Digital Exclusion and Depressive Symptoms among Older People: Findings from Five Aging Cohort Studies across 24 Countries.

Health data science Pub Date : 2024-01-10 eCollection Date: 2025-01-01 DOI:10.34133/hds.0218
Jingjing Wang, Xinran Lu, Sing Bik Cindy Ngai, Lili Xie, Xiaoyun Liu, Yao Yao, Yinzi Jin
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Abstract

Background: Digital exclusion is a global issue that disproportionately affects older individuals especially in low- and middle-income nations. However, there is a wide gap in current research regarding the impact of digital exclusion on the mental health of older adults in both high-income and low- and middle-income countries. Methods: We analyzed data from 5 longitudinal cohorts: the Health and Retirement Study (HRS), the English Longitudinal Study of Aging (ELSA), the Survey of Health, Ageing and Retirement in Europe (SHARE), the China Health and Retirement Longitudinal Study (CHARLS), and the Mexican Health and Aging Study (MHAS). These cohorts consisted of nationwide samples from 24 countries. Digital exclusion was defined as the self-reported lack of access to the internet. Depressive symptoms were assessed using comparable scales across all cohorts. We used generalized estimating equation models, fitting a Poisson model, to investigate the association between the digital exclusion and depressive symptoms. We adjusted for the causal directed acyclic graph (DAG) minimal sufficient adjustment set (MSAS), which includes gender, age, retirement status, education, household wealth, social activities, and weekly contact with their children. Results: During the study period (2010-2018), 122,242 participants underwent up to 5 rounds of follow-up. Digital exclusion varied greatly across countries, ranging from 21.1% in Denmark to 96.9% in China. The crude model revealed a significant association between digital exclusion and depressive symptoms. This association remained statistically significant in the MSAS-adjusted model across all cohorts: HRS [incidence rate ratio (IRR), 1.37; 95% confidence interval (CI), 1.28 to 1.47], ELSA (IRR, 1.32; 95% CI, 1.23 to 1.41), SHARE (IRR, 1.30; 95% CI, 1.27 to 1.33), CHARLS (IRR, 1.62; 95% CI, 1.38 to 1.91), and MHAS (IRR, 1.31; 95% CI, 1.26 to 1.37); all Ps < 0.001. Notably, this association was consistently stronger in individuals living in lower wealth quintile households across all 5 cohorts and among those who do not regularly interact with their children, except for ELSA. Conclusions: Digital exclusion is globally widespread among older adults. Older individuals who are digitally excluded are at a higher risk of developing depressive symptoms, particularly those with limited communication with their offspring and individuals living in lower wealth quintile households. Prioritizing the provision of internet access to older populations may help reduce the risks of depression symptoms, especially among vulnerable groups with limited familial support and with lower income.

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老年人的数字排斥和抑郁症状:来自24个国家的5项老年队列研究的结果
背景:数字排斥是一个全球性问题,对老年人的影响尤为严重,尤其是在低收入和中等收入国家。然而,关于数字排斥对高收入国家和中低收入国家老年人心理健康的影响,目前的研究存在很大差距。方法:我们分析了来自5个纵向队列的数据:健康与退休研究(HRS)、英国老龄化纵向研究(ELSA)、欧洲健康、老龄化和退休调查(SHARE)、中国健康与退休纵向研究(CHARLS)和墨西哥健康与老龄化研究(MHAS)。这些队列由来自24个国家的全国性样本组成。数字排斥被定义为自我报告无法访问互联网。在所有队列中使用可比量表评估抑郁症状。我们使用广义估计方程模型,拟合泊松模型,来研究数字排斥与抑郁症状之间的关系。我们调整了因果有向无环图(DAG)最小充分调整集(MSAS),其中包括性别、年龄、退休状态、教育程度、家庭财富、社会活动和每周与子女的接触。结果:在研究期间(2010-2018年),122242名参与者接受了多达5轮的随访。数字排斥在各国之间差异很大,从丹麦的21.1%到中国的96.9%不等。粗略的模型揭示了数字排斥和抑郁症状之间的显著关联。在所有队列的msas校正模型中,这种关联仍然具有统计学意义:HRS[发病率比(IRR), 1.37;95%可信区间(CI), 1.28 ~ 1.47], ELSA (IRR, 1.32;95% CI, 1.23 ~ 1.41), SHARE (IRR, 1.30;95% CI, 1.27 ~ 1.33), CHARLS (IRR, 1.62;95% CI, 1.38 - 1.91)和MHAS (IRR, 1.31;95% CI, 1.26 ~ 1.37);p < 0.001。值得注意的是,在所有5个队列中,生活在较低财富五分之一家庭的个人以及那些不经常与孩子互动的人(ELSA除外)中,这种关联一直更强。结论:数字排斥在全球老年人中普遍存在。被数字技术排斥在外的老年人出现抑郁症状的风险更高,尤其是那些与子女沟通有限的人,以及生活在财富较低五分之一家庭的人。优先向老年人提供互联网接入可能有助于减少抑郁症状的风险,特别是在家庭支持有限和收入较低的弱势群体中。
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