School of Public Health, University of Alberta, Edmonton, Alberta T6G 2L9, Canada.
BMC Med Res Methodol. 2010 Jun 23;10:59. doi: 10.1186/1471-2288-10-59.
Consumers of epidemiology may prefer to have one measure of risk arising from analysis of a 2-by-2 table. However, reporting a single measure of association, such as one odds ratio (OR) and 95% confidence interval, from a continuous exposure variable that was dichotomized withholds much potentially useful information. Results of this type of analysis are often reported for one such dichotomization, as if no other cutoffs were investigated or even possible.
This analysis demonstrates the effect of using different theory and data driven cutoffs on the relationship between body mass index and high cholesterol using National Health and Nutrition Examination Survey data. The recommended analytic approach, presentation of a graph of ORs for a range of cutoffs, is the focus of most of the results and discussion.
These cutoff variations resulted in ORs between 1.1 and 1.9. This allows investigators to select a result that either strongly supports or provides negligible support for an association; a choice that is invisible to readers. The OR curve presents readers with more information about the exposure disease relationship than a single OR and 95% confidence interval.
As well as offering results for additional cutoffs that may be of interest to readers, the OR curve provides an indication of whether the study focuses on a reasonable representation of the data or outlier results. It offers more information about trends in the association as the cutoff changes and the implications of random fluctuations than a single OR and 95% confidence interval.
流行病学的使用者可能更希望从 2×2 表的分析中得到一个风险度量。然而，从一个连续的暴露变量中报告一个单一的关联度量，如单一的比值比（OR）和 95%置信区间，而将潜在的有用信息隐瞒起来。这种类型的分析通常会报告一个这样的二分法的结果，就好像没有调查或甚至不可能调查其他的截止值一样。
本分析使用美国国家健康和营养调查（NHANES）的数据，演示了使用不同理论和数据驱动的截止值对体重指数与高胆固醇之间关系的影响。推荐的分析方法是展示一系列截止值的 OR 图，这是大部分结果和讨论的重点。
这些截止值的变化导致了 1.1 到 1.9 之间的 OR。这使得研究人员可以选择一个结果，要么强烈支持，要么提供对关联的微不足道的支持；这种选择对读者来说是不可见的。OR 曲线为读者提供了比单一的 OR 和 95%置信区间更多的关于暴露与疾病关系的信息。
OR 曲线不仅为读者提供了可能感兴趣的额外截止值的结果，还提供了一个指示，表明研究是否关注数据的合理表示或异常值结果。它提供了关于关联随着截止值变化的趋势的更多信息，以及随机波动的影响，而不仅仅是单一的 OR 和 95%置信区间。
