Depressive Symptom Trajectory is Associated With Smartwatch Step Counts: the Electronic Framingham Heart Study (Preprint)

Author:

Wang XuzhiORCID,Pathiravasan Chathurangi H.ORCID,Zhang Yuankai,Trinquart Ludovic,Borrelli BelindaORCID,Spartano Nicole L.ORCID,Lin Honghuang,Nowak ChristopherORCID,Kheterpal VikORCID,Benjamin Emelia J.ORCID,McManus David D.,Murabito Joanne M.ORCID,Liu Chunyu

Abstract

BACKGROUND

Few studies examined the association between depressive symptom trajectories and objectively measured physical activity.

OBJECTIVE

We aimed to investigate if antecedent depressive symptoms predict subsequent daily step counts among participants in the electronic Framingham Heart Study (eFHS).

METHODS

We performed group-based multi-trajectory modeling to construct depressive symptom trajectory groups using both depressive symptoms (CES-D >16) and antidepressant use in eFHS participants who attended three FHS research exams over fourteen years. At the third exam, eFHS participants were provided with a study smartwatch for measuring daily step counts. We performed linear mixed models to examine the association between depressive symptom trajectories and daily step counts over one-year follow-up adjusting for age, sex, wear-hour, body mass index, and smoking status.

RESULTS

We identified two depressive symptom trajectory groups from 724 eFHS participants (mean age 53 years, 60% women). The low symptom group (n=566; mean follow-up 286±111 days) consisted of ≤5% of participants with depressive symptoms and ≤1% reporting antidepressant medication use, and the high symptom group (n = 158; 269±113 days) consisted of ≥28% of participants with depressive symptoms and ≥47% reporting antidepressant medication use across the three exams. Compared to those in the low symptom group, participants in the high symptom group walked fewer daily steps during one-year follow-up (690 fewer; 95% CI: 254-1125).

CONCLUSIONS

Antecedent depressive symptoms/anti-depressive medication use was associated with lower subsequent daily step counts in eFHS. Our findings suggest that adding interventions to improve mood via mHealth technologies may help promote people’s daily physical activity.

Publisher

JMIR Publications Inc.

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