Dealing with variability in food production chains: a tool to enhance the sensitivity of epidemiological studies on phytochemicals
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| Publicado en: | European Journal of Nutrition vol. 42, no. 1 (Feb 2003), p. 67 |
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Springer Nature B.V.
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| Acceso en línea: | Citation/Abstract Full Text Full Text - PDF |
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| 100 | 1 | |a Dekker, Matthijs | |
| 245 | 1 | |a Dealing with variability in food production chains: a tool to enhance the sensitivity of epidemiological studies on phytochemicals | |
| 260 | |b Springer Nature B.V. |c Feb 2003 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a 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. 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. 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. 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. 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. 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. | |
| 650 | 2 | 2 | |a Anticarcinogenic Agents |x analysis |
| 650 | 2 | 2 | |a Anticarcinogenic Agents |x metabolism |
| 650 | 1 | 2 | |a Anticarcinogenic Agents |x pharmacology |
| 650 | 2 | 2 | |a Bias (Epidemiology) |
| 650 | 2 | 2 | |a Biological Availability |
| 650 | 1 | 2 | |a Brassica |x chemistry |
| 650 | 2 | 2 | |a Cohort Studies |
| 650 | 2 | 2 | |a Dose-Response Relationship, Drug |
| 650 | 2 | 2 | |a Epidemiologic Methods |
| 650 | 2 | 2 | |a Epidemiologic Studies |
| 650 | 2 | 2 | |a Food Habits |
| 650 | 1 | 2 | |a Food Handling |
| 650 | 2 | 2 | |a Food Supply |
| 650 | 2 | 2 | |a Glucosinolates |x analysis |
| 650 | 2 | 2 | |a Glucosinolates |x metabolism |
| 650 | 1 | 2 | |a Glucosinolates |x pharmacology |
| 650 | 2 | 2 | |a Humans |
| 650 | 2 | 2 | |a Monte Carlo Method |
| 650 | 1 | 2 | |a Neoplasms |x prevention & control |
| 650 | 2 | 2 | |a Risk Factors |
| 700 | 1 | |a Verkerk, Ruud | |
| 773 | 0 | |t European Journal of Nutrition |g vol. 42, no. 1 (Feb 2003), p. 67 | |
| 786 | 0 | |d ProQuest |t Consumer Health Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/214869217/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/214869217/fulltext/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/214869217/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |