Clustering de riesgo de metatipo basado en biomarcadores de enfermedades metabólicas y su asociación con el síndrome metabólico en adultos coreanos: hallazgos de la Encuesta Nacional de Salud y Nutrición de Corea (KNHANES) 2016-2023
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Ver abstracta en PubMed
Resumen
Este resumen es generado por máquina.El síndrome metabólico (MetS) se puede clasificar en grupos de riesgo distintos utilizando metabotyping. Este enfoque ayuda a la identificación temprana de las personas de alto riesgo para estrategias de prevención personalizadas.
Área De La Ciencia
- Endocrinología y Metabolismo
- Descubrimiento de biomarcadores
- Investigación en salud pública
Sus Antecedentes
- El síndrome metabólico (MetS) es un conjunto de afecciones que incluyen obesidad central, dislipidemia, hipertensión y alteración del metabolismo de la glucosa.
- MetS aumenta significativamente el riesgo de desarrollar diabetes tipo 2 y enfermedades cardiovasculares.
Objetivo Del Estudio
- Identificar fenotipos metabólicos distintos (metabotipos) dentro de la población heterogénea de individuos con MetS.
- Investigar la asociación entre estos metabotypes identificados y la prevalencia de MetS.
Principales Métodos
- Se utilizó la agrupación de medios k en base a los biomarcadores: índice de masa corporal (IMC), ácido úrico, glucosa en sangre en ayunas (GBF), colesterol de lipoproteínas de alta densidad (HDLc) y colesterol no HDL (no HDLc).
- Se analizaron datos de 1245 adultos coreanos (de 19 a 79 años) de la Encuesta Nacional de Salud y Nutrición de Corea 2016-2023.
- Se empleó regresión logística multivariable para determinar las asociaciones entre los grupos de metabotipos y MetS.
Principales Resultados
- Se identificaron tres grupos de riesgo metabólico: bajo, intermedio y alto.
- El grupo de alto riesgo mostró perfiles metabólicos significativamente más pobres (por ejemplo, aumento del IMC, GFB, HbA1c, triglicéridos; reducción del HDLc).
- La prevalencia de MetS aumentó en todos los grupos (OR: 5.46), con fuertes asociaciones tanto en hombres como en mujeres, revelando diferencias lipídicas específicas del sexo.
Conclusiones
- El metabotipado con biomarcadores de rutina es efectivo para la identificación temprana de individuos de alto riesgo.
- Esta estrategia apoya el desarrollo de planes personalizados de prevención y gestión para MetS.
- Los hallazgos tienen implicaciones para la práctica clínica y las iniciativas de salud pública.
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