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Moreira ME, Soares FV, Meio MD, Abranches AD, Gomes Junior SC. Energy expenditure in very low birth weight newborns: a comparison between small‐ and appropriate‐for‐gestational‐age. Acta Paediatr 2010; 99: 651–653: Author’s reply

sure and outcome is called ‘causation’ or ‘association’ ... Similarly, it simply does not matter whether you say that ‘smoking is associated with lung cancer’ or ‘smoking predicts lung cancer’. What does matter is that identifying and then removing or reducing predictors from populations can improve the human condition’ (1). Let me offer some clarifications. First, I did not suggest that it does not matter whether some relationship between exposure and outcome represents correlation or causation. What I wrote is that it does not matter how we talk about purported relationships between exposures and outcomes. Using either the language of association or the language of prediction or the language of causation can help identify potentially useful targets for intervention. Second, Gagliardi writes that we already know that the relationship between smoking and cancer is causal and, therefore, it does not matter whether we call the relationship an association or causation. However, I would insist that even before causal knowledge about a certain exposure–outcome relationship appears to be certain, arguments about which language to choose when talking about it should be considered less important than discussions about biologically plausible preventive action. Neither observational research nor experimental studies (laboratory-based or clinical trial) alone can provide causal knowledge that can be extrapolated to the complex system called ‘human disease aetiology’. Indeed, the multimodal, interventionist, probabilistic programme for causal inference we recently suggested (3) holds that our chances to identify targets for interventions that are likely to improve human health can be maximized if data from multiple different types of research are considered in concert. Removing purported causes from populations is part of this interdisciplinary strategy. The beauty of this multimodal causation research is that it brings us closer to both, causative aetiologic knowledge and improved health.