Dissertation/Thesis Abstract

Chrononutrition: Associations between Regular Eating Patterns and Body Composition
by Delane, Desiree, M.S.N., Bastyr University, 2017, 95; 10599456
Abstract (Summary)

Background: Contemporary eating patterns reflect dynamic temporal responses to environmental stimuli. Individual eating behaviors are influenced by many interrelated factors and are difficult to characterize. Chrononutrition is gaining recognition as observations of inconsistent eating patterns have emerged with the prevalence of obesity. Investigations evaluating eating frequency and timing associated with body composition have produced equivocal results. This study created methodology to objectively classify regularity in terms of eating occasion frequency (EO), time intervals (TI) between EO, and energy intake (EI) and to analyze variability and temporal distributions within and between individuals in relation to body composition.

Methods: Analyses of data from participants (N=126) in the USDA Nutritional Phenotyping study evaluated relationships between eating pattern variables and body composition. EO, TI, and EI were assessed for age, gender, BMI, waist circumference, and body fat percentage. Coefficients of variation (CV) for eating pattern variables were used to assign regularity scores. EO and EI were examined by daily temporal distributions. Statistical models were employed to predict body composition by CV, score, and temporal distribution.

Results: Regularity scores for EI differed significantly by gender (Females, N=44; Males, N=18); no scores significantly predicted body composition variables. Regression analyses with CV suggested a positive association between BMI and EI. Afternoon and evening time categories contained greatest EO and highest EI.

Conclusions: Eating patterns reflect inconsistency between participants; within-individual variability was not significantly related to eating frequency or timing and body composition. Results suggest that daily EI may be more regular in females, and EI variation may predict BMI. Temporal analyses imply late-day eating patterns. Future studies should improve upon methodology for regularity classification and consider confounds. Findings provide foundations for continued research and recommend personalized approaches to nutrition.

Indexing (document details)
Advisor: Kazaks, Alexandra
Commitee: Bartok, Cynthia, Harris, Cristen
School: Bastyr University
Department: Department of Nutrition
School Location: United States -- Washington
Source: MAI 56/05M(E), Masters Abstracts International
Source Type: DISSERTATION
Subjects: Biostatistics, Nutrition, Public health
Keywords: Body composition, Chrononutrition, Eating patterns
Publication Number: 10599456
ISBN: 9780355102789
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