I am interested in the relationship between religiosity and religious distrust ( would you dislike having as neighbours people of different religions.)

One of my main goals is to make the role of each individual religion insignificant; according to my argument monotheism leads to distrust, regardless of the particular religion. However, religions explain about 53% of my variation in religious distrust according to the R-squared. 
I wanted to include variables that would ' take away'  from this influence of religion in terms of explanatory variable. For example, economic inequality in most Muslim countries might be a reason for differences in distrust, or the number of times people pray, which is less in Protestant countries. So I added as independent variables: Economic inequality, urbanization, separation church/state, number of times people pray, and education. When I include these in a model *without religion* I get an R-squared of about 37%. 

When I include all these independent variables + religion, religion becomes significant again, I think because religion incorporates much more explanation than either single one of my other independent variables. My R-squared in this model is, again, 53. 
My question is, is there any way to support the claim that although religion might matter, my independent variables ' take away'  at least some of its explanatory value? 

So:
religion alone explain 53%; 
my independent variables explain 37% alone; 
together they explain 53% again

Could I say that of the 53% religion used to explain, 37% / 53% is now explained by my other independent variables? So in a sense, I took away about 2/3 of the explanatory value of religion by introducing other variables? Or is this not statistically valid, because they might for example explain different parts of the variation in my dependent variable?