Gas‑stove math can mislead regulators

When researchers mix incompatible effect measures (e.g., prevalence ratios with odds ratios) and apply them to population attributable formulas, they can produce large, misleading estimates that travel fast into regulatory debates. That statistical slippage can turn modest or uncertain epidemiology into a headline‑ready percent of disease supposedly 'caused' by a consumer product, driving premature policy action. — Regulators, journalists, and advocates need to scrutinize the specific estimands and transformations behind headline percentages because methodological errors can create policy panics with large costs.