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

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. MILPgenerated 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.

Relative Validity of a Method Based on a Smartphone App (Electronic 12-Hour Dietary Recall) to Estimate Habitual Dietary Intake in Adults

“…The 3 methods for determining diet refer to the same tracking period to avoid possible variations in the intake of different foods over time [13,22,28,46]. This is especially likely among the university students who make up the sample of this study.…”

“…To make comparisons, the 3 tools registered the consumption of the same food groups, used the same standard servings as a reference, and the intake record corresponded to the same time period, to avoid possible variations in individual diets during different periods [13,22,28,46].…”

“…In large-scale epidemiological and intervention studies, where detailed dietary assessment is not feasible [9], FFQs have been the most accessible and commonly utilized dietary assessment tool [1,7,10,11,15,16,21]. FFQs are retrospective methods that require respondents to report the frequency of consumption of a predefined list of food groups over an extended period of time (weeks or months) [14,22]. FFQs are practical and easy to administer; they do not affect food intake patterns and can assess habitual dietary patterns with a single administration [10].…”

Electronic 12-Hour Dietary Recall (e-12HR): Comparison of a Mobile Phone App for Dietary Intake Assessment With a Food Frequency Questionnaire and Four Dietary Records

“…The e-12HR app was developed to record daily consumption of a list of 10 food groups. The list could not be too long to minimize the workload on participants as well as the research costs [ 28 ]. These food groups were selected as they are indicators of health/disease and are considered protective factors (fruit, vegetables, legumes or fish) or risk factors (soft drinks, commercial baked foods, and precooked meals) for chronic illnesses [ 4 , 12 , 29 ].…”

Electronic 12-Hour Dietary Recall (e-12HR): Comparison of a Mobile Phone App for Dietary Intake Assessment With a Food Frequency Questionnaire and Four Dietary Records (Preprint)

“…The list could not be too long in order to minimize the workload on the participants as well as the research costs [28]. These food groups were selected as they are indicators of health/disease and are considered protective factors (fruit, vegetables, legumes or fish) or risk factors (soft drinks, commercial baked goods and precooked meals) for chronic illnesses [4,12,29].…”