Associations between metabolic syndrome components and markers of inflammation in Welsh school children

Non Eleri Thomas, David A. Rowe, Elaine M. Murtagh, Jeffrey W. Stephens, Rhys Williams

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Abstract

We investigated the multivariate dimensionality and strength of the relationship between metabolic syndrome (MetS) and inflammation in children. Caucasian school children (N = 229; 12-14 yr) from Wales were tested on several health indicators including measures of body composition, inflammation, fasting glucose regulation, blood pressure and lipids. The multivariate associationbetween MetS and inflammation was investigated via canonical correlation analysis. Data were corrected for non-normality by log transformation, and sex-specific z-scores computed for variables where there was a significant sex difference. Structure r’s were interpreted to determine the dimensions of MetS and inflammation responsible for significant canonical variates. The overallmultivariate association between MetS and inflammation was significant (Wilks’ Lambda = 0.54, p < 0.001). The relationship was explained primarily by the waist circumference dimension of MetS (CC = 0.87) and inflammatory markers of fibrinogen (CC = 0.52) and C-reactive protein (CC = 0.50). The pattern of results was similar regardless of whether variables were adjusted for sex differences.Conclusions: Central adiposity is the strongest predictor of the inflammatory aspect of cardiovascular disease risk in Caucasian adolescents. Future research into MetS and cardiometabolic risk should consider multivariate statistical approaches, in order to identify the separate contributions of each dimension in interrelationships and to identify which dimensions are influenced by preventive interventions.
Original languageEnglish
Number of pages9
JournalEuropean Journal of Pediatrics
Early online date22 Dec 2017
DOIs
Publication statusE-pub ahead of print - 22 Dec 2017

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Keywords

  • multivariate statistics
  • adolescents
  • waist circumference
  • c-reactive protein
  • fibrinogen

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