title: Biologic risk markers for coronary heart disease: nonlinear associations with income.
abstract: BACKGROUND
  It is unclear whether a linear relationship is an appropriate description of the association between income and biologic markers of coronary heart disease risk. Stronger associations at certain levels of income would have implications for underlying mechanisms.
  
  
  METHODS
  The study is based on a healthy sample of 25-64 year olds (n = 14,022) from a nationally representative cross-sectional study (the 1988-1994 United States Third National Health and Nutrition Examination Survey). We use regression splines to model the shape of the association between income and 8 biologic markers for coronary heart disease risk, controlling for age, race/ethnicity, marital status, and education.
  
  
  RESULTS
  Substantial income-biomarker associations were found for 5 outcomes among women (HDL cholesterol, triglycerides, C-reactive protein, systolic blood pressure, and venous blood lead) and for 3 outcomes among men (HDL cholesterol, triglycerides, and venous blood lead). The most common shapes of association were a stronger association at lower income levels and a greater risk level of biomarker near median income.
  
  
  CONCLUSIONS
  We find that the associations of income with biologic risk markers are often nonlinear. The differences in the shape of association suggest there are multiple pathways through which income is associated with coronary heart disease risk.
authors.affiliation: Department of Society, Human Development and Health, Harvard School of Public Health, Boston, MA, USA. drehkopf@gmail.com
authors.forename: David H
authors.initials: DH
authors.lastname: Rehkopf
authors.forename: Nancy
authors.initials: N
authors.lastname: Krieger
authors.forename: Brent
authors.initials: B
authors.lastname: Coull
authors.forename: Lisa F
authors.initials: LF
authors.lastname: Berkman
mesh_terms: D000328:Adult; D015415:Biomarkers / Q000097:blood*; D003324:Coronary Artery Disease / Q000097:blood / Q000191:economics / Q000453:epidemiology*; D005260:Female; D006801:Humans; D007182:Income; D008297:Male; D008875:Middle Aged; D017711:Nonlinear Dynamics; D009749:Nutrition Surveys; D012306:Risk
chemical_list: D015415:Biomarkers