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Optimising the selection of food items for FFQs using Mixed Integer Linear Programming.

Objective: To support the selection of food items for FFQs in such a way that the amount of information on all relevant nutrients is maximised while the food list is as short as possible.Design: Selection of the most informative food items to be included in FFQs was modelled as a Mixed Integer Linea...

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Published in:Public Health Nutrition Vol. 18; no. 1; pp. 68 - 75
Main Authors: Gerdessen, Johanna C, Souverein, Olga W, van 't Veer, Pieter, de Vries, Jeanne Hm
Format: research Journal Article
Published: Cambridge University Press Jan2015
Online Access:View this record in EBSCOhost
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      dt: Jan2015
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      pub: Cambridge University Press
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        2013129317
        10.1017/S1368980013003479
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        109621097
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        atl: Optimising the selection of food items for FFQs using Mixed Integer Linear Programming.
      aug:
        au:
          Gerdessen, Johanna C
          Souverein, Olga W
          van 't Veer, Pieter
          de Vries, Jeanne Hm
      sug:
      ab: Objective: To support the selection of food items for FFQs in such a way that the amount of information on all relevant nutrients is maximised while the food list is as short as possible.Design: Selection of the most informative food items to be included in FFQs was modelled as a Mixed Integer Linear Programming (MILP) model. The methodology was demonstrated for an FFQ with interest in energy, total protein, total fat, saturated fat, monounsaturated fat, polyunsaturated fat, total carbohydrates, mono- and disaccharides, dietary fibre and potassium.Results: The food lists generated by the MILP model have good performance in terms of length, coverage and R 2 (explained variance) of all nutrients. MILP-generated food lists were 32-40 % shorter than a benchmark food list, whereas their quality in terms of R 2 was similar to that of the benchmark.Conclusions: The results suggest that the MILP model makes the selection process faster, more standardised and transparent, and is especially helpful in coping with multiple nutrients. The complexity of the method does not increase with increasing number of nutrients. The generated food lists appear either shorter or provide more information than a food list generated without the MILP model.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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