Identifying Latent Classes of Risk Factors for Coronary Artery Disease
Journal of Korean Academy of Nursing
;
: 817-827, 2017.
Artículo
en Coreano
| WPRIM
| ID: wpr-60164
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.
Texto completo:
Disponible
Índice:
WPRIM (Pacífico Occidental)
Asunto principal:
Características de la Población
/
Enfermedad de la Arteria Coronaria
/
Factores de Riesgo
/
Modelos Estadísticos
/
Vasos Coronarios
/
Centros Médicos Académicos
/
Dislipidemias
/
Registros Electrónicos de Salud
/
Ocupaciones
Tipo de estudio:
Estudio de etiología
/
Estudio pronóstico
/
Factores de riesgo
Límite:
Humanos
Idioma:
Coreano
Revista:
Journal of Korean Academy of Nursing
Año:
2017
Tipo del documento:
Artículo
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