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J Hum Hypertens ; 26(5): 325-33, 2012 May.
Artículo en Inglés | MEDLINE | ID: mdl-21412265

RESUMEN

Here we examined whether the Matsuda-DeFronzo insulin sensitivity index (ISI-M) is more efficient than the homeostasis model assessment of insulin resistance (HOMA-IR) for assessing risk of hypertension. Cross-sectional and longitudinal analyses were conducted using normotensive subjects who were selected among 1399 subjects in the Tanno-Sobetsu cohort. In the cross-sectional analysis (n=740), blood pressure (BP) level was correlated with HOMA-IR and with ISI-M, but correlation coefficients indicate a tighter correlation with ISI-M. Multiple linear regression analysis adjusted by age, sex, body mass index (BMI) and serum triglyceride level (TG) showed contribution of ISI-M and fasting plasma glucose, but not of HOMA-IR. In the longitudinal analysis (n=607), 241 subjects (39.7%) developed hypertension during a 10-year follow-up period, and multiple logistic regression indicated that age, TG, systolic BP and ISI-M, but not HOMA-IR, were associated with development of hypertension. In subjects <60 years old, odds ratio of new-onset hypertension was higher in the low ISI-M group (ISI-M, less than the median) than in the high ISI-M group for any tertile of BMI. In conclusion, ISI-M is a better predictor of hypertension than is HOMA-IR. Non-hepatic IR may be a determinant, which is independent of TG, BP level and BMI, of the development of hypertension.


Asunto(s)
Glucemia/metabolismo , Presión Sanguínea , Hipertensión/epidemiología , Resistencia a la Insulina , Insulina/sangre , Modelos Biológicos , Anciano , Biomarcadores/sangre , Índice de Masa Corporal , Estudios Transversales , Ayuno/sangre , Femenino , Prueba de Tolerancia a la Glucosa , Homeostasis , Humanos , Hipertensión/sangre , Hipertensión/fisiopatología , Japón/epidemiología , Modelos Lineales , Modelos Logísticos , Estudios Longitudinales , Masculino , Persona de Mediana Edad , Análisis Multivariante , Oportunidad Relativa , Valor Predictivo de las Pruebas , Pronóstico , Medición de Riesgo , Factores de Riesgo , Factores de Tiempo , Triglicéridos/sangre
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