Health-related Quality of Life in Gulf War Era Military Personnel

Margaret D. Voelker1, Kenneth G. Saag2, David A. Schwartz3, Elizabeth Chrischilles4, William R. Clarke5, Robert F. Woolson5 and Bradley N. Doebbeling1,4,6

1 Department of Internal Medicine, The University of Iowa College of Medicine, Iowa City, IA.
2 Department of Medicine, The University of Alabama, Birmingham, Birmingham, AL.
3 Pulmonary and Critical Care Medicine, Duke University Medical Center, Durham, NC.
4 Department of Epidemiology, The University of Iowa College of Public Health, Iowa City, IA.
5 Department of Biostatistics, The University of Iowa College of Public Health, Iowa City, IA.
6 Veterans' Affairs Medical Center, Iowa City, IA.


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The Gulf War's impact on veterans' health-related quality of life (HRQL) remains unclear. The authors examined the HRQL of military personnel deployed to the Gulf War Theater compared with those not deployed. In 1995–1996, a structured, population-based telephone survey was conducted 5 years postconflict among a cohort originally from Iowa on active duty during the conflict. The sample included 4,886 eligible subjects stratified by deployment and military status and proportionately distributed within five substrata. The Medical Outcome Study Short Form-36 (SF-36) assessed HRQL, and multivariable linear regression identified pre- and perideployment risk factors. A total of 3,695 respondents (76%) participated. Nondeployed participants reported excellent health more often than deployed participants (31% vs. 21%, p < 0.01). SF-36 scores for deployed participants were poorer than those for nondeployed controls across all health domains. Modifiable factors such as smoking and military preparedness, and other factors such as predeployment physical and mental health morbidity, were independent risk factors for poorer HRQL after deployment. Deployed veterans reported slightly poorer HRQL even after the authors adjusted for other risk factors. Further investigation of factors influencing postdeployment HRQL is needed. Routine collection of health information by using standardized instruments pre- and perideployment should be implemented.

health status; health surveys; military personnel; models, statistical; Persian Gulf syndrome; quality of life; risk factors

Abbreviations: HRQL, health-related quality of life; MCS, mental component summary; PCS, physical component summary; SE, standard error; SF-36, Medical Outcome Study Short Form 36


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Approximately 700,000 US military personnel were deployed during the Gulf War conflict. Although the air and ground war lasted less than 45 days, a large international military presence was in the region from August 1990 through July 1991. Military personnel encountered a wide variety of potentially adverse exposures during that time as well as the threat of biologic and chemical warfare.

When Gulf War troops returned home, concern mounted that some health problems experienced by veterans and their spouses and children were a result of exposures encountered in the Persian Gulf (1Go). Despite multiple investigations (2GoGoGoGoGoGo–8Go) and evidential review by scientific panels (1Go, 9GoGoGo–12Go), few clear clinical or physiologic consequences of deployment have been identified or etiologic explanations for illness confirmed. However, epidemiologic studies have consistently shown increased symptomatology among those deployed (13Go, 14Go), and the impact of the Gulf War on veterans' health-related quality of life (HRQL) remains unclear.

The use of HRQL measures in medical research has grown in the past decade (15GoGo–17Go). Theoretical models are useful in defining health dimensions and in identifying potential contributors to HRQL (18Go). Wilson and Cleary specified a hierarchic pathway of health outcomes leading from biologic and symptom variables to functional status and overall quality of life (15Go); a variety of factors including individual and environmental characteristics were identified as influencing health outcomes. Similarly, Aday and Anderson classified predisposing, enabling, and need factors as influencing health services utilization (19Go). Again, medical as well as nonmedical factors have been identified as contributing to health outcomes (20Go).

Current medical illness is an influential contributor to HRQL (21GoGo–23Go), explaining 12–24 percent of the variance (24Go). However, additional cofactors such as sociodemographic, psychological, and treatment characteristics as well as illness duration and severity must be considered (25Go). Collectively, available factors have explained up to 40 percent of the variance in HRQL scores (26Go).

The Iowa Gulf War Study was initiated to determine the prevalence of symptoms and illnesses 5 years postconflict among military personnel deployed to the Gulf War Theater (subsequently referred to as deployed) compared with active-duty, but not Gulf War-deployed (referred to as nondeployed) controls. We reported previously that Medical Outcome Study Short Form 36 (SF-36) scores were poorer among Gulf War-deployed veterans compared with nondeployed controls (13Go). We also reported that participants meeting the criteria for multiple chemical sensitivity syndrome reported impaired HRQL (27Go). The objective of this analysis was to further characterize the HRQL of military personnel, comparing deployed with nondeployed, and to identify potential pre- and perideployment risk factors for poorer HRQL.


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Study design, sample, and survey protocol
The Iowa Gulf War Study was conducted as a population-based epidemiologic study that combined the methodology of cohort and cross-sectional designs. A cohort of 29,010 military personnel was defined by using records from the Defense Manpower Data Center (Monterey, California). Eligibility criteria for inclusion in the sample were 1) active-duty or activated National Guard or Reserve status between August 2, 1990, and July 31, 1991, and 2) the state of Iowa as the home of record at enlistment.

A stratified random sample was drawn equally from four domains based on deployment to the Gulf War Theater ("deployed" vs. "nondeployed") and military status (regular military vs. National Guard or Reserve). The survey design was further stratified, with proportional allocation and oversampling of small strata, by service branch (Army, Air Force, Marines, or Navy/Coast Guard), rank (enlisted or officer), gender, race (White or Black/Other), and age in years (<=25 or >25).

A total of 4,886 eligible subjects were randomly selected and were surveyed to assess the prevalence of health problems and exposures. Interviews were conducted from September 1995 through May 1996, approximately 5 years after the conflict. Trained personnel administered the study survey via two structured telephone interviews. An introductory interview obtained subject consent and demographic information (mean length, 10 minutes). The health and exposure assessments were conducted during the main interview (mean length, 60 minutes).

Study procedures and instruments were approved by the institutional review board, and a Public Health Service Certificate of Confidentiality was obtained. In addition, reliability interviews were conducted with a random subsample of participants to assess test-retest reliability. Proxy interviews were also conducted when warranted. Further details regarding the survey methods and descriptive results are reported elsewhere (13Go, 28Go).

Study instruments
The structured interview was developed to assess a broad array of health concerns. Emphasis was placed on using standardized and validated questions or instruments. Investigator-derived questions were also used based on peer-reviewed data, interviews with Department of Veterans Affairs Gulf War Registry participants, pilot studies, and input from public and scientific advisory committees. Participants were asked about potential risk factors for poor health, such as sociodemographic and behavioral factors and current and predeployment medical and psychiatric health history. Military preparedness was characterized by using six items that asked how prepared or trained participants were in August 1990 to do their job. The number of positive responses indicated their level of preparedness, as follows: 0–3, least prepared; 4–5, moderately prepared, 6, most prepared.

The SF-36, a widely used general-health-profile questionnaire with established reliability and validity, was used to assess HRQL (29Go). The SF-36 has demonstrated sensitivity to health differences in the general population and in patients with chronic diseases (30Go). Questions are allocated to the following eight scales: 1) limitations in physical activities because of health (physical functioning), 2) limitations in social activities because of physical or emotional problems (social functioning), 3) limitations in role activities because of physical health problems (role-physical), 4) bodily pain (bodily pain), 5) general mental health (mental health), 6) limitations in role activities because of emotional problems (role-emotional), 7) vitality (vitality), and 8) general health perceptions (general health). Two SF-36 summary scales, the physical component summary (PCS) score and the mental component summary (MCS) score, have been identified and account for more than 80 percent of the variance in the subscales (31Go). The PCS score is a single measure of physical health derived primarily from the physical functioning, role-physical, bodily pain, and general health subscales. The MCS score is a single measure of mental health derived primarily from the mental, role-emotional, social functioning, and vitality subscales. Scoring was performed according to recommended guidelines and ranged from 0 to 100; lower scores reflect poorer health (32Go).

Analytical methods
The statistical program SUDAAN (33Go) was used to account for the complex sample design. Standard errors were calculated according to standard techniques for estimation under stratified random sampling without replacement (34Go). Means and standard errors were reported for continuous variables. Tests of association were calculated by using the SUDAAN linear regression procedure. Coefficients of the independent variables provided estimates of the adjusted mean differences in outcome. Ninety-five percent confidence intervals for these coefficients tested the hypotheses of no mean difference. The alpha value was set at 0.05, and all p values were two tailed.

Cronbach's alpha assessed internal consistency of the SF-36 scales (35Go). Test-retest agreement was assessed by using the weighted kappa statistic (36Go). Construct validity, or whether measures relate to other variables as expected, was evaluated by hypothesizing and then identifying the relations between various SF-36 scales and specific current medical conditions using t tests (37Go).

The clinical significance of observed differences in HRQL across groups was evaluated by comparison with values published from other study samples and by evaluating effect size. The effect size was calculated as the difference between mean scores for nondeployed versus deployed participants divided by the subscale's standard deviation for the general US population (32Go).

To control for potential confounders in the relation between deployment and HRQL and to identify potential risk factors, multivariate linear regression methods were used (38Go). Modeling strategies outlined by Harrell et al. were adopted (39Go). Independent variables were organized into theoretically related groups as follows: sociodemographic and behavioral factors, predeployment medical conditions, mental health history, and exposures. Dependent variables were the SF-36 PCS and MCS scores, each modeled independently.

The association of potential risk factors with each summary measure was evaluated. Among those factors with univariate p values of 0.25 or less, stepwise regression identified independent risk factors for physical and mental health. The stepwise procedure was performed by using SAS software, version 6.12 (40Go). Initial selection was conducted within each variable group because of the potential advantages over single-variable selection methods (38Go). All variables retained after the initial selection process were then considered in a final stepwise procedure, conducted independently for the PCS and MCS scores. Final model parameter estimates and standard errors were obtained by using SUDAAN software (33Go). The R2 statistic was used to estimate each model's "goodness-of-fit."


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Overall, 3,695 (76 percent) of the 4,886 eligible subjects (91 percent of those located) participated in the study. Participant characteristics are presented in table 1. Most subjects were male, 25 years of age or less at the time of the Gulf War, married, and White. As expected, most military personnel were enlisted, and the Army was the largest service branch represented.


View this table:
[in this window]
[in a new window]
 
TABLE 1. Characteristics of study participants by deployment status, Iowa Gulf War Study, September 1995–May 1996

 
Reliability and validity of outcome measures
Internal consistency (Cronbach's alpha) ranged from 0.81 to 0.90 for the SF-36 subscales; there were no meaningful differences across deployment status. Excellent test-retest agreement (90–97 percent), with weighted kappa statistics from 0.39 to 0.79, was observed.

We predicted that certain medical conditions would be inversely associated with specific subscales, while others would not. For example, persons reporting arthritis were predicted to have low bodily pain scores, whereas low mental health scores were predicted for those with depressive symptomatology. Mean SF-36 subscale and summary scores varied as hypothesized, supporting the construct validity (41Go). Participants reporting current physical or mental health disorders also had significantly lower SF-36 scores than those without the specific disorder (t test p < 0.001).

Figure 1 illustrates the distribution of the PCS (deployed mean = 51.4, standard error (SE), 0.2 and nondeployed mean = 53.1, SE, 0.2) and MCS (deployed mean = 51.3, SE, 0.2 and nondeployed mean = 53.4, SE, 0.2) scores by deployment status. Regardless of deployment status, health states ranged from dysfunction to positive well-being, with a slight skew toward poorer health. Deployed veterans tended to have lower values than nondeployed controls.



View larger version (15K):
[in this window]
[in a new window]
 
FIGURE 1. Distribution of Medical Outcome Study Short Form 36 component summary scores among study participants approximately 5 years after the Gulf War, by deployment status, Iowa Gulf War Study, September 1995–May 1996. GWT, Gulf War Theater.

 
HRQL by deployment status
Nondeployed participants, more often than deployed veterans, self-rated their health as excellent as opposed to very good, good, fair, or poor (31 vs. 21 percent, p < 0.01). Similarly, deployed veterans compared with those not deployed more frequently reported their health as good, fair, or poor.

Each mean SF-36 subscale and summary score, adjusted for the stratification variables (figure 2), was significantly lower for deployed veterans compared with nondeployed controls. The unadjusted standardized differences, or effect sizes, across deployment status were as follows: physical functioning, 0.07; role-physical, 0.13; bodily pain, 0.24; general health, 0.32; vitality, 0.34; social functioning, 0.12; role-emotional, 0.11; mental health, 0.21; PCS score, 0.17; and MCS score, 0.20. General health and vitality showed the largest differences, whereas physical and emotional functioning and role were least affected by deployment. An effect size of 0.20 is considered small, 0.50 is considered moderate, and 0.80 is considered large (42Go).



View larger version (32K):
[in this window]
[in a new window]
 
FIGURE 2. Weighted mean Medical Outcome Study Short Form 36 (SF-36) scores for Gulf War Theater (GWT)-deployed versus nondeployed study participants approximately 5 years after the Gulf War and US population (Pop) normative values for particular age groups, Iowa Gulf War Study, September 1995–May 1996. PF, physical functioning; RP, role-physical; BP, bodily pain; GH, general health; VT, vitality; SF, social functioning; RE, role-emotional; MH, mental health; MCS, mental component summary; PCS, physical component summary. *, p < 0.01 for the weighted mean difference between deployed versus nondeployed participants, after adjustment for all stratification variables (age, gender, race, military rank, military branch, and military status); +, MCS and PCS scores were standardized to reflect a general population mean of 50 and a standard deviation of 10.

 
Nondeployed participants reported the same or slightly higher (better health) mean scores than the normative values for the general US population (31Go, 32Go). However, the lower mean scores of deployed veterans were below national population norms for all but the social functioning, role-emotional, and mental health subscales and the MCS score.

HRQL correlates and multivariate modeling
Linear regression results are shown in table 2. Each variable's univariate association with the summary score (PCS and MCS) is shown, along with the mean score for the referent group. Deployment to the Persian Gulf was associated with a 1.7 (SE, 0.3)-point lower mean PCS score and a 2.0 (SE, 0.3)-point lower mean MCS score.


View this table:
[in this window]
[in a new window]
 
TABLE 2. Univariate health-related quality of life risk factor coefficients obtained from linear regression models of the Medical Outcome Study Short Form 36 physical and mental component summary scores, Iowa Gulf War Study, September 1995–May 1996

 
Table 2 also shows the adjusted coefficients for those variables independently associated with the outcome. To be able to evaluate the potential impact of deployment on health status, potential correlates of HRQL were required to temporally precede the Gulf War conflict. Specific health conditions that might exclude a person from military service might have developed after enlistment or might not have been reported to the military. Multivariate modeling suggested several independent risk factors for poorer HRQL. After adjustment for these factors, deployment remained associated with lower PCS (mean = –2.08, SE, 0.31) and MCS (mean = –1.91, SE, 0.31) scores.

Significant risk factors for a poorer PCS score included deployment, the Army branch of the military (vs. other services), unemployment, being married, lower military preparedness, cigarette smoking, prior mental health care, previous jail time, and several specific pre–Gulf War medical conditions (hypertension, migraines, asthma, chronic sinusitis, chronic ear infection, ulcer disease, gastritis, colitis, arthritis/rheumatism, fibromyalgia, and lumbago). This model accounted for 19 percent of the common variance.

Significant risk factors for a poorer MCS score included deployment, non-White race, the Army branch of the military (vs. other services), divorce, shorter active-duty duration, cigarette smoking, prior mental health care, and several pre–Gulf War medical conditions (seizures/convulsions, asthma, enteritis, kidney disease, arthritis/rheumatism, post-traumatic stress disorder, and depression). This model accounted for 22 percent of the common variance.


    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Gulf War-deployed veterans reported slightly poorer health status and HRQL than comparable nondeployed military controls 5 years postconflict. The greatest impact was on general health and vitality, although a broad spectrum of health domains was affected. After adjusting for sociodemographic characteristics, behavioral factors, predeployment medical conditions, and mental health history, we found that deployment remained significantly associated with poorer mental and physical health. However, most of the SF-36 score variability remained unexplained, indicating that important risk factors and potential confounders have yet to be identified.

Potentially modifiable factors such as smoking and military preparedness, and other nonmodifiable factors such as predeployment medical and mental health comorbidity, marital status, race, and service branch, were identified as risk factors for worse postdeployment HRQL. The identified variables may be important predisposing, precipitating, perpetuating, or prognostic factors and should be considered in health protection and promotion efforts (43Go).

Theoretical models provided a framework to examine contributors to and potential confounders in the relation between deployment and HRQL (15Go, 44Go). Health status potentially resulting from deployment (postdeployment variables) was not included in the multivariate models. For example, considering health conditions present at the time of the survey would have increased the model variance explained but may be a consequence of deployment. In cross-sectional data, it is difficult to determine whether current health conditions are independent causes or confound the relation with altered HRQL. These data demonstrate the need for routine general health status assessments using standardized instruments prior to and during future deployments.

The health disparity associated with deployment changed very little after we adjusted for other factors. SF-36 PCS and MCS scores remained approximately two points lower for deployed compared with nondeployed military personnel. These summary measures are scored to have a mean of 50 and a standard deviation of 10 in the general US population. A difference of one point in the PCS score is roughly equivalent to the annual average decline in the summary score for people aged 65 years or more (31Go) and has been associated with increased health service utilization (45Go).

The unadjusted mean difference across deployment status on the eight subscales ranged from 1.7 to 7.1. These differences, while statistically significant, are relatively small clinically, whereas a 10-point difference is considered moderate and 20 points very large (32Go). Comparatively, a meaningful difference among Hodgkin's disease patients was regarded as 7–10 points (46Go). However, the bodily pain and vitality scores for deployed veterans were similar to those reported by patients with minor medical conditions (47Go). Deployed veterans reported reduced health for all domains, much as medically unexplained physical symptoms often involve multiple organ systems (48Go). The general health and vitality health domains were the most impacted, followed by bodily pain and mental health. In contrast, physical and emotional functioning and role subscales were impacted the least.

The health profile of deployed veterans generally was slightly below US norms, although the mean scores of these veterans remained higher than those for medically and mentally ill populations (32Go). However, for these veterans, the MCS score was higher than age-matched US norms. Perhaps the emotional burden of service is less severe than the more subtle physical consequences, which potentially lead to medically unexplained physical symptoms. Additionally, veterans may be reluctant to acknowledge impaired mental health. Other potential explanations such as age distribution, media effect, reporting bias, and regional trends need to be explored.

Our results are consistent with reports from other studies. Similar health status distributions were found among a small group of Air Force Gulf War veterans from Pennsylvania seeking medical evaluation (14Go). British researchers found very similar SF-36 scores and also noted a larger difference in general health relative to physical functioning for Gulf War veterans versus controls (49Go). Compared with controls, Canadian Gulf War veterans have reported a greater reduction in activities because of poor health and a higher number of bed days (50Go). Proctor et al. reported significantly lower SF-36 scores for Gulf War veterans (n = 291) compared with those deployed to Europe (n = 50); however, the prevalence of fair or poor health status was twice that seen here, perhaps because of these authors' use of a more highly selected group (51Go). More recently, Proctor et al. reported SF-36 scores for Gulf War-deployed veterans (n = 141) and Germany-deployed controls (n = 46) 4 years postconflict (52Go). Gulf War veterans were also shown to have poorer health than the general US population. In contrast to our study, these authors identified current medical and psychological conditions associated with lower physical functioning.

Our study has a number of unique strengths. A 76 percent participation rate is one of the highest among comparable studies and minimizes the likelihood of participation bias (53Go). Inclusion of all personnel, regardless of whether they were discharged from military service, reduces concerns of bias due to unequal follow-up or a healthy worker effect. The deployed sample served throughout the Gulf War Theater, and, importantly, a comparable nondeployed control group was included. The large sample was important for the analytical methods used. Finally, we considered a broad range of health, personal, and environmental characteristics as potential risk factors in these analyses.

Generalizability may be limited, since the population was restricted to subjects reporting Iowa as the home of record at enlistment. Ascertainment of health status and risk factor data might have been influenced by recall or reporting bias, especially given the extensive media coverage of a potential "Gulf War syndrome." Disability claim status may also have influenced reporting. However, only 9 percent of respondents reported receiving Department of Veterans Affairs disability compensation, and there was no difference by deployment status. Of note, this study assessed HRQL 5 years postconflict; thus, we could not address the immediate impact of deployment on HRQL. Given the cross-sectional design, observed relations between variables are descriptive, not causal. Although a broad range of potential risk factors was assessed, other factors not assessed, such as health behavior or social support, might have obscured the true relation between HRQL and deployment.

Although our study identified that slightly poorer HRQL was associated with deployment, much of the variability in scores remains unexplained. It is not clear whether the poorer health status of Gulf War veterans is specifically related to deployment, unmeasured factors, or perhaps recall or reporting bias. Even though we have identified important trends and risk factors for HRQL, further studies of the determinants of postdeployment health are needed.

Clearly, there are health consequences of military service other than obvious war injuries. Complaints similar to those reported by Gulf War veterans have historically been common among veterans following major conflicts (54Go). While much research to date has focused on detecting a novel Gulf War illness (14Go, 55Go, 56Go), we and others believe it is essential to evaluate HRQL thoroughly. A recent report highlighted the need for broad-based health status assessment and compilation of personal and environmental health correlates (53Go). Efforts are also under way to improve medical surveillance and record keeping for future conflicts. The Department of Veterans Affairs has adopted an outcomes management system that includes ongoing SF-36 data collection (57Go). There has also been a call to further explore methods to prevent or at least mitigate deployment-related health effects (58Go). The determinants of HRQL we identified may be useful in designing preventive and therapeutic interventions aimed at helping both Gulf War veterans and future military personnel successfully adapt to life after war.


    ACKNOWLEDGMENTS
 
This work was partially supported by Centers for Disease Control and Prevention cooperative agreement U50/CCU711513 and US Department of Defense grant DAMD17-97-1-7355. Dr. Voelker was also partially supported through National Institute of Mental Health training grant 5 T32 MH15158-23.

The authors appreciate the contributions of all research personnel in coordinating and administrating the original study, Statistical Laboratory Survey Section of the Iowa State University Statistics Department personnel in carefully conducting the telephone interview and data collection, and members of the Iowa Gulf War Study Group for their advice concerning development and analysis of the original telephone survey. The authors also acknowledge Mike Dove and the Defense Manpower Data Center for their assistance in making data available to draw the sample. The contributions of the Scientific Advisory Committee and Public Advisory Committee in providing advice, input, and review during development of the project are also greatly appreciated.


    NOTES
 
Reprint requests to Dr. Bradley N. Doebbeling, SE 625 GH, Department of Internal Medicine, University of Iowa HealthCare, 200 Hawkins Drive, Iowa City, IA 52242.


    REFERENCES
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

  1. The Persian Gulf experience and health. NIH Technology Assessment Workshop Panel. JAMA 1994;272:391–6.[ISI][Medline]
  2. Hyams KC, Hanson K, Wignall FS, et al. The impact of infectious diseases on the health of US troops deployed to the Persian Gulf during Operations Desert Shield and Desert Storm. Clin Infect Dis 1995;20:1497–504.[ISI][Medline]
  3. Berezuk GP, McCarty GE. Investigational drugs and vaccines fielded in support of Operation Desert Storm. Mil Med 1992;157:404–6.[ISI][Medline]
  4. Abou-Donia MB, Wilmarth KR, Jensen KF, et al. Neurotoxicity resulting from co-exposure to pyridostigmine bromide, DEET, and permethrin: implications of Gulf War chemical exposures. J Toxicol Environ Health 1996;48:35–56.[ISI][Medline]
  5. Unexplained illness among Persian Gulf War veterans in an Air National Guard Unit: preliminary report--August 1990–March 1995. MMWR Morb Mortal Wkly Rep 1995;44:443–7.[Medline]
  6. Gray GC, Coate BD, Anderson CM, et al. The postwar hospitalization experience of US veterans of the Persian Gulf War. N Engl J Med 1996;335:1505–13.[Abstract/Free Full Text]
  7. Kang HK, Bullman TA. Mortality among US veterans of the Persian Gulf War. N Engl J Med 1996;335:1498–504.[Abstract/Free Full Text]
  8. Haley RW, Kurt TL, Hom J. Is there a Gulf War Syndrome? Searching for syndromes by factor analysis of symptoms. JAMA 1997;277:215–22. (Erratum published in JAMA 1997;278:388).[Abstract]
  9. Committee to Review the Health Consequences of Service During the Persian Gulf War, Medical Follow-up Agency, Institute of Medicine. Health consequences of service during the Persian Gulf War: initial findings and recommendations for immediate action. Washington, DC: National Academy Press, 1995.
  10. Defense Science Board. Report of the Defense Science Board Task Force on Persian Gulf War Health Effects. Washington, DC: Office of the Undersecretary of Defense for Acquisition and Technology, 1994.
  11. Committee on the DoD Persian Gulf Syndrome Comprehensive Clinical Evaluation Program, Institute of Medicine Division of Health Promotion and Disease Prevention. Evaluation of the US Department of Defense Persian Gulf Comprehensive Clinical Evaluation Program. Washington, DC: National Academy Press, 1995.
  12. Unexplained illnesses among Desert Storm veterans. A search for causes, treatment, and cooperation. Persian Gulf Veterans Coordinating Board. Arch Intern Med 1995;155:262–8.[Abstract]
  13. Self-reported illness and health status among Gulf War veterans. A population-based study. The Iowa Persian Gulf Study Group. JAMA 1997;277:238–45.[Abstract]
  14. Fukuda K, Nisenbaum R, Stewart G, et al. Chronic multisymptom illness affecting Air Force veterans of the Gulf War. JAMA 1998;280:981–8.[Abstract/Free Full Text]
  15. Wilson IB, Cleary PD. Linking clinical variables with health-related quality of life: a conceptual model of patient outcomes. JAMA 1995;273:59–65.[Abstract]
  16. Guyatt GH, Feeny DH, Patrick DL. Measuring health-related quality of life. Ann Intern Med 1993;118:622–9.[Abstract/Free Full Text]
  17. Kessler RC, Mroczek DK. Measuring the effects of medical interventions. Med Care 1995;33(suppl 4):AS109–AS119.[ISI][Medline]
  18. Patrick DL, Erickson P. Health status and health policy: allocating resources to health care. New York, NY: Oxford University Press, 1993.
  19. Aday LA, Anderson R. Equity of access to medical care: a conceptual and empirical overview. Med Care 1981;19:4–27.[ISI][Medline]
  20. Andersen RM, Davidson PL, Ganz PA. Symbiotic relationships of quality of life, health services research and other health research. Qual Life Res 1994;3:365–71.[ISI][Medline]
  21. Jette AM, Branch LG, Berlin J. Musculoskeletal impairments and physical disablement among the aged. J Gerontol 1990;45:M203–M208.[ISI][Medline]
  22. Verbrugge LM, Patrick DL. Seven chronic conditions: their impact on US adults' activity levels and use of medical services. Am J Public Health 1995;85:173–82.[Abstract]
  23. Lawrence WF, Fryback DG, Martin PA, et al. Health status and hypertension: a population-based study. J Clin Epidemiol 1996;49:1239–45.[ISI][Medline]
  24. Stewart AL, Greenfield S, Hays RD, et al. Functional status and well-being of patients with chronic conditions: results from the Medical Outcomes Study. JAMA 1989;262:907–13.[Abstract]
  25. McGee DL, Liao Y, Cao G, et al. Self-reported health status and mortality in a multiethnic US cohort. Am J Epidemiol 1999;149:41–6.[Abstract]
  26. Wachtel T, Piette J, Mor V, et al. Quality of life in persons with human immunodeficiency virus infection: measurement by the Medical Outcomes Study Instrument. Ann Intern Med 1992;116:129–37.[ISI][Medline]
  27. Black DW, Doebbeling BN, Voelker MD, et al. Quality of life and health services utilization in a population-based sample of military personnel reporting multiple chemical sensitivities. J Occup Environ Med 1999;41:928–33.[ISI][Medline]
  28. Doebbeling BN, Jones MF, Hall DB, et al. Methodological issues in a population-based health survey of Gulf War veterans. J Clin Epidemiol (in press).
  29. Ware JE Jr, Sherbourne CD. The MOS 36-Item Short-Form Health Survey (SF-36): I. conceptual framework and item selection. Med Care 1992;30:473–83.[ISI][Medline]
  30. Corrigan JD, Smith-Knapps K, Granger CV. Outcomes in the first five years of traumatic brain injury. Arch Phys Med Rehabil 1998;79:298–305.[ISI][Medline]
  31. Ware JE. SF-36 Physical and Mental Health Summary Scores: manual and interpretation guide. Boston, MA: The Health Institute, 1995.
  32. Ware JE, Snow KK, Kosinski M, et al. SF-36 Health Survey: manual and interpretation guide. Boston, MA: The Health Institute, 1993.
  33. Shah BV, Barnwell BG, Bieler GS. SUDAAN user's manual: software for analysis of correlated data, release 6.4. Research Triangle Park, NC: Research Triangle Institute, 1992.
  34. Cohen SB, Burt VL, Jones GK. Efficiencies in variance estimation for complex survey data. Am Stat 1986;40:157–64.[ISI]
  35. Cronbach LJ. Coefficient alpha and the internal structure of tests. Psychometrika 1951;16:297–334.[ISI]
  36. Fleiss J, Cohen J. The equivalence of weighted kappa and the intraclass correlation coefficient as measures of reliability. Educ Psychol Meas 1973;33:613–19.[ISI]
  37. Kirshner B, Guyatt G. A methodological framework for assessing health indices. J Chronic Dis 1985;38:27–36.[ISI][Medline]
  38. Kleinbaum DG, Kupper LL, Muller KE. Applied regression analysis and other multivariate methods. 2nd ed. Boston, MA: PWS-Kent Publishing Company, 1988.
  39. Harrell FE Jr, Lee KL, Califf RM, et al. Regression modeling strategies for improved prognostic prediction. Stat Med 1984;3:143–52.[ISI][Medline]
  40. SAS Institute, Inc. SAS/STAT user's guide, version 6, 4th ed. Cary, NC: SAS Institute Inc, 1990.
  41. McDowell I, Newell C. Measuring health: a guide to rating scales and questionnaires. New York, NY: Oxford University Press, 1987.
  42. Cohen J. Statistical power analysis for the behavioral sciences. Hillsdale, NJ: Lawrence Erlbaum Associates, 1988.
  43. Engel CC, Katon WJ. Population and need-based prevention of unexplained physical symptoms in the community. In: Strategies to protect the health of deployed US forces: medical surveillance, record keeping and risk reduction. Washington, DC: Institute of Medicine, National Academy Press, 1999:173–212.
  44. Bergner M. Measurement of health status. Med Care 1985;23:696–704.[ISI][Medline]
  45. Allen HM Jr, Rogers WH. The consumer health plan value survey: round two. Health Aff (Millwood) 1997;16:156–66.[Free Full Text]
  46. Kaasa S, Knoble H, Havard Loge J, et al. Hodgkin's disease: quality of life in future trials. Ann Oncol 1998;9(suppl 5):S137–S145.
  47. McHorney CA, Ware JE Jr, Raczek AE. The MOS 36-Item Short-Form Health Survey (SF-36): II. Psychometric and clinical tests of validity in measuring physical and mental health constructs. Med Care 1993;31:247–63.[ISI][Medline]
  48. Hyams KC. Developing case definitions for symptom-based conditions: the problem of specificity. Epidemiol Rev 1998;20:148–56.[ISI][Medline]
  49. Unwin C, Blatchley N, Coker W, et al. Health of UK servicemen who served in Persian Gulf War. Lancet 1999;353:169–78.[ISI][Medline]
  50. Canadian Department of National Defense. Health study of Canadian forces personnel involved in the 1991 conflict in the Persian Gulf. Vol I. Ottawa, Ontario, Canada: Goss Gilroy, Inc, 1998.
  51. Proctor SP, Heeren T, White R, et al. Health status of Persian Gulf War veterans: self-reported symptoms, environmental exposures and the effect of stress. Int J Epidemiol 1998;27:1000–10.[Abstract]
  52. Proctor SP, Harley A, Wolfe F, et al. Health-related quality of life in Persian Gulf War veterans. Mil Med 2001;166:510–19.[Medline]
  53. Committee on Measuring the Health of Gulf War Veterans. Gulf War veterans: measuring health. Washington, DC: Institute of Medicine, National Academy Press, 1999.
  54. Hyams KC, Wignall FS, Roswell R. War syndromes and their evaluation: from the US Civil War to the Persian Gulf War. Ann Intern Med 1996;125:398–405.[Abstract/Free Full Text]
  55. Ismail K, Everitt B, Blatchley N, et al. Is there a Gulf War syndrome? Lancet 1999;353:179–82.[ISI][Medline]
  56. Doebbeling BN, Clarke WR, Watson D, et al. Is there a Persian Gulf War syndrome? Evidence from a large population-based survey of veterans and nondeployed controls. Am J Med 2000;108:695–704.[ISI][Medline]
  57. Kazis LE, Ren XS, Lee A, et al. Health status in VA patients: results from the Veterans Health Study. Am J Med Qual 1999;14:28–38.[ISI][Medline]
  58. Committee on a National Center on War-related Illnesses and Postdeployment Health Issues. National Center for Military Deployment Health Research. Washington, DC: Institute of Medicine, National Academy Press, 1999.
Received for publication August 10, 2001. Accepted for publication January 11, 2002.