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dc.contributor.authorKynde, Iben
dc.contributor.authorHeitmann, Berit L.
dc.contributor.authorBygbjerg, Ib C.
dc.contributor.authorAndersen, Lars Bo
dc.contributor.authorHelge, Jørn W.
dc.date.accessioned2010-01-14T12:40:30Z
dc.date.issued2009-08-27
dc.identifierSeksjon for idrettsmedisinske fag / Department of Sports Medicine
dc.identifier.citationMetabolism: Clinical and Experimental. 2009, 58(12), 1817-1824en
dc.identifier.issn0026-0495
dc.identifier.urihttp://hdl.handle.net/11250/170857
dc.descriptionI Brage finner du siste tekst-versjon av artikkelen, og den kan inneholde ubetydelige forskjeller fra forlagets pdf-versjon. Forlagets pdf-versjon finner du på www.sciencedirect.com: http://dx.doi.org/10.1016/j.metabol.2009.06.014 / In Brage you'll find the final text version of the article, and it may contain insignificant differences from the journal's pdf version. The original publication is available at www.sciencedirect.com: http://dx.doi.org/10.1016/j.metabol.2009.06.014en
dc.description.abstractPrognostic biomarkers are needed to identify children at increased cardiometabolic risk. The objective was to study whether markers of metabolism and inflammation, for example, circulating plasma adiponectin, leptin, interleukin-8, and hepatocyte growth factor, are associated with cardiometabolic risk factors in childhood and adolescence. This was a cross-sectional and prospective study, and the setting was the Danish part of the European Youth Heart Studies I and II. Participants were randomly selected girls and boys 8 to 10 years of age with complete baseline data (n = 256) and complete follow-up data 6 years later (n = 169). Cardiometabolic risk profile was calculated using a continuous composite score derived from summing of 6 factors standardized to the sample means (Z scores): body mass index, homeostasis model assessment of insulin resistance, total serum cholesterol to serum high-density lipoprotein cholesterol ratio, serum triglycerides, systolic blood pressure, and the reciprocal value of fitness (maximum watts per kilogram). Overweight was defined using international classification of body mass index cutoff points for children. Plasma adiponectin, leptin, interleukin-8, and hepatocyte growth factor were assessed using immunochemical assays. Linear relationships were found between metabolic risk score and both plasma adiponectin (inverse, P = .02) and plasma leptin (P b .0001) at baseline after adjustment for several confounders. In overweight but not normal-weight children, plasma adiponectin at baseline was inversely associated with metabolic risk score 6 years later (P = .04). In childhood, both hypoadiponectinemia and hyperleptinemia accompany a negative metabolic risk profile. In addition, circulating plasma adiponectin may be a useful biomarker to identify overweight children at greater future risk of the cardiometabolic adverse effects of overweight.en
dc.format.extent213012 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoengen
dc.publisherElsevieren
dc.subjectadiponectin deficiencyen
dc.subjectadolescenten
dc.subjectblood pressureen
dc.subjectbody mass indexen
dc.subjectchilden
dc.subjectcytokinesen
dc.subjectDenmarken
dc.subjectdisease progressionen
dc.subjectfemaleen
dc.subjecthepatocyte growth factoren
dc.subjecthumansen
dc.subjectinsulin resistanceen
dc.subjectinterleukin-8en
dc.subjectleptinen
dc.subjectlipidsen
dc.subjectmaleen
dc.subjectmetabolic diseasesen
dc.subjectoverweighten
dc.subjectregression analysisen
dc.subjectrisk assessmenten
dc.subjectphysiology
dc.subjectmetabolism
dc.subjectepidemiology
dc.subjectblood
dc.titleHypoadiponectinemia in overweight children contributes to a negative metabolic risk profile 6 years lateren
dc.typePeer revieweden
dc.typeJournal articleen
dc.subject.nsiVDP::Medical disciplines: 700en
dc.source.pagenumber1817-1824en
dc.source.volume58en
dc.source.journalMetabolism: Clinical and Experimentalen
dc.source.issue12en


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