School of Nursing and Health Sciences, Faculty of Health Sciences and Wellbeing, University of Sunderland, Sunderland, SR1 3SD, UK.
BMC Public Health. 2018 Apr 23;18(1):543. doi: 10.1186/s12889-018-5215-1.
Physical activity and sedentary behaviour are difficult to assess in overweight and obese adults. However, the use of open-source, raw accelerometer data analysis could overcome this. This study compared raw accelerometer and questionnaire-assessed moderate-to-vigorous physical activity (MVPA), walking and sedentary behaviour in normal, overweight and obese adults, and determined the effect of using different methods to categorise overweight and obesity, namely body mass index (BMI), bioelectrical impedance analysis (BIA) and waist-to-hip ratio (WHR).
One hundred twenty adults, aged 24-60 years, wore a raw, tri-axial accelerometer (Actigraph GT3X+), for 3 days and completed a physical activity questionnaire (IPAQ-S). We used open-source accelerometer analyses to estimate MVPA, walking and sedentary behaviour from a single raw accelerometer signal. Accelerometer and questionnaire-assessed measures were compared in normal, overweight and obese adults categorised using BMI, BIA and WHR.
Relationships between accelerometer and questionnaire-assessed MVPA (Rs = 0.30 to 0.48) and walking (Rs = 0.43 to 0.58) were stronger in normal and overweight groups whilst sedentary behaviour were modest (Rs = 0.22 to 0.38) in normal, overweight and obese groups. The use of WHR resulted in stronger agreement between the questionnaire and accelerometer than BMI and BIA. Finally, accelerometer data showed stronger associations with BMI, BIA and WHR (Rs = 0.40 to 0.77) than questionnaire data (Rs = 0.24 to 0.37).
Open-source, raw accelerometer data analysis can be used to estimate MVPA, walking and sedentary behaviour from a single acceleration signal in normal, overweight and obese adults. Our data supports the use of WHR to categorise overweight and obese adults. This evidence helps researchers obtain more accurate measures of physical activity and sedentary behaviour in overweight and obese populations.
在超重和肥胖成年人中，身体活动和久坐行为难以评估。然而，使用开源、原始加速度计数据分析可以克服这一问题。本研究比较了正常体重、超重和肥胖成年人中原始加速度计和问卷评估的中等到剧烈体力活动（MVPA）、步行和久坐行为，并确定了使用不同方法（体重指数（BMI）、生物电阻抗分析（BIA）和腰臀比（WHR））来分类超重和肥胖的效果。
120 名年龄在 24-60 岁的成年人佩戴原始三轴加速度计（Actigraph GT3X+）3 天，并完成体力活动问卷（IPAQ-S）。我们使用开源加速度计分析从单个原始加速度计信号估计 MVPA、步行和久坐行为。使用 BMI、BIA 和 WHR 对正常、超重和肥胖成年人进行分类，比较加速度计和问卷评估的测量值。
在正常和超重组中，加速度计和问卷评估的 MVPA（Rs=0.30 至 0.48）和步行（Rs=0.43 至 0.58）之间的关系更强，而在正常、超重和肥胖组中，久坐行为的关系适度（Rs=0.22 至 0.38）。与 BMI 和 BIA 相比，WHR 的使用导致问卷和加速度计之间的一致性更强。最后，与问卷数据（Rs=0.24 至 0.37）相比，加速度计数据与 BMI、BIA 和 WHR（Rs=0.40 至 0.77）之间的关联更强。
开源原始加速度计数据分析可用于从正常、超重和肥胖成年人的单个加速度信号中估计 MVPA、步行和久坐行为。我们的数据支持使用 WHR 来分类超重和肥胖成年人。该证据有助于研究人员在超重和肥胖人群中获得更准确的身体活动和久坐行为测量值。
