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The Discovery Of Data-Driven Temporal Dietary Patterns And A Validation Of Their Description Using Energy And Time Cut-Offs, Luotao Lin, Jiaqi Guo, Yitao Li, Saul Gelfand, Edward Delp, Anindya Bhadra, Elizabeth Richards, Erin Hennessy, Heather A. Eicher-Miller
The Discovery Of Data-Driven Temporal Dietary Patterns And A Validation Of Their Description Using Energy And Time Cut-Offs, Luotao Lin, Jiaqi Guo, Yitao Li, Saul Gelfand, Edward Delp, Anindya Bhadra, Elizabeth Richards, Erin Hennessy, Heather A. Eicher-Miller
School of Nursing Faculty Publications
Objectives
Data-driven methods were recently applied to create temporal dietary patterns (TDPs) incorporating timing and amount of energy intake over 24-hours; their relationships to obesity were determined. However, description of the data-driven TDPs using energy and time cut-offs were not validated against obesity. Aims were to (1) create data-driven TDPs, describe pattern characteristics using energy and time cut-offs, and determine relationships to BMI and waist circumference (WC); (2) assess the concurrent validity of TDPs derived using the cut-offs by determining relationships with BMI and WC. Methods
Amount and timing of energy intake from the first day 24-hour dietary recall of …