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A society's health status is not simply the sum of the health of individuals, but an emergent property. While epidemiology has evolved from the study of simple epidemics to the study of the determinants of population health, it is still appropriate to consider the population as the epidemiologist's patient. At the same time, the population is also our study subject-we study populations to identify ways to prevent disease in populations. This article illustrates some of the implications for the prevention of disease that result from treating society as our patient. [ABSTRACT FROM AUTHOR]

Previous evidence suggests that severe heat illness may cause permanent acute damage to the heart, kidneys, and liver, which may possibly lead to chronic and even fatal disorders. We investigated whether individuals who had been hospitalized for severe heat illness were at increased risk of cause-specific and total mortality. A cohort mortality study was conducted of male and female US Army personnel hospitalized for heat illness (HI) from 1971 to 2000 using appendicitis (APX) as the reference. Hospitalization records were acquired from the Total Army Injury and Health Outcomes Database (TAIHOD) for 3971 cases of HI and 17,233 APX reference cases. Subject vital status was established through the National Death Index. HI cases had a 40% increased risk of all-cause mortality compared to APX cases. Further examining cause-specific deaths, male cases of HI were at an increased rate of death from cardiovascular disease (CVD) (rate ratio (RR)=1.71, 95% confidence interval (CI): 1.01, 2.89) and ischemic heart disease (IHD) (RR=2.23, 95% CI: 1.02, 4.90) compared to APX reference cases. Our findings provide preliminary evidence for increased risk of mortality among those who have experienced prior hospitalization for heat illness. [Copyright &y& Elsevier]

The eruption of genetic research presents a tremendous opportunity to epidemiologists to improve our ability to identify causes of ill health. Epidemiologists have enthusiastically embraced the new tools of genomics and proteomics to investigate gene-environment interactions. We argue that neither the full import nor limitations of such studies can be appreciated without clarifying underlying theoretical models of interaction, etiologic fraction, and the fundamental concept of causality. We therefore explore different models of causality in the epidemiology of disease arising out of genes, environments, and the interplay between environments and genes. We begin from Rothman's "pie" model of necessary and sufficient causes, and then discuss newer approaches, which provide additional insights into multifactorial causal processes. These include directed acyclic graphs and structural equation models. Caution is urged in the application of two essential and closely related concepts found in many studies: interaction (effect modification) and the etiologic or attributable fraction. We review these concepts and present four important limitations. 1. Interaction is a fundamental characteristic of any causal process involving a series of probabilistic steps, and not a second-order phenomenon identified after first accounting for "main effects". 2. Standard methods of assessing interaction do not adequately consider the life course, and the temporal dynamics through which an individual's sufficient cause is completed. Different individuals may be at different stages of development along the path to disease, but this is not usually measurable. Thus, for example, acquired susceptibility in children can be an important source of variation. 3. A distinction must be made between individual-based and population-level models. Most epidemiologic discussions of causality fail to make this distinction. 4. At the population level, there is additional uncertainty in quantifying interaction and assigning etiologic fractions to different necessary causes because of ignorance about the components of the sufficient cause. [ABSTRACT FROM AUTHOR]