Literature DB >> 18457010

Metabolic risk-factor clustering estimation in obese children.

G Bueno1, L A Moreno, O Bueno, J Morales, T Pérez-Roche, J M Garagorri, M Bueno.   

Abstract

The purpose of this study was to apply the new approach for Metabolic Individual Risk-factor And Clustering Estimation (MIRACLE) score in a group of Spanish obese children and adolescents and to describe its relationship with other metabolic risk factors. 153 children with simple obesity were studied: 79 males and 74 females, mean age 11.2 +/- 2.2. Obesity was defined when BMI was higher than the age and sex specific equivalent to 30 kg/m2 in adults. MIRACLE score included: family history (early cardiovascular disease, type 2 diabetes, and hypertension), individual history (small for gestational age and ethnic origin), clinical features (BMI, waist circumference > 90th percentile and blood pressure > 95th percentile) and metabolic abnormalities (glucose intolerance or type 2 diabetes). It was assigned a value of 1 to "presence" and 0 to" absence" in every patient. The children were considered as having metabolic risk when at least 5 items were present. Triglycerides, HDL-cholesterol, apolipoprotein B, apolipoprotein A1, glucose and HOMA index, were measured too. The most frequent clinical features of MIRACLE score were: excess waist circumference (95.4%) and hypertension (41.8%). Family history criteria were frequent (55.3% for type 2 diabetes, 39.1% for hypertension and 31.3% for early cardiovascular disease). Individual risk factors were not frequent. Glucose intolerance was detected in 22.2% of the obese patients. A MIRACLE score > or = 5 was found in 37.4% of the children studied, being associated with a significant risk of dyslipidemia (triglycerides, p = 0.040; HDL-cholesterol, p = 0.006; LDL-cholesterol p = 0.038; apolipoprotein B, p = 0.008) only in females. In conclusion, the MIRACLE score is useful in order to detect metabolic risk in obese children but it seems necessary to improve the score, by including other features of the metabolic syndrome like lipid profile or indirect indicators of insulin resistance.

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Year:  2007        PMID: 18457010     DOI: 10.1007/BF03165766

Source DB:  PubMed          Journal:  J Physiol Biochem        ISSN: 1138-7548            Impact factor:   5.080


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