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The use of food consumption data in assessments of exposure to food chemicals including the application of probabilistic modelling

  • Joyce Lambe (a1)

Abstract

Emphasis on public health and consumer protection, in combination with globalisation of the food market, has created a strong demand for exposure assessments of food chemicals. The food chemicals for which exposure assessments are required include food additives, pesticide residues, environmental contaminants, mycotoxins, novel food ingredients, packaging-material migrants, flavouring substances and nutrients. A wide range of methodologies exists for estimating exposure to food chemicals, and the method chosen for a particular exposure assessment is influenced by the nature of the chemical, the purpose of the assessment and the resources available. Sources of food consumption data currently used in exposure assessments range from food balance sheets to detailed food consumption surveys of individuals and duplicate-diet studies. The fitness-for-purpose of the data must be evaluated in the context of data quality and relevance to the assessment objective. Methods to combine the food consumption data with chemical concentration data may be deterministic or probabilistic. Deterministic methods estimate intakes of food chemicals that may occur in a population, but probabilistic methods provide the advantage of estimating the probability with which different levels of intake will occur. Probabilistic analysis permits the exposure assessor to model the variability (true heterogeneity) and uncertainty (lack of knowledge) that may exist in the exposure variables, including food consumption data, and thus to examine the full distribution of possible resulting exposures. Challenges for probabilistic modelling include the selection of appropriate modes of inputting food consumption data into the models.

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Copyright

Corresponding author

Corresponding author: Dr Joyce Lambe, fax +353 1 670 9176, email iefs@iefs.ie

References

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Beaton, GH (1982) What do we think we are estimating? In Proceedings of the Symposium on Dietary Data Collection, Analysis and Significance, MA Research Bulletin no. 675, pp. 3648 [Beal, VA and Laus, MJ, editors]. Amherst, MA: Massachusetts Agricultural Research Station, University of Massachusetts.
Becker, W, Foley, S, Shelley, E & Gibney, M (1999) Energy under-reporting in Swedish and Irish dietary surveys: implications for food-based dietary guidelines. British Journal of Nutrition 81, Suppl. 2, S119S126.
Bingham, S (1987) The dietary assessment of individuals; methods, accuracy, new techniques and recommendations. Nutrition Abstracts and Reviews 57, 705741.
Cadby, P (1996) Estimating intakes of flavouring substances. Food Additives and Contaminants 13, 453460.
Chambolle, M (1999) Assessment of extreme levels of chronic food intakes. Regulatory Toxicology and Pharmacology 30, 1318.
Cullen, AC & Frey, HC (1999) Probabilistic Techniques in Exposure Assessment. New York: Plenum Press.
Department of Clinical Medicine (1999). Irish National Food Ingredient Database User's Manual. Dublin: Department of Clinical Medicine, Trinity College Dublin.
Environmental Protection Agency (1996) Acute dietary exposure assessment office policy. http://www.epa.gov/opphed01/ acutesop.htm.
European Commission (1997). Improvement of Knowledge of Food Consumption with a View to Protection of Public Health by Means of Exchanges and Collaboration Between Database Managers (Report of Experts Participating in Task 4.1). Luxembourg: Office for Official Publications of the European Commission.
European Commission (1998). Report on Methodologies for the Monitoring of Food Additive Intake across the European Union (Report of Experts Participating in Task 4.2). Luxembourg: Office for Official Publications of the European Commission.
European Union (2000) EU Commission white paper on Food Safety 1. http://europa.eu.int/comm/dgs/health_consumer/ library/pub/pubo6_en.pdf.
Finley, B & Paustenbach, D (1994) The benefits of probabilistic exposure assessment: three case studies involving contaminated air, water and soil. Risk Analysis 14, 5373.
Fisher, CE (1987) Dietary studies in the United Kingdom. In Total Diet Studies in Europe. A Concerted Action Project on Nutrition and Health in the European Community, pp. 1421 [van Dokkum, W and de Vos, RH, editors]. Zeist, The Netherlands: TNO.
Food and Agriculture Organization/World Health Organization (1989). Supplement 2 to Codex Alimentarius Volume V: Guidelines for Simple Evaluation of Food Additive Intake. Rome: FAO.
Galal-Gorchev, H (1993) Key elements of food contamination monitoring programmes. Food Additives and Contaminants 10, 14.
Gibney, MJ (1999) Dietary intake methods for estimating food additive intake. Regulatory Toxicology and Pharmacology 30, 3133.
Gibney, MJ & Lambe, J (1996) Estimation of food additive intake: methodology overview. Food Additives and Contaminants 13, 405410.
Gilsenan, MB, Lambe, J, Kearney, J & Gibney, MJ (2001) Assessment of the influence of energy under-reporting on food additive exposure estimates. Proceedings of the Nutrition Society 60, 158A.
Helsing, E & Verster, V (1995) Opening address. In Dietary Exposure to Contaminants and Additives: Risk Assessment in Europe, pp. 36 [Kardinaal, AFM, Löwik, MRH and van der Heij, DG, editors]. Zeist, The Netherlands: TNO Nutrition and Food Research Institute.
Hermann, JL & Younes, M (1999) Background to the ADI/TDI/PTWI. Regulatory Toxicology and Pharmacology 30, S109S113.
Holland, B, Unwin, ID & Buss, D (1988) Cereals and Cereal Products. Third Supplement to McCance & Widdowson's The Composition of Foods, 4th ed. Cambridge: The Royal Society of Chemistry and Ministry of Agriculture, Fisheries and Food.
Irish Universities Nutrition Alliance (2001). North/South Ireland Food Consumption Database. Dublin: IUNA.
Lambe, J, Cadby, P & Gibney, MJ (2001) Comparison of stochastic modelling of the intakes of intentionally added flavouring substances with Theoretical Added Maximum Daily Intakes (TAMDI) and Maximised Survey-Derived Daily Intakes (MSDI). Food Additives and Contaminants (In the Press).
Lambe, J, Kearney, J, Becker, W, Hulshof, KFAM & Gibney, MJ (1998) Predicting percentage of individuals consuming foods from percentage of households purchasing foods to improve the use of household budget surveys in estimating food chemical intakes. Public Health Nutrition 1, 239247.
Langlais, R (1996) Additive usage levels. Food Additives and Contaminants 13, 443451.
Livingstone, MBE, Prentice, AM, Strain, JJ, Coward, WA, Black, AE, Barker, ME, McKenna, PG & Whitehead, RG (1990) Accuracy of weighed dietary records in studies of diet and health. British Medical Journal 308, 708713.
Löwik, MRH (1996) Possible use of food consumption surveys to estimate exposure to additives. Food Additives and Contaminants 13, 427441.
Löwik, MRH, Hulshof, KFAM, Brussard, JH & Kistemaker, C (1999) Dependence of dietary intake estimates on the time frame of assessment. Regulatory Toxicology and Pharmacology 30, 4856.
Nusser, SM, Carriquiry, AL, Dodd, KW & Fuller, WA (1996) A semiparametric transformation approach to estimating usual daily intake distributions. Journal of the American Statistical Association 91, 14401449.
Nutriscan (1992). An Evaluation of the Methodologies for the Estimation of Intakes of Food Additives and Contaminants in the European Community. Dublin: Nutriscan.
Nutriscan (1994). Options for the Routine Collection of Data on Usage Levels of Food Additives in the European Union. Dublin: Nutriscan.
Pentillä, PL (1995) Estimation of Food Additive and Pesticide Intakes by Means of a Stepwise Method. Turku, Finland: University of Turku.
Price, PS, Curry, CL, Goodrum, PE, Gray, MN, McCrodden, JI, Harrington, NW, Carlson-Lynch, H & Keenan, RE (1996) Monte Carlo modeling of time-dependent exposures using a microexposure event approach. Risk Analysis 16, 339348.
Rees, NMA & Day, MJL (2000) UK consumption databases relevant to acute exposure assessment. Food Additive and Contaminants 17, 575581.
Renwick, AG (1996) Needs and methods for priority setting for estimating the intake of food additives. Food Additives and Contaminants 13, 467475.
Sempos, C, Looker, A & Johnson, C (1991) The importance of within-person variability in estimating prevalence. In Monitoring Dietary Intakes, pp. 99109 [I MacDonald, editor]. New York: Springer–Verlag.
Slob, W (1991) A comparison of two statistical approaches to estimate long-term exposure distributions from short-term measurements. Risk Analysis 16, 195200.
Tennant, DR (1995) The use of biomarkers in food chemical risk assessment. In Biomarkers in Food Chemical Risk Assessment, pp. 123128 [Crews, HM & Hanley, AB, editors]. Cambridge: The Royal Society of Chemistry.
Verger, P, Garnier-Sagne, I & LeBlanc, JC (1999) Identification of risk groups for intake of food chemicals. Regulatory Toxicology and Pharmacology 30, 103113.
Vose, D (1996) Quantitative Risk Analysis: A Guide to Monte Carlo Simulation Modelling. Chichester, West Sussex: John Wiley and Sons Ltd.
Vose, D (2000) Risk Analysis: A Quantitative Guide, 2nd ed. Chichester, West Sussex: John Wiley and Sons Ltd.
Wagstaffe, PJ (1996) The assessment of food additive usage and consumption: the Commission Perspective. Food Additives and Contaminants 13, 397403.
Walker, R (1995) Toxicological risks mediated by food. In Dietary Exposure to Contaminants and Additives: Risk Assessment in Europe, pp. 1326 [Kardinaal, AFM, Löwik, MRH & van der Heij, DG, editors]. Zeist, The Netherlands: TNO Nutrition and Food Research Institute.
Walker, R (1998) Toxicity testing and derivation of the ADI. Food Additives and Contaminants 15, 1116.
Wallace, LA, Duan, N & Ziegenfus, R (1994) Can long-term exposure be predicted from short-term measurements? Risk Analysis 14, 7585.
World Health Organization (1995). Application of Risk Analysis to Food Standards Issues. Report of the Joint FAO/WHO Expert Consultation. Geneva: WHO.
World Health Organization (1998) GEMS/Food Regional Diets. Regional Per Capita Consumption of Raw and Semi-processed Agricultural Commodities. WHO/FSF/FOS/98.3. Geneva: WHO.

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The use of food consumption data in assessments of exposure to food chemicals including the application of probabilistic modelling

  • Joyce Lambe (a1)

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