The added value of food frequency questionnaire (FFQ) information to estimate the usual food intake based on repeated 24-hour recalls

Cloë Ost,Karin A A De Ridder,Herman Van Oyen,Jean Tafforeau

doi:10.1186/s13690-017-0214-8

Abstract

BackgroundStatistical methods to model the usual dietary intake of foods in a population generally ignore the additional information on the never-consumers. The objective of this study is to determine the added value of Food Frequency Questionnaire (FFQ) data allowing distinguishing the never-consumers from the non-consumers while modeling the usual intake distribution.MethodsThree food items with a different proportion of never-consumers were selected from the database of the Belgian food consumption survey of 2004 (N = 3200). The usual intake distribution for these food items was modeled with the Statistical Program for Analysis of Dietary Exposure (SPADE) and modeling parameters were extracted. These parameters were used to simulate (a) a new database with two 24-h recalls per respondent and (b) a “true” usual intake distribution. The usual intake distribution from the new database was obtained by modeling the 24-h recalls with SPADE, once without and once with the inclusion of the FFQ data on the never-consumers. Ratios were calculated for the different percentiles of the usual intake distribution: the modeled usual intake (g/day) (for both SPADE with and without the inclusion of FFQ data on never-consumers) was divided by the corresponding percentile of the simulated “true” usual intake (g/day). The closer the ratio is to one, the better the model fits the data.ResultsInclusion of the FFQ information to identify the never-consumers did not improve the estimation of the higher percentiles of the usual intake distribution. However, taking into account this FFQ information improved the estimation of the lower percentiles of the usual intake distribution even when the proportion of never-consumers was low.ConclusionsThe inclusion of FFQ information to identify the never-consumers is beneficial when interested in the whole usual intake distribution or in the lower percentiles only, no matter how low the proportion of never-consumers for that food item may be. However, when interest is only in the higher percentiles of the usual intake distribution, inclusion of FFQ information to identify the never-consumers will have no benefit.

Highlights

Statistical methods to model the usual dietary intake of foods in a population generally ignore the additional information on the never-consumers
On the other hand the results indicate that using the Food Frequency Questionnaire (FFQ) data to identify the never-consumers is crucial while estimating the lower percentiles of the usual intake distribution, even when the proportion of never-consumers is low
The inclusion of FFQ information to identify the neverconsumers improves the estimation of the usual intake distribution, but only at the lower percentiles

Summary

Introduction

Statistical methods to model the usual dietary intake of foods in a population generally ignore the additional information on the never-consumers. Studies comparing dietary and disease patterns in large populations provided evidence for the relation between nutrition and disease incidence This led to the recognition that an unhealthy diet and lifestyle factors, such as a lack of physical activity, are key risk factors for developing a large variety of chronic conditions, such as cardiovascular diseases, cancer and diabetes [1,2,3]. This illustrates the importance of assessing the prevalence and distribution of food health indicators in the population. The measurement of the usual food intake is challenging when the number of 24HRs is limited [1, 4,5,6,7,8,9,10]

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