Metabolic syndrome across Europe: different clusters of risk factors

Angelo Scuteri, Stephane Laurent, Francesco Cucca, John Cockcroft, Pedro Guimaraes Cunha, Leocadio Rodriguez Mañas, Francesco U Mattace Raso, Maria Lorenza Muiesan, Ligita Ryliškytė, Ernst Rietzschel, James Strait, Charalambos Vlachopoulos, Henry Völzke, Edward G Lakatta, Peter M Nilsson, Metabolic Syndrome and Arteries Research (MARE) Consortium, Angelo Scuteri, Stephane Laurent, Francesco Cucca, John Cockcroft, Pedro Guimaraes Cunha, Leocadio Rodriguez Mañas, Francesco U Mattace Raso, Maria Lorenza Muiesan, Ligita Ryliškytė, Ernst Rietzschel, James Strait, Charalambos Vlachopoulos, Henry Völzke, Edward G Lakatta, Peter M Nilsson, Metabolic Syndrome and Arteries Research (MARE) Consortium

Abstract

Background: Metabolic syndrome (MetS) remains a controversial entity. Specific clusters of MetS components - rather than MetS per se - are associated with accelerated arterial ageing and with cardiovascular (CV) events. To investigate whether the distribution of clusters of MetS components differed cross-culturally, we studied 34,821 subjects from 12 cohorts from 10 European countries and one cohort from the USA in the MARE (Metabolic syndrome and Arteries REsearch) Consortium.

Methods: In accordance with the ATP III criteria, MetS was defined as an alteration three or more of the following five components: elevated glucose (G), fasting glucose ≥110 mg/dl; low HDL cholesterol, < 40mg/dl for men or <50 mg/dl for women; high triglycerides (T), ≥150 mg/dl; elevated blood pressure (B), ≥130/≥85 mmHg; abdominal obesity (W), waist circumference >102 cm for men or >88 cm for women.

Results: MetS had a 24.3% prevalence (8468 subjects: 23.9% in men vs. 24.6% in women, p < 0.001) with an age-associated increase in its prevalence in all the cohorts. The age-adjusted prevalence of the clusters of MetS components previously associated with greater arterial and CV burden differed across countries (p < 0.0001) and in men and women (p < 0.0001). In details, the cluster TBW was observed in 12% of the subjects with MetS, but was far more common in the cohorts from the UK (32.3%), Sardinia in Italy (19.6%), and Germany (18.5%) and less prevalent in the cohorts from Sweden (1.2%), Spain (2.6%), and the USA (2.5%). The cluster GBW accounted for 12.7% of subjects with MetS with higher occurrence in Southern Europe (Italy, Spain, and Portugal: 31.4, 18.4, and 17.1% respectively) and in Belgium (20.4%), than in Northern Europe (Germany, Sweden, and Lithuania: 7.6, 9.4, and 9.6% respectively).

Conclusions: The analysis of the distribution of MetS suggested that what follows under the common definition of MetS is not a unique entity rather a constellation of cluster of MetS components, likely selectively risky for CV disease, whose occurrence differs across countries.

Keywords: Blood pressure; Europe; HDL cholesterol; epidemiology; glucose; metabolic syndrome; triglycerides; waist circumference.

Conflict of interest statement

Conflict of Interest: None

© The European Society of Cardiology 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Figures

Figure 1
Figure 1
Age distribution (mean and SD) of subject enrolled in participating cohorts of the MARE Consortium
Figure 1
Figure 1
Age distribution (mean and SD) of subject enrolled in participating cohorts of the MARE Consortium
Figure 2
Figure 2
Overall prevalence of MetS in different age groups (top panel),and diabetes mellitus in participating cohorts (middle panel); gender-specific prevalence of MetS in participating cohorts (bottom panel) of the MARE Consortium
Figure 2
Figure 2
Overall prevalence of MetS in different age groups (top panel),and diabetes mellitus in participating cohorts (middle panel); gender-specific prevalence of MetS in participating cohorts (bottom panel) of the MARE Consortium
Figure 2
Figure 2
Overall prevalence of MetS in different age groups (top panel),and diabetes mellitus in participating cohorts (middle panel); gender-specific prevalence of MetS in participating cohorts (bottom panel) of the MARE Consortium
Figure 3
Figure 3
Distribution of MetS components in subjects with MetS in participating cohorts of the MARE Consortium
Figure 3
Figure 3
Distribution of MetS components in subjects with MetS in participating cohorts of the MARE Consortium
Figure 4
Figure 4
Age-adjusted prevalence of clusters of MetS components in subjects with MetS in participating cohorts of the MARE Consortium: overall prevalence (top panel), men (middle panel), women (bottom panel).
Figure 4
Figure 4
Age-adjusted prevalence of clusters of MetS components in subjects with MetS in participating cohorts of the MARE Consortium: overall prevalence (top panel), men (middle panel), women (bottom panel).

Source: PubMed

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