Metabolic syndrome in a metapopulation of Croatian island isolates

Kolčić, Ivana and Vorko-Jović, Ariana and Salzer, Branka and Smoljanović, Mladen and Kern, Josipa and Vuletić, Silvije (2006) Metabolic syndrome in a metapopulation of Croatian island isolates. Croatian Medical Journal, 47 (4). pp. 585-592. ISSN 0353-9504

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Abstract

AIM: To investigate the prevalence and factors associated with the metabolic syndrome in 9 isolated populations on Adriatic islands, Croatia, and in the group of immigrants to these islands. ----- METHODS: Random samples of 100 inhabitants from each village and 101 immigrants were collected during 2002 and 2003. Bivariate and multivariate methods were used in data analysis. Age, gender, village, diet, smoking habits, physical activity, education, occupational class, and personal genetic history (a pedigree-based estimate of the individual genome-wide heterozygosity level) were used as independent variables in logistic regression. ----- RESULTS: A total of 343 (34%) examinees met criteria of the metabolic syndrome diagnosis, with significant differences in the prevalence among villages (P=0.002). Metabolic syndrome was most frequently detected on Mljet island (53%), where all examinees exhibited fasting plasma glucose over 6.1 mmol/L. Examinees with metabolic syndrome were significantly older than those without it (median age 60.0 vs 53.0; P<0.001). Women were more frequently diagnosed than men (39% vs 28%; P<0.001). The highest prevalence of the metabolic syndrome was found in the autochthonous group, whereas the lowest proportion was recorded in the admixed group (39% vs 21%, respectively, P=0.017). However, only age (odds ratio [OR], 1.06; 95% confidence intervals [CI], 1.03-1.08) and having a university degree (OR, 0.18; 95% CI 0.04-0.92) were significantly associated with metabolic syndrome in the regression model. ----- CONCLUSION: Metabolic syndrome was not associated with pedigree-based individual genome-wide heterozygosity estimate, after controlling for a number of confounding factors. More precise marker based genomic measures are needed to provide a clear answer whether metabolic syndrome development is influenced by the population genetic structure.

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