Comparison of two methods to assess PAEE during six activities in children
Comparison of two methods to assess PAEE during six activities in children
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DOI：
10.1249/mss.0b013e318150dff8
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发表时间：
2007-12-01
影响因子：
4.1
通讯作者：
Ekelund, Ulf
中科院分区：
文献类型：
--
作者：
Corder, Kirsten;Brage, Soren;Ekelund, Ulf
科尔德，K.，S.布拉吉角马托克斯，A.尼斯角里多赫河J. WAREHAM和U. Ekelund。两种方法评估儿童六种活动中PAEE的比较医学科学体育锻炼：第39卷，第12期，第39页。2180-2188，2007。目的：本研究的目的是比较身体活动能量消耗（PAEE）预测模型的准确性，单独使用加速度计（ACC）和加速度计结合心率监测（HR+ACC），以估计儿童在六种常见活动（躺着，坐着，慢走和快走，跳房子，跑步）期间的PAEE。三个PAEE预测模型，使用当前的数据，和五个以前发表的预测模型进行了交叉验证，以估计PAEE在这个样本。方法：在145名儿童（12.4 +/- 0.2岁）的6项活动中，使用ACC、HR+ACC和间接测热法评估PAEE。一个ACC和两个HR+ACC PAEE预测模型是使用线性回归对当前研究的数据进行推导的。这三个新的模型进行交叉验证，使用刀切法，并使用修改后的Bland-Altman方法来评估所有八个模型的有效性。结果如下：使用当前研究中推导出的一个ACC和两个HR+ACC模型进行的PAEE预测与测量值密切相关（RMSE = 97.3-118.0 J.min（-1）.kg（-1））。所有五个先前发表的模型总体上一致（RMSE = 115.6-245.3 J.min（-1）.kg（-1）），但其中大部分存在系统误差，ACC. Conclusions：ACC和HR+ACC均可用于预测儿童在这六种活动期间的总体PAEE;然而，所有预测均存在系统误差。虽然ACC和HR+ACC都能准确预测总体PAEE，但根据本研究中的活动，使用HR+ACC的PAEE预测模型可能比仅基于加速度计的模型更准确，适用范围更广。
CORDER, K., S. BRAGE, C. MATTOCKS, A. NESS, C. RIDDOCH, N. J. WAREHAM, and U. EKELUND. Comparison of Two Methods to Assess PAEE during Six Activities in Children. Med. Sci. Sports Exerc., Vol. 39, No. 12, pp. 2180-2188, 2007. Purpose: The purpose of this study was to compare the accuracy of physical activity energy expenditure (PAEE)-prediction models using accelerometry alone (ACC) and accelerometry combined with heart rate monitoring (HR+ACC) to estimate PAEE during six common activities in children (lying, sitting, slow and brisk walking, hop-scotch, running). Three PAEE-prediction models derived using the current data, and five previously published prediction models were cross-validated to estimate PAEE in this sample. Methods: PAEE was assessed using ACC, HR+ACC, and indirect calorimetry during six activities in 145 children (12.4 +/- 0.2 yr). One ACC and two HR+ACC PAEE-prediction models were derived using linear regression on data from the current study. These three new models were cross-validated using a jackknife approach, and a modified Bland-Altman method was used to assess the validity of all eight models. Results: PAEE predictions using the one ACC and two HR+ACC models derived in the current study correlated strongly with measured values (RMSE = 97.3-118.0 J.min(-1).kg(-1)). All five previously published models agreed well overall (RMSE = 115.6-245.3 J.min(-1).kg(-1)), but systematic error was present for most of these, to a greater extent for ACC. Conclusions: ACC and HR+ACC can both be used to predict overall PAEE during these six activities in children; however, systematic error was present in all predictions. Although both ACC and HR+ACC provide accurate predictions of overall PAEE, according to the activities in this study, PAEE-prediction models using HR+ACC may be more accurate and widely applicable than those based on accelerometry alone.