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老年人网络排斥与抑郁症状之间的关联:五项纵向队列研究的面板数据分析

Association between internet exclusion and depressive symptoms among older adults: panel data analysis of five longitudinal cohort studies.

作者信息

Yan Rui, Liu Xinwei, Xue Ruyue, Duan Xiaoran, Li Lifeng, He Xianying, Cui Fangfang, Zhao Jie

机构信息

Internet Medical and System Applications of National Engineering Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, PR China.

Department of Breast Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, PR China.

出版信息

EClinicalMedicine. 2024 Aug 2;75:102767. doi: 10.1016/j.eclinm.2024.102767. eCollection 2024 Sep.

DOI:10.1016/j.eclinm.2024.102767
PMID:39188711
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11345591/
Abstract

BACKGROUND

Internet exclusion and depressive symptoms are prevalent phenomena among older adults; however, the association between internet exclusion and depressive symptoms remains limited. This study aims to investigate the association between internet exclusion and depressive symptoms among older adults from high-income countries (HICs) and low- and middle-income countries (LMICs).

METHODS

We conducted a comprehensive longitudinal, cross-cultural analysis, and the participants were adults aged 60 years and older from 32 countries participating in five nationally representative longitudinal cohort studies: the Health and Retirement Study (HRS), the English Longitudinal Study of Ageing (ELSA), the Survey of Health, Ageing and Retirement in Europe (SHARE), the China Health and Retirement Longitudinal Study (CHARLS), and the Mexican Health and Ageing Study (MHAS). Internet exclusion was defined as the self-reported absence from internet use. Depressive symptoms were evaluated using the Centre for Epidemiologic Studies of Depression scale (CES-D) or the Euro-Depression scale (Euro-D). These five cohorts, being heterogeneous, were respectively conducted with panel data analysis. Logistic regression, implemented within the generalized estimating equations framework, was used to examine the association between internet exclusion and the likelihood of experiencing depressive symptoms, adjusting for the causal-directed-acyclic-graph (DAG) minimal sufficient adjustment set (MSAS), including gender, age, education, labour force status, household wealth level, marital status, co-residence with children, residence status, cognitive impairment, and functional ability.

FINDINGS

Our study included a total of 129,847 older adults during the period from 2010 to 2020, with a median follow-up of 5 (2, 7) years. The pooled proportion of internet exclusion was 46.0% in HRS, 32.6% in ELSA, 54.8% in SHARE, 92.3% in CHARLS, and 65.3% in MHAS. Internet exclusion was significantly associated with depressive symptoms across all cohort studies: HRS (OR = 1.13, 95% CI 1.07-1.20), ELSA (OR = 1.22, 95% CI 1.11-1.34), SHARE (OR = 1.55, 95% CI 1.47-1.62), CHARLS (OR = 1.49, 95% CI 1.26-1.77), and MHAS (OR = 1.48, 95% CI 1.39-1.58). Moreover, internet exclusion was found to be associated with all dimensions of depression in the SHARE, MHAS, and ELSA cohorts (except for sleep and felt sad) cohorts.

INTERPRETATION

A considerable proportion of older adults experienced internet exclusion, particularly those in LMICs. Internet exclusion among older adults, irrespective of their geographic location in HICs or LMICs, was associated with a higher likelihood of experiencing depressive symptoms, which demonstrated the importance of addressing barriers to internet access and promoting active participation in the internet society among older adults.

FUNDING

National Key R&D Program of China (grant number 2022ZD0160704), the Scientific Research and Innovation Team of The First Affiliated Hospital of Zhengzhou University (grant number ZYCXTD2023005), the Collaborative Innovation Major Project of Zhengzhou (grant number 20XTZX08017), the Joint Project of Medical Science and Technology of Henan Province (grant number LHGJ20220428), and National Natural Science Foundation of China (grant number 82373341).

摘要

背景

网络排斥和抑郁症状在老年人中是普遍现象;然而,网络排斥与抑郁症状之间的关联仍不明确。本研究旨在调查高收入国家(HICs)和低收入及中等收入国家(LMICs)老年人中网络排斥与抑郁症状之间的关联。

方法

我们进行了一项全面的纵向跨文化分析,参与者为来自32个国家的60岁及以上成年人,他们参与了五项具有全国代表性的纵向队列研究:健康与退休研究(HRS)、英国老龄化纵向研究(ELSA)、欧洲健康、老龄化与退休调查(SHARE)、中国健康与退休纵向研究(CHARLS)以及墨西哥健康与老龄化研究(MHAS)。网络排斥被定义为自我报告的未使用互联网情况。抑郁症状使用流行病学研究中心抑郁量表(CES-D)或欧洲抑郁量表(Euro-D)进行评估。这五个队列具有异质性,分别进行了面板数据分析。在广义估计方程框架内实施的逻辑回归用于检验网络排斥与出现抑郁症状可能性之间的关联,并针对因果无环图(DAG)最小充分调整集(MSAS)进行调整,包括性别、年龄、教育程度、劳动力状况、家庭财富水平、婚姻状况、与子女同住情况、居住状况、认知障碍和功能能力。

结果

我们的研究共纳入了2010年至2020年期间的129,847名老年人,中位随访时间为5(2,7)年。HRS中网络排斥的合并比例为46.0%,ELSA中为32.6%,SHARE中为54.8%,CHARLS中为92.3%,MHAS中为65.3%。在所有队列研究中,网络排斥均与抑郁症状显著相关:HRS(OR = 1.13,95%CI 1.07 - 1.20)、ELSA(OR = 1.22,95%CI 1.11 - 1.34)、SHARE(OR = 1.55,95%CI 1.47 - 1.62)、CHARLS(OR = 1.49,95%CI 1.26 - 1.77)以及MHAS(OR = 1.48,95%CI 1.39 - 1.58)。此外,在SHARE、MHAS和ELSA队列中,发现网络排斥与抑郁的所有维度相关(睡眠和感到悲伤除外)。

解读

相当一部分老年人经历了网络排斥,尤其是低收入及中等收入国家的老年人。无论身处高收入国家还是低收入及中等收入国家,老年人中的网络排斥都与出现抑郁症状的较高可能性相关,这表明解决互联网接入障碍以及促进老年人积极参与网络社会的重要性。

资助

国家重点研发计划(项目编号2022ZD0160704)、郑州大学第一附属医院科研创新团队(项目编号ZYCXTD2023005)、郑州市协同创新重大项目(项目编号20XTZX08017)、河南省医学科技联合项目(项目编号LHGJ20220428)以及国家自然科学基金(项目编号82373341)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7810/11345591/a2a8a1c9aa2a/figs2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7810/11345591/fbaf218787bc/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7810/11345591/afd4adf60771/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7810/11345591/2ad6de3b5edd/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7810/11345591/0770a17ee655/figs1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7810/11345591/a2a8a1c9aa2a/figs2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7810/11345591/fbaf218787bc/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7810/11345591/afd4adf60771/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7810/11345591/2ad6de3b5edd/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7810/11345591/0770a17ee655/figs1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7810/11345591/a2a8a1c9aa2a/figs2.jpg

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