I have counts of people with a condition, by age (5-year groups), sex, and area (100-200 areas).
For each area, I have:
- estimated population by age (5-year groups) and sex,
- estimated population percent living in city, small town or rural (sum to 100%),
- estimated population in high, middle and low socioeconomic status (sum to 100%), and
- estimated population proportion treated (via food or water supply fortification).
I know nothing about individual-level correlation between rurality and socioeconomic status (or even if it's the same across areas). I expect proportion treated is near 100% in cities, lower in small towns, much lower in rural areas.
Researcher wants adjusted rate (or odds) ratios for having the condition (and p-values) for rural vs cities, low vs high SES, untreated vs treated, young vs older.
Can I produce valid estimates?
If so, how should I model it?