2015
DOI: 10.1080/10807039.2014.967039
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The Use of Epidemiology in Risk Assessment: Challenges and Opportunities

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Cited by 18 publications
(7 citation statements)
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“…Quantification of occupational exposure to pesticides is crucial to investigate potential adverse health effects in workers 1 2. As it is often logistically not feasible or too costly to collect human samples (eg, urine, stool) and measure exposure biomarkers over time, algorithms have been developed to calculate pesticide exposure intensity scores 3 4.…”
Section: Introductionmentioning
confidence: 99%
“…Quantification of occupational exposure to pesticides is crucial to investigate potential adverse health effects in workers 1 2. As it is often logistically not feasible or too costly to collect human samples (eg, urine, stool) and measure exposure biomarkers over time, algorithms have been developed to calculate pesticide exposure intensity scores 3 4.…”
Section: Introductionmentioning
confidence: 99%
“…Not only did the North Carolina cohort mentioned above collect multiple milk samples, but researchers also calculated exposures using the amount of milk consumed and length of time breastfeeding, completing what was one of the most comprehensive and complete postnatal exposure assessments in this database. Many studies included duration of breastfeeding in their exposure calculations, but some dichotomized duration data in their analyses (i.e., expressed duration as “ some number of weeks or months” or “> some number of weeks or months”), which poses increased risk of misclassification bias (Christensen et al. 2015).…”
Section: Resultsmentioning
confidence: 99%
“…Non-differential measurement error of exposures will usually bias the results toward the null by lowering precision and therefore reducing the ability to distinguish potential effects between non-exposed and exposed subjects or among different exposure categories. Differential measurement of exposures across the exposure groups will also bias the exposure-outcome relationship, although the direction of the biases is less clear; some examples include observer and recall bias (Blair et al, 2007; Christensen et al, 2014). …”
Section: Overview Of Current Methods (Framework and Tools)mentioning
confidence: 99%