Literature DB >> 29326412

[Identifying Latent Classes of Risk Factors for Coronary Artery Disease].

Eunsil Ju1, JiSun Choi2.   

Abstract

PURPOSE: This study aimed to identify latent classes based on major modifiable risk factors for coronary artery disease.
METHODS: 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.
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 of these 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 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.
© 2017 Korean Society of Nursing Science

Entities:  

Keywords:  Coronary artery disease; Dyslipidemia; Metabolic syndrome; Risk factors; Statistical models

Mesh:

Year:  2017        PMID: 29326412     DOI: 10.4040/jkan.2017.47.6.817

Source DB:  PubMed          Journal:  J Korean Acad Nurs        ISSN: 2005-3673            Impact factor:   0.984


  1 in total

1.  Diagnosis and risk stratification of coronary artery disease in Yemeni patients using treadmill test.

Authors:  Nouradden N Aljaber; Shanei A Shanei; Sultan Abdulwadoud Alshoabi; Kamal D Alsultan; Moawia B Gameraddin; Khaled M Al-Sayaghi
Journal:  J Family Med Prim Care       Date:  2020-05-31
  1 in total

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