ArticleBMC geriatrics2024
An analysis of factors influencing cognitive dysfunction among older adults in Northwest China based on logistic regression and decision tree modelling.
Article in BMC geriatrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed.
- Associations of Iron Indicators with Cognitive Impairment Risk in Postmenopausal Women: Evidence from a Matched Case-Control Study and Back Propagation Neural Network Model.Molecular neurobiology · 2026Article
- Factors Associated With Self-Rated Health Among Older Adults in Japan: A Decision Tree Analysis.Cureus · 2025Article
- Establishing a clinical prediction model for diabetic foot ulcers in type 2 diabetic patients with lower extremity arteriosclerotic occlusion using machine learning.Scientific reports · 2025Article
- ADL and Cognitive Function in Chinese Elderly: Mediating Role of Social Participation and Moderating Role of Intergenerational Support.Journal of multidisciplinary healthcare · 2025Article
- The multiple mediating roles of depression and grandchild care in the relationship between social participation and cognitive function among middle-aged and elderly Chinese: an empirical study based on CHARLS 2020 data.Frontiers in aging neuroscience · 2025Article
- Construction of a predictive model for cognitive impairment among older adults in Northwest China.Frontiers in aging neuroscience · 2025Article
- Risk factors analysis of cognitive frailty among geriatric adults in nursing homes based on logistic regression and decision tree modeling.Frontiers in aging neuroscience · 2024Article
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5 authors.
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Abstract
backgroundCognitive dysfunction is one of the leading causes of disability and dependence in older adults and is a major economic burden on the public health system. The aim of this study was to investigate the risk factors for cognitive dysfunction and their predictive value in older adults in Northwest China.
methodsA cross-sectional study was conducted using a multistage sampling method. The questionnaires were distributed through the Elderly Disability Monitoring Platform to older adults aged 60 years and above in Northwest China, who were divided into cognitive dysfunction and normal cognitive function groups. In addition to univariate analyses, logistic regression and decision tree modelling were used to construct a model to identify factors that can predict the occurrence of cognitive dysfunction in older adults.
resultsA total of 12,494 valid questionnaires were collected, including 2617 from participants in the cognitive dysfunction group and 9877 from participants in the normal cognitive function group. Univariate analysis revealed that ethnicity, BMI, age, educational attainment, marital status, type of residence, residency status, current work status, main economic source, type of chronic disease, long-term use of medication, alcohol consumption, participation in social activities, exercise status, social support, total scores on the Balanced Test Assessment, total scores on the Gait Speed Assessment total score, and activities of daily living (ADL) were significantly different between the two groups (all P < 0.05). According to logistic regression analyses, ethnicity, BMI, educational attainment, marital status, residency, main source of income, chronic diseases, annual medical examination, alcohol consumption, exercise status, total scores on the Balanced Test Assessment, and activities of daily living (ADLs) were found to influence cognitive dysfunction in older adults (all P < 0.05). In the decision tree model, the ability to perform activities of daily living was the root node, followed by total scores on the Balanced Test Assessment, marital status, educational attainment, age, annual medical examination, and ethnicity.
conclusionsTraditional risk factors (including BMI, literacy, and alcohol consumption) and potentially modifiable risk factors (including balance function, ability to care for oneself in daily life, and widowhood) have a significant impact on the increased risk of cognitive dysfunction in older adults in Northwest China. The use of decision tree models can help health care workers better assess cognitive function in older adults and develop personalized interventions. Further research could help to gain insight into the mechanisms of cognitive dysfunction and provide new avenues for prevention and intervention.
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