Gender distribution of serum uric acid and cardiovascular risk factors: population based study

Rodrigues, Sérgio Lamego; Baldo, Marcelo Perim; Capingana, Pires; Magalhães, Pedro; Dantas, Eduardo Miranda; Molina, Maria del Carmen Bisi; Salaroli, Luciane Bresciani; Morelato, Renato Lário; Mill, José Geraldo

Abstracts

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 variables. MEHTODS: 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-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.

Uric acid; risk factors; cardiovascular diseases; population studies; epidemiology; Brazil

FUNDAMENTO: Não há dados relativos à epidemiologia da hiperuricemia em estudos brasileiros de base populacional. OBJETIVO: Investigar a distribuição de ácido úrico sérico e sua relação com variáveis demográficas e cardiovasculares. MÉTODOS: Estudamos 1.346 indivíduos. A hiperuricemia foi definida como > 6,8 e > 5,4 mg/dL para homens e mulheres, respectivamente. A síndrome metabólica (SM) foi definida utilizando-se os critérios NCEP ATP III. RESULTADOS: A prevalência de hiperuricemia foi de 13,2%. A associação de ácido úrico sérico (AUS) com fatores de risco cardiovasculares foi específica para o gênero: em mulheres, maiores níveis de AUS estiveram associados com IMC elevado, mesmo após ajustes da pressão arterial sistólica para idade (PAS). Em homens, a relação do AUS com o colesterol HDL esteve mediada pelo IMC, enquanto em mulheres, o AUS mostrou-se semelhante e dependente do IMC, independentemente dos níveis glicose e presença de hipertensão. Nos homens, os triglicerídeos, a circunferência abdominal (CA) e a PAS explicaram 11%, 4% e 1% da variabilidade do AUS, respectivamente. Nas mulheres, a circunferência abdominal e os triglicerídeos explicaram 9% e 1% da variabilidade de AUS, respectivamente. Em comparação com o primeiro quartil, homens e mulheres no quarto quartil apresentavam 3,29 e 4,18 vezes mais de aumento de risco de SM, respectivamente. As mulheres apresentaram uma prevalência quase três vezes maior de diabetes melito. Homens normotensos com MS apresentaram maiores níveis de AUS, independente do IMC. CONCLUSÃO: Nossos resultados parecem justificar a necessidade de uma avaliação baseada no gênero em relação à associação do AUS com fatores de risco cardiovasculares, que se mostraram mais acentuados em mulheres. A SM esteve positivamente associada com AUS elevado, independentemente do gênero. A obesidade abdominal e a hipertrigliceridemia foram os principais fatores associados com a hiperuricemia mesmo em indivíduos normotensos, o que pode adicionar maior risco para a hipertensão.

Ácido úrico; fatores de risco; doenças cardiovasculares; estudos populacionais; epidemiologia; Brasil

RFUNDAMENTO: No existen datos relativos a la epidemiología de la hiperuricemia en los estudios brasileros de base poblacional. OBJETIVO: Investigar la distribución del ácido úrico sérico y su relación con las variables demográficas y cardiovasculares. MÉTODOS: Estudiamos 1.346 individuos. La hiperuricemia se definió como > 6,8 y > 5,4 mg/dL para hombres y mujeres, respectivamente. El síndrome metabólico (SM) fue definido utilizando los criterios NCEP ATP III. RESULTADOS: La prevalencia de hiperuricemia fue de un 13,2%. La asociación del ácido úrico sérico (AUS), con los factores de riesgo cardiovasculares fue específica para el género: en las mujeres, mayores niveles de AUS estuvieron asociados con un IMC elevado, incluso después de los ajustes para la presión arterial sistólica (PAS) y edad . En los hombres, la relación del AUS con el colesterol HDL fue mediada por el IMC, mientras que en las mujeres, el AUS demostró ser parecido y dependiente del IMC, independientemente de los niveles de glucosa y de la presencia de hipertensión. En los hombres, los triglicéridos, la circunferencia abdominal (CA) y la PAS, explicaron el 11%, 4% y el 1% de la variabilidad del AUS, respectivamente. En las mujeres, la circunferencia abdominal y los triglicéridos explicaron el 9% y el 1% de la variabilidad de AUS, respectivamente. En comparación con el primer cuartil, los hombres y las mujeres, en el cuarto cuartil, tenían 3,29 y 4,18 veces más aumento de riesgo de SM, respectivamente. Las mujeres tenían una prevalencia casi tres veces mayor de diabetes mellitus. Los hombres normotensos con MS tenían mayores niveles de AUS, independiente del IMC. CONCLUSIONES: Nuestros resultados parecen justificar la necesidad de una evaluación con base en el género, respecto de la asociación del AUS con los factores de riesgo cardiovasculares, que demostraron ser más acentuados en las mujeres. La SM estuvo positivamente asociada con el AUS elevado, independientemente del género. La obesidad abdominal y la hipertrigliceridemia fueron los principales factores asociados con la hiperuricemia incluso en los individuos normotensos, lo que puede añadirle un riesgo mayor a la hipertensión.

Ácido úrico; factores de riesgo; enfermedades cardiovasculares; estudios poblacionales; epidemiología; Brasil

Gender distribution of serum uric acid and cardiovascular risk factors: population based study

Sérgio Lamego Rodrigues^I; Marcelo Perim Baldo^I; Daniel Pires Capingana^I; Pedro Magalhães^I; Eduardo Miranda Dantas^I; Maria del Carmen Bisi Molina^II; Luciane Bresciani Salaroli^II; Renato Lário Morelato^{I, III}; José Geraldo Mill^I

^IDepartamento de Ciências Fisiológicas - Universidade Federal do Espírito Santo, Espírito Santo, Brazil

^IIDepartamento de Saúde Coletiva - Universidade Federal do Espírito Santo, Espírito Santo, Brazil

^IIIDepartamento de Clínica Médica - Escola Superior de Ciências da Santa Casa de Misericórdia de Vitória (EMESCAM), Espírito Santo, Brazil

Mailing Address

ABSTRACT

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 variables.

MEHTODS: 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-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.

Keywords: Uric acid, risk factors, cardiovascular diseases, population studies, epidemiology, Brazil.

Introduction

The association between serum uric acid (SUA) and cardiovascular (CV) diseases such as hypertension¹, metabolic syndrome (MS)², coronary and cerebral vascular diseases^3,4has 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 levels^10,11. 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.

Methods

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 (2564 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).

Measurements

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 510 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 studies^18,19.

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 KolmogorovSmirnov 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 pressure <140/90 mmHg, serum creatinine <1.2 mg/dL, triglycerides <150 mg/dL, cholesterol <200 mg/dL, glucose <100 mg/dL and BMI <27.5 Kg/m², was used to generate cut-off points to define hyperuricemia (SUA concentration >95^th percentile of the normal distribution curve). The 95% SUA values were 6.8 mg/dL (in men) and 5.4 mg/dL (in women). Then, the total sample was divided into quartiles (Q) of SUA as follows: Men: 1^st Q (<4.5 mg/dL), 2^nd Q (4.5-5.19 mg/dL), 3^rd Q (5.2-6.1 mg/dL) and 4^th Q (>6.1 mg/dL); Women: 1^st Q (<3.2 mg/dL), 2^nd Q (3.2-3.89 mg/dL), 3^rd Q (3.9-4.7 mg/dL) and 4^th Q (>4.7 mg/dL).

Logistic regression procedures were used to examine the risk of having metabolic syndrome. Univariate and multiple variable logistic regression procedures were employed to calculate odds ratios (OR) of SUA associated with MS. Confidence intervals were also reported for each OR. Covariates included in the model were age, smoking status and physical activity. Statistical significance was set at P <0.05 for proportions and means, unless otherwise stated.

Results

Using the internally derived cut off points for high SUA levels (6.8 mg/dL for men and 5.4 mg/dL for women), the overall prevalence of hyperuricemia was 13.2% (IC_95%11.4-15.0%), higher in men (16.0%-IC_95%14.0%-18.0%) than in women (10.7%-IC_95%9.0%-12.0%). SUA was similar among social class and race-ethnicity groups (34% white, 50% mulatto and 8.3% black), in active and sedentary individuals (despite the high prevalence of sedentary individuals, around 75%), and in smokers and non smokers, regardless of gender. However, the association of SUA with BMI status after adjustments for age and systolic blood pressure was gender specific: in men, SUA was higher in overweight and obesity individuals when compared to the normal weight group (but without difference between the overweight-obese categories), whereas in women, significantly higher SUA was positively associated with increasing BMI groups (table 1).

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SUA was significantly higher in men (p in parentheses, table 2) as compared to women. In all participants, after gender adjustment, SUA was significantly associated with increasing number of MS components, abdominal obesity, low HDLc, impaired fasting glucose, high triglycerides, and the presence of MS and hypertension. However, stratification of individuals according to gender revealed that the pattern of SUA association with low HDLc, impaired fasting glucose and the presence of hypertension was gender-specific: in men exclusively, the relationship of SUA with low HDLc was not independent, but, mediated by BMI, whereas in women, the association of impaired fasting glucose and hypertension with SUA was mediated by BMI, that is, fasting glucose and hypertension were not independently associated with SUA. Conversely, MS was significantly associated with higher SUA in both genders, even after adjustments for age and BMI showing an independent association with SUA (table 2).

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Women with hyperuricemia, as compared to those without this condition, showed higher increment in the prevalence of hypertension (almost 2 fold compared to 1.52 fold in men) and MS (2.2 fold compared to 1.6 fold in men). As opposed to men, who did not show any difference in the prevalence of DM, women with hyperuricemia presented almost 3 fold higher prevalence of DM.

Table 3 summarizes Pearson's correlation coefficients between SUA and CV risk factors, stratified by gender. All variables correlated significantly with SUA, except glucose in both gender and age in men. It is noteworthy that waist circumference in both gender and triglycerides in men presented the strongest correlations with SUA. There was a positive association of SUA with increasing number of MS components, adjusted for age. Mean SUA increased in men and women, respectively, from 4.8±1.2 mg/dL and 3.6±0.8 mg/dL in individuals with no component of the MS to 5.8±1.4 mg/dL and 4.4±1.0 mg/dL in individuals with three components and to 6.1±1.4 mg/dL and 5.2±1.3 mg/dL in those with the full spectrum of the syndrome (table 1).

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The relationship between SUA and MS is also illustrated by the fact that MS prevalence ratio in individuals with and without hyperuricemia were 1.88 (IC_95%1.322.65) and 2.71 (IC_95%1.784.12) for men and women, respectively. In addition, figure 1 shows the successive increase in the prevalence of MS across quartiles of SUA. We can notice a smooth increase of MS prevalence along SUA quartiles in women, but the same seems not to occur in men. Furthermore, we investigated the relative risk of MS, according to the quartiles of SUA adjusted for age, smoking status and physical activity in men and women, respectively. The results are shown in table 4. Compared to the first quartile, men and women in the highest SUA quartile had a 3.29 fold and 4.18 fold increase of MS risk, respectively. It is worth to note the linear component in risk of having MS in relation to increased SUA concentrations, regardless of genders.

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We further explored the association of SUA and MS in individuals with normal blood pressure (BP <130/85 mmHg), stratified by gender. Figure 2 shows that in these 723 normotensive individuals stratified by gender, after adjustments for age and BMI, SUA was significantly higher only in men with MS, as compared to the counterpart without the syndrome.

Factors associated with increased SUA were investigated by multivariate stepwise regression analysis, stratified by gender. In men, triglycerides (β= 0.23, p<0.001), waist circumference (β= 0.21, p<0.001) and systolic blood pressure (β= 0.11, p=0.004) explained 11%, 4% and 1% of the SUA variability, respectively. In women, waist circumference (β= 0.26, p<0.001) and triglycerides (β= 0.09, p=0.02) explained 9% and 1% of the SUA variability, respectively. Age was excluded from the model in both genders. Indeed, the prevalence of hyperuricemia did not change in relation to age categories. However, in women but not in men, SUA was significantly higher above the age of 54 (25-54 years: 5.22±1.14 mg/dL and 3.92±1.19 mg/dL; 55-65 years: 5.45±1.37 mg/dl and 4.36±1.11 mg/dl, in men and women, respectively). Table 5 shows the areas under the ROC curves (AURC) and the optimal cut-off points (according to the highest sensitivity and specificity) of SUA associated with MS. The best cut offs were 5.3 mg/dL for men and 4.0 mg/dL for women, that are roughly in the 75^th percentile of the SUA distribution curve of the normal healthy sub sample.

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Discussion

to the best of our knowledge, this is the first report on the prevalence of hyperuricemia and the association of SUA with demographic, hemodynamic and metabolic risk factors in a Brazilian population-based study. We focused our analyses specifically on the effects of gender on this relationship. Even though it was found that men presented higher SUA regarding all variables analyzed (all participants, with p for gender in parentheses, table 1), we noticed specific differences after gender stratification. In men exclusively, the relationship of SUA with high or low HDLc was mediated by BMI. On the other hand, in women exclusively, the association of impaired fasting glucose and hypertension with SUA was dependent on BMI (table 2). Concerning BMI status, an index of general adiposity, even after adjustments for age and systolic blood pressure, women presented a more pronounced and positive association of SUA with increasing BMI groups, and differently from men, which presented similar SUA in overweight and obese individuals (table 1).

We observed significantly positive associations of SUA with the risk factors investigated and the higher prevalence of MS and hypertension in hyperuricemic individuals, mainly in women. It is worth to note the increased prevalence (almost three fold high) of diabetes mellitus exclusively in women with hyperuricemia, as compared to those with normal SUA levels. More importantly, was the detection of increased SUA exclusively, in normotensive men with MS, which was independent of age and BMI, and diverse from women, that presented BMI as the mediator of SUA (figure 2).

Analyses of the whole sample showed that triglycerides in men and waist circumference (surrogate measure for visceral fat) in both genders were identified as the main factors associated with hyperuricemia. Accordingly, it has been reported that hypertriglyceridemia is the major abnormality of MS and there is evidence that the association between SUA concentration and insulin resistance may be mediated by increased triglyceride²³. Even though the mechanism by which excess body fat leads to increased SUA is still not totally elucidated, in addition to the increase in endogenous production of urate, evidence shows that accumulated visceral fat leads to an increase in free fatty acids and tumor necrosis factor alpha (TNF-α), together with a decrease in adiponectin concentration, which leads in turn to reduced renal excretion of uric acid²⁴.

Overall, the prevalence of hyperuricemia was 13.2%. It is worth to mention that we investigated individuals not in use of drugs that interfere with uric acid metabolism and without apparent renal failure. Moreover, the cut-off ratio was defined internally (healthy sub-sample) as the sex-specific 95^th percentile (6.8 mg/dL and 5.4 mg/dL for men and women, respectively) which is 0.2 mg/dL and 0.6 mg/dL lower in men and women respectively, was compared to the cut-offs in use²⁵.

We found that SUA increased with the number of MS components, even when adjusted for age, and that the odds ratio for MS increased across quartiles of SUA, regardless of gender. Besides, we found 5.3 mg/dL in men and 4.0 mg/dL in women as the best cut-off points of SUA associated with MS by ROC curve analysis with sensibilities and specificities around 62%.

In general, our data agree with several cross-sectional studies from different populations that established an association between SUA and MS^2,26, and with a Brazilian study that included 352 white male individuals from high social class²⁷and an observational study that evaluated 756 individuals (369 men) from a convenience sample¹².

Taken together, our study suggests that depending on gender, hyperuricemia might be a component of the clinical picture of MS or possibly, an independent risk factor. Despite the presence of generally lower concentration of SUA in women, when compared to men, the female gender showed a more pronounced association of BMI with higher SUA besides a closer relationship with MS, diabetes mellitus and hypertension. However, studies without gender stratification, may fail to notice potential gender-specific differences regarding SUA and cardiometabolic risk factors. Therefore, the results of our study seem to justify the need for gender-based evaluation when investigating the association of SUA with cardiovascular risk factors.

Hyperuricemia can result from either increased uric acid synthesis or decreased uric acid excretion, or from a combination of both. Diminished uric acid excretion is reported in patients with MS²⁸and appears to reflect impaired renal uric acid excretion secondary to enhanced proximal tubular sodium reabsortion mediated by hyperinsulinemia²⁹. Hypertension in turn, has been reported to mediate the direct relationship between MS and increased SUA levels³⁰. Indeed, we identified blood pressure higher than 130/85mmHg in roughly 85% of individuals with MS. Thus, blood pressure increase clearly represents the main risk factor associated with MS in our population. Chronic inflammation and endothelial dysfunction, as observed in patients with increased SUA, are likely to have participation in the mechanisms through which this substance may affect renal structure and operation³¹ leading to the genesis of hypertension mainly in young individuals³². Conversely, it has been questioned if uric acid is a substance that is increased by the organism to counteract the increased oxidative stress associated with insulin resistance, inflammation, and other risk factors that usually cluster with increased SUA concentrations³³ thus, representing only a defense mechanism.

The interpretation of this investigation has some limitations. Firstly, data were restricted to a cross-sectional study in a population with 36% whites, 53% mulattos and 9% blacks and should be generalized to other populations with caution. Secondly, no serum insulin levels were measured as an index for insulin resistance. As insulin resistance is believed to play a major role in the metabolic syndrome, the inclusion of this variable in our statistical analysis would have been important. Thirdly, information on alcohol intake was not available. However, as mentioned before, we did not find differences in SUA stratified by gender regarding smoking status, social class or race-ethnicity (as others have found higher SUA in male black individuals, partially related to alcohol ingestion)³⁴, which may have dampened the importance of alcohol in our analysis, that is, if alcohol was consumed, the amount did not seem to impact SUA in our sample. Another possible weakness of our study is, as expected, the small number of normotensive drug-free individuals with the diagnosis of MS. However, we further explored 723 individuals with blood pressure <130/85mmHg and found out that there was a graded increase in SUA in relation to the number of concurrent MS components in both genders. Our findings agree with data recently reported in which it was found that around 73% of hiperuricemic individuals had more than one MS component³⁵. Moreover, we found that men and women with SUA levels above 6.1 mg/dL and 4.7 mg/dL, had 3 and 4 times higher risk, respectively, of having MS.

Therefore, since hyperuricemia is potentially a modifiable factor, measuring SUA that is cheap and easily available, might provide a cost-beneficial investigation allowing the identification of individuals with increased SUA, which in turn, may benefit to have a full work up for the risk factors associated with MS. It is worth to note that regarding normotensive individuals, the detection of high SUA might be an alert and a warning to increment preventive measures to avoid hypertension. Even though our study does not allow to establish causal relationships, under the light of the latest evidences^7,8 our data may suggest a possible role of increased SUA in cardiovascular physiopathology. Strategies to improve people's awareness about the necessity to urgently modify eating habits and to avoid sedentary lifestyle are necessary, mainly focusing on the pursuit of "healthy" and properly individualized waist line measurements^36,37.

Acknowledgements

This work was supported with grants from CNPq and FAPES (PRONEX, n. 35884886).

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14. Molina MC, Cunha RS, Herbenhoff FL, Mill JG. [Hypertension and salt intake in an urban population]. Rev Saude Publica. 2003;37(6):743-50.
15. The sixth report of the Joint National Committee on prevention, detection, evaluation, and treatment of high blood pressure. Arch Intern Med. 1997;157(21):2413-46.
16. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive Summary of the Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). JAMA. 2001;285(19):2486-97.
17. Instituto Brasileiro de Geografia e Estatística (IBGE). Pesquisa Nacional por Amostra de Domicílios 2000: microdados. Rio de Janeiro: Fundação Instituto Brasileiro de Geografia e Estatística; 2001.
18. Krieger H, Morton NE, Mi MP, Azevedo E, Freire-Maia A, Yasuda N. Racial admixture in north-eastern Brazil. Ann Hum Genet. 1965;29(2):113-25.
19. Carvalho-Silva DR, Santos FR, Rocha J, Pena SD. The phylogeography of Brazilian Y-chromosome lineages. Am J Hum Genet. 2001;68(1):281-6.
20. Hanley JA, McNeil BJ. The meaning and use of the area under a receiver operating characteristic curve. Radiology. 1982;143(1):29-36.
21. Metz CE. Basic principles of ROC analysis. Semin Nucl Med. 1978;8(4):283-98.
22. Altman DG, Gardner M. Diagnostics tests. In: Altman DG, Machin D, Trevor NB, Gardner S. (eds.). Statistics with confidence: confidence intervals and statistics guidelines. 2nd ed. London: John Wiley & Sons; 2000. p. 105-19.
23. Giacomello A, Di Sciascio N, Quaratino CP. Relation between serum triglyceride level, serum urate concentration, and fractional urate excretion. Metabolism. 1997;46(9):1085-9.
24. Choi HK, Mount DB, Reginato AM. Pathogenesis of gout. Ann Intern Med. 2005;143(7):499-516.
25. Fang J, Alderman MH. Serum uric acid and cardiovascular mortality. The NHANES I epidemiologic follow-up study, 19711992. National Health and Nutrition Examination Survey. JAMA. 2000,283(18):2404-10.
26. Choi HK, Ford ES. Prevalence of the metabolic syndrome in individuals with hyperuricemia. Am J Med. 2007;120(5):442-7.
27. Desai MY, Santos RD, Dalal D, Carvalho JA, Martin DR, Flynn JA, et al. Relation of serum uric acid with metabolic risk factors in asymptomatic middle-aged Brazilian men. Am J Cardiol. 2005;95(7):865-8.
28. López-Suárez A, Elvira-Gonzalez J, Bascunana-Quirell A, Rosal-Obrador J, Michán-Doña A, Escribano-Serrano J, et al. [Serum urate levels and urinary uric acid excretion in subjects with metabolic syndrome]. Med Clin (Barc). 2006;126(9):321-4.
29. Strazzullo P, Barbato A, Galletti F, Barba G, Siani A, Iacone R, et al. Abnormalities of renal sodium handling in the metabolic syndrome: results of the Olivetti Heart Study. J Hypertens. 2006;24(8):1633-9.
30. Lin KC, Tsao HM, Chen CH, Chou P. Hypertension was the major risk factor leading to development of cardiovascular diseases among men with hyperuricemia. J Rheumatol. 2004;31(6):1152-8.
31. Zoccali C, Maio R, Mallamaci F, Sesti G, Perticone F. Uric acid and endothelial dysfunction in essential hypertension. J Am Soc Nephrol. 2006;17(5):1466-71.
32. Feig DI, Johnson RJ. Hyperuricemia in childhood primary hypertension. Hypertension. 2003;42(3):247-52.
33. Nieto FJ, Iribarren C, Gross MD, Cosmotock GW, Cutler RG. Uric acid and serum antioxidant capacity: a reaction to atherosclerosis? Atherosclerosis. 2000;148(1):131-9.
34. Conen D, Wietlisbach V, Bovet P, Shamlaye C, Riesen W, Paccaud F, et al. Prevalence of hyperuricemia and relation of serum uric acid with cardiovascular risk factors in a developing country. BMC Public Health. 2004 Mar 25;4:9.
35. Tsouli SG, Liberopoulos EN, Mikhailidis DP, Athyros VG, Elisaf MS. Elevated serum uric acid levels in metabolic syndrome: an active component or an innocent bystander? Metabolism. 2006;55(10):1293-301.
36. Rodrigues SL, Baldo MP, Sá Cunha R, Angelo LC, Pereira AC, Krieger JE, et al. Anthropometric measures of increased central and overall adiposity in association with echocardiographic left ventricular hypertrophy. Hypertens Res. 2010;33(1):83-7.
37. Rodrigues SL, Baldo MP, Mill JG. Association of waist-stature ratio with hypertension and metabolic syndrome: population-based study. Arq Bras Cardiol. 2010;95(2):186-91.

Correspondência:

Sergio Lamego Rodrigues

Rua Ary Siqueira, 55, Enseada do Sua

29055-490 – Vitória, ES, Brasil

E-mail:

slamego@cardiol.br;

sergiolamegor@gmail.com

Publication Dates

Publication in this collection
08 Dec 2011
Date of issue
Jan 2012

History

Received
17 May 2011
Accepted
28 July 2011
Reviewed
05 July 2011

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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[2] 2. Onat A, Uyarel H, Hergenc G, Karabulut A, Albayrak S, Sari I, et al. Serum uric acid is a determinant of metabolic syndrome in a population-based study. Am J Hypertens. 2006;19(10):1055-62.

[3] 3. Tuttle KR, Short RA, Johnson RJ. Sex differences in uric acid and risk factors for coronary artery disease. Am J Cardiol. 2001;87(12):1411-4.

[4] 4. Lehto S, Niskanen L, Rönnemaa T, Laakso M. Serum uric acid is a strong predictor of stroke in patients with non-insulin-dependent diabetes mellitus. Stroke. 1998;29(3):635-9.

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[8] 8. Wiik BP, Larstorp AC, Høieggen A, Kjeldsen SE, Olsen MH, Ibsen H, et al. Serum uric acid is associated with new-onset diabetes in hypertensive patients with left ventricular hypertrophy: The LIFE Study. Am J Hypertens. 2010;23(8):845-51.

[9] 9. Marquezine GF, Oliveira CM, Pereira AC, Krieger JE, Mill JG. Metabolic syndrome determinants in an urban population from Brazil: social class and gender-specific interaction. Int J Cardiol. 2008;129(2):259-65.

[10] 10. Schmidt MI, Duncan BB, Watson RL, Sharrett AE, Brancati FL, Heiss G. A metabolic syndrome in whites and African-Americans. The atherosclerosis risk in communities' baselines study. Diabetes Care. 1996;19(5):414-8.

[11] 11. Yoo TW, Sung KC, Shin HS, Kim BJ, Kim BS, Kang JH, et al: Relationship between serum uric acid concentration and insulin resistance and metabolic syndrome. Circ J. 2005;69(8):928-33.

[12] 12. Barbosa MC, Brandão AA, Pozzan R, Magalhães ME, Campana EM, Fonseca FL, et al. Association between uric acid and cardiovascular risk variables in a non-hospitalized population. Arq Bras Cardiol. 2011;96(3):212-8.

[13] 13. Pereira AC, Mota GF, Cunha RS, Herbenhoff FL, Mill JG, Krieger JE. Angiotensinogen 235T allele 'dosage' is associated with blood pressure phenotypes. Hypertension. 2003;41(1):25-30.

[14] 14. Molina MC, Cunha RS, Herbenhoff FL, Mill JG. [Hypertension and salt intake in an urban population]. Rev Saude Publica. 2003;37(6):743-50.

[15] 15. The sixth report of the Joint National Committee on prevention, detection, evaluation, and treatment of high blood pressure. Arch Intern Med. 1997;157(21):2413-46.

[16] 16. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive Summary of the Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). JAMA. 2001;285(19):2486-97.

[17] 17. Instituto Brasileiro de Geografia e Estatística (IBGE). Pesquisa Nacional por Amostra de Domicílios 2000: microdados. Rio de Janeiro: Fundação Instituto Brasileiro de Geografia e Estatística; 2001.

[18] 18. Krieger H, Morton NE, Mi MP, Azevedo E, Freire-Maia A, Yasuda N. Racial admixture in north-eastern Brazil. Ann Hum Genet. 1965;29(2):113-25.

[19] 19. Carvalho-Silva DR, Santos FR, Rocha J, Pena SD. The phylogeography of Brazilian Y-chromosome lineages. Am J Hum Genet. 2001;68(1):281-6.

[20] 20. Hanley JA, McNeil BJ. The meaning and use of the area under a receiver operating characteristic curve. Radiology. 1982;143(1):29-36.

[21] 21. Metz CE. Basic principles of ROC analysis. Semin Nucl Med. 1978;8(4):283-98.

[22] 22. Altman DG, Gardner M. Diagnostics tests. In: Altman DG, Machin D, Trevor NB, Gardner S. (eds.). Statistics with confidence: confidence intervals and statistics guidelines. 2nd ed. London: John Wiley & Sons; 2000. p. 105-19.

[23] 23. Giacomello A, Di Sciascio N, Quaratino CP. Relation between serum triglyceride level, serum urate concentration, and fractional urate excretion. Metabolism. 1997;46(9):1085-9.

[24] 24. Choi HK, Mount DB, Reginato AM. Pathogenesis of gout. Ann Intern Med. 2005;143(7):499-516.

[25] 25. Fang J, Alderman MH. Serum uric acid and cardiovascular mortality. The NHANES I epidemiologic follow-up study, 19711992. National Health and Nutrition Examination Survey. JAMA. 2000,283(18):2404-10.

[26] 26. Choi HK, Ford ES. Prevalence of the metabolic syndrome in individuals with hyperuricemia. Am J Med. 2007;120(5):442-7.

[27] 27. Desai MY, Santos RD, Dalal D, Carvalho JA, Martin DR, Flynn JA, et al. Relation of serum uric acid with metabolic risk factors in asymptomatic middle-aged Brazilian men. Am J Cardiol. 2005;95(7):865-8.

[28] 28. López-Suárez A, Elvira-Gonzalez J, Bascunana-Quirell A, Rosal-Obrador J, Michán-Doña A, Escribano-Serrano J, et al. [Serum urate levels and urinary uric acid excretion in subjects with metabolic syndrome]. Med Clin (Barc). 2006;126(9):321-4.

[29] 29. Strazzullo P, Barbato A, Galletti F, Barba G, Siani A, Iacone R, et al. Abnormalities of renal sodium handling in the metabolic syndrome: results of the Olivetti Heart Study. J Hypertens. 2006;24(8):1633-9.

[30] 30. Lin KC, Tsao HM, Chen CH, Chou P. Hypertension was the major risk factor leading to development of cardiovascular diseases among men with hyperuricemia. J Rheumatol. 2004;31(6):1152-8.

[31] 31. Zoccali C, Maio R, Mallamaci F, Sesti G, Perticone F. Uric acid and endothelial dysfunction in essential hypertension. J Am Soc Nephrol. 2006;17(5):1466-71.

[32] 32. Feig DI, Johnson RJ. Hyperuricemia in childhood primary hypertension. Hypertension. 2003;42(3):247-52.

[33] 33. Nieto FJ, Iribarren C, Gross MD, Cosmotock GW, Cutler RG. Uric acid and serum antioxidant capacity: a reaction to atherosclerosis? Atherosclerosis. 2000;148(1):131-9.

[34] 34. Conen D, Wietlisbach V, Bovet P, Shamlaye C, Riesen W, Paccaud F, et al. Prevalence of hyperuricemia and relation of serum uric acid with cardiovascular risk factors in a developing country. BMC Public Health. 2004 Mar 25;4:9.

[35] 35. Tsouli SG, Liberopoulos EN, Mikhailidis DP, Athyros VG, Elisaf MS. Elevated serum uric acid levels in metabolic syndrome: an active component or an innocent bystander? Metabolism. 2006;55(10):1293-301.

[36] 36. Rodrigues SL, Baldo MP, Sá Cunha R, Angelo LC, Pereira AC, Krieger JE, et al. Anthropometric measures of increased central and overall adiposity in association with echocardiographic left ventricular hypertrophy. Hypertens Res. 2010;33(1):83-7.

[37] 37. Rodrigues SL, Baldo MP, Mill JG. Association of waist-stature ratio with hypertension and metabolic syndrome: population-based study. Arq Bras Cardiol. 2010;95(2):186-91.