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构建标准化生长标准的LMS方法。

The LMS method for constructing normalized growth standards.

作者信息

Cole T J

机构信息

MRC Dunn Nutrition Unit, Cambridge, UK.

出版信息

Eur J Clin Nutr. 1990 Jan;44(1):45-60.

PMID:2354692
Abstract

It is now common practice to express child growth status in the form of SD scores. The LMS method provides a way of obtaining normalized growth centile standards which simplifies this assessment, and which deals quite generally with skewness which may be present in the distribution of the measurement (eg height, weight, circumferences or skinfolds). It assumes that the data can be normalized by using a power transformation, which stretches one tail of the distribution and shrinks the other, removing the skewness. The optimal power to obtain normality is calculated for each of a series of age groups and the trend summarized by a smooth (L) curve. Trends in the mean (M) and coefficient of variation (S) are similarly smoothed. The resulting L, M and S curves contain the information to draw any centile curve, and to convert measurements (even extreme values) into exact SD scores. A table giving approximate standard errors for the smoothed centiles is provided. The method, which is illustrated with US girls' weight data, should prove useful both for the construction and application of growth standards.

摘要

现在,以标准差分数的形式来表示儿童生长状况已成为常见做法。LMS方法提供了一种获得标准化生长百分位标准的途径,这简化了评估过程,并且能普遍处理测量值(如身高、体重、周长或皮褶厚度)分布中可能存在的偏态。该方法假定数据可以通过幂变换进行标准化,这种变换会拉伸分布的一端并压缩另一端,从而消除偏态。针对一系列年龄组中的每一组,计算出获得正态性的最佳幂次,并通过一条平滑的(L)曲线总结其趋势。均值(M)和变异系数(S)的趋势也以类似方式进行平滑处理。由此得到的L、M和S曲线包含了绘制任何百分位曲线以及将测量值(甚至是极端值)转换为精确标准差分数所需的信息。文中提供了一个给出平滑百分位数近似标准误差的表格。该方法以美国女孩体重数据为例进行了说明,对于生长标准的构建和应用都应具有实用性。

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