摘要
目的对2020年中国健康与养老追踪调查(China health and retirement longitudinal study,CHARLS)数据库的数据进行分析,探究中国中老年人群血脂异常现状,揭示体力活动与血脂异常患病风险的关系,为中国中老年人群血脂异常相关政策的制定提供依据。方法本研究纳入45~74岁信息完整的研究对象12132名,按照体力活动进行四分位数分组后,采用logistic回归分析模型分析中老年人体力活动与血脂异常患病风险之间的关系,将患有其他慢性病的研究对象排除后进行敏感性分析。结果12132名研究对象中,血脂异常者1187人,检出率为9.78%(95%CI:9.26%~10.31%)。在调整混杂因素后,中老年人高水平体力活动组相较于低水平体力活动组的血脂异常患病风险降低(OR=0.796,95%CI:0.668~0.950),敏感性分析结果一致(OR=0.734,95%CI:0.571~0.944)。结论高水平体力活动可降低中老年人的血脂异常患病风险,提示增强体力活动可作为促进中老年人群心脑血管健康的有利手段。
Objective The 2020 survey data from the China health and retirement longitudinal study(CHARLS)were analyzed to investigate the current status of dyslipidemia among the middle-aged and elderly population in China,and to reveal the relationship between physical activity and the risk of dyslipidemia.It will provide a reference for the formulation of policies related to dyslipidemia in this demographic.Methods This study included 12132 middle-aged and elderly individuals aged 45 to 74 with complete information.Participants were divided into quartile groups based on their level of physical activity.We used a logistic regression model to analyze the relationship between physical activity and the risk of dyslipidemia among the middle-aged and elderly adults,and conducted a sensitivity analysis after excluding participants with other chronic diseases.Results Among the 12132 participants,1187 had dyslipidemia,with a detection rate of 9.78%(95%CI:9.26%-10.31%).After adjusting for confounders,middle-aged and elderly individuals in the high-level physical activity group have a reduced risk of dyslipidemia compared to the low-level physical activity group(OR=0.796,95%CI:0.668-0.950),consistent with the results of the sensitivity analysis(OR=0.734,95%CI:0.571-0.944).Conclusions High-level physical activity can reduce the risk of dyslipidemia in middle-aged and elderly people,so strengthening physical activity can be used as a favorable means to promote cardiovascular and cerebrovascular health in middle-aged and elderly people.
作者
胡佳康
戈琼
赖文浩
罗时文
卢曲琴
HU Jiakang;GE Qiong;LAI Wenhao;LUO Shiwen;LU Quqin(Department of Epidemic and Health Statistics,School of Public Health,Jiangxi Medical College,Nanchang University,Nanchang 330006,China;Jiangxi Provincial Key Laboratory of Disease Prevention and Public Health,Nanchang University,Nanchang 330006,China;Jiangxi Provincial Key Laboratory for Precision Pathology and Intelligent Diagnosis,Center for Experimental Medicine,The First Affiliated Hospital of Nanchang University,Nanchang 330006,China)
出处
《中华疾病控制杂志》
CAS
CSCD
北大核心
2024年第9期1010-1014,1116,共6页
Chinese Journal of Disease Control & Prevention
基金
国家自然科学基金地区项目(32260143)
江西省重点研发计划(20202BBG72003)。