Serum uric acid predicts incident metabolic syndrome in the elderly in an analysis of the Brisighella Heart Study

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Arrigo Francesco Giuseppe Cicero
Federica Fogacci
Marina Giovannini
Elisa Grandi
Martina Rosticci
Sergio D’Addato
Claudio Borghi
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[1] Sant’Orsola-Malpighi University Hospital,Hypertension and Atherosclerosis Research Group, Medical and Surgical Sciences Department
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Scientific Reports | / 8卷
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Several epidemiological studies report a positive correlation between hyperuricemia and metabolic syndrome (MetS) in adults, which hyperuricemic subjects seem to more easily develop. We aimed to verify if serum uric acid (SUA) concentrations were positively associated with MetS prevalence and middle-term (4-year) incidence in older overall healthy subjects. We also purposed to identify which SUA cut-off values could be functional in MetS diagnosis in addition to the traditionally used parameters. For this reason, we selected from the historical cohort of the Brisighella Heart Study 923 older healthy subjects repeatedly visited during the 2008 and 2012 population surveys. In our sample, MetS was more frequent for higher SUA concentrations rather than the population’s mean in both men [OR = 2.12, 95%C.I.(1.55, 2.90)] and women [OR = 2.69,95%C.I.(1.91, 3.78)]. ROC analysis showed SUA was predictive of MetS in the whole population [AUC = 0.647, 95%C.I.(0.609, 0.686), P = 0.000001] and in both sex subgroups [men: AUC = 0.592, 95%C.I.(0.529, 654); P = 0.004; women: AUC = 0.758, 95%C.I.(0.711, 0.806), P < 0.000001], even there were sex-related differences in the best cut-off values (5.5 mg/dL for men; 4.2 mg/dL for women). Prospectively, SUA appeared predictive of middle-term (4-year) MetS incidence in the whole population (AUC = 0.604, 95%C.I.[0.518, 0.690], P = 0.029, best cut-off value = 4.7 mg/dL) and in the female group (AUC = 0,641, 95%C.I.[0.519, 0.762], P = 0.039, best cut-off value = 3.9 mg/dL) though not in the male one (P > 0.05). In conclusion, in our cohort, SUA is a frequent component of MetS, other than a middle-term predictor of newly diagnosed MetS in older women.
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