Ann & Robert H. Lurie Children's Hospital of Chicago Stanley Manne Children's Research Institute, 225 E Chicago Ave, Box 157, Chicago, IL, 60611, USA.
Faculty of Education, Arts and Sport, Western Norway University of Applied Sciences, Sogndal, Norway.
Int J Behav Nutr Phys Act. 2019 Apr 29;16(1):40. doi: 10.1186/s12966-019-0801-x.
Accelerometers are widely used to assess child physical activity (PA) levels. Using the accelerometer data, several PA metrics can be estimated. Knowledge about the relationships between these different metrics can improve our understanding of children's PA behavioral patterns. It also has significant implications for comparing PA metrics across studies and fitting a statistical model to examine their health effects. The aim of this study was to examine the relationships among the metrics derived from accelerometers in children.
Accelerometer data from 24,316 children aged 5 to 18 years were extracted from the International Children's Accelerometer Database (ICAD) 2.0. Correlation coefficients between wear time, sedentary behavior (SB), light-intensity PA (LPA), moderate-intensity PA (MPA), vigorous-intensity PA (VPA), moderate- and vigorous-intensity PA (MVPA), and total activity counts (TAC) were calculated.
TAC was approximately 22X10 counts higher (p < 0.01) with longer wear time (13 to 18 h/day) as compared to shorter wear time (8 to < 13 h/day), while MVPA was similar across the wear time categories. MVPA was very highly correlated with TAC (r = .91; 99% CI = .91 to .91). Wear time-adjusted correlation between SB and LPA was also very high (r = -.96; 99% CI = -.96, - 95). VPA was moderately correlated with MPA (r = .58; 99% CI = .57, .59).
TAC is mostly explained by MVPA, while it could be more dependent on wear time, compared to MVPA. MVPA appears to be comparable across different wear durations and studies when wear time is ≥8 h/day. Due to the moderate to high correlation between some PA metrics, potential collinearity should be addressed when including multiple PA metrics together in statistical modeling.
加速度计被广泛用于评估儿童的身体活动（PA）水平。使用加速度计数据，可以估计几个 PA 指标。了解这些不同指标之间的关系可以提高我们对儿童 PA 行为模式的理解。这对于比较研究之间的 PA 指标以及拟合统计模型以检查其健康影响也具有重要意义。本研究旨在检查儿童加速度计衍生指标之间的关系。
从国际儿童加速度计数据库（ICAD）2.0 中提取了 24316 名 5 至 18 岁儿童的加速度计数据。计算了佩戴时间、久坐行为（SB）、低强度 PA（LPA）、中强度 PA（MPA）、高强度 PA（VPA）、中高强度 PA（MVPA）和总活动计数（TAC）之间的相关系数。
与佩戴时间较短（8 至 <13 小时/天）相比，佩戴时间较长（13 至 18 小时/天）时，TAC 高约 22X10 计数（p <0.01），而 MVPA 在佩戴时间类别中相似。MVPA 与 TAC 高度相关（r =.91；99%CI =.91 至.91）。SB 与 LPA 之间的佩戴时间调整后的相关性也非常高（r = -.96；99%CI = -.96，-95）。VPA 与 MPA 中度相关（r =.58；99%CI =.57，.59）。
与 MVPA 相比，TAC 主要由 MVPA 解释，而与 MVPA 相比，TAC 可能更多地依赖佩戴时间。当佩戴时间≥8 小时/天时，MVPA 似乎在不同佩戴持续时间和研究中是可比的。由于一些 PA 指标之间存在中度到高度相关性，因此在将多个 PA 指标一起包含在统计模型中时，应解决潜在的共线性问题。
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