Physical activity phenotypes in endometriosis using unsupervised learning via functional mixture models.

ABSTRACT:

Background

Endometriosis is a chronic condition associated with severe pelvic pain, dysmenorrhea, infertility, and worsening quality of life. Regular physical activity (PA) is effective for pain management and reducing chronic disease symptoms, yet individuals with endometriosis are more likely to be insufficiently active. This study investigated latent profiles of daily PA trajectories in this population via clustering.

Methods

We analyzed 171 adults (4,795 person-level days) with a confirmed diagnosis of endometriosis enrolled in the All of Us Research Program. PA data were collected from participants using Fitbit wrist-worn trackers. We used 30 consecutive days of data from each individual, allowing up to 10 days of missingness, imputed using multiple imputed chained equa

SUBMITTER: Tricoche BT 

PROVIDER: S-EPMC12802236 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature