title: Including socioeconomic status in coronary heart disease risk estimation.
abstract: OBJECTIVE
  Socioeconomic status (SES) predicts coronary heart disease independently of the Framingham risk-scoring factors included in cholesterol treatment guidelines, possibly resulting in undertreatment of lower SES persons. We examined whether hybrid SES measures (based on area measures of income and individual education) address this bias and derived an approach to incorporating SES information into treatment guidelines.
  
  
  METHODS
  The Atherosclerosis Risk in Communities study data (initiated in 1987 with a 10-year follow-up of 15,495 adults aged 45 to 64 years in 4 southern and midwestern communities) were used to assess the calibration bias of 4 Cox models predicting 10-year coronary heart disease risk: Framingham risk score alone, and Framingham risk score plus SES using an individual-based measure (income less than 150% federal poverty level or less then 12 years of schooling), and 2 hybrid SES measures substituting area-based income measures (block group or zip code median incomes of less than 25th national percentiles) for the individual income component. Revised cholesterol treatment thresholds based on SES risk were also derived.
  
  
  RESULTS
  Use of either the block group hybrid or individual-based SES measures eliminated the significant SES bias observed using Framingham risk score alone. Cholesterol treatment guideline thresholds of 10% and 20% coronary heart disease risk (based on the Framingham risk score) were reduced to 6% and 13% for those with low SES.
  
  
  CONCLUSIONS
  Using patient income based on block group and individual education minimizes the SES bias in Framingham risk scoring and suggests more aggressive cholesterol treatment thresholds for low-SES persons.
authors.affiliation: Center for Healthcare Policy and Research, Sacramento, California, USA. pfranks@ucdavis.edu
authors.forename: Peter
authors.initials: P
authors.lastname: Franks
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Tancredi
authors.forename: Paul
authors.initials: P
authors.lastname: Winters
authors.forename: Kevin
authors.initials: K
authors.lastname: Fiscella
mesh_terms: D000368:Aged; D003327:Coronary Disease / Q000453:epidemiology* / Q000209:etiology; D005260:Female; D006801:Humans; D007182:Income / Q000706:statistics & numerical data*; D053208:Kaplan-Meier Estimate; D008297:Male; D008875:Middle Aged; D012111:Residence Characteristics / Q000706:statistics & numerical data*; D012307:Risk Factors; D012923:Social Class; D012959:Socioeconomic Factors; D013997:Time Factors; D014481:United States / Q000453:epidemiology