Utilización de mediciones antropométricas para predecir resistencia a la insulina / Use of anthropometric measures to predict insulin resistance

Objetivo: La obesidad está estrechamente relacionada con la resistencia a la insulina (RI), pero se valora de forma dispar en las diversas definiciones de síndrome metabólico. El objetivo del estudio fue comprobar la utilidad de distintas mediciones antropométricas para predecir RI y valorar los mejores puntos de corte. Sujetos y método: Estudio transversal sobre población de 40 a 70 años (2.143 habitantes); se obtuvo una muestra aleatoria simple de 305 pacientes no diabéticos. Se recogieron variables sociodemográficas, exploración y analítica habituales más insulinemia. Se consideró RI un índice de HOMA (homeostasis model assessment) $ 2,9. Se practicó una regresión logística por pasos hacia delante para obtener las mejores variables para predecir RI; después se construyó una ecuación logística y se comparó el área bajo la curva ROC (receiver operating characteristic) de ésta y de las distintas variables antropométricas en su capacidad de predicción, y los mejores puntos de corte según el índice de Youden. Resultados: Han entrado en el modelo el índice de masa corporal (IMC) y la razón cintura/cadera 3 100. No han entrado la edad, el sexo, la cintura, la cadera y la superficie corporal. La ecuación logística hallada: p(RI) = 1/1 + exp {­[­14,295] ­ [0,234 3 IMC] ­ [0,07 3 (cintura/cadera 3 100)]} mostró un buen ajuste, y la probabilidad calculada por ella presenta la mayor área en general y para cada sexo, seguida en mujeres por el IMC y en varones por la cintura, pero sin diferencias significativas. Conclusiones: No se ha encontrado diferencias significativas ente IMC, cintura, cadera y un modelo logístico para predecir la RI (AU)

Objective: Obesity is closely related to insulin-resistance (IR) but it is evaluated differently in the diverse definitions of the metabolic syndrome. The objective of this study was to verify the utility of different anthropometric measures to predict IR and to evaluate the best cut-off points. Subjects and method: We performed a cross-sectional study of the general population aged 40 to 70 years old (n = 2,143); a simple random sample of 305 non-diabetic persons was obtained. Sociodemographic data, physical examination and routine biochemical analysis with insulinemia were obtained. IR was defined by a HOMA index (Homeostasis Model Assessment) $ 2.9. To obtain the best variables to predict IR, a forward stepwise logistic regression was performed. Subsequently, a logistic equation was constructed and its predictive capacity was compared with the different anthropometric variables by the area under the ROC (receiver-operating characteristic) curve (AUC). The best cut-off points were established according to the Youden index. Results: Body mass index (BMI) and the waist/hip ratio 3 100 were entered into the model, but age, sex, waist, hip and body surface were not. The logistic equation found: p(RI) = 1/1 + exp{­[­14.295] ­ [0.234 3 IMC] ­ [0.07 3 (waist/hip 3 100)]} showed good adjustment, and the probability calculated on the basis of this equation showed the greatest AUC overall and in both sexes, followed in women by BMI and by waist measurement in men, but without significant differences. Conclusions: No significant differences were found between the BMI, waist or hip measurements and the logistic model to predict IR (AU)

Reynold's Risk Score ¿tiene utilidad en la práctica clínica en poblaciones de bajo riesgo? / Is reynold’s risk score useful in clinical practice for low-risk populations?

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Use of anthropometric measures to predict insulin resistance.

OBJECTIVE: Obesity is closely related to insulin-resistance (IR) but it is evaluated differently in the diverse definitions of the metabolic syndrome. The objective of this study was to verify the utility of different anthropometric measures to predict IR and to evaluate the best cut-off points. SUBJECTS AND METHOD: We performed a cross-sectional study of the general population aged 40 to 70 years old (n=2,143); a simple random sample of 305 non-diabetic persons was obtained. Sociodemographic data, physical examination and routine biochemical analysis with insulinemia were obtained. IR was defined by a HOMA index (Homeostasis Model Assessment) ≥2.9. To obtain the best variables to predict IR, a forward stepwise logistic regression was performed. Subsequently, a logistic equation was constructed and its predictive capacity was compared with the different anthropometric variables by the area under the ROC (receiver-operating characteristic) curve (AUC). The best cut-off points were established according to the Youden index. RESULTS: Body mass index (BMI) and the waist/hip ratio ×100 were entered into the model, but age, sex, waist, hip and body surface were not. The logistic equation found: p(RI)=1/1+exp{-[-14.295]-[0.234×IMC]-[0.07×(waist/hip×100)]} showed good adjustment, and the probability calculated on the basis of this equation showed the greatest AUC overall and in both sexes, followed in women by BMI and by waist measurement in men, but without significant differences. CONCLUSIONS: No significant differences were found between the BMI, waist or hip measurements and the logistic model to predict IR.

Relación entre la proteína C reactiva ultrasensible y el síndrome metabólico / Association of high-sensitivity C-reactive protein levels and metabolic syndrome in a semi-urban population in Spain

Objetivo. El propósito de este estudio fue describir la relación entre los valores de proteína C reactiva ultrasensible (PCR-us) y el síndrome metabólico (SM) en una población semiurbana española. Materiales y métodos. Se estudiaron los niveles de PCR-us en una muestra aleatoria de una población semiurbana española (358 pacientes de ambos sexos atendidos en el Consultorio de Colloto) de 40 a 75 años, así como los factores clínicos y analíticos precisos para aplicar las definiciones de SM según los criterios de la Organización Mundial de la Salud y del ATP-III (cintura, cadera, índice de masa corporal, glucemia basal, insulinemia basal, índice HOMA, colesterol unido a lipoproteínas de alta densidad, triglicéridos y presión arterial sistólica y diastólica). Resultados. La media de PCR-us en pacientes con SM fue superior, al aplicar cualquiera de las definiciones, que en los individuos sin SM, fue mayor cuanto mayor número de factores definitorios reunían los pacientes y, de forma inversa, la prevalencia de SM era mayor cuanto mayor fue el índice de PCR-us. Conclusiones. Se confirma la idea de que la PCR-us tiene una importante relación con la existencia del SM por cualquiera de sus definiciones. Esta relación sería continua y con una tendencia lineal (AU)

Objective. To describe the association between high-sensitivity C-reactive protein (hsCRP) levels and metabolic syndrome (MS) in a semi-urban population in Spain. Materials and methods. Levels of hsCRP were measured in a random sample of a semi-urban population in Spain (358 patients of both sexes, aged between 40 and 75 years old, attending the medical center of Colloto). The clinical and laboratory factors required for a diagnosis of MS according to the WHO and ATP-III criteria (waist, hip, body mass index, fasting glucose, fasting insulinemia, HOMA index, HDL-C, triglycerides, and systolic and diastolic blood pressure) were also measured. Results. When either of the definitions was used, the mean hsCRP level was higher in patients with MS than in those without MS. The greater the number of distinctive factors in patients, the higher the levels of hsCRP. Equally, the greater the hsCRP level, the greater the prevalence of MS. Conclusions. This study confirms that hsCRP is associated with the presence of MS, irrespective of the definition of MS used. This relationship seems to be continuous and has a linear tendency (AU)

Comparación de los modelos SCORE y Framinghan en el cálculo de alto riesgo cardiovascular para una muestra de varones de 45 y 65 años de Asturias / Comparison of the SCORE and Framingham Models in Calculating High Cardiovascular Risk for a Sample of Males within the 45-65 Age Range in Asturias, Spain

Fundamento: Recientemente el Comité Español Interdisciplinariopara la Prevención Cardiovascular (CEIP) elaboró un consensopara adaptar las recomendaciones de la Guía Europea de Prevencióncardiovascular a la población española, utilizando el SCOREcomo método de cálculo de riesgo. El objetivo de este trabajo esconocer las diferencias que supone pasar del criterio de Framinghamal de SCORE en la clasificación de los varones en el grupo de altoriesgo.Métodos: Estudio descriptivo transversal realizado en atenciónprimaria. El número de participantes fue de 379 varones de entre 45y 65 años, correspondientes a 4 cupos de medicina general de 3 centrosde salud del Principado de Asturias. Medidas principales: cálculodel riesgo cardiovascular y prevalencia de alto riesgo según Framinghamclásico y según SCORE. Estimación de curva de prevalenciade alto riesgo por regresión logística.Resultados: La prevalencia de alto riesgo según la ecuación deFramingham fue de 24% (IC95%=19,9-28,7) y según SCORE de17,9% (IC95%=14,3-22,3) siendo la diferencia estadísticamente significativa(p=0,02). El modelo SCORE presenta prevalencias menoresen sujetos menores de 60 años y mayores por encima de los 60; envarones fumadores SCORE presenta prevalencias menores en personasmenores de 58 años; los varones de alto riesgo con Framinghamy bajo riesgo con SCORE son más jóvenes, fumadores y con cifrasmedias más bajas de presión arterial y cifras moderadas de colesterol.Conclusiones: Al aplicar el modelo SCORE clasificamos menosvarones como de alto riesgo, sobre todo en menores de 58 años,fumadores y con cifras moderadas de colesterol, que con la escala deFramingham

Background: The Spanish Interdisciplinary Committee forCardiovascular Prevention has recently drafted a consensus foradapting the European Cardiovascular Prevention Guide to theSpanish population, using SCORE as the risk-calculation method.This study is aimed as ascertaining the differences involved inchanging over from the Framingham to the SCORE criterion in theclassification of males within the high-risk group.Methods: Descriptive cross-sectional study conducted in primarycare. A total of 379 males within the 45-65 age range, correspondingto four (4) groups from general practitioners from threehealthcare centers in the Principality of Asturias. Main measurements:calculation of the cardiovascular risk and high-risk prevalenceby the conventional Framingham method and according to SCORE.High-risk prevalence curve estimated by logic regression.Results: The high-risk prevalence according to the Framinghamequation was 24% (CI95%=19.9-28.7) and was 17.9%(CI95%=14.3-22.3) for SCORE, the difference being statistically significant(p=0.02). The SCORE model shows lower prevalencesamong subjects under age 60 and higher for those over age 60.Among male smokers, SCORE shows lower prevalences among individualsunder 58 years of age, the high-risk males with Framinghamand low-risk with SCORE being younger, smokers and having loweraverage blood pressure figures and moderate cholesterol figures.Conclusions: On applying the SCORE model, we classify fewermales as high-risk, especially among those under 58 years of agewho are smokers having moderate cholesterol figures than when theFramingham scale is used

[Differences in the prevalence of metabolic syndrome according to the ATP-III and WHO definitions]. / Diferencias en la prevalencia del síndrome metabólico según las definiciones del ATP-III y la OMS.

BACKGROUND AND OBJECTIVE: The objective of the study is to know the prevalence of the metabolic syndrome (MS), as well as to know the differences in its prevalence according to the Adult Treatment Panel of the National Cholesterol Education Program (ATP-III) and World Health Organization (WHO) criteria. PATIENTS AND METHOD: Cross-sectional descriptive study performed in primary care in population of both sexes aged between 40 and 74 years. Variables studied were risk factors as well as each one of the components of MS, according to both definitions. RESULTS: We studied 358 patients, 161 (45%) men and 197 women. The prevalence of MS using the WHO criteria was 17.9% and according with the ATP-III criteria it was 23.5%. The prevalence increased with age and the body mass index. Both definitions agreed in the classification of MS in 80% of cases (kappa = 0.38). If we considered the definition of MS according to the WHO taken as the "gold standard", the ATP-III definition displays a sensitivity of 59.4%, specificity of 84.4% and negative predictive value of 90.5%. The agreement is greater in women and older than 60 years. CONCLUSIONS: The prevalence of MS is smaller with the WHO criteria. The agreement between both methods is scarce and the clinical application of the ATP-III criteria in primary care needs its homologation with clinic-epidemiological studies.

Diferencias en la prevalencia del síndrome metabólico según las definiciones del ATP-III y la OMS / Differences in the prevalence of metabolic syndrome according to the ATP-III and WHO definitions

FUNDAMENTO Y OBJETIVO: El objetivo del estudio fue conocer y comparar las diferencias en la prevalencia del síndrome metabólico (SM) estimada según las definiciones del Adult Treatment Panel III the National Cholesterol Education Program (ATP-III) y de la Organización Mundial dela Salud (OMS).PACIENTES Y MÉTODO: Estudio descriptivo transversal en atención primaria, en población de 40 a74 años. Se estudiaron los factores de riesgo así como cada uno de los componentes del SM, según ambas definiciones. RESULTADOS: Estudiamos a 358 pacientes, 161 (45%) varones y 197 mujeres. La prevalencia del SM según criterios de la OMS fue del 17,9% y según los del ATP-III, del 23,5%. Esta prevalencia aumenta con la edad y con el índice de masa corporal. Ambas definiciones coinciden en la clasificación en el 80% de los casos (índice de kappa = 0,38). Considerando de referencia la definición de la OMS, el ATP-III presenta una sensibilidad del 59,4%, una especificidad del 84,4% y un valor predictivo negativo del 90,5%, y la concordancia mayor en mujeres y en pacientes mayores de 60 años. CONCLUSIONES: La prevalencia del SM es menor con los criterios de la OMS. La concordancia entre los criterios de la OMS y los del ATP III es escasa. La aplicación clínica de los criterios del ATP-III en atención primaria precisa su homologación con estudios clinic epidemiológicos

BACKGROUND AND OBJECTIVE: The objective of the study is to know the prevalence of the metabolic syndrome (MS), as well as to know the differences in its prevalence according to the Adult Treatment Panel of the National Cholesterol Education Program (ATP-III) and World Health Organization(WHO) criteria. PATIENTS AND METHOD: Cross-sectional descriptive study performed in primary care in population f both sexes aged between 40 and 74 years. Variables studied were risk factors as well as each one of the components of MS, according to both definitions. RESULTS: We studied 358 patients, 161 (45%) men and 197 women. The prevalence of MSusing the WHO criteria was 17.9% and according with the ATP-III criteria it was 23,5%. The prevalence increased with age and the body mass index. Both definitions agreed in the classification of MS in 80% of cases (kappa = 0.38). If we considered the definition of MS according to the WHO taken as the «gold standard», the ATP-III definition displays a sensitivity of59.4%, specificity of 84.4% and negative predictive value of 90.5%. The agreement is greater in women and older than 60 years. CONCLUSIONS: The prevalence of MS is smaller with the WHO criteria. The agreement between both methods is scarce and the clinical application of the ATP-III criteria in primary care needs its homologation with clinic-epidemiologal studies

[Comparison of the SCORE and Framingham models in calculating high cardiovascular risk for a sample of males within the 45-65 age range in Asturias, Spain]. / Comparación de los modelos SCORE y Framinghan en el cálculo de alto riesgo cardiovascular para una muestra de varones de 45 y 65 años de Asturias.

BACKGROUND: The Spanish Interdisciplinary Committee for Cardiovascular Prevention has recently drafted a consensus for adapting the European Cardiovascular Prevention Guide to the Spanish population, using SCORE as the risk-calculation method. This study is aimed as ascertaining the differences involved in changing over from the Framingham to the SCORE criterion in the classification of males within the high-risk group. METHODS: Descriptive cross-sectional study conducted in primary care. A total of 379 males within the 45-65 age range, corresponding to four (4) groups from general practitioners from three healthcare centers in the Principality of Asturias. MAIN MEASUREMENTS: calculation of the cardiovascular risk and high-risk prevalence by the conventional Framingham method and according to SCORE. High-risk prevalence curve estimated by logic regression. RESULTS: The high-risk prevalence according to the Framingham equation was 24% (CI95%=19.9-28.7) and was 17.9% (CI95%=14.3-22.3) for SCORE, the difference being statistically significant (p=0.02). The SCORE model shows lower prevalences among subjects under age 60 and higher for those over age 60. Among male smokers, SCORE shows lower prevalences among individuals under 58 years of age, the high-risk males with Framingham and low-risk with SCORE being younger, smokers and having lower average blood pressure figures and moderate cholesterol figures. CONCLUSIONS: On applying the SCORE model, we classify fewer males as high-risk, especially among those under 58 years of age who are smokers having moderate cholesterol figures than when the Framingham scale is used.