Sheppard Zoë A, Norris Shane A, Pettifor John M, Cameron Noël, Griffiths Paula L
Department of Human Sciences, Loughborough University, Loughborough, Leicestershire, United Kingdom.
Am J Hum Biol. 2009 Jan-Feb;21(1):48-54. doi: 10.1002/ajhb.20814.
The objectives of this article were to compare the variance explained in anthropometric outcomes when using individual measures of socioeconomic status (SES) versus different approaches to create SES indices within the urban African context, and to examine the influence of SES measured during infancy on child anthropometric outcomes at 7/8 years. Data from the 1990 Birth-to-Twenty cohort study set in Johannesburg-Soweto, South Africa, were used (n = 888). Linear regression models were used to investigate the association between SES (individual and index measures) during infancy and anthropometric measures at age 7/8 years, controlling for sex, age, and population group. Both individual and index measures of SES explained similar proportions of the variance for each anthropometric outcome. SES measured during infancy influenced weight more than height at age 7/8 years in Johannesburg-Soweto. Positive associations were found between SES and the anthropometric measures--ownership of a car, telephone, and having an inside flush toilet were the most significant SES variables. The similarities observed in the variance explained relating to the anthropometric outcomes suggest that researchers who want to adjust for SES in analyses could use an SES index to make statistical models more parsimonious. However, using such indices loses information relating to the specific socioeconomic factors that are important for explaining child anthropometrics. If the purpose of the research is to make policy recommendations for the improvement of child growth, individual SES variables would provide more specific information to target interventions.
本文的目的是比较在城市非洲背景下,使用社会经济地位(SES)的个体测量指标与创建SES指数的不同方法时,人体测量结果中所解释的方差,并研究婴儿期测量的SES对7/8岁儿童人体测量结果的影响。使用了来自南非约翰内斯堡 - 索韦托的1990年从出生到20岁队列研究的数据(n = 888)。线性回归模型用于研究婴儿期的SES(个体和指数测量指标)与7/8岁时的人体测量指标之间的关联,并控制性别、年龄和人口群体。SES的个体和指数测量指标对每种人体测量结果所解释的方差比例相似。在约翰内斯堡 - 索韦托,婴儿期测量的SES对7/8岁儿童体重的影响大于身高。SES与人体测量指标之间存在正相关关系——拥有汽车、电话以及有室内冲水马桶是最显著的SES变量。在人体测量结果所解释的方差方面观察到的相似性表明,希望在分析中对SES进行调整的研究人员可以使用SES指数使统计模型更简洁。然而,使用这样的指数会丢失与解释儿童人体测量学重要的特定社会经济因素相关的信息。如果研究目的是为改善儿童生长提出政策建议,个体SES变量将提供更具体的信息以确定干预目标。