Ecologic studies use data aggregated over groups rather than data on individuals. Such studies are popular because they use existing databases and can offer large exposure variation if the data arise from broad geographical areas. Unfortunately, the aggregation of data that define ecologic studies results in an information loss that can lead to ecologic bias. Specifically, ecologic bias arises from the inability of ecologic data to characterize within-area variability in exposures and confounders. We describe in detail particular forms of ecologic bias so that their potential impact on any particular study may be assessed. The only way to overcome such bias, while avoiding uncheckable assumptions concerning the missing information, is to supplement the ecologic with individual-level information, and we outline a number of proposals that may achieve this aim.

中文翻译：

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重新研究生态学。

生态研究使用的是按组汇总的数据，而不是有关个人的数据。此类研究之所以受欢迎是因为它们使用现有的数据库，并且如果数据来自广泛的地理区域，则可以提供较大的暴露差异。不幸的是，定义生态研究的数据汇总会导致信息丢失，从而导致生态偏见。具体而言，生态偏差是由于无法通过生态数据来描述暴露和混杂因素的区域内变化而造成的。我们详细描述了生态偏见的特定形式，以便可以评估其对任何特定研究的潜在影响。克服这种偏见的唯一方法是，避免对丢失的信息做出无可辩驳的假设，同时在生态学方面补充个人信息，