Identifying risk factors associated with the health-related quality of life for coronary heart diseases elderly using association rule mining
Abstract Health-related quality of life (HRQoL) is a crucial outcome measure in the care of elderly patients with coronary heart disease (CHD). This research aims to identify risk factors associated with HRQoL in elderly patients with CHD. A cross-sectional study was carried out in Shanghai, China,...
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Nature Portfolio
2025-04-01
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| Online Access: | https://doi.org/10.1038/s41598-025-95046-2 |
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| author | Chunzi Wang Yunwei Zhang Shuangcheng Wang Yi Wang Yifei Shen Hansheng Ding |
| author_facet | Chunzi Wang Yunwei Zhang Shuangcheng Wang Yi Wang Yifei Shen Hansheng Ding |
| author_sort | Chunzi Wang |
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| description | Abstract Health-related quality of life (HRQoL) is a crucial outcome measure in the care of elderly patients with coronary heart disease (CHD). This research aims to identify risk factors associated with HRQoL in elderly patients with CHD. A cross-sectional study was carried out in Shanghai, China, from January to May 2023. Data on demographics and general symptoms and signs of CHD among elderly patients were collected by a structured questionnaire. HRQoL was measured by 21 items including both physical and psychological symptoms. The association rule mining (ARM) technique was performed to identify significant rules (support>10% and confidence >85%) for the sick and healthy conditions. In total, 179141 individuals were enrolled. 3,583 sick individuals (with CHD only, 34.4% male and 65.6% female) and 10,790 healthy individuals (free of any chronic disease, 39.5% male and 60.5% female) were included in our study. Among the significant rules for the sick condition, the most frequently occurring factors were “MedicalConstipation=1”, “MotorFunction=1”, “Sleep=1”, “MasticatoryFunction=1” and “Gender=2”. In contrast, for the healthy condition, the frequently occurring factors were “MotorFunction=0”, “EducationLevel=3”, “Sleep=0”, “MedicalConstipation=0”, and “MasticatoryFunction=0”. ARM is effective in identifying the important risk factors. Impairments in medical constipation, sleep, motor function, and masticatory function are significant risk factors associated with the HRQoL in elderly patients with CHD. Early detection and management of these four symptoms could be crucial in reducing the disease burden and improving outcomes. Additionally, gender and education level may also influence the risk of developing CHD. |
| format | Article |
| id | doaj-art-3b86c93b05bd4f26a0d6172a20ee2e20 |
| institution | DOAJ |
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| language | English |
| publishDate | 2025-04-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-3b86c93b05bd4f26a0d6172a20ee2e202025-08-20T03:07:41ZengNature PortfolioScientific Reports2045-23222025-04-0115111610.1038/s41598-025-95046-2Identifying risk factors associated with the health-related quality of life for coronary heart diseases elderly using association rule miningChunzi Wang0Yunwei Zhang1Shuangcheng Wang2Yi Wang3Yifei Shen4Hansheng Ding5Department of Fintech, Shanghai Normal University Tianhua CollegeShanghai Health Development Research Center (Shanghai Medical Information Center)Department of Fintech, Shanghai Normal University Tianhua CollegeDahua HospitalShanghai Health Development Research Center (Shanghai Medical Information Center)Shanghai Health Development Research Center (Shanghai Medical Information Center)Abstract Health-related quality of life (HRQoL) is a crucial outcome measure in the care of elderly patients with coronary heart disease (CHD). This research aims to identify risk factors associated with HRQoL in elderly patients with CHD. A cross-sectional study was carried out in Shanghai, China, from January to May 2023. Data on demographics and general symptoms and signs of CHD among elderly patients were collected by a structured questionnaire. HRQoL was measured by 21 items including both physical and psychological symptoms. The association rule mining (ARM) technique was performed to identify significant rules (support>10% and confidence >85%) for the sick and healthy conditions. In total, 179141 individuals were enrolled. 3,583 sick individuals (with CHD only, 34.4% male and 65.6% female) and 10,790 healthy individuals (free of any chronic disease, 39.5% male and 60.5% female) were included in our study. Among the significant rules for the sick condition, the most frequently occurring factors were “MedicalConstipation=1”, “MotorFunction=1”, “Sleep=1”, “MasticatoryFunction=1” and “Gender=2”. In contrast, for the healthy condition, the frequently occurring factors were “MotorFunction=0”, “EducationLevel=3”, “Sleep=0”, “MedicalConstipation=0”, and “MasticatoryFunction=0”. ARM is effective in identifying the important risk factors. Impairments in medical constipation, sleep, motor function, and masticatory function are significant risk factors associated with the HRQoL in elderly patients with CHD. Early detection and management of these four symptoms could be crucial in reducing the disease burden and improving outcomes. Additionally, gender and education level may also influence the risk of developing CHD.https://doi.org/10.1038/s41598-025-95046-2Coronary heart diseaseAssociation rule miningHealth-related quality of lifeRisk factor |
| spellingShingle | Chunzi Wang Yunwei Zhang Shuangcheng Wang Yi Wang Yifei Shen Hansheng Ding Identifying risk factors associated with the health-related quality of life for coronary heart diseases elderly using association rule mining Scientific Reports Coronary heart disease Association rule mining Health-related quality of life Risk factor |
| title | Identifying risk factors associated with the health-related quality of life for coronary heart diseases elderly using association rule mining |
| title_full | Identifying risk factors associated with the health-related quality of life for coronary heart diseases elderly using association rule mining |
| title_fullStr | Identifying risk factors associated with the health-related quality of life for coronary heart diseases elderly using association rule mining |
| title_full_unstemmed | Identifying risk factors associated with the health-related quality of life for coronary heart diseases elderly using association rule mining |
| title_short | Identifying risk factors associated with the health-related quality of life for coronary heart diseases elderly using association rule mining |
| title_sort | identifying risk factors associated with the health related quality of life for coronary heart diseases elderly using association rule mining |
| topic | Coronary heart disease Association rule mining Health-related quality of life Risk factor |
| url | https://doi.org/10.1038/s41598-025-95046-2 |
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