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Predicting cardiovascular risk in young adulthood from the metabolic syndrome, its component risk factors, and a cluster score in childhood
Author(s) -
KELLY AARON S.,
STEINBERGER JULIA,
JACOBS DAVID R.,
HONG CHINGPING,
MORAN ANTOINETTE,
SINAIKO ALAN R.
Publication year - 2011
Publication title -
international journal of pediatric obesity
Language(s) - English
Resource type - Journals
eISSN - 1747-7174
pISSN - 1747-7166
DOI - 10.3109/17477166.2010.528765
Subject(s) - medicine , metabolic syndrome , anthropometry , young adult , blood pressure , cluster (spacecraft) , insulin resistance , demography , pediatrics , obesity , sociology , computer science , programming language
Objective . The value of metabolic syndrome (MetS) in childhood and adolescence and its stability into young adulthood have been questioned. This study compared the MetS in late childhood (mean age 13) versus a cluster score of the MetS components as predictors of young adult (mean age 22) cardiovascular risk. Methods . Anthropometrics, blood pressure, lipid profile, and insulin resistance (insulin clamp) were obtained in 265 individuals at mean ages 13 and 22. The MetS was defined dichotomously by current pediatric and adult criteria. The MetS cluster score used the average of deviates of the MetS components standardized to their means and standard deviations at mean age 13. Results . The MetS was rarely present at mean age 13 and did not predict MetS at mean age 22 but identified individuals who continued to have adverse levels of risk factors at mean age 22. In contrast to the standard MetS definition, the MetS cluster score tracked strongly and at mean age 22 was significantly higher in the individuals with MetS at mean age 13 (0.78 ± 0.71) than those without MetS at mean age 13 (0.09 ± 0.70, p <0.0001). Conclusions . Although the MetS at mean age 13, using the conventional definition, is not a reliable method for predicting the MetS at mean age 22, it does predict adverse levels of cardiovascular risk factors. A cluster score, using the MetS components as continuous variables, is more reliable in predicting young adult risk from late childhood.

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