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Home All Specialties Pediatrics

Current BMI standards may be predictive of metabolic syndrome

byBrandon ChildsandLeah Carr, MD
February 8, 2014
in Pediatrics, Public Health
Reading Time: 4 mins read
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1. BMI percentiles/cutoffs which have been established by the CDC and school based fitness program, FITNESSGRAM (FGram) can be used to identify children and adolescents with metabolic syndrome.

2. Ideal BMI thresholds for detecting metabolic syndrome established by the current study are most similar to the CDC standards for boys and the FGram standards for girls.

Evidence Rating Level: 1 (Excellent) 

Study Rundown: Currently, body mass index (BMI) percentiles established by the CDC and a school-based fitness testing program called FITNESSGRAM (FGram), which links BMI and body fat percentage, are commonly used to identify children who are overweight or obese.  Both CDC and FGram measures have unique BMI thresholds used to group individuals into weight categories. These methods have not been previously evaluated as to their effectiveness in determining if children are at risk of developing metabolic syndrome*. The authors of the current study used data from the National Health and Examination Survey (NHANES) in their goal  of detailing the diagnostic performance of FGram and CDC BMI standards while identifying children with metabolic risk. They also set out to determine ideal BMI thresholds for detecting metabolic syndrome in children and adolescents. At the study’s conclusion, about 7% of the cohort met criteria for metabolic syndrome. It was determined that both the CDC and FGram methods can be used to predict metabolic syndrome. However, ideal thresholds for metabolic syndrome identification were most similar to the CDC standard for boys and the FGram standard for girls. Limitations in this study exist as researchers did not stratify results based on race/ethnic group and the prevalence of this disease may vary among different populations. Practitioners should be aware of the usefulness of BMI percentiles as they may be helpful in identifying children/adolescents who are in need of medical intervention to prevent metabolic sequela.

Click to read the study, published today in Pediatrics

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Relevant Reading: US Preventative Services Task Force: Screening for obesity in children and adolescents

Study Author, Dr. Kelly R. Laurson, PhD, talks to 2 Minute Medicine: Illinois State University, School of Kinesiology and Recreation.  

“Body mass index (BMI) is commonly used to screen for adolescent obesity. Many clinicians and researchers use BMI, with the Centers for Disease Control (CDC) or FITNESSGRAM standards, to categorize youth as normal weight, overweight, or obese. Our goal was to evaluate the diagnostic performance of the CDC and FITNESSGRAM BMI standards in regard to metabolic syndrome. In a nationally representative sample, we found the CDC and FITNESSGRAM standards were generally similar, but with varying nuances in diagnostic performance practitioners should be aware of. For example, the CDC standards tended to have a higher true-negative rate, but a lower true-positive rate, than those of FITNESSGRAM. BMI was a powerful predictor of metabolic syndrome; <2% of normal weight adolescents had metabolic syndrome in contrast to the 20-35% prevalence in obese youth. We hope practitioners can use this information to better convey the health outcomes associated with obesity to parents and children.”

In-Depth [prospective cohort data]: Data from a total of 3385 boys and girls (ages 12 to 18) from the NHANES were included in this study. Calculated BMI scores for each participant were used for assignment into categories defined by the CDC and FGram standards. Categories were normal weight, overweight, and obese. For boys: normal weight (CDC N =1160, FGram N =1071), overweight (CDC N =N =280, FGram N =227), and obese (CDC N =345, FGram N =487). Girls: normal weight (CDC N =1006, FGram N =918), overweight (CDC N =274, FGram N =182), and obese (CDC N =320, FGram N =500). Researchers used waist circumference, blood pressure, triglycerides, HDL cholesterol, and fasting glucose measurements to determine the presence of metabolic syndrome in each participant. The prevalence of metabolic syndrome was 7.9% (95% CI 5.5-10.2) in boys and 6.7% (95% CI 4.9-8.6) in girls. In terms of detecting metabolic syndrome, sensitivities ranged from 83% to 93% for overweight thresholds among CDC and FGram standards. CDC standards had higher positive predictive values for each category and, in most cases, FGram had higher negative predictive values. Researchers used receiver operating characteristic (ROC) statistics to calculate ideal thresholds for metabolic syndrome detection. ROC analysis indicated that the 91st percentile for girls and the 97th percentile for boys were ideal cutoff points for detecting children at high risk of metabolic syndrome. These ideal thresholds were closer to CDC standards for boys and FGram standards for girls. Optimal percentiles for low-risk identification were defined at 80th percentile for girls and 87th percentile for boys.

*Metabolic syndrome is defined as a presence of 3 out of 5 of the following criteria: Abdominal obesity, high blood pressure, high triglycerides, low HDL cholesterol, and high fasting glucose.

 

More from this author: Increased cognitive activity post-concussion associated with prolonged symptom duration, Early adiposity rebound associated with worse metabolic markers, Dramatic rise of gun violence seen in PG-13 movies, Increased sleep linked to lower dietary intake in children, Multiple variables related to physical activity levels in preschool children  

©2012-2014 2minutemedicine.com. All rights reserved. No works may be reproduced without expressed written consent from 2minutemedicine.com. Disclaimer: We present factual information directly from peer reviewed medical journals. No post should be construed as medical advice and is not intended as such by the authors, editors, staff or by 2minutemedicine.com. PLEASE SEE A HEALTHCARE PROVIDER IN YOUR AREA IF YOU SEEK MEDICAL ADVICE OF ANY SORT. 

Tags: BMIFGrammetabolic syndrome
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