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

IF 9.6 1区 医学 Q1 MEDICINE, GENERAL & INTERNAL EClinicalMedicine Pub Date : 2024-08-02 eCollection Date: 2024-09-01 DOI:10.1016/j.eclinm.2024.102767
Rui Yan, Xinwei Liu, Ruyue Xue, Xiaoran Duan, Lifeng Li, Xianying He, Fangfang Cui, Jie Zhao
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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).

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互联网排斥与老年人抑郁症状之间的关系:对五项纵向队列研究的面板数据分析。
背景:互联网排斥和抑郁症状是老年人中普遍存在的现象;然而,互联网排斥和抑郁症状之间的关联仍然有限。本研究旨在调查高收入国家(HICs)和中低收入国家(LMICs)老年人中互联网排斥与抑郁症状之间的关联:我们进行了一项全面的跨文化纵向分析,参与者是来自 32 个国家的 60 岁及以上的成年人,他们参与了五项具有国家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)。互联网排斥的定义是自我报告没有使用互联网。抑郁症状采用抑郁流行病学研究中心量表(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,因此分别采用了面板数据分析方法。在广义估计方程框架内实施的逻辑回归被用来研究互联网排斥与抑郁症状发生可能性之间的关系,并对因果导向-关联图(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、居住状况、认知障碍和功能能力:我们的研究在 2010 年至 2020 年期间共纳入了 129847 名老年人,中位随访时间为 5(2,7)年。在HRS、ELSA、SHARE、CHARLS和MHAS中,互联网排斥的总比例分别为46.0%、32.6%、54.8%、92.3%和65.3%。在所有队列研究中,网络排斥与抑郁症状均有明显关联: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)和 MHAS(OR = 1.48,95% CI 1.39-1.58)。此外,在SHARE、MHAS和ELSA队列中(除睡眠和感到悲伤外),网络排斥与抑郁的所有方面都有关联:相当一部分老年人,尤其是低收入和中等收入国家的老年人,都有过被网络排斥的经历。无论老年人的地理位置是在高收入国家还是低收入国家,他们被互联网排斥都与出现抑郁症状的可能性较高有关,这表明了解决老年人上网障碍和促进他们积极参与互联网社会的重要性:国家重点研发计划(批准号:2022ZD0160704)、郑州大学第一附属医院科研创新团队(批准号:ZYCXTD2023005)、郑州市协同创新重大项目(批准号:20XTZX08017)、河南省医学科技联合项目(批准号:LHGJ20220428)、国家自然科学基金(批准号:82373341)。
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来源期刊
EClinicalMedicine
EClinicalMedicine Medicine-Medicine (all)
CiteScore
18.90
自引率
1.30%
发文量
506
审稿时长
22 days
期刊介绍: eClinicalMedicine is a gold open-access clinical journal designed to support frontline health professionals in addressing the complex and rapid health transitions affecting societies globally. The journal aims to assist practitioners in overcoming healthcare challenges across diverse communities, spanning diagnosis, treatment, prevention, and health promotion. Integrating disciplines from various specialties and life stages, it seeks to enhance health systems as fundamental institutions within societies. With a forward-thinking approach, eClinicalMedicine aims to redefine the future of healthcare.
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