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5至6岁社会经济条件不利儿童的身体活动量和运动质量与执行功能的关联

Associations of physical activity dose and movement quality with executive functions in socioeconomically disadvantaged children aged 5-6 years.

作者信息

O'Callaghan Laura, Foweather Lawrence, Crotti Matteo, Oppici Luca, Pesce Caterina, Boddy Lynne, Fitton Davies Katie, Rudd James

机构信息

Faculty of Health and Life Sciences, Oxford Brookes University, Oxford, UK.

School of Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, UK.

出版信息

Psychol Sport Exerc. 2024 Jan;70:102546. doi: 10.1016/j.psychsport.2023.102546. Epub 2023 Oct 17.

Abstract

BACKGROUND

Growing up in areas of high deprivation can negatively impact children's movement behaviours and cognitive development. Enhancing the quantity and quality of children's movement experiences is believed to enhance cognitive development. This study investigated the association of three different modes of movement assessment, movement proficiency and divergent movement ability (collectively understood as motor competence) and PA dose with executive function in a low socio-economic demographic. Demographics, motor competence, and a combination of motor competence and physical activity were hypothesized to be significantly predictor of executive functions.

METHOD

In this cross-sectional study, 360 children aged 5-6 years from deprived areas were assessed using three movement assessments: wrist-worn accelerometery for physical activity dose, Test of Gross Motor Development-3 for movement proficiency, and divergent movement assessment. Executive function, including inhibitory control, working memory, and cognitive flexibility, was measured using the NIH Toolbox on an iPad. Multiple linear regression models were designed to evaluate the independent and combined association of demographics, movement competence and physical activity variables with executive function.

RESULTS

The regression analysis, with demographic factors only, explained 12% of EF variance (r = 0.12 95%CI 0.06-0.18). In addition to this demographics the model with divergent movement explained 19% of EF variance (r = 0.19 95% CI = 0.12-0.28), the model with movement proficiency explained 16% of EF variance (r = 0.16 95% CI = 0.08-0.26) and the model with PA dose explained 13% of EF variance (r = 0.13 95% CI = 0.07-0.20). In these models both divergent movement and proficiency were significant predictors, whilst physical activity variables were not. The final models, combining motor competence and physical activity variables, explained 24% and 23% of EF variance (r = 0.24 CI = 0.14-0.33 and r = 0.23 CI = 0.14-0.32). In these models, motor competence variables were significant predictors, and only vigorous physical activity and Euclidean Norm Minus One emerged as significant PA dose predictors.

DISCUSSION

These findings emphasise that motor competence and physical activity variables better predict executive functions when they are combined. When considered individually both motor competence variables were significant predictors of executive function whilst physical activity variables were not. Importantly, among the two movement competence facets, divergent movement assessment exhibited the strongest association with executive function. Future interventions should consider how to facilitate both movement and cognitive development in children. Future interventions should consider both the interplay of movement quality and quantity and the importance of environments that invite children's exploratory movement behavior.

摘要

背景

在高度贫困地区成长可能会对儿童的运动行为和认知发展产生负面影响。人们认为,增加儿童运动体验的数量和质量有助于促进认知发展。本研究调查了三种不同运动评估模式、运动熟练度和发散性运动能力(统称为运动能力)以及身体活动量与低社会经济人口群体执行功能之间的关联。研究假设人口统计学、运动能力以及运动能力与身体活动的综合因素是执行功能的重要预测指标。

方法

在这项横断面研究中,对360名来自贫困地区的5至6岁儿童进行了三种运动评估:使用腕部佩戴的加速度计测量身体活动量,采用《粗大运动发展测试-3》评估运动熟练度,以及进行发散性运动评估。使用iPad上的美国国立卫生研究院工具箱测量执行功能,包括抑制控制、工作记忆和认知灵活性。设计了多个线性回归模型,以评估人口统计学、运动能力和身体活动变量与执行功能之间的独立关联和综合关联。

结果

仅包含人口统计学因素的回归分析解释了执行功能变异的12%(r = 0.12,95%置信区间0.06 - 0.18)。除人口统计学因素外,包含发散性运动的模型解释了执行功能变异的19%(r = 0.19,95%置信区间 = 0.12 - 0.28),包含运动熟练度的模型解释了执行功能变异的16%(r = 0.16,95%置信区间 = 0.08 - 0.26),包含身体活动量的模型解释了执行功能变异的13%(r = 0.13,95%置信区间 =

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