Prescott E, Andersen P K, Osler M, Lange P, Vestbo J
Copenhagen Center for Prospective Population Studies at the Institute of Preventive Medicine, Bispebjerg Hospital, University of Copenhagen, Denmark.
Epidemiology. 1999 Mar;10(2):176-80.
Because of a "healthy responder effect," secular trends in mortality based on cohort studies may be biased if based on responders only. Because responders are selected on the basis of their health at study entry, subjects just entering a study are not comparable with subjects who have been in the study for several years. The result may be an artificial increase in mortality, which impedes analyzing the effect of secular trends in risk factors on mortality. The objective of this paper is to suggest a solution by using data on nonresponders and applying a sensitivity analysis. We illustrate this solution with data on trends in smoking prevalence and all-cause mortality based on a large Danish cohort study with 19 years of complete follow-up on responders and nonresponders. Secular trends in mortality based on the whole sample vs responders only illustrated that results based on responders were biased. In a sensitivity analysis, the observed person-years of nonresponders were distributed among six categories of persons with respect to smoking behavior (never-smokers; ex-smokers; noninhaling current smokers; and current smokers of 1-14, 15-24, and > or =25 gm tobacco per day) according to preset assumptions regarding smoking habits. The observed deaths among nonresponders were then distributed on the six smoking categories according to relative risks derived from a Poisson regression analysis among responders. This procedure allowed us to study the effect of adjustment for smoking on the unbiased secular trend in mortality. By applying different assumptions regarding smoking habits among nonresponders, we explored the effect of the assumptions on the adjusted secular trend in mortality. We conclude that secular trends in mortality based on responders in a cohort study are likely to be biased. If complete follow-up on nonresponders is available, this method could prove useful in other cohort studies.
由于“健康应答者效应”，基于队列研究的死亡率长期趋势若仅基于应答者可能存在偏差。因为应答者是根据研究开始时的健康状况挑选出来的，刚进入研究的受试者与已参与研究数年的受试者不可比。结果可能是死亡率的人为上升，这妨碍了分析风险因素长期趋势对死亡率的影响。本文的目的是通过使用无应答者的数据并进行敏感性分析来提出一种解决方案。我们基于一项对应答者和无应答者进行了19年完整随访的大型丹麦队列研究，用吸烟流行趋势和全因死亡率的数据来说明这一解决方案。基于整个样本与仅基于应答者的死亡率长期趋势表明，基于应答者的结果存在偏差。在一项敏感性分析中，根据关于吸烟习惯的预设假设，将观察到的无应答者人年数分配到六类人群（从不吸烟者；已戒烟者；不吸入的当前吸烟者；以及每天吸烟1 - 14克、15 - 24克和≥25克烟草的当前吸烟者）中。然后，根据应答者中泊松回归分析得出的相对风险，将观察到的无应答者死亡数分配到这六个吸烟类别中。这一程序使我们能够研究吸烟调整对死亡率无偏长期趋势的影响。通过对无应答者的吸烟习惯应用不同假设，我们探究了这些假设对调整后的死亡率长期趋势的影响。我们得出结论，队列研究中基于应答者的死亡率长期趋势可能存在偏差。如果能获得对无应答者的完整随访数据，这种方法在其他队列研究中可能会有用。
