Sedentary Time in Children: Influence of Accelerometer Processing on Health Relations
Sedentary Time in Children: Influence of Accelerometer Processing on Health Relations
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DOI：
10.1249/mss.0b013e318282190e
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发表时间：
2013-06-01
影响因子：
4.1
通讯作者：
Brage, Soren
中科院分区：
文献类型：
--
作者：
Atkin, Andrew J.;Ekelund, Ulf;Brage, Soren
目的：在流行病学研究中，加速度计越来越多地被用于评估久坐时间，但处理这些数据的最合适方法仍不确定。这项横断面研究考察了选定的加速度计切割点和非磨损标准对久坐时间与肥胖和聚集性代谢风险之间关系的影响。方法：数据来自欧洲青年心脏研究，其中包括用加速度计评估久坐时间。基于经常使用的切割点（每分钟100、500、800和1100次）和非磨损标准（10、20、60和100分钟连续零）的组合，构建了16个久坐时间变量。通过四项皮褶厚度测量的总和来评估肥胖。计算聚类代谢风险评分作为标准化代谢综合征成分的平均值，包括血压、胰岛素抵抗和空腹倒胆固醇。采用多水平横断面时间序列回归进行分析，并根据整体身体活动（每分钟加速度计计数）进行调整。荟萃分析用于获得所有处理方案的暴露-结果关联的汇总估计；meta回归用于确定非磨损和切点方案对观察到的关联的影响。结果：久坐时间服从截断点（指数= 0.27）和零串（指数= 0.03）的幂律，与聚集性代谢风险呈正相关（beta = 0.0051, 95%可信区间= 0.0018-0.0085）。这种关联被切点所缓和，切点越高通常产生更强的关联。未观察到久坐时间与肥胖之间的显著关联。结论：加速度计切断点的选择可能会缓和久坐时间与聚集性代谢风险之间的关联，这表明使用不同切断点的研究之间的直接比较必须谨慎。
Purpose: Accelerometry is increasingly being used to assess sedentary time in epidemiological studies, yet the most appropriate means of processing these data remains uncertain. This cross-sectional study examined the influence of selected accelerometer cut points and nonwear criteria on associations of sedentary time with adiposity and clustered metabolic risk. Methods: Data were from the European Youth Heart Study, which included assessment of sedentary time by accelerometer. Sixteen sedentary time variables were constructed based on combinations of frequently used cut points (100, 500, 800, and 1100 counts per minute) and nonwear criteria (10-, 20-, 60-, and 100-min consecutive zeros). Adiposity was assessed by sum of four skinfold thickness measures. A clustered metabolic risk score was calculated as the mean of standardized metabolic syndrome components, including blood pressure, insulin resistance, and inverted fasting HDL-cholesterol. Analyses were conducted using multilevel cross-sectional time series regression, adjusted for overall physical activity (accelerometer counts per minute). Meta-analysis was used to obtain pooled estimates of the exposure-outcome association over all processing protocols; meta-regression was used to determine the influence of nonwear and cut point protocol on observed associations. Results: Sedentary time follows a power law with cut point (exponent = 0.27) and zero string (exponent = 0.03), and it was positively associated with clustered metabolic risk (beta = 0.0051; 95% confidence interval = 0.0018-0.0085). The association was moderated by cut point, with higher cut points typically producing stronger associations. No significant association between sedentary time and adiposity was observed. Conclusions: The choice of accelerometer cut point may moderate the association between sedentary time and clustered metabolic risk, suggesting that direct comparisons of associations between studies using different cut points must be made with caution.