Table 2_Unraveling life expectancy and death spectrum changes of registered residents (hukou) in Quzhou, China, 2015–2023: a study using Arriaga decomposition method.docx

ObjectiveIn less-developed, rapidly aging areas like Quzhou, in-depth analyses of life expectancy change are scarce. Using Arriaga decomposition method, this study quantify age- and cause-specific contributions to changes in Quzhou’s life expectancy in 2015–2023, assess the major causes of death affect registered residents (hukou), and provide evidence to inform targeted health policies and resource allocation in Quzhou and other similar underdeveloped, aging regions.
MethodsThe death data was sourced from the Zhejiang Province Chronic Disease Monitoring Information Management System, while population data was sourced from the Zhejiang Province Public Security Department. Residents in the death and population data refer to individuals registered in the Household Registration (hukou) System in Quzhou. Chiang abridged life table was compiled using Excel 2019. The Arriaga decomposition method was employed to analyze the differences in life expectancy across different periods.
ResultsOver the period 2015–2023 in Quzhou, life expectancy increased by 1.55 years. Age groups 55–80 made significant positive contributions, while 0- and 85- groups saw decreased contributions. Malignant neoplasms showed the most significant positive growth in contribution rates, increasing by 57.10%, while respiratory diseases exhibited the most notable negative growth, decreasing by 77.07%. The top 10 causes of death shifted, with malignant neoplasms consistently leading. The loss of life expectancy rate due to malignant neoplasms consistently ranked first at 4.22, 3.89, and 3.32% in 2015, 2019, and 2023, respectively. The loss of life expectancy due to respiratory diseases decreased from 3.22 years in 2015 to 1.92 years in 2023.
ConclusionThe life expectancy from 2015 to 2023 showed an increasing trend, with the Arriaga decomposition method revealing positive contributions of infants and older adults aged 60–85 to the growth in life expectancy. However, adjustments in health strategies are needed to address the negative contributions in the 85- age group. Malignant neoplasms and respiratory system diseases, among other chronic illnesses, showed high contribution rates to the increase in life expectancy, emphasizing the need for a comprehensive system for the prevention and control of chronic diseases.

研究目标：在衢州这类欠发达且快速老龄化的地区，针对预期寿命变化的深度分析较为匮乏。本研究采用阿利亚加分解法（Arriaga decomposition method），量化2015-2023年衢州预期寿命变化的年龄别与死因别贡献度，评估主要死因对衢州户籍（hukou）居民的影响，并为衢州及其他同类欠发达老龄化地区的针对性卫生政策制定与资源配置提供依据。
研究方法：死亡数据来源于浙江省慢性病监测信息管理系统，人口数据来源于浙江省公安厅。本研究纳入的死亡与人口数据对象，均为衢州地区登记在户籍登记（Household Registration，即hukou）系统中的居民。采用Excel 2019编制蒋氏简略寿命表（Chiang abridged life table），并运用阿利亚加分解法分析不同时期预期寿命的差异。
研究结果：2015-2023年，衢州地区居民预期寿命提升了1.55岁。其中55-80岁年龄组对预期寿命增长产生了显著正向贡献，而0岁组与85岁及以上年龄组的贡献度则有所下降。恶性肿瘤（malignant neoplasms）的贡献增长率最为显著，提升了57.10%；呼吸系统疾病（respiratory diseases）则呈现最显著的负向增长，降幅达77.07%。衢州地区的前十位死因顺位发生了变化，恶性肿瘤始终位居首位。2015年、2019年及2023年，恶性肿瘤导致的预期寿命损失率分别为4.22%、3.89%及3.32%，持续位列第一。呼吸系统疾病导致的预期寿命损失从2015年的3.22岁下降至2023年的1.92岁。
研究结论：2015-2023年衢州居民预期寿命呈上升趋势，阿利亚加分解法分析显示，婴儿与60-85岁老年群体对预期寿命增长具有正向贡献。但85岁及以上年龄组的负向贡献仍需通过卫生策略调整加以应对。恶性肿瘤、呼吸系统疾病等慢性疾病对预期寿命增长的贡献度较高，这凸显了构建完善的慢性病预防控制体系的必要性。