ABSTRACT

CIFID and Faculty of Sport, University of Porto, Porto, Portugal 8.1 INTRODUCTION Metabolic syndrome (MS) is an aggregate of cardiovascular risk factors. Different operational definitions of MS are available (Alberti et al., 2005). Yet, there is some consensus concerning a list of five putative indicators: high systolic blood pressure, high glycemia, high triglycerides, high waist girth, and low HDL cholesterol (NCEP, 2001). Metabolic syndrome has been consistently associated with significant increases of type II diabetes, cardiovascular disease and mortality (Gami et al., 2007). Its prevalence has increased over the last years not only in adults (Li and Ford, 2006), but also in children (Kim et al., 2007). In addition, physical inactivity and non-healthy nutritional habits seem to play important roles in the emergence of MS. Genetic and environmental factors are the main agents in the clustering of these five metabolic risk factors at the individual and population levels. Several lines of research with families suggest that there is a moderate-tohigh level of additive genetic effects (Poulsen et al., 2001). It is known (Fiúza et al., 2007) that the prevalence of MS of Portuguese adults is 29.4% (27.5% in males and 31.2% in females). No population information is available concerning the prevalence of MS in children, and there are no records concerning its aggregation within Portuguese families. The purposes of this study are twofold: (1) to estimate the clustering of MS in Azorean families, and (2) its genetic and environmental components. 8.2 METHODS Azores, a transcontinental archipelago, being an autonomous region of the republic of Portugal, is located in the northwest Atlantic. It consists of nine main islands. We sampled 410 subjects belonging to 133 nuclear families from Faial (n=25 families), São Miguel (n=21 families) and Pico (n=87 families) whose age, sex and parental distribution is shown in Table 8.1

Physical activity was recorded with the Bouchard 3-day dairy (Bouchard et al., 1983). All subjects attended their local Health Center for blood sampling after 10 hours of fasting conditions. Trained nurses took their blood, measured their blood pressure and waist girth. Triglycerides, C-HDL and Glycemia values were obtained from a single certified laboratory using standard procedures. Blood pressure measures were taken with an electronic device (Dinamap, BP 8800 model) using a standard protocol (Pickering et al., 2005), and waist girth was measured in accordance with suggestions made by WHO (1989). Metabolic syndrome indicators and cut-off values were defined as suggested from different sources (NCEP, 2001; Cook et al., 2003). Data analysis includes the usual descriptive statistics. Familial correlations were computed in S.A.G.E. Maximum likelihood procedures were used to estimate genetic components in each of the MS indicators using SOLAR 4.0 software. 8.3 RESULTS Correlations among family members are presented on Table 8.2 and their patterns are low (DBP) to high (C-HDL; Glucose), suggesting familial aggregation in the different indicators of the MS. The somewhat high standard errors are due to the small sample size. Heritability estimates are presented in Table 8.3, and all values are statistically significant, even when controlling for different covariates. Genetic factors account for low (DBP), moderate (GLU) and high (WG, SBP, C-HDL) percentage of the total variation at the population level. Even when controlled for physical activity levels, heritability estimates remain very similar to those shown in Table 8.3.