ABSTRACT
Katholieke Universiteit Leuven, Belgium; 3Department of Biology, University of
Madeira, Portugal; 4Department of Physical Education and Sport, University of
Madeira, Portugal
7.1 INTRODUCTION Metabolic syndrome (MetS) is characterized by a constellation of metabolic risk factors in one individual. In children and adolescents, Ferranti et al. (2004) and Cook et al. (2003) observed a high prevalence of MetS in US. Since indicators of MetS are moderately stable from childhood and adolescence into young adulthood (Katzmarzyk et al. 2001) and that, in adults, MetS is associated with an increased risk of type 2 diabetes, cardiovascular disease, and all cause mortality, it is of great importance to study the pathogenesis of MetS. Genetic factors together with physical inactivity, unhealthy diet and overweight are the root causes of MetS (Terán-Garcia and Bouchard, 2007). As far we know, no other study has examined the role of genetic and environmental factors in the development of MetS in Portuguese children and adolescents. This study will generate more information on MetS and make it possible to devise combined intervention programs to reduce these risk factors. Hence, the purpose of the current study was to examine the genetic and environmental influences in the five indicators of the MetS. 7.2 METHODS 7.2.1 Sample, metabolic syndrome and zygosity Data are from the ‘Madeira Twin-Families Study’, a cross-sectional study carried out in Autonomous Region of Madeira (ARM), Portugal. The sample comprised
207 pairs of twins, 84 MZ and 123 DZ, from 3 to 18 years of age. Pediatric MetS was defined using criteria defined by Ferranti et al. (2004). Blood fasting samples were taken from all participants in a private laboratory. The generated genotypes were analyzed in the Laboratory of Human Genetics of University of Madeira and subsequently the probability of monozygosity was calculated. Height was measured with a portable stadiometer (Siber-Hegner, GPM) to the nearest millimeter. Body mass was measured on a balance-beam scale accurate to 100 g (Seca Optima 760, Germany). WC was measured at the level of the narrowest point between the lower costal border and the iliac crest. 7.2.2 Statistical analyses All analyses were performed using STATA 10 and TWINAN92 packages. Descriptive statistics were expressed as means and standard deviations (mean ± SD). Test-retest reliability for anthropometric characteristics was estimated on the basis of the intraclass correlation coefficient (R). Indicators of MetS were adjusted for age, sex and respective interactions. Genetic factors (a2), common environment (c2) and unique environment (e2) were computed and models were compared by likelihood. The model retained was the more parsimonious. Statistical significance was chosen as p < 0.05. 7.3 RESULTS Results of homogeneity and heterogeneity between MZ and DZ twins are given in Table 7.1. MZ twins show higher intraclass correlation coefficients than DZ twins in all indicators of MetS. Heritability (a2) and common (c2) and unique environments (e2) estimates are shown in Table 7.2.
