I ran a GLM (poisson) analysis and have a list of my coefficients with their SEs. I need help interpreting the betas because the predictor variable data were log transformed prior to analysis.

Here is the example:

Y = dependent variable

A = independent variable

B = natural log of (A+1)

The regression equation is:

Y ~ constant + B

So, if variable B had a beta estimate of -0.19 +/- 0.02, then how do I interpret this in terms of A's effect on Y? ie, the effect of untransformed data on Y?

Do I simply back-transform the beta estimate and SE? How do I back-transform the SE's?