Interpreting a meta-regression table with odds ratios

I need a little help with my meta-regression interpretation. The effect sizes are based on odds ratios.

I have used rma in the metafor package: reg <- rma(yi = es, sei = se, data = df, method = "ML", mods = ~ Group) which produced this table:

             b        see    zval    p     ci.lb    ci.ub
Intercept   -0.44   0.225   -1.955  0.051   -0.882  0.001
(ref)       --        --     --     --     --      --
A        -0.525   0.173   -3.037  0.002   -0.863  -0.186  **
B        -0.353   0.195   -1.808  0.071   -0.736  0.03



I'm wondering how to interpret this...

Question 1 = Does this mean that compared to the reference, the OR for group A is 0.55 lower than the reference group, and the OR for group B is 0.35 lower than the reference group?

Question 2 = So, Group A and Group B are interventions for reducing disease incidence... Can I, therefore, say that compared to the reference Group, group A was the most effective intervention compared to the reference group. And group A is 17.2% more effective than group B (difference between the two values)

I hope that makes sense; many thanks in advance ~R

I assume es are log odds ratios, since using raw odds ratios as input wouldn't really make sense. So the results are also given in terms of log odds ratios and differences thereof. So, based on the output, studies from group A have a log odds ratio that is on average $$0.53$$ points lower than the average log odds ratio of studies from the reference group (which is estimated to be $$-0.44$$). One can exponentiate this value (i.e., $$\exp(-0.525) = 0.59$$) which then gives you the ratio of the two (average) odds ratios. So the odds ratio of group B is on average $$41\%$$ lower (i.e., $$1-0.59=0.41$$) than the average odds ratio of the reference group.