Wit Jan M, Himes John H, van Buuren Stef, Denno Donna M, Suchdev Parminder S
Department of Pediatrics, Leiden University Medical Center, Leiden, the Netherlands.
Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota, USA.
Horm Res Paediatr. 2017;88(1):79-90. doi: 10.1159/000456007. Epub 2017 Feb 14.
BACKGROUND/AIMS: Childhood stunting is a prevalent problem in low- and middle-income countries and is associated with long-term adverse neurodevelopment and health outcomes. In this review, we define indicators of growth, discuss key challenges in their analysis and application, and offer suggestions for indicator selection in clinical research contexts.
Critical review of the literature.
Linear growth is commonly expressed as length-for-age or height-for-age z-score (HAZ) in comparison to normative growth standards. Conditional HAZ corrects for regression to the mean where growth changes relate to previous status. In longitudinal studies, growth can be expressed as ΔHAZ at 2 time points. Multilevel modeling is preferable when more measurements per individual child are available over time. Height velocity z-score reference standards are available for children under the age of 2 years. Adjusting for covariates or confounders (e.g., birth weight, gestational age, sex, parental height, maternal education, socioeconomic status) is recommended in growth analyses.
The most suitable indicator(s) for linear growth can be selected based on the number of available measurements per child and the child's age. By following a step-by-step algorithm, growth analyses can be precisely and accurately performed to allow for improved comparability within and between studies.
背景/目的：儿童发育迟缓在低收入和中等收入国家是一个普遍存在的问题，并且与长期不良神经发育及健康结果相关。在本综述中，我们定义生长指标，讨论其分析和应用中的关键挑战，并为临床研究背景下的指标选择提供建议。
对文献进行批判性综述。
与标准生长标准相比，线性生长通常用年龄别身长或年龄别身高Z评分（HAZ）来表示。条件HAZ校正了生长变化与先前状态相关时的均值回归。在纵向研究中，生长可以表示为两个时间点的ΔHAZ。当每个儿童随时间有更多测量值时，多级建模更可取。2岁以下儿童有身高增长速度Z评分参考标准。在生长分析中建议对协变量或混杂因素（如出生体重、孕周、性别、父母身高、母亲教育程度、社会经济地位）进行校正。
可以根据每个儿童可用测量值的数量和儿童年龄选择最适合的线性生长指标。通过遵循逐步算法，可以精确且准确地进行生长分析，以提高研究内部和研究之间的可比性。
