Evidence map›Paper›PMID 41393032›Full record

ArticleFrontiers in public health2025

Unraveling life expectancy and death spectrum changes of registered residents (hukou) in Quzhou, China, 2015-2023: a study using Arriaga decomposition method.

Jie Pan, Yewei Huang, Shilin Jiao, Biyun Zheng, Zhiying Yin, Zhijuan Gan

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Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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6 authors.

Jie Pan *Department of NCDs Control and Prevention, Quzhou Center for Disease Control and Prevention, Quzhou, Zhejiang, China.
Yewei Huang *Department of NCDs Control and Prevention, Changshan County Center for Disease Control and Prevention, Quzhou, Zhejiang, China.
Shilin JiaoDepartment of NCDs Control and Prevention, Quzhou Center for Disease Control and Prevention, Quzhou, Zhejiang, China.
Biyun ZhengDepartment of NCDs Control and Prevention, Quzhou Center for Disease Control and Prevention, Quzhou, Zhejiang, China.
Zhiying YinDepartment of NCDs Control and Prevention, Quzhou Center for Disease Control and Prevention, Quzhou, Zhejiang, China.
Zhijuan GanDepartment of NCDs Control and Prevention, Quzhou Center for Disease Control and Prevention, Quzhou, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: In 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. Methods: The 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. Results: Over 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. Conclusion: The 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.

Indexed as

Life ExpectancyAdolescentAdultAgedAged, 80 and overCause of DeathChildChild, PreschoolChinaFemaleHumansInfantInfant, NewbornMaleMiddle AgedYoung AdultArriaga decomposition methodcause-eliminated life expectancydeath spectrumlife expectancyloss of life expectancy rate

Identifiers

PMID41393032
PMCPMC12698370

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.