respiratory Digestive Dermatological Musculoskeletal Signs and symptoms

Medical Diagnosis

Unadjusted incidence (%)

Combat Experiencesa

Table 4 Unadjusted Incidence and Adjusted Odds of New diagnoses, 12 Months Postdeployment, by Combat Severity and Posttraumatic Stress Symptoms among Deployed Participants at Postdeployment Deployment, Combat, PTSD, and Medical Diagnoses

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determine. A delayed elective care effect, as described by Smith, Leardmann, et al. (2009), could also be a potential influence on our findings. Soldiers who were awaiting deployment may have decided to postpone elective medical procedures, instead waiting until they returned home from deployment to seek care. While this is a possible influence, we do not see any pattern where soldiers who eventually exhibited higher levels of PTSD symptoms would have been more prone to delay beneficial, predeployment elective medical procedures than deployed soldiers as a whole. Other possible limitations include uncontrolled aspects of the study: the possibility that participant dropout, which was primarily due to transfer to another unit and could not be modelled with propensity score matching procedures, might have been due to stress-related symptoms; and the lack of external validation for the occurrence and timing of reported stressors. Finally, as indicated earlier, the required sample size needed to find a significant difference increases as the base rate for a disorder declines. Thus, power was good for higher frequency disorders even with small effect sizes (i.e., small odds ratios), but decreased for lower occurrence issues. We therefore cannot exclude the possibility that deployment-related effects exist for a combination of small effect sizes within overall low-frequency disorders, or for other ICD9-CM categories we did not measure. This underpowering, while a limitation, shows that that a statistically significant difference would be of a relatively small impact on overall group differences in health outcomes. Finally, within this context, to avoid potential overcorrection and Type II error, we did not control for multiple comparisons, leading to the possibility of Type I error. In conclusion, using prospective data, we found an association between PTSD and new-onset diagnoses that occurred remarkably soon after deployment in a relatively young cohort of active duty service members. The increased risk for new onset medical diagnoses, particularly of nervous system and musculoskeletal disorders (problems that often become chronic), highlights that, in addition to being important for war zone veterans’ mental well-being, PTSD screening may also help identify individuals at risk for serious and costly medical disorders. War zone veterans with elevated PTSD symptoms should be carefully examined for medical comorbidities to facilitate early intervention, and future research should examine whether PTSD treatment could offset both short and long-term postdeployment medical risk. References Andersen, J., Wade, M., Possemato, K., & Ouimette, P. (2010). Association between posttraumatic stress disorder and primary care provider-diagnosed disease among Iraq and Afghanistan veterans. Psychosomatic Medicine, 72, 498–504. https://doi.org/10.1097/PSY.0b013e3181d969a1 Boscarino, J. A. (2006). Posttraumatic stress disorder and mortality among US Army veterans 30 years after military service. Annals of Epidemiology, 16, 248–256. https://doi.org/10.1016/j.annepidem.2005.03.009 Boscarino, J. A. (2008). A prospective study of PTSD and early-age heart disease mortality among Vietnam veterans: implications for surveil-

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Appendix 1 Diagnoses included in each diagnostic category

Diagnoses

Diagnoses Any medical condition

All below

Medical diagnosis Endocrine

All except signs and symptoms Diabetes mellitus

Testicular dysfunction Disorders of lipoid metabolism Disorders of fluid electrolyte and acid-base balance (predominantly hypovolemia) Overweight, obesity and other hyperalimentation Nervous System Migraine Facial nerve disorders Nerve root and plexus disorders Visual disturbances Other disorders of ear Circulatory

Respiratory

Digestive

Essential and secondary hypertension Other acute and subacute forms of ischemic heart disease Unspecified disease of pericardium Cardiac dysrhythmias Ill-defined descriptions and complications of heart disease Atherosclerosis Other peripheral vascular disease Hemorrhoids Chronic pharyngitis and nasopharyngitis Chronic sinusitis Chronic disease of tonsils and adenoids Peritonsillar abscess Allergic rhinitis Other diseases of upper respiratory tract Pneumonia (all causes) Influenza Bronchitis, all types Asthma Pleurisy Pneumothorax Other diseases of respiratory system Gingival and periodontal diseases Dentofacial anomalies including malocclusion (includes TMJ) Diseases of esophagus Gastritis and duodenitis Disorders of function of stomach

Appendicitis unqualified Hernia Regional enteritis Ulcerative enterocolitis Other and unspecified noninfectious gastroenteritis and colitis Intestinal obstruction w/o mention of hernia Functional digestive disorders not elsewhere classified Other disorders of intestine Diseases of pancreas Gastrointestinal hemorrhage Dermatological Carbuncle and furuncle Cellulitis and abscess of finger and toe Other cellulitis and abscess Impetigo Pilonidal cyst Other local infections of skin and subcutaneous tissue Erythematosquamous dermatosis Atopic dermatitis and related conditions Contact dermatitis and other eczema Dermatitis due to substances taken internally Pruritus and related conditions Diseases of sebaceous glands Chronic ulcer of skin Urticaria (hives) Other disorders of skin and subcutaneous tissue Musculoskeletal Diffuse diseases of connective tissue Osteoarthrosis and allied disorders Other and unspecified arthropathies Internal derangement of knee Other derangement of joint Other and unspecified disorders of joint Ankylosing spondylitis and other inflammatory spondylopathies Spondylosis and allied disorders Intervertebral disc disorders Other disorders of cervical region Other and unspecified disorders of back Peripheral enthesopathies and allied syndromes


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Diagnoses Other disorders of synovium tendon and bursa Disorders of muscle ligament and fascia Other disorders of soft tissues Other disorders of bone and cartilage Nonallopathic lesions not elsewhere classified Signs/symptoms Other alterations of consciousness Syncope and collapse Other convulsions Dizziness and giddiness Insomnia NEC Hypersomnia Unspecified sleep apnea Pyrexia of unknown origin Malaise and fatigue NEC Memory loss Other general symptoms Abnormality of gait Disturbance of skin sensation Rash and other nonspecific skin eruptions NEC Flushing Headache Throat pain Voice disturbance, NEC Tachycardia Functional and undiagnosed cardiac murmurs

Diagnoses Enlargement lymph nodes Shortness of breath Other dyspnea and respiratory abnormality Cough Chest pain NEC/NOS Nausea, vomiting, both Heartburn Dysphagia Diarrhea Other symptoms involving digestive system Renal colic Dysuria Urinary incontinence Urinary frequency Urethral discharge Abdominal pain, all sites Other nonspecific abnormal serum enzymes Other nonspecific findings on examination of blood Proteinuria Abnormal finding skull, head Abnormal finding, biliary tract Abnormal finding, musculoskeletal system Abnormal finding, body structure NEC High blood pressure without hypertension Abnormal clinical findings, NEC Debility, NOS Ill-defined conditions NEC Other and unknown causes of morbidity and mortality, not PGW syndrome
