Suppr超能文献

提升加速度计评估的身体活动的价值:数据驱动的转化加速度计指标的有意义视觉比较。

Enhancing the value of accelerometer-assessed physical activity: meaningful visual comparisons of data-driven translational accelerometer metrics.

作者信息

Rowlands Alex V, Dawkins Nathan P, Maylor Ben, Edwardson Charlotte L, Fairclough Stuart J, Davies Melanie J, Harrington Deirdre M, Khunti Kamlesh, Yates Tom

机构信息

Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, LE5 4PW, UK.

NIHR Leicester Biomedical Research Centre, Leicester, UK.

出版信息

Sports Med Open. 2019 Dec 5;5(1):47. doi: 10.1186/s40798-019-0225-9.

Abstract

The lack of consensus on meaningful and interpretable physical activity outcomes from accelerometer data hampers comparison across studies. Cut-point analyses are simple to apply and easy to interpret but can lead to results that are not comparable. We propose that the optimal accelerometer metrics for data analysis are not the same as the optimal metrics for translation. Ideally, analytical metrics are precise continuous variables that cover the intensity spectrum, while translational metrics facilitate meaningful, public-health messages and can be described in terms of activities (e.g. brisk walking) or intensity (e.g. moderate-to-vigorous physical activity). Two analytical metrics that capture the volume and intensity of the 24-h activity profile are average acceleration (volume) and intensity gradient (intensity distribution). These allow investigation of independent, additive and interactive associations of volume and intensity of activity with health; however, they are not immediately interpretable. The MX metrics, the acceleration above which the most active X minutes are accumulated, are translational metrics that can be interpreted in terms of indicative activities. Using a range of MX metrics illustrates the intensity gradient and average acceleration (i.e. 24-h activity profile). The M120, M60, M30, M15 and M5 illustrate the most active accumulated minutes of the day, the M/ the most active accumulated 8 h of the day. We demonstrate how radar plots of MX metrics can be used to interpret and translate results from between- and within-group comparisons, provide information on meeting guidelines, assess individual activity profiles relative to percentiles and compare activity profiles between domains and/or time periods.

摘要

对于加速度计数据中具有意义且可解释的身体活动结果缺乏共识,这妨碍了不同研究之间的比较。切点分析应用简单且易于解释,但可能导致结果缺乏可比性。我们认为,用于数据分析的最佳加速度计指标与用于转化的最佳指标并不相同。理想情况下,分析指标是精确的连续变量,涵盖强度范围,而转化指标则有助于传达有意义的公共卫生信息,并且可以用活动(如快走)或强度(如中度至剧烈身体活动)来描述。两个能够捕捉24小时活动概况的量和强度的分析指标是平均加速度(量)和强度梯度(强度分布)。这些指标能够研究活动的量和强度与健康之间的独立、相加和交互关联;然而,它们并不能立即得到解释。MX指标,即累积最活跃X分钟时的加速度,是可以根据指示性活动进行解释的转化指标。使用一系列MX指标可以说明强度梯度和平均加速度(即24小时活动概况)。M120、M60、M30、M15和M5分别表示一天中最活跃的累积分钟数,M/表示一天中最活跃的累积8小时。我们展示了如何使用MX指标的雷达图来解释和转化组间和组内比较的结果,提供有关是否符合指南的信息,评估相对于百分位数的个体活动概况,以及比较不同领域和/或时间段之间的活动概况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d5f/6895365/942fddfb002a/40798_2019_225_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验