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Bias in occupational epidemiology studies

¹ Centre for Public Health Research, Massey University Wellington Campus, Wellington, New Zealand
² Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA
³ International Agency for Research on Cancer, Lyon, France
⁴ Department of Work Environment, University of Massachusetts at Lowell, Massachusetts, USA

Correspondence to:
Correspondence to:
Professor N Pearce
Director, Centre for Public Health Research, Massey University Wellington Campus, Private Box 756, Wellington, New Zealand; n.e.pearce{at}massey.ac.nz

The design of occupational epidemiology studies should be based on the need to minimise random and systematic error. The latter is the focus of this paper, and includes selection bias, information bias and confounding. Selection bias can be minimised by obtaining a high response rate (and by appropriate selection of the control group in a case-control study). In general, it is important to ensure that information bias is minimised and is also non-differential (for example, that the misclassification of exposure is not related to disease status) by collecting data in a standardised manner. A major concern in occupational epidemiology studies usually relates to confounding, because exposure has not been randomly allocated, and the groups under study may therefore have different baseline disease risks. For each of these types of bias, the goal should be to avoid the bias by appropriate study design and/or appropriate control in the analysis. However, it is also important to attempt to assess the likely direction and strength of biases that cannot be avoided or controlled.

Abbreviations: MWF, metal working fluids; SMR, standardised mortality ratio

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