Utility of waist circumference percentile for risk evaluation in obese children.
OBJECTIVE
Increased waist circumference has been shown to contribute to cardiovascular risk in obese adults. This study was designed to examine whether routinely assessing waist circumference in obese children adds predictive value for the development of diabetes and other cardiovascular risk factors.


METHODS
This is a cross-sectional study on a community sample of 188 apparently healthy obese children 7-11 years, 60% black, 39% male. Anthropometry, fasting lipid profile, oral glucose tolerance test, and magnetic resonance imaging of abdominal fat were done. High waist circumference was defined as > or = 90(th) percentile for age and sex. Statistical analyses were done to examine the relationship between waist circumference and the different cardiovascular risk factors.


RESULTS
Those with a high waist circumference had significantly lower high-density lipoprotein, higher triglycerides, fasting insulin, insulin response to glucose, subcutaneous and visceral abdominal fat than those with a normal waist circumference. Children with a high waist circumference were 3.6 times more likely than those with a normal waist status to have a low high-density lipoprotein level, 3.0 times more likely to have high triglycerides, and 3.7 times more likely to have a high fasting insulin level.


CONCLUSIONS
Obese children with waist circumference at or above the 90th percentile are at higher risk for dyslipidemia and insulin resistance than obese children with normal waist circumference. These results indicate that routine waist circumference evaluation in obese children may help clinicians identify which obese children are at greater risk of diabetes and other cardiovascular disease.
Bassali
Reda
R
Georgia Prevention Institute, Pediatrics, Medical College of Georgia, Augusta, USA. rbassali@mcg.edu
Waller
Jennifer L
JL
Gower
Barbara
B
Allison
Jerry
J
Davis
Catherine L
CL
D050153:Abdominal Fat / Q000473:pathology; D050154:Adiposity; D000886:Anthropometry; D001786:Blood Glucose / Q000378:metabolism; D002318:Cardiovascular Diseases / Q000097:blood / Q000209:etiology* / Q000473:pathology / Q000503:physiopathology; D002648:Child; D003430:Cross-Sectional Studies; D003920:Diabetes Mellitus / Q000097:blood / Q000209:etiology* / Q000473:pathology / Q000503:physiopathology; D005260:Female; D005845:Georgia; D005951:Glucose Tolerance Test; D006801:Humans; D007328:Insulin / Q000097:blood; D007333:Insulin Resistance; D008055:Lipids / Q000097:blood; D016015:Logistic Models; D008279:Magnetic Resonance Imaging; D008297:Male; D009765:Obesity / Q000097:blood / Q000150:complications / Q000175:diagnosis* / Q000473:pathology / Q000503:physiopathology; D011237:Predictive Value of Tests; D018570:Risk Assessment; D012307:Risk Factors; D055105:Waist Circumference
D001786:Blood Glucose; D007328:Insulin; D008055:Lipids