[R-meta] Rationale for performing a moderator test without heterogeneity

Dear all,

I am performing a meta-analysis on the effects of muscle disuse on 
muscle loss. We choose age, duration of the intervention and initial 
muscle strength as a priory moderators. The meta-analysis for muscle 
loss is as follows:
Random-Effects Model (k = 30; tau^2 estimator: DL)
   logLik  deviance       AIC       BIC      AICc
-17.9973   27.8366   39.9946   42.7970   40.4391
   tau^2 (estimated amount of total heterogeneity): 0 (SE = 0.0511)
tau (square root of estimated tau^2 value):      0
I^2 (total heterogeneity / total variability):   0.00%
H^2 (total variability / sampling variability):  1.00
Test for Heterogeneity:
Q(df = 29) = 27.8366, p-val = 0.5267
Model Results:
estimate      se     zval    pval    ci.lb    ci.ub
-0.3986  0.0803  -4.9619  <.0001  -0.5561  -0.2412  ***

My first question is if there is any rationale to further perform the 
moderator test. In fact, when I perform it for initial force the test of 
moderators is significant. How can I interpret this?

Second, I am a little bit confused on how to interpret the test for 
moderators when I perform it for each variable in separate and when all 
moderators are analysed together. For instance, when I perform the 
moderators test for muscle strength it is significant; however, when 
both duration and strength are introduced in the model while the 
moderator test is significant, only duration reached a significant 
effect.

Thank you very much,
Kind regards

Rafael A. Casuso
PhD in Health Sciences. Postdoctoral Researcher.

University of Granada.
Department of Physiology.
Email: racasuso at ugr.es