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Obesity remains a public health challenge in the United States, projected to affect more than half of adults by 2030 and contribute to $1.4 trillion dollars in direct and indirect healthcare costs. Furthermore, nearly half of all cardio-metabolic conditions such as type 2 diabetes, hypertension, hyperlipidemia, and cardiovascular disease are attributable to obesity, and in particular, excess visceral adiposity. Visceral adiposity, adipose tissue surrounding internal abdominal organs, is pro-inflammatory, hormonally active, and atherogenic. Excess visceral adiposity (i.e. visceral obesity) is established to be causally associated with cardio-metabolic disease. Despite visceral obesity being one of the strongest risk factors for cardio-metabolic disease, there exist few tools to estimate it directly in the primary care setting. The purpose of this project is to develop an algorithm to estimate visceral adiposity, and understand the barriers to implementation of these measures and waist circumference into routine clinical practice, and ultimately provide the tools to develop a multimodal lifestyle intervention to reduce visceral abdominal obesity.
Aim 1. To develop, externally validate, and compare a novel algorithm to estimate visceral adiposity in the primary care setting to other published measures.
Aim 2. To understand barriers to implementation of clinical obesity measures (e.g. waist circumference, predicted visceral adiposity) and to integrate these measures into the electronic health record and routine outpatient healthcare workflow.
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