Impress: Improving Exposure Assessment Methodologies for Epidemiological Studies on Pesticides. (1st February 2019)

• Record Type: Journal Article
• Authors: Galea, Karen; Basinas, Ioannis; Cherrie, John; Fuhrimann, Samuel; Harding, Anne-Helen; Jones, Kate; Kromhout, Hans; Ohlander, Johan; Povey, Andrew; Ahmad, Zulkhairul Naim Sidek; van Tongeren, Martie; Vermeulen, Roel
• Is Part Of: Outlooks on pest management. Volume 30:Number 1(2019:Jan./Feb.)
• Page Start: 18
• Page End: 19
• Publication Date: 2019-02-01
• Subjects: Pesticides -- Periodicals; Pesticides -- Application -- Periodicals; 632.905
• DOI: 10.1564/v30_feb_05
• Languages: English
• ISSNs: 1743-1034

Abstract

This article introduces 'IMPRESS: Improving exposure assessment methodologies for epidemiological studies on pesticides', a new research project focussed on better understanding the performance of exposure assessment methodologies in pesticide epidemiology studies. Exposure to certain pesticides is suspected to result in several chronic diseases such as cancers, reproductive effects (e.g. reduced semen quality, low birth weight) and Parkinson's disease. Studying chronic health diseases requires the assessment of historical exposures. However, exposure measurement data are rarely available. Therefore, assessment of historical exposures frequently needs to be based on self-reported information such as a person's job title, duration of employment, and/or whether they were ever exposed (yes/no) to pesticides or registered data like spray calendars. Naturally, such exposure measures suffer from some limitations (e.g. the ability of a person to remember their exposure history over a long time-period), which may affect the conclusions of a study. The large number of pesticides and pesticide mixtures involved, and the seasonality and broad range of characteristics regarding their application and use further complicates matters. With an increasing number of studies on occupational exposure to pesticides conducted each year, bias associated with respective exposure assessment methods may aggregate over time leading to potentially spurious associations or associations going undetected. Understanding the performance of the applied surrogate measures in exposure assessment is therefore important to allow proper evaluation of the involved risks.