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1990―2019年中国慢性肾病发病趋势及预测

孙科 倪帅虎 郑卿勇 罗小峰

孙科, 倪帅虎, 郑卿勇, 罗小峰. 1990―2019年中国慢性肾病发病趋势及预测[J]. 中华疾病控制杂志, 2024, 28(3): 262-268. doi: 10.16462/j.cnki.zhjbkz.2024.03.003
引用本文: 孙科, 倪帅虎, 郑卿勇, 罗小峰. 1990―2019年中国慢性肾病发病趋势及预测[J]. 中华疾病控制杂志, 2024, 28(3): 262-268. doi: 10.16462/j.cnki.zhjbkz.2024.03.003
SUN Ke, NI Shuaihu, ZHENG Qingyong, LUO Xiaofeng. Study on the trend and forecast of the incidence of chronic kidney disease in China from 1990 to 2019[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2024, 28(3): 262-268. doi: 10.16462/j.cnki.zhjbkz.2024.03.003
Citation: SUN Ke, NI Shuaihu, ZHENG Qingyong, LUO Xiaofeng. Study on the trend and forecast of the incidence of chronic kidney disease in China from 1990 to 2019[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2024, 28(3): 262-268. doi: 10.16462/j.cnki.zhjbkz.2024.03.003

1990―2019年中国慢性肾病发病趋势及预测

doi: 10.16462/j.cnki.zhjbkz.2024.03.003
孙科和倪帅虎为共同第一作者
基金项目: 

兰州大学医学教育创新发展项目 lzuyxcx-2022-23

兰州大学医学教育创新发展项目 lzuyxcx-2022-220

详细信息
    通讯作者:

    罗小峰,E-mail: luoxiaof@lzu.edu.cn

  • 中图分类号: R692;R81

Study on the trend and forecast of the incidence of chronic kidney disease in China from 1990 to 2019

SUN Ke and NI Shuaihu contributed equally to this article
Funds: 

Medical Innovation and Development Project of Lanzhou University lzuyxcx-2022-23

Medical Innovation and Development Project of Lanzhou University lzuyxcx-2022-220

More Information
  • 摘要:   目的  了解各地区人口死因现状,研究各疾病死因的变化趋势,为卫生资源合理利用提供可靠依据。  方法  对比2010、2015、2020年东、中、西部地区死因顺位,编制全死因寿命表以及去死因寿命表。计算死亡率、年龄标化死亡率和减寿率等指标,并采用第七次全国人口普查数据进行标化。  结果  各地区死亡率呈上升趋势,西部地区年龄标化死亡率最高,各地区期望寿命年均增长0.32、0.34和0.31岁。恶性肿瘤、脑血管病、心脏病、呼吸系统疾病和伤害是各地区死因前5位。恶性肿瘤是东部地区死因首位,而脑血管病是中部地区的死因首位。心脏病寿命损失率在各地区都呈上升趋势,2020年中部地区≥85岁年龄组心脏病寿命损失率已达49.50%;呼吸系统导致的寿命损失率逐年降低,但随年龄的增长呈上升趋势,且对西部地区的寿命影响最大;伤害导致的寿命损失率在≥75岁年龄组呈上升趋势。  结论  各地区人口期望寿命逐步增加,但心血管病导致的寿命损失率在持续升高,且伤害对老年人群的寿命影响也在不断增加。不同疾病对不同地区寿命影响程度存在差异,应根据不同年龄、地区的老年人制定有针对性地疾病防治策略。
  • 图  1  1990―2019年中国不同性别慢性肾病粗发病率(A)、标化发病率(B)和发病人数(C)

    Figure  1.  Crude incidence rate (A), standardized incidence rate (B) and incidence number (C) of chronic kidney disease in China from 1990 to 2019

    图  2  1990―2019年中国慢性肾病发病率年龄-时期-队列模型分析: 纵向年龄曲线(A)、局部漂移和全局漂移(B)、时期相对风险(C)、队列相对风险(D)

    Figure  2.  Analysis of the age-period-cohort model of chronic kidney disease incidence in China from 1990 to 2019: longitudinal age curve (A), local drift and global drift (B), relative risk of period (C) and relative risk of cohort (D)

    图  3  2020―2034年中国慢性肾病男性发病率预测(A)、女性发病率预测(B)、发病人数预测(C)

    BAPC: 贝叶斯-时期-队列分析。

    Figure  3.  Prediction of male incidence (A), female incidence (B) and incidence number (C) of chronic kidney disease in China from 2020 to 2034

    BAPC: Bayesian age-period-cohort analysis.

    表  1  1990―2019年中国慢性肾病发病率年龄-时期-队列模型检验

    Table  1.   Age-period-cohort model test of incidence of chronic kidney disease in China from 1990 to 2019

    零假设Null hypothesis 全人群Population 男性Male 女性Female
    χ2
    value
    P
    value
    χ2
    value
    P
    value
    χ2
    value
    P
    value
    全局变化Net drift=0 389.72 < 0.001 444.96 < 0.001 267.38 < 0.001
    总年龄偏差All age deviations=0 69 161.84 < 0.001 99 741.01 < 0.001 44 963.84 < 0.001
    总时期偏差All period deviations=0 365.64 < 0.001 440.41 < 0.001 272.43 < 0.001
    总队列偏差All cohort deviations=0 588.17 < 0.001 621.60 < 0.001 505.92 < 0.001
    全时期RR值All period RR value=1 818.31 < 0.001 940.34 < 0.001 589.10 < 0.001
    全队列RR值All period RR value=1 1 907.42 < 0.001 1 981.50 < 0.001 1 575.45 < 0.001
    所有局部变化=全局变化All local drifts=Net drift 586.50 < 0.001 618.81 < 0.001 504.64 < 0.001
    下载: 导出CSV
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  • 收稿日期:  2023-08-24
  • 修回日期:  2024-01-10
  • 网络出版日期:  2024-04-08
  • 刊出日期:  2024-03-10

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