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Detalle de: Effectiveness of PRECEDE model for health education in metabolic control and reduction of cardiovascular risk factors in patients with diabetes type 2,Eficacia del modelo PRECEDE, de educación para la salud, en el control metabólico y de los factores de riesgo cardiovascular en pacientes con diabetes mellitus tipo 2

Title Effectiveness of PRECEDE model for health education in metabolic control and reduction of cardiovascular risk factors in patients with diabetes type 2,Eficacia del modelo PRECEDE, de educación para la salud, en el control metabólico y de los factores de riesgo cardiovascular en pacientes con diabetes mellitus tipo 2
Abstract

Objective To evaluate the effectiveness of PRECEDE model for health education, in the metabolic control and the reduction of cardiovascular risk factors, in type 2 diabetic patients followed for over two years in primary health care services. Materials and methods PRECEDE model for health education was used in 318 patients with type 2 diabetes, from five primary health care centres. The study was conducted during two years of monitoring. Results After two years of follow-up was observed decrease in diastolic and systolic pressures (p Discussion PRECEDE model for health education is a useful method in the management of type 2 diabetes, that reduce the levels of blood pressure both systolic and diastolic, decrease the lipid levels, and improve the level of therapeutic adherence in type 2 diabetic patients, followed for two years.

Apa Reference Salinero-Fort, M., Arrieta-Blanco, F., Carrillo-de Santa Pau, E., Martín-Madrazo, C., Piñera-Tames, M., Vázquez-Martínez, C., & Abánades-Herranz, J. C. (2009). Eficacia del modelo PRECEDE, de educación para la salud, en el control metabólico y de los factores de riesgo cardiovascular en pacientes con diabetes mellitus tipo 2. Revista Clínica Española, 209(7), 325–331. 10.1016/s0014-2565(09)71816-8
Doi 10.1016/S0014-2565(09)71816-8
Publication Date Aug 2009
Publication Type Article
Researcher Enrique Carrillo de Santa Pau
Ontology
Research Groups Computational Biology (IMDEA)
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