Depression and Anxiety-Free Life Expectancy by Sex and Urban–Rural Areas in Jiangxi, China in 2013 and 2018

Yuhang Wu, Huilie Zheng, Zhitao Liu, Shengwei Wang, Xiaoyun Chen, Huiqiang Yu, Yong Liu and Songbo Hu
Additional contact information
Yuhang Wu: Jiangxi Province Key Laboratory of Preventive Medicine, School of Public Health, Nanchang University, Nanchang 330006, Jiangxi, China
Huilie Zheng: Jiangxi Province Key Laboratory of Preventive Medicine, School of Public Health, Nanchang University, Nanchang 330006, Jiangxi, China
Zhitao Liu: Jiangxi Province Key Laboratory of Preventive Medicine, School of Public Health, Nanchang University, Nanchang 330006, Jiangxi, China
Shengwei Wang: Jiangxi Province Key Laboratory of Preventive Medicine, School of Public Health, Nanchang University, Nanchang 330006, Jiangxi, China
Xiaoyun Chen: Jiangxi Province Key Laboratory of Preventive Medicine, School of Public Health, Nanchang University, Nanchang 330006, Jiangxi, China
Huiqiang Yu: Jiangxi Province Key Laboratory of Preventive Medicine, School of Public Health, Nanchang University, Nanchang 330006, Jiangxi, China
Yong Liu: Jiangxi Province Key Laboratory of Preventive Medicine, School of Public Health, Nanchang University, Nanchang 330006, Jiangxi, China
Songbo Hu: Jiangxi Province Key Laboratory of Preventive Medicine, School of Public Health, Nanchang University, Nanchang 330006, Jiangxi, China

IJERPH, 2021, vol. 18, issue 4, 1-11

Abstract: Objective: To quantitatively estimate life expectancy (LE) and depression and anxiety-free life expectancy (DAFLE) for the years 2013 and 2018 in Jiangxi Province, China, by sex and urban–rural areas. Additionally, to compare the discrepancy of DAFLE/LE of different sexes and urban-rural areas over various years. Methods: Based on the summary of the health statistics of Jiangxi Province in 2013 and 2018 and the results of the 5th and 6th National Health Service Surveys in Jiangxi Province, the model life table is used to estimate the age-specific mortality rate by sex and urban–rural areas. Sullivan’s method was used to calculate DAFLE. Results: Data from 2013 indicate that those aged 15 can expect to live 56.20 years without depression and anxiety for men and 59.67 years without depression and anxiety for women. Compared to 2013, DAFLE had not fluctuated significantly in 2018. The proportion of life expectancy without depression and anxiety (DAFLE/LE) declined between 2013 and 2018. DAFLE/LE in urban areas was higher than in rural areas. Men had higher DAFLE/LE than women. From 2013 to 2018, the DAFLE aged 15 decreased by 0.18 years for urban men and decreased by 0.52 years for urban women, rural areas also decreased to varying degrees. Conclusions: Even if women had a longer life span than men, they would spend more time with depression or anxiety. DAFLE did not increase with the increase in LE from 2013 to 2018, suggesting an absolute expansion of the burden, especially in rural areas. Depression and anxiety health services in Jiangxi, China will face more serious obstacles and challenges, which may lead to more disability. This requires more attention and more effective measures from the public, medical departments and the government.

Keywords: healthy life expectancy; depression; anxiety; mental health; urban-rural areas (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1660-4601/18/4/1991/pdf (application/pdf)
https://www.mdpi.com/1660-4601/18/4/1991/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:18:y:2021:i:4:p:1991-:d:501685

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().