Association between Major Non-communicable Diseases Risk Factors and Fasting Blood Glucose in Iran: Comparison of Two Techniques, with and Without Dichotomizing the Response

Abstract

Background: Dichotomizing a continuous outcome variable is a common approach to estimate the odds ratio (OR) as a measure of association. In the present study we aimed to compare a non-dichotomizing technique with logistic regression which exploits dichotomizing the response for estimating OR. Method: Data including a total of 17,152 Iranian individuals aged 25–65 years were derived from the third national survey of non-communicable Diseases Risk Factors in Iran. To measure the associations between fasting blood glucose and attributed risk factors two distinct techniques were used. Using a non-dichotomizing technique, an approach proposed by B.K. Moser and L. Coombs (2004) was employed to estimate odds ratios and associated 95% confidence intervals (CIs); A binary logistic regression model was also applied to fit the data as a common dichotomizing approach. Finally the results of two methods were compared by use of relative efficiencies and relative length of CIs. Results: The odds ratios provided by both approaches are approximately the same, but relative efficiencies and relative length of CIs are greater than 2 which reflected better results for the technique used a non-dichotomizing approach compared to Logistic Regression Model. Conclusions: Dichotomizing continues outcome variable is not necessary to estimate ORs, especially when there is no pre-specified optimal cut-off point for the response variable.