Lee Paul H
School of Nursing, Hong Kong Polytechnic University, Hong Kong.
Gait Posture. 2015 Feb;41(2):516-21. doi: 10.1016/j.gaitpost.2014.12.008. Epub 2014 Dec 10.
Accelerometers are gaining popularity for measuring physical activity, but there are many different ways to process accelerometer data. A sensitivity analysis was conducted to study the effect of varying accelerometer data processing protocols on estimating the association between PA level and socio-demographic characteristics using the National Health and Nutrition Examination Survey (NHANES) accelerometer data.
The NHANES waves 2003-2004 and 2005-2006 accelerometer data (n=14,072) were used to investigate the effect of changing the accelerometer non-wearing time and valid day definitions on the demographic composition of the filtered datasets and the association between physical activity (PA) and socio-demographic characteristics (sex, age, race, educational level, marital status).
Under different filtering rules (minimum number of valid day and definition of non-wear time), the demographic characteristics of the final sample varied. The proportion of participants aged 20-29 decreased from 18.9% to 15.8% when the minimum number of valid days required increased from 1 to 4 (p for trend<0.001), whereas that for aged ≥70 years increased from 18.9% to 20.6% (p for trend<0.001). Furthermore, with different filters, the effect of these demographic variables and PA varied, with some variables being significant under certain filtering rules but becoming insignificant under some other rules.
The sensitivity analysis showed that the significance of the association between socio-demographic variables and PA could be varied with the definition of non-wearing time and minimum number of valid days.
加速度计在测量身体活动方面越来越受欢迎,但处理加速度计数据有多种不同方法。利用美国国家健康与营养检查调查(NHANES)的加速度计数据进行了一项敏感性分析,以研究不同的加速度计数据处理方案对估计身体活动水平与社会人口学特征之间关联的影响。
使用NHANES 2003 - 2004年和2005 - 2006年的加速度计数据(n = 14,072),研究改变加速度计非佩戴时间和有效日定义对过滤后数据集的人口构成以及身体活动(PA)与社会人口学特征(性别、年龄、种族、教育水平、婚姻状况)之间关联的影响。
在不同的过滤规则(有效日的最少数量和非佩戴时间的定义)下,最终样本的人口学特征有所不同。当所需有效日的最少数量从1天增加到4天时,20 - 29岁参与者的比例从18.9%降至15.8%(趋势p<0.001),而70岁及以上参与者的比例从18.9%增至20.6%(趋势p<0.001)。此外,使用不同的过滤器时,这些人口学变量与PA之间的效应有所变化,一些变量在某些过滤规则下具有显著性,但在其他一些规则下则变得不显著。
敏感性分析表明,社会人口学变量与PA之间关联的显著性可能会因非佩戴时间的定义和有效日的最少数量而有所不同。