Baseline self reported functional health and vulnerability to post-traumatic stress disorder after combat deployment: prospective US military cohort study

Objective To determine if baseline functional health status, as measured by SF-36 (veterans), predicts new onset symptoms or diagnosis of post-traumatic stress disorder among deployed US military personnel with combat exposure

Exploratory factor analysis of self-reported symptoms in a large, population-based military cohort

<p>Abstract</p> <p>Background</p> <p>US military engagements have consistently raised concern over the array of health outcomes experienced by service members postdeployment. Exploratory factor analysis has been used in studies of 1991 Gulf War-related illnesses, and may increase understanding of symptoms and health outcomes associated with current military conflicts in Iraq and Afghanistan. The objective of this study was to use exploratory factor analysis to describe the correlations among numerous physical and psychological symptoms in terms of a smaller number of unobserved variables or factors.</p> <p>Methods</p> <p>The Millennium Cohort Study collects extensive self-reported health data from a large, population-based military cohort, providing a unique opportunity to investigate the interrelationships of numerous physical and psychological symptoms among US military personnel. This study used data from the Millennium Cohort Study, a large, population-based military cohort. Exploratory factor analysis was used to examine the covariance structure of symptoms reported by approximately 50,000 cohort members during 2004-2006. Analyses incorporated 89 symptoms, including responses to several validated instruments embedded in the questionnaire. Techniques accommodated the categorical and sometimes incomplete nature of the survey data.</p> <p>Results</p> <p>A 14-factor model accounted for 60 percent of the total variance in symptoms data and included factors related to several physical, psychological, and behavioral constructs. A notable finding was that many factors appeared to load in accordance with symptom co-location within the survey instrument, highlighting the difficulty in disassociating the effects of question content, location, and response format on factor structure.</p> <p>Conclusions</p> <p>This study demonstrates the potential strengths and weaknesses of exploratory factor analysis to heighten understanding of the complex associations among symptoms. Further research is needed to investigate the relationship between factor analytic results and survey structure, as well as to assess the relationship between factor scores and key exposure variables.</p

Early mortality experience in a large military cohort and a comparison of mortality data sources

<p>Abstract</p> <p>Background</p> <p>Complete and accurate ascertainment of mortality is critically important in any longitudinal study. Tracking of mortality is particularly essential among US military members because of unique occupational exposures (e.g., worldwide deployments as well as combat experiences). Our study objectives were to describe the early mortality experience of Panel 1 of the Millennium Cohort, consisting of participants in a 21-year prospective study of US military service members, and to assess data sources used to ascertain mortality.</p> <p>Methods</p> <p>A population-based random sample (n = 256,400) of all US military service members on service rosters as of October 1, 2000, was selected for study recruitment. Among this original sample, 214,388 had valid mailing addresses, were not in the pilot study, and comprised the group referred to in this study as the invited sample. Panel 1 participants were enrolled from 2001 to 2003, represented all armed service branches, and included active-duty, Reserve, and National Guard members. Crude death rates, as well as age- and sex-adjusted overall and age-adjusted, category-specific death rates were calculated and compared for participants (n = 77,047) and non-participants (n = 137,341) based on data from the Social Security Administration Death Master File, Department of Veterans Affairs (VA) files, and the Department of Defense Medical Mortality Registry, 2001-2006. Numbers of deaths identified by these three data sources, as well as the National Death Index, were compared for 2001-2004.</p> <p>Results</p> <p>There were 341 deaths among the participants for a crude death rate of 80.7 per 100,000 person-years (95% confidence interval [CI]: 72.2,89.3) compared to 820 deaths and a crude death rate of 113.2 per 100,000 person-years (95% CI: 105.4, 120.9) for non-participants. Age-adjusted, category-specific death rates highlighted consistently higher rates among study non-participants. Although there were advantages and disadvantages for each data source, the VA mortality files identified the largest number of deaths (97%).</p> <p>Conclusions</p> <p>The difference in crude and adjusted death rates between Panel 1 participants and non-participants may reflect healthier segments of the military having the opportunity and choosing to participate. In our study population, mortality information was best captured using multiple data sources.</p

Health impact of US military service in a large population-based military cohort: findings of the Millennium Cohort Study, 2001-2008

<p>Abstract</p> <p>Background</p> <p>Combat-intense, lengthy, and multiple deployments in Iraq and Afghanistan have characterized the new millennium. The US military's all-volunteer force has never been better trained and technologically equipped to engage enemy combatants in multiple theaters of operations. Nonetheless, concerns over potential lasting effects of deployment on long-term health continue to mount and are yet to be elucidated. This report outlines how findings from the first 7 years of the Millennium Cohort Study have helped to address health concerns related to military service including deployments.</p> <p>Methods</p> <p>The Millennium Cohort Study was designed in the late 1990s to address veteran and public concerns for the first time using prospectively collected health and behavioral data.</p> <p>Results</p> <p>Over 150 000 active-duty, reserve, and National Guard personnel from all service branches have enrolled, and more than 70% of the first 2 enrollment panels submitted at least 1 follow-up survey. Approximately half of the Cohort has deployed in support of operations in Iraq and Afghanistan.</p> <p>Conclusion</p> <p>The Millennium Cohort Study is providing prospective data that will guide public health policymakers for years to come by exploring associations between military exposures and important health outcomes. Strategic studies aim to identify, reduce, and prevent adverse health outcomes that may be associated with military service, including those related to deployment.</p

Challenges of self-reported medical conditions and electronic medical records among members of a large military cohort

<p>Abstract</p> <p>Background</p> <p>Self-reported medical history data are frequently used in epidemiological studies. Self-reported diagnoses may differ from medical record diagnoses due to poor patient-clinician communication, self-diagnosis in the absence of a satisfactory explanation for symptoms, or the "health literacy" of the patient.</p> <p>Methods</p> <p>The US Department of Defense military health system offers a unique opportunity to evaluate electronic medical records with near complete ascertainment while on active duty. This study compared 38 self-reported medical conditions to electronic medical record data in a large population-based US military cohort. The objective of this study was to better understand challenges and strengths in self-reporting of medical conditions.</p> <p>Results</p> <p>Using positive and negative agreement statistics for less-prevalent conditions, near-perfect negative agreement and moderate positive agreement were found for the 38 diagnoses.</p> <p>Conclusion</p> <p>This report highlights the challenges of using self-reported medical data and electronic medical records data, but illustrates that agreement between the two data sources increases with increased surveillance period of medical records. Self-reported medical data may be sufficient for ruling out history of a particular condition whereas prevalence studies may be best served by using an objective measure of medical conditions found in electronic healthcare records. Defining medical conditions from multiple sources in large, long-term prospective cohorts will reinforce the value of the study, particularly during the initial years when prevalence for many conditions may still be low.</p

The physical and mental health of a large military cohort: baseline functional health status of the Millennium Cohort

<p>Abstract</p> <p>Background:</p> <p>The US military is currently involved in large, lengthy, and complex combat operations around the world. Effective military operations require optimal health of deployed service members, and both mental and physical health can be affected by military operations.</p> <p>Methods:</p> <p>Baseline data were collected from 77,047 US service members during 2001–2003 as part of a large, longitudinal, population-based military health study (the Millennium Cohort Study). The authors calculated unadjusted, adjusted, and weighted means for the Medical Outcomes Study Short Form 36-item Survey for Veterans physical (PCS) and mental component summary (MCS) scores over a variety of demographic and military characteristics at baseline.</p> <p>Results:</p> <p>The unadjusted mean PCS and MCS scores for this study were 53.4 (95% confidence interval: 53.3–53.4) and 52.8 (95% confidence interval: 52.7–52.9). Average PCS and MCS scores were slightly more favorable in this military sample compared to those of the US general population of the same age and sex. Factors independently associated with more favorable health status included male gender, being married, higher educational attainment, higher military rank, and Air Force service. Combat specialists had similar health status compared to other military occupations. Having been deployed to Southwest Asia, Bosnia, or Kosovo between 1998 and 2000 was not associated with diminished health status.</p> <p>Conclusion:</p> <p>The baseline health status of this large population-based military cohort is better than that of the US general population of the same age and sex distribution over the same time period, especially in older age groups. Deployment experiences during the period of 1998–2001 were not associated with decreased health status. These data will serve as a useful reference for other military health studies and for future longitudinal analyses.</p

Assessing nonresponse bias at follow-up in a large prospective cohort of relatively young and mobile military service members

<p>Abstract</p> <p>Background</p> <p>Nonresponse bias in a longitudinal study could affect the magnitude and direction of measures of association. We identified sociodemographic, behavioral, military, and health-related predictors of response to the first follow-up questionnaire in a large military cohort and assessed the extent to which nonresponse biased measures of association.</p> <p>Methods</p> <p>Data are from the baseline and first follow-up survey of the Millennium Cohort Study. Seventy-six thousand, seven hundred and seventy-five eligible individuals completed the baseline survey and were presumed alive at the time of follow-up; of these, 54,960 (71.6%) completed the first follow-up survey. Logistic regression models were used to calculate inverse probability weights using propensity scores.</p> <p>Results</p> <p>Characteristics associated with a greater probability of response included female gender, older age, higher education level, officer rank, active-duty status, and a self-reported history of military exposures. Ever smokers, those with a history of chronic alcohol consumption or a major depressive disorder, and those separated from the military at follow-up had a lower probability of response. Nonresponse to the follow-up questionnaire did not result in appreciable bias; bias was greatest in subgroups with small numbers.</p> <p>Conclusions</p> <p>These findings suggest that prospective analyses from this cohort are not substantially biased by non-response at the first follow-up assessment.</p