Comparison of metabolic syndrome prevalence using six different definitions in overweight pre-pubertal children enrolled in a weight management study.
OBJECTIVE
To assess the implications of variation in Metabolic Syndrome (MS) definition (biochemical and anthropometric indicators) on MS prevalence estimates in a population of overweight and mildly obese children.


METHODS
Cross-sectional study.


METHODS
Ninety-nine (64 girls) overweight or mildly obese, but otherwise healthy, pre-pubertal 6-9-year olds recruited for a randomized controlled trial of weight management.


METHODS
Height, weight and waist circumference were measured with BMI and waist z-scores calculated. Fasting cholesterol and fractions, glucose and insulin were measured, together with systolic and diastolic blood pressure (BP). Anthropometric and metabolic indicators were classified as normal or elevated using adult- or child-specific cut points with clustering of MS indicators also assessed using two adult and three child-specific definitions.


RESULTS
A total of 0-4% of subjects were classified with MS when adult definitions were applied. This increased to between 39 and 60% using child-specific definitions, varying according to whether hyperinsulinaemia was central to the MS classification. Systolic BP, triglycerides, total cholesterol, high-density lipoprotein cholesterol and waist z-score increased across insulin quartiles (P<0.05). The use of body mass index and waist circumference in the MS definition classified the same subjects.


CONCLUSIONS
The classification of MS in children depends strongly on the definition chosen, with MS prevalence estimates higher if insulin is part of the definition and child-specific cut points for metabolic indicators are used. Hyperinsulinaemia and MS are common consequences of childhood obesity but they are not commonly part of the assessment or management plan for weight management in children. There is a need for the establishment of normal insulin ranges and consistent definition of MS in childhood and adolescence.
Golley
R K
RK
Department of Nutrition and Dietetics, Flinders University, Adelaide, SA, Australia. gehl0002@flinders.edu.au
Magarey
A M
AM
Steinbeck
K S
KS
Baur
L A
LA
Daniels
L A
LA
D000367:Age Factors; D000886:Anthropometry; D001315:Australia / Q000453:epidemiology; D001786:Blood Glucose / Q000032:analysis; D001794:Blood Pressure; D015992:Body Mass Index; D002648:Child; D002784:Cholesterol / Q000097:blood; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D007328:Insulin / Q000097:blood; D008297:Male; D024821:Metabolic Syndrome / Q000145:classification / Q000453:epidemiology*; D050177:Overweight; D015995:Prevalence; D012680:Sensitivity and Specificity
D001786:Blood Glucose; D007328:Insulin; D002784:Cholesterol