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The document discusses the potential biases introduced by multi-pollutant adjustments in air pollution epidemiology, particularly through collider bias, which can distort causal associations between pollutants and health outcomes. It presents empirical evidence from a Canadian cohort study and a simulation study, highlighting the need for caution in interpreting multi-pollutant analyses. The authors propose strategies to mitigate these biases, emphasizing the importance of accurate causal inference in air q
- Author
- Jeadran Malagon
- Language
- EN