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.
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