Department of Epidemiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, 2-5-1 Shikata-cho, Kita-ku, Okayama, 700-8558, Japan.
Okayama University of Science, 1-1 Ridai-cho, Kita-ku, Okayama, 700-0005, Japan.
Eur J Epidemiol. 2021 Sep;36(9):899-908. doi: 10.1007/s10654-021-00798-6. Epub 2021 Sep 26.
The assessment of causality is fundamental to epidemiology and biomedical sciences. One well-known approach to distinguishing causal from noncausal explanations is the nine Bradford Hill viewpoints. A recent article in this journal revisited the viewpoints to incorporate developments in causal thinking, suggesting that the sufficient cause model is useful in elucidating the theoretical underpinning of the first of the nine viewpoints-strength of association. In this article, we discuss how to discern the causal mechanisms of interest in the sufficient cause model, which pays closer attention to the relationship between the sufficient cause model and the Bradford Hill viewpoints. To this end, we explicate the link between the sufficient cause model and the potential-outcome model, both of which have become the cornerstone of causal thinking in epidemiology and biomedicine. A clearer understanding of the link between the two models provides significant implications for interpretation of the observed risks in the subpopulations defined by exposure and confounder. We also show that the concept of potential completion times of sufficient causes is useful to fully discerning completed sufficient causes, which leads us to pay closer attention to the fourth of the nine Bradford Hill viewpoints-temporality. Decades after its introduction, the sufficient cause model may be vaguely understood and thus implicitly used under unreasonably strict assumptions. To strengthen our assessment in the face of multifactorial causality, it is significant to carefully scrutinize the observed associations in a complementary manner, using the sufficient cause model as well as its relevant causal models.
因果关系的评估是流行病学和生物医学科学的基础。区分因果关系和非因果关系解释的一种著名方法是布拉德福·希尔观点。本期刊上的一篇最近的文章重新审视了这些观点，以纳入因果思维的发展，表明充分原因模型在阐明九个观点中的第一个——关联强度的理论基础方面是有用的。在本文中，我们讨论了如何在充分原因模型中辨别出感兴趣的因果机制，该模型更关注充分原因模型和布拉德福·希尔观点之间的关系。为此，我们阐述了充分原因模型和潜在结果模型之间的联系，这两个模型都已成为流行病学和生物医学中因果思维的基石。更清楚地理解这两个模型之间的联系，对于解释暴露和混杂因素定义的亚人群中观察到的风险具有重要意义。我们还表明，充分原因的潜在完成时间的概念有助于充分辨别已完成的充分原因，这使我们更加关注九个观点中的第四个——时间性。在引入充分原因模型几十年后，它可能被模糊地理解，并因此在不合理的严格假设下被隐含使用。为了在面对多因素因果关系时加强我们的评估，仔细地以互补的方式审视观察到的关联是很重要的，既要使用充分原因模型，也要使用其相关的因果模型。
