# In a matched case-control study, what do I use for hypothesis testing in the descriptive statistics or the “univariate” associations?

I am doing a case-control study with 80 disease cases matched 1:3 to non-diseased controls and examining whether they had a binary exposure prior to developing the disease. I am using multivariable conditional logistic regression for the main analysis. My question is, for the "descriptive" or "univariate" table where we try to investigate simple associations of each (non-matched) variable with the outcome, do I just use something like a chi-square test and ignore the matching, or do I use main effects conditional logistic regression (or something else)? Any help would be greatly appreciated.

To test whether prevalence of exposure in cases differed from prevalence of exposure in (3x) controls, I might recommend reading Miettinen's generalization of McNemar's test (McNemar's test is a $\chi^{2}$ test that accounts for the individual matching of the case data with the control data):