Chi square vs Mcneamar's test

Hello I have a cohort study where a cohort of subjects with a specific characteristic has been matched to a control group according to age (+/ 3 years) and sex. Before running the main analysis I am analyzing differences at baseline about whether the two groups smoke and drink alcohol (boh variables binary 0/1).
Specifically I would want to check whether there are differences of sex smoking status and drinking status between matches and controls. Shall I use the Chi square or the Mcneamar's test in this case?
I would go for Chi square for sex and Mcneamar's for smoking and alcohol consumption. What do you think?
And also, I am quite familiar with the interpretation of the Chi square, not as much for the McNeamar's test. If I find a significant result for the alcohol consumption what does it mean?
Many thanks in advance


Omega Contributor
Superficially seems about right. And you would be hoping the Chi sq has a high pvalue to validate the process.

You amight aso think about conditional logistic regression, since you may have more options with that procedure.
Yes, the p value for sex is quite high (as the two populations were matched according to gender too). It is just that using the Mcneamar's for sex doesn't sound quite right to me even if I read that is an appropriate test for testing the difference of distribution of a variable in matched groups
I have another question about the topic, is the McNeamar still the right approach to use when you have matched case-control population with a ratio 1:2 and you want to test whether there is a different frequency of the binary variable (i.e. smoking status categorized as "yes" "no") between cases and controls ?
In this case the paired data would appear twice as matched twice to different controls, therefore I was wondering if this is still the right approach to use to test such things.
Many thanks in advance