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  • Title: Adiposity indices in the prediction of insulin resistance in prepubertal Colombian children.
    Author: Mueller NT, Pereira MA, Buitrago-Lopez A, Rodríguez DC, Duran AE, Ruiz AJ, Rueda-Clausen CF, Villa-Roel C.
    Journal: Public Health Nutr; 2013 Feb; 16(2):248-55. PubMed ID: 22916737.
    Abstract:
    OBJECTIVE: To compare BMI with abdominal skinfold thickness (ASF), waist circumference and waist-to-height ratio in the prediction of insulin resistance (IR) in prepubertal Colombian children. DESIGN: We calculated age- and sex-specific Z-scores for BMI, ASF, waist circumference, waist-to-height ratio and three other skinfold-thickness sites. Logistic regression with stepwise selection (P = 0·80 for entry and P = 0·05 for retention) was performed to identify predictors of IR and extreme IR, which were determined by age- and sex-specific Z-scores to identify the ≥ 90th and ≥ 95th percentile of homeostasis model assessment (HOMAIR), respectively. We used receiver operating characteristic curves to compare the area under the curve between models. SETTING: Bucaramanga, Colombia. SUBJECTS: Children (n 1261) aged 6-10 years in Tanner stage 1 from a population-based study. RESULTS: A total of 127 children (seventy girls and fifty-seven boys) were classified with IR, including sixty-three children (thirty-three girls and thirty boys) classified with extreme IR. Only ASF and BMI Z-scores were retained as predictors of IR by stepwise selection. Adding ASF Z-score to BMI Z-score improved the area under the curve from 0·794 (95 % CI 0·752, 0·837) to 0·811 (95 % CI 0·770, 0·851; P for contrast = 0·01). In predicting extreme IR, the addition of ASF Z-score to BMI Z-score improved the area under the curve from 0·837 (95 % CI 0·790, 0·884) to 0·864 (95 % CI 0·823, 0·905; P for contrast = 0·01). CONCLUSIONS: ASF Z-score predicted IR independent of BMI Z-score in our population of prepubertal children. ASF and BMI Z-scores together improved IR risk stratification compared with BMI Z-score alone, opening new perspectives in the prediction of cardiometabolic risk in prepubertal children.
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