Background

Physical activity promotes healthy ageing in older people. Accurate measurement of physical activity in free-living environment is important in evaluating physical activity interventions. Research question:What is the criterion validity of 1)an ActiGraph to identify physical activity at different intensity levels and 2)an ActiGraph and a smartphone to measure step rate?

Methods

Community-dwelling older people aged≥60 were recruited. The index tests were using ActiGraph worn in different positions (i.e.,both wrists and hip) to measure physical activity intensity and step rate and using smartphone (i.e., Samsung J2 pro and Google Fit) worn in different positions (i.e.,trousers pocket and waist pouch) to measure the step rate. The reference standards were using indirect calorimetry (i.e.,CosMedK4b 2) to measure physical activity intensity and using direct observation for step rate. Subjects were exposed in different physical activity intensity levels (i.e.,sedentary:MET < 1.5,light: MET = 1.5–2.99, moderate:MET = 3.0–6.0, vigorous:MET>6) and step rates through walking on a treadmill at different speeds (i.e.,2−8 km) for approximately 30 min. Spearman’s rho, ROC analysis, and percentage error were employed to report the criterion validity. Results:31 participants completed the tests. ActiGraphs worn in different body positions could significantly differentiate physical activity intensity at the levels of “light- or-above” (VM cut-off = 279.5–1959.1,AUC = 0.932−0.954), “moderate-or-above” (VM cut- off = 1051.0–4212.9,AUC = 0.918−0.932), and “vigorous” (VM cut-off = 3335.4–5093.0, AUC = 0.890−0.907) well with different cut-off points identified. The step rate measured by direct observation correlated significantly with ActiGraph and smartphone (rho = 0.415−0.791). Both ActiGraph and smartphone at different positions generally underestimated the step rate (%error= -20.5,-30.3).

Significance

A wrist-worn ActiGraph can accurately identify different physical activity intensity levels in older people, but lower cut-off points in older people should be adopted. To measure step rate, a hip-mounted ActiGraph is preferable than a wrist- worn one. A smartphone employing Google Fit generally underestimates step rate but it gives a relatively more accurate estimation of step rate when the older people walk at a speed of 4−8 km/h.

中文翻译：

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关于使用智能手机和腕戴式ActiGraphs来测量老年人不同强度和步速的身体活动的验证研究

背景

体育锻炼可促进老年人的健康衰老。自由生活环境中体育活动的准确测量对于评估体育活动干预措施很重要。研究问题：1）使用ActiGraph识别不同强度水平的体育活动以及2）使用ActiGraph和智能手机测量步速的标准有效性是什么？

方法

招募了60岁以上的社区居住老年人。指数测试是使用在不同位置（即手腕和臀部）佩戴的ActiGraph来测量体力活动强度和步速，并使用在不同位置（即裤子的口袋和腰部）佩戴的智能手机（例如Samsung J2 pro和Google Fit）袋）来测量步幅。参考标准使用间接量热法（即CosMedK4b 2）测量身体活动强度，并使用直接观察步速。受试者暴露在不同的体育活动强度水平下（即，中度：MET <1.5，轻度：MET = 1.5–2.99，中度：MET = 3.0–6.0，剧烈运动：MET> 6），并且在不同的跑步机上行走的步速速度（即2-8公里）约30分钟。Spearman的rho，ROC分析，使用百分比误差报告标准的有效性。结果：31名参与者完成了测试。佩戴在不同身体位置的ActiGraphs可以显着地区分“轻度或高于”（VM截止= 279.5–1959.1，AUC = 0.932-0.954），“中度或高于”（VM截止）水平的体育活动强度-off = 1051.0–4212.9，AUC = 0.918–0.932）和“剧烈”（VM截止= 3335.4–5093.0，AUC = 0.890–0.907），并确定了不同的截止点。通过直接观察测得的步速与ActiGraph和智能手机显着相关（rho = 0.415-0.791）。处于不同位置的ActiGraph和智能手机通常都低估了步进率（％error = -20.5，-30.3）。佩戴在不同身体位置的ActiGraphs可以显着地区分“轻度或高于”（VM截止= 279.5–1959.1，AUC = 0.932-0.954），“中度或高于”（VM截止）水平的体育活动强度-off = 1051.0–4212.9，AUC = 0.918–0.932）和“剧烈”（VM截止= 3335.4–5093.0，AUC = 0.890–0.907），并确定了不同的截止点。通过直接观察测得的步速与ActiGraph和智能手机显着相关（rho = 0.415-0.791）。处于不同位置的ActiGraph和智能手机通常都低估了步进率（％error = -20.5，-30.3）。佩戴在不同身体位置的ActiGraphs可以显着地区分“轻度或高于”（VM截止= 279.5–1959.1，AUC = 0.932-0.954），“中度或高于”（VM截止）水平的体育活动强度-off = 1051.0–4212.9，AUC = 0.918–0.932）和“剧烈”（VM截止= 3335.4–5093.0，AUC = 0.890–0.907），并确定了不同的截止点。通过直接观察测得的步速与ActiGraph和智能手机显着相关（rho = 0.415-0.791）。处于不同位置的ActiGraph和智能手机通常都低估了步进率（％error = -20.5，-30.3）。907）确定了不同的分界点。通过直接观察测得的步速与ActiGraph和智能手机显着相关（rho = 0.415-0.791）。处于不同位置的ActiGraph和智能手机通常都低估了步进率（％error = -20.5，-30.3）。907）确定了不同的分界点。通过直接观察测得的步速与ActiGraph和智能手机显着相关（rho = 0.415-0.791）。处于不同位置的ActiGraph和智能手机通常都低估了步进率（％error = -20.5，-30.3）。

意义

戴在手腕上的ActiGraph可以准确识别老年人的不同运动强度水平，但应采用较低的临界值。为了测量步速，在臀部安装的ActiGraph比在腕上佩戴的ActiGraph更可取。使用Google Fit的智能手机通常会低估步速，但是当老年人以4-8 km / h的速度行走时，它会相对准确地估算步速。