孟诗迪, 刘韫宁, 周脉耕, 殷鹏, 齐金蕾, 刘江美, 由金玲, 林琳, 王黎君. 2009-2019年中国60岁及以上老年人群危险因素归因疾病负担分析[J]. 疾病监测, 2022, 37(9): 1236-1241. DOI: 10.3784/jbjc.202204250177
引用本文: 孟诗迪, 刘韫宁, 周脉耕, 殷鹏, 齐金蕾, 刘江美, 由金玲, 林琳, 王黎君. 2009-2019年中国60岁及以上老年人群危险因素归因疾病负担分析[J]. 疾病监测, 2022, 37(9): 1236-1241. DOI: 10.3784/jbjc.202204250177
Meng Shidi, Liu Yunning, Zhou Maigeng, Yin Peng, Qi Jinlei, Liu Jiangmei, You Jinling, Lin Lin, Wang Lijun. Burden of disease of risk factors for elderly people aged 60 and over in China in 2009 and 2019[J]. Disease Surveillance, 2022, 37(9): 1236-1241. DOI: 10.3784/jbjc.202204250177
Citation: Meng Shidi, Liu Yunning, Zhou Maigeng, Yin Peng, Qi Jinlei, Liu Jiangmei, You Jinling, Lin Lin, Wang Lijun. Burden of disease of risk factors for elderly people aged 60 and over in China in 2009 and 2019[J]. Disease Surveillance, 2022, 37(9): 1236-1241. DOI: 10.3784/jbjc.202204250177

2009-2019年中国60岁及以上老年人群危险因素归因疾病负担分析

Burden of disease of risk factors for elderly people aged 60 and over in China in 2009 and 2019

  • 摘要:
      目的  利用全球疾病负担研究(GBD)2019最新数据分析中国60岁及以上不同性别和不同省份的老年人群危险因素归因疾病负担及变化情况,助力老年人群的病因预防。
      方法  利用GBD2019中国60岁及以上老年人群危险因素的疾病负担数据,以归因伤残调整寿命年(DALY)为指标评估不同危险因素在2009—2019年对中国分省、分性别的老年人群的健康和寿命的影响及变化情况,以2010年第六次人口普查的60岁及以上人口为标准人口计算标化率。
      结果  2019年危险因素合计导致中国60岁及以上老年人群的DALY达11 451.79万人年,占老年人群总DALY的60.19%。 影响我国老年人群健康最主要的危险因素包括烟草、高收缩压、膳食因素、空气污染、高空腹血糖、高体质指数、高低密度脂蛋白胆固醇、肾功能不全、非最适温度和饮酒。 影响老年男性人群健康最主要的危险因素是烟草,而老年女性人群是高收缩压。 2019年膳食因素、高体质指数、肾功能不全和饮酒归因DALY的顺位所有提高,而空气污染、高低密度脂蛋白胆固醇和非最适温度的顺位下降。 与2009年相比,2019年中国各省60岁及以上老年人群归因DALY标化率均下降,下降幅度最大的5个省份分别是福建(27.00%)、广东(25.70%)、天津(24.24%)、浙江(22.96%)和北京(21.47%)。
      结论  2009—2019年中国60岁及以上老年人群的归因疾病负担加重,为实现健康老龄化目标,应通过实施有效的政策和措施,如开展健康教育、改善生活环境、提供健康管理服务等,积极开展病因预防,有针对性地降低烟草、饮酒、膳食因素、空气污染、高体质指数和环境温度等因素对老年人群造成的疾病负担。

     

    Abstract:
      Objective   To analyze the attributable burden of disease and changes of risk factors in the elderly population aged 60 and over in different genders and provinces in China, so as to help the etiological prevention of the elderly population.
      Methods   Using GBD 2019 burden of disease data of risk factors for the elderly aged 60 and over in China, the effects and changes of different risk factors on health and life expectancy of the elderly by province and sex in China from 2009 to 2019 were evaluated with attribution disability-adjusted life years(DALY) as the index, and the standardized rate was calculated with the population aged 60 years old and over in the sixth population census in 2010 as the standard population.
      Results   In 2019, the total number of risk factors led to the DALY of the elderly aged 60 and over in China reached 114.5179 million person years, accounting for 60.19% of the total DALY of the elderly population. The main risk factors affecting the health of the elderly in China include tobacco, high systolic blood pressure, dietary factors, air pollution, high fasting blood glucose, high body mass index, high LDL-C, kidney dysfunction, non-optimal temperature and drinking alcohol. The main risk factor affecting the health of elderly men is tobacco, while elderly women have high systolic blood pressure. In 2019, dietary factors, high body mass index, kidney dysfunction, and drinking alcohol all increased in the order of DALY, while air pollution, high LDL-C and non-optimal temperature decreased in the order of DALY. Compared with 2009, the attributable DALY standardized rate of the elderly aged 60 and over in all provinces of China decreased in 2019. The five provinces with the largest decline were Fujian (27.00%), Guangdong (25.70%), Tianjin (24.24%), Zhejiang (22.96%) and Beijing (21.47%).
      Conclusion   From 2009 to 2019, the attributable disease burden of the elderly aged 60 and over in China increased. In order to achieve the goal of healthy aging, we should actively carry out etiological prevention through the implementation of effective policies and measures, such as health education, improving living environment and providing health management services, so as to reduce the disease burden caused by tobacco, drinking alcohol, dietary factors, air pollution, high body mass index and non-optimal temperature.

     

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