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Synergy Between Adiposity, Insulin Resistance, Metabolic Risk Factors, and Inflammation in Adolescents

OBJECTIVE: The purpose of this study was to investigate relationships between inflammatory markers and components of a metabolic syndrome cluster in adolescents. RESEARCH DESIGN AND METHODS: This was a cross-sectional analysis of an Australian childhood cohort (n = 1,377) aged 14 years. Cluster anal...

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Autores principales: Huang, Rae-Chi, Mori, Trevor A., Burke, Valerie, Newnham, John, Stanley, Fiona J., Landau, Louis I., Kendall, Garth E., Oddy, Wendy H., Beilin, Lawrence J.
Formato: Texto
Lenguaje:English
Publicado: American Diabetes Association 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2660473/
https://www.ncbi.nlm.nih.gov/pubmed/19131468
http://dx.doi.org/10.2337/dc08-1917
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author Huang, Rae-Chi
Mori, Trevor A.
Burke, Valerie
Newnham, John
Stanley, Fiona J.
Landau, Louis I.
Kendall, Garth E.
Oddy, Wendy H.
Beilin, Lawrence J.
author_facet Huang, Rae-Chi
Mori, Trevor A.
Burke, Valerie
Newnham, John
Stanley, Fiona J.
Landau, Louis I.
Kendall, Garth E.
Oddy, Wendy H.
Beilin, Lawrence J.
author_sort Huang, Rae-Chi
collection PubMed
description OBJECTIVE: The purpose of this study was to investigate relationships between inflammatory markers and components of a metabolic syndrome cluster in adolescents. RESEARCH DESIGN AND METHODS: This was a cross-sectional analysis of an Australian childhood cohort (n = 1,377) aged 14 years. Cluster analysis defined a “high-risk” group similar to adults with metabolic syndrome. Relevant measures were anthropometry, fasting insulin, glucose, lipids, inflammatory markers, liver function, and blood pressure. RESULTS: Of the children, 29% fell into a high-risk metabolic cluster group compared with 2% by a pediatric metabolic syndrome definition. Relative to the “low-risk” cluster, they had higher BMI (95% CI 19.5–19.8 vs. 24.5–25.4), waist circumference (centimeters) (95% CI 71.0–71.8 vs. 83.4–85.8), insulin (units per liter) (95% CI 1.7–1.8 vs. 3.5–3.9), homeostasis model assessment (95% CI 1.7–1.8 vs. 3.5–3.9), systolic blood pressure (millimeters of mercury) (95% CI 110.8–112.1 vs. 116.7–118.9), and triglycerides (millimoles per liter) (95% CI 0.78–0.80 vs. 1.25–1.35) and lower HDL cholesterol (millimoles per liter) (95% CI 1.44–1.48 vs. 1.20–1.26). Inflammatory and liver function markers were higher in the high-risk group: C-reactive protein (CRP) (P < 0.001), uric acid (P < 0.001), alanine aminotransferase (ALT) (P < 0.001), and γ-glutamyl transferase (GGT) (P < 0.001). The highest CRP, GGT, and ALT levels were restricted to overweight children in the high-risk group. CONCLUSIONS: Cluster analysis revealed a strikingly high proportion of 14 year olds at risk of cardiovascular disease–related metabolic disorders. Adiposity and the metabolic syndrome cluster are synergistic in the pathogenesis of inflammation. Systemic and liver inflammation in the high-risk cluster is likely to predict diabetes, cardiovascular disease, and nonalcoholic fatty liver disease.
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spelling pubmed-26604732010-04-01 Synergy Between Adiposity, Insulin Resistance, Metabolic Risk Factors, and Inflammation in Adolescents Huang, Rae-Chi Mori, Trevor A. Burke, Valerie Newnham, John Stanley, Fiona J. Landau, Louis I. Kendall, Garth E. Oddy, Wendy H. Beilin, Lawrence J. Diabetes Care Original Research OBJECTIVE: The purpose of this study was to investigate relationships between inflammatory markers and components of a metabolic syndrome cluster in adolescents. RESEARCH DESIGN AND METHODS: This was a cross-sectional analysis of an Australian childhood cohort (n = 1,377) aged 14 years. Cluster analysis defined a “high-risk” group similar to adults with metabolic syndrome. Relevant measures were anthropometry, fasting insulin, glucose, lipids, inflammatory markers, liver function, and blood pressure. RESULTS: Of the children, 29% fell into a high-risk metabolic cluster group compared with 2% by a pediatric metabolic syndrome definition. Relative to the “low-risk” cluster, they had higher BMI (95% CI 19.5–19.8 vs. 24.5–25.4), waist circumference (centimeters) (95% CI 71.0–71.8 vs. 83.4–85.8), insulin (units per liter) (95% CI 1.7–1.8 vs. 3.5–3.9), homeostasis model assessment (95% CI 1.7–1.8 vs. 3.5–3.9), systolic blood pressure (millimeters of mercury) (95% CI 110.8–112.1 vs. 116.7–118.9), and triglycerides (millimoles per liter) (95% CI 0.78–0.80 vs. 1.25–1.35) and lower HDL cholesterol (millimoles per liter) (95% CI 1.44–1.48 vs. 1.20–1.26). Inflammatory and liver function markers were higher in the high-risk group: C-reactive protein (CRP) (P < 0.001), uric acid (P < 0.001), alanine aminotransferase (ALT) (P < 0.001), and γ-glutamyl transferase (GGT) (P < 0.001). The highest CRP, GGT, and ALT levels were restricted to overweight children in the high-risk group. CONCLUSIONS: Cluster analysis revealed a strikingly high proportion of 14 year olds at risk of cardiovascular disease–related metabolic disorders. Adiposity and the metabolic syndrome cluster are synergistic in the pathogenesis of inflammation. Systemic and liver inflammation in the high-risk cluster is likely to predict diabetes, cardiovascular disease, and nonalcoholic fatty liver disease. American Diabetes Association 2009-04 2009-01-08 /pmc/articles/PMC2660473/ /pubmed/19131468 http://dx.doi.org/10.2337/dc08-1917 Text en © 2009 by the American Diabetes Association. https://creativecommons.org/licenses/by-nc-nd/3.0/Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. See http://creativecommons.org/licenses/by-nc-nd/3.0/ (https://creativecommons.org/licenses/by-nc-nd/3.0/) for details.
spellingShingle Original Research
Huang, Rae-Chi
Mori, Trevor A.
Burke, Valerie
Newnham, John
Stanley, Fiona J.
Landau, Louis I.
Kendall, Garth E.
Oddy, Wendy H.
Beilin, Lawrence J.
Synergy Between Adiposity, Insulin Resistance, Metabolic Risk Factors, and Inflammation in Adolescents
title Synergy Between Adiposity, Insulin Resistance, Metabolic Risk Factors, and Inflammation in Adolescents
title_full Synergy Between Adiposity, Insulin Resistance, Metabolic Risk Factors, and Inflammation in Adolescents
title_fullStr Synergy Between Adiposity, Insulin Resistance, Metabolic Risk Factors, and Inflammation in Adolescents
title_full_unstemmed Synergy Between Adiposity, Insulin Resistance, Metabolic Risk Factors, and Inflammation in Adolescents
title_short Synergy Between Adiposity, Insulin Resistance, Metabolic Risk Factors, and Inflammation in Adolescents
title_sort synergy between adiposity, insulin resistance, metabolic risk factors, and inflammation in adolescents
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2660473/
https://www.ncbi.nlm.nih.gov/pubmed/19131468
http://dx.doi.org/10.2337/dc08-1917
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