Department of Anesthesiology, West China Second University Hospital, Sichuan University, Chengdu, China.
Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, China.
J Med Internet Res. 2024 Nov 15;26:e56636. doi: 10.2196/56636.
Cognition disorders not only lead to adverse health consequences but also contribute to a range of socioeconomic challenges and diminished capacity for performing routine daily activities. In the digital era, understanding the impact of digital exclusion on cognitive function is crucial, especially in developing countries.
This study aimed to evaluate the association between digital exclusion and cognitive function among elderly populations in developing countries.
Using data from CHARLS (China Health and Retirement Longitudinal Study) from 2011 to 2020 and MHAS (Mexican Health & Aging Study) from 2012 to 2021, we defined digital exclusion as self-reported absence from the internet. Cognitive function was assessed through 5 tests: orientation, immediate verbal recall, delayed verbal recall, serial 7s, and figure recall. Cognitive function was assessed in 2 categories: worse cognition (a categorical variable that classifies cognition as either better or worse compared to the entire cohort population) and cognitive scores (a continuous variable representing raw cognitive scores across multiple follow-up waves). Logistic regression analyses and generalized estimating equation (GEE) analyses were used to examine the relationship between cognitive function and digital exclusion, adjusting for potential confounders, including demographics, lifestyle factors, history of chronic diseases, basic activities of daily living (BADL) disability, instrumental activities of daily living (IADL) disability, and basic cognitive abilities.
After excluding participants with probable cognitive impairment at baseline and those who did not have a complete cognitive assessment in any given year (ie, all tests in the cognitive assessment must be completed in any follow-up wave), a total of 24,065 participants in CHARLS (n=11,505, 47.81%) and MHAS (n=12,560, 52.19%) were included. Of these, 96.78% (n=11,135) participants in CHARLS and 70.02% (n=8795) in MHAS experienced digital exclusion. Adjusted logistic regression analyses revealed that individuals with digital exclusion were more likely to exhibit worse cognitive performance in both CHARLS (odds ratio [OR] 2.04, 95% CI 1.42-2.99; P<.001) and MHAS (OR 1.40, 95% CI 1.26-1.55; P<.001). Gender and age did not significantly modify the relationship between digital exclusion and worse cognition (intervention P>.05). The fully adjusted mean differences in global cognitive scores between the 2 groups were 0.98 (95% CI 0.70-1.28; P<.001) in CHARLS and 0.50 (95% CI 0.40-0.59; P<.001) in MHAS.
A substantial proportion of older adults, particularly in China, remain excluded from internet access. Our study examined longitudinal changes in cognitive scores and performed cross-sectional comparisons using Z-score standardization. The findings suggest that digital exclusion is linked to an increased risk of cognitive decline among older adults in developing countries. Promoting internet access may help mitigate this risk and support better cognitive health in these populations.
认知障碍不仅会导致不良的健康后果，还会带来一系列社会经济挑战，并降低人们进行日常活动的能力。在数字时代，了解数字排斥对认知功能的影响至关重要，尤其是在发展中国家。
本研究旨在评估发展中国家老年人中数字排斥与认知功能之间的关联。
我们使用了来自 CHARLS（中国健康与退休纵向研究）2011 年至 2020 年和 MHAS（墨西哥健康与老龄化研究）2012 年至 2021 年的数据，将数字排斥定义为自我报告的互联网缺失。认知功能通过 5 项测试进行评估：定向、即时口头回忆、延迟口头回忆、连续 7 秒和图形回忆。认知功能分为两类：较差的认知（将认知与整个队列人群相比分为更好或更差的分类变量）和认知评分（代表多个随访波中原始认知评分的连续变量）。使用逻辑回归分析和广义估计方程（GEE）分析来检查认知功能与数字排斥之间的关系，同时调整了潜在的混杂因素，包括人口统计学因素、生活方式因素、慢性病史、基本日常生活活动（BADL）障碍、工具性日常生活活动（IADL）障碍和基本认知能力。
在排除了基线时可能存在认知障碍的参与者和在任何一年都没有完成完整认知评估的参与者（即，认知评估中的所有测试都必须在任何随访波中完成）之后，CHARLS 共有 24,065 名参与者（n=11,505，47.81%）和 MHAS 共有 12,560 名参与者（n=12,560，52.19%）符合条件。其中，CHARLS 中 96.78%（n=11,135）的参与者和 MHAS 中 70.02%（n=8795）的参与者经历了数字排斥。经调整的逻辑回归分析显示，在 CHARLS（比值比 [OR] 2.04，95%置信区间 [CI] 1.42-2.99；P<.001）和 MHAS（OR 1.40，95% CI 1.26-1.55；P<.001）中，数字排斥的个体更有可能表现出较差的认知表现。性别和年龄并不能显著改变数字排斥与较差认知之间的关系（干预 P>.05）。两组之间全球认知评分的完全调整均值差异分别为 CHARLS 中的 0.98（95% CI 0.70-1.28；P<.001）和 MHAS 中的 0.50（95% CI 0.40-0.59；P<.001）。
相当一部分老年人，尤其是在中国，仍然无法访问互联网。我们的研究使用纵向变化评估认知评分，并使用 Z 分数标准化进行横断面比较。研究结果表明，数字排斥与发展中国家老年人的认知能力下降风险增加有关。促进互联网接入可能有助于降低这种风险，并支持这些人群的更好的认知健康。
