4.3 Article

The adiposity of children is associated with their lifestyle behaviours: a cluster analysis of school-aged children from 12 nations

期刊

PEDIATRIC OBESITY
卷 13, 期 2, 页码 111-119

出版社

WILEY
DOI: 10.1111/ijpo.12196

关键词

Lifestyle behaviours; diet; obesity; compositional analysis

向作者/读者索取更多资源

Background: The relationship between children's adiposity and lifestyle behaviour patterns is an area of growing interest. Objectives: The objectives of this study are to identify clusters of children based on lifestyle behaviours and compare children's adiposity among clusters. Methods: Cross-sectional data from the International Study of Childhood Obesity, Lifestyle and the Environment were used. Participants: the participants were children (9-11years) from 12 nations (n=5710). Measures: 24-h accelerometry and self-reported diet and screen time were clustering input variables. Objectively measured adiposity indicators were waist-to-height ratio, percent body fat and body mass index z-scores. Analysis: sex-stratified analyses were performed on the global sample and repeated on a site-wise basis. Cluster analysis (using isometric log ratios for compositional data) was used to identify common lifestyle behaviour patterns. Site representation and adiposity were compared across clusters using linear models. Results: Four clusters emerged: (1) Junk Food Screenies, (2) Actives, (3) Sitters and (4) All-Rounders. Countries were represented differently among clusters. Chinese children were over-represented in Sitters and Colombian children in Actives. Adiposity varied across clusters, being highest in Sitters and lowest in Actives. Conclusions: Children from different sites clustered into groups of similar lifestyle behaviours. Cluster membership was linked with differing adiposity. Findings support the implementation of activity interventions in all countries, targeting both physical activity and sedentary time.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.3
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据