Demographics adjustment for combined counts

#1
Hello!

My unit of observation was cities within a county. Since asthma counts were too small for each city, I decided to combine counts from various cities by a binary variable (all 'yes' cities combined and 'no' cities combined). How can I then adjust for demographic variables, such as age group, in this situation?

Thanks for your responses, I appreciate it!
 

Dason

Ambassador to the humans
#2
It's not clear to me what is going on. Could you describe your study in more detail? Don't forget to mention what you measured and what your research question actually is.
 
#3
The objective is to evaluate whether monthly/annual rates of asthma have decreased or not since the implementation of several policies within a county. Policy is a binary variable and varies by year and city. Cities are assigned a ‘1’ after a policy was implemented regardless if additional policies were passed following the initial one. Covariates include: linear time, policy, time*policy. Since age and gender are associated with asthma, it’s necessary to account for them. However, since asthma counts are too sparse for smaller cities, I felt it appropriate to sum counts by policy group (1/0) and then generate rates (which is the outcome). So now I’m unsure of how to account for age/gender since city is no longer the unit of analysis but rather the policy groups. I have demographic data at the individual level (hospitalization records) and census level by city.

Any suggestions on how to account/standardize for age/gender/ethnicity (maybe)?