"Something else to remember is that the coefficients on a model with natural splines defy any sort of interpretation. So forget using the “1-unit increase in x leads to a __ increase in y” method to explain association. An alternative approach is an effect plot, which allows you to visualize your model given certain predictor values. "
So, ignoring that Jake and Dason and hlsmith know what they are talking about, how does one interpret the impact of a predictor that has a non-linear relationship to Y? Just run the regression at certain levels of X?