A Practical Approach, Second Edition=Ronald D. Ho.pdf

HUMAN STUDIES 829B. The Formation of CohortsIn the classical cohort study, a group of persons is identified because of an exposure and is thenfollowed with respect to the development of a disease, but this is seldom the case in reproductiveepidemiology. As exposures during pregnancy are of major interest, this approach necessitates thatwomen are followed into pregnancy with respect to their exposures. Even when this approachmakes it possible to obtain rather exact exposure information, it will usually result in small numbersof subjects; therefore, it remains difficult to study rare outcomes, such as congenital malformations.Very often, retrospective cohorts are formed instead, e.g., women who work at a specificworkplace, and information on previous pregnancies and their outcome is identified (ideally, thisshould include determination of whether exposure occurred during those pregnancies). There is aclear danger in this approach, notably with respect to occupational exposures. If women have atendency to stop working after childbirth (which is often the case and was previously even moreprevalent), women remaining in the workforce will be selected for previous poor reproductiveoutcome or subfertility. Any such cohort will thus have a tendency to show an abnormally highincidence of reproductive failures. This may also be true when a specific geographic area is studied;if the area is less suitable for families with small children, a differential emigration from the areamay occur after successful pregnancies, leaving couples with poor reproductive outcome.A third possibility is that the cohort is defined from recorded exposures during the pregnanciesto be studied, e.g., drugs taken, occupations held, place of living. The problem lies in identifyingsuch cohorts. Sometimes this can be done by use of prospective or retrospective records obtainedfor all pregnant women (e.g., by interviews in early pregnancy or after delivery), and sometimesit can be achieved by linkage of different registries, e.g., census information linked to medical birthregistry information.C. Comparison MaterialThe pregnancy outcome in the defined cohort must be compared with that of another group. Quiteoften, a comparison is made with the expected outcomes known from the entire population or areasonable sample of the population. If, for instance, the perinatal death rate is known in thepopulation, the rate in a specific cohort can be evaluated. The problem resembles that in case controlstudies; the cohort under study may have characteristics that by themselves influence pregnancyoutcome, e.g., maternal age distribution or socioeconomic level. This may be avoided by a methodsimilar to that used in the matched case control study, i.e., the comparison with another cohortshould be selected to ensure as many similarities with the study cohort as possible except for theexposure under study. If a specific industrial occupational exposure is of interest, women with otherindustrial jobs may form a suitable cohort for comparison. If nurses working in anesthesiology arestudied, nurses working in wards of internal medicine might be chosen as controls. 61 As when sickcontrols are used in case control studies, it must be remembered that the cohort of comparison mayalso be exposed to reproductive hazards.There are two main problems with the cohort approach: the difficulty in definition and selectionof cohorts, and the problem with size. One needs very large numbers to study rare outcomes, suchas specific congenital malformations, and even large cohorts may be insufficient. We made a studyof reproductive outcome among women working as dentists, dental assistants, or dental technicians,because of an alleged increased risk of having an infant with spina bifida. 62 We studied more than8000 such births and found 3 infants with spina bifida when the expected number was 4.2. Wecould thus not confirm the alleged risk, but in spite of the large size of the study group, it is possiblethat an increased risk exists. This is true because the observed number of 3 may be a randomlylow sample estimate of a true expected number of 8.8 (i.e., a doubling of the risk).© 2006 by Taylor & Francis Group, LLC