Relative Impact of Predictors with a Binary Logistic Regress

[Crystal]

Hi,

I'm trying to find a means to interpret the odds ratios resulting from a binary logistic regression. I have a binary response variable and (5) binary predictor variables.

I know how to interpret the individual odds ratios -- but is there a way to say what impact a unit increase in (1) of the (5) predictor variables has vs. what the impact is there is a unit increase in all (5) predictor variables?

Is it additive?

Also - is there a way to use the odds to speaking to a ranking of the predictor variables...if odds ratio for 1st predictor variable is 2.5 and odds ratio for 2nd predictor variable is 7.5, does this mean that changes in the response variable is 75% due to the 2nd predictor variable?

Thanks for any clarification / explanation.