Measuring free-living energy expenditure and physical activity with triaxial accelerometry
Measuring free-living energy expenditure and physical activity with triaxial accelerometry
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DOI：
10.1038/oby.2005.165
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发表时间：
2005-08-01
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影响因子：
--
通讯作者：
Westerterp, K
中科院分区：
文献类型：
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作者：
Plasqui, G;Joosen, AMCP;Westerterp, K
目的：研究新开发的三轴加速度计在自由生活条件下预测总能量消耗（EE）（TEE）和活动相关能量消耗（AEE）的能力。研究方法和程序：受试者为 29 名年龄在 18 岁至 40 岁之间的健康受试者。连续佩戴运动登记三轴加速度计（Tracmor）15 天。 Trammor 输出定义为所有三个轴或每个轴单独（ACD-X、ACD-Y、ACD-Z）总和的每日活动计数 (ACD)。 TEE 采用双标记水技术测量。睡眠代谢率（SMR）是在呼吸室过夜期间测量的。体力活动水平计算为TEE X SMR-1，AEE计算为[(0.9 X TEE) - SMR]。使用 Siri 的三室模型根据体重、身体体积和体内总水分计算身体成分。结果：年龄、身高、体重和 ACD 解释了 TEE 变化的 83% [估计标准误差 (SEE) = 1.00 MJ/d] 和 AEE 变化的 81% (SEE = 0.70 MJ/d)。 ACD 与 TEE 和 AEE 的部分相关性分别为 0.73 (p < 0.001) 和 0.79 (p < 0.001)。当 SMR 或身体成分数据与 ACD 结合使用时，TEE 的解释变异为 90%（SEE 分别 = 0.74 和 0.77 MJ/d）。使用三轴而不是一轴（垂直）解释的变异增加了 5% (p < 0.05)。讨论：Tracmor 输出和 EE 测量之间的相关性是迄今为止报道的最高。为了测量日常生活活动，使用三轴加速度测量似乎比单轴更有好处。
Objective: To investigate the ability of a newly developed triaxial accelerometer to predict total energy expenditure (EE) (TEE) and activity-related EE (AEE) in free-living conditions.Research Methods and Procedures: Subjects were 29 healthy subjects between the ages of 18 and 40. The Triaxial Accelerometer for Movement Registration (Tracmor) was worn for 15 consecutive days. Tracmor output was defined as activity counts per day (ACD) for the sum of all three axes or each axis separately (ACD-X, ACD-Y, ACD-Z). TEE was measured with the doubly labeled water technique. Sleeping metabolic rate (SMR) was measured during an overnight stay in a respiration chamber. The physical activity level was calculated as TEE X SMR-1, and AEE was calculated as [(0.9 X TEE) - SMR]. Body composition was calculated from body weight, body volume, and total body water using Siri's three-compartment model.Results: Age, height, body mass, and ACD explained 83% of the variation in TEE [standard error of estimate (SEE) = 1.00 MJ/d] and 81% of the variation in AEE (SEE = 0.70 MJ/d). The partial correlations for ACD were 0.73 (p < 0.001) and 0.79 (p < 0.001) with TEE and AEE, respectively. When data on SMR or body composition were used with ACD, the explained variation in TEE was 90% (SEE = 0.74 and 0.77 MJ/d, respectively). The increase in the explained variation using three axes instead of one axis (vertical) was 5% (p < 0.05).Discussion: The correlations between Tracmor output and EE measures are the highest reported so far. To measure daily life activities, the use of triaxial accelerometry seems beneficial to uniaxial.