Biological Anthropology and Comparative Anatomy Research Unit, School of Biomedicine, The University of Adelaide, Adelaide, Australia.
Institute of Evolutionary Medicine, University of Zurich, Zurich, Switzerland.
PLoS One. 2022 Jun 7;17(6):e0269420. doi: 10.1371/journal.pone.0269420. eCollection 2022.
Child growth in populations is commonly characterised by cross-sectional surveys. These require data collection from large samples of individuals across age ranges spanning 1-20 years. Such surveys are expensive and impossible in restrictive situations, such as, e.g. the COVID pandemic or limited size of isolated communities. A method allowing description of child growth based on small samples is needed.
Small samples of data (N~50) for boys and girls 6-20 years old from different socio-economic situations in Africa and Europe were randomly extracted from surveys of thousands of children. Data included arm circumference, hip width, grip strength, height and weight. Polynomial regressions of these measurements on age were explored.
Polynomial curves based on small samples correlated well (r = 0.97 to 1.00) with results of surveys of thousands of children from same communities and correctly reflected sexual dimorphism and socio-economic differences.
Fitting of curvilinear regressions to small data samples allows expeditious assessment of child growth in a number of characteristics when situations change rapidly, resources are limited and access to children is restricted.
人群中的儿童生长通常通过横断面调查来描述。这些调查需要在跨越 1-20 岁年龄范围的大量个体中收集数据。这种调查费用高昂，在限制条件下是不可能进行的，例如 COVID 大流行或隔离社区规模有限。因此，需要一种基于小样本描述儿童生长的方法。
从数千名儿童的调查中随机抽取了来自不同社会经济环境的非洲和欧洲 6-20 岁男孩和女孩的小样本数据（N~50）。数据包括臂围、臀宽、握力、身高和体重。探索了这些测量值随年龄的多项式回归。
基于小样本的多项式曲线与来自同一社区数千名儿童的调查结果高度相关（r = 0.97 至 1.00），正确反映了性别差异和社会经济差异。
当情况迅速变化、资源有限且儿童难以接触时，拟合小样本的曲线回归可以快速评估儿童在多个特征方面的生长情况。
