Obesity is prevalent in the United States. It is associated with multiple serious chronic diseases. However, the health and economic consequences of obesity-related multimorbidity (the coexistence of multiple chronic diseases) in a lifetime horizon have not been extensively studied. The proposed research will use a quantitative modeling approach to study the relationship between obesity, the coexistence of multiple obesity- related chronic diseases (ORCDs), and mortality in the U.S. population age 40 or older. Moreover, we will investigate life years lost and lifetime healthcare costs associated with these ORCDs. We will use three large, nationally representative datasets: the Medical Expenditure Panel Survey, the National Health Interview Survey, and the National Health and Nutrition Examination Survey. We will target 5 ORCDs, including hypertension, high cholesterol, diabetes, coronary heart disease, and stroke. Specifically, we will estimate lifetime risks of developing ORCDs and mortality for the target populations (Aim 1); obtain annual healthcare costs of ORCDs throughout the lifetime (Aim 2); forecast trajectory and distribution of BMI for the U.S. population age ?40 (Aim 3); and develop a Markov model to determine lifetime health and economic consequences of obesity and ORCDs (Aim 4). The proposed research is innovative in its use of modeling approaches to investigate the health and economic consequences of obesity and multiple ORCDs, which have been under-studied; in its lifetime horizon perspective; and in its prediction and use of individuals' BMI over time. To our knowledge, this is the first such study to do so. This project is significant in its capability to contribute to an evidence base that is currently devoid of clinical studies due to its complexity, large scale, and lifetime horizon nature. The outcomes of this research correspond to the core metrics for population health recommended by the Institute of Medicine. Therefore, this research will be instrumental in understanding the burden of multimorbidity in the U.S. general population. Moreover, the studied impact of multimorbidity has the potential to shift the focus and design of future clinical trials from one single disease and excluding patients with multiple conditions to multimorbidity and improving outcomes of patients with multiple concurrent conditions. The proposed research will be a seminal step in bridging the gap in modeling multimorbidity, an undertaking of considerable importance given the current prevalence of obesity and the rapid aging in the United States. Looking to the future, the results will provide preliminary data for several R21, R01, or equivalent applications. The modeling framework built in the proposed research can be used in future projects, such as exploring the coexistence of other chronic diseases and cancer, examining comparative effectiveness of treatments of obesity, e.g., exercise, diet control, medication, and surgery, or evaluating government health policies with regard to optimal interventions to achieve the goal of reduction in obesity prevalence.
RELEVANCE: The lifetime health and economic consequences of obesity in the context of multiple obesity- related chronic diseases are understudied and of critical importance considering the prevalence of obesity and multimorbidity in the United States. In the proposed study we seek to use a quantitative modeling approach to study obesity, the coexistence of obesity-related chronic diseases, and mortality in the United States in terms of life expectancy and lifetime healthcare costs.
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