Association of serum total cholesterol with coronary disease and all-cause mortality: multivariate correction for bias due to measurement error.

Abstract

Measurement error in the exposure under investigation is an important but often ignored source of bias in observational studies. The authors examined the impact of measurement error in the association between total serum cholesterol and 16-year coronary heart disease and all-cause mortality in a cohort of 6,137 middle-aged men of Japanese descent in the Honolulu Heart Program (1973-1988). A Cox regression model that enables modeling of survival time with correction for measurement errors in multiple covariates was employed. After controlling for age, body mass index, systolic blood pressure, smoking status, alcohol consumption, dietary cholesterol, and total calorie intake, a difference of one standard deviation (38 mg/dL) in total cholesterol was associated with a significant increase in the risk of coronary disease death (uncorrected hazard ratio = 1.35). After correction for measurement errors in total cholesterol and covariates (except smoking and age), the estimated hazard ratio increased to 1.65 (a 22% increase). A U-shaped relation was observed between total cholesterol levels and the risk of all-cause mortality. This association was then examined with a quadratic model and with a two-slope or V-shaped regression model. In the quadratic fit, the magnitude of the quadratic total cholesterol term increased threefold after the adjustment for measurement error. In the V fit, the hazard ratio of all-cause death corresponding to a change in one standard deviation above 214 mg/dL (the nadir of the V) was 1.15, and increased to 1.49 (by 29%) after the correction. The corresponding hazard ratio of a change in one standard deviation below 214 mg/dL was 1.11, and increased to 1.37 (by 23%) after the correction. The authors conclude that the impact of elevated total cholesterol on the risk of coronary disease and all-cause mortality may be greater than previously estimated with standard methods of analysis. In addition, the correction for measurement error in total cholesterol and covariates did not explain the excess mortality associated with low total cholesterol. More research is needed to elucidate the fundamental issues underlying the U-shaped association, i.e., confounding versus causal implications.