dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-27T11:28:10Z
dc.date.available2014-05-27T11:28:10Z
dc.date.created2014-05-27T11:28:10Z
dc.date.issued2013-01-16
dc.identifierNutrition Journal, v. 12, n. 1, 2013.
dc.identifier1475-2891
dc.identifierhttp://hdl.handle.net/11449/74386
dc.identifier10.1186/1475-2891-12-11
dc.identifierWOS:000315383600001
dc.identifier2-s2.0-84872151884
dc.identifier2-s2.0-84872151884.pdf
dc.identifier2287552780901172
dc.identifier7805298466001457
dc.description.abstractBackground: High plasma uric acid (UA) is a prerequisite for gout and is also associated with the metabolic syndrome and its components and consequently risk factors for cardiovascular diseases. Hence, the management of UA serum concentrations would be essential for the treatment and/or prevention of human diseases and, to that end, it is necessary to know what the main factors that control the uricemia increase. The aim of this study was to evaluate the main factors associated with higher uricemia values analyzing diet, body composition and biochemical markers. Methods. 415 both gender individuals aged 21 to 82 years who participated in a lifestyle modification project were studied. Anthropometric evaluation consisted of weight and height measurements with later BMI estimation. Waist circumference was also measured. The muscle mass (Muscle Mass Index - MMI) and fat percentage were measured by bioimpedance. Dietary intake was estimated by 24-hour recalls with later quantification of the servings on the Brazilian food pyramid and the Healthy Eating Index. Uric acid, glucose, triglycerides (TG), total cholesterol, urea, creatinine, gamma-GT, albumin and calcium and HDL-c were quantified in serum by the dry-chemistry method. LDL-c was estimated by the Friedewald equation and ultrasensitive C-reactive protein (CRP) by the immunochemiluminiscence method. Statistical analysis was performed by the SAS software package, version 9.1. Linear regression (odds ratio) was performed with a 95% confidence interval (CI) in order to observe the odds ratio for presenting UA above the last quartile (♂UA > 6.5 mg/dL and ♀ UA > 5 mg/dL). The level of significance adopted was lower than 5%. Results: Individuals with BMI ≥ 25 kg/m§ssup§2§esup§ OR = 2.28(1.13-4.6) and lower MMI OR = 13.4 (5.21-34.56) showed greater chances of high UA levels even after all adjustments (gender, age, CRP, gamma-gt, LDL, creatinine, urea, albumin, HDL-c, TG, arterial hypertension and glucose). As regards biochemical markers, higher triglycerides OR = 2.76 (1.55-4.90), US-CRP OR = 2.77 (1.07-7.21) and urea OR = 2.53 (1.19-5.41) were associated with greater chances of high UA (adjusted for gender, age, BMI, waist circumference, MMI, glomerular filtration rate, and MS). No association was found between diet and UA. Conclusions: The main factors associated with UA increase were altered BMI (overweight and obesity), muscle hypotrophy (MMI), higher levels of urea, triglycerides, and CRP. No dietary components were found among uricemia predictors. © 2013 de Oliveira et al.; licensee BioMed Central Ltd.
dc.languageeng
dc.relationNutrition Journal
dc.relation3.568
dc.relation1,447
dc.rightsAcesso aberto
dc.sourceScopus
dc.subjectBody composition
dc.subjectDiet
dc.subjectInflammation
dc.subjectMetabolic syndrome components
dc.subjectUric acid
dc.subjectalbumin
dc.subjectbiochemical marker
dc.subjectC reactive protein
dc.subjectcalcium
dc.subjectcholesterol
dc.subjectcreatinine
dc.subjectgamma glutamyltransferase
dc.subjectglucose
dc.subjecthigh density lipoprotein cholesterol
dc.subjectlow density lipoprotein cholesterol
dc.subjecttriacylglycerol
dc.subjecturea
dc.subjecturic acid
dc.subjectadult
dc.subjectaged
dc.subjectalbumin blood level
dc.subjectanalytic method
dc.subjectanthropometry
dc.subjectbioimpedance
dc.subjectblood chemistry
dc.subjectblood sampling
dc.subjectbody composition
dc.subjectbody fat
dc.subjectbody height
dc.subjectbody mass
dc.subjectbody weight
dc.subjectcalcium blood level
dc.subjectchemiluminescence immunoassay
dc.subjectcholesterol blood level
dc.subjectclinical article
dc.subjectclinical assessment tool
dc.subjectcontrolled study
dc.subjectcreatinine blood level
dc.subjectdata analysis software
dc.subjectdiagnostic test accuracy study
dc.subjectdiet
dc.subjectdietary intake
dc.subjectdry chemistry method
dc.subjectfemale
dc.subjectfood chain
dc.subjectgamma glutamyl transferase blood level
dc.subjectgender
dc.subjectglucose blood level
dc.subjectHealthy Eating Index
dc.subjecthuman
dc.subjecthyperuricemia
dc.subjectimmunochemiluminiscence
dc.subjectimpedance
dc.subjectlifestyle modification
dc.subjectmale
dc.subjectmetabolic syndrome X
dc.subjectmuscle mass
dc.subjectMuscle Mass Index
dc.subjectobesity
dc.subjectrisk factor
dc.subjectsensitivity and specificity
dc.subjectserum
dc.subjecttriacylglycerol blood level
dc.subjecturea blood level
dc.subjecturic acid blood level
dc.subjectwaist circumference
dc.subjectAdult
dc.subjectAged
dc.subjectAged, 80 and over
dc.subjectBiological Markers
dc.subjectBlood Glucose
dc.subjectBlood Pressure
dc.subjectBody Composition
dc.subjectBody Mass Index
dc.subjectC-Reactive Protein
dc.subjectCalcium
dc.subjectCardiovascular Diseases
dc.subjectCholesterol, HDL
dc.subjectCholesterol, LDL
dc.subjectCreatinine
dc.subjectCross-Sectional Studies
dc.subjectElectric Impedance
dc.subjectEnergy Intake
dc.subjectFatty Acids, Unsaturated
dc.subjectFemale
dc.subjectHumans
dc.subjectLife Style
dc.subjectMale
dc.subjectMetabolic Syndrome X
dc.subjectMiddle Aged
dc.subjectOdds Ratio
dc.subjectSerum Albumin
dc.subjectTriglycerides
dc.subjectUrea
dc.subjectUric Acid
dc.subjectWaist Circumference
dc.subjectYoung Adult
dc.titleDietary, anthropometric, and biochemical determinants of uric acid in free-living adults
dc.typeArtículos de revistas


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