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3. Is there evidence of increased respiratory complaints following deployment compared to pre-deployment?

1 PECOT QUESTION

Is there evidence of increased respiratory complaints following deployment compared to pre-deployment?

Why is this question important?

A basic assumption for inferring a causal relationship is that the cause must precede the effect. Demonstrating that the cause (in this case, exposure to airborne hazards in the Southwest Aisa Theater of Operations [SWATO]) occurs earlier in time than the effect (developing respiratory diseases and conditions), provides additional evidence toward inferring a causal relationship.

2 CONCLUSION

Research focused on respiratory changes pre- to post-deployment supports a temporal association between exposure to hazards in the SWATO and changes in symptoms, pulmonary function, and disease diagnosis. However, this appears to be true only for a subset of deployed military personnel. Research appears to suggest that an underlying susceptibility plays a part in addition to being exposed to multiple pro-inflammatory insults during deployment. However, because most of the available research is able to adjust for or stratify by smoking status, it is clear that the temporal relationship between deployment and disease cannot be due to smoking alone.

Evidence Level: Taking into consideration evidence for the primary hypotheses, combined with uncertainty and evidence for the alternative hypotheses, the evidence level for this conclusion is Low/Moderate.

Figure 1 . Evidence Level

3 KNOWN BIASES

There are known biases in the research on military exposures. We summarize the direction and magnitude of these biases in the table below.

Table 1 . Known Biases in Military Literature: Direction and Magnitude

 

In summary, the diversity of the research collected here makes it difficult to make
global statements regarding the overall direction and magnitude of possible biases.
Thus, possible biases will be evaluated on a study-by-study basis.

4 SUMMARY

Twelve studies were identified that provide evidence on the temporal relationship between exposure and respiratory diseases.5-16 However, the evidence provided is diverse and heterogeneous, focusing on:

  • Subject characteristics that differentiate deployers who developed new onset respiratory symptoms following deployment compared to military who did not deploy. 11
  • Changes in pulmonary function of military personnel from pre-deployment to 6-month post- deployment (both studies from STAPMEDE set of studies). 14,16,20
  • Changes in diagnosed conditions or diseases from pre- to post-deployment 5,6,11,21
    Possible explanations for why some military developed symptoms/diseases pre- to post-deployment but others did not. 7,9,10,14

It is important to note, that only one study (Lewin-Smith et al 2021) reported on the development of interstitial lung diseases (ILDs). All other studies focused on other diseases or respiratory characteristics and symptoms. However, if respiratory complaints and diseases, in general, occur more commonly following deployment exposures, then this provides indirect evidence for a temporal connection between deployment exposures and ILDs in deployed military personnel.

Two studies are particularly important for establishing temporality—i.e., that the exposure preceded the symptoms or disease: the Millenium Cohort Study (MCS), and Study of Active-Duty Military for Pulmonary Disease Related to Environmental Deployment Exposures (STAMPEDE).

Three reports included in this analysis come from the Millenium Cohort Study 7,10,11 . Briefly, the MCS was initiated in July 2001 and obtains follow-up survey data every 3 years until 2022. It is a population-based, stratified random sample of US military personnel from all service branches and includes more than 150,000 consented participants. Participants were surveyed both during active duty and following separation from military service. 22 Because of its longitudinal design, the MCS allows us to establish an approximate time-period of the development of self-reported symptoms or disease conditions that were absent in earlier waves of the study. While the MCS suffers from the standard limitations of any survey (e.g., self-selection into the study, self-report responses), its strength lies in the size of the sample, the validated questionnaire used, and the fact that it samples both deployed and non-deployed military personnel and so allows for a comparison between the two cohorts.

The STAMPEDE II enrolled 450 active duty and retired military personnel who were deployed for a minimum of six months in Southwest Asia (Iraq, Afghanistan, Kuwait or Qatar) (n=380 completing both pre- and post-deployment data). These were individuals who had been referred for chronic respiratory symptoms, primarily shortness of breath or decreased exercise tolerance, after being deployed. The strength of the STAMPEDE studies lies in the fact that they collected clinical data with spirometry both pre- and post-deployment.

In the sections below, we review the data on new onset symptoms, changes in pulmonary function pre- to post-deployment, and new onset diagnoses. Additionally, we examine a set of correlational studies that seek to identify characteristics of subjects who reported (or were diagnosed with) new onset respiratory conditions versus military personnel who did not (as of the time of the study). This latter section is important because “deployment” is a very crude measure of exposure (deployed individuals may have very different levels of exposure to any number of respiratory hazards [see Known Biases section above]) and we know that not all individuals who were deployed develop respiratory conditions. Being able to identify potential predictors of respiratory conditions may provide insight into why some but not all deployers experience different respiratory conditions.

4.1 SYMPTOMS

Three studies 8,11,16 report on the development of new respiratory symptoms.

Roop et al 2007 8 surveyed 1,250 Army personnel and DOD contractors returning from Operation Enduring Freedom or Operation Iraqi Freedom deployments through the Soldier Readiness Processing Center at Fort Bliss, Texas from April through July 2003. Respondents were asked whether they had experienced a range of symptoms before and during deployment. Results were split out for those who reported a previous diagnosis of asthma versus those who did not. For all symptoms (wheezing, cough, sputum production, chest pain/tightness and allergy symptoms), there was a statistically significant increase in symptoms from before to during deployment (range: 13% to 29% increase). For asthmatic respondents, there was a significant increase in all symptoms except wheezing (range: 15% to 20% increase). Across symptoms, individuals classified as “uncontrolled asthmatics” had the highest increase in symptoms (with the exception of allergy symptoms). Significantly, while 14% of non-asthmatic participants reported receiving medical care for respiratory symptoms during deployment, 44% of asthmatic respondents (and 69% of uncontrolled asthmatics) reported receiving care. Similarly, only 4% of non asthmatic respondents reported requiring limited duty or hospitalization during deployment compared to 16% of asthmatics (and 31% of uncontrolled asthmatics). The authors also compare changes in symptoms separately for smokers versus non-smokers. While smokers had a higher proportion of symptoms both pre- and post-deployment (with the exception of allergy symptoms), the differences from pre- to post-deployment were negligible (again, except for allergies, where non- smokers saw a 29% increase in allergy symptoms compared to an increase of only 4% among smokers).

Smith et al 2009 11 compared deployers and non-deployers who reported no respiratory symptoms at the time of the baseline questionnaire (July 2001–June 2003) and who responded to the first 3-year follow- up (June 2004–January 2006) were included in this analysis (n=38,993 participants available for analyses). Three respiratory outcomes were examined: persistent or recurring cough or shortness of breath (combined as “respiratory symptoms”), chronic bronchitis or emphysema (combined due to small numbers for each), and asthma. The presence of these conditions was determined via a survey question, “Has your doctor or other health professional ever told you that you have any of the following conditions?’’ Rates of the development of these three respiratory conditions over three years were small, as were differences between deployers and non-deployers:

  • New onset respiratory symptoms: 14% of deployers versus 10% of non-deployers,
  • Chronic bronchitis or emphysema: 1% of deployers versus 1% of non-deployers,
  • Asthma: 1% of deployers versus 1% of non-deployers.

The authors then sought to identify differences between deployers and non-deployers in terms of the development of new onset conditions. In other words, even if the same proportion of deployers versus non-deployers experienced new onset of the disease, the reasons for the new onset may be different. In adjusted models, deployers who were in the Army and the Marines had elevated odds (73% and 49% respectively) of reporting new onset respiratory symptoms compared to non-deployers (both statistically significant). There was also a 48% increase in the odds of chronic bronchitis or emphysema in Army deployers, though this did not reach statistical significance due to the small number of respondents reporting these conditions.

It is important to note that this study provides limited and indirect evidence regarding the development of interstitial lung diseases (ILDs). Even if there is evidence of slightly higher levels of respiratory symptoms in deployers and evidence that this rate appears to be service related, these symptoms (cough, dyspnea) are non-specific. ILDs are heterogeneous and the chronic inflammation and progressive fibrosis that characterize this family of diseases may take many years to develop to a stage where a specific ILD can be definitely diagnosed 19 . So, while the three-year time frame provides evidence of the differential development of symptoms and perhaps different reasons for developing these symptoms, we cannot definitely determine that these are the early symptoms of what may later become ILDs.

McMahon et al 2021 (STAMPEDE III) 16 recruited active duty or retired military who reported new respiratory symptoms related to deployment (n=380). While the purpose of this article was to determine whether the presence of PTSD was associated with cardiopulmonary responses to exercise, the authors surveyed participants (n=303) regarding respiratory symptoms before, during and following deployment. Responses were classified as: 1 = never; 2 = <2 times per week; 3 = 2 to 5 times per week; 4 = daily. The averages for respondents with and without PTSD are presented in Figure 1 . A similar figure not broken down by PTSD status is presented in Morris et al 2020. 23 What we see is a clear trend for individuals with and without PTSD moving from means close to “never” experiencing the symptoms pre-deployment to close to “daily” post-deployment.

Figure 2 .Changes in Respiratory Symptoms for Participants with and Without PTSD: Before, During and After Deployment

Summary While all three of the included studies are based on self-report of symptoms, the Millenium Cohort Study provides the strongest evidence since respondents were asked only to report recent symptoms at the time of the survey panel and were not asked to remember frequency of symptoms before or during deployment. However, the findings corroborate each other: each finding higher rates of symptoms (and in the case of the MCS study, certain diseases) following deployment compared to before.

Table 2 . Summary of Symptom Findings

4.2 FUNCTION

Beyond self-report, it is important to document changes in clinical measures from pre- to post-deployment. While we know of no study that uses population-based sampling to compare relative changes in deployers versus non-deployers over time, the two studies12,14 provide measures of respiratory changes in deployed military personnel.

Morris et al 2019 (STAMPEDE II) 14 , recruited participants from Ft. Hood during their pre-deployment processing, gathering measures of chest radiography, spirometry and impulse oscillometry. The same evaluation was repeated post-deployment in individuals who returned through Ft. Hood before their next deployment (within approximately 6 months of the end of their previous deployment). Thus, personnel who left service or were not being redeployed (50.2%, potentially in part because of the onset of respiratory issues) would not have been included in this sample—thus causing a potential “healthy warrior” bias. 17

The authors make two comparisons of note: (1) Pre and post deployment functional measures on all military who were examined both pre and post (n=843, 49.8% of original sample), and (2) a sub-analysis of differences pre- to post-deployment in soldiers who were confirmed to have no respiratory obstruction (FEV1/FVC<LLN) prior to deployment (n=116).

For the entire cohort, results of spirometry and impulse oscillometry show small but clinically insignificant improvements (with statistically significant decreases in resistance and reactance). The authors interpret these changes as within the normal variation of testing. Similar small improvements were seen in the subset of military who had measured airway obstruction at some point, with the exception of individuals who did not have obstruction pre-deployment but had measures of obstruction post-deployment. For individuals who developed new onset airway obstruction during deployment (n=29), FEV1/FVC decreased by 7.9% (<0.001) and FEF 25-75 % predicted decreased by 10.9% (p=0.01,indicating a decrease in the airflow through the smaller air passages in the lungs).

Woods et al 2022 12 carried out a retrospective search of the Military Health System database to identify individuals deployed to the SWATO between 2006 and 2015 and who had an ICD-9 code for asthma, a CPT code for spirometry pre- and post-deployment, and had a minimum of three encounters at a DOD pulmonary clinic. Unlike the Morris et al 2019, the focus of the Woods et al paper was specifically on changes in military personnel who had diagnosed asthma prior to deployment. Similar to the Morris et al 2019 findings, there was a non-significant (both statistically and clinically) increase in FEV1 and FVC from pre- to post-deployment. Though, among individuals who had pre-deployment obstruction, the improvement from pre- to post-deployment in FEV1 % predicted showed a medium effect size (74.7 ± 10.0 to 80.9±14.4, p=0.06). In contrast, among the subgroup of individuals whose pre- and post- deployment spirometry included bronchodilator administration, there was a statistically significant decrease in change in FEV1(L) from +0.31±0.26 pre-deployment to +0.16±0.23 post-deployment (p=0.02). Because an increase in FEV1 post-bronchodilator is an indicator of reversibility of airway obstruction, for a subgroup of individuals in the Woods et al study, the small but significant decrease in responsiveness could indicate a deployment-related response to medication.

Taken together, in terms of empirical spirometric and oscillometry measures from pre-deployment to approximately six months post deployment, we see a statistically significant decrease in respiratory measures in only a subset of individuals. While the results in the set of individuals who had both pre-and post-deployment measures show, on the whole, clinically insignificant improvements, it is difficult to interpret the accuracy or applicability of this to the general military population given the loss of 50.2% of the sample in the Morris et al 2019 study, and the limitation to individuals with a diagnosis of asthma in the Woods study. In the Morris study, if some proportion of those who did not redeploy were dropped because of no longer being able to meet respiratory health requirements, then the apparent “improvement” would be a result of healthy warrior bias rather than actual improvement in respiratory health during deployment. An additional limitation of the Morris et al 2019 study is the very short timeframe for post-deployment pulmonary function—only 6 months. Given that the inflammatory and fibrotic processes associated with ILD generally take years if not decades to develop, it is unlikely that the effect of changes of this sort would have been detectable in this time period. While the time period between spirometry tests in the Woods et al study was longer (about 3.5 years), it should be noted that spirometry is not used diagnostically for interstitial lung diseases and so would be insensitive to changes in the interstitium. For the Woods et al study, while the results indicate that deployment was not, in general, harmful for pulmonary function, there is a concern regarding how deployment exposures may affect some individuals’ response to medication.

In summary, what we can say with some confidence is that, among a subset of military deployers without airway obstruction prior to deployment, there is a clear temporal relationship between hazard exposures during deployment and empirical measures of pulmonary function.

4.3 DIAGNOSED CONDITIONS

Are military personnel diagnosed with respiratory conditions at a higher rate post-deployment than before deployment? Four studies 5,6,11,21 provide evidence for a temporal relationship.

Abraham et al 2012a 5 examine medical encounter data from the Defense Medical Surveillance System of all deployed personnel as of December 31, 2005 (approximately 2.3 million records). Using ICD-9 codes, they compared pre- and post-deployment medical encounter rates for the following conditions:

  • Acute respiratory infections
  • Other diseases of the upper respiratory tract
  • Pneumonia and influenza
  • Asthma/chronic obstructive pulmonary disease (COPD) and allied conditions
  • Pneumoconiosis and other lung diseases due to external agents
  • Other diseases of the respiratory system
  • Symptoms involving respiratory system

The authors find that, all diagnostic codes combined, there was a decrease in the number of respiratory system encounters: 300.6 encounters per 1000 person-years pre-deployment to 276.2 encounters per 1000 person-years post-deployment. However, when examining specific ICD codes, they found a 25% increase in asthma/chronic obstructive pulmonary disease encounters post-deployment (p<0.05).

Significantly, the authors report different patterns for personnel deployed only once versus personnel
with multiple deployments. While single deployer obstructive pulmonary disease (asthma/COPD)
encounters rose from 20.4 encounters/1000 person-years pre-deployment to 30.1 post-deployment,
there was no such increase for multiple deployers during the same period.

This may be interpreted to indicate that a subset of initial personnel deployed to SWATO had an underlying susceptibility to some respiratory diseases. After their initial deployment, these individuals would be at higher risk for developing respiratory conditions that would then prevent them from being deployed further. This explanation is bolstered by the pattern seen in personnel with multiple encounters. While the number of medical encounters for at least one respiratory system diagnosis steadily increases from the first through third deployments, by the fourth deployment the number of encounters drops. This tells us that while those with the highest susceptibility drop out of the deployment pool early on, those with less susceptibility slowly increase in encounters over time until, by the fourth deployment, only personnel with the lowest level of susceptibility remain in the deployment pool.

Gwini et al 2016 use a two-wave questionnaire to survey Australian veterans of the 1990 Gulf War (similar to the design used by the Millenium Cohort Study). Veterans were surveyed first between 2000-2002 and then again between 2011-2012. Participants were presented with a 63-item symptom checklist. Based on the number of symptoms reported at Wave 1 (which would be approximately 10 years following their deployment) participants were classified into Low, Moderate, and High symptom categories. At both waves, veterans were also asked whether a doctor had diagnosed them with a range of diseases. Veterans who did not report being diagnosed with a disease at Wave 1 but who did report the diagnosis of the disease at Wave 2 (approximately ten years later) would be considered new onset cases. The authors then examined whether there was any difference between low, moderate, and high symptom veterans and the new onset of these diseases between Wave 1 and Wave 2 of the study.

After adjusting for a number of covariates, including smoking status, the authors report a 112% higher rate of newly diagnosed asthma in the high symptom group compared to the low symptom group. This difference did not reach statistical significance due to the relatively small number of new diagnoses during that period (2.7% [n=7] increase in new asthma diagnoses in the low symptom group versus 4.4% increase in new asthma diagnoses in the high symptom group [n=3]). However, the difference between low versus high symptom veterans could point to a subset of higher versus lower susceptibility personnel similar to the pattern described in Abraham et al described above.

As noted above, Smith et al 2009 11 also reported on new onset asthma and chronic bronchitis/emphysema. While these authors did not find a difference in the rates of new onset diseases when comparing deployers to non-deployers, they did find that new onset diagnoses was associated with service branch among deployers. So, even if the rates of new onset diagnoses were equivalent within the three-year period between MCS waves, the reasons for the development of the new disease appear to be different. This difference appears to be related to divergent experiences of Army and Marine personnel during deployment compared to non-deployers.

Finally, as noted above, only two articles 21,25 by researchers at the Joint Pathology Center provide evidence on the development of ILDs among deployed and non-deployed military. Because the Lewin-Smith et al 2021 is an expansion and enhancement of the previous Madar 2017 et al study, only the findings of the later article are discussed here. While the authors’ exclusion of any cases where biopsy was carried out prior to deployment ensured that a positive diagnosis of ILD could have happened only after deployment, we cannot know for certain whether some proportion of the deployers included in the analysis had occult or undiagnosed ILDs at the time of service.

The development of ILDs was rare over the time period examined (2002-2015) in both deployers and non-deployers; though this is unsurprising given that ILDs are diseases that appear most commonly in older adults (60-70 yrs) 19 and the median age of the deployers in this dataset was 39 years for deployers and 43 for non-deployers (matched sample). However, the authors report different rates of diseases for deployers and non-deployers, with some forms of ILD more evident in non-deployers (e.g., organizing pneumonia, fibrous pleuritis) while other forms of ILD more evident in deployers (e.g. constrictive bronchiolitis, smooth muscle disease, usual interstitial pneumonia). (See Q10) Similar to some of the articles described above, these differences may suggest different etiological pathways (i.e., different sets of causes) for deployers versus non-deployers.

Summary: There is evidence that following deployment there is (1) an increase in respiratory symptom complaints, (2) a decrease respiratory functionality, and (3) the diagnosis of different respiratory diagnoses among some but not all deployers. Further, there is evidence that even when these same diseases and conditions manifest in non-deployed military, their causes may be different than in deployed military.

While the purpose of this synthesis was to evaluate the evidence for a temporal relationship between exposure to hazards in the SWATO and respiratory diseases and conditions, the synthesis found that the causal relationship between exposure and respiratory disease is neither necessary nor sufficient, but rather is complex.

If the relationship between exposure and disease was necessary, then only military personnel who were deployed would develop certain diseases.

If the relationship between exposure and disease was sufficient, then every deployer would develop certain diseases.

As it stands, the explanation that would best explain the variation seen above is that the manifestation of respiratory diseases in general (and interstitial lung diseases in particular) in veterans is some combination of baseline susceptibility combined with a particular combination of sufficient component cause 26 exposure. Or, put another way, respiratory diseases in conditions in general, and ILDs in particular, are the result of a “multi-hit” susceptibility/exposure combination. 27-29

In the next section, we examine the literature to identify possible individual, occupational and exposure characteristics that may help explain some of the patterns identified above.

4.4 EXPLANATIONS

Table 1 provides an overview of the subject, occupational and exposure related characteristics associated with the development of a respiratory disease following deployment.

4.4.1 Veteran Characteristics: Compound and Synergistic Sources of Inflammation?

Several characteristics appear to be consistently associated with an increased risk of developing a respiratory disease or condition:

  • Being obese 7,14
  • Having PTSD 7,16
  • Being older 7,10,23
  • Being Hispanic 7,10

It is notable that both obesity 30 and PTSD, are pro-inflammatory states. 31,32 While precise pathways are complex and have yet to be fully elucidated, both conditions involve inflammatory pathways that may interact with, and in some cases worsen, inflammatory processes involved in respiratory disorders and perhaps disease progression. 28,29 For instance, with the heightened inflammation associated with PTSD 31 , activated immune cells release pro-inflammatory cytokines (such as interleukins, tumor necrosis factor- alpha (TNF-α)) which signal to lung epithelial cells, activating or enhancing immune response. Additionally, neutrophils and macrophages generate reactive oxygen species (ROS) and reactive nitrogen species (RNS) during their activation. These molecules can directly damage lung epithelial cells exacerbating existing airborne hazard induced inflammation 33 . With respect to the fibrotic processes characteristic of ILDs, chronic activation of these immune cells can lead to fibrosis, characterized by excessive collagen deposition and tissue remodeling. 34 With obesity, adipokines may act as mediators of pro-inflammatory changes that lead to interstitial lung abnormalities and fibrosis. Chronic inflammation triggered by dysfunctional adipose tissue can impact lung health and contribute to ILD progression. 35 Aging is an established risk factor for ILD 29 and so, like obesity and PTSD would reasonably serve to increase susceptibility to lung diseases, in particular ILDs.

The evidence for sex and smoking are less consistent in this literature. While smoking is an established risk factor for lung disease 33 , it is unclear how sex could affect differential rates of lung disease among military personnel. It is possible that higher levels of some types of stress experienced by women in the military. For instance, compared to their male counterparts, women in service face a higher risk of exposure to interpersonal stressors and abuse including sexual assault, sexual harassment, and gender harassment 36 . Additionally, compared to their male counterparts, service women face higher levels of family stress as well. 37 The integrated stress response has been associated as a critical pathway in the pathogenesis of various diseases including pulmonary fibrosis 38 and oxidative stress potentiates inflammatory activities in the lung, favoring the progression of chronic airway diseases. 39 Thus, differences in stress levels between male and female military personnel may serve to additionally increase the susceptibility to certain types of lung disease.

As we noted above, an underlying susceptibility—which could be related to a baseline pro-inflammatory state—could explain, in part, why some deployers, but not others, report higher incidence of respiratory diseases and conditions than others.

4.4.2 Occupational Characteristics

Regarding occupational exposures in the military, the evidence is somewhat mixed. Two characteristics are consistent across studies:

  • Enlisted military personnel have a greater risk than officers 5,7,11
  • Army has a greater risk compared to other branches. 5,7,10,11

It is unclear whether the increased risk for these groups is a function of different levels of exposure to airborne hazards, increased levels of stress, or some other factor. While there is evidence for increased risk of respiratory diseases and conditions associated with combat roles 7 , this evidence is inconsistent. It may be that within-occupation variations and specific duty assignments provide more accurate estimates of exposure than crude MOS categories. As noted by Zell-Baran et al 2019:

Factors other than MOS code such as deployment location, deployment date, presence of a burn
pit, and job duties in theatre are needed to inform likelihood and intensity of exposure to burn pit
smoke as well as to seasonal dust exposure events such as sandstorms. 40

4.4.3 Exposure Variation Characteristics

Exposure variation was measured in terms of length of deployment 5,10 , number of deployments 5 , proximity to airborne hazard 10,13 , location 5,10 , and acute weather events. 13 Other literature, not discussed above, also attempts to operationalize level of exposure based on these characteristics 41-55 , but, as with the above literature, the findings are not unequivocal.

In summary: research focused on respiratory changes pre- to post-deployment supports a temporal association between exposure to hazards in the SWATO and changes in symptoms, pulmonary function, and disease diagnosis. However, this appears to be true only for a subset of deployed military personnel. Research appears to suggest that an underlying susceptibility plays a part in addition to being exposed to multiple pro inflammatory states.

5 UNCERTAINTY

Outcome Misclassification in the Reference Populations: ILDs are difficult to diagnose and are often misdiagnosed. 24,56,57 One study found that the most common misdiagnoses were asthma (13.5%), pneumonia (13.0%) and bronchitis (12.3%). A meta-analysis (n=14 studies) spanning pre and post 911 military conflicts found that deployers were 27.5% (<0.001) more likely than non-deployers to have an asthma diagnosis. It is highly likely that many of these were misdiagnoses of ILD-related problems. Assuming that the misdiagnoses were balanced between deployers and non-deployers, this would place the odds of deployers having ILD conditions higher than this estimate compared to non-deployers (that is, because of the known bias toward the null for healthy warrior 17 and exposure misclassification biases, we would expect that the odds of deployers having ILD-related conditions would be substantially higher than 30% compared to non-deployers).

Related to the above, especially in the military population, there is some uncertainty regarding the definition and differentiation of different lung diseases characterized by pathological inflammation and fibrotic activity in the airways. 58,59 Additionally, there is evidence that the way that exposure-related diseases manifest in the military population may be quite different compared to civilian populations. 60 Thus, our confidence in the relative prevalence of any particular ILD in the deployed versus non-deployed population is somewhat decreased.

Mechanistic Pathways for Different Interstitial Diseases: Though there is mechanistic evidence to indicate a causal between airborne hazards present in the SWATO and the combined inflammatory and fibrotic pathologies (link to Q6-7), it is unclear how differences in exposures between deployed and non-deployed would result in disproportions in risk of some specific diseases (e.g., organizing pneumonia). Research demonstrates that non-deployed military are subject to many of the same hazardous occupational exposures as deployed military—only at decreased rates 18 . Differences in origin, dosage and intensity of exposure as well as length of exposure to these occupational hazards may differentiate the pathogenesis of ILDs in deployers versus non-deployers.

Research Underpowered for Rare Diseases: Because ILD diagnoses are rare, confidence intervals are wide even in relatively large datasets. So, it is unlikely that comparisons between deployed and non-deployed military will ever reach strong statistical significance. However, given known biases in the military research, it is highly likely that the risk of ILD-related conditions in the deployed population is much higher than is evident in the literature (see Known Biases, above).

6. STRENGTH OF EVIDENCE

7 ALTERNATIVE EXPLANATIONS

The most plausible alternative explanations for differences in the risk of different ILDs between deployed versus non-deployed military are:

  • Differences in prevalence of smoking (there is evidence that deployers are more likely to smoke than non-deployers)
  • Differences in occupational or environmental exposures following separation from military service.

Regarding smoking: The majority of the studies either adjusted for smoking statistically or by design. Thus, while there is evidence for differences in post-deployment conditions between smokers and non-smokers, it is clear that changes cannot be attributed simply to smoking.

Regarding differences in occupational and environmental exposures, there is no available evidence to suggest that, following service, formerly deployed versus non-deployed veterans have differential exposure to pathogens shown to be associated with ILD.

 

9 RISK OF BIAS

The risk of bias assessment for the included articles is presented below.

9.1 COHORT

Figure 3 . Cohort Risk of Bias

9.2 CASE SERIES

Figure 4 . Case Series Risk of Bias

9.3 CASE CONTROL

Figure 5 . Case-Control Risk of Bias

On balance, the risk of bias was generally moderate across the different studies and study types. Lack of adjustment for confounding and attrition between measurements were the primary concerns for several studies. As noted above, lack of adjustment could lead to an overestimate of effect. Attrition bias could lead to either underestimates of effect (most likely for Morris et al 2019) or overestimates of effect (possible with Smith et al 2009 if subjects less likely to be experiencing problems responded to the second panel at a lower rate). Because of differences in subject selection and design, each study suffered from its own biases so that there is no general conclusion that can be made regarding other biases that may compound across studies.

10 METHODOLOGICAL NOTE

 

11 REFERENCES

1. Obernolte H, Niehof M, Braubach P, et al. Cigarette smoke alters inflammatory genes and the extracellular matrix—investigations on viable sections of peripheral human lungs. Cell and Tissue Research. 2022:1-12.
2. Maccarone JR, Sterns OR, Timmons A, et al. Deployment-related Cigarette Smoking Behaviors and Pulmonary Function Among U.S. Veterans. Mil Med. Mar 25 2024;doi:10.1093/milmed/usae049
3. Harte CB, Proctor SP, Vasterling JJ. Prospective Examination of Cigarette Smoking Among Iraq- Deployed and Nondeployed Soldiers: Prevalence and Predictive Characteristics. Annals of Behavioral Medicine. 2014;48(1):38-49. doi:10.1007/s12160-013-9584-5
4. Pauchet A, Chaussavoine A, Pairon JC, et al. Idiopathic Pulmonary Fibrosis: What do we Know about the Role of Occupational and Environmental Determinants? A Systematic Literature Review and Meta-Analysis. J Toxicol Environ Health B Crit Rev. Oct 3 2022;25(7):372-392. doi:10.1080/10937404.2022.2131663
5. Abraham JH, DeBakey SF, Reid L, Zhou J, Baird CP. Does deployment to Iraq and Afghanistan affect respiratory health of US military personnel? J Occup Environ Med. Jun 2012;54(6):740-5. doi:10.1097/JOM.0b013e318252969a
6. Gwini SM, Kelsall HL, Ikin JF, Sim MR, McFarlane AC, Forbes AB. New onset of chronic diseases and changes in lifestyle risk factors among Gulf War veterans. Journal of Occupational and Environmental Medicine. 2016;58(8):770-777.
7. Rivera AC, Powell TM, Boyko EJ, et al. New-onset asthma and combat deployment: findings from the Millennium Cohort Study. American journal of epidemiology. 2018;187(10):2136-2144.
8. Roop SA, Niven AS, Calvin BE, Bader J, Zacher LL. The prevalence and impact of respiratory symptoms in asthmatics and nonasthmatics during deployment. Military medicine. 2007;172(12):1264- 1269.
9. Shorr AF, Scoville SL, Cersovsky SB, et al. Acute eosinophilic pneumonia among US Military personnel deployed in or near Iraq. Jama. Dec 22 2004;292(24):2997-3005. doi:10.1001/jama.292.24.2997
10. Smith B, Wong CA, Boyko EJ, et al. The effects of exposure to documented open-air burn pits on respiratory health among deployers of the Millennium Cohort Study. J Occup Environ Med. Jun 2012;54(6):708-16. doi:10.1097/JOM.0b013e31825107f9
11. Smith B, Wong CA, Smith TC, Boyko EJ, Gackstetter GD, Margaret AKRftMCST. Newly reported respiratory symptoms and conditions among military personnel deployed to Iraq and Afghanistan: a prospective population-based study. Am J Epidemiol. Dec 1 2009;170(11):1433-42. doi:10.1093/aje/kwp287
12. Woods MC U, Jeffrey T, Walter MC U, Robert J, Houle MC U, Mateo C, Barber BS, Morris MJ. The effect of deployment on pulmonary function in military personnel with asthma. presented at: Military Medicine; 2022;
13. Abraham JH, Baird CP. A case-crossover study of ambient particulate matter and cardiovascular and respiratory medical encounters among US military personnel deployed to southwest Asia. J Occup Environ Med. Jun 2012;54(6):733-9. doi:10.1097/JOM.0b013e318253356c
14. Morris MJ, Skabelund AJ, Rawlins FA, 3rd, Gallup RA, Aden JK, Holley AB. Study of Active Duty Military Personnel for Environmental Deployment Exposures: Pre- and Post-Deployment Spirometry (STAMPEDE II). Respir Care. May 2019;64(5):536-544. doi:10.4187/respcare.06396
15. Szema AM, Peters MC, Weissinger KM, Gagliano CA, Chen JJ. New-onset asthma among soldiers serving in Iraq and Afghanistan. 2010:67.
16. McMahon MJ, Holley AB, Warren WA, et al. Posttraumatic Stress Disorder Is Associated With a Decrease in Anaerobic Threshold, Oxygen Pulse, and Maximal Oxygen Uptake. Chest. Sep 2021;160(3):1017-1025. doi:10.1016/j.chest.2021.03.057
17. Haley RW. Point: bias from the &quot;healthy-warrior effect&quot; and unequal follow-up in three government studies of health effects of the Gulf War. Am J Epidemiol. Aug 15 1998;148(4):315-23. doi:10.1093/oxfordjournals.aje.a009645
18. Barth SK, Dursa EK, Peterson MR, Schneiderman A. Prevalence of respiratory diseases among veterans of Operation Enduring Freedom and Operation Iraqi Freedom: results from the National Health Study for a New Generation of U.S. Veterans. Mil Med. Mar 2014;179(3):241-5. doi:10.7205/MILMED-D- 13-00338
19. Sack C, Raghu G. Idiopathic pulmonary fibrosis: unmasking cryptogenic environmental factors. European Respiratory Journal. 2019;53(2)doi:10.1183/13993003.01699-2018
20. Morris MJ, Zacher LL, Jackson DA. Investigating the respiratory health of deployed military personnel. Mil Med. Oct 2011;176(10):1157 61. doi:10.7205/milmed-d-10-00436
21. Lewin-Smith MR, Martinez A, Brooks DI, Franks TJ. Pulmonary Pathology Diagnoses in the US Military During the Global War on Terrorism. Lung. Aug 2021;199(4):345-355. doi:10.1007/s00408-021- 00446-6
22. Belding JN, Castañeda SF, Jacobson IG, et al. The Millennium Cohort Study: the first 20 years of research dedicated to understanding the long-term health of US Service Members and Veterans. Annals of epidemiology. 2022;67:61-72.
23. Morris MJ, Walter RJ, McCann ET, et al. Clinical Evaluation of Deployed Military Personnel With Chronic Respiratory Symptoms: Study of Active Duty Military for Pulmonary Disease Related to Environmental Deployment Exposures (STAMPEDE) III. Chest. Jun 2020;157(6):1559-1567. doi:10.1016/j.chest.2020.01.024

24. Spagnolo P, Ryerson CJ, Putman R, et al. Early diagnosis of fibrotic interstitial lung disease: challenges and opportunities. The Lancet Respiratory Medicine. 2021;9(9):1065-1076.
25. Madar CS, Lewin-Smith MR, Franks TJ, Harley RA, Klaric JS, Morris MJ. Histological Diagnoses of Military Personnel Undergoing Lung Biopsy After Deployment to Southwest Asia. Lung. Aug 2017;195(4):507-515. doi:10.1007/s00408-017-0009-2
26. Shimonovich M, Pearce A, Thomson H, Keyes K, Katikireddi SV. Assessing causality in epidemiology: revisiting Bradford Hill to incorporate developments in causal thinking. European journal of epidemiology. 2020;36(9):873-887. doi:10.1007/s10654-020-00703-7
27. Berman R, Rose CS, Downey GP, Day BJ, Chu HW. Role of particulate matter from Afghanistan and Iraq in deployment-related lung disease. Chemical Research in Toxicology. 2021;34(12):2408-2423.
28. Pavord ID, Birring SS, Berry M, Green RH, Brightling CE, Wardlaw AJ. Multiple inflammatory hits and the pathogenesis of severe airway disease. Eur Respir J. May 2006;27(5):884-8. doi:10.1183/09031936.06.00128105
29. Korfei M, MacKenzie B, Meiners S. The ageing lung under stress. Eur Respir Rev. Jun 30 2020;29(156)doi:10.1183/16000617.0126 2020
30. Dixon AE, Poynter ME. Mechanisms of Asthma in Obesity. Pleiotropic Aspects of Obesity Produce Distinct Asthma Phenotypes. Am J Respir Cell Mol Biol. May 2016;54(5):601-8. doi:10.1165/rcmb.2016-0017PS
31. Kim TD, Lee S, Yoon S. Inflammation in Post-Traumatic Stress Disorder (PTSD): A Review of Potential Correlates of PTSD with a Neurological Perspective. Antioxidants (Basel). Jan 26 2020;9(2)doi:10.3390/antiox9020107
32. Smith EG, Hentig J, Martin C, et al. Cytokine Profiles Differentiate Symptomatic from Asymptomatic PTSD in Service Members and Veterans with Chronic Traumatic Brain Injury. Biomedicines. 2022;10(12):3289.
33. Hiemstra PS, McCray PB, Jr., Bals R. The innate immune function of airway epithelial cells in inflammatory lung disease. Eur Respir J. Apr 2015;45(4):1150-62. doi:10.1183/09031936.00141514
34. Suwara MI, Green NJ, Borthwick LA, et al. IL-1alpha released from damaged epithelial cells is sufficient and essential to trigger inflammatory responses in human lung fibroblasts. Mucosal Immunol. May 2014;7(3):684-93. doi:10.1038/mi.2013.87
35. Macklin M, Thompson C, Kawano-Dourado L, et al. Linking Adiposity to Interstitial Lung Disease: The Role of the Dysfunctional Adipocyte and Inflammation. Cells. Sep 5 2023;12(18)doi:10.3390/cells12182206
36. Tepe V, Yarnell A, Nindl BC, Van Arsdale S, Deuster PA. Women in Combat: Summary of Findings and a Way Ahead. Mil Med. Jan 2016;181(1 Suppl):109-18. doi:10.7205/MILMED-D-15-00409
37. Bray RM, Camlin CS, Fairbank JA, Dunteman GH, Wheeless SC. The Effects of Stress on Job Functioning of Military Men and Women. Armed Forces Soc. Apr 1 2001;27(3):397-417. doi:10.1177/0095327X0102700304

38. Emanuelli G, Nassehzadeh-Tabriz N, Morrell NW, Marciniak SJ. The integrated stress response in pulmonary disease. Eur Respir Rev. Sep 30 2020;29(157)doi:10.1183/16000617.0184-2020
39. Albano GD, Gagliardo RP, Montalbano AM, Profita M. Overview of the Mechanisms of Oxidative Stress: Impact in Inflammation of the Airway Diseases. Antioxidants (Basel). Nov 13 2022;11(11)doi:10.3390/antiox11112237
40. Zell-Baran LM, Meehan R, Wolff J, et al. Military Occupational Specialty Codes: Utility in Predicting Inhalation Exposures in Post-9/11 Deployers. J Occup Environ Med. Dec 2019;61(12):1036- 1040. doi:10.1097/JOM.0000000000001731
41. Cowan DN, Lange JL, Heller J, Kirkpatrick J, DeBakey S. A case-control study of asthma among U.S. Army Gulf War veterans and modeled exposure to oil well fire smoke. Mil Med. Sep 2002;167(9):777-82.
42. Dhoma S, Gottschall B, Robinson M, et al. Lung Disease In Deployers Returning From Afghanistan And Iraq. presented at: American Thoracic Society International Conference; 2013; Philadelphia, PA. Session Occupational and Environmental Determinants of Lung Function.
43. Abraham JH, Eick-Cost A, Clark LL, et al. A retrospective cohort study of military deployment and postdeployment medical encounters for respiratory conditions. Mil Med. May 2014;179(5):540-6. doi:10.7205/MILMED-D-13-00443
44. Armed Forces Health Surveillance C. Associations between repeated deployments to OEF/OIF/OND, October 2001-December 2010, and post-deployment illnesses and injuries, active component, U.S. Armed Forces. Vol. 18. 2011:2-11. MSMR. 2158-0111 (Print) 2152 8217 (Linking). Jul. https://www.ncbi.nlm.nih.gov/pubmed/21815709
45. Falvo MJ, Abraham JH, Osinubi OY, et al. Bronchodilator Responsiveness and Airflow Limitation Are Associated With Deployment Length in Iraq and Afghanistan Veterans. J Occup Environ Med. Apr 2016;58(4):325-8. doi:10.1097/JOM.0000000000000675
46. Falvo MJ, Sotolongo AM, Osinubi OY, et al. Gas Exchange Is Impaired In Iraq/afghanistan Veterans And Related To Deployment Length. presented at: American Thoracic Society International Conference; 2015; Denver, CO. Session OCCUPATION, OBESITY, AND LUNG HEALTH.
47. Holley AB, Sobieszczyk M, Perkins M, et al. Lung function abnormalities among service members returning from Iraq or Afghanistan with respiratory complaints. Respiratory Medicine. 2016;118:84-87.
48. Klein-Adams JC, Sotolongo AM, Serrador JM, Ndirangu DS, Falvo MJ. Exercise-induced bronchoconstriction in Iraq and Afghanistan Veterans with deployment-related exposures. Military Medicine. 2020;185(3-4):e389-e396.
49. Liu J, Lezama N, Gasper J, et al. Burn pit emissions exposure and respiratory and cardiovascular conditions among airborne hazards and open burn pit registry participants. Journal of Occupational and Environmental Medicine. 2016;58(7):e249-e255.
50. Petruccelli BP, Goldenbaum M, Scott B, et al. Health effects of the 1991 Kuwait oil fires: a survey of US army troops. Journal of occupational and environmental medicine. 1999:433-439.

51. Proctor S, Heeren T, White R, et al. Health status of Persian Gulf War veterans: self-reported symptoms, environmental exposures and the effect of stress. International Journal of Epidemiology. 1998;27(6):1000-1010.
52. Pugh MJ, Jaramillo CA, Leung K-w, et al. Increasing prevalence of chronic lung disease in veterans of the wars in Iraq and Afghanistan. Military medicine. 2016;181(5):476-481.
53. Rohrbeck P, Hu Z, Mallon TM. Assessing health outcomes after environmental exposures associated with open pit burning in deployed US service members. Journal of occupational and environmental medicine. 2016;58(8 Suppl 1):S104.
54. Sharkey JM, Abraham JH, Clark LL, et al. Postdeployment respiratory health care encounters following deployment to Kabul, Afghanistan: a retrospective cohort study. Military medicine. 2016;181(3):265-271.
55. Smith TC, Heller JM, Hooper TI, Gackstetter GD, Gray GC. Are Gulf War veterans experiencing illness due to exposure to smoke from Kuwaiti oil well fires? Examination of Department of Defense hospitalization data. Am J Epidemiol. May 15 2002;155(10):908-17. doi:10.1093/aje/155.10.908
56. Akhter N, Rizvi NA. Interstitial lung diseases misdiagnosed as tuberculosis. Pakistan journal of medical sciences. 2018;34(2):338.
57. Cosgrove GP, Bianchi P, Danese S, Lederer DJ. Barriers to timely diagnosis of interstitial lung disease in the real world: the INTENSITY survey. BMC pulmonary medicine. 2018;18:1-9.
58. Lewin-Smith MR, Morris MJ, Galvin JR, Harley RA, Franks T. The problems with constrictive bronchiolitis: histopathological and radiological perspectives. Airborne hazards related to deployment Fort Sam Houston, TX: Borden Institute, US Army Medical Department and School. 2015:153-161.
59. Falvo MJ, Sotolongo AM, Osterholzer JJ, et al. Consensus statements on deployment-related respiratory disease, inclusive of constrictive bronchiolitis: a modified Delphi study. Chest. 2023;163(3):599-609.
60. Banks DE, Bolduc CA, Ali S, Morris MJ. Constrictive Bronchiolitis Attributable to Inhalation of Toxic Agents: Considerations for a Case Definition. J Occup Environ Med. Jan 2018;60(1):90-96. doi:10.1097/JOM.0000000000001176