基于 Lifelog 的每日步数,步行速度和新陈代谢健康状态
Ga-Young Lim1,2, Eunkyo Park1,2, Ji-Young Song3
1Center for Cohort Studies, Total Healthcare Center, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Suwon, Republic of Korea.
Digital health
|July 29, 2024
概括
来自生活记录的步行速度,而不仅仅是步数,对于识别代谢不健康的个体至关重要. 这项技术可以帮助早期检测代谢异常.
科学领域:
- 代谢健康 代谢健康
- 身体活动监测 身体活动监测
- 数字健康数字健康
背景情况:
- 代谢健康状态对于预防慢性疾病至关重要.
- 从生活记录中获得的体育活动数据为评估健康状况提供了一种新的方法.
研究的目的:
- 调查生活日志衍生的身体活动与代谢健康状况之间的关联.
- 评估生命记录数据对代谢健康的预测能力.
主要方法:
- 对51名没有慢性疾病的韩国成年人 (30-40岁) 进行横截面研究.
- 身体活动通过国际身体活动问卷-简单表格 (IPAQ-SF) 和来自三星健康的生命记录数据 (步数,步行速度) 进行评估.
- 由缺乏代谢综合征成分决定的代谢健康状态.
主要成果:
- 生命日记衍生的步行速度显示,与代谢不健康状态有显著的反向关联.
- 包括步行速度,年龄和性别在内的模型显示了代谢不健康状态的最高预测能力 (AUC).
- 与传统方法相比,将生命记录数据 (步数和步行速度) 纳入预测代谢不健康状况的预测显著改善.
结论:
- 较慢的生命日记衍生的步行速度与更高的代谢不健康状态的流行率有关.
- 生命日志的体力活动数据,特别是步行速度,可以帮助识别有代谢异常的个体.
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