{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T20:31:38Z","timestamp":1791232298631,"version":"4.1.0"},"reference-count":40,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Mhealth Uhealth"],"abstract":"\n Background<\/jats:title>\n Tobacco use remains a leading preventable cause of morbidity and mortality. Digital health tools and wearable technologies offer scalable opportunities for behavioral self-monitoring. However, real-world evidence characterizing long-term tobacco use trajectories and associated physiological changes during wearable adoption is limited.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n This study aims to characterize longitudinal trajectories of self-reported tobacco use during the first 72 weeks of wearable adoption and to examine associations between tobacco use and wearable-derived cardiopulmonary and sleep measures.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n We analyzed data from 12,678 new wearable members (18-79 years) who contributed up to 72 weeks of daily self-reported tobacco use and wearable-derived biometric data. Longitudinal trajectories of tobacco use were examined across prespecified 12-week quarters (Q1-Q6) using generalized linear mixed-effects models. Associations between tobacco use and wearable-derived nocturnal resting heart rate (RHR), heart rate variability (HRV), respiratory rate (RR), and sleep duration were evaluated using linear mixed-effects models that accounted for within- and between-person variation and adjusted for demographic and temporal covariates.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n Across 3,765,573 person-days, the estimated daily probability of tobacco use declined from 55.1% (95% CI 53.8-56.4) during Q1 to 27.2% (95% CI 26.1-28.3) during Q6, representing an absolute reduction of 27.9 percentage points (95% CI \u201328.4 to \u201327.4). Among tobacco users with end-of-follow-up data, over one-quarter (1404\/4975, 28.22%) reported no tobacco use during Q6. Greater logging engagement was associated with larger reductions in tobacco use; each 10-percentage-point increase in engagement corresponded to a 0.92-percentage-point greater decline from Q1 to Q6 (95% CI \u20131.58 to \u20130.26). Following tobacco use days, RHR was 1.71 beats\/minute higher (95% CI 1.70-1.73), HRV was 3.54 ms lower (95% CI \u20133.59 to \u20133.49), RR was 0.19 breaths\/minute higher (95% CI 0.19-0.20), and sleep duration was 9.78 minutes shorter (95% CI \u201310.08 to \u20139.49) relative to nonuse days. Reductions in tobacco use over time were associated with directionally favorable changes in RHR (P=.001), RR (P=.002), and sleep duration (P=.02).<\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n In this large-scale, observational, real-world study of wearable users, the probability of tobacco use declined over the first 72 weeks of adoption. Among participants with end-of-follow-up data, more than one-quarter reported no tobacco use during Q6. Tobacco use was consistently associated with less favorable cardiopulmonary and sleep measures, while reductions in tobacco use over time co-occurred with directionally favorable changes in these measures, although such changes may also reflect broader lifestyle or health changes. Overall, this study provides large-scale, longitudinal evidence that sustained reductions in tobacco use co-occur with favorable changes in physiological markers within a digital self-monitoring environment. As the findings derive from a single commercial ecosystem, independent replication in noncommercial, multiplatform settings will be needed to establish generalizability.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/98116","type":"journal-article","created":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T18:25:06Z","timestamp":1782239106000},"page":"e98116","source":"Crossref","is-referenced-by-count":3,"title":["Tobacco Use Trajectories and Associated Changes in Biometrics and Sleep During the First 72 Weeks of Wearable Membership: Observational Cohort Study"],"prefix":"10.2196","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-9809-8815","authenticated-orcid":false,"given":"Dylan 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