effect, it is important to consider the size of the sample and whether the study had the power to detect an effect of a given size.
Epidemiologic study designs differ in their ability to provide valid estimates of an association (Ellwood 1998). An important issue is that the studies reviewed by the committee were seldom designed to answer the question in the committee’s charge, that is, does exposure to deployment-related stress result in long-term adverse health and psychosocial effects. Cross-sectional studies generally provide a lower level of evidence than cohort and case-control studies. Determining whether a given statistical association rises to the level of causation requires inference (Hill 1965). As discussed by the International Agency for Research on Cancer in the preamble of its monographs evaluating cancer risks (for example, IARC 2004), a strong association is demonstrated by repeated observations in a number of different studies, specificity of effects, and an increased risk of disease with increasing exposure or a decline in risk after cessation of exposure. Those characteristics all strengthen the likelihood that an association seen in epidemiologic studies is a causal effect. Inferences from epidemiologic studies, however, are often limited to population or ecologic associations because of a lack of individual exposure information. Exposures are rarely, if ever, controlled in epidemiologic studies, and in most cases there is large uncertainty in the assessment of exposure. To assess whether explanations other than causality are responsible for an observed association, one must bring together evidence from different studies and apply well-established criteria, which have been refined over more than a century (Evans 1976; Hill 1965; Susser 1973, 1977, 1988, 1991; Wegman et al. 1997). For a review of those criteria, see the 2004 report of the U.S. Surgeon General (Office of the Surgeon General-HHS 2004).
When examining the available epidemiologic studies, the committee addressed the question, “Does the available evidence support a causal relationship or an association between exposure (deployment to a war zone) and a health effect?” Even a causal relationship between deployment and a specific health effect would not mean that deployment invariably results in the health effect or that all cases of the effect are the result of deployment. Such complete correspondence between exposure and disease is the exception in large populations (IOM 1994). The committee evaluated the data and based its conclusions on the strength and coherence of the data in the selected epidemiologic studies that met its inclusion criteria. The major types of epidemiologic studies discussed in this chapter are cohort, case-control, and cross-sectional studies.
A cohort, or longitudinal, study follows a defined group, or cohort, over time. It can test hypotheses about whether an exposure to a specific stressor is related to the development of a health effect and can examine multiple health effects that may be associated with exposure to a given stressor. A cohort study starts by classifying study participants according to whether or not they have been exposed to the stressor under study, in this case deployment to a war zone. A cohort study compares health effects in individuals who have been exposed to the stressor in question with those without the exposure. Such a comparison can be used to estimate a risk difference or a relative risk, two statistics that measure association. The risk difference is the rate of disease or health effect in exposed persons minus the rate in unexposed persons. A value greater than zero (H0 = 0.0) implies that extra cases of disease or health effect are associated with the exposure. The relative risk or risk ratio is determined by dividing the rate of developing the disease in the exposed group by the rate in the nonexposed group. A relative risk greater than 1