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Direct methods of obtaining information on cigarette smoking in occupational studies
Author(s) -
Marsh Gary M.,
Sachs David P. L.,
Callahan Catherine,
Leviton Laura C.,
Ricci Edmund,
Henderson Vivian
Publication year - 1988
Publication title -
american journal of industrial medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.7
H-Index - 104
eISSN - 1097-0274
pISSN - 0271-3586
DOI - 10.1002/ajim.4700130106
Subject(s) - medicine , confounding , environmental health , reliability (semiconductor) , data collection , epidemiology , cigarette smoking , validity , statistics , pathology , psychometrics , clinical psychology , power (physics) , physics , mathematics , quantum mechanics
Abstract Many occupational epidemiology studies require complete and accurate information on tobacco use to control for confounding by smoking and to assess interactions of smoking with workplace exposures. This paper reviews and evaluates the availability, reliability, validity, and efficiency of the various data sources and techniques for obtaining individual smoking data, including existing records, biological markers, and surveys. Emphasis is placed on the highly problematic issue of obtaining retrospective smoking histories. In general, the survey technique is currently deemed the most feasible approach for obtaining lifetime smoking histories. Both theoretical and practical aspects of smoking surveys are discussed in detail and are illustrated with a review of the recent literature and with data from two recent retrospective cohort studies conducted at the University of Pittsburgh. Several recommendations involving both the use of smoking data and areas for future methodologic research are presented. These include (1) justification for collecting smoking data in occupational studies based primarily on the potential for smoking to act as an effect modifier rather than solely as a confounder, (2) checks for reliability and validity in all studies which involve the collection of smoking data, (3) more methodologic research to better understand the impact that missing, unreliable, and invalid smoking data may have on the ability to detect and quantify important smoking‐exposure interactions, and (4) an assessment of the correlation between biological markers and cigarette carcinogen exposure.