Tobacco Use Trajectories and Associated Changes in Biometrics and Sleep During the First 72 Weeks of Wearable Membership: Observational Cohort Study.

IF 6.3 2区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Dylan J Curran, Josh Leota, William von Hippel, Finnbarr Fielding, Christopher J Chapman, Jenna G Cohen, David M Presby, Reha Jhunjhunwala, Kristen E Holmes, Gregory J Grosicki
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引用次数: 0

Abstract

Background: 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.

Objective: 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.

Methods: 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.

Results: 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 -28.4 to -27.4). 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 -1.58 to -0.26). 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 -3.59 to -3.49), RR was 0.19 breaths/minute higher (95% CI 0.19-0.20), and sleep duration was 9.78 minutes shorter (95% CI -10.08 to -9.49) 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).

Conclusions: 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.

烟草使用轨迹和生物特征与睡眠的相关变化在可穿戴会员的前72周:观察队列研究。
背景:烟草使用仍然是发病和死亡的主要可预防原因。数字健康工具和可穿戴技术为行为自我监测提供了可扩展的机会。然而,在采用可穿戴设备期间,表征长期烟草使用轨迹和相关生理变化的真实证据是有限的。目的:描述可穿戴设备使用前72周内自我报告烟草使用的纵向轨迹,并检查烟草使用与可穿戴设备衍生的心肺和睡眠测量之间的关系。方法:我们分析了12,678名新可穿戴成员(18-79岁)的数据,他们提供了长达72周的每日自我报告烟草使用情况和可穿戴设备衍生的生物识别数据。使用广义线性混合效应模型,在预先指定的12周季度(Q1-Q6)中检查了烟草使用的纵向轨迹。使用线性混合效应模型评估烟草使用与夜间静息心率(RHR)、心率变异性(HRV)、呼吸率(RR)和睡眠时间之间的关系,该模型考虑了人体内和人之间的差异,并根据人口统计学和时间协变量进行了调整。结果:在3,765,573人/天中,估计每天使用烟草的概率从第一季度的55.1% (95% CI: 53.8, 56.4)下降到第六季度的27.2% (95% CI: 26.1, 28.3),绝对减少了27.9个百分点(95% CI: -28.4, -27.4)。在随访结束数据的烟草使用者中,28.2%(4975人中的1404人)报告在第6季度不使用烟草。更多的伐木参与与烟草使用的更大减少有关;从第一季度到第6季度,用户粘性每增加10个百分点,就意味着下降0.92个百分点(95% CI: -1.58, -0.26)。吸烟后,与不吸烟日相比,RHR升高1.71 bpm (95% CI: 1.70, 1.73), HRV降低3.54 ms (95% CI: -3.59, -3.49), RR升高0.19次/分钟(95% CI: 0.19, 0.20),睡眠时间缩短9.78分钟(95% CI: -10.08, -9.49)。随着时间的推移,烟草使用的减少与RHR、RR和睡眠时间的方向有利变化相关(p≤0.03)。结论:在这项针对可穿戴设备用户的大规模观察性现实研究中,在采用可穿戴设备的前72周内,吸烟的可能性有所下降。在随访结束数据的参与者中,超过四分之一的人报告在第六季度没有吸烟。烟草使用始终与较不利的心肺和睡眠指标相关,而随着时间的推移,烟草使用的减少与这些指标的方向性有利变化同时发生,尽管这些变化也可能反映了更广泛的生活方式或健康变化。这些发现提供了大规模的纵向证据,表明在数字自我监测环境中,烟草使用的持续减少与生理指标的可测量的有利变化同时发生。由于这些发现来自单一的商业生态系统,因此需要在非商业、多平台环境中独立复制,以建立普遍性。临床试验:
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
JMIR mHealth and uHealth
JMIR mHealth and uHealth Medicine-Health Informatics
CiteScore
12.60
自引率
4.00%
发文量
159
审稿时长
10 weeks
期刊介绍: JMIR mHealth and uHealth (JMU, ISSN 2291-5222) is a spin-off journal of JMIR, the leading eHealth journal (Impact Factor 2016: 5.175). JMIR mHealth and uHealth is indexed in PubMed, PubMed Central, and Science Citation Index Expanded (SCIE), and in June 2017 received a stunning inaugural Impact Factor of 4.636. The journal focusses on health and biomedical applications in mobile and tablet computing, pervasive and ubiquitous computing, wearable computing and domotics. JMIR mHealth and uHealth publishes since 2013 and was the first mhealth journal in Pubmed. It publishes even faster and has a broader scope with including papers which are more technical or more formative/developmental than what would be published in the Journal of Medical Internet Research.
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