1 School of Nursing, Oregon Health and Science University, Portland, OR.
2 Center for Research on Occupational and Environmental Toxicology, Oregon Health and Science University, Portland, OR.
Received for publication August 16, 2001; accepted for publication May 24, 2002.
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ABSTRACT |
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chemical warfare agents; factor analysis, statistical; military medicine; Persian Gulf syndrome; veterans
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INTRODUCTION |
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Bieliauskas and Turner (7) have recommended that research on the current health of Gulf War veterans focus on those most likely to have been exposed to environmental toxins such as chemical warfare agents. One group that fits this criterion is veterans who were deployed in the Khamisiyah area of coalition-occupied Iraq, particularly those who witnessed a controlled detonation of Iraqi munitions later determined to have contained known chemical warfare agents.
In 1996, the US Department of Defense disclosed that on March 4, 1991, US personnel destroyed munitions containing 8.5 metric tons of sarin/cyclosarin housed in bunker 73 at Khamisiyah and that on March 10, 1991, additional sarin/cyclosarin rockets were destroyed in a pit at Khamisiyah (17, 18). In 1997, the Defense Department notified all of the approximately 20,000 individuals who had been operating within a 50-km radius of the Khamisiyah site between March 4 and March 13, 1991, of their possible exposure to low levels of chemical warfare agents and the availability of clinical examinations by the Department of Defense or the Department of Veterans Affairs (19, 20).
In a recent study, McCauley et al. (16) reported on the health status of veterans who had been deployed within a 50-km radius of Khamisiyah. They noted no increased risk of current self-reported symptoms among veterans deployed in the Khamisiyah area compared with those who had been deployed to the Gulf region but not to Khamisiyah. Within the Khamisiyah group, however, veterans close enough to witness the demolition reported significantly more of 16 different symptoms within 2 weeks of the demolition than nonwitnesses, and all but three of these symptoms were consistent with exposure to organophosphate agents. Eight years after the demolition, these same witnesses reported a significant excess of eight health-related symptoms, some of which could plausibly be related to long-term effects of low-dose exposure to chemical warfare agents.
This paper presents the results of further analysis of the McCauley et al. (16) data. Our first purpose was to subject the self-reported health data of Khamisiyah troops to a factor analysis to determine whether a unique pattern of symptoms or factors was present and, if so, whether the pattern differed from that of non-Khamisiyah troops and troops not deployed to the Gulf region. Our second purpose was to compare the results of the factor analysis with those reported by McCauley et al., especially as they related to the apparent increase in the presence of certain current symptoms among veterans who witnessed the detonation. Our last purpose was to examine how factor analysis behaves when the data are dichotomous.
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MATERIALS AND METHODS |
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The sampling pool for the telephone interview consisted of 3,219 veterans. We contacted 2,918 of these (90.6 percent), but 530 were found to be ineligible, primarily because they were not veterans of the Gulf War or were not members of the designated military branches (the Army or National Guard) during the Gulf War. Of the 2,918 telephone contacts made, 1,833 interviews were completed, and we were able to use 1,779 of these interviews in our analyses. Details on the sampling procedure, the location and recruitment of participants, and the characteristics of nonrespondents have been provided elsewhere (16).
The 1,779 Gulf War veterans in the study included 516 who were on active duty during the study period but were not deployed to the Gulf region, 610 who were deployed to southwestern Asia but not within the 50-km radius around Khamisiyah, and 653 who were deployed within the 50-km radius around Khamisiyah. Within the Khamisiyah group, 162 veterans reported that they had witnessed the munitions detonations (the witness subgroup) and 405 reported that they had not (the nonwitness subgroup).
Study instrument
We adapted an existing survey instrument used in a population-based study of Gulf War veterans in the northwestern United States (2124). We adapted the questionnaire to obtain more information on troop movements in the Khamisiyah area, including exposure to detonation of ammunition bunkers. In addition, we modified the health symptom questionnaire to include more questions on specific neurologic symptoms, as explored by Haley et al. in 1997 (5). The reliability of the instrument is reported elsewhere (2123). Study participants completed two checklists: one of health symptoms they had experienced within 2 weeks of the Khamisiyah detonations and one of current health symptoms that had been present within the past month. We used only the current health symptoms in our factor analysis.
Statistical analyses
Factor analysis
For the first part of the study, an exploratory factor analysis of each deployment group (Khamisiyah, deployed non-Khamisiyah, and nondeployed) was performed using SPSS, version 10.0 (25). Factors were extracted by principal components and subjected to a varimax rotation (26). Those factors having eigenvalues greater than 1 and individually accounting for at least 5 percent of the overall variance were retained. Symptoms with rotated loadings greater than 0.60 in absolute value were considered "dominant" and served as the defining symptoms for each specific factor. Ordinary least-squares (i.e., unweighted regression) analysis (26) was used to calculate factor scores. These decision rules regarding factor retention and identification of dominant and defining symptoms were empirically derived through a Monte Carlo simulation and are more fully described below.
Comparison of factor analysis results with prevalence of self-reported symptoms
Although a factor analysis was performed on the entire Khamisiyah group (n = 653), the limited number of veterans who had witnessed the munitions detonation (n = 162) prevented an independent factor analysis of this subpopulation. Instead, we determined whether the distribution of factor scores differed significantly between veterans who had witnessed the demolition and their nonwitnessing counterparts (n = 405), using a Wald-Wolfowitz runs test (27). Eighty-six of the 653 veterans in the Khamisiyah group were dropped from this part of the analysis because we were unable to reliably ascertain their status as an observer/nonobserver of the detonation. We then classified veterans as possessing a particular factor on the basis of their endorsing all of the dominant symptoms within the factor. Using this rule, a veteran could possess several factors simultaneously, a single factor, or none at all. The number of veterans within each combination of factors was then stratified by the veterans status as witnesses or nonwitnesses to the demolition activities. Within this stratification (table 1), associations between combinations of factors and the witness/nonwitness status of veterans were examined using log-linear models (28). Unlike logistic regression, this technique can be used to investigate the structure of dependencies within a multiway table without having to specify a particular dependent outcome variable.
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RESULTS |
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Factor analysis using principal-components extraction with varimax rotation was initially conducted on the Khamisiyah veteran sample (table 3). Three factors with eigenvalues greater than 1.0 were identified, and together they accounted for 46.7 percent of the total variance. Using a cutoff of 0.60 for factor loadings, the first factor contained six symptoms: unusual irritability/anger; mood swings; changes in memory; persistent fatigue, tiredness, or weakness; difficulty concentrating; and depression. This was labeled a "cognitive/psychological" factor. Factors 2 and 3 each contained two variables. The second factor, "dysesthesia," consisted of a tingling, burning sensation of pins and needles and numbness or lack of feeling. The third factor, labeled "vestibular dysfunction," contained loss of balance or coordination and dizzy spells.
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Factor analysis of the deployed non-Khamisiyah veterans yielded three factors accounting for 49.8 percent of the total variance (table 3). The first factor, again identified as "cognitive/psychological," consisted of changes in memory, difficulty sleeping, depression, unusual irritability/anger, mood swings, and difficulty concentrating. The second factor, also called "dysesthesia," contained numbness or lack of feeling and a sensation of pins and needles. The third factor, "mixed," contained loss of balance or coordination, dizzy spells, shortness of breath, and chemical sensitivities.
Factor analysis results versus epidemiologic analysis of symptom prevalence
Results from the nonparametric Wald-Wolfowitz test indicated no significant differences in the distributions of factor scores between the witness and nonwitness subgroups (factor 1, p = 0.88; factor 2, p = 0.19; factor 3, p = 0.28). Log-linear analysis revealed that factors 1 and 3 ("cognitive/psychological" and "vestibular dysfunction") were unrelated to a veterans status as a witness (2 (2 df) = 0.66, p = 0.72) and that factor 2 ("dysesthesia") was significantly associated with whether a veteran had witnessed the demolition (
2 (1 df) = 6.10, p = 0.013). When factor 2 was treated as the dependent outcome in a logistic regression model, the estimated odds of having witnessed the demolition activities among veterans reporting both symptoms related to dysesthesia were 0.77 (table 1). This estimate was 2.08 times higher (95 percent confidence interval: 1.16, 3.68) than the corresponding odds for veterans who did not report any of the symptoms related to dysesthesia (odds = 0.37).
Performance of factor analysis with dichotomous variables
The Monte Carlo simulations produced similar results for all three populations (Khamisiyah, deployed non-Khamisiyah, and nondeployed), so we report only those from the Khamisiyah group in detail. Again, the purpose of this portion of the study was to investigate how traditional criteria for selecting factors (eigenvalues in excess of 1) and subsequently determining which components dominate a given factor (loadings in excess of 0.40) are affected when factor analysis is performed on random dichotomous data.
Simulations revealed that eigenvalues for the first eight factors were always in excess of 1; the ninth factor satisfied this criterion 84 percent of the time, and factors 1219 never produced eigenvalues greater than 1. Additionally, the proportion of variance explained by each of the individual factors ranged between 3.4 percent and 7.6 percent, with an average of 5.3 percent. This may be regarded as the "typical" amount of variance explained, per factor, when variables are uncorrelated. These data further indicated that for 19 randomly generated dichotomous variables, five factors were sufficient to account for an average of 32 percent of the total variance. Additionally, the 90th percentile for the rotated loadings varied from 0.60 to 0.62, with approximately 95 percent of the rotated loadings exceeding 0.45.
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DISCUSSION |
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Although our findings are largely consistent with those of most other investigators, direct comparisons are not possible, for several reasons. First, different investigators have used different lists of symptoms in their studies. Second, the sizes, sources, and compositions of the samples used in other reports have varied considerably. Third, investigators have used different factor extraction and rotation techniques and different thresholds for factor loadings to identify their syndromes. While these analytical variations are entirely acceptable (31), this has resulted in disparate findings. Table 4 summarizes these differences.
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Comparison of factor analysis with epidemiologic analysis
In their earlier paper, McCauley et al. (16) found some evidence of increased symptoms among Khamisiyah veterans who had witnessed the detonation of munitions containing known chemical warfare agents compared with other veterans who had been within 50 km of Khamisiyah but had not witnessed the detonations. These symptoms are shown in table 5.
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Although the epidemiologic evidence in McCauley et al.s earlier paper clearly demonstrated an increase in bloody diarrhea in the witness group compared with the nonwitness group (odds ratio = 3.1, 95 percent confidence interval: 1.6, 6.0), we did not include this symptom in our factor analysis, because it failed to correlate with any other symptoms. This was the only significant symptom in the witness group that was not included in our factor analysis. This illustrates another limitation of using factor analysis for epidemiologic purposes: Factor analysis only identifies joint associations among variables and the latent structures that may describe them; it provides no information about individual variables, thereby making it possible to miss an isolated symptom that significantly adds to the burden of illness in a population.
Performance of factor analysis with dichotomous variables
Factor analysis has been used extensively to test measurement scales and to refine and test constructs such as intelligence and self-concept (31, 32). These analyses have been used traditionally with ordinal and interval-level data, and at least one statistical program specifies interval-level data as the minimum requirement for factor analysis (25); yet many of the data used in previously reported factor analyses of Gulf War veterans operate below this level. Knoke et al. (6) addressed this issue briefly in their paper; otherwise, previous investigators have had little to say about the ways in which factor analysis might perform on non-interval-level variables and how that might have affected their results.
Our work has shown that application of standard rules to 19 randomly generated and independently created dichotomous variables could result in models containing five factors, which explained approximately 30 percent of the total variance. Even more troubling is the realization that rotated loadings in excess of 0.40, the traditional cutoff used by investigators, occurred more than 95 percent of the time in our randomly generated data set. If, as our simulation demonstrated, similar results can be obtained using randomly generated data, we are forced to reconsider the existence of syndromes found in earlier studies, especially those discovered through factor analysis of dichotomous variables.
One of the advantages of factor analysis is that it allows investigators to explore their data rather liberally. Because there are few "rules" governing the choices of factor extraction, rotation, or factor loading cutoffs, factor analysis is often used as a last resort when other analyses fail to yield significant results (31). Since the publication of Haley et al.s initial paper (5), investigators in this field seem compelled to provide results of factor analysis as a necessary component of analyses related to unexplained Gulf War illnesses. In the absence of more robust decision rules for these kinds of data, the resulting factors may be a rich mixture of randomness, which could lead investigators down uninformative paths. While we do not intend to imply that the hard work of previous investigators has been inadequate, we feel that there has been a rush to use this technique to try to identify a unique Gulf War syndrome when more classic epidemiologic methods have failed to do so. Given the limitations cited above, it seems that factor analysis has also failed in this task.
Our study was subject to several limitations, most of which are fully detailed in the paper by McCauley et al. (16). These include all of the issues related to self-reporting of symptoms, such as recall and selection bias, and to the sampling biases inherent in the use of telephone surveys. Our sample was limited to individuals who had served in the Army or National Guard and whose telephone numbers could be tracked using common search mechanisms; therefore, our sample may not be representative of the entire population of troops serving in the Gulf War. Although we have compared the results of our factor analysis with those reported by other investigators, it is important to realize that the methods used to sample the veterans in these studies differed substantially, and data were collected using different approaches.
The results of our simulation are unique to this data set and cannot be taken to establish guidelines for other studies in which factor analysis is performed on dichotomous variables. We urge other investigators performing factor analysis with dichotomous variables to determine how their analytical techniques would perform using simulated data sets of an appropriate size, with individual variables randomly generated to mimic the observed symptom frequencies.
Comments
Research on whether a unique Gulf War syndrome exists tends to be of three types: studies that rely solely on standard epidemiologic analyses; studies that rely solely on factor analyses; and studies that use a combination of these techniques. Taken together, this body of research indicates that Gulf War veterans have reported an increased burden of illness as long as 8 years after their participation in the Gulf War. However, the majority of studies have not disclosed a unique "Gulf War syndrome"that is, a set of symptoms appearing in these veterans which is different from any other identified disease entity, which appeared only after participation in the Gulf War, and which does not appear with similar frequency in other populations of veterans or nonveterans.
This is not to minimize the health problems encountered by veterans of the Gulf War. We now recognize that many of those veterans were possibly exposed to known chemical warfare agents, and it is reasonable to expect that some will experience physical symptoms even after more than 10 years time. Veterans suffering from war-related symptoms deserve to be thoroughly evaluated and treated, regardless of the fact that a unique Gulf War syndrome has yet to be described.
We agree with Steele (33) that problems reported by Gulf War veterans are complex and that investigators in this field need to consider many possible causes and combinations of causes as the basis for these symptoms. These complexities make it unlikely that any single analytical tool, such as factor analysis, will be the sole source of answers in this continuing controversy.
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ACKNOWLEDGMENTS |
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NOTES |
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REFERENCES |
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