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Dissecting metabolic syndrome components: data from an epidemiologic survey in a genetic isolate

The metabolic syndrome (MetS) is a large-scale and expanding public-health and clinical threat worldwide. We investigated the determinants of MetS, assessed its prevalence and components and, estimated their genetic contribution, taking advantage of the special characteristics of Sardinian isolated...

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Autores principales: Biino, Ginevra, Concas, Maria Pina, Cena, Hellas, Parracciani, Debora, Vaccargiu, Simona, Cosso, Massimiliano, Marras, Francesca, D’Esposito, Vittoria, Beguinot, Francesco, Pirastu, Mario
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4493262/
https://www.ncbi.nlm.nih.gov/pubmed/26180744
http://dx.doi.org/10.1186/s40064-015-1049-9
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author Biino, Ginevra
Concas, Maria Pina
Cena, Hellas
Parracciani, Debora
Vaccargiu, Simona
Cosso, Massimiliano
Marras, Francesca
D’Esposito, Vittoria
Beguinot, Francesco
Pirastu, Mario
author_facet Biino, Ginevra
Concas, Maria Pina
Cena, Hellas
Parracciani, Debora
Vaccargiu, Simona
Cosso, Massimiliano
Marras, Francesca
D’Esposito, Vittoria
Beguinot, Francesco
Pirastu, Mario
author_sort Biino, Ginevra
collection PubMed
description The metabolic syndrome (MetS) is a large-scale and expanding public-health and clinical threat worldwide. We investigated the determinants of MetS, assessed its prevalence and components and, estimated their genetic contribution, taking advantage of the special characteristics of Sardinian isolated populations. Inhabitants of 10 villages in Ogliastra region participated in a cross-sectional survey in 2002–2008 (n = 9,647). Blood samples, blood pressure (BP), anthropometry and, data from a standardized interview were collected. Prevalence of MetS was estimated by the direct method of standardization. Variables associated with the MetS were identified using multilevel logistic regression. Heritability was determined using variance component models. MetS Prevalence was 19.6% (95% CI 18.9–20.4%) according to NCEP-ATPIII, 24.8% (95% CI 24.0–25.6%) according to IDF and, 29% (95% CI 28.1–29.8%) according to AHA/NHLBI harmonized criteria, ranging from 9 to 26% among villages. The most prevalent combination was BP + HDL-cholesterol (HDL) + triglycerides (TRIG) (19%), followed by BP + HDL + waist circumference (WAIST) (17%) and, BP + HDL + TRIG + WAIST (13.6%). Heritability of MetS was 48% (p = 1.62 × 10(−25)), as the two most common combinations (BP + HDL + TRIG and BP + HDL + WAIST) showed heritability of 53 and 52%, respectively. The larger genetic components of the two most frequent combinations determining MetS deserve greater investigation in order to understand the underlying mechanisms. Besides, further studies are warranted to confirm these findings both in isolated and outbred populations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40064-015-1049-9) contains supplementary material, which is available to authorized users.
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spelling pubmed-44932622015-07-15 Dissecting metabolic syndrome components: data from an epidemiologic survey in a genetic isolate Biino, Ginevra Concas, Maria Pina Cena, Hellas Parracciani, Debora Vaccargiu, Simona Cosso, Massimiliano Marras, Francesca D’Esposito, Vittoria Beguinot, Francesco Pirastu, Mario Springerplus Research The metabolic syndrome (MetS) is a large-scale and expanding public-health and clinical threat worldwide. We investigated the determinants of MetS, assessed its prevalence and components and, estimated their genetic contribution, taking advantage of the special characteristics of Sardinian isolated populations. Inhabitants of 10 villages in Ogliastra region participated in a cross-sectional survey in 2002–2008 (n = 9,647). Blood samples, blood pressure (BP), anthropometry and, data from a standardized interview were collected. Prevalence of MetS was estimated by the direct method of standardization. Variables associated with the MetS were identified using multilevel logistic regression. Heritability was determined using variance component models. MetS Prevalence was 19.6% (95% CI 18.9–20.4%) according to NCEP-ATPIII, 24.8% (95% CI 24.0–25.6%) according to IDF and, 29% (95% CI 28.1–29.8%) according to AHA/NHLBI harmonized criteria, ranging from 9 to 26% among villages. The most prevalent combination was BP + HDL-cholesterol (HDL) + triglycerides (TRIG) (19%), followed by BP + HDL + waist circumference (WAIST) (17%) and, BP + HDL + TRIG + WAIST (13.6%). Heritability of MetS was 48% (p = 1.62 × 10(−25)), as the two most common combinations (BP + HDL + TRIG and BP + HDL + WAIST) showed heritability of 53 and 52%, respectively. The larger genetic components of the two most frequent combinations determining MetS deserve greater investigation in order to understand the underlying mechanisms. Besides, further studies are warranted to confirm these findings both in isolated and outbred populations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40064-015-1049-9) contains supplementary material, which is available to authorized users. Springer International Publishing 2015-07-07 /pmc/articles/PMC4493262/ /pubmed/26180744 http://dx.doi.org/10.1186/s40064-015-1049-9 Text en © Biino et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research
Biino, Ginevra
Concas, Maria Pina
Cena, Hellas
Parracciani, Debora
Vaccargiu, Simona
Cosso, Massimiliano
Marras, Francesca
D’Esposito, Vittoria
Beguinot, Francesco
Pirastu, Mario
Dissecting metabolic syndrome components: data from an epidemiologic survey in a genetic isolate
title Dissecting metabolic syndrome components: data from an epidemiologic survey in a genetic isolate
title_full Dissecting metabolic syndrome components: data from an epidemiologic survey in a genetic isolate
title_fullStr Dissecting metabolic syndrome components: data from an epidemiologic survey in a genetic isolate
title_full_unstemmed Dissecting metabolic syndrome components: data from an epidemiologic survey in a genetic isolate
title_short Dissecting metabolic syndrome components: data from an epidemiologic survey in a genetic isolate
title_sort dissecting metabolic syndrome components: data from an epidemiologic survey in a genetic isolate
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4493262/
https://www.ncbi.nlm.nih.gov/pubmed/26180744
http://dx.doi.org/10.1186/s40064-015-1049-9
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