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首页> 外文期刊>Preventive Medicine: An International Journal Devoted to Practice and Theory >The gap between evidence discovery and actual causal relationships.
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The gap between evidence discovery and actual causal relationships.

机译：证据发现与实际因果关系之间的差距。

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摘要

The concept of causation in epidemiology can be illuminated by situating the discussion within a more general concept of causation in biology: "a causal relationship is one that has a mechanism that by its operation makes a difference". Mechanism and difference-making are complementary, and discovery can proceed from either direction; each type of evidence can be qualitative or quantitative. An explanation becomes fully convincing only when supported by both. In biology, causation is typically stochastic and/or multiple. Multiple causation can be analysed statistically/epidemiologically, even though it is not truly (ontologically) stochastic. This requires some degree of regularity in the outcome variable, plus sufficient variation in the exposure(s). The analysis then demonstrates co-variations between exposure(s) and outcome that regularly occur. Rose's important distinction of "causes of incidence" and "causes of cases" should be reconceptualised in terms of epidemiological visibility, raising the possibility of epidemiological "dark matter".
机译：流行病学中的因果关系概念可以通过将讨论置于生物学的因果关系的更一般概念中来阐明：“因果关系是一种因其运作而有所作为的机制”。机制与差异化是相辅相成的，发现可以从任一方向进行;每种类型的证据都可以定性或定量。只有得到双方的支持，解释才能完全令人信服。在生物学中，因果关系通常是随机的和/或多重的。即使不是真正（本体论）随机的，也可以通过统计/流行病学分析多重因果关系。这就要求结果变量具有一定程度的规律性，并要求暴露量有足够的变化。然后，分析表明暴露与定期发生的结局之间存在协变量。罗斯在“发病原因”和“病例原因”之间的重要区别应该从流行病学可见度的角度重新概念化，从而增加了流行病学“暗物质”的可能性。

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