OBJECTIVES: To identify and characterize subclasses of patients with dyslipidemia in a nationally representative sample using Latent Class Analysis (LCA). METHODS: Dyslipidemia patients were identified from a national database of electronic medical records containing diagnosis, lab and medication information in primary care setting from 1997 to 2004. LCA was applied to patient classification based on patient demographics, biomarker measures (low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), and triglyceride (TG)), and pre-existing coronary heart disease (CHD), diabetes and hypertension. RESULTS: There were 72,533 patients included in this analysis. All information indices and Lo-Mendell-Rubin test consistently suggested that a 5-class model fit the data best. Patients were classified into one of the five classes with sizes of 17.7%, 9.6%, 29.4%, 32.6% and 10.8%, respectively. Patients in Class 1 were featured with 34.4% of HDL-C and 39.5% of TG abnormalities and high prevalence of CHD (29.6%), diabetes (31.5%), and hypertension (78.2%). Patients in Class 2 shared similar lipid-profile as those in Class 1, but smaller percent of them carried co-morbidities. Classes 3 and 4 were dominated by those with high LDL-C and TC, but higher percent of patients in Class-3 had co-morbidities. Class 5 was characterized by patients with abnormalities for all four biomarkers (80.0% for LDL-C, 76.8% for HDL-C; 99.4% for TC, and 81.4% for TG). Patients in Classes 1 and 3 were more likely on antidyslipidemics at diagnosis, suggesting that co-morbid CHD, diabetes and hypertension are strong predictors of pharmacotherapy in primary care setting. CONCLUSION: LCA appears to offer a useful approach to studying case-mix of patients with dyslipidemia by classifying patients into clinically similar sub-groups, which might provide better insights to understand unmet needs and identify appropriate treatment options. Our findings suggest that co-morbidities play a major role in driving antidyslipidemic use in primary care setting.