Epidemiology confounding factors

When epidemiological data are available, the issues to be dealt with include selection of the appropriate study and control populations, evaluation of exposure levels and tissue doses, determination of the reliability of cancer ascertainment, allowance for the latent period and age distribution of cancers, control of biases and confounding factors, fitting of models to the data to characterize the dose-incidence relationship, and derivation of risk estimates with their associated ranges of uncertainty. 

When setting up epidemiological studies and when assessing their significance, it is important to be aware of confounding factors such as bias and the need for proper controls. For further details on epidemiology, the reader is referred to the bibliography. 

It has been suspected that low concentrations of serum cholesterol might be associated with an increased risk of cancer or overall mortality. All fibrates and statins cause cancer in rodents, but the relevance of this finding to man has been questioned (68). In an epidemiological study these risks were almost non-existent after adjusting for confounding factors. 

Criteria for the adequacy of epidemiologic studies are well recognized (Monson, 1990). They include, for example, proper selection and characterization of exposed and comparison groups, adequacy of the duration and quality of follow-up, proper identification and characterization of confounding factors, attention to potential methodologic biases, appropriate consideration of latency effects, valid ascertainment of the causes of morbidity and death, and the ability to detect specific responses. The statistical power to detect a particular response... 

A difficulty with epidemiologic studies at low doses is the inability to adequately control for potentially confounding factors to the extent necessary to exclude spurious observations, either positive or negative. Epidemiologic studies are not capable of detecting increased responses unless the excess relative risk is on the order of 30 to 40 percent or higher. 

Reproductive hazards in the workplaces can be identified through epidemiologic research, outcomes such as spontaneous abortions and malformations require large sample sizes that cannot usually be collected from single workplaces. Several workplaces need to be pooled and a coordinated effort is required in the execution of the studies. However, a systematic follow-up of the rates of spontaneous abortions and malformations by industrial physicians may offer clues to reproductive hazards. On other outcomes, such as birthweight of children and sperm abnormalities in exposed men, smaller sample sizes are required but many types of confounding factors may exist that impede the interpretation of the results. 

Unfortunately, whenever questionnaires are used to gather epidemiological data (which is much of the time), none of the conclusions ever have the reliability we achieve with planned experiments. In the example we looked at, we had collected data on both of the confounded factors and we could identify and eliminate the problem. However, if we had only gathered data on health status and not recorded respondents ages, we could well have mistakenly concluded that people s health in some way influenced their opinions. 

Evidence from well-conducted epidemiological studies does not support any meaningful associations between the intake of total fat, fat type or individual fatty acids and the risk of colon, breast or prostate cancer. Final proof of a null effect should come from randomized clinical trials. However, such trials seem unlikely because initiation of tumors may occur early in life, whereas the clinical symptoms arise late in life. The cost of appropriate trials would be prohibitive. Further advances, however, may come from improved dietary assessment and a better understanding of, and adjustment for, confounding factors in epidemiological studies. 

The design of the studies is very important, and control subjects should be of the same sex as the exposed subjects and as similar as possible in age and lifestyle. Those who set up and interpret epidemiological studies must be aware of sources of bias and any confounding factors, for example smoking or alcohol consumption by members of the population studied, especially when evaluating the incidence of certain diseases (for example, cancer or liver disease). 

For human evidence to provide the primary basis for a Category lA classification there must be reliable evidence of an adverse effect on reproduction in humans. Evidence used for classification should ideally be firom well conducted epidemiological studies which include the use of appropriate controls, balanced assessment, and due consideration of bias or confounding factors. Less rigorous data from studies in humans should be supplemented with adequate data firom studies in experimental animals and classification in Category IB should be considered. 

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