UNSTRUCTURED
Introduction: The interrelationship between physical and social activities plays a crucial role in influencing health outcomes, particularly in populations with obesity and depression. This study aims to develop the "social-physical coherence" method for measuring the alignment between physical and social activities, investigating its association with obesity and depression.
Methods: The research encompassed 135 participants (average age: 43.8±12.3 years; 65.2% female), including individuals with a history of major depression, those with obesity, and health-care professionals participating in a workplace health program. Body Mass Index (BMI) and the Patient Health Questionnaire-9 (PHQ-9) scale were employed to determine obesity and depression levels, respectively. Activity data were collected over a minimum of four weeks using wrist actigraphy devices and the Rhythm app, yielding 3,973 person-days of data. The Rhythm app tracked human-smartphone interactions and computed rest-activity rhythm (RAR) patterns, including interdaily stability (IS), from both standard actigraphy and app-derived data, thus offering two distinct RAR measurements. Social-physical coherence was assessed by combining physical activity data from actigraphy with social activity data derived from human-smartphone interactions.
Results: Findings demonstrated a significant positive correlation between social-physical coherence and IS, particularly significant in app-derived IS (ISapp) over a period of 1-6 weeks. Analysis of the relationship with BMI revealed a significant negative correlation for both social-physical coherence and ISapp within the first 2-4 weeks, whereas no notable correlation was found with actigraphy-based IS (ISact). Regarding depressive symptom scores, a borderline-significant negative correlation was observed with ISact when examining data from the first 1, 3, 4, or 5 weeks (P=.054 to .062). No significant correlation was found between social-physical coherence or ISapp and PHQ-9 scores across all timeframes studied.
Conclusions: This study leveraging digital phenotyping through actigraphy and human-smartphone interactions, reveals an inverse relationship between social-physical coherence and obesity, and a more complex association with depression.