Differential Participation, a Potential Cause of Spurious Associations in Observational Cohorts in Environmental Epidemiology.

IF 4.7 2区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Epidemiology Pub Date : 2024-03-01 Epub Date: 2023-01-30 DOI:10.1097/EDE.0000000000001711
Chen Chen, Hong Chen, Jay S Kaufman, Tarik Benmarhnia
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引用次数: 0

Abstract

Differential participation in observational cohorts may lead to biased or even reversed estimates. In this article, we describe the potential for differential participation in cohorts studying the etiologic effects of long-term environmental exposures. Such cohorts are prone to differential participation because only those who survived until the start of follow-up and were healthy enough before enrollment will participate, and many environmental exposures are prevalent in the target population and connected to participation via factors such as geography or frailty. The relatively modest effect sizes of most environmental exposures also make any bias induced by differential participation particularly important to understand and account for. We discuss key points to consider for evaluating differential participation and use causal graphs to describe two example mechanisms through which differential participation can occur in health studies of long-term environmental exposures. We use a real-life example, the Canadian Community Health Survey cohort, to illustrate the non-negligible bias due to differential participation. We also demonstrate that implementing a simple washout period may reduce the bias and recover more valid results if the effect of interest is constant over time. Furthermore, we implement simulation scenarios to confirm the plausibility of the two mechanisms causing bias and the utility of the washout method. Since the existence of differential participation can be difficult to diagnose with traditional analytical approaches that calculate a summary effect estimate, we encourage researchers to systematically investigate the presence of time-varying effect estimates and potential spurious patterns (especially in initial periods in the setting of differential participation).

环境流行病学中观察性队列中的差异参与--产生虚假关联的潜在原因。
观察性队列中的差异参与可能会导致有偏差甚至相反的估计结果。在这篇文章中,我们描述了在研究长期环境暴露的病因学影响的队列中出现差异参与的可能性。此类队列很容易出现差异参与,因为只有那些存活到随访开始且在入组前足够健康的人才会参与,而许多环境暴露在目标人群中普遍存在,并通过地理或虚弱等因素与参与相关联。大多数环境暴露的影响大小相对较小,这也使得了解和考虑因不同参与而引起的偏差变得尤为重要。我们讨论了评估差异参与的要点,并使用因果图描述了在长期环境暴露的健康研究中可能出现差异参与的两种示例机制。我们用一个真实的例子--加拿大社区健康调查队列--来说明差异化参与造成的不可忽略的偏差。我们还证明,如果感兴趣的效应随时间变化而不变,那么实施简单的冲洗期可以减少偏差并恢复更有效的结果。此外,我们还实施了模拟情景,以证实造成偏差的两种机制的合理性以及冲洗方法的实用性。由于传统的分析方法难以诊断是否存在差异化参与,因此我们鼓励研究人员系统地调查是否存在时变效应估计和潜在的虚假模式(尤其是在差异化参与背景下的初始阶段)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Epidemiology
Epidemiology 医学-公共卫生、环境卫生与职业卫生
CiteScore
6.70
自引率
3.70%
发文量
177
审稿时长
6-12 weeks
期刊介绍: Epidemiology publishes original research from all fields of epidemiology. The journal also welcomes review articles and meta-analyses, novel hypotheses, descriptions and applications of new methods, and discussions of research theory or public health policy. We give special consideration to papers from developing countries.
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