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주은실 ( Ju Eun-Sil ) - 강동경희대학교병원
최지선 ( Choi Ji-Sun ) - 경희대학교 간호과학대학
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Abstract
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Purpose: This study aimed to identify latent classes based on major modifiable risk factors for coronary artery disease.
Methods: This was a secondaryanalysis using data from the electronic medical records of 2,022 patients, who were newly diagnosed with coronary artery disease at auniversity medical center, from January 2010 to December 2015. Data were analyzed using SPSS version 20.0 for descriptive analysis and Mplusversion 7.4 for latent class analysis.
Results: Four latent classes of risk factors for coronary artery disease were identified in the final model:‘smoking-drinking’, ‘high-risk for dyslipidemia’, ‘high-risk for metabolic syndrome’, and ‘high-risk for diabetes and malnutrition’. The likelihood ofthese latent classes varied significantly based on socio-demographic characteristics, including age, gender, educational level, and occupation.
Conclusion: The results showed significant heterogeneity in the pattern of risk factors for coronary artery disease. These findings provide helpfuldata to develop intervention strategies for the effective prevention of coronary artery disease. Specific characteristics depending on the subpopulationshould be considered during the development of interventions.
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KeyWords
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관상동맥질환, 이상지질혈증, 대사증후군, 위험요인, 통계적 모델
Coronary artery disease, Dyslipidemia, Metabolic syndrome, Risk factors, Statistical models
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원문 및 링크아웃 정보
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등재저널 정보
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