From the aDepartments of Environmental Health and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA; and bDepartment of Environmental Health, Boston University School of Public Health, Boston, MA.
Epidemiology. 2017 Sep;28(5):635-643. doi: 10.1097/EDE.0000000000000686.
The technological ability to make personal measurements of toxicant exposures is growing rapidly. While this can decrease measurement error and therefore help reduce attenuation of effect estimates, we argue that as measures of exposure or dose become more personal, threats to validity of study findings can increase in ways that more proxy measures may avoid. We use directed acyclic graphs (DAGs) to describe conditions where confounding is introduced by use of more personal measures of exposure and avoided via more proxy measures of personal exposure or target tissue dose. As exposure or dose estimates are more removed from the individual, they become less susceptible to biases from confounding by personal factors that can often be hard to control, such as personal behaviors. Similarly, more proxy exposure estimates are less susceptible to reverse causation. We provide examples from the literature where adjustment for personal factors in analyses that use more proxy exposure estimates have little effect on study results. In conclusion, increased personalized exposure assessment has important advantages for measurement accuracy, but it can increase the possibility of biases from personal factors and reverse causation compared with more proxy exposure estimates. Understanding the relation between more and less proxy exposures, and variables that could introduce confounding are critical components to study design.
个人暴露物测量的技术能力正在迅速发展。虽然这可以减少测量误差，从而有助于减少效应估计的衰减，但我们认为，随着暴露或剂量的衡量标准变得更加个体化，研究结果有效性的威胁可能会以更具代表性的衡量标准所避免的方式增加。我们使用有向无环图（DAG）来描述使用更个体化的暴露物衡量标准引入混杂，并通过更具代表性的个人暴露物或靶组织剂量衡量标准来避免混杂的情况。随着暴露或剂量的衡量标准与个体的距离越来越远，它们就越不容易受到个人因素混杂的影响，这些个人因素往往难以控制，例如个人行为。同样，更具代表性的暴露物衡量标准也不太容易受到反向因果关系的影响。我们提供了文献中的例子，其中在使用更具代表性的暴露物衡量标准的分析中，对个人因素进行调整对研究结果的影响很小。总之，与更具代表性的暴露物衡量标准相比，增加个体化暴露评估对测量准确性有重要优势，但与更具代表性的暴露物衡量标准相比，它可能会增加个人因素和反向因果关系引起的偏倚的可能性。了解更多和更少的代表性暴露物之间的关系，以及可能引入混杂的变量，是研究设计的关键组成部分。
