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DOI 10.1155/da/2617282

Медицинская библиотека · Depression and anxiety · 2025

Rest-Activity Rhythm Patterns and Their Associations With Depression and Obesity: A Study Using Actigraphy and Human-Smartphone Interactions.

Chen I-Ming, Lin Chen, She Guan-Jie, Chang Hsiang-Chih, Chuang Hai-Hua, Chen Tien-Yu, Lin Yu-Hsuan

СтатьяПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

Background

This study aimed to empirically derive subgroups based on both actigraphy- and app-measured rest-activity rhythm (RAR) patterns and investigate the relationship between these profiles and health outcomes, including depression and obesity.

Methods

We developed a mobile app, Rhythm, to record human-smartphone interactions and calculate RAR patterns alongside standard actigraphy in 135 participants (mean age: 43.8 ± 12.3 years, 64% women) with and without major depressive disorder and/or obesity. Wrist actigraphy and Rhythm app recorded activity data for at least 4 weeks, totaling 3978 person-days. Person-centered clustering was conducted to identify subgroups based on RAR characteristics, and their associations with clinical outcomes were evaluated using multivariable regression models.

Results

Three distinct groups with different RAR patterns were identified based on acrophase, interdaily stability (IS), and intradaily variability (IV), measured by actigraphy and human-smartphone interactions, respectively. The "earlier" group exhibited earlier acrophase both by actigraphy and the app and had lower depressive symptom severity than the other two groups. The "later" group showed a later acrophase and a lower body mass index (BMI) compared to the "earlier" group. The "irregular" group, characterized by higher IV, lower IS, and desynchronized actigraphy- and app-measured acrophase, was associated with higher levels of depressive symptom severity and BMI.

Conclusions

Our study highlights the usefulness of human-smartphone interaction patterns in providing a comprehensive understanding of individuals' circadian rhythms beyond standard actigraphy measurements. Identifying distinct RAR profiles based on both actigraphy and app measurements contributes to a better understanding of the associations between circadian disruptions and mental and physical health outcomes.

Для цитирования: Chen I-Ming, Lin Chen, She Guan-Jie, Chang Hsiang-Chih, Chuang Hai-Hua, Chen Tien-Yu, Lin Yu-Hsuan. Rest-Activity Rhythm Patterns and Their Associations With Depression and Obesity: A Study Using Actigraphy and Human-Smartphone Interactions.. Depression and anxiety. 2025. DOI: 10.1155/da/2617282.

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