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Association rule analysis and identification of related factors for comorbidity of chronic diseases in middle-aged and elderly Chinese population
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Wen-yu SU1, Huai-ju GE1, Wen-jing CHANG1, Shi-hong DONG1, Hui-yu JIA1, Shan JIANG1, Yu-qing MI1, Jie YU2, *, Gui-feng MA*
Modern Preventive Medicine | 2024, 51(24) : 4417 - 4422
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Modern Preventive Medicine | 2024, 51(24): 4417-4422
Association rule analysis and identification of related factors for comorbidity of chronic diseases in middle-aged and elderly Chinese population
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Wen-yu SU1, Huai-ju GE1, Wen-jing CHANG1, Shi-hong DONG1, Hui-yu JIA1, Shan JIANG1, Yu-qing MI1, Jie YU2, *, Gui-feng MA*
Affiliations
  • School of Public Health, Shandong Second Medical University, Weifang, Shandong 261053, China
Published: 2024-12-25 doi: 10.20043/j.cnki.MPM.202407540
Outline
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Objective

To explore the comorbidity patterns and influencing factors of chronic diseases in middle-aged and elderly people in China, so as to provide new ideas for the development of corresponding chronic disease prevention and control strategies and measures.

Methods

Using data from the China Health and Retirement Longitudinal Study (CHARLS) 2018, after excluding samples with missing variables for 14 chronic diseases, a final sample of 19,390 individuals aged 45 and older was included. The Apriori algorithm from association rule analysis was utilized to explore the comorbidity patterns among middle-aged and elderly individuals in China. The occurrence of chronic comorbidity (two or more chronic diseases or three or more chronic diseases) was taken as the dependent variable, and the independent variable was determined according to the five dimensions of social determinants of health. 5 696 samples were included after deletion of the missing values, and the influential factors of chronic comorbidity were analyzed by univariate χ2 test and multiple logistic regression.

Results

The prevalence of comorbid chronic diseases among middle-aged and elderly individuals in our country was 55.4%. The most common comorbidity patterns were arthritis or rheumatic diseases and hypertension. Association rule analysis identified 24 strong rule combinations, with the most common binary association being gastrointestinal or digestive system diseases with arthritis or rheumatic diseases, and the most common ternary association being gastrointestinal or digestive system diseases, hypertension, and arthritis or rheumatic diseases.The results of the multivariate analysis showed that both two or more chronic diseases and three or more chronic diseases were significantly associated with increased risk factors, including: age 60-80 years (two or more chronic diseases: OR=1.479, 95% CI: 1.244-1.759; three or more chronic diseases: OR=1.526, 95% CI: 1.267-1.839), age >80 years (OR=1.545, 95% CI: 1.144-2.087; OR=1.591, 95% CI: 1.175-2.154), depressive symptoms (OR=1.435, 95% CI: 1.267-1.626; OR=1.382, 95% CI: 1.216-1.570), having a pension (OR=1.350, 95% CI: 1.141-1.598; OR=1.332, 95% CI: 1.118-1.586), and residence in central (OR=1.268, 95% CI: 1.096-1.470; OR=1.269, 95% CI: 1.088-1.479) or western regions (OR=1.217, 95% CI: 1.062-1.395; OR=1.198, 95% CI: 1.038-1.382).Conversely, factors associated with a reduced risk of chronic multimorbidity included alcohol consumption (two or more chronic diseases: OR=0.811, 95% CI: 0.707-0.930; three or more chronic diseases: OR=0.837, 95% CI: 0.724-0.968), 6-8 hours of night sleep (OR=0.806, 95% CI: 0.702-0.926; OR=0.792, 95% CI: 0.688-0.912), more than 8 hours of night sleep (OR=0.738, 95% CI: 0.635-0.858; OR=0.745, 95% CI: 0.637-0.872), self-rated general health (OR=0.357, 95% CI: 0.307-0.414; OR=0.343, 95% CI: 0.299-0.392), and self-rated good health (OR=0.136, 95% CI: 0.114-0.163; OR=0.117, 95% CI: 0.096-0.142).

Conclusion

It is suggested that the prevention and intervention of chronic comorbidity should be multidimensional, and the health care personnel should take into account the comorbidity of patients and the problem of multiple drug use in the formulation of comorbidity treatment plan.

Chronic disease comorbidity  /  Middle-aged and elderly people  /  Association rules  /  Social determinants of health  /  Analysis of influencing factors
Wen-yu SU, Huai-ju GE, Wen-jing CHANG, Shi-hong DONG, Hui-yu JIA, Shan JIANG, Yu-qing MI, Jie YU, Gui-feng MA. Association rule analysis and identification of related factors for comorbidity of chronic diseases in middle-aged and elderly Chinese population[J]. Modern Preventive Medicine, 2024 , 51 (24) : 4417 -4422 . DOI: 10.20043/j.cnki.MPM.202407540
Year 2024 volume 51 Issue 24
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doi: 10.20043/j.cnki.MPM.202407540
  • Receive Date:2024-07-30
  • Online Date:2026-03-18
  • Published:2024-12-25
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  • Received:2024-07-30
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    School of Public Health, Shandong Second Medical University, Weifang, Shandong 261053, China
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表12种不同金属材料的力学参数

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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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