Validation and sensitivity analysis of probabilistic models of dietary exposure to micronutrients: an example based on vitamin B₆

Abstract

Probabilistic modelling can be used to get an insight into the variability and uncertainty of the nutrient intake in a population. When a probabilistic model is used, it is important that it is validated. Furthermore, a sensitivity analysis of the model output can give an insight into the most important input variables of the model and can be used as an aid to describe the reliability of the model. In this study, four models to estimate vitamin B₆ intake among males and females were validated using the method of Kaaks et al. This method compares the relationship between three diferent kind of measurements with the unknown ‘true’ intake. In each of these four models, only one input variable (concentration or bioavailability) was changed compared with a reference model. A sensitivity analysis was also performed. The results of the validation showed that for males, a model using a fixed bioavailability factor at the food group level was valid, while for females a model using either a fixed value or a distribution for the bioavailability factor was valid. Use of a distribution for the concentration of vitamin B₆ in supplements was not valid. The results of the sensitivity analysis showed that the concentration of vitamin B₆ in food and supplements was the key contributor to variability and uncertainty in the model estimates of vitamin B₆ intake, in both males and females. All results indicated that when taking variability and uncertainty into account by using probabilistic modelling, the effect on the nutrient intake for nutrients that are present in many common eaten foods, is small. For these broadly available nutrients, fixed concentrations and bioavailability factors give a good estimate of the nutrient intake in a population. When using probabilistic modelling, it is very important to collect more actual information about the concentration.

Keywords:

• probabilistic modelling
• micronutrients
• vitamin B6
• model validation