View in EDS

Stroke Risk Factors in United States: An Analysis of the 2013–2018 National Health and Nutrition Examination Survey

Saved in:
Bibliographic Details
Title: Stroke Risk Factors in United States: An Analysis of the 2013–2018 National Health and Nutrition Examination Survey
Authors: Ren Z, Fu X
Source: International Journal of General Medicine, Vol 14, Pp 6135-6147 (2021)
Publisher Information: Dove Medical Press, 2021.
Publication Year: 2021
Collection: LCC:Medicine (General)
Subject Terms: diabetes, hyperglycemia, k-means clustering method, Medicine (General), R5-920
Description: Zhouming Ren, Xinzheng Fu Department of Neurology, Haining People’s Hospital, Haining, Zhejiang, People’s Republic of ChinaCorrespondence: Xinzheng FuDepartment of Neurology, Haining People’s Hospital, No. 2 Qianjiang West Road, Haining, Zhejiang, People’s Republic of ChinaTel +86-15325739220Email fxzncfxzncfxznc@126.comPurpose: This research intended to identify significant risk factors of stroke among the elderly population in the United States using the k-means clustering method.Patients and Methods: In this cross-sectional study, we analyzed data of 4346 subjects aged ≥ 60 years using the National Health and Nutrition Examination Survey (NHANES) 2013– 2018 datasets. Questionnaire data, dietary data, and laboratory data were accessed to acquire measurements of the potential risk factors. A pre-defined classification method was used based on the Medical Condition Questionnaire to define the stroke group. K-means clustering analysis used all potential risk factors for differentiating both groups. A stepwise logistic regression analysis examined the association between significant risk factors and the odds of stroke.Results: Age (OR:1.053, 95% CI:1.029– 1.077), diabetes (OR: 28.019, 95% CI: 19.139– 41.020), glycohemoglobin (OR: 2.309, 95% CI: 1.818– 2.934), plasma fasting glucose (OR: 1.017, 95% CI: 1.010– 1.024), hypertension (OR: 2.343, 95% CI: 1.602– 3.426), dietary fiber consumption (OR:0.980, 95% CI:0.964– 0.995), and education level (OR:0.541, 95% CI: 0.411– 0.713) were identified as significant risk factor for stroke among the elderly population in the k-means clustering method. In the pre-defined grouping method, age (OR:1.093, 95% CI:1.054– 1.132), diabetes (OR:2.228, 95% CI: 1.432– 3.466), hypertension (OR:2.295, 95% CI:1.338– 3.938), and dietary fiber consumption (OR: 0.966, 95CI%:0.947– 0.985) were found to influence to the risk of stroke.Conclusion: Age, hypertension, dietary fiber consumption, and education level are the significant risk factors of stroke among elders aged > 60 years. Among all the risk factors, diabetes is the strongest predictor of stroke. Glycohemoglobin and plasma fasting glucose are also associated with stroke risks, implying that glycemic control is particularly crucial in stroke prevention and management among older adults.Keywords: diabetes, hyperglycemia, k-means clustering method
Document Type: article
File Description: electronic resource
Language: English
ISSN: 1178-7074
Relation: https://www.dovepress.com/stroke-risk-factors-in-united-states-an-analysis-of-the-20132018-natio-peer-reviewed-fulltext-article-IJGM; https://doaj.org/toc/1178-7074
Access URL: https://doaj.org/article/f1efca0e4fb149ccbffece844c877514
Accession Number: edsdoj.f1efca0e4fb149ccbffece844c877514
Database: Directory of Open Access Journals
Description
Abstract:Zhouming Ren, Xinzheng Fu Department of Neurology, Haining People’s Hospital, Haining, Zhejiang, People’s Republic of ChinaCorrespondence: Xinzheng FuDepartment of Neurology, Haining People’s Hospital, No. 2 Qianjiang West Road, Haining, Zhejiang, People’s Republic of ChinaTel +86-15325739220Email fxzncfxzncfxznc@126.comPurpose: This research intended to identify significant risk factors of stroke among the elderly population in the United States using the k-means clustering method.Patients and Methods: In this cross-sectional study, we analyzed data of 4346 subjects aged ≥ 60 years using the National Health and Nutrition Examination Survey (NHANES) 2013– 2018 datasets. Questionnaire data, dietary data, and laboratory data were accessed to acquire measurements of the potential risk factors. A pre-defined classification method was used based on the Medical Condition Questionnaire to define the stroke group. K-means clustering analysis used all potential risk factors for differentiating both groups. A stepwise logistic regression analysis examined the association between significant risk factors and the odds of stroke.Results: Age (OR:1.053, 95% CI:1.029– 1.077), diabetes (OR: 28.019, 95% CI: 19.139– 41.020), glycohemoglobin (OR: 2.309, 95% CI: 1.818– 2.934), plasma fasting glucose (OR: 1.017, 95% CI: 1.010– 1.024), hypertension (OR: 2.343, 95% CI: 1.602– 3.426), dietary fiber consumption (OR:0.980, 95% CI:0.964– 0.995), and education level (OR:0.541, 95% CI: 0.411– 0.713) were identified as significant risk factor for stroke among the elderly population in the k-means clustering method. In the pre-defined grouping method, age (OR:1.093, 95% CI:1.054– 1.132), diabetes (OR:2.228, 95% CI: 1.432– 3.466), hypertension (OR:2.295, 95% CI:1.338– 3.938), and dietary fiber consumption (OR: 0.966, 95CI%:0.947– 0.985) were found to influence to the risk of stroke.Conclusion: Age, hypertension, dietary fiber consumption, and education level are the significant risk factors of stroke among elders aged > 60 years. Among all the risk factors, diabetes is the strongest predictor of stroke. Glycohemoglobin and plasma fasting glucose are also associated with stroke risks, implying that glycemic control is particularly crucial in stroke prevention and management among older adults.Keywords: diabetes, hyperglycemia, k-means clustering method
ISSN:11787074