Miscommunicating risk, uncertainty, and causation: fine particulate air pollution and mortality risk as an example

A recent paper in this journal (Fann et al., 2012) estimated that "about 80,000 premature mortalities would be avoided by lowering PM(2.5) levels to 5 μg/m(3) nationwide" and that 2005 levels of PM(2.5) cause about 130,000 premature mortalities per year among people over age 29, with a 95% confidence interval of 51,000 to 200,000 premature mortalities per year.((1)) These conclusions depend entirely on misinterpreting statistical coefficients describing the association between PM(2.5) and mortality rates in selected studies and models as if they were known to be valid causal coefficients. But they are not, and both the expert opinions of EPA researchers and analysis of data suggest that a true value of zero for the PM(2.5) mortality causal coefficient is not excluded by available data. Presenting continuous confidence intervals that exclude the discrete possibility of zero misrepresents what is currently known (and not known) about the hypothesized causal relation between changes in PM(2.5) levels and changes in mortality rates, suggesting greater certainty about projected health benefits than is justified.