I have ran a logistic regression looking at predictors of weight loss (group 1 losing weight v group 2 not losing weight). my model has one entry (all variables in at once e.g. sex (categorised as first), age, number of other disorders, diabetes score and appetite, fatigue, e.g. inflammation makers like CRP). I have a model that has significant model (e.g. better than block 0) and has "good fit" (e.g. not sign) and explains 30-70% of the variance in the outcome (hope that makes sense). However none of my variables are significant. I then removed all clinical baseline measure sex and age etc and just looked at key medical variables thought to predict weight loss in this group e.g. appetite level, diabetes score, CRP, fatigue scores. now I have two sign predictors. My question is do I have to include or control for age and sex variables as data is already nonparametric, e.g. sample sizes are not same, not normality distributed so age, sex etc are irrelevant anyway....help?