Underestimating the Effect of Lipids on Cardiovascular Events: Regression Dilution Bias in the Population-Based Cohort of Tehran Lipid and Glucose Study

Background: Random errors in the measurement of risk factors lead to bias in the exposure-disease association. Objectives: This study aimed to examine the extent of underestimation in the association of total cholesterol (TC), high density lipoprotein cholesterol (HDL-C) and triglyceride (TG) with cardiovascular disease (CVDs) in the Tehran Lipid and Glucose Study. Patients and Methods: Of 6327 eligible people in the original cohort followed for about 10 years to detect CVD events, 3063 (1224 men and 1839 women) had replicate measurements for blood lipids. Two regression dilution ratios were calculated by nonparametric and parametric methods, using replicate data from reexaminations three and six years after baseline. Adjusted and unadjusted hazard ratios (HR) were corrected for regression dilution bias. Results: By parametric method, based on reexamination three years after baseline, the strength of real association of usual levels of TC, TG and HDL-C with cardiovascular disease, considering β coefficients of related models, were underestimated about 42%, 51% and 81% in men and 40%, 43% and 62% in women, respectively. Underestimations were relatively independent of age, sex and body mass index. Correction for regression dilution bias led to more than 60% increase in estimated HR for TC adjusted for confounders. Conclusions: Using baseline measurements of lipids led to considerable underestimation in the association of these factors with CVD outcome in TLGS. The underestimation increased with time interval between baseline and follow-up measurements for TC and TG. TC had more attenuation on estimated HR due to stronger relation with CVD risk.