Intervening on risk factors for coronary heart disease: an application of the parametric g-formula

Int J Epidemiol. 2009 Dec;38(6):1599-611. doi: 10.1093/ije/dyp192. Epub 2009 Apr 23.


Estimating the population risk of disease under hypothetical interventions--such as the population risk of coronary heart disease (CHD) were everyone to quit smoking and start exercising or to start exercising if diagnosed with diabetes--may not be possible using standard analytic techniques. The parametric g-formula, which appropriately adjusts for time-varying confounders affected by prior exposures, is especially well suited to estimating effects when the intervention involves multiple factors (joint interventions) or when the intervention involves decisions that depend on the value of evolving time-dependent factors (dynamic interventions). We describe the parametric g-formula, and use it to estimate the effect of various hypothetical lifestyle interventions on the risk of CHD using data from the Nurses' Health Study. Over the period 1982-2002, the 20-year risk of CHD in this cohort was 3.50%. Under a joint intervention of no smoking, increased exercise, improved diet, moderate alcohol consumption and reduced body mass index, the estimated risk was 1.89% (95% confidence interval: 1.46-2.41). We discuss whether the assumptions required for the validity of the parametric g-formula hold in the Nurses' Health Study data. This work represents the first large-scale application of the parametric g-formula in an epidemiologic cohort study.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Alcohol Drinking / adverse effects
  • Alcohol Drinking / epidemiology
  • Cause of Death
  • Cohort Studies
  • Coronary Disease / epidemiology*
  • Coronary Disease / mortality
  • Coronary Disease / prevention & control*
  • Exercise / physiology
  • Female
  • Health Behavior
  • Humans
  • Life Style
  • Mathematics*
  • Middle Aged
  • Models, Statistical*
  • Risk Assessment
  • Risk Factors
  • Smoking / adverse effects
  • Smoking / epidemiology
  • Weight Loss