| 基于贵州省人群队列的代谢综合征发病风险和影响因素分析 |
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| 引用本文： | 张骥,周婕,吴延莉,王艺颖,李雪娇,龙梦雅,林深荣,刘涛.基于贵州省人群队列的代谢综合征发病风险和影响因素分析[J].现代预防医学,2022,0(6):975-980. |
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| 作者姓名： | 张骥 周婕 吴延莉 王艺颖 李雪娇 龙梦雅 林深荣 刘涛 |
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| 作者单位： | 1.贵州省疾病预防控制中心，贵州 贵阳 550004；2.贵州医科大学公共卫生与健康学院，环境污染与疾病监控教育部重点实验室，贵州 贵阳 550025；3.贵州大学医学院，贵州 贵阳 550025 |
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| 摘 要： | 目的 探讨代谢综合征（MS）的发病风险和影响因素，为预防MS提供科学依据。方法 采取多阶段整群抽样方法，于2010年建立贵州省人群队列，排除基线MS患者后，共有7 136人进入MS随访队列，收集队列人群基线社会人口学信息、生活行为方式和生理指标，并于2016—2020年进行随访，最终纳入4 754人进行分析。采用COX比例风险模型分析MS的发病风险及其影响因素的HR（95% CI），并计算影响因素的人群归因危险度（PAF%）。同时根据基线人群的MS组分得分建立亚队列，分析亚队列人群MS的影响因素。结果 队列人群累计随访33 424.18人年，中位随访6.57年，新发MS 963人，MS发病密度为28.81/1 000人年。COX回归分析结果显示:年龄45～59岁（HR = 1.53，95%CI:1.32～1.77）、年龄≥60岁（HR = 1.53，95%CI:1.27～1.86）、城市（HR = 1.71，95%CI:1.47～1.99）、吸烟（HR = 1.22，95%CI:1.01～1.48）、每日油摄入＞30 g（HR = 1.16，95%CI:1.01～1.34）、每日盐摄＞6 g（HR = 1.22，95%CI:1.05～1.42）、静态时间≥4 h/d（HR = 1.16，95%CI:1.02～1.32）、超重（HR = 1.66，95%CI:1.44～1.92）、肥胖（HR = 2.27，95%CI:1.71～3.02）、静息心率70～80次/min（HR = 1.32，95%CI:1.11～1.58）和 ＞80次/min（HR = 1.28，95%CI:1.07～1.54)是MS的危险因素，其PAF%分别为17.47%、11.32%、19.52%、5.89%、11.33%、13.66%、7.01%、12.91%、5.30%、17.68%、13.92%，文化程度升高（HR = 0.75，95%CI:0.68～0.83）和饮茶行为（HR = 0.82，95%CI:0.71～0.95）是MS的保护因素，其PAF%分别为16.21%和6.97%。亚队列研究结果与总体结果相似。结论 不健康的生活方式和超重、肥胖、静息心率升高是MS的影响因素，应将中老年人和城市居民作为预防MS的重点人群，采取相应措施控制烟草消费、油盐摄入，维持正常体重和适当心率，提高人群知识水平，保持饮茶行为，预防MS发生。
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| 关 键 词： | 代谢综合征 队列 发病风险 影响因素 |
The risk and influencing factors for metabolic syndrome based on population cohort in Guizhou Province |
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| ZHANG Ji,ZHOU Jie,WU Yan-li,WANG Yi-ying,LI Xue-jiao,LONG Meng-ya,LIN Seng-rong,LIU Tao.The risk and influencing factors for metabolic syndrome based on population cohort in Guizhou Province[J].Modern Preventive Medicine,2022,0(6):975-980. |
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| Authors: | ZHANG Ji ZHOU Jie WU Yan-li WANG Yi-ying LI Xue-jiao LONG Meng-ya LIN Seng-rong LIU Tao |
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| Affiliation: | *Guizhou Center for Disease Control and Prevention, Guiyang, Guizhou 550004, China |
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| Abstract: | Objective To explore the risk and influencing factors for metabolic syndrome (MS), so as to provide references for the prevention and control of MS. Methods A multi-stage whole-group sampling method was used to establish a population cohort in Guizhou Province in 2010. After excluding baseline MS patients, a total of 7 136 people were entered into the MS follow-up cohort, and baseline sociodemographic information, lifestyle and physiological indicators were collected from the cohort population and followed up from 2016 to 2020. A total of 4 754 people were finally included for analysis. The COX proportional risk model was used to analyze the HR (95%CI) for the risk of developing MS and its influencing factors, and the population-attributable risk for influencing factors (PAF%) was calculated. A subcohort was also established based on the MS component scores of the baseline population, and the influencing factors of MS in the subcohort population were analyzed. Results The cohort population had a cumulative follow-up of 33 424.18 person-years, with a median follow-up of 6.57 years, 963 new MS, and MS incidence density of 28.81/1 000 person-years. COX regression analysis showed that age 45 to 59 years (HR=1.53, 95%CI: 1.32-1.77), age ≥60 years (HR=1.53, 95%CI: 1.27-1.86), urban (HR=1.71, 95%CI: 1.47-1.99), smoking (HR=1.22, 95%CI: 1.01-1.48), oil intake >30 g per day (HR=1.16, 95%CI: 1.01-1.34), salt intake >6 g per day (HR=1.22, 95%CI: 1.05-1.42), resting time ≥4 h/d (HR=1.16, 95%CI: 1.02-1.32), overweight (HR=1.66, 95%CI: 1.44-1.92), obese (HR=2.27, 95%CI: 1.71-3.02), resting heart rate 70-80 beats/min (HR=1.32, 95%CI: 1.11-1.58) and >80 beats/min (HR=1.28, 95%CI: 1.07-1.54) were risk factors for MS with PAF% of 17.47%, 11.32%, 19.52%, 5.89%, 11.33%, 13.66%, 7.01%, 12.91%, 5.30%, 17.68%, and 13.92%, and elevated literacy (HR=0.75, 95%CI: 0.68-0.83) and tea drinking behavior (HR=0.82, 95%CI: 0.7-0.95) were protective factors for MS with PAF% of 16.21% and 6.97%, respectively. The results of the subcohort study were similar to the overall results. Conclusion Unhealthy lifestyle and overweight, obesity, and elevated resting heart rate are influencing factors of MS. Middle-aged and elderly people and urban residents should be considered as the key population for MS prevention, and appropriate measures should be taken to control tobacco consumption, oil and salt intake, maintain normal body weight and appropriate heart rate, improve the knowledge level of the population, and maintain tea drinking behavior to prevent the occurrence of MS. |
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| Keywords: | Metabolic syndrome Cohort Risk Influencing factors |
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