Date of Award

8-22-2025

Date Published

September 2025

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Exercise Science

Advisor(s)

Joon Young Kim

Second Advisor

Sara Vasilenko

Keywords

Insulin Sensitivity;Obesity;Young Adults;Youth

Subject Categories

Kinesiology | Life Sciences

Abstract

Parallel to the escalating rate of overweight and obesity in the youth and young adult population, the incidence and prevalence of type 2 diabetes are also mounting, presenting significant public health problems. Among the various pathophysiological factors, insulin sensitivity has emerged as a critical risk factor for impaired glucose tolerance (IGT) and type 2 diabetes in youth. Despite the pivotal role of insulin sensitivity in the development and progression of these conditions, current methodologies for its assessment, such as the hyperinsulinemic-euglycemic clamp and intravenous glucose tolerance test, are limited by their invasive methods, high cost, and unsuitability for use in large-scale clinical and observational studies. Moreover, existing predictive models, primarily derived from adult populations with a wide age range and/or limited racial/ethnic backgrounds, fail to address the unique metabolic characteristics and racial/ethnic disparities observed in insulin sensitivity among youth and young adults. This study introduces an innovative research initiative to develop and validate a Race-specific Insulin Sensitivity Estimator (RISE) based on physical and fasting-based metabolic characteristics using advanced machine learning techniques. Eventually, the RISE evaluated the effectiveness of High-Intensity Interval Training (HIIT) and Time-restricted eating (TRE) as lifestyle interventions designed to improve insulin sensitivity and reduce diabetes risk among young population with overweight and obesity. Further, RISE can be a tool for identifying responders and non-responders to lifestyle interventions. Taken together, this project addressed the critical need for an accurate and accessible tool to assess insulin sensitivity that considers racial/ethnic disparities in youth and young adults. The findings are clinically relevant as we not only created machine-learning-based RISE but also evaluated its applicability in a clinical trial focused on lifestyle changes in diabetes prevention (obesity treatment).

Access

Open Access

Available for download on Thursday, September 17, 2026

Included in

Kinesiology Commons

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