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1. 重庆市南岸区疾病预防控制中心
2. 重庆医科大学公共卫生与管理学院
纸质出版日期:2022,
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陶杨, 张勇, 钟韵, 等. 基于智能穿戴设备和互联网络的社区慢病管理在社区高血压病人健康管理中的应用效果[J]. 保健医学研究与实践, 2022,19(4):134-137.
Tao Yang, Zhang Yong, Zhong Yun, et al. E ffects of community-based chronic disease management based on smart wearable devices and the Internet in the health management of hypertensive patients in the community[J]. Health Medicine Research and Practice, 2022,19(4):134-137.
陶杨, 张勇, 钟韵, 等. 基于智能穿戴设备和互联网络的社区慢病管理在社区高血压病人健康管理中的应用效果[J]. 保健医学研究与实践, 2022,19(4):134-137. DOI:
Tao Yang, Zhang Yong, Zhong Yun, et al. E ffects of community-based chronic disease management based on smart wearable devices and the Internet in the health management of hypertensive patients in the community[J]. Health Medicine Research and Practice, 2022,19(4):134-137. DOI:
目的 探讨基于智能穿戴设备和互联网络的社区慢病管理在社区高血压病人健康管理中的应用效果。方法 采用多级整群抽样方法于2018年7月—2019年7月从重庆市南岸区6个社区选取研究对象。每个社区选取符合条件的受试者50人
采用随机数字表法将研究对象分为对照组和干预组
各150人。对照组研究对象采用符合国家现行规定和要求的常规高血压慢病管理。干预组研究对象采用基于智能穿戴设备和互联网络的社区慢病管理。采用自制的问卷收集研究对象的相关资料
其中问卷中体成分(体成分包括体质量、肌肉量、内脏脂肪等级、骨量、体脂率、体内水分、身体得分)和血压在干预前后均需要采集
其他资料均在干预后采集。结果 经过6个月的干预
干预组完成随访的有99人
对照组完成随访的有102人。2组研究对象的失访率比较
差异无统计学意义(P>0.05)。2组研究对象年龄、身高、文化程度等一般资料比较
差异均有统计学意义(P<0.05)。2组研究对象体质量、体质指数等均高于干预前
差异有统计学意义(P<0.05)。采用倍差法回归分析干预对体质量、血压和体成分的净效应
结果显示相对于对照组
干预组的净效应是明显减少身体内脏脂肪等级评分(P<0.05)。同时也可以看到干预在改变2组研究对象体质量、血压、肌肉量、骨量、体脂率和身体得分上的净效应没有统计学意义(P>0.05)。结论 基于智能穿戴设备和互联网络的社区慢病管理方式对高血压的控制有辅助作用
尤其是改变高血压患者的内脏脂肪等级评分
后续还应开展深入研究
以明确其长期效果和成本效益。
Objective To explore the effects of community-based chronic disease management based on smart wearable devices and the Internet in the health management of hypertensive patients in the community. Methods The multistage cluster sampling method was used to enroll study subjects from six communities in Nan’an District
Chongqing
from July 2018 to July 2019. Fifty eligible subjects were selected from each community
and the random number table method was used to divide the study subjects into a control group and an intervention group
150 cases each. The subjects in the control group were subjected to conventional hypertension chronic disease management in accordance with the current national regulations and requirements. The subjects in the intervention group received community-based chronic disease management based on smart wearable devices and the Internet. A self-made questionnaire was used to collect relevant information from the study subjects. Data for body composition(body composition including body mass
muscle mass
visceral fat index
bone mass
body fat percentage
body water
and body score) and blood pressure were collected before and after the intervention
and all other information was collected after the intervention. Results After 6 months of intervention
99 subjects in the intervention group completed follow-up and 102 subjects in the control group completed follow-up. The difference between the two groups in this regard was not statistically significant(P>0.05). The difference between the two groups was statistically significant(P<0.05) when comparing general information like age
height
and education level. The body mass and body mass index of subjects in both groups were higher than those before the intervention
and the differences were statistically significant(P<0.05). The net effect of the intervention on body mass
blood pressure
and body composition was analyzed using double-difference regression
and the results showed that the net effect in the intervention group was a significant reduction in body visceral fat index scores compared to the control group(P<0.05). It was also seen that the net effect of the intervention in changing body mass
blood pressure
muscle mass
bone mass
body fat percentage and body score in the 2 study groups was not statistically significant(P>0.05). Conclusion The community-based chronic disease management approach based on smart wearable devices and the Internet has an adjunctive effect on hypertension control
especially in changing visceral fat index scores in hypertensive patients
and in-depth studies should be conducted in the future to clarify its long-term effects and cost-benefit ratio.
移动医疗高血压身体成分慢病管理
MhealthhypertensionBody compositionChronic disease management
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