Methodology for Classifying Regularity of Eating Patterns Through Within‐Subject Variability in Dietary Recall Variables
Authors: Delane Desiree , Kazaks Alexandra , Harris Cristen , Bartok Cynthia , Baldiviez Lacey M , Stephensen Charles B , Keim Nancy L 
Published: November 2023

Background/Objective

Daily variability in eating occasion frequency (EO), time intervals (TI) between EOs, and energy intakes (EI) contributes to the concept of irregular individual eating patterns. The idea of “chrononutrition” has emerged through recognition of human biological clocks that respond to changes in nutrient timing. Inconsistent eating patterns may disrupt synchronization of cellular rhythms and interfere with energy metabolism. The objective is to develop valid methodology for classifying regularity of individual eating patterns from dietary recall data.

Methods

Regularity of individual eating patterns is defined as a function of variability in daily EO, TI, and EI. Data from four 24‐hour complete dietary recalls per subject will be systematically evaluated to identify these variables. Means and standard deviations will be employed to calculate a daily coefficient of variation (CV) for each parameter in comparison to its cumulative mean. A test of homogeneity will assess between‐day and between‐subject differences.

Classification of individual subjects into regular and irregular eating pattern types will be defined through comparisons of the CV for each variable. Median CVs for EO, TI, and EI will establish separation criteria in the assignment of eating pattern type.

Results/Application

Data is drawn from dietary recall and anthropometric data from the USDA Nutritional Phenotyping study ongoing at the Western Human Nutrition Research Center at the University of California, Davis. Current volunteer study participants, recruited locally between May 2015 and November 2016, include 118 healthy adults aged 19‐66 years old (mean 37.5 ± 13.9), 40% male and 60% female, and BMI between 18.5‐39.9 kg/m2 (range 19.2‐41.7; mean 26.6 ± 4.0). Anthropometric data were collected from initial in‐person screenings. Dietary recalls were completed through one in‐person training session and three at‐home random prompts. Significant differences between CVs for training and at‐home recalls will be examined to confirm validity of including training data.

Also known as relative standard deviation, CV is a unitless measure, appropriate for comparing variability between different parameter types. The present analysis provides a unique examination of the CV for multiple variables in categorizing subjects according to regular or irregular patterns of eating. Multi‐pass 24‐hour dietary recalls completed at multiple, non‐consecutive time points are valid estimates of usual intake. The methodology is subject to sampling error, and statistical power increases with number of participants and quantity of individual recalls. Classification of subjects into eating pattern categories creates an independent variable that can be applied in more complex correlational or regression analyses.

Conclusions

Establishing a valid methodological process for classifying eating pattern types may facilitate future investigations of relationships between eating patterns and nutrition‐related outcomes. A focus on consistency in individual eating behaviors may offer a more personalized approach to dietary strategies than deriving assumptions from group‐based models.