BACKGROUND: Factor analyses suggest that the structure underlying metabolic syndrome is similar in adolescents and adults. However, adolescence is a period of intense physiological change, and therefore stability of the underlying metabolic structure and clinical categorization based on metabolic risk is uncertain. METHODS AND RESULTS: We analyzed data from 1098 participants in the Princeton School District Study, a school-based study begun in 2001-2002, who were followed up for 3 years. We performed factor analyses of 8 metabolic risks at baseline and follow-up to assess stability of factor patterns and clinical categorization of metabolic syndrome. Metabolic syndrome was defined using the current American Heart Association/National Heart, Lung, and Blood Institute definition for adults (AHA), a modified AHA definition used in prior pediatric metabolic syndrome studies (pediatric AHA), and the International Diabetes Federation (IDF) guidelines. We found that factor structures were essentially identical at both time points. However, clinical categorization was not stable. Approximately half of adolescents with baseline metabolic syndrome lost the diagnosis at follow-up regardless of the definitions used: pediatric AHA=56% (95% confidence interval [CI], 42% to 69%), AHA=49% (95% CI, 32% to 66%), IDF=53% (95% CI, 38% to 68%). In addition to loss of the diagnosis, new cases were identified. Cumulative incidence rates were as follows: pediatric AHA=3.8% (95% CI, 2.8% to 5.2%); AHA=4.4% (95% CI, 3.3% to 5.9%); IDF=5.2% (95% CI, 4.0% to 6.8%). CONCLUSIONS: During adolescence, metabolic risk factor clustering is consistent. However, marked instability exists in the categorical diagnosis of metabolic syndrome. This instability, which includes both gain and loss of the diagnosis, suggests that the syndrome has reduced clinical utility in adolescence and that metabolic syndrome-specific pharmacotherapy for youth may be premature.
BACKGROUND: Factor analyses suggest that the structure underlying metabolic syndrome is similar in adolescents and adults. However, adolescence is a period of intense physiological change, and therefore stability of the underlying metabolic structure and clinical categorization based on metabolic risk is uncertain. METHODS AND RESULTS: We analyzed data from 1098 participants in the Princeton School District Study, a school-based study begun in 2001-2002, who were followed up for 3 years. We performed factor analyses of 8 metabolic risks at baseline and follow-up to assess stability of factor patterns and clinical categorization of metabolic syndrome. Metabolic syndrome was defined using the current American Heart Association/National Heart, Lung, and Blood Institute definition for adults (AHA), a modified AHA definition used in prior pediatric metabolic syndrome studies (pediatric AHA), and the International Diabetes Federation (IDF) guidelines. We found that factor structures were essentially identical at both time points. However, clinical categorization was not stable. Approximately half of adolescents with baseline metabolic syndrome lost the diagnosis at follow-up regardless of the definitions used: pediatric AHA=56% (95% confidence interval [CI], 42% to 69%), AHA=49% (95% CI, 32% to 66%), IDF=53% (95% CI, 38% to 68%). In addition to loss of the diagnosis, new cases were identified. Cumulative incidence rates were as follows: pediatric AHA=3.8% (95% CI, 2.8% to 5.2%); AHA=4.4% (95% CI, 3.3% to 5.9%); IDF=5.2% (95% CI, 4.0% to 6.8%). CONCLUSIONS: During adolescence, metabolic risk factor clustering is consistent. However, marked instability exists in the categorical diagnosis of metabolic syndrome. This instability, which includes both gain and loss of the diagnosis, suggests that the syndrome has reduced clinical utility in adolescence and that metabolic syndrome-specific pharmacotherapy for youth may be premature.
Authors: Hanna-Maaria Lakka; David E Laaksonen; Timo A Lakka; Leo K Niskanen; Esko Kumpusalo; Jaakko Tuomilehto; Jukka T Salonen Journal: JAMA Date: 2002-12-04 Impact factor: 56.272
Authors: Costan G Magnussen; Juha Koskinen; Wei Chen; Russell Thomson; Michael D Schmidt; Sathanur R Srinivasan; Mika Kivimäki; Noora Mattsson; Mika Kähönen; Tomi Laitinen; Leena Taittonen; Tapani Rönnemaa; Jorma S A Viikari; Gerald S Berenson; Markus Juonala; Olli T Raitakari Journal: Circulation Date: 2010-10-04 Impact factor: 29.690
Authors: Véronique L Roger; Alan S Go; Donald M Lloyd-Jones; Emelia J Benjamin; Jarett D Berry; William B Borden; Dawn M Bravata; Shifan Dai; Earl S Ford; Caroline S Fox; Heather J Fullerton; Cathleen Gillespie; Susan M Hailpern; John A Heit; Virginia J Howard; Brett M Kissela; Steven J Kittner; Daniel T Lackland; Judith H Lichtman; Lynda D Lisabeth; Diane M Makuc; Gregory M Marcus; Ariane Marelli; David B Matchar; Claudia S Moy; Dariush Mozaffarian; Michael E Mussolino; Graham Nichol; Nina P Paynter; Elsayed Z Soliman; Paul D Sorlie; Nona Sotoodehnia; Tanya N Turan; Salim S Virani; Nathan D Wong; Daniel Woo; Melanie B Turner Journal: Circulation Date: 2011-12-15 Impact factor: 29.690
Authors: Véronique L Roger; Alan S Go; Donald M Lloyd-Jones; Robert J Adams; Jarett D Berry; Todd M Brown; Mercedes R Carnethon; Shifan Dai; Giovanni de Simone; Earl S Ford; Caroline S Fox; Heather J Fullerton; Cathleen Gillespie; Kurt J Greenlund; Susan M Hailpern; John A Heit; P Michael Ho; Virginia J Howard; Brett M Kissela; Steven J Kittner; Daniel T Lackland; Judith H Lichtman; Lynda D Lisabeth; Diane M Makuc; Gregory M Marcus; Ariane Marelli; David B Matchar; Mary M McDermott; James B Meigs; Claudia S Moy; Dariush Mozaffarian; Michael E Mussolino; Graham Nichol; Nina P Paynter; Wayne D Rosamond; Paul D Sorlie; Randall S Stafford; Tanya N Turan; Melanie B Turner; Nathan D Wong; Judith Wylie-Rosett Journal: Circulation Date: 2010-12-15 Impact factor: 29.690
Authors: Aaron S Kelly; Julia Steinberger; David R Jacobs; Ching-Ping Hong; Antoinette Moran; Alan R Sinaiko Journal: Int J Pediatr Obes Date: 2010-11-11