Dealing with variability in food production chains: a tool to enhance the sensitivity of epidemiological studies on phytochemicals |
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Authors: | Matthijs Dekker Ruud Verkerk |
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Institution: | (1) Wageningen University, Product Design and Quality Management Group, Dept. of Agrotechnology and Food Sciences, P. O. Box 8129, 6700 EV Wageningen, The Netherlands. matthijs.dekker@wur.nl, NL |
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Abstract: | Summary. Background: Many epidemiological studies have tried to associate the intake of certain food products with a reduced risk for certain
diseases. Results of these studies are often ambiguous, conflicting, or show very large deviations of trends. Nevertheless,
a clear and often reproduced inverse association is observed between total vegetable and fruit consumption and cancer risk.
Examples of components that have been indicated to have a potential protective effect in food and vegetables include antioxidants,
allium compounds and glucosinolates. Aim: The food production chain can give a considerable variation in the level of bioactive components in the products that are
consumed. In this paper the effects of this variability in levels of phytochemicals in food products on the sensitivity of
epidemiological studies are assessed. Methods: Information on the effect of variation in different steps of the food production chain of Brassica vegetables on their glucosinolate content is used to estimate the distributions in the levels in the final product that is
consumed. Monte Carlo simulations of an epidemiological cohort study with 30,000 people have been used to assess the likelihood
of finding significant associations between food product intake and reduced cancer risk. Results: By using the Monte Carlo simulation approach, it was shown that if information on the way of preparation of the products
by the consumer was quantified, the statistical power of the study could at least be doubled. The statistical power could
be increased by at least a factor of five if all variation of the food production chain could be accounted for. Conclusions: Variability in the level of protective components arising from the complete food production chain can be a major disturbing
factor in the identification of associations between food intake and reduced risk for cancer. Monte Carlo simulation of the
effect of the food production chain on epidemiological cohort studies has identified possible improvements in the set up of
such studies. The actual effectiveness of food compounds already identified as cancer-protective by current imprecise methods
is likely to be much greater than estimated at present.
Received: 15 July 2002, Accepted: 26 January 2003
Correspondence to: Matthijs Dekker |
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Keywords: | Monte Carlo simulations – epidemiology – food production chain – processing – sensitivity – glucosinolates |
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