How do I find Odds Ratio for X2 for a model with interactions?

fitted model :

p = 1/ (1+exp {-0.377 + 0.0939*x1 - 0.464*X2 + 0.0308*X3 + 0.586*X1*X2+ 0.118*X2*X3 + 0.49*X1*X3 + 0.37*X1*X2*X3)

where beta0,1,2,3,4,5,6,7 are as follows respectively:

-0.377

0.0939

-0.464

0.0308

0.586

0.118

0.49

0.37

I understand that Odds Ratio |x2=1 / Odds Ratio |x2=0

and that the final result is :

= exp {beta2 + beta4*X1 + beta5*X3 +beta7*X1*X3}

for a model without interactions, i can just do exp {Beta2}

but for a model WITH interactions, how do i decide on what value to fix so that odds ratio for X2 can be compared ??