Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, China.
Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, China
BMJ Open. 2022 Apr 29;12(4):e059395. doi: 10.1136/bmjopen-2021-059395.
Improved national Disease Surveillance Points systems (DSPs) in China have clarified mortality causes in the Chinese population. This study aimed to investigate the variations and drivers of multiple mortality causes.
This was a retrospective cross-sectional surveillance study.
Original data in 1991 and 2000, and secondary data in 2010 and 2019 were collected from DSPs across China.
Standardised mortality rates (SMRs) and crude mortality rates (CMRs) of the Chinese population in 1991, 2000, 2010 and 2019 were ascertained.
Changes in the Gini coefficients (), computed using SMR, were decomposed into reranking () and proportionality () to identify variations in communicable, maternal, neonatal and nutritional diseases (CMNN); non-communicable diseases (NCDs) and injury. The CMR difference (in %) was partitioned into the demographic structure and non-demographic factors using the mortality-rate-difference method.
From 1991 to 2019, the overall CMR increased from 591.327/100 000 to 674.505/100 000, whereas the SMR continually decreased. An increasing concentration of NCDs contributed to the increased all-cause from 0.443 to 0.560 during 1991-2019. Between 1991 and 2019, compared with CMNN (=0.054) and NCDs (=0.037), the ranking of injury changed the most (=0.174). The ranking of diabetes, falls and road traffic accidents increased markedly over time. The decreased SMR of NCDs (=-0.013) was mainly due to low-ranking causes, whereas changes in CMNN (=0.003) and injury (=0.131) were due to high-ranking causes. All-cause CMR increased by 14.06% from 1991 to 2019 due to greater contributions from the demographic structure (68.46%) than the non-demographic factors (-54.40%). Demographic structural changes accounted more for CMR increases in males (70.52%) and urban populations (75.58%).
Prevention and control measures targeting NCDs and specific causes are imperatively needed, and should be strengthened as the population ages, especially for males and rural populations.
中国改进后的全国疾病监测点系统（DSPs）明确了中国人群的死亡原因。本研究旨在调查多种死亡原因的变化和驱动因素。
这是一项回顾性的横断面监测研究。
原始数据来自 1991 年和 2000 年，以及 2010 年和 2019 年中国各地的 DSPs 的二次数据。
确定了 1991 年、2000 年、2010 年和 2019 年中国人口的标准化死亡率（SMR）和粗死亡率（CMR）。
使用 SMR 计算的基尼系数（）的变化被分解为重新排序（）和比例（），以确定传染性疾病、孕产妇、新生儿和营养疾病（CMNN）、非传染性疾病（NCDs）和损伤的变化。使用死亡率差异法，将 CMR 差异（%）划分为人口结构和非人口因素。
1991 年至 2019 年期间，总体 CMR 从 591.327/100000 增加到 674.505/100000，而 SMR 持续下降。NCDs 浓度的增加导致 1991-2019 年全因 从 0.443 增加到 0.560。1991 年至 2019 年期间，与 CMNN（=0.054）和 NCDs（=0.037）相比，损伤的排名变化最大（=0.174）。糖尿病、跌倒和道路交通伤害的排名随时间显著上升。NCDs 的 SMR 下降（=-0.013）主要归因于低排名原因，而 CMNN（=0.003）和损伤（=0.131）的变化归因于高排名原因。1991 年至 2019 年，全因 CMR 增加了 14.06%，主要原因是人口结构的贡献（68.46%）大于非人口因素的贡献（-54.40%）。人口结构变化对男性（70.52%）和城市人口（75.58%）CMR 的增加贡献更大。
迫切需要针对 NCDs 和特定病因采取预防和控制措施，随着人口老龄化，这些措施应得到加强，特别是对男性和农村人口。
