Department of Health, Nutrition, and Exercise Sciences, North Dakota State University, Fargo, ND, 58108, USA.
Division of Kinesiology, School of Public Health, The University of Hong Kong Li Ka Shing Faculty of Medicine, Room 301D 3/F, Jockey Club Building for Interdisciplinary Research, 5 Sassoon Road, Pokfulam, Hong Kong.
BMC Med Res Methodol. 2019 Feb 7;19(1):29. doi: 10.1186/s12874-019-0668-1.
Recent advances in sensor technologies have promoted the use of consumer-based accelerometers such as Fitbit Flex in epidemiological and clinical research; however, the validity of the Fitbit Flex in measuring sedentary behavior (SED) and physical activity (PA) has not been fully determined against previously validated research-grade accelerometers such as ActiGraph GT3X+. Therefore, the purpose of this study was to examine the concurrent validity of the Fitbit Flex against ActiGraph GT3X+ in a free-living condition.
A total of 65 participants (age: M = 42, SD = 14 years, female: 72%) each wore a Fitbit Flex and GT3X+ for seven consecutive days. After excluding sleep and non-wear time, time spent (min/day) in SED and moderate-to-vigorous PA (MVPA) were estimated using various cut-points for GT3X+ and brand-specific algorithms for Fitbit, respectively. Repeated measures one-way ANOVA and mean absolute percent errors (MAPE) served to examine differences and measurement errors in SED and MVPA estimates between Fitbit Flex and GT3X+, respectively. Pearson and Spearman correlations and Bland-Altman (BA) plots were used to evaluate the association and potential systematic bias between Fitbit Flex and GT3X+. PROC MIXED procedure in SAS was used to examine the equivalence (i.e., the 90% confidence interval with ±10% equivalence zone) between the devices.
Fitbit Flex produced similar SED and low MAPE (mean difference [MD] = 37 min/day, P = .21, MAPE = 6.8%), but significantly higher MVPA and relatively large MAPE (MD = 59-77 min/day, P < .0001, MAPE = 56.6-74.3%) compared with the estimates from GT3X+ using three different cut-points. The correlations between Fitbit Flex and GT3X+ were consistently higher for SED (r = 0.90, ρ = 0.86, P < .01), but weaker for MVPA (r = 0.65-0.76, ρ = 0.69-0.79, P < .01). BA plots revealed that there is no apparent bias in estimating SED.
In comparison with the GT3X+ accelerometer, the Fitbit Flex provided comparatively accurate estimates of SED, but the Fitbit Flex overestimated MVPA under free-living conditions. Future investigations using the Fitbit Flex should be aware of present findings.
最近传感器技术的进步推动了消费级加速度计(如 Fitbit Flex)在流行病学和临床研究中的应用;然而,Fitbit Flex 在测量久坐行为(SED)和身体活动(PA)方面的有效性尚未通过与 ActiGraph GT3X+等经过验证的研究级加速度计进行充分确定。因此,本研究的目的是在自由生活条件下检验 Fitbit Flex 与 ActiGraph GT3X+ 的同时效度。
共有 65 名参与者(年龄:M=42,SD=14 岁,女性:72%)每人佩戴 Fitbit Flex 和 GT3X+连续 7 天。在排除睡眠和非佩戴时间后,使用 GT3X+的各种截断值和 Fitbit 的品牌特定算法分别估计 SED 和中等到剧烈体力活动(MVPA)的时间(分钟/天)。重复测量单向方差分析和平均绝对百分比误差(MAPE)用于分别检查 Fitbit Flex 和 GT3X+之间 SED 和 MVPA 估计值的差异和测量误差。Pearson 和 Spearman 相关性以及 Bland-Altman(BA)图用于评估 Fitbit Flex 和 GT3X+之间的关联和潜在系统偏差。SAS 中的 PROC MIXED 过程用于检查设备之间的等效性(即,90%置信区间加 10%等效区间)。
Fitbit Flex 产生了相似的 SED 和较低的 MAPE(平均差异[MD]=37 分钟/天,P=.21,MAPE=6.8%),但使用三个不同截断值时,MVPA 显著较高且相对较大的 MAPE(MD=59-77 分钟/天,P<.0001,MAPE=56.6-74.3%)。与 GT3X+的估计相比,Fitbit Flex 与 GT3X+的相关性始终更高SED(r=0.90,ρ=0.86,P<.01),但 MVPA 较弱(r=0.65-0.76,ρ=0.69-0.79,P<.01)。BA 图显示,在估计 SED 方面,没有明显的偏差。
与 GT3X+加速度计相比,Fitbit Flex 提供了相对准确的 SED 估计值,但在自由生活条件下,Fitbit Flex 高估了 MVPA。使用 Fitbit Flex 的未来研究应该注意到目前的发现。