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Structural Validation of a French Food Frequency Questionnaire of 94 Items

Overview of attention for article published in Frontiers in Nutrition, December 2017
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Title
Structural Validation of a French Food Frequency Questionnaire of 94 Items
Published in
Frontiers in Nutrition, December 2017
DOI 10.3389/fnut.2017.00062
Pubmed ID
Authors

Rozenn Gazan, Florent Vieux, Nicole Darmon, Matthieu Maillot

Abstract

Food frequency questionnaires (FFQs) are used to estimate the usual food and nutrient intakes over a period of time. Such estimates can suffer from measurement errors, either due to bias induced by respondent's answers or to errors induced by the structure of the questionnaire (e.g., using a limited number of food items and an aggregated food database with average portion sizes). The "structural validation" presented in this study aims to isolate and quantify the impact of the inherent structure of a FFQ on the estimation of food and nutrient intakes, independently of respondent's perception of the questionnaire. A semi-quantitative FFQ (n = 94 items, including 50 items with questions on portion sizes) and an associated aggregated food composition database (named the item-composition database) were developed, based on the self-reported weekly dietary records of 1918 adults (18-79 years-old) in the French Individual and National Dietary Survey 2 (INCA2), and the French CIQUAL 2013 food-composition database of all the foods (n = 1342 foods) declared as consumed in the population. Reference intakes of foods ("REF_FOOD") and nutrients ("REF_NUT") were calculated for each adult using the food-composition database and the amounts of foods self-reported in his/her dietary record. Then, answers to the FFQ were simulated for each adult based on his/her self-reported dietary record. "FFQ_FOOD" and "FFQ_NUT" intakes were estimated using the simulated answers and the item-composition database. Measurement errors (in %), spearman correlations and cross-classification were used to compare "REF_FOOD" with "FFQ_FOOD" and "REF_NUT" with "FFQ_NUT". Compared to "REF_NUT," "FFQ_NUT" total quantity and total energy intake were underestimated on average by 198 g/day and 666 kJ/day, respectively. "FFQ_FOOD" intakes were well estimated for starches, underestimated for most of the subgroups, and overestimated for some subgroups, in particular vegetables. Underestimation were mainly due to the use of portion sizes, leading to an underestimation of most of nutrients, except free sugars which were overestimated. The "structural validation" by simulating answers to a FFQ based on a reference dietary survey is innovative and pragmatic and allows quantifying the error induced by the simplification of the method of collection.

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Mendeley readers

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Geographical breakdown

Country Count As %
Unknown 40 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 20%
Researcher 7 18%
Student > Master 5 13%
Other 4 10%
Student > Postgraduate 3 8%
Other 6 15%
Unknown 7 18%
Readers by discipline Count As %
Medicine and Dentistry 12 30%
Nursing and Health Professions 6 15%
Agricultural and Biological Sciences 5 13%
Computer Science 3 8%
Neuroscience 2 5%
Other 3 8%
Unknown 9 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 December 2017.
All research outputs
#18,579,736
of 23,012,811 outputs
Outputs from Frontiers in Nutrition
#3,119
of 4,666 outputs
Outputs of similar age
#328,880
of 440,645 outputs
Outputs of similar age from Frontiers in Nutrition
#22
of 24 outputs
Altmetric has tracked 23,012,811 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,666 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.8. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 440,645 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.