scholarly journals Differential association between S100A4 levels and insulin resistance in prepubertal children and adult subjects with clinically severe obesity

2019 ◽  
Vol 6 (1) ◽  
pp. 99-106
Author(s):  
Siri D. Taxerås ◽  
María Galán ◽  
Laura Campderros ◽  
Irene Piquer‐Garcia ◽  
Silvia Pellitero ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Severe Obesity ◽  
Differential Association ◽  
Prepubertal Children ◽  
Clinically Severe Obesity

Disorders Associated With Clinically Severe Obesity: Significant Improvement After Surgical Weight Reduction

1998 ◽  
Vol 91 (12) ◽  
pp. 1143-1148 ◽  
Author(s):  
J MELISSAS ◽  
M CHRISTODOULAKIS ◽  
M SPYRIDAKIS ◽  
G SCHORETSANITIS ◽  
D MICHALOUDIS ◽  
...  
Keyword(s):  
Weight Reduction ◽  
Severe Obesity ◽  
Clinically Severe Obesity

scholarly journals Severe Obesity and Insulin Resistance due to Deletion of the Maternal Gsα Allele Is Reversed by Paternal Deletion of the Gsα Imprint Control Region

Endocrinology ◽  
2008 ◽  
Vol 149 (5) ◽  
pp. 2443-2450 ◽  
Author(s):  
Tao Xie ◽  
Min Chen ◽  
Oksana Gavrilova ◽  
Edwin W. Lai ◽  
Jie Liu ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Control Region ◽  
Severe Obesity ◽  
Imprint Control Region

scholarly journals Obstructive Sleep Apnea, Insulin Resistance, and Steatohepatitis in Severe Obesity

2009 ◽  
Vol 179 (3) ◽  
pp. 228-234 ◽  
Author(s):  
Vsevolod Y. Polotsky ◽  
Susheel P. Patil ◽  
Vladimir Savransky ◽  
Alison Laffan ◽  
Shannon Fonti ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Severe Obesity ◽  
Obstructive Sleep

Liver Steatosis in Obese Prepubertal Children: A Possible Role of Insulin Resistance

Obesity ◽  
2008 ◽  
Vol 16 (3) ◽  
pp. 677-683 ◽  
Author(s):  
Ebe D'Adamo ◽  
Mario Impicciatore ◽  
Rita Capanna ◽  
M. Loredana Marcovecchio ◽  
Fabio G. Masuccio ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Liver Steatosis ◽  
Prepubertal Children

scholarly journals Adiposity indices in the prediction of insulin resistance in prepubertal Colombian children

2012 ◽  
Vol 16 (2) ◽  
pp. 248-255 ◽  
Author(s):  
Noel T Mueller ◽  
Mark A Pereira ◽  
Adriana Buitrago-Lopez ◽  
Diana C Rodríguez ◽  
Alvaro E Duran ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Waist Circumference ◽  
Area Under The Curve ◽  
Skinfold Thickness ◽  
Model Assessment ◽  
Height Ratio ◽  
Prepubertal Children ◽  
Stepwise Selection ◽  
Waist To Height Ratio ◽  
Age And Sex

AbstractObjectiveTo 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.DesignWe 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.SettingBucaramanga, Colombia.SubjectsChildren (n 1261) aged 6–10 years in Tanner stage 1 from a population-based study.ResultsA 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).ConclusionsASF 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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