Prediction of Incident Depression in Middle-Aged and Older Adults using Digital Gait Biomarkers Extracted from Large-Scale Wrist Sensor Data

被引:9
作者
Chan, Lloyd L. Y. [1 ,2 ]
Brodie, Matthew A. [1 ,3 ]
Lord, Stephen R. [1 ,2 ,4 ]
机构
[1] Neurosci Res Australia, Sydney, Australia
[2] Univ New South Wales, Sch Populat Hlth, Sydney, Australia
[3] Univ New South Wales, Grad Sch Biomed Engn, Sydney, Australia
[4] Neurosci Res Australia, 139 Baker St, Randwick, NSW 2031, Australia
关键词
Smartwatch; wearable electronic device; walking; gait analysis; free-living daily walking; LATE-LIFE DEPRESSION; C-REACTIVE PROTEIN; PHYSICAL-ACTIVITY; INTERLEUKIN-6; RISK; SYMPTOMS;
D O I
10.1016/j.jamda.2023.04.008
中图分类号
R592 [老年病学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 100203 ;
摘要
Objectives: To determine if digital gait biomarkers captured by a wrist-worn device can predict the incidence of depressive episodes in middle-age and older people.Design: Longitudinal cohort study. Setting and Participants: A total of 72,359 participants recruited in the United Kingdom.Methods: Participants were assessed at baseline on gait quantity, speed, intensity, quality, walk length distribution, and walk-related arm movement proportions using wrist-worn accelerometers for up to 7 days. Univariable and multivariable Cox proportional-hazard regression models were used to analyze the associations between these parameters and diagnosed incident depressive episodes for up to 9 years.Results: A total of 1332 participants (1.8%) had incident depressive episodes over a mean of 7.4 & PLUSMN; 1.1 years. All gait variables, except some walk-related arm movement proportions, were significantly associated with the incidence of depressive episodes (P < .05). After adjusting for sociodemographic, lifestyle, and comorbidity covariates; daily running duration, steps per day, and step regularity were identified as independent and significant predictors (P < .001). These associations held consistent in subgroup analysis of older people and individuals with serious medical conditions. Conclusions and Implications: The study findings indicate digital gait quality and quantity biomarkers derived from wrist-worn sensors are important predictors of incident depression in middle-aged and older people. These gait biomarkers may facilitate screening programs for at-risk individuals and the early implementation of preventive measures.& COPY; 2023 AMDA -The Society for Post-Acute and Long-Term Care Medicine.
引用
收藏
页码:1106 / 1113.e11
页数:19
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