Relationship between Uric Acid and Metabolic Syndrome among Users of a Primary Care Clinic in Mexico
Received Date: Nov 24, 2017 / Accepted Date: Dec 08, 2017 / Published Date: Jan 03, 2018
Introduction: Metabolic syndrome and hyperuricemia are important risk factors for cardiovascular disease.
Objective: To assess the association between uric acid and metabolic syndrome.
Methods: A cross-sectional analytic study enrolled 203 volunteers, aged ≥ 20 years, who presented to a primary care clinic that provides care for a state university staff and their families. Hyperuricemia was defined as a blood uric acid level of ≥ 7.0 mg/dL in men and ≥ 6.0 mg/dL in women. Metabolic syndrome was defined according to the National Cholesterol Education Program, Adult Treatment Panel III (ATPIII) criteria. The association between these variables was assessed using Pearson´s correlation and multivariate regression.
Results: The mean age was 52 ± 13.5 years. Sixty percent of the subjects were female. The prevalence of metabolic syndrome in subjects with and without hyperuricemia was 49% and 33%, respectively. There was a statistically significant association between the uric acid level and metabolic syndrome in the gender-adjusted multivariate analysis (odds ratio=1.5, 95% confidence intervals=1.2 to 1.9). We identified hyperglycemia as a predictor for hyperuricemia (odds ratio=e 3.0, 95% confidence interval=1.4 to 6.3).
Conclusion: The results showed that high concentrations of uric acid are associated with metabolic syndrome and suggest that the presence of fasting hyperglycemia is strongly associated with hyperuricemia in women.
Keywords: Hyperuricemia; Metabolic syndrome; Primary care
Some authors suggest that hyperuricemia should be considered a marker for MS given the noted independent positive association between these variables and the association of uric acid (UA) levels with the incidence of MS [4-7].
The last national health survey in Mexico showed a high prevalence of overweight and obesity (70.5%), hypercholesterolemia (35.5%), hypertriglyceridemia (29.9%), arterial hypertension (31.5%) and diabetes mellitus type 2 (9.2%), which are conditions that have contributed to epidemiological data related to metabolic syndrome [8-11]. However, the literature is limited regarding this association in Mexico; therefore, this study aimed to evaluate the association between UA levels and MS in patients from a primary care clinic that provides care for a state university staff and their families.
Material and Methods
Study design and population studied: A cross-sectional study was conducted in a primary care clinic, located in Xalapa, Veracruz (Mexico), that provides care for a state university staff and their families.
Volunteers aged 20 years and older, who were not pregnant and did not have kidney disease were selected between July 1, 2012, and March 31, 2013, to participate in the study. The absence of kidney disease and pregnancy was verified using medical records. All consecutive attendants to the clinic were invited to participate.
To calculate our sample size, we used the previously reported MS prevalence of 66.2% and 37% in patients with and without hyperuricemia, respectively .We estimated the need for at least 36 subjects with and without hyperuricemia to calculate the ratio differences.
A questionnaire was used to collect the demographic characteristics and lifestyle data concerning the participants. We conducted the STEP wise 17-item questionnaire  to obtain information regarding alcohol and tobacco consumption. Waist circumference was measured using an anthropometric tape that was placed midway between the lower costal margin and the iliac crest. Well-trained nurses measured the systolic blood pressure (SBP) and diastolic blood pressure (DBP) two times in the left arm of the participants according to a standardized protocol. The average of the two readings was calculated to determine the reported blood pressure for each participant.
Blood was drawn from each subject during fasting for measurement of the HDL cholesterol, triglycerides, plasma glucose and uric acid concentrations. These variables were measured using standard enzymatic automated methods. The uric acid level was assayed using the colorimetric uricase-peroxidase system.
Definition of metabolic syndrome
MS was diagnosed according to the National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATP III) [14,15] criteria as follows: blood pressure ≥ 130/85 mmHg; triglycerides ≥ 150 mg/dL; HDL cholesterol <40 mg/dL in men and <50 mg/dL in women; fasting blood glucose >100 mg/dL. The following criteria were recommended by the Latin American Diabetes Association (ALAD)  for the determination of abdominal obesity: waist circumference ≥ 94 cm in men and ≥ 88 cm in women.
Assessment of uric acid concentration: Hyperuricemia was defined as ≥ 7.0 mg/dL in men and ≥ 6.0 mg/dL in women, which is consistent with prior epidemiologic studies examining hyperuricemia and cardiovascular outcomes .
The study was authorized by the Technical Council of the “Instituto de Salud Pública” (Public Health Institute) of the University of Veracruz. All participants provided written consent to participate in the study.
The Kolmogorov-Smirnov test was used to analyze the distribution of continuous variables. The means and standard deviations for the variables with normal or medium distribution and minimum and maximum values were expressed when this distribution was not found.
Categorical variables were analyzed using the chi-square test or Fisher’s exact test accordingly. Continuous variables without normal distribution were analyzed using the Mann-Whitney U test. The correlation between UA and MS and its components was assessed using Spearman´s Rho correlation coefficient. A logistic regression analysis was conducted to assess the relationship between hyperuricemia and MS. Models were developed where MS was the dependent variable, and the level of uric acid, age, and gender were the covariates. A second set of models included the presence of hyperuricemia as the dependent variable and abdominal obesity, hypertension, hyperglycemia, hypocholesterolemia-cholesterol, hypertriglyceridemia, age and gender as covariates, p<0.05 was considered to be statistically significant.
A total of 313 subjects were enrolled to participate in the study. Of these, 110 (35%) subjects were excluded because they lacked laboratory analysis results. A final sample of 203 participants were included in the analysis. Of these, 61.6% were women. The prevalence of hyperuricemia was 34%, and the prevalence of MS was 38.4%. A total of 12.3% of the participants were smokers (consuming an average of 5 ± 9 cigarettes daily), and the prevalence of smoking was higher in men. Twenty percent of the participants reported drinking alcohol on a weekly basis.
Subjects with hyperuricemia had a greater waist circumference, higher levels of glucose and triglycerides, and lower levels of HDL cholesterol (Table 1) than subjects with normal uric levels. Additionally, the proportion of men in the group with hyperuricemia was almost 3 times higher than the proportion of men without hyperuricemia, which is in agreement with other reports .When the results were stratified by gender, median levels of triglycerides were significantly higher in men than in women, and the levels were higher in the group with hyperuricemia (p=0.04). The median fasting glucose level was higher in women with hyperuricemia (p=0.01). All of the other variables were not significantly different between genders. No gender association was found with smoking and alcohol intake.
|Variables||With hyperuricemia (n=69)||Without hyperuricemia (n=134)||Probability|
|All Sex, n (%)|
|Men||47 (68.1)||31 (23,1)||<0.001|
|Women||22 (31.9)||103 (76.9)|
|Smoker, n (%)||10 (40)||15 (60)||0.5|
|Alcohol intake, n (%)||38 (38)||62 (62)||0.24|
|Comorbidities, n (%)||17(26.1)||48 (73.9)||0.09|
|Age (years)||57 (85, 20)||54 (82,20)||0.45|
|WC (cm)||89 (126,71)||86 (128,65)||0.006|
|SBP (mmHg)||120 (160,100)||120 (150, 90)||0.35|
|DBP (mmHg)||80 (110,70)||80 (110,60)||0.35|
|Glucose (mg/dL)||94 (160,74)||88 (163, 68)||<0.001|
|HDLChol (mg/dL), mean ± SD||42 ± 10.5||46 ± 9.9||0.004|
|Triglycerides (mg/dL)||185 (413, 54)||147 (779,48)||<0.001|
|Age (years)||55 (85, 20)||57 (76, 20)||0.75|
|WC (cm)||92 (117, 71)||92 (113, 78)||0.98|
|SBP (mmHg)||120 (160, 100)||120 (150, 100)||0.78|
|DBP (mmHg)||80 (110,70)||80 (100, 70)||0.99|
|Glucose (mg/dL)||94 (160,74)||90 (136, 78)||0.27|
|HDLChol (mg/dL)a, mean ± SD||39.8 ± 9.8||42.2 ± 8.9||0.28|
|Triglycerides (mg/dL)||187 (413,54)||151 (302,48)||0.04|
|Age (years)||58 (84, 22)||53 (82, 21)||0.18|
|WC (cm)||87 (126, 76)||84 (128, 65)||0.2|
|SBP (mmHg)||120 (150, 100)||120 (150, 90)||0.99|
|DBP (mmHg)||80 (100, 70)||80 (110, 60)||0.86|
|Glucose (mg/dL)||95 (126, 78)||87 (163, 68)||0.01|
|HDLChol (mg/dL), mean ± SD||45.7 ± 10.7||47.3 ± 9.9||0.5|
|Triglycerides (mg/dL)||178 (364,62)||145 (779,49)||0.08|
Table 1: Comparison of age and biochemical characteristics among patients with or without hyperuricemia.
Unless otherwise stated, the values are expressed as the medians and, maximum and minimum values: median (max, min). WC: waist circumference, SBP: systolic blood pressure, DBP: diastolic blood pressure, a HDLChol: HDL cholesterol (median, SD: standard deviation). The Mann-Whitney U-Test was used for comparing independent groups. The chi square test was used for comparing proportions.
There was a significant correlation between MS and waist circumference, diastolic blood pressure, fasting glucose, HDL (negative correlation), triglycerides and number of criteria for the total sample (Table 2). Women showed a significant correlation with the same variables, except for diastolic blood pressure. Men showed a significant correlation only with triglycerides and the number of criteria for MS.
|Systolic Blood Pressure||0.1||0.15||0.09||0.45||0.07||0.42|
|Diastolic Blood Pressure||0.19||0.007||0.14||0.21||0.16||0.08|
|Meets many criteria of MS||0.3||< 0.001||0.23||0.04||0.41||< 0.001|
Table 2: The correlation between the components of metabolic syndrome (MS) and uric acid.
Rho: Spearman´s Rho correlation coefficient
In the overall sample, patients with hyperuricemia had twice the odds of MS as subjects without hyperuricemia (p=0.02) (Table 3). Additionally, patients with hyperuricemia also had higher odds of hyperglycemia (OR 3.1, p<0.001) and hypertriglyceridemia than did patients with normal uric acid levels (OR 2.1, p=0.02). When the results were stratified by gender, women showed almost 5 times the odds of hyperglycemia as men (OR=4.8, 95%CI=1.7 to 13.4).
|Variables||With hyperuricemia||Without hyperuricemia||OR||95% CI||p|
|Abdominal obesity (%)||40.6||35.1||1.3||0.7-2.3||0.44|
|Arterial hypertension (%)||464||38.1||1.4||0.8-2.5||0,25|
|Hyperglycemia (%)||36.2||14.9||3.2||1.6-6.4||< 0.001|
|HDL Hypocholesterolemia (%)||58||61.2||0.9||0.5-1.6||0.66|
|MS (%)||48.9||35.5||1.7||0.7 – 4.4||0.24|
|Abdominal obesity (%)||40.4||41.9||0.9||0.4 – 2.4||0.94|
|Arterial hypertension (%)||46.8||45.2||1.1||0.4 – 2.7||0.89|
|Hyperglycemia (%)||34||22.6||1.8||0.7 – 4.9||0.28|
Table 3: Comparison of the prevalence of MS and its components in patients with or without hyperuricemia.
MS: metabolic syndrome, OR: odds ratio, proportions were compared using the Chi square test Abdominal obesity: waist circumference >88 cm (women) or >94 cm (men). Hypertension: SBP ≥ 135 mmHg or DBP >85. Hyperglycemia: fasting glucose ≥ 100 mg/dL. HDL Hypocholesterolemia: HDL cholesterol <50 mg/dL (women) or <40 mg/dL (men). Hypertriglyceridemia: triglycerides ≥ 150 mg/dL. Hyperuricemia: uric acid ≥ 7 mg/dL (men) or ≥ 6 mg/dL (women).
When comparing the prevalence of MS by quartiles, for-uric acid distribution, the quartile with the highest UA level (UA ≥ 6.3 mg/dL) had 3 times the odds of MS as the quartile with the lowest uric acid level (OR=3.1, 95% CI=1.4 to 7.1) (Table 4). We found a similar association in women but not in men.
|Patients||With MS n (%)||Without MS n (%)||OR||95% CI||P|
|IV (≥ 6.30 mg/dL||29 (37.2)||24 (19.2)||3.1||1.4 – 7.1||0.006|
|III (5.5 – 6.29 mg/dL)||22 (28.2)||30 (24.0)||1.9||0.8 – 4.3||0.013|
|II (4.6 – 5.49 mg/dL)||13 (16.7)||35 (28.0)||0.9||0.4 – 2.3||0.91|
|I (<4.6 mg/dL)||14 (17.9)||36 (28.8)||1||--||--|
|IV (≥ 6.30 mg/dL)||21 (61.8)||19 (43.2)||1.4||0.3 – 7.4||0.64|
|III (5.5 – 6.29 mg/dL)||7 (20.6)||10 (22.7)||0.9||0.2 – 5.5||0.94|
|II (4.6 – 5.49 mg/dL)||3 (8.8)||11 (25.0)||0.4||0.1 – 2.6||0.3|
|I (<4.6 mg/dL)||3 (8.8)||4 (9.1)||1||--||--|
|IV (≥ 6.30 mg/dL)||8 (18.2)||5 (6.2)||4.7||1.3 – 17.3||0.02|
|III (5.5 – 6.29 mg/dL)||15 (34.1)||20 (24.7)||2.2||0.8 – 5.7||0.11|
|II (4.6 – 5.49 mg/dL)||10 (22.7)||24 (29.6)||1.2||0.4 – 3.3||0.71|
|I (<4.6 mg/dL)||11 (25.0)||32 (39.5)||1||--||--|
Table 4: Comparison of quartiles of uric acid in patients with and without metabolic
syndrome MS: metabolic syndrome. OR: odds ratio. P=probability. n:number of subjects with the characteristic of interest.
Table 5 shows two models of multivariate analysis using binary logistic regression to investigate whether the UA level (independent variable) that was represented in a continuous scale (mg/dL) or according to an ordinal expression (quartiles) was associated with MS (dependent variable). When adjusted by gender in Model I, UA levels expressed in mg/dL were significantly associated with the presence of MS (OR=1.5, 95% CI=1.2 to 1.9). Once we assessed the results according to gender, the association between the UA level (mg/dL) and the presence of MS persisted. Uric acid was grouped into quartiles in Model II, and the fourth quartile (AU ≥ 6.3 mg/dL) showed a strong association with the presence of MS (OR=3.1, 95% CI=1.3 to 7.1) after the results were adjusted by gender. Additionally, age showed a weak association with CI values, with the results being very close to 1.
|Variables||Unadjusted model||Adjusted model|
|OR (95%CI)||P||OR (95%CI)||P|
|Model I. Dependent variable: presence of MS|
|Uric acid, mg/dL||1.6 (1.2 -2.1)||0.001||1.5 (1.2-1.9)||0.001|
|Age||1.03 (1.003-1.05)||0.03||1.03 (1.003-1.05)||0.03|
|Sex female||1.3 (0.6-2.6)||0.46||---||0.46|
|Uric acid, mg/dL||1.4 (1.01-23)||0.04||14 (1.01-2.0)||0.04|
|Uric acid, mg/dL||1.7 (1.2-2.6)||0.007||1.7 (1.2-2.6)||0.007|
|Age||1.04 (1.006-107)||0.02||1.04 (1.006-1.07)||0.02|
|Model II. Dependent variable: presence of MS|
|4.6 a 5.49 mg/dL||0.98 (0.4-2.4)||0.96||0.96 (0.4-2.4)||0.94|
|5.5 a 6.29 mg/dL||1.8 (0.8-4.2)||0.17||1.8 (0.8-4.1)||0.18|
|≥ 6.3 mg/dL||3.3 (1.3-8.3)||0.01||3.1 (1.3-7.1)||0.008|
|Age||1.03 (1.003-1.05)||0.03||1.03 (1.003-1.05)||0.03|
|Sex female||1.1 (0.6-2.2)||0.78||–––||0.78|
Table 5: Multivariate analysis using the presence of MS as the dependent variable
MS: metabolic syndrome. OR: odds ratio (obtained by logistic regression), Model I: Uric acid was introduced as a continuous variable, Model II: Uric acid was introduced as categorical variable. Reference category: uric acid<4.6mg/dL. The OR was not calculated for adjusted variables.
Table 6 shows a multivariate analysis with hyperuricemia as the dependent variable. When analyzing the total sample after adjusting for age and other criteria for MS, both fasting hyperglycemia (OR=3.0, 95% CI=1.4 to 6.3) and male gender (OR=6.8, 95% CI 3.5 to 13.2) were identified as strong factors associated with hyperuricemia. However, when analyzing the results according to gender, there were no significant associations I men. Women, however, showed a strong association between fasting hyperglycemia and hyperuricemia (OR=4.8, 95% CI=1.7 to 13.4%).
|Variables||Unadjusted model||Adjusted model|
|OR (95%CI)||P||OR (95% CI)||P|
|Dependent variable: presence of hyperuricemia|
|Abdominal obesity||0.9 (0.5-1.9)||0.83||-||0.88|
|Arterial hypertension||1.02 (0.5-2.1)||0.96||-||0.93|
|Hyperglycemia||2.7 (1.2-6.1)||0.02||3.0 (1.4-6.3)||0.005|
|HDL Hypocholesterolemia||1.04 (0.5-2.2)||0.91||-||0.69|
|Sex male||6.8 (3.4-13.5)||< 0.001||6.8 (3.5 -13.2)||< 0.001|
|Abdominal obesity||0.8 (0.3-2.3)||0.74||-||0.89|
|Arterial hypertension||0.9 (0.3-2.7)||0.93||-||0.89|
|HDL Hypocholesterolemia||0.9 (0.3-2.7)||0.91||-||0.61|
|Abdominal obesity||0.9 (0.3-2.6)||0.79||-||0.84|
|Arterial hypertension||1.2 (0.4-3.4)||0.71||-||0.63|
|Hyperglycemia||4.4 (1.4-13.7)||0.01||4.8 (1.7-13.4)||0.003|
|HDL Hypocholesterolemia||13 (0.4-4.1)||0.68||-||0.55|
Table 6: Multivariate analysis using the presence of hyperuricemia as a dependent variable
OR: odds ratio (obtained by logistic regression).
Hyperuricemia: uric acid ≥ 7 mg/dL (men) or ≥ 6 mg/dL (women).
The OR was not calculated for adjusted variables.
HDL Hypocholesterolemia: HDL cholesterol <50 mg/dL (women) or <40 mg/dL (men).
In our study, a direct relationship was observed between uric acid levels and the prevalence of MS, even after adjusting for potential confounders. One of the important findings in our study was the high prevalence of hyperuricemia (34%), which was higher than the estimates reported for some populations (8.4% among Iranian adults, and 14.4% among Chinese adults, 24.4% among Spanish adults, and 31.4% among other populations in Mexico) using the same definition of hyperuricemia [9,11,16,18]. It is noteworthy that nearly half (49.3%) of the subjects with hyperuricemia had MS. It should be noted that the size of the minimum sample was greatly exceeded.
When the results were stratified by gender, significant correlations between the level of UA and some of the components of MS such as waist circumference (only in women), triglycerides (both male and female) and fasting glucose (only in women) were found. Although significant epidemiological studies have established a close relationship between hyperuricemia and an increased prevalence of MS components, including glucose levels in plasma, triglycerides/HDLcholesterol, obesity and hypertension [16,19] the results of this study only showed an association with hyperglycemia in women.
In the multivariate model, when the results were adjusted for confounding factors such as age and gender, a greater presence of hyperuricemia was observed in men. These results are consistent with the studies conducted in China and Iran [4,12,18].This was a crosssectional study; therefore, there were no dependent or independent variables, because both were measured concurrently, and it could not be guaranteed that the temporary criteria were met. This is the reason we used different models for different dependent variables .
The underlying mechanism of gender regarding the levels of UA and the risk for MS has not been elucidated to date . A study conducted in American women showed that natural and surgical menopause was independently associated with hyperuricemia, while the use of replacement hormones was associated with low levels of UA in .
Surprisingly, according to our results, no criteria for MS were associated with hyperuricemia in men; only a weak association with triglycerides was found in the correlation matrix. This finding was not ratified in the multivariate model. These results differ from those of another study in a population of middle-aged and elderly individuals who reported a close relationship between the UA and triglycer levels in men, with a better lipid index associated with hyperuricemia in men then in women [20,21].
In contrast, it must be noted that in our analysis, the presence of hyperglycemia was strongly associated with hyperuricemia (almost five times) in women. These results are consistent with those obtained by Viazzi and collaborators ,where the UA levels was a powerful predictor of type 2 diabetes mellitus in primary hypertension, especially in women .
The prevalence of both gout and hyperuricemia remains substantial and may have increased over the past 2 decades, which is likely related to increasing frequencies of adiposity and hypertension . Furthermore, emerging evidence suggests that gout is strongly associated with metabolic syndrome  and may lead to myocardial infarction [24-26], type 2 diabetes mellitus , and premature death [23,28].
The non-response rate was 35.1%. However, since the prevalence found in our study was consistent with that reported in Mexico, we consider the risk to be low. There were other factors that could have influenced the level of UA such as eating and lifestyle habits, and other comorbidities .
Our results show that high concentrations of uric acid are associated with metabolic syndrome and suggest that the presence of fasting hyperglycemia is strongly associated with hyperuricemia in women.
We are grateful to Dr. Esteban Cedillo-Couvert from the University of Illinois at Chicago for providing valuable comments and corrections to this paper.
- Ford ES (2005) Risks for all-cause mortality, cardiovascular disease, and diabetes associated with the metabolic syndrome: a summary of the evidence. Diabetes Care 28: 1769-1778.
- Ioachimescu AG, Brennan DM, Hoar BM, Hazen SL, Hoogwerf BJ (2008) Serum uric acid is an independent predictor of all‐cause mortality in patients at high risk of cardiovascular disease: A preventive cardiology information system (PreCIS) database cohort study. Arthritis Rheum 52: 623-630.
- Mangge H, Zelzer S, Puerstner P, Schnedl WJ, Reeves G, et al. (2013) Uric acid best predicts metabolically unhealthy obesity with increased cardiovascular risk in youth and adults. Obesity 21: E71-77.
- Chiou WK, Wang MH, Huang DH, Chiu HT, Lee YJ, et al. (2010) The relationship between serum uric acid level and metabolic syndrome: differences by sex and age in Taiwanese. J Epidemiol 20: 219-224.
- Lee YJ, Cho S, Kim SR (2014) A possible role of serum uric acid as a marker of metabolic syndrome. Intern Med J 44: 1210-1216.
- Zhang ML, Gao YX, Wang X, Chang H, Huang GW (2013) Serum uric acid and appropriate cutoff value for prediction of metabolic syndrome among Chinese adults. J Clin Biochem Nutr 52: 38-42.
- Goncalves JP, Oliveira A, Severo M, Santos AC, Lopes C (2012) Cross-sectional and longitudinal associations between serum uric acid and metabolic syndrome. Endocrine 41: 450-457.
- Gutiérrez JP, Rivera-DJ, Shamah-LT, Villalpando-HS, Franco A, et al. (2012) Encuesta Nacional de Salud y Nutrición 2012. Resultados Nacionales. Cuernavaca, México Instituto Nacional de Salud Pública.
- Barrera Cruz A, Rodríguez GA, Molina AM (2013) Escenario actual de la obesidad en México. Rev Med Inst Mex Seguro Soc 51: 292-299.
- Escobedo de la Peña J, De Jesús Pérez R, Schargrodsky H, Champagne B (2014) Prevalencia de dislipidemias en la ciudad de México y su asociación con otros factores de riesgo cardiovascular. Resultados del estudio CARMELA. Gac Med Mex 150: 128-136
- Campos-Nonato I, Hernández-Barrera L, Rojas-Martínez R, Pedroza A, Medina-García C, et al. (2013) Hipertensión arterial: prevalencia, diagnóstico oportuno, control y tendencias en adultos mexicanos. Salud Pública Mex 55: S144-S150.
- Ziaee A, Esmailzadehha N, Ghorbani A, Asefzadeh S (2013) Association between Uric Acid and Metabolic Syndrome in Qazvin Metabolic Diseases Study (QMDS), Iran Glob J Health Sci 5: 155-165.
- WHO, World Health Organization (2007) The WHO STEPwise approach to chronic disease risk factor surveillance (STEPS). STEPS Instrument. Geneva, Switzerland
- Sierra-Johnson J, Johnson BD, Allison TG, Bailey KR, Schwartz GL, et al. (2006) Correspondence between the adult treatment panel III criteria for metabolic syndrome and insulin resistance. Diabetes Care 29: 668-672.
- Grundy SM, Brewer HB Jr, Cleeman JI, Smith SC Jr, Lenfant C (2004) American eart A. Definition of metabolic syndrome: Report of the National Heart, Lung, and Blood Institute/American Heart Association Conference on Scientific issues related to definition. Circulation 109: 433-438.
- Rosas-Guzmán J, González-Chávez A, Aschner P, Bastarrachea R (2010) Epidemiología, Diagnóstico, Control, Prevención y Tratamiento del Síndrome Metabólico en Adultos. Santiago, Chile: Asociación Latinoamericana de Diabetes.
- Kim SY, Guevara JP, Kim KM, Choi HK, Heitjan DF, et al. (2010) Hyperuricemia and coronary heart disease: A systematic review and meta-analysis. Arthritis Care Res 62: 170-180.
- Fu YQ, Yang H, Zheng JS, Zeng XY, Zeng W, et al. (2017) Positive association between metabolic syndrome and serum uric acid in Wuhan. Asia Pac J Clin Nutr 26: 343-350.
- Hak AE, Choi HK (2008) Menopause, postmenopausal hormone use and serum uric acid levels in US women-The Third National Health and Nutrition Examination Survey. Arthritis Res Ther 10: R116.
- Xu J, Peng H, Ma QH, Zhou XH, Xu WX, et al. (2014) Associations of non-high density lipoprotein cholesterol and traditional blood lipid profiles with hyperuricemia among middle-aged and elderly Chinese people: a community-based cross-sectional study. Lipids Health Dis 13: 117.
- Viazzi F, Leoncini G, Vercelli M, Deferrari G, Vercelli M (2011) Serum Uric Acid Levels Predict New-Onset Type 2 Diabetes in Hospitalized Patients With Primary Hypertension: The MAGIC Study. Diabetes care 34: 126-128.
- Zhu Y, Pandya BJ, Choi HK (2011) Prevalence of gout and hyperuricemia in the US general population: The National Health and Nutrition Examination Survey 2007–2008. Arthritis Rheum 63: 3136-3141.
- Choi HK, Ford ES, Li C, Curhan G (2007) Prevalence of the metabolic syndrome in patients with gout: the Third National Health and Nutrition Examination Survey. Arthritis Rheum 57: 109-115.
- Abbott RD, Brand FN, Kannel WB, Castelli WP (1998) Gout and coronary heart disease: the Framingham Study. J Clin Epidemiol 41: 237-242.
- Choi HK, Curhan G (2007) Independent impact of gout on mortality and risk for coronary heart disease. Circulation 116: 894-900.
- Krishnan E, Baker JF, Furst DE, Schumacher HR (2006) Gout and the risk of acute myocardial infarction. Arthritis Rheum 54: 2688-2696.
- Choi HK, De Vera MA, Krishnan E (2008) Gout and the risk of type 2 diabetes among men with a high cardiovascular risk profile. Rheumatology (Oxford) 47: 1567-1570.
- Krishnan E, Svendsen K, Neaton JD, Grandits G, Kuller LH (2008) Long-term cardio vascular mortality among middle-aged men with gout. Arch Intern Med 168: 1104-1110.
- Zimmet P, Magliano D, Matsuzawa Y, Alberti G, Shaw J (2005) The metabolic syndrome: a global public health problem and a new definition. J Atheroscler Thromb 12: 295-300.
Citation: Aguilar-Andrade G, Álvarez-Bañuelos TM, Morales-Romero J, Fonseca-Reyes S, Margozzini-Maira P, et al. (2018) Relationship between Uric Acid and Metabolic Syndrome among Users of a Primary Care Clinic in Mexico. Metabolomics (Los Angel) 8: 197. DOI: 10.4172/2153-0769.1000197
Copyright: © 2018 Aguilar-Andrade G, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Select your language of interest to view the total content in your interested language
Share This Article
- Total views: 498
- [From(publication date): 0-2018 - Sep 25, 2018]
- Breakdown by view type
- HTML page views: 467
- PDF downloads: 31