Kendler K S
Department of Psychiatry, Medical College of Virginia/Virginia Commonwealth University, Richmond 23298.
Compr Psychiatry. 1988 May-Jun;29(3):218-27. doi: 10.1016/0010-440x(88)90045-4.
This article presents an algebraic treatment of the impact of diagnostic hierarchies on the estimation of prevalence rates of psychiatric disorders. A method for correcting for this "hierarchy effect" is developed and illustrated. Using the terminology of Boyd et al., when the dominant disorder is common and/or the odds ratio for the dominant and the excluded disorders is high, the observed prevalence of an excluded disorder can substantially underestimate its true prevalence. This "hierarchy effect" can be particularly important in genetic-epidemiologic investigations which compare the prevalence of an excluded disorder in two populations which differ in the prevalence of the dominant disorder. The impact of certain kinds of diagnostic hierarchies can be easily understood and corrected for; with others, particularly those based on etiologic assumptions, a straight-forward interpretation is not always possible.
本文提出了一种代数方法，用于处理诊断层次结构对精神疾病患病率估计的影响。开发并举例说明了一种校正这种“层次效应”的方法。使用博伊德等人的术语，当主要疾病常见和/或主要疾病与排除疾病的比值比很高时，排除疾病的观察患病率可能会大幅低估其真实患病率。这种“层次效应”在遗传流行病学调查中可能尤为重要，这类调查比较了两种人群中排除疾病的患病率，而这两种人群中主要疾病的患病率有所不同。某些类型的诊断层次结构的影响很容易理解并得到校正；而对于其他一些层次结构，尤其是基于病因假设的那些，往往无法进行直接的解释。
