How would you study air quality and health cross-sectionally, and what limits a causal interpretation?
Instruction: Define exposure and outcome timing, select confounders using a causal model, and distinguish an adjusted association from an identified causal effect. Propose follow-up data or a design that addresses the remaining limitations.
Updated
Official answer available
Read the opening below, then unlock the full answer and practical guidance.
A cross-sectional study can estimate an air-quality/health association, but a single snapshot does not by itself identify a causal effect. First define the population, pollutant, exposure window, and outcome. For example, relate a specified prior exposure estimate to current respiratory-symptom prevalence; do not call prevalence an incidence rate.
Use a causal diagram to select pre-exposure confounders, potentially including age,...