Gupta Nidhi, Christiansen Caroline Stordal, Hanisch Christiana, Bay Hans, Burr Hermann, Holtermann Andreas
National Research Centre for the Working Environment, Copenhagen, Denmark.
Federal Institute for Occupational Safety and Health (BAuA), Nöldnerstr, Berlin, Germany.
BMJ Open. 2017 Jan 16;7(1):e013251. doi: 10.1136/bmjopen-2016-013251.
To investigate the differences between a questionnaire-based and accelerometer-based sitting time, and develop a model for improving the accuracy of questionnaire-based sitting time for predicting accelerometer-based sitting time.
183 workers in a cross-sectional study reported sitting time per day using a single question during the measurement period, and wore 2 Actigraph GT3X+ accelerometers on the thigh and trunk for 1-4 working days to determine their actual sitting time per day using the validated Acti4 software. Least squares regression models were fitted with questionnaire-based siting time and other self-reported predictors to predict accelerometer-based sitting time.
Questionnaire-based and accelerometer-based average sitting times were ≈272 and ≈476 min/day, respectively. A low Pearson correlation (r=0.32), high mean bias (204.1 min) and wide limits of agreement (549.8 to -139.7 min) between questionnaire-based and accelerometer-based sitting time were found. The prediction model based on questionnaire-based sitting explained 10% of the variance in accelerometer-based sitting time. Inclusion of 9 self-reported predictors in the model increased the explained variance to 41%, with 10% optimism using a resampling bootstrap validation. Based on a split validation analysis, the developed prediction model on ≈75% of the workers (n=132) reduced the mean and the SD of the difference between questionnaire-based and accelerometer-based sitting time by 64% and 42%, respectively, in the remaining 25% of the workers.
This study indicates that questionnaire-based sitting time has low validity and that a prediction model can be one solution to materially improve the precision of questionnaire-based sitting time.
探讨基于问卷和基于加速度计的久坐时间之间的差异,并建立一个模型以提高基于问卷的久坐时间预测基于加速度计的久坐时间的准确性。
在一项横断面研究中,183名工人在测量期间通过一个单一问题报告每日久坐时间,并在大腿和躯干佩戴2个Actigraph GT3X+加速度计1至4个工作日,使用经过验证的Acti4软件确定其每日实际久坐时间。采用基于问卷的久坐时间和其他自我报告的预测因素拟合最小二乘回归模型,以预测基于加速度计的久坐时间。
基于问卷和基于加速度计的平均久坐时间分别约为272分钟/天和476分钟/天。发现基于问卷和基于加速度计的久坐时间之间的Pearson相关性较低(r = 0.32),平均偏差较高(204.1分钟),一致性界限较宽(549.8至 -139.7分钟)。基于问卷久坐时间的预测模型解释了基于加速度计久坐时间方差的10%。在模型中纳入9个自我报告的预测因素后,解释方差增加到41%,使用重采样自助验证法时乐观估计为10%。基于分割验证分析,在约75%的工人(n = 132)中开发的预测模型,在其余25%的工人中,将基于问卷和基于加速度计的久坐时间差异的均值和标准差分别降低了64%和42%。
本研究表明基于问卷的久坐时间有效性较低,且预测模型可能是大幅提高基于问卷的久坐时间精度的一种解决方案。