Diabetes, Metabolic Syndrome and Obesity (Sep 2020)
Association of Metabolic Syndrome and Hyperferritinemia in Patients at Cardiovascular Risk
Abstract
Ricardo José Tofano,1,2 Leticia Maria Pescinni-Salzedas,1 Eduardo Federighi Baisi Chagas,2 Claudia Rucco Penteado Detregiachi,2 Elen Landgraf Guiguer,1– 3 Adriano Cressoni Araujo,1,2 Marcelo Dib Bechara,1 Claudio José Rubira,1 Sandra Maria Barbalho1– 3 1Department of Biochemistry and Pharmacology, School of Medicine, University of Marília (UNIMAR), Marília, São Paulo, Brazil; 2Postgraduate Program in Structural and Functional Interactions in Rehabilitation, UNIMAR, Marília, São Paulo, Brazil; 3School of Food and Technology of Marilia (FATEC), Marilia, São Paulo, BrazilCorrespondence: Sandra Maria BarbalhoDepartment of Biochemistry and Pharmacology, School of Medicine, University of Marília (UNIMAR), Av. Higino Muzzi Filho 1001, Marília 15525-902, São Paulo, BrazilTel +55 14 99655-3190Email [email protected]: To evaluate the association between parameters of hyperferritinemia (HF) and metabolic syndrome (MS) in patients at cardiovascular risk.Patients and Methods: This is a cross-sectional analytical observational study that included 269 patients who attended a cardiology unit. Biochemical and anthropometric parameters were evaluated to identify the presence of HF and MS. The presence of MS was evaluated according to NCEP ATP III. Biochemical parameters (glycemia, triglycerides, HDL-c) were assessed according to the manufacturer’s protocols. Anthropometric measurements and blood pressure measurements were made by a trained professional. The chi-square (X2) test, odds ratio, normality distribution (verified by the Kolmogorov–Smirnov test), and Levene’s test were used to analyze the variables. To evaluate the effect of MS, HF, and the interaction between MS and HF, two-way analysis of variance (ANOVA) was performed based on the homogeneity of the variances, followed by Bonferroni’s post hoc comparisons. Spearman correlation analysis was performed to evaluate the relationship between quantitative variables. A multiple linear regression model was used to analyze the effect of covariables. A logistic regression model was built to analyze the variables that contribute significantly to predict the outcome (HF) using the backward method.Results: Our results showed that 57% of men and 49.5% of women presented with MS; 44% of men and 11% of women presented with HF. The presence of MS and hypertriglyceridemia increase the probability of having HF by up to 2.1 and 1.88 times, respectively, while for male sex it is increased by 6.2 times. Patients with HF have higher values of C-reactive protein, ferritin, and transferrin saturation, regardless of the presence of MS. The linear regression analysis model indicated that the variables considered in this study explain less than 30% of the variation in ferritin and that the presence of MS in men is responsible for 22% of the variation in the probability of the occurrence of HF.Conclusion: Our results show that hyperferritinemia is closely associated with the components of MS (positive correlation with glycemia, triglycerides levels, blood pressure, and waist circumference, and negative correlation with HDL-c values) in the studied population.Keywords: cardiovascular disease, hyperferritinemia, iron overload syndrome, metabolic syndrome
