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Metabolically healthy and unhealthy obesity phenotypes in the general population: the FIN-D2D Survey
BACKGROUND: The aim of this work was to examine the prevalence of different metabolical phenotypes of obesity, and to analyze, by using different risk scores, how the metabolic syndrome (MetS) definition discriminates between unhealthy and healthy metabolic phenotypes in different obesity classes. M...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3198943/ https://www.ncbi.nlm.nih.gov/pubmed/21962038 http://dx.doi.org/10.1186/1471-2458-11-754 |
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author | Pajunen, Pia Kotronen, Anna Korpi-Hyövälti, Eeva Keinänen-Kiukaanniemi, Sirkka Oksa, Heikki Niskanen, Leo Saaristo, Timo Saltevo, Juha T Sundvall, Jouko Vanhala, Mauno Uusitupa, Matti Peltonen, Markku |
author_facet | Pajunen, Pia Kotronen, Anna Korpi-Hyövälti, Eeva Keinänen-Kiukaanniemi, Sirkka Oksa, Heikki Niskanen, Leo Saaristo, Timo Saltevo, Juha T Sundvall, Jouko Vanhala, Mauno Uusitupa, Matti Peltonen, Markku |
author_sort | Pajunen, Pia |
collection | PubMed |
description | BACKGROUND: The aim of this work was to examine the prevalence of different metabolical phenotypes of obesity, and to analyze, by using different risk scores, how the metabolic syndrome (MetS) definition discriminates between unhealthy and healthy metabolic phenotypes in different obesity classes. METHODS: The Finnish type 2 diabetes (FIN-D2D) survey, a part of the larger implementation study, was carried out in 2007. The present cross-sectional analysis comprises 2,849 individuals aged 45-74 years. The MetS was defined with the new Harmonization definition. Cardiovascular risk was estimated with the Framingham and SCORE risk scores. Diabetes risk was assessed with the FINDRISK score. Non-alcoholic fatty liver disease (NAFLD) was estimated with the NAFLD score. Participants with and without MetS were classified in different weight categories and analysis of regression models were used to test the linear trend between body mass index (BMI) and various characteristics in individuals with and without MetS; and interaction between BMI and MetS. RESULTS: A metabolically healthy but obese phenotype was observed in 9.2% of obese men and in 16.4% of obese women. The MetS-BMI interaction was significant for fasting glucose, 2-hour plasma glucose, fasting plasma insulin and insulin resistance (HOMA-IR)(p < 0.001 for all). The prevalence of total diabetes (detected prior to or during survey) was 37.0% in obese individuals with MetS and 4.3% in obese individuals without MetS (p < 0.001). MetS-BMI interaction was significant (p < 0.001) also for the Framingham 10 year CVD risk score, NAFLD score and estimated liver fat %, indicating greater effect of increasing BMI in participants with MetS compared to participants without MetS. The metabolically healthy but obese individuals had lower 2-hour postload glucose levels (p = 0.0030), lower NAFLD scores (p < 0.001) and lower CVD risk scores (Framingham, p < 0.001; SCORE, p = 0.002) than normal weight individuals with MetS. CONCLUSIONS: Undetected Type 2 diabetes was more prevalent among those with MetS irrespective of the BMI class and increasing BMI had a significantly greater effect on estimates of liver fat and future CVD risk among those with MetS compared with participants without MetS. A healthy obese phenotype was associated with a better metabolic profile than observed in normal weight individuals with MetS. |
format | Online Article Text |
id | pubmed-3198943 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-31989432011-10-23 Metabolically healthy and unhealthy obesity phenotypes in the general population: the FIN-D2D Survey Pajunen, Pia Kotronen, Anna Korpi-Hyövälti, Eeva Keinänen-Kiukaanniemi, Sirkka Oksa, Heikki Niskanen, Leo Saaristo, Timo Saltevo, Juha T Sundvall, Jouko Vanhala, Mauno Uusitupa, Matti Peltonen, Markku BMC Public Health Research Article BACKGROUND: The aim of this work was to examine the prevalence of different metabolical phenotypes of obesity, and to analyze, by using different risk scores, how the metabolic syndrome (MetS) definition discriminates between unhealthy and healthy metabolic phenotypes in different obesity classes. METHODS: The Finnish type 2 diabetes (FIN-D2D) survey, a part of the larger implementation study, was carried out in 2007. The present cross-sectional analysis comprises 2,849 individuals aged 45-74 years. The MetS was defined with the new Harmonization definition. Cardiovascular risk was estimated with the Framingham and SCORE risk scores. Diabetes risk was assessed with the FINDRISK score. Non-alcoholic fatty liver disease (NAFLD) was estimated with the NAFLD score. Participants with and without MetS were classified in different weight categories and analysis of regression models were used to test the linear trend between body mass index (BMI) and various characteristics in individuals with and without MetS; and interaction between BMI and MetS. RESULTS: A metabolically healthy but obese phenotype was observed in 9.2% of obese men and in 16.4% of obese women. The MetS-BMI interaction was significant for fasting glucose, 2-hour plasma glucose, fasting plasma insulin and insulin resistance (HOMA-IR)(p < 0.001 for all). The prevalence of total diabetes (detected prior to or during survey) was 37.0% in obese individuals with MetS and 4.3% in obese individuals without MetS (p < 0.001). MetS-BMI interaction was significant (p < 0.001) also for the Framingham 10 year CVD risk score, NAFLD score and estimated liver fat %, indicating greater effect of increasing BMI in participants with MetS compared to participants without MetS. The metabolically healthy but obese individuals had lower 2-hour postload glucose levels (p = 0.0030), lower NAFLD scores (p < 0.001) and lower CVD risk scores (Framingham, p < 0.001; SCORE, p = 0.002) than normal weight individuals with MetS. CONCLUSIONS: Undetected Type 2 diabetes was more prevalent among those with MetS irrespective of the BMI class and increasing BMI had a significantly greater effect on estimates of liver fat and future CVD risk among those with MetS compared with participants without MetS. A healthy obese phenotype was associated with a better metabolic profile than observed in normal weight individuals with MetS. BioMed Central 2011-10-01 /pmc/articles/PMC3198943/ /pubmed/21962038 http://dx.doi.org/10.1186/1471-2458-11-754 Text en Copyright ©2011 Pajunen et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Pajunen, Pia Kotronen, Anna Korpi-Hyövälti, Eeva Keinänen-Kiukaanniemi, Sirkka Oksa, Heikki Niskanen, Leo Saaristo, Timo Saltevo, Juha T Sundvall, Jouko Vanhala, Mauno Uusitupa, Matti Peltonen, Markku Metabolically healthy and unhealthy obesity phenotypes in the general population: the FIN-D2D Survey |
title | Metabolically healthy and unhealthy obesity phenotypes in the general population: the FIN-D2D Survey |
title_full | Metabolically healthy and unhealthy obesity phenotypes in the general population: the FIN-D2D Survey |
title_fullStr | Metabolically healthy and unhealthy obesity phenotypes in the general population: the FIN-D2D Survey |
title_full_unstemmed | Metabolically healthy and unhealthy obesity phenotypes in the general population: the FIN-D2D Survey |
title_short | Metabolically healthy and unhealthy obesity phenotypes in the general population: the FIN-D2D Survey |
title_sort | metabolically healthy and unhealthy obesity phenotypes in the general population: the fin-d2d survey |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3198943/ https://www.ncbi.nlm.nih.gov/pubmed/21962038 http://dx.doi.org/10.1186/1471-2458-11-754 |
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