Wang Jingjing, Lu Xinran, Ngai Sing Bik Cindy, Xie Lili, Liu Xiaoyun, Yao Yao, Jin Yinzi
Department of Global Health, School of Public Health, Peking University, Beijing, China.
China Center for Health Development Studies, School of Public Health, Peking University, Beijing, China.
Health Data Sci. 2024 Jan 10;5:0218. doi: 10.34133/hds.0218. eCollection 2025.
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. 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. 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 s < 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. 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.
数字排斥是一个全球性问题，对老年人影响尤甚，在低收入和中等收入国家更是如此。然而，目前关于数字排斥对高收入以及低收入和中等收入国家老年人心理健康影响的研究存在很大差距。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）。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的无法接入互联网。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联。我们根据因果有向无环图（DAG）最小充分调整集（MSAS）进行了调整，其中包括性别、年龄、退休状况、教育程度、家庭财富、社会活动以及与子女的每周联系情况。在研究期间（2010 - 2018年），122,242名参与者接受了多达5轮随访。数字排斥在各国差异很大，从丹麦的21.1%到中国的96.9%不等。粗略模型显示数字排斥与抑郁症状之间存在显著关联。在所有队列的MSAS调整模型中，这种关联在统计学上仍然显著：HRS [发病率比（IRR），1.37；95%置信区间（CI），1.28至1.47]，ELSA（IRR，1.32；95% CI，1.23至1.41），SHARE（IRR，1.30；95% CI，1.27至1.33），CHARLS（IRR，1.62；95% CI，1.38至1.91），以及MHAS（IRR，1.31；95% CI，1.26至1.37）；所有p < 0.001。值得注意的是，在所有5个队列中，除了ELSA，这种关联在居住在财富五分位数较低家庭的个体以及那些不经常与子女互动的个体中始终更强。数字排斥在全球老年人中普遍存在。被数字排斥的老年人患抑郁症状的风险更高，尤其是那些与后代沟通有限以及居住在财富五分位数较低家庭的个体。优先为老年人群体提供互联网接入可能有助于降低抑郁症状的风险，特别是在家庭支持有限且收入较低的弱势群体中。
