Estimating and presenting non-linear associations with restricted cubic splines

Most of the regression models commonly used in epidemiology-including logistic regression and methods for time-to-event outcomes such as Cox regression-define the relationship between a set of covariates and the outcome of interest using linear functions, thus making implicit assumptions of linearity for continuous covariates. Categorizing continuous covariates, which represents a common option to address non-linearities, introduces additional assumptions and has recognized limitations in terms of results interpretation. Restricted cubic splines (RCS) offer a flexible alternative tool that can improve the model fit in the presence of non-linear associations, overcoming many of the limitations of categorical…