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

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 communi

SUBMITTER: Schwedhelm C 

PROVIDER: S-EPMC6108519 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature