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消费者可穿戴活动追踪器测量的身体活动与自我报告测量的身体活动的比较:健康电子心脏研究的横断面分析。

Comparison of the Physical Activity Measured by a Consumer Wearable Activity Tracker and That Measured by Self-Report: Cross-Sectional Analysis of the Health eHeart Study.

机构信息

Department of Medicine, University of California San Francisco, San Francisco, CA, United States.

Division of Cardiology, Department of Medicine, University of California San Francisco, San Francisco, CA, United States.

出版信息

JMIR Mhealth Uhealth. 2020 Dec 29;8(12):e22090. doi: 10.2196/22090.

DOI:10.2196/22090
PMID:33372896
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7803477/
Abstract

BACKGROUND

Commercially acquired wearable activity trackers such as the Fitbit provide objective, accurate measurements of physically active time and step counts, but it is unclear whether these measurements are more clinically meaningful than self-reported physical activity.

OBJECTIVE

The aim of this study was to compare self-reported physical activity to Fitbit-measured step counts and then determine which is a stronger predictor of BMI by using data collected over the same period reflecting comparable physical activities.

METHODS

We performed a cross-sectional analysis of data collected by the Health eHeart Study, a large mobile health study of cardiovascular health and disease. Adults who linked commercially acquired Fitbits used in free-living conditions with the Health eHeart Study and completed an International Physical Activity Questionnaire (IPAQ) between 2013 and 2019 were enrolled (N=1498). Fitbit step counts were used to quantify time by activity intensity in a manner comparable to the IPAQ classifications of total active time and time spent being sedentary, walking, or doing moderate activities or vigorous activities. Fitbit steps per day were computed as a measure of the overall activity for exploratory comparisons with IPAQ-measured overall activity (metabolic equivalent of task [MET]-h/wk). Measurements of physical activity were directly compared by Spearman rank correlation. Strengths of associations with BMI for Fitbit versus IPAQ measurements were compared using multivariable robust regression in the subset of participants with BMI and covariates measured.

RESULTS

Correlations between synchronous paired measurements from Fitbits and the IPAQ ranged in strength from weak to moderate (0.09-0.48). In the subset with BMI and covariates measured (n=586), Fitbit-derived predictors were generally stronger predictors of BMI than self-reported predictors. For example, an additional hour of Fitbit-measured vigorous activity per week was associated with nearly a full point reduction in BMI (-0.84 kg/m, 95% CI -1.35 to -0.32) in adjusted analyses, whereas the association between self-reported vigorous activity measured by IPAQ and BMI was substantially smaller in magnitude (-0.17 kg/m, 95% CI -0.34 to -0.00; P<.001 versus Fitbit) and was dominated by the Fitbit-derived predictor when compared head-to-head in a single adjusted multivariable model. Similar patterns of associations with BMI, with Fitbit dominating self-report, were seen for moderate activity and total active time and in comparisons between overall Fitbit steps per day and IPAQ MET-h/wk on standardized scales.

CONCLUSIONS

Fitbit-measured physical activity was more strongly associated with BMI than self-reported physical activity, particularly for moderate activity, vigorous activity, and summary measures of total activity. Consumer-marketed wearable activity trackers such as the Fitbit may be useful for measuring health-relevant physical activity in clinical practice and research.

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd1/7803477/ec503e2bbea9/mhealth_v8i12e22090_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd1/7803477/521b15f5fc03/mhealth_v8i12e22090_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd1/7803477/4e47a9d5f840/mhealth_v8i12e22090_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd1/7803477/3578f01fcad3/mhealth_v8i12e22090_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd1/7803477/ec503e2bbea9/mhealth_v8i12e22090_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd1/7803477/521b15f5fc03/mhealth_v8i12e22090_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd1/7803477/4e47a9d5f840/mhealth_v8i12e22090_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd1/7803477/3578f01fcad3/mhealth_v8i12e22090_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd1/7803477/ec503e2bbea9/mhealth_v8i12e22090_fig4.jpg
摘要

背景

市售的可穿戴活动追踪器,如 Fitbit,可提供客观、准确的身体活动时间和步数测量,但尚不清楚这些测量值是否比自我报告的身体活动更有临床意义。

目的

本研究旨在比较自我报告的身体活动与 Fitbit 测量的步数,并使用同期反映可比身体活动的数据来确定哪种测量方式对 BMI 的预测能力更强。

方法

我们对健康电子心脏研究(一项大型的移动健康心血管健康和疾病研究)中收集的数据进行了横断面分析。该研究纳入了在自由生活条件下使用市售 Fitbit 并在 2013 年至 2019 年期间完成国际体力活动问卷(IPAQ)的成年人(N=1498)。Fitbit 步数用于按活动强度量化时间,与 IPAQ 对总活动时间和久坐、步行或进行适度活动或剧烈活动时间的分类相匹配。Fitbit 每天的步数作为与 IPAQ 测量的整体活动(代谢当量[MET]-小时/周)进行探索性比较的整体活动的衡量标准。通过 Spearman 秩相关直接比较测量值。使用多元稳健回归在具有 BMI 和协变量测量值的参与者子集中比较 Fitbit 与 IPAQ 测量值与 BMI 的关联强度。

结果

Fitbit 和 IPAQ 同步配对测量值之间的相关性从弱到中度不等(0.09-0.48)。在具有 BMI 和协变量测量值的参与者子集(n=586)中,Fitbit 衍生的预测因子通常比自我报告的预测因子更能预测 BMI。例如,每周 Fitbit 测量的剧烈活动增加一小时与 BMI 降低近一个点相关(-0.84kg/m,95%CI-1.35 至-0.32),而 IPAQ 测量的自我报告剧烈活动与 BMI 的关联强度要小得多(-0.17kg/m,95%CI-0.34 至-0.00;P<.001 与 Fitbit),并且在单一调整后的多变量模型中,与 Fitbit 衍生的预测因子相比,该关联主要由 Fitbit 衍生的预测因子主导。在对 BMI 的关联模式中,Fitbit 对自我报告的影响更大,这在中度活动、剧烈活动和总活动时间的比较中以及在标准化量表上 Fitbit 每天的总步数与 IPAQ MET-h/wk 的比较中均可见到。

结论

与自我报告的身体活动相比,Fitbit 测量的身体活动与 BMI 的相关性更强,尤其是对于中度活动、剧烈活动和总活动的综合测量。市售的可穿戴活动追踪器,如 Fitbit,可能在临床实践和研究中用于测量与健康相关的身体活动。

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