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. 2024 Nov 15:26:e56636.
doi: 10.2196/56636.

Digital Exclusion and Cognitive Function in Elderly Populations in Developing Countries: Insights Derived From 2 Longitudinal Cohort Studies

Sainan Duan #  1   2   3 , Dongxu Chen #  1   2 , Jinping Wang  3   4 , Mohammed Sharooq Paramboor  1   2   3 , Zhen Xia  5 , Wanting Xu  6 , Kun Han  1   2 , Tao Zhu  3   4 , Xiaoqin Jiang  1   2
Affiliations

Digital Exclusion and Cognitive Function in Elderly Populations in Developing Countries: Insights Derived From 2 Longitudinal Cohort Studies

Sainan Duan et al. J Med Internet Res. .

Abstract

Background: 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.

Objective: This study aimed to evaluate the association between digital exclusion and cognitive function among elderly populations in developing countries.

Methods: 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.

Results: 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.

Conclusions: 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.

Keywords: CHARLS; China Health and Retirement Longitudinal Study; MHAS; cognition; cognitive decline; cohort study; developing country; digital exclusion.

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Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
Subgroup analysis of digital exclusion and worse cognition by age group and sex in (A) CHARLS and (B) MHAS. Values are adjusted for age, gender, BMI group, marital status, education level, residence, smoking status, drinking status, BADL and IADL disabilities, chronic diseases, and baseline cognitive scores. BADL: basic activities of daily living; CHARLS: China Health and Retirement Longitudinal Study; IADL: instrumental activities of daily living; MHAS: Mexican Health & Aging Study; OR: odds ratio.
Figure 2
Figure 2
Average follow-up global cognitive scores in (A) CHARLS and (B) MHAS. Values are adjusted for baseline global cognitive scores, age, gender, BMI group, marital status, education level, residence, smoking status, BADL disability, IADL disability, and chronic diseases. BADL: basic activities of daily living; CHARLS: China Health and Retirement Longitudinal Study; IADL: instrumental activities of daily living; MHAS: Mexican Health & Aging Study.
Figure 3
Figure 3
Average follow-up tests’ cognitive scores in CHARLS and MHAS. (A) Orientation scores in CHARLS, (B) orientation scores in MHAS, (C) immediate verbal recall scores in CHARLS, (D) immediate verbal recall scores in MHAS, (E) delayed verbal recall scores in CHARLS, (F) delayed verbal recall scores in MHAS, (G) figure recall scores in CHARLS, (H) figure recall scores in MHAS, and (I) serial 7s scores in CHARLS. Values are adjusted for baseline cognitive scores, age, gender, BMI group, marital status, educational level, residence, smoking status, BADL and IADL disabilities, and chronic diseases. BADL: basic activities of daily living; CHARLS: China Health and Retirement Longitudinal Study; IADL: instrumental activities of daily living; MHAS: Mexican Health & Aging Study.
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