The Impact of the Development Level of Rural E-commerce on the Depressive Symptoms Among Rural Older Adult Individuals

Overview

Journal Front Public Health

Specialty Public Health

Date 2024 Dec 26

PMID 39722711

Authors

Xiaofeng Xie

Siying Wei

Ling Zhu

Xiaoting Gan

Yong He

Rui Wang

Affiliations

Soon will be listed here.

Abstract

Background: In the context of China, where the demographic trend of population aging intertwines with the rapid advancement of information digitalization, rural older adult individuals, who are part of a vulnerable population, are witnessing a deteriorating depression status. The proliferation of rural e-commerce, which fuels the digital economic revolution in rural areas, is concurrently affecting the depressive symptoms among rural older adult individuals.

Methods: This study uses longitudinal data from the China Health and Retirement Longitudinal Study (CHARLS) and applies a multi-period Difference-in-Differences (DID) model to explore how rural e-commerce affects the depressive symptoms among rural older adult individuals.

Results: The findings indicate that the development of rural e-commerce can indeed improve the depressive symptoms among rural older adult individuals, with a particularly pronounced effect on those residing in the eastern and central regions of China, as well as those who do not live with their children. The mechanism analysis indicates that e-commerce improves depressive symptoms among rural older adult individuals by enhancing social interaction frequency and increasing financial support by children.

Conclusion: Based on these insights, we recommend a targeted approach to implementing e-commerce policies in rural areas, focusing on innovative methods to improve the depressive symptoms among rural older adult individuals.

References

Schofield P, Thygesen M, Das-Munshi J, Becares L, Cantor-Graae E, Pedersen C . Ethnic density, urbanicity and psychosis risk for migrant groups - A population cohort study. Schizophr Res. 2017; 190:82-87. PMC: 5735221. DOI: 10.1016/j.schres.2017.03.032. View

Adhikari R, Jampaklay A, Chamratrithirong A . Impact of children's migration on health and health care-seeking behavior of elderly left behind. BMC Public Health. 2011; 11:143. PMC: 3056748. DOI: 10.1186/1471-2458-11-143. View

Tang T, Jiang J, Tang X . Prevalence of depressive symptoms among older adults in mainland China: A systematic review and meta-analysis. J Affect Disord. 2021; 293:379-390. DOI: 10.1016/j.jad.2021.06.050. View

Topino E, Cacioppo M, Gori A . The Relationship between Attachment Styles and Compulsive Online Shopping: The Mediating Roles of Family Functioning Patterns. Int J Environ Res Public Health. 2022; 19(13). PMC: 9266044. DOI: 10.3390/ijerph19138162. View

Garey L, Olofsson H, Garza T, Shepherd J, Smit T, Zvolensky M . The Role of Anxiety in Smoking Onset, Severity, and Cessation-Related Outcomes: a Review of Recent Literature. Curr Psychiatry Rep. 2020; 22(8):38. DOI: 10.1007/s11920-020-01160-5. View

Tang D, Lin Z, Chen F . Moving beyond living arrangements: the role of family and friendship ties in promoting mental health for urban and rural older adults in China. Aging Ment Health. 2019; 24(9):1523-1532. DOI: 10.1080/13607863.2019.1602589. View

He W, Jiang L, Ge X, Ye J, Yang N, Li M . Quality of life of empty-nest elderly in China: a systematic review and meta-analysis. Psychol Health Med. 2019; 25(2):131-147. DOI: 10.1080/13548506.2019.1695863. View

Li C, Xia Z, Liu Y, Li S, Ren S, Zhao H . Is online shopping addiction still a depressive illness? -- the induced consumption and traffic trap in live E-commerce. Heliyon. 2024; 10(9):e29895. PMC: 11061708. DOI: 10.1016/j.heliyon.2024.e29895. View

Wang X, Wang P, Wang P, Cao M, Xu X . Relationships among mental health, social capital and life satisfaction in rural senior older adults: a structural equation model. BMC Geriatr. 2022; 22(1):73. PMC: 8785491. DOI: 10.1186/s12877-022-02761-w. View

10.

Richardson R, Keyes K, Medina J, Calvo E . Sociodemographic inequalities in depression among older adults: cross-sectional evidence from 18 countries. Lancet Psychiatry. 2020; 7(8):673-681. PMC: 7597555. DOI: 10.1016/S2215-0366(20)30151-6. View

11.

Liu X, Cao H, Zhu H, Zhang H, Niu K, Tang N . Association of chronic diseases with depression, anxiety and stress in Chinese general population: The CHCN-BTH cohort study. J Affect Disord. 2021; 282:1278-1287. DOI: 10.1016/j.jad.2021.01.040. View

12.

Ji X, Xu J, Zhang H . Environmental effects of rural e-commerce: A case study of chemical fertilizer reduction in China. J Environ Manage. 2022; 326(Pt A):116713. DOI: 10.1016/j.jenvman.2022.116713. View

13.

Wang Y, Li Z, Gao S, Fu C . Volunteer activity and depression among the elderly in China: A study on rural-urban differences. Medicine (Baltimore). 2021; 100(39):e27315. PMC: 8483842. DOI: 10.1097/MD.0000000000027315. View

14.

Patwardhan V, Gil G, Arrieta A, Cagney J, DeGraw E, Herbert M . Differences across the lifespan between females and males in the top 20 causes of disease burden globally: a systematic analysis of the Global Burden of Disease Study 2021. Lancet Public Health. 2024; 9(5):e282-e294. PMC: 11080072. DOI: 10.1016/S2468-2667(24)00053-7. View

15.

Abdoli N, Salari N, Darvishi N, Jafarpour S, Solaymani M, Mohammadi M . The global prevalence of major depressive disorder (MDD) among the elderly: A systematic review and meta-analysis. Neurosci Biobehav Rev. 2021; 132:1067-1073. DOI: 10.1016/j.neubiorev.2021.10.041. View

16.

Hao Y . Productive activities and psychological well-being among older adults. J Gerontol B Psychol Sci Soc Sci. 2008; 63(2):S64-72. DOI: 10.1093/geronb/63.2.s64. View

17.

Wang W, Sun X, Zhang M . Does the central environmental inspection effectively improve air pollution?-An empirical study of 290 prefecture-level cities in China. J Environ Manage. 2021; 286:112274. DOI: 10.1016/j.jenvman.2021.112274. View

18.

Liu J, Rozelle S, Xu Q, Yu N, Zhou T . Social Engagement and Elderly Health in China: Evidence from the China Health and Retirement Longitudinal Survey (CHARLS). Int J Environ Res Public Health. 2019; 16(2). PMC: 6352065. DOI: 10.3390/ijerph16020278. View

19.

Treur J, Munafo M, Logtenberg E, Wiers R, Verweij K . Using Mendelian randomization analysis to better understand the relationship between mental health and substance use: a systematic review. Psychol Med. 2021; 51(10):1593-1624. PMC: 8327626. DOI: 10.1017/S003329172100180X. View

20.

Verduyn P, Gugushvili N, Massar K, Taht K, Kross E . Social comparison on social networking sites. Curr Opin Psychol. 2020; 36:32-37. DOI: 10.1016/j.copsyc.2020.04.002. View