Ju Eunsil, Choi JiSun
Kyung Hee University Hospital at Gangdong, Seoul, Korea.
College of Nursing Science · East-West Nursing Research Institute, Kyung Hee University, Seoul, Korea.
J Korean Acad Nurs. 2017 Dec;47(6):817-827. doi: 10.4040/jkan.2017.47.6.817.
This study aimed to identify latent classes based on major modifiable risk factors for coronary artery disease.
This was a secondary analysis using data from the electronic medical records of 2,022 patients, who were newly diagnosed with coronary artery disease at a university medical center, from January 2010 to December 2015. Data were analyzed using SPSS version 20.0 for descriptive analysis and Mplus version 7.4 for latent class analysis.
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 of these latent classes varied significantly based on socio-demographic characteristics, including age, gender, educational level, and occupation.
The results showed significant heterogeneity in the pattern of risk factors for coronary artery disease. These findings provide helpful data to develop intervention strategies for the effective prevention of coronary artery disease. Specific characteristics depending on the subpopulation should be considered during the development of interventions.
本研究旨在基于冠状动脉疾病的主要可改变风险因素识别潜在类别。
这是一项二次分析，使用了2010年1月至2015年12月期间在某大学医学中心新诊断为冠状动脉疾病的2022例患者的电子病历数据。使用SPSS 20.0版进行描述性分析，使用Mplus 7.4版进行潜在类别分析。
最终模型中识别出了四类冠状动脉疾病风险因素的潜在类别：“吸烟饮酒”、“血脂异常高危”、“代谢综合征高危”以及“糖尿病和营养不良高危”。这些潜在类别的可能性因社会人口学特征（包括年龄、性别、教育水平和职业）而异。
结果显示冠状动脉疾病风险因素模式存在显著异质性。这些发现为制定有效预防冠状动脉疾病的干预策略提供了有用数据。在制定干预措施时应考虑亚人群的具体特征。
