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已发表论文
2型糖尿病老年患者的认知功能潜在剖面特征及其相关因素研究：基于潜在剖面分析
Authors Ye B, Pan M, Lei X, Wen Y, Zhang Q
Received 11 July 2025
Accepted for publication 26 November 2025
Published 10 December 2025 Volume 2025:20 Pages 2493—2503
DOI https://doi.org/10.2147/CIA.S553115
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 3
Editor who approved publication: Dr Maddalena Illario
Beilei Ye,1,2 Mengxia Pan,1,2 Xiaoju Lei,2 Ying Wen,2 Qiong Zhang2
1Geriatric Medicine Center, Department of Geriatric Medicine, Zhejiang Provincial People’s Hospital(Affiliated People’s Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, People’s Republic of China; 2Department of Nursing, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, People’s Republic of China
Correspondence: Qiong Zhang, Department of Nursing, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, People’s Republic of China, Email zqzjsrmyy@163.com
Objective: This study aims to explore the latent profile characteristics of cognitive function in older adults living with diabetes and analyze the influencing factors, providing theoretical evidence for early intervention.
Methods: A cross-sectional study design was used to select older adults living with diabetes hospitalized at a tertiary hospital as the study population. Cognitive function was assessed using the Mini-Mental State Examination (MMSE). Demographic characteristics, disease-related data (such as duration of diabetes, BMI, and HbA1c levels), and lifestyle factors (such as sleep quality, physical activity, and social support) were collected. Latent profile analysis (LPA) was employed to classify cognitive function, and ordered multinomial logistic regression was performed to analyze the influencing factors of each cognitive profile.
Results: A total of 564 patients were included. Latent profile analysis of cognitive impairment identified three categories: complete cognitive impairment (12.82%), partial cognitive impairment (54.74%), and at-risk cognitive impairment (32.44%). Logistic regression analysis revealed that gender, education level, duration of diabetes, HbA1c, diverse intellectual activities, and nutrition were independent factors influencing cognitive impairment (P< 0.05).
Conclusion: Cognitive impairment in older adults living with diabetes exhibits distinct profile characteristics and is influenced by multiple factors. Interventions should focus on improving blood glucose control, promoting diverse intellectual activities, and enhancing social support to delay the decline in cognitive function.
Keywords: older adults, diabetes, cognitive impairment, influencing factors
1Geriatric Medicine Center, Department of Geriatric Medicine, Zhejiang Provincial People’s Hospital(Affiliated People’s Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, People’s Republic of China; 2Department of Nursing, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, People’s Republic of China
Correspondence: Qiong Zhang, Department of Nursing, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, People’s Republic of China, Email zqzjsrmyy@163.com
Objective: This study aims to explore the latent profile characteristics of cognitive function in older adults living with diabetes and analyze the influencing factors, providing theoretical evidence for early intervention.
Methods: A cross-sectional study design was used to select older adults living with diabetes hospitalized at a tertiary hospital as the study population. Cognitive function was assessed using the Mini-Mental State Examination (MMSE). Demographic characteristics, disease-related data (such as duration of diabetes, BMI, and HbA1c levels), and lifestyle factors (such as sleep quality, physical activity, and social support) were collected. Latent profile analysis (LPA) was employed to classify cognitive function, and ordered multinomial logistic regression was performed to analyze the influencing factors of each cognitive profile.
Results: A total of 564 patients were included. Latent profile analysis of cognitive impairment identified three categories: complete cognitive impairment (12.82%), partial cognitive impairment (54.74%), and at-risk cognitive impairment (32.44%). Logistic regression analysis revealed that gender, education level, duration of diabetes, HbA1c, diverse intellectual activities, and nutrition were independent factors influencing cognitive impairment (P< 0.05).
Conclusion: Cognitive impairment in older adults living with diabetes exhibits distinct profile characteristics and is influenced by multiple factors. Interventions should focus on improving blood glucose control, promoting diverse intellectual activities, and enhancing social support to delay the decline in cognitive function.
Keywords: older adults, diabetes, cognitive impairment, influencing factors