MRC Epidemiology Unit, University of Cambridge, Cambridge, UK.
School of Health Sciences, Western Sydney University, Sydney, Australia.
Int J Behav Nutr Phys Act. 2022 Apr 2;19(1):41. doi: 10.1186/s12966-022-01282-4.
Physical activity (PA) declines during childhood. Important sources of PA are active travel, organised sport and physical education (PE), but it is unclear how these domain-specific PA sources contribute to (changes in) daily moderate-to-vigorous PA (MVPA) in young people. This study aimed to examine (1) the cross-sectional association between domain-specific physical activity (i.e., active travel, organised sport and PE) and daily minutes in accelerometer-assessed MVPA; and (2) the longitudinal association between domain-specific physical activity at baseline and change in daily minutes in MVPA.
Participants (baseline age 11.3 ± .1.2 years) were drawn from three studies in the International Children's Accelerometry Database. The contribution of self-reported standardised active travel, organised sport and PE to accelerometer-measured daily minutes in MVPA was examined using linear regression. In cross-sectional analyses, MVPA was regressed on each PA domain in separate models, adjusted for study, age, sex, maternal education, season, and monitor wear time. In longitudinal analyses, change in MVPA was regressed on each of the baseline PA domains, additionally adjusting for changes in season and wear time, follow-up duration, and baseline MVPA. R-squared was used to compare variance explained by each PA domain.
In the cross-sectional analyses (n = 3871), organised sport (standardised β = 3.81, 95% confidence interval [95%CI] = 3.06, 4.56) and active travel (β = 3.46, 95%CI = 2.73, 4.19) contributed more to daily MVPA than PE (β = 0.82, 95%CI = -0.02, 1.66). Compared to the base model which included only covariates (R = 21.5%), organised sport (absolute change: + 1.9%) and active travel (+ 1.7%) models explained more of the variance than the PE model (± < 0.1%). Associations followed a similar pattern in the longitudinal analyses (n = 2302), but none of the PA domains predicted change in MVPA (organised sport: standardised β = 0.85, 95%CI = -0.03, 1.72; active travel: β = 0.68, 95%CI = -0.14, 1.50; PE: β = 0.02, 95%CI = -0.87, 0.91).
A multi-sectoral approach covering a wide range of PA domains should be promoted to minimise the age-related decline in MVPA during childhood.
儿童期的身体活动(PA)会下降。PA 的重要来源包括积极出行、有组织的运动和体育教育(PE),但尚不清楚这些特定领域的 PA 来源如何促进年轻人日常中到剧烈 PA(MVPA)的变化。本研究旨在检验:(1)特定领域的身体活动(即积极出行、有组织的运动和 PE)与加速度计评估的日常 MVPA 分钟数之间的横断面关联;(2)基线时特定领域的身体活动与日常 MVPA 分钟数变化之间的纵向关联。
参与者(基线年龄为 11.3±0.1.2 岁)来自国际儿童加速度数据库中的三项研究。使用线性回归检验自我报告的标准化积极出行、有组织的运动和 PE 对加速度计测量的日常 MVPA 分钟数的贡献。在横断面分析中,MVPA 分别在单独的模型中回归到每个 PA 领域,调整了研究、年龄、性别、母亲教育、季节和监测佩戴时间。在纵向分析中,MVPA 的变化回归到基线 PA 领域中的每一个,此外还调整了季节和佩戴时间、随访持续时间和基线 MVPA 的变化。R-squared 用于比较每个 PA 领域解释的方差。
在横断面分析中(n=3871),有组织的运动(标准化β=3.81,95%置信区间 [95%CI]=3.06,4.56)和积极出行(β=3.46,95%CI=2.73,4.19)比 PE(β=0.82,95%CI=-0.02,1.66)对日常 MVPA 的贡献更大。与仅包含协变量的基础模型相比(R²=21.5%),有组织的运动(绝对变化:+1.9%)和积极出行(+1.7%)模型比 PE 模型(±<0.1%)解释了更多的方差。在纵向分析中(n=2302),关联也呈现出类似的模式,但 PA 领域中没有一个可以预测 MVPA 的变化(有组织的运动:标准化β=0.85,95%CI=0.03,1.72;积极出行:β=0.68,95%CI=-0.14,1.50;PE:β=0.02,95%CI=-0.87,0.91)。
应推广多部门方法,涵盖广泛的 PA 领域,以最大限度地减少儿童期与年龄相关的 MVPA 下降。