Arq. Bras. Cardiol. vol.98 número1

Original Article
Gender Distribution of Serum Uric Acid and Cardiovascular Risk
Factors: Population Based Study
Sérgio Lamego Rodrigues1, Marcelo Perim Baldo1, Daniel Pires Capingana1, Pedro Magalhães1, Eduardo Miranda
Dantas1, Maria del Carmen Bisi Molina2, Luciane Bresciani Salaroli2, Renato Lírio Morelato1,3, José Geraldo Mill1
Departamento de Ciências Fisiológicas - Universidade Federal do Espírito Santo1; Departamento de Saúde Coletiva - Universidade Federal do Espírito
Santo2; Departamento de Clínica Médica - Escola Superior de Ciências da Santa Casa de Misericórdia de Vitória (EMESCAM)3, Vitória, ES - Brazil

Background: There is no data concerning the epidemiology of hyperuricemia in Brazilian population-based studies.
Objective: To investigate the distribution of serum uric acid and its relationship with demographics and cardiovascular
Methods: We studied 1,346 individuals. Hyperuricemia was defined as ≥ 6.8 and ≥ 5.4 mg/dL for men and women,
respectively. Metabolic syndrome (MS) was defined with NCEP ATP III criteria.
Results: The prevalence of hyperuricemia was 13.2%. The association of serum uric acid (SUA) with cardiovascular
risk factors was gender-specific: in women, higher SUA was associated with increasing BMI, even after adjustments for
age and systolic blood pressure (SBP). In men, the relationship of SUA with HDLc was mediated by BMI, whereas in
women, SUA was similar and dependent on BMI, regardless of glucose levels and presence of hypertension. In men,
triglycerides, waist circumference (WC) and SBP explained 11%, 4% and 1% of SUA variability, respectively. In women,
WC and triglycerides explained 9% and 1% of SUA variability, respectively. Compared to the first quartile, men and
women in the fourth quartile had a 3.29 fold and 4.18 fold increase of MS risk, respectively. Women had almost three
fold higher prevalence of diabetes mellitus. Normotensive men with MS presented higher SUA, regardless of BMI.
Conclusion: Our results seem to justify the need for gender-based evaluation regarding the association of SUA with
cardiovascular risk factors, which was more pronounced in women. MS was positively associated with increasing SUA,
regardless of gender. Abdominal obesity and hypertriglyceridemia were the main factors associated with hyperuricemia
even in normotensive individuals, which may add a higher risk for hypertension. (Arq Bras Cardiol 2012;98(1):13-21)
Keywords: Uric acid, risk factors, cardiovascular diseases, population studies, epidemiology, Brazil.

The association between serum uric acid (SUA) and
cardiovascular (CV) diseases such as hypertension1, metabolic
syndrome (MS)2, coronary and cerebral vascular diseases3,4
has been reported in several epidemiologic studies. However,
SUA has not been considered an independent cardiovascular
risk factor, but only an additional factor associated with
CV diseases due to the presence of other conditions such
as obesity, dyslipidemia, hypertension, use of diuretics or
insulin resistance5. Accordingly, hyperuricemia has been
largely considered a finding without specific significance
unless complicated by gout or kidney stones6. However,
recent reports added further indication of a possible link
between SUA and cardiovascular disease, as hyperuricemia
was associated with increased mortality and myocardial
infarction in individuals with renal failure, even after
adjustment for renal function and risk factors for MS7. In
addition, SUA was identified as an independent risk marker

for new onset diabetes in hypertensive patients with left
ventricular hypertrophy8.
Not differently from many other developing countries,
Brazil is facing a growing incidence of obesity and metabolic
disturbances9. Large epidemiological studies have shown that
SUA is often high in individuals with MS and that its prevalence
increases according to SUA levels10,11. However, as recently
reported12, there is scarce data regarding SUA in Brazil and
so far, no data has been reported on the prevalence and
epidemiological characteristics of hyperuricemia on studies
that reflect the general Brazilian population with diverse ethnic
groups, food intake and physical activity habits. Therefore, we
sought to investigate in a large population-based sample the
distribution of SUA and its relationship with gender, ethnicity,
social class, physical activity, MS and cardiovascular risk
factors. In addition, we searched for the best cut off points
of SUA associated with MS by using the receiver-operating
characteristics (ROC) curve analysis.

Mailing Address: Sergio Lamego Rodrigues •
Centro de Investigação Cardiovascular - UFES – Av. Marechal Campos, 1468 – Maruípe – 29042-755 – Vitória, ES, Brazil
Manuscript received May 17, 2011, revised manuscript received July 05, 2011; accepted July 28, 2011.


Rodrigues et al
Uric acid and metabolic syndrome

Original Article
Study Design and Sample Selection
A cross-sectional and population-based study was
performed to determine the prevalence and severity of
cardiovascular risk factors in the urban population of
Vitória, Brazil. Data were collected according to the general
guidelines of the MONICA-WHO Project13. A sample of 1,661
individuals was selected from the eligible population (25–64
years) by using a procedure of household randomization.
These individuals came to the University Hospital to undergo
clinical and laboratory exams. The design and sampling
of this survey was described elsewhere14. The project was
approved by the institutional ethics committee and all
participants gave informed written consent. Individuals in use
of drugs to lower serum lipids, uric acid or blood pressure
(including diuretics) or with serum creatinine >1.2 mg/dL
were excluded from this analysis, leaving a final sample of
1,346 individuals (645 men).
Blood pressure was measured during the morning period
(07:00 to 09:00 AM) in fasting individuals in the sitting
position by using a standard mercury sphygmomanometer
on the left arm after a 5–10 min rest period. The first and
fifth phases of Korotkoff sounds were used to indicate
systolic and diastolic blood pressure, respectively. Mean
values of systolic and diastolic blood pressure were
calculated from two measurements carried out by two
independent trained staff members, with a minimal interval
of 10 min between the two readings. Blood pressure was
defined according to the VI Joint National Committee
on Prevention, Detection, Evaluation, and Treatment
of High Blood Pressure15. Participants were considered
hypertensive in the presence of systolic blood pressure ≥
140 mmHg or diastolic blood pressure ≥ 90 mmHg. For
biochemical analysis, blood samples were collected soon
after blood pressure measurements to determine glucose,
creatinine, triglycerides, uric acid, total cholesterol and
high-density lipoprotein-cholesterol (HDLc) by using
validated commercial kits.
Anthropometric parameters were obtained by trained
technicians using standard methods. Body weight was taken
on a calibrated scale to the nearest 0.1 kg. Height was taken
with a wall-mounted stadiometer to the nearest 0.5 cm.
Body mass index (BMI) was calculated as body weight (kg)
to the squared height (m2). Waist circumference (WC) was
measured at the mean point between the lowest rib margin
and iliac crest with the participant standing and at the
maximum point of normal expiration. History of cigarette
smoking was considered present if an individual was a
current smoker. Individuals were considered physically
active if they engaged in moderate physical activity for
at least 30 minutes ≥ 3 times a week. According to the
NECP ATP III criteria16, MS was defined when any three
of the five following diagnostic criteria were present: WC
≥ 102 cm in men and ≥88cm in women; type II diabetes
mellitus or fasting glucose ≥110 mg/dL; HDL-chol ≤ 40 mg/

dL in men and ≤50 mg/dL in women; triglycerides ≥ 150
mg/dL; systolic blood pressure ≥ 130 mmHg or diastolic
blood pressure ≥ 85 mmHg. Diabetes was defined when
a positive history was present or the fasting blood glucose
was ≥ 126 mg/dL. Impaired fasting glucose was defined
as fasting glucose ranging from 110 mg/dL to 125.9 mg/dL.
The individuals were classified into five socioeconomic
classes on the basis of data on the education level of the
household head and the type and quantity of domestic
equipment at home17. The ethnic morphological subgroup
classification was based on phenotype pigmentation of the
abdomen, hair color, type and conformation of the nose
and lips, and family history, as determined and agreed upon
by two examining physicians. Even though in the Brazilian
population morphological criteria are not strongly consistent
with ancestry, this classification has been validated and
previously used in other studies18,19.
Statistical analysis
Statistical analysis was carried out using the SPSS 18.0
statistical package (Chicago, IL, USA). Data were described
as means ± standard deviation for continuous variables.
Proportions were used to express dichotomous variables.
Goodness to fit to normal distribution was evaluated using
the Kolmogorov–Smirnov test. Student t-test or analyses
of variance (with Tukey post hoc test) were used to
assess differences between two or more than two means,
respectively. Pearson correlation coefficients were obtained
for anthropometric, biological and metabolic variables and
SUA levels. Multivariate Linear Stepwise Regression and the
Univariate General Linear Models were used to adjust for
confounding variables. BMI and triglycerides were analyzed
after log transformation. The predictability of SUA to identify
MS was identified by ROC curve analyses20. Differences
of the areas under the ROC curve were compared using
a method previously described21. Optimal cutoff points
were registered as the measures representing the largest
concomitant sensitivity and specificity22.
A healthy sub sample of 294 individuals with blood

Arq. Bras. Cardiol. vol.98 número1