Evaluating Relationships Between Immunometabolism and Excess Adiposity Using Anthropometric and Body Composition Measurements

Authors

• Corina Grimaldo, University of Nebraska-LincolnFollow

First Advisor

Edward C. Deehan

Committee Members

Jennifer Auchtung, Weiwen Chai, Amanda Ramer-Tait

Date of this Version

7-2026

Document Type

Thesis

Citation

A thesis presented to the faculty of the graduate college at the University of Nebraska in partial fulfillment of requirements for the degree of Master of Science

Major: Food Science and Technology

Under the supervision of Professor Edward C. Deehan

Lincoln, Nebraska, July 2026

Comments

Copyright © 2026, Corina Grimaldo. Used by permission

Abstract

Metabolic dysfunction is a key contributor to the development of chronic disease and is associated with excessive adiposity. Though body mass index (BMI) is a common screening tool used to identify possible metabolic dysfunction, it does not consider fat distribution. Other tools are needed to assess body composition and determine fat distribution. In recent studies, it has been suggested that alterations in metabolic processes may occur prior to a clinical diagnosis, and the combination of body composition and blood-based markers can help identify those early changes. The overall objective of this study is to identify low-cost indicators of metabolic dysregulation in healthy adults by examining body composition and surrogate health markers. This cross-sectional study assessed relationships between body composition, diet, and metabolic health in healthy adults from the Lincoln area and surrounding communities. A biobank of stool and blood samples was established to support this and future studies. A total of 62 participants were enrolled and completed two visits over a one-week period. Study procedures included the collection of demographics, dietary, and lifestyle information, anthropometric body composition assessment, and collection of biospecimens. Results showed that BMI and BMI combined with waist circumference identified slightly more differences in surrogate health markers than percent body fat. Several insulin resistance, dyslipidemia, and anthropometric-based indices also differed across classification groups, supporting their use as low-cost indicators of early metabolic differences in apparently healthy adults. Although most participants did not meet the criteria for metabolic syndrome, many were classified as pre-metabolic syndrome, with waist circumference being the most common criterion met. Together, these findings suggest that anthropometric, body composition, and blood-based measures may provide complementary information for assessing early metabolic differences in apparently healthy adults. The cohort, biospecimens, and data collected through the biobank may support future studies examining how diet, the gut microbiome, and immune function relate to early metabolic dysfunction.

Advisor: Edward C. Deehan