Meal and habitual dietary networks identified through Semiparametric Gaussian Copula Graphical Models in a German adult population

PloS One
Carolina SchwedhelmKhalid Iqbal

Abstract

Gaussian graphical models (GGMs) are exploratory methods that can be applied to construct networks of food intake. Such networks were constructed for meal-structured data, elucidating how foods are consumed in relation to each other at meal level. Meal-specific networks were compared with habitual dietary networks using data from an EPIC-Potsdam sub-cohort study. Three 24-hour dietary recalls were collected cross-sectionally from 815 adults in 2010-2012. Food intake was averaged to obtain the habitual intake. GGMs were applied to four main meals and habitual intakes of 39 food groups to generate meal-specific and habitual dietary networks, respectively. Communities and centrality were detected in the dietary networks to facilitate interpretation. The breakfast network revealed five communities of food groups with other vegetables, sauces, bread, margarine, and sugar & confectionery as central food groups. The lunch and afternoon snacks networks showed higher variability in food consumption and six communities were detected in each of these meal networks. Among the central food groups detected in both of these meal networks were potatoes, red meat, other vegetables, and bread. Two dinner networks were identified with five commun...Continue Reading

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Citations

Jan 19, 2021·Advances in Nutrition·Cathal O'Hara, Eileen R Gibney
Jan 30, 2021·Journal of Cardiovascular and Thoracic Research·Zahra AkbarzadeSakineh Shab-Bidar
Mar 27, 2021·The International Journal of Behavioral Nutrition and Physical Activity·Rebecca M LeechSarah A McNaughton
Jul 25, 2021·The International Journal of Behavioral Nutrition and Physical Activity·Carolina SchwedhelmTonja R Nansel

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Methods Mentioned

BETA
PCA

Software Mentioned

SAS
EPIC
Soft
R Foundation for Statistical Computing
R package
R package “ linkcomm ”
nethet
R
CorelDRAW Graphics Suite X3

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