British Journal of Nutrition

Full Papers

Innovative Techniques

A probabilistic model to evaluate population dietary recommendations

Zaid Chalabia1, Elaine Fergusona2 c1, Robert Stanleya3a4 and André Brienda5

a1 Department of Social and Environmental Health Research, London School of Hygiene and Tropical Medicine, 15-17 Tavistock Place, London WC1H 9SH, UK

a2 Department of Population Health, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK

a3 CoMPLEX, University College London, Gower Street, London WC1E 6BT, UK

a4 Department of Cell and Developmental Biology, University College London, London WC1E 6BT, UK

a5 Department of International Health, University of Tampere Medical School, Tampere FIN-33014, Finland

Abstract

Food-based dietary recommendations (FBR) play an essential role in promoting a healthy diet. To support the process of formulating a set of population-specific FBR, a probabilistic model was developed specifically to predict the changes in the percentage of a population at risk of inadequate nutrient intakes after the adoption of alternative sets of FBR. The model simulates the distribution of the number of servings per week from food groups or food items at baseline and after the hypothetical successful adoption of alternative sets of FBR, while ensuring that the population's energy intake distribution remains similar. The simulated changes from baseline in median nutrient intakes and the percentage of the population at risk of inadequate nutrient intakes are calculated and compared across the alternative sets of FBR. The model was illustrated using a hypothetical population of 12- to 18-month-old breast-feeding children consuming a cereal-based diet low in animal source foods.

(Received July 16 2013)

(Revised February 14 2014)

(Accepted February 24 2014)

(Online publication April 29 2014)

Key Words:

  • Mathematical;
  • models;
  • Dietary recommendations;
  • Nutrients

Correspondence

c1 Corresponding author: Dr E. Ferguson, fax +44 20 7958 8111, email elaine.ferguson@lshtm.ac.uk

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