Statistical modelling of usual intake

Within the EFSA Article 36 project “European Tool Usual Intake” (ETUI) a workshop was organised in May 2010 where the different available models to calculate usual intake were presented and discussed. This report integrates the workshop background document, the presentations given by experts, and the discussions during the workshop. The purpose of the workshop was to evaluate existing statistical methods for estimating usual intake with respect to a number of criteria, so that the performance of each method on each criterion will be well understood after the workshop. The outcome of the workshop allows choices to be made for a European Tool Usual Intake, to be implemented in the remainder of the project. A starting document was provided to the participants of the workshop with up-to-date information on methods, data and criteria, as a basis for discussion. It was apparent from the workshop that there is not one optimal model for all cases, rather a toolbox approach is suitable. The choice of the most appropriate model has to be fine-tuned case by case. Criteria to be considered are related to data availability and data pre-processing (e.g. compatibility of existing data formats, need to handle complicating factors like food code conversion, left-censored data, processing factors, brand loyalty, pooling over multiple datasets), the appropriateness of modelling assumptions for frequencies and amounts modelling (e.g. level of conservatism, additivity assumption and data transformations, the need to model intake as a function of covariates, correlations), the usefulness to combine survey and food frequency questionnaire data, the need to model single food intake or diet-aggregated intake, the need to evaluate uncertainties, and the usefulness of implementations. For the short term, case studies will be performed based on issues relevant for EFSA panels. Results from the workshop and possibilities of using models to calculate usual intake were recently discussed during the 5th meeting of the EFSA Expert group on food consumption data. Currently only few EU Member States use this kind of models but there is a lot of interest in gaining experience with the usual intake modelling. Several requests were received concerning the possibility of having more information about the ETUI project and even the organisation of a future training. In conclusion, this interim report is considered by EFSA to be a good review of the different models used and presents the main challenges related to the use of these techniques. Its publication could be useful to those who want to start using this kind of methodology

[1]  W. Slob,et al.  Integration of Probabilistic Exposure Assessment and Probabilistic Hazard Characterization , 2007 .

[2]  D. Midthune,et al.  Statistical methods for estimating usual intake of nutrients and foods: a review of the theory. , 2006, Journal of the American Dietetic Association.

[3]  W Slob,et al.  Modeling long-term exposure of the whole population to chemicals in food. , 1993, Risk analysis : an official publication of the Society for Risk Analysis.

[4]  J. Boer,et al.  the potential of AGE MODE, an age-dependent model, to estimate usual intakes and prevalences of inadequate intakes in a population. , 2006, The Journal of nutrition.

[5]  C. Glasbey,et al.  A latent Gaussian model for multivariate consumption data , 2007 .

[6]  I. Huybrechts,et al.  SCIENTIFIC REPORT submitted to EFSA Long-term dietary exposure to different food colours in young children living in different European countries 1 , 2010 .

[7]  On Lange and Ryan's plotting technique for diagnosing non-normality of random effects , 2005 .

[8]  H. Voet,et al.  Long-term dietary exposure to lead in young children living in different European countries. Scientific report submitted to EFSA , 2010 .

[9]  Raymond J Carroll,et al.  Modeling Data with Excess Zeros and Measurement Error: Application to Evaluating Relationships between Episodically Consumed Foods and Health Outcomes , 2009, Biometrics.

[10]  Exposure Assessment for Pesticide Intake from Multiple Food Products: A Bayesian Latent‐Variable Approach , 2008, Risk analysis : an official publication of the Society for Risk Analysis.

[11]  W. D. de Boer,et al.  Comparison of two models for the estimation of usual intake addressing zero consumption and non-normality , 2009, Food additives & contaminants. Part A, Chemistry, analysis, control, exposure & risk assessment.

[12]  Probabilistic acute dietary exposure assessments to captan and tolylfluanid using several European food consumption and pesticide concentration databases. , 2009, Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association.

[13]  D. Midthune,et al.  The food propensity questionnaire: concept, development, and validation for use as a covariate in a model to estimate usual food intake. , 2006, Journal of the American Dietetic Association.

[14]  I. Huybrechts,et al.  Long‐term dietary exposure to different food colours in young children living in different European countries , 2010 .

[15]  Edith D. de Leeuw,et al.  Survey Measurement and Process Quality: Lyberg/Survey , 1997 .

[16]  H. Voet,et al.  A probabilistic model for simultaneous exposure to multiple compounds from food and its use for risk-benefit assessment. , 2007 .

[17]  S. De Henauw,et al.  Estimating the distribution of usual dietary intake by short-term measurements , 2002, European Journal of Clinical Nutrition.

[18]  Marc C Kennedy,et al.  Bayesian modelling of long-term dietary intakes from multiple sources. , 2010, Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association.

[19]  R. Carroll,et al.  A new statistical method for estimating the usual intake of episodically consumed foods with application to their distribution. , 2006, Journal of the American Dietetic Association.

[20]  Hilko van der Voet,et al.  Can current dietary exposure models handle aggregated intake from different foods? A simulation study for the case of two foods. , 2010, Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association.

[21]  H. Voet,et al.  SCIENTIFIC REPORT submitted to EFSA Long-term dietary exposure to chromium in young children living in different European countries 1 , 2010 .

[22]  A. Carriquiry,et al.  A Semiparametric Transformation Approach to Estimating Usual Daily Intake Distributions , 1996 .

[23]  Keith E. Muller,et al.  Extending the Box–Cox transformation to the linear mixed model , 2006 .

[24]  A. Petersen,et al.  Harmonisation of food consumption data format for dietary exposure assessments of chemicals analysed in raw agricultural commodities. , 2009, Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association.

[25]  Wout Slob,et al.  Probabilistic dietary exposure assessment taking into account variability in both amount and frequency of consumption. , 2006, Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association.

[26]  Michiel J W Jansen,et al.  Risk assessment of dietary exposure to pesticides using a Bayesian method. , 2005, Pest management science.