Structural equation modeling of food craving across the menstrual cycle T using behavioral, neuroendocrine, and metabolic factors

Authors

Sridevi Krishnan, University of California, DavisFollow
Karan Agrawal, University of California, Davis
Rebecca R. Tryon, University of California, Davis
Lucas C. Welch, University of California, Davis
William F. Horn, University of California, Davis & USDA, ARS, Western Human Nutrition Research Center, Obesity and Metabolism Research UnitFollow
John W. Newman, University of California, Davis & USDA, ARS, Western Human Nutrition Research Center, Obesity and Metabolism Research UnitFollow
Nancy L. Keim, University of California, Davis & USDA, ARS, Western Human Nutrition Research Center, Obesity and Metabolism Research UnitFollow

Document Type

Article

Date of this Version

2018

Citation

Physiology & Behavior 195 (2018) 28–36

https://doi.org/10.1016/j.physbeh.2018.07.011

Comments

U.S. government works are not subject to copyright.

Abstract

Objective: To identify associations between circulating endocannabinoids and craving during the luteal phase of the menstrual cycle. This report is a secondary analysis of a trial registered in clinicaltrials.gov as NCT01407692. Methods: Seventeen premenopausal women were studied during the follicular and luteal phases of their menstrual cycle. Previously we had reported fasting plasma estradiol, progesterone, leptin associations with luteal phase cravings for carbohydrate, fat, sweet-rich foods, and eating behavior. Here, we measured fasting plasma endocannabinoids (ECs) endocannabinoid-like substances (ECLs), and postprandial metabolic responses to a mixed meal challenge. Structural equation modeling was used to evaluate relationships between measured variables and cravings.

Results: Oleoylethanolamide (OEA) and postprandial lipids were inversely associated with craving sweet-rich foods, while progesterone was positively associated (RMSEA = 0.041, χ2 p: 0.416 i.e. hypothetical and physiological models not different). OEA, progesterone and disinhibition were positively associated with craving carbohydrates (RMSEA: < 0.001, χ2 p: 0.919). ECs and ECLs combined were stronger predictors of craving than clinical metabolic parameters, ECs only, satiety hormones or gonadocorticoids.

Conclusions: Our theoretical model suggests that ECs and ECLs influence craving. Since these metabolites can be modulated via dietary fat intake, they could be potential targets to alter menstrual cycle cravings.