EVALUATING THE EFFECTS OF INTENTIONAL WEIGHT LOSS ON BONE HEALTH AMONG AGING INDIVIDUALS

Abstract

Over the past several decades, obesity has risen to epidemic proportions and is predicted to impact 1 in 4 people globally by 2035, if current trends prevail. While weight loss is an efficacious treatment for obesity and its concomitant comorbidities, mounting evidence suggests that among older populations, it negatively impacts bone health, accelerating aging-related skeletal fragility and increasing fracture risk. This dissertation uses biomedical images collected from older adult participants in two clinical trials to evaluate the influence of weight loss interventions on hip and spine musculoskeletal health indices. Collectively, this work contributes to the ongoing development of a noninvasive imaging and computational biomechanics pipeline for bone health assessment, including testing the performance of a machine learning model to automate the historically tedious process of image segmentation. The findings from the pipeline’s application to our current and future clinical trials research will serve to inform clinical recommendations for attenuating bone loss and mitigating fracture risk in older adults undergoing intentional weight loss.

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bone mineral density, bone strength, computed tomography, image segmentation, machine learning, obesity

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Wake Forest University