# Can you adjust an odds ratio for covariates without having subject level data on those covariates?

I'm working on a research project and am trying to adjust an odds ratio for several covariates including sex, age, high/low socioeconomic status, and high/low disease comorbidity. I have the number of subjects that fall into each covariate for each group such that I can compute individual odds ratios for each covariate. (see below for an example of the data I have). For example, I know there are 2000/8000 subjects with high/low SES in group A and 550/450 in group B. Is this type of analysis possible? If so, any tips on how to do it?

Thanks!

Group A (n) = 10,000

Group B (n) = 1,000

(1) Disease No disease

Group A 6200 3800

Group B 390 610

Odds ratio 0.39

(2) Labs No Labs

Group A 5000 5000

Group B 300 700

Odds ratio 0.43

(3) Imaging No imaging

Group A 6000 4000

Group B 300 700

Odds ratio 0.29

Covariates

(4) Female Male

Group A 6800 3200

Group B 670 330

Odds ratio 0.96

(5) Age Std dev

Group A 50.5 8

Group B 51.2 9

(6) High SES Low SES

Group A 2000 8000

Group B 550 450

Odds ratio 4.89

(7) High comorbidity Low comorbidity

Group A 6000 4000

Group B 580 420

Odds ratio 0.92