Generalized Additive Models applied to analysis of the relation between amount and type of alcohol and all-cause mortality

Abstract

The J-shaped relation between alcohol intake and mortality is well established, whereas the nadir of the curve is not determined. Due to non-linearity of the relation, categorical alcohol variables have been used to model the relation. In Generalized Additive Models (GAM) non-linear relations can be modelled without the disadvantages of categorization and without assumptions regarding the functional form. The aim of this study was to use GAM to evaluate the relation between alcohol intake, amount and type, and mortality. The relation was investigated using data from the Copenhagen City Heart Study (11,920 participants of whom 5552 died during 20 years follow-up). Using GAM, a smooth J-shaped relation between alcohol and mortality was found. However, if non-drinkers were categorized separately there was a positive association between alcohol and mortality even for low alcohol intake. For equal total alcohol intake, men and women drinking wine or spirits had lower mortality than beer drinkers. The nadir of the relation between alcohol and mortality was sensitive to the handling of non-drinkers. When non-drinkers were categorized separately we found no indication of a beneficial influence of low alcohol intake on mortality.