[Research Statistics] Chi-Squared Test?

Hi,

I've got some data that I need to do some analysis on, and I THINK I've selected the right test, but I don't want to risk being wrong.

I want to do the tests on a measure of Gestational Diabetes in conjunction with Iron and/or Vitamin C supplementation, so:

**Dependent Variable:**

Gestational Diabetes (GDM) (0 = no; 1 = yes)

**Independent Variables:**

Iron Supplementation (0 = no; 1 = yes)

Vitamin C Supplementation (0 = no; 1 = yes)

And in measuring them I would need to have 4 variables (*I think?*), those being:

**Iron Only**

Vitamin C Only

Both

Neither

So from what I understand, I should be able to do a **chi-squared test**, since they're all categorical variables? Is that correct, or did I miss something big? Furthermore, do I need to do a chi-squared test on each category (e.g. GDM Yes - Iron Only; GDM Yes - Vitamin C Only; GDM No - Iron Only; etc)

Also, I need to validate those against a few confounding variables, namely

Age (continuous)

Body Mass Index (continuous)

Parity (continuous)

To compare against those, would I need to use a t test? Would I compare each confounder to each of the 4 categories above (Iron, Vit C, Both, Neither)? Or would I need to somehow compare all of them at once to the variables, or..?

Thanks!