热适应行为对老年人静息心率对夏季温度反应的影响:一项可穿戴设备面板研究

IF 6.2 2区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Chi-Hsien Chen, Feipei Lai, Yu-Lin Chen, Yue Leon Guo
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引用次数: 0

摘要

背景:夏季高温对老年人健康的影响日益受到公众关注,但其生理反应,特别是静息心率(RHR)的变化,以及个人热适应行为的作用仍未得到充分探讨。可穿戴设备为客观监测生理反应和评估现实环境中适应策略的有效性提供了机会。目的:本研究旨在量化夏季温度与老年人RHR之间的短期关联,并在考虑年龄、性别、体重指数(BMI)和慢性疾病状态等个人特征的情况下,研究个体热适应行为如何改变这种关系。方法:我们于2021年夏季(5 - 9月)对台北市83名≥65岁的社区老年人进行了一项面板研究。参与者佩戴Garmin®智能手表,持续监测心率。每日RHR被定义为最低的30分钟平均心率。9月,通过结构化电话访谈对热适应行为进行评估。环境温度和相对湿度由附近的监测站获得。线性混合效应模型用于估计温度与rhr的关联,并包括相互作用项来检查行为改变。进行亚组分析,探讨年龄、性别、体重指数(BMI)和慢性疾病状况等个体特征对疗效的影响。结果:在滞后0-1天内,日平均温度每升高1°C, RHR增加0.11次/分钟(95% CI 0.07-0.15);结论:夏季高温与老年人RHR升高有关,但这种影响可以通过有针对性的热适应行为来缓解。智能手表监测为捕捉生理变化提供了一种可行且信息丰富的方法,支持在气候变暖的情况下为老年人提供个性化的热健康建议。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。
Effects of heat adaptation behaviors on resting heart rate response to summer temperatures in the elderly: a wearable device panel study.

Background: The health impact of summer heat on older adults is a growing public concern, yet the physiological responses, particularly changes in resting heart rate (RHR), and the role of personal heat adaptation behaviors remain underexplored. Wearable devices offer an opportunity to objectively monitor physiological responses and evaluate the effectiveness of adaptation strategies in real-world settings.

Objective: This study aimed to quantify the short-term association between summer temperatures and RHR in older adults and to examine how individual heat adaptation behaviors modify this relationship, with additional consideration of personal characteristics such as age, sex, body mass index (BMI), and chronic disease status.

Methods: We conducted a panel study among 83 community-dwelling older adults (≥65 years) in Taipei City during the summer of 2021 (May to September). Participants wore Garmin® smartwatches to continuously monitor heart rate. Daily RHR was defined as the lowest 30-minute average heart rate. In September, heat adaptation behaviors were assessed via structured telephone interviews. Ambient temperature and relative humidity were obtained from a nearby monitoring station. Linear mixed-effect models were used to estimate temperature-RHR associations, and interaction terms were included to examine behavioral modifications. Subgroup analyses were conducted to explore effect modification by individual characteristics such as age, sex, body mass index (BMI), and chronic disease status.

Results: Each 1°C increase in daily mean temperature over lag days 0-1 was associated with a 0.11 beats/min increase in RHR (95% CI 0.07-0.15; P<.0001). After mutual adjustment for behaviors, several heat adaptation strategies showed significant protective effects, including reducing physical activity (β=-0.15, P=.001), drinking cold beverages (β=-0.24, P<.0001), increasing naps or sleep duration (β=-0.28, P=.003), drinking additional water ≥500mL (β=-0.10, P=.023), using air conditioning before (β=-0.15, P=.002) and during sleep (β=-0.13, P=.007), and using electric fans during sleep (β=-0.12, P=.012). Subgroup analyses revealed stronger effects for certain behaviors in vulnerable populations: reduced physical activity was particularly beneficial for those with higher BMI; air conditioning use and cold beverage intake were more effective in diabetics; increased naps yielded the largest benefits in hypertensive individuals; and the use of air conditioning or fans during sleep was especially protective for older adults and females.

Conclusions: Summer heat is associated with elevated RHR in the elderly, but this effect can be mitigated through targeted heat adaptation behaviors. Smartwatch monitoring provides a feasible and informative approach for capturing physiological changes, supporting the development of personalized heat-health recommendations for aging populations in a warming climate.

Clinicaltrial:

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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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