I'm not sure what the question is. The model which specifies
random personID;
fits a model with a random intercept term, whereas the model which specifies
random intercept age diet / sub=personID;
fits a model in which each person has their own age slope and their own diet slope. Are you wondering if the model with person-specific age and diet slope effects produces a model which has better fit to the data, then you could use a likelihood ratio test.
Note that this second model would only seem to be valid if each person was observed on multiple diets. If each person receives only a single diet, then there would be no data that would allow you to compute a person-specific diet slope effect. Also, if each person receives only a single diet, then the subject effect should be nested within diet.