The University of Queensland, School of Population Health, Herston Road, Herston Qld 4006, Australia.
Br J Psychiatry. 2009 Dec;195(6):516-9. doi: 10.1192/bjp.bp.109.066191.
For some phenomena the mean of population distributions predicts the proportion of people exceeding a threshold value.
To investigate whether in depression, too, the population mean predicts the number of individuals at the extreme end of the distribution.
We used data from the European Outcome in Depression International Network (ODIN) study from populations in Finland, Norway and the UK to create models that predicted the prevalence of depression based on the mean Beck Depression Inventory (BDI) score. The models were tested on data from Ireland and Spain.
Mean BDI score correlated well with the prevalence of depression determined by clinical interviews. A model based on the beta distribution best fitted the BDI distribution. Both models predicted the depression prevalence in Ireland and Spain fairly well.
The mean of a continuous population distribution of mood predicts the prevalence of depression. Characteristics of both individuals and populations determine depression rates.
对于某些现象，人口分布的平均值可以预测超过阈值的人数比例。
探讨在抑郁症中，人口平均值是否也可以预测分布末端的个体数量。
我们使用了来自芬兰、挪威和英国的欧洲抑郁症结局国际网络（ODIN）研究的数据，创建了基于贝克抑郁量表（BDI）平均得分预测抑郁症患病率的模型。我们在爱尔兰和西班牙的数据上测试了这些模型。
平均 BDI 得分与临床访谈确定的抑郁症患病率相关性良好。基于 beta 分布的模型最适合 BDI 分布。这两个模型都很好地预测了爱尔兰和西班牙的抑郁症患病率。
情绪连续人口分布的平均值可以预测抑郁症的患病率。个体和人群的特征决定了抑郁症的发病率。
