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探索小学儿童的分类体重指数轨迹

Exploring Categorical Body Mass Index Trajectories in Elementary School Children.

作者信息

Moreno-Black Geraldine, Boles Shawn, Johnson-Shelton Deb, Evers Cody

机构信息

Oregon Research Institute, 1776 Millrace Drive, Eugene, OR 97403.

Portland State University, PO Box 751, Portland, OR 97207.

出版信息

J Sch Health. 2016 Jul;86(7):495-506. doi: 10.1111/josh.12402.

Abstract

BACKGROUND

Studies of body mass index (BMI) change have focused on understanding growth trajectories from childhood to adolescence and adolescence to adulthood, but few have explored BMI trajectories solely in elementary (grades K-5) school children. This report complements these studies by exploring changes in obesity status using analytic methods developed to investigate categorical changes in life-course events.

METHODS

Sequences of a 4-state BMI variable (underweight, normal, overweight, and obese) were calculated using height and weight data collected annually (2008-2013) from 414 kindergarten and first-grade students participating in the Community and Schools Together (CAST) project. These sequences were explored using the TraMineR software package to investigate the distribution of sequences and states, calculate transition rates among states, and examine clustering of sequences.

RESULTS

Aggregated cluster solutions were identified consisting of either 4 clusters (normal, stepped, mixed, and obese) or 3 clusters (aggregation of obese cluster cases into stepped cluster) with membership in the former predicted by ethnicity and socioeconomic status (SES) and the latter by SES alone. Transition rate patterns among states varied markedly by cluster and state.

CONCLUSION

The finding of early emergence of stable obesity states, especially in Hispanic children confirms the need for early childhood interventions to influence BMI.

摘要

背景

对体重指数(BMI)变化的研究主要集中在理解从儿童期到青春期以及从青春期到成年期的生长轨迹,但很少有研究仅探讨小学(幼儿园至五年级)儿童的BMI轨迹。本报告通过使用为研究生命历程事件中的分类变化而开发的分析方法来探索肥胖状况的变化,对这些研究进行了补充。

方法

利用从参与“社区与学校携手共进”(CAST)项目的414名幼儿园和一年级学生(2008 - 2013年)每年收集的身高和体重数据,计算出一个4状态BMI变量(体重过轻、正常、超重和肥胖)的序列。使用TraMineR软件包对这些序列进行探索,以研究序列和状态的分布、计算状态之间的转换率,并检验序列的聚类情况。

结果

确定了聚合聚类解决方案,包括4个聚类(正常、逐步变化、混合和肥胖)或3个聚类(将肥胖聚类案例聚合到逐步变化聚类中),前者的聚类成员由种族和社会经济地位(SES)预测,后者仅由SES预测。状态之间的转换率模式因聚类和状态而有显著差异。

结论

稳定肥胖状态早期出现的发现,尤其是在西班牙裔儿童中,证实了需要进行幼儿期干预以影响BMI。

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