When comparing studies with different exposure assessment tools, different distributions or characteristics of exposure (e.g., different sizes or chemical constituents of particulate air pollution across regions), or different confounders (e.g., co-pollutants, ethnic distributions with differing genetic background risk), the potential for true heterogeneity is magnified. If explanations can be found for such heterogeneity5, there is an opportunity for insights about the complexity of the disease, but spurious inconsistency due to methodological or data quality differences will just add confusion.
