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Latent profile analysis of cognitive function in older adults and its influencing factors
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Hai-ni MO, Cai-jiao WU, Yan-ping YING, Li LI, Liu YANG, Su-yi WU, Zi-rong LI
Modern Preventive Medicine | 2025, 52(5) : 893 - 899
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Modern Preventive Medicine | 2025, 52(5): 893-899
Health and Social Behavior
Latent profile analysis of cognitive function in older adults and its influencing factors
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Hai-ni MO, Cai-jiao WU, Yan-ping YING, Li LI, Liu YANG, Su-yi WU, Zi-rong LI
Affiliations
  • The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, China
Published: 2025-03-10 doi: 10.20043/j.cnki.MPM.202409057
Outline
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Objective

To explore the latent categories of cognitive function in older adults and their influencing factors.

Methods

Data from the 2020 CHARLS (China Health and Retirement Longitudinal Study) were used, including 4 606 participants aged 60 years and above. Latent profile analysis (LPA) was employed to identify the latent categories of cognitive function, and multivariate logistic regression and restricted cubic spline analysis were conducted to examine the influencing factors.

Results

Cognitive function in older adults was classified into four categories: “Low Cognitive Function-Low Attention Group” (21%), “Moderate Cognitive Function-Balanced Group” (18.6%), “High Cognitive Function-High Attention Group” (47.7%), and “Low Cognitive Function-High Visuospatial Ability Group” (12.7%). Protective factors for the “High Cognitive Function-High Attention Group” included age <70 years, higher education level, male gender, internet use, non-smoking, and absence of depressive symptoms (P < 0.05). Age exhibited a non-linear dose-response relationship with the risk of belonging to the “Low Cognitive Function-Low Attention Group” (P overalltrend <0.001, P non-linearity <0.001), “Moderate Cognitive Function-Balanced Group” (P overalltrend =0.016, P non-linearity =0.006), and “Low Cognitive Function-High Visuospatial Ability Group” (Poveralltrend =0.007, Pnon-linearity =0.004).

Conclusion

Cognitive function in older adults demonstrates distinct categorical characteristics, suggesting that healthcare professionals should develop targeted and personalized intervention strategies based on these categories and their influencing factors to prevent and delay cognitive impairment.

Cognitive function  /  Older adults  /  Latent profile analysis
Hai-ni MO, Cai-jiao WU, Yan-ping YING, Li LI, Liu YANG, Su-yi WU, Zi-rong LI. Latent profile analysis of cognitive function in older adults and its influencing factors[J]. Modern Preventive Medicine, 2025 , 52 (5) : 893 -899 . DOI: 10.20043/j.cnki.MPM.202409057
Year 2025 volume 52 Issue 5
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doi: 10.20043/j.cnki.MPM.202409057
  • Receive Date:2024-09-05
  • Online Date:2026-03-18
  • Published:2025-03-10
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  • Received:2024-09-05
Affiliations
    The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, China
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表12种不同金属材料的力学参数

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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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