Elevated low density lipoprotein cholesterol (LDL-C) levels are a major risk factor for coronary heart disease. One approach to determining some of the factors responsible for elevated LDL-C has involved performing lipoprotein turnover studies. Such studies determine the pathways of lipoprotein metabolism and quantify the rates of production and catabolism of the different lipoprotein species. With the technology now readily available for using stable isotopes to trace the different apolipoproteins, there has been renewed interest in performing such studies. In addition, with the use of stable isotopes has come the ability to perform multiple turnover studies in the same individual under different experimental conditions, such as drug therapy and/or dietary changes. The use of radioactive tracers in the past limited the experimenters ability to perform multiple turnover studies because of risks associated with radiation exposure. Many compartmental models of lipoprotein metabolism have been developed in the past thirty years (1 -5). S10b models have been fit to an individual's data set to determine the kinetic parameters of interest. To deternibw group kinetic parameters, averages of the kinetic parameters are calculated ignoring the errors associated WW the individual parameters or the covariances between the parameters. Further, no studies have integrated tile information obtained following the fitting process with other covariates, such as measures of obesity hypertension, dyslipidernia and insulin resistance. Conclusions drawn from tracer studies may be confoUn by the lack of understanding of population variability and also because covariates have not been included in% analysis of the kinetic data
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