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Table 1_Analysis of disparate factors affecting cognitive function among populations with different educational levels: a large-scale longitudinal study.docx

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NIAID Data Ecosystem2026-05-10 收录
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https://figshare.com/articles/dataset/Table_1_Analysis_of_disparate_factors_affecting_cognitive_function_among_populations_with_different_educational_levels_a_large-scale_longitudinal_study_docx/31810564
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ObjectiveTo explore the influencing factors and patterns of cognitive function among populations with different educational levels. MethodsUsing data from the China Health and Retirement Longitudinal Study (2015–2020), we analyzed 29,620 subjects aged 45–85 years who completed cognitive function assessments. Participants were stratified by educational level: illiterate (n = 7,670), primary school (n = 7,897), junior high school (n = 8,904), and high school and above (n = 5,149). Mixed-effects models were used to analyze cognitive function determinants across educational groups, with sensitivity analyses performed to verify result robustness. ResultsCognitive function scores demonstrated a significant educational gradient, with the highest scores in the high-education group [20.0 (18.0–23.0)] and lowest in the illiterate group [16.0 (13.0–18.0)]. Age negatively correlated with cognitive function, with stronger effects in higher education groups (illiterate: β = −0.665; high-education: β = −1.033, p < 0.001). Gender effects varied by education level: males showed cognitive advantages in the illiterate group (β = 0.716, p < 0.001), but disadvantages in the high-education group (β = −0.739, p < 0.001). Internet use demonstrated enhanced protective effects with increasing education (illiterate: β = 0.254; high-education: β = 0.411, p < 0.001). Urban residence benefits strengthened with education level (illiterate: β = 0.188; high-education: β = 0.439, p < 0.001). Memory-related diseases showed the most significant impact in the high-education group (β = −2.325, p < 0.05). ConclusionEducational level appears to act not only as an independent correlate of cognitive function but also as a potential modifier of its associations with gender, Internet use, residential environment, and chronic disease burden. These observations suggest educational background warrants consideration when designing cognitive health strategies for older adults.
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2026-03-19
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