ArticleChildren (Basel, Switzerland)2021
Analysis of Children's Physical Characteristics Based on Clustering Analysis.
Article in Children (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Developing the optimal gross movement interventions to improve the physical fitness of 3-10 year-old children: a systematic review and meta-analysis.Frontiers in psychology · 2024Pooled it
- Multiscale Impact of Environmental and Socio-Economic Factors on Low Physical Fitness among Chinese Adolescents and Regionalized Coping Strategies.International journal of environmental research and public health · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study assessed the physical development, physical fitness (muscular endurance, muscular strength, flexibility, agility, power, balance), and basal metabolic rate (BMR) in a total of 4410 children aged six (73-84 months) residing in Korea. Their physical fitness was visually classified according to the physical fitness factor and-considering that children showed great variations in the physical fitness criteria depending on their physique and body composition-the study aimed to assess characteristics such as physique and BMR, the precursor for fat-free mass, based on the physical health clusters selected through a multivariate approach. As a result, the physical health clusters could be subdivided into four clusters: balance (1), muscular strength (2), low agility (3), and low physical fitness (3) cluster. Cluster 1 showed a high ratio of slim and slightly slim children, while cluster 2 had a high proportion of children that were obese, tall, or heavy, and had the highest BMR. We consider such results as important primary data for constituting physical fitness management programs customized to each cluster. It seems that it is necessary to have a multidirectional approach toward physical fitness evaluation and analysis methodologies that involve various physical fitness factors of children.
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Registered trials
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