Usually the condition of the validity of a logistic regression is to have 10 events per predictor.
In our model the binary outcome variable (1 if Healthy aging ; 0 otherwise) has a frequency of healthy aging for around 1000 observations (37% of the sample).
Also there are 13 predictor variables, so the assumption of having 10 events per variable is widely satisfied.
But the question is the frequency of 37%.
In this logistic regression model, we can't interpret odds-ratios as relative risks due to high event rate. What other regression methods can we use to model a binary outcome?