Optimising the selection of food items for FFQs using Mixed Integer Linear Programming.
Public Health Nutr
; 18(1): 68-74, 2015 Jan.
Article
in En
| MEDLINE
| ID: mdl-24476899
ABSTRACT
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.Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Beverages
/
Nutrition Assessment
/
Diet
/
Food
/
Models, Theoretical
Type of study:
Prognostic_studies
Limits:
Adult
/
Humans
Country/Region as subject:
Europa
Language:
En
Journal:
Public Health Nutr
Journal subject:
CIENCIAS DA NUTRICAO
/
SAUDE PUBLICA
Year:
2015
Document type:
Article
Affiliation country:
Netherlands