(PO11-04-22) Body Composition Measures Associated With Postprandial Triglyceride Concentrations

The ePoster content is available to NUTRITION 2022 LIVE ONLINE attendees who are logged in.<br><br>If you are registered, log in and then come back here to use this button.

Presenting Author(s)

SF

Sadie A. Freudenberger, BSHS
– Undergraduate Student, Oklahoma State University, Stillwater, Oklahoma, United States

Co-Author(s)

Bryant H. Keirns, MS
– Graduate Student, Oklahoma State University, Stillwater, Oklahoma, United States
Christina M. Sciarrillo, PhD, RD
– Graduate Research Assistant, Oklahoma State University, Sugar Land, Texas, United States
KP

Kara L. Poindexter
– Oklahoma State University
MD

Madison D. Dixon
– Oklahoma State University
SH

Sam M. Hart
– Oklahoma State University
SE

Sam R. Emerson, PhD
– Assistant Professor, Oklahoma State University, Stillwater, Oklahoma, United States

Disclosure(s):

Sadie A. Freudenberger, BSHS: No relevant financial relationship(s) with ineligible companies to disclose.

Bryant H. Keirns, MS: No relevant financial relationship(s) with ineligible companies to disclose.

Christina M. Sciarrillo, PhD, RD: No relevant financial relationship(s) with ineligible companies to disclose.

Objectives: A large increase in triglyceride (TG) concentrations following a high-fat meal (i.e., postprandial lipemia) is an independent cardiovascular disease risk factor. However, little is known regarding individual factors that are associated with or determine postprandial triglycerides. We aimed to identify body composition measures that are associated with postprandial triglyceride concentrations following a high-fat meal.

Methods: We conducted a secondary analysis of data from 5 previously conducted studies in our laboratory, each utilizing identical methods. Postprandial TG were measured at baseline and 4 hours after a high-fat shake (73% fat; 9kcal/kg). In addition to body mass index (BMI) and waist circumference (WC), body composition variables – relative body fat (BF%), relative muscle mass (MM%), and visceral adipose tissue (VAT) – were measured via bioelectrical impedance.

Results: Across 5 studies, complete data from 156 participants (age: 44.9 ± 21.0 years; sex: 83F/73M; BMI: 27.3 ± 5.5 kg/m²; fasting glucose: 98.6 ± 7.8 mg/dL; fasting TG: 94.6 ± 45.3 mg/dL; fasting total cholesterol: 170.8 ± 34.5 mg/dL) were compiled for this secondary analysis. Postprandial TG were correlated with age (r = 0.24, p = 0.003) but no difference between sexes was observed (p = 0.06). Significantly associated with 4-hr TG were BMI (r = 0.29, p < 0.0001), WC (r = 0.33, p < 0.0001), BF% (r = 0.23, p = 0.004), MM% (r = 0.23, p = 0.004), and VAT (r = 0.35, p < 0.0001). In a backward elimination regression (R² = 0.15), the variables most predictive of 4-hr TG were MM% (β = 0.21, p = 0.009), VAT (β = 0.25, p = 0.004), and BF% (β = 0.16, p = 0.064).

Conclusions: In a secondary analysis of 156 participants across 5 studies, we identified MM%, VAT, and BF% as being the most predictive of 4-hr TG. Although the strength of the relationship may be weak to moderate, body composition appears to influence postprandial triglycerides. Further research could determine preventative measures regarding body composition to lower the risk of cardiovascular disease associated with postprandial triglycerides.

Funding Sources: Oklahoma Center for the Advancement of Science and Technology (HR20-027), American Society for Nutrition, Donna Cadwalader Research and Development Grant, Oklahoma State University Office of the Vice President for Research.