MODELING THE COEXISTENCE OF CHRONIC DISEASES RELATED TO OBESITY

项目摘要/摘要 肥胖症在美国很普遍。它与多种严重的慢性病有关。然而， 肥胖相关多发病的健康和经济后果(多种慢性疾病并存 疾病)在一生中没有得到广泛的研究。拟议的研究将使用一种 用定量建模方法研究肥胖、多种肥胖并存与肥胖的关系 相关慢性病(ORCDs)，以及美国40岁或以上人口的死亡率。此外，我们还将 调查与这些ORCDs相关的寿命损失年数和终生医疗费用。我们将使用三个大的， 具有全国代表性的数据集：医疗支出小组调查，国民健康访谈 调查，以及国民健康和营养检查调查。我们将针对5个ORCD，包括 高血压、高胆固醇、糖尿病、冠心病和中风。具体地说，我们将估计 目标人群患ORCDs的终生风险和死亡率(目标1)；获得年度保健 ORCDs在整个生命周期中的成本(目标2)；美国BMI的预测轨迹和分布 人口年龄≥40(目标3)；并开发马尔可夫模型以确定终生健康和经济 肥胖和ORCDs的后果(目标4)。拟议的研究在模型的使用方面是创新的 调查肥胖和多发性ORCDs的健康和经济后果的方法，这有 在它的终生视野中；在它对个人身体质量指数的预测和使用方面； 时间到了。据我们所知，这是第一次这样做的研究。这个项目的重大意义在于它有能力 为目前缺乏临床研究的证据基础做出贡献，因为其复杂性、大规模和 终生的地平线自然。这项研究的结果与人口健康的核心指标相一致 由医学研究所推荐。因此，这项研究将有助于理解 美国普通人群中的多发病负担。此外，所研究的多发病的影响 将未来临床试验的重点和设计从单一疾病和 排除多病并存的患者，改善患者的预后 多个并发条件。这项拟议的研究将是弥合建模差距的开创性步骤 多发病，这是一项相当重要的工作，因为目前肥胖症的流行和 美国的老龄化速度很快。展望未来，结果将提供几个R21的初步数据， R01或同等的应用程序。所构建的建模框架可以在以后的研究中使用 项目，如探索其他慢性病和癌症的共存情况，检查比较 肥胖治疗的有效性，例如，运动、饮食控制、药物和手术，或评估 关于实现减少肥胖目标的最佳干预措施的政府卫生政策 流行率。

PROJECT SUMMARY/ABSTRACT 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.