Measurement Variability Related to Insulin Secretion and Sensitivity : Assessment and Implications in Epidemiological Studies

There is a growing interest in random measurement variability of biological variables. In regression models, such variability of the predictors yields biased estimators of coefficients (regression dilution bias). The objectives of this thesis were to develop an efficient method to correct for such bias, to reveal the relative importance of insulin sensitivity and insulin secretion, corrected for regression dilution bias, on glucose tolerance, and to explore the seasonal nature of the variability of insulin sensitivity. A reliability study is often designed to randomly select subjects from the main study. Our idea was to collect replicates for subjects with extreme values on their first measurement. The extreme selection design, in combination with maximum likelihood estimation, resulted in an efficient estimator of a corrected regression coefficient in a simple linear regression model. Results were presented theoretically and with an application: The relation between insulin sensitivity and fasting insulin in Uppsala Longitudinal Study of Adult Men (ULSAM) where the extreme selection design decreased the standard error of the estimated regression coefficient with 28 per cent compared with the random sampling design. We estimated the partial longitudinal effects of the predictors insulin sensitivity and insulin secretion, corrected for regression dilution bias, on glucose tolerance in ULSAM. The effects of the predictors, when corrected, were similar. Insulin sensitivity in ULSAM increased during summer and decreased during winter and insulin secretion exposed opposite variation keeping glucose homeostasis nearly constant. Insulin sensitivity was related to outdoor temperature. In summary, we developed a cost-efficient reliability design for correction for regression dilution bias. Insulin sensitivity and insulin secretion had similar longitudinal effects on glucose tolerance, which implies that interventions aimed at these targets are equally important. Further, we revealed the seasonal nature of variations of insulin sensitivity and insulin secretion. This result has implications on glycaemic control in diabetic patients