Demographic Multi-State Modeling of Chronic Diseases

描述(由申请人提供)：拟议的研究将继续发展人口统计多状态模型来研究慢性病过程。它关注的是一种综合征，它结合了与以前被认为无关的不同疾病相关的疾病：胰岛素抵抗综合征(IRS)。旨在识别定义IRS的症状群的因素分析方法会导致相互矛盾的结果。然而，胰岛素抵抗综合征通常被定义为包括空腹胰岛素、肥胖和血脂异常。IRS与代谢综合征(或代谢障碍综合征)密切相关，后者通常被定义为包括高血压和其他疾病。我们将开发一个潜在类别模型，其中一个类别具有IRS的三个基本组成部分的高风险。该模型将应用于来自多个来源的数据，以确定该综合征是否存在，定义它的基本症状是什么，以及是否有证据表明存在不止一个综合征。将对模型的变化数量进行测试，以确定结果是否稳健。该模型还将用于研究性别和种族/民族的差异，并提供对生命表中死因缺失的人口模型的见解。

DESCRIPTION (provided by applicant): The proposed research will continue the development of demographic multi-state models for studying chronic disease processes. It focuses on a syndrome that combines conditions associated with different diseases that were previously thought to be unrelated: the insulin resistance syndrome (IRS). Factor analytic approaches designed to identify the cluster of symptoms that define IRS lead to conflicting results. However, IRS is generally defined as including fasting insulin, obesity, and dyslipidemia. IRS is closely related to the metabolic syndrome (or dysmetabolic syndrome), which is generally defined as including hypertension and often other conditions. We will develop a latent class model with one class having elevated risks of the three basic components of IRS. The model will be applied to data from multiple sources to determine if the syndrome exists, what are the basic symptoms that define it, and whether there is evidence of more than one syndrome. The number of variations of the model will be tested to determine if the results are robust. The model will also be used to study differences by sex and race/ethnicity and to provide insights into demographic models of cause-of-death deletion in life tables.