title: Risk-factor clustering and cardiovascular disease risk in hypertensive patients.
abstract: BACKGROUND
  Patients with hypertension often have other major risk factors for cardiovascular disease (CVD). Little is known, however, about the extent of risk-factor clustering in these patients and its importance in CVD risk and medical-care costs.
  
  
  METHODS
  Study subjects were selected from the electronic medical records system of Kaiser Permanente Northwest, a large health maintenance organization, and included all patients aged > or =35 years with hypertension who were free of CVD in 1998. Subjects were stratified into eight risk-factor clusters based on whether or not they also had diabetes, hyperlipidemia, or a high body mass index (BMI). The risk of cardiovascular events was examined in each cluster over 6 years beginning January 1, 1999, using Kaplan-Meier methods and Cox proportional hazards models. Cumulative total medical-care costs (per patient) over 6 years also were examined.
  
  
  RESULTS
  A total of 57,573 patients with hypertension who were free of CVD in 1998 were identified; 56% of subjects also had diabetes, hyperlipidemia, or high BMI. In analyses controlling for age, sex, and smoking status, the relative risk of cardiovascular events over 6 years was highest for patients with comorbid diabetes, ranging from 2.07 (95% confidence interval, 1.86-2.30) for those with diabetes only to 2.80 (95% confidence interval, 2.48-3.17) for those with diabetes, hyperlipidemia, and high BMI. Cumulative medical-care costs generally increased with additional risk factors. Comorbid diabetes had the greatest impact on costs over 6 years.
  
  
  CONCLUSIONS
  More than 50% of patients with hypertension also had diabetes, hyperlipidemia, or high BMI. Patients with these additional risk factors (especially diabetes) had a substantially higher CVD risk and medical-care costs.
authors.affiliation: Policy Analysis, Inc., Brookline, Massachusetts 02445, USA. dweycker@pai2.com
authors.forename: Derek
authors.initials: D
authors.lastname: Weycker
authors.forename: Gregory A
authors.initials: GA
authors.lastname: Nichols
authors.forename: Maureen
authors.initials: M
authors.lastname: O'Keeffe-Rosetti
authors.forename: John
authors.initials: J
authors.lastname: Edelsberg
authors.forename: Zeba M
authors.initials: ZM
authors.lastname: Khan
authors.forename: Satyin
authors.initials: S
authors.lastname: Kaura
authors.forename: Gerry
authors.initials: G
authors.lastname: Oster
mesh_terms: D000367:Age Factors; D000368:Aged; D002318:Cardiovascular Diseases / Q000150:complications* / Q000191:economics*; D016000:Cluster Analysis; D048909:Diabetes Complications / Q000150:complications / Q000191:economics; D005260:Female; D017048:Health Care Costs / Q000706:statistics & numerical data*; D006801:Humans; D006949:Hyperlipidemias / Q000150:complications / Q000191:economics; D006973:Hypertension / Q000150:complications* / Q000191:economics; D053208:Kaplan-Meier Estimate; D008297:Male; D024821:Metabolic Syndrome / Q000150:complications / Q000191:economics; D008875:Middle Aged; D009765:Obesity / Q000150:complications / Q000191:economics; D016016:Proportional Hazards Models; D012307:Risk Factors; D012737:Sex Factors; D012907:Smoking / Q000009:adverse effects