Prevalence of metabolic syndrome in a Portuguese obese adolescent population according to three different definitions

Hugo Braga-Tavares, Helena Fonseca
European Journal of Pediatrics 2010, 169 (8): 935-40
In order to determine the prevalence of metabolic syndrome (MS) in a Portuguese pediatric overweight population according to three different sets of criteria, 237 overweight and obese adolescents were evaluated at engagement in a specific multidisciplinary program. Two of the used definitions were based on the National Cholesterol Education Program (ATPIII) guidelines modified for pediatric age and were proposed by Cook et al. (Arch Pediatr Adolesc Med 157(8):821-827, 2003) and de Ferranti et al. (Circulation 110(16):2494-2497, 2004). The third definition used resulted from a consensus of the International Diabetes Federation (IDF 2005). All of them include five components: waist circumference, blood pressure, high-density lipoprotein cholesterol, triglycerides, and fasting glucose values, with different cut-off points. Of the studied sample, 53% were girls, median age 13.4 years, 89% classified as obese, and the remaining as overweight. MS prevalence was 15.6%, 34.9%, and 8.9% according to Cook's, de Ferranti's, and IDF definitions, respectively. No adolescent fulfilled the five MS criteria, and only three (1.2%), 15 (6%), and 13 (5.1%) had no criteria at all, according to the three definitions used. Waist circumference was the most prevalent component (89.5%, 98.7%, and 93.2%), and high fasting glucose the least (1.3% for the two first and 2.5% according to the IDF definition). A significant correlation between increased body mass index and MS was found, using the two first definitions (Cook et al. p < 0.05; de Ferranti et al. p < 0.01), but not when using the third one. Considerable prevalence differences were found using three different MS criteria. It is urgent to establish a consensus on MS definition to allow early identification of adolescents at risk and the development of prospective studies to define what cut-offs are the best indicators of future morbidity.

Full Text Links

Find Full Text Links for this Article


You are not logged in. Sign Up or Log In to join the discussion.

Related Papers

Remove bar
Read by QxMD icon Read

Save your favorite articles in one place with a free QxMD account.


Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"