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Prevalence of Hyperuricemia and its Relationship with Metabolic Syndrome in Thai Adults Receiving Annual Health Exams
Archives of Medical Research 37 (2006) 883–889
ORIGINAL ARTICLE
Prevalence of Hyperuricemia and its Relationship with Metabolic Syndrome in Thai Adults Receiving Annual Health Exams Vitool Lohsoonthorn,a Bodi Dhanamun,a and Michelle A. Williamsb a
b
Department of Preventive and Social Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand Department of Epidemiology, Multidisciplinary International Research Training Program, University of Washington School of Public Health and Community Medicine, Seattle, Washington Received for publication October 25, 2005; accepted March 27, 2006 (ARCMED-D-05-00443).
Background. Associations between hyperuricemia, metabolic syndrome, cardiovascular disease and diabetes have been reported. Limited information, however, is available concerning the prevalence and correlates of hyperuricemia among Thai men and women. We sought to estimate the prevalence of hyperuricemia among a population of patients receiving annual health exams and to evaluate its relationship with metabolic syndrome (MetS). Methods. We conducted a cross-sectional study of 1,381 patients (376 men and 1,005 women) who first participated in annual health examinations at the Preventive Medicine Clinic of the King Chulalongkorn Memorial Hospital in Bangkok, Thailand during the period July 1999 through February 2000. Hyperuricemia was defined as O7.0 mg/dL in men and O6.0 mg/dL in women. MetS was defined using the modified ATP III criteria. Results. The overall prevalence of the hyperuricemia was 10.6%. The condition was more common in men than in women (18.4 vs. 7.8%). Among women, serum uric acid was statistically significantly correlated with body mass index (BMI), systolic and diastolic blood pressure, high-density lipoprotein-cholesterol, triglyceride and fasting plasma glucose (all p !0.05). Men with serum uric acid concentrations O6.7 mg/dL (upper quartile) had a 3.91-fold increased in risk of MetS (95% CI:1.36–11.23), as compared with those who had concentrations !5.1 mg/dL (lowest quartile). Among women, the risk of MetS increased at least 2-fold for concentration of serum uric acid concentrations O4.0 mg/dL ( p for trend !0.001). Conclusions. Hyperuricemia is prevalent among Thai men and women receiving routine health exams. Additionally, serum uric acid is positively associated with MetS. Ó 2006 IMSS. Published by Elsevier Inc. Key Words: Prevalence, Hyperuricemia, Metabolic syndrome.
Introduction Hyperuricemia is commonly detected in subjects with abnormal purine metabolism, including overproduction of uric acid and insufficient uric acid excretion from the kidney (1). Prolonged hyperuricemia, often associated with gout, is an important risk factor for damaged joint (2). Hyperurice-
Address reprint requests to: Dr. Vitool Lohsoonthorn, University of Washington, MIRT Program, Department of Epidemiology (Box 357236), 1959 NE Pacific Street (HSB, F-263), Seattle, WA 98195; E-mail: [email protected]
mia has been shown to be associated with several components of metabolic syndrome (MetS) and investigators have postulated that increased concentrations of uric acid may be another important component of the syndrome (3). In some epidemiologic studies, a close relationship between hyperuricemia and hypertension, insulin resistance and cardiovascular disease risk factors (such as obesity and smoking) has been reported (4–7). Hyperuricemia is diagnosed in 5–30% of the general population, although the prevalence is higher among some ethnic groups (e.g., Japanese) and appears to be increasing worldwide (8). Serum uric acid concentrations are known to increase with age
0188-4409/06 $–see front matter. Copyright Ó 2006 IMSS. Published by Elsevier Inc. doi: 10.1016/j.arcmed.2006.03.008
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and are further increased after menopause in women (9). Considering current increases in the incidence and prevalence of obesity and MetS worldwide, as well as emerging evidence documenting associations between hyperuricemia and cardiovascular complications, Conen and colleagues have called for increased emphasis to be placed on understanding the epidemiological characteristic of hyperuricemia in developing countries (4). Little information, however, exists concerning the prevalence and epidemiological characteristics of hyperuricemia in Thailand. We, therefore, conducted the present study to estimate the prevalence of hyperuricemia among Thai men and women receiving routine health examinations. We also sought to evaluate the extent to which, if at all, serum uric acid concentrations were associated with the risk of MetS.
Methods Study Population and Data Collection We conducted a cross-sectional study of 1,381 patients (376 men and 1,005 women) who first participated in annual health examinations at the Preventive Medicine Clinic of the King Chulalongkorn Memorial Hospital in Bangkok, Thailand during the period of July 1999 through February 2000. Participants were those with no previously diagnosed diabetes mellitus, hypertension, or gout and were not taking uric acid-, lipid- or blood pressure-lowering medication. During routine clinic visits participants were asked to provide information about their age, marital status, occupation, educational level, medical history, smoking status, alcohol consumption habits, participation in regular weekly physical exercise and other recreational physical activities. Participants underwent routine physical examinations that included determining their height, weight, resting blood pressure, and providing an overnight fasting venous blood sample. Standing height was measured without shoes to the nearest 0.5 cm. Weight was determined without shoes and with participants lightly clothed. Weight was measured using an automatic electronic scale (Seca, Inc., Hamburg, Germany) to the nearest 100 g. Blood pressure was determined using an automatic sphygmomanometer (UDEXIIa, UEDA Corporation, Tokyo, Japan). Participants were instructed to sit resting for 5 min before blood pressure measurements were determined. Laboratory Analyses Participants provided an overnight fasting venous blood sample. Serum samples were used to determine participants’ lipid profiles. Serum triglyceride (TG) concentration was determined by standardized enzymatic procedures using glycerol phosphate oxidase assay. High-density lipoprotein–cholesterol (HDL-C) was measured by a chemical
precipitation technique using dextran sulfate. Serum uric acid concentrations were measured using the Uricase EMST method. Plasma samples were used to determine participants’ fasting plasma glucose (FPG) using the hexakinase method. All laboratory assays were completed without knowledge of participants’ medical history. Lipid, lipoprotein, uric acid and plasma glucose concentrations were reported as mg/dL. All participants provided informed consent and the research protocol was reviewed and approved by the Ethical Committee of the Faculty of Medicine, Chulalongkorn University, and the Division of Human Subjects Research, University of Washington, Seattle, WA. Analytical Variable Specification MetS was defined using a modified version of the ATP III criteria (10). Briefly, four of the five MetS components were defined using the following ATP III categorizations: 1) high blood pressure $130/85 mmHg; 2) hypertriglyceridemia $150 mg/dL; 3) low high-density lipoprotein-cholesterol (HDL-C) !40 mg/dL for men and !50 mg/dL for women; 4) hyperglycemia or high fasting glucose $110 mg/dL. The fifth component was defined based on body mass index (BMI) rather than on waist circumference measurements to identify individuals with central adiposity because we did not have measurements of waist circumference (11). We classified participants with a BMI $25 kg/m2 as having high central obesity. Participants with three of any of the five components were classified as having MetS. We defined subjects as having hyperuricemia if their serum uric acid concentration was O7.0 mg/dL (in men) or O6.0 mg/dL (in women) (12,13). We also classified subjects according to categories of uric acid. Uric acid concentrations were categorized into approximate quartiles for men and women separately. The resulting four categories for men were 1) !5.1 mg/dL; 2) 5.1–5.8 mg/dL; 3) 5.9– 6.7 mg/dL; and 4) O6.7 mg/dL. The corresponding categories for women were as follows: 1) !3.5 mg/dL; 2) 3.5–4.0 mg/dL; 3) 4.1–4.6 mg/dL; and 4) O4.6 mg/dL. Statistical Analyses We first explored frequency distributions of sociodemographic, behavioral characteristics and medical histories. For categorical variables we used the chi-square test to evaluate differences in distribution of covariates for affected and unaffected patients. Pearson’s correlation coefficients were obtained for each of the MetS components and the respective uric acid concentration. Fasting plasma glucose and TG were skewed and were normalized by logarithmic transformation in all analyses. Mean uric acid concentrations were calculated across the categorized components of MetS. All mean values were adjusted for years of age, smoking status, drinking status and the other MetS components by means of a multiple linear regression
Prevalence of Hyperuricemia and its Relation to Metabolic Syndrome
model. Logistic regression procedures were used to examine the risks of having metabolic syndrome. Univariate and multiple variable logistic regression procedures were employed to calculate unadjusted odd ratios (OR) of potential risk factors associated with metabolic syndrome. Confidence intervals were also reported for each OR. Confounding factors were evaluated on the basis of their hypothesized relationship with covariates of interest and with metabolic syndrome. Confounding was assessed by entering potential cofounders into a logistic regression model one at a time and by comparing the adjusted and unadjusted ORs (14). Final logistic regression models included covariates that altered unadjusted ORs by at least 10%. All analyses were completed separately for male and female patients. Statistical analyses were performed using SPSS (version 13.0, SPSS Inc., Chicago, IL) software. All reported p values are two tailed, and confidence intervals were calculated at the 95% level.
Results Overall, the prevalence of hyperuricemia was 10.6% in this study population. Hyperuricemia was more common in men than in women (18.4 vs. 7.8%) (Table 1). Men with hyperuricemia, as compared to those without the condition, were older ( p 5 0.001), were more likely to have reported smoking ( p 5 0.019), and were former consumers of alcohol ( p 5 0.184). Women with hyperuricemia as compared with their counterparts without the condition were older ( p !0.001), less well educated ( p 5 0.004) and were less likely to report that they participated in regular exercise ( p 5 0.070). Participation in leisure-time activities, as well as occupation as a laborer, were not statistically significantly associated with hyperuricemia. As shown in Table 2, among men the prevalence of MetS increased across successive quartiles of serum uric acid concentrations. A similar linear gradient of increased prevalence of MetS across increasing quartile of uric acid was observed for women (4.0, 4.8, 11.4 and 22.6% for successive quartiles). Adjusted mean serum uric acid concentrations according to presence or absence of each of the five components of MetS are listed in Table 3. Women with MetS-defining abnormalities had higher serum uric acid concentrations than those without such abnormalities. This pattern of association was not evident among men. Women with BMI $25 kg/m2, high blood pressure, high FPG, high TG or low HDL-C had serum uric acid concentrations that were approximately 0.23–0.65 mg/dL higher than those without metabolic abnormalities ( p !0.05). Men with elevated TG had statistically significant higher serum uric acid concentration (0.65 mg/dL) ( p !0.001) than those without elevated TG. Table 4 summarizes Pearson’s correlation coefficients between each of the MetS-defining abnormalities and serum uric acid concentrations. Among men, uric acid
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concentrations were statistically significantly positively correlated ( p !0.01) with body mass index, diastolic blood pressure, and log-transformed serum triglyceride concentrations. Uric acid was negatively correlated with serum HDL-C and log-transformed fasting plasma glucose concentrations. Uric acid concentrations were most strongly correlated with serum triglyceride concentrations (r 5 0.35) and body mass index (r 5 0.27). Among women, statistically significant positive correlations were noted for the serum uric acid concentrations with body mass index, systolic and diastolic blood pressure, log-transformed triglyceride and log-transformed fasting plasma glucose concentrations. Uric acid concentrations were inversely correlated with serum HDL-C concentrations ( p !0.001). Among women, body mass index (r 5 0.37) and serum triglyceride concentrations (r 5 0.39) were most strongly correlated with uric acid concentrations. We next evaluated the relative risk of MetS in relation to varying concentrations of serum uric acid in men and women, respectively. For these analyses, we used multivariable logistic regression procedures to control for confounding factors. Results from these analyses are summarized in Table 5. There was some evidence of a linear component in risk of MetS in relation to uric acid concentrations ( p for trend 5 0.002). After adjusting for confounding by age, smoking status and recent alcohol consumption, we noted that men with uric acid concentrations in the highest quartile (O6.7 mg/dL) had a 3.91-fold increased in risk of MetS as compared with men with uric acid concentrations in the lowest quartile (!5.1 mg/dL) (OR 5 3.91, 95% CI: 1.36– 11.23). Among women, the risk of MetS increased in relation to serum uric acid concentrations O4.0 mg/dL, and a positive linear trend in risk across quartiles was noted ( p for trend !0.001). Women with uric acid concentrations in the third quartile (4.1–4.6 mg/dL), as compared with those with concentrations in the first quartile (!3.5 mg/dL), had a 2.37-fold increased risk of MetS (95% CI: 1.06–5.28). Women with concentrations O4.6 mg/dL (fourth quartile) had an almost 5-fold increased risk of MetS (OR 5 4.86, 95% CI: 2.33–10.14) as compared with women with value in the reference group (!3.5 mg/dL, first quartile).
Discussion The 10.6% prevalence of hyperuricemia noted among Thai men and women in our study is higher than estimates reported for several other populations. For instance, Al-Arfaj and colleagues reported that the prevalence of hyperuricemia was 8.4% among Saudi men and women (15). Notably, hyperuricemia was defined using the same criteria for both studies. The prevalence of hyperuricemia in our study population is lower, however, than estimates reported for Japanese men and women who participated in a community-based mass screening program in Okinawa, Japan. In their study
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Table 1. Characteristics of study population according to hyperuricemia status among Thai men and women receiving health exams
Characteristics
Men
Women
Hyperuricemia
Hyperuricemia
No (n 5 307)
No (n 5 927)
n
%
n
%
3 54 83 59 57 40 11
1.0 17.6 27.0 19.2 18.6 13.0 3.6
3 4 12 25 9 11 5
4.3 5.8 17.4 36.2 13.0 15.9 7.2
43.7 6 13.9
47.6 6 14.6
p value 0.001
n
%
n
%
9 131 229 277 190 77 14
1.0 14.1 24.7 29.9 20.5 8.3 1.5
1 2 12 20 21 19 3
1.3 2.6 15.4 25.6 26.9 24.4 3.8
43.1 6 12.1
0.036 0.981
84 125 93
27.8 41.4 30.8
20 28 21
29.0 40.6 30.4
42 264
13.7 86.3
9 60
13.0 87.0
110 196
35.9 64.1
19 50
27.5 72.5
163 143
53.3 46.7
26 43
37.7 62.3
158 147
51.8 48.2
31 38
44.9 55.1
202 102 64
66.4 33.6 20.9 112.1 6 52.8 126.8 6 76.0 1.1 6 0.4
50 19 20
72.5 27.5 29.0 107.1 6 33.0 175.6 6 114.6 1.2 6 0.4
Yes (n 5 78)
51.2 6 11.7
!0.001 0.004
441 250 218
48.5 27.5 24.0
51 17 8
67.1 22.4 10.5
121 805
13.1 86.9
11 67
14.1 85.9
708 216
76.6 23.4
64 14
82.1 17.9
868 54
94.1 5.9
72 6
92.3 7.7
319 602
34.6 65.4
35 43
44.9 55.1
576 350 130
62.2 37.8 14.0
46 32 28
59.0 41.0 35.9 110.8 6 31.9 192.0 6 144.5 0.9 6 0.3
0.881
0.795
0.184
0.274
0.019
0.512
0.302
0.070
0.335
0.146 0.448 0.001 0.004
p value !0.001
0.573
99.1 6 28.6 103.4 6 61.8 0.8 6 0.1
!0.001 0.001 !0.001 !0.001
Lohsoonthorn et al./ Archives of Medical Research 37 (2006) 883–889
Age (years) !20 20–29 30–39 40–49 50–59 60–69 $70 (Mean 6 SD) Education #Primary education !Bachelor degree $Bachelor degree Laborer occupation Yes No Drinking status Never drinker Ever drinker Smoking status Never smoker Ever smoker Exercise Yes No Recreational activities Yes No Hypertension (%) FPG (mean 6 SD) Triglyceride (mean 6 SD) Creatinine (mean 6 SD)
Yes (n 5 69)
Prevalence of Hyperuricemia and its Relation to Metabolic Syndrome Table 2. Prevalence of metabolic syndrome by quartiles of serum uric acid concentration among Thai men and women receiving health exams Men
Women
Uric acid (mg/dL)*
n
(%)
Uric acid (mg/dL)*
n
(%)
1st Q (!5.1) 2nd Q (5.1–5.8) 3rd Q (5.9–6.7) 4th Q (O6.7) Total
5 8 26 19 58
(5.8) (9.1) (24.1) (21.1) (15.4)
1st Q (!3.5) 2nd Q (3.5–4.0) 3rd Q (4.1–4.6) 4th Q (O4.6) Total
9 11 26 72 118
(4.0) (4.8) (11.4) (22.6) (11.7)
*Q refers to quartiles.
of 4,489 subjects, Nagahama and colleagues reported that 24.4% of participants were diagnosed with hyperuricemia. Hyperuricemia was defined as serum uric acid $7.0 mg/dL and $6.0 mg/dL in men and women, respectively (16). From the Nutritional and Health Survey in Taiwan (17), 26% of adult males ($19 years) either had hyperuricemia (serum uric acid O7.7 mg/dL) or were taking medication for it. The investigators also reported that approximately 17% of adult females had hyperuricemia (serum uric acid O6.6 mg/dL) or were taking medication for the condition. The prevalence of hyperuricemia is age dependent. In the present study, hyperuricemia was infrequent among younger subjects (!5% for both men and women in the 20- to 29-year-age group) but rose considerably to 36.2 and 25.6% for men and women, respectively, in the 40to 49-year-age group. Similar patterns of increased prevalence of hyperuricemia with increasing age have been reported by several other investigators (18,19). Consistent
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with observations recently reported by Ishizaka and colleagues, we noted a general increase in the prevalence of MetS with increased concentrations of serum uric acid (20). In our study population, serum uric acid concentrations were statistically significantly and positively correlated with body mass index, diastolic blood pressure and serum triglyceride concentrations; and statistically significant and inverse correlations were noted for serum uric acid and serum HDL-C concentrations. These associations were generally similar to those reported by other investigators (13,21,22). In addition to being correlated with individual cardiovascular disease risk factors such as obesity, hypertension, and dyslipidemia, investigators have noted that hyperuricemic subjects tend to have a clustering of these risk factors (16). Moreover, increased serum uric acid concentrations have been positively associated with cardiovascular mortality in non-Hispanic White and African-American populations in the U.S. (18). Although we were not able to evaluate the relation between serum uric acid and incident cardiovascular disease, we did note positive linear associations between risk of component of MetS and quartiles of serum uric acid concentrations in men and women in our study population. These finings are similar to those reported by Ishizaka et al. (20) who reported that the odds ratios for MetS increased across successive quartiles of serum uric acid concentrations (odds ratios for women with corresponding 95% confidence intervals were as follows: 1.00 (reference group), 1.06 (0.60–1.87), 2.18 (1.30–3.64), and 4.17 (2.56–6.79). The corresponding odds ratios and 95% confidence intervals for men were as follows: 1.00 (reference group), 0.92 (0.74–1.14), 1.52 (1.25–1.65), and 1.97 (1.61–2.40).
Table 3. Adjusted means of uric acid (mg/dL) among Thai men and women according to selected features of metabolic syndrome Men
Variables Obesity BMI $25 kg/m2 BMI !25 kg/m2 High blood pressure SBP $130 mmHg or DBP $85 mmHg SBP !130 mmHg and DBP !85 mmHg High fasting plasma glucose FPG $110 mg/dL FPG !110 mg/dL High triglyceride TG $150 mg/dL TG !150 mg/dL Low HDL-cholesterol HDL-C !40 mg/dL(men)/!50 mg/dL (women) HDL-C $40 mg/dL(men)/$50 mg/dL (women)
n
Means of uric acid (95% CI)
14 356
6.34 (5.62–7.06) 6.01 (5.87–6.15)
151 219
Women
n
Means of uric acid (95% CI)
0.377
86 909
4.90 (4.67–5.14) 4.25 (4.18–4.32)
!0.001
6.02 (5.79–6.25) 6.03 (5.84–6.21)
0.970
303 692
4.47 (4.34–4.60) 4.24 (4.16–4.32)
0.005
81 289
5.94 (5.63–6.25) 6.05 (5.89–6.21)
0.554
113 882
4.53 (4.32–4.74) 4.28 (4.21–4.35)
0.029
123 247
6.46 (6.21–6.72) 5.81 (5.63–5.98)
!0.001
197 798
4.65 (4.49–4.82) 4.23 (4.15–4.30)
!0.001
90 280
6.29 (6.00–6.57) 5.94 (5.78–6.10)
0.042
317 678
4.47 (4.35–4.59) 4.23 (4.15–4.32)
0.002
p value
p value
Separate models were estimated for men and women. Means of uric acid were adjusted for age, smoking status, drinking status, BMI, high blood pressure, high fasting plasma glucose, high triglyceride and low HDL-cholesterol.
Lohsoonthorn et al./ Archives of Medical Research 37 (2006) 883–889
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Table 4. Pearson’s correlation coefficients (r) for each component of metabolic syndrome in relation to uric acid concentrations (mg/dL) Men
Covariate Age (years) Body mass index (kg/m2) Systolic blood pressure (mmHg) Diastolic blood pressure (mmHg) HDL (mg/dL) Log-transformed triglyceride (mg/dL) Log-transformed FPG (mg/dL)
Women
Pearson Pearson correlation (r) p value correlation (r) p value 0.12 0.27
0.021 !0.001
0.28 0.37
!0.001 !0.001
0.06
0.285
0.24
!0.001
0.14
0.006
0.22
!0.001
20.15 0.35
0.005 !0.001
20.19 0.39
!0.001 !0.001
20.06
0.244
0.09
0.003
Biological mechanisms for the statistical associations observed in our study are presently unknown. However, results from several animal experimental studies suggest that hyperuricemia may affect blood pressure acutely through a rennin-dependent pathophysiological pathway (23). Additionally, hyperuricemia has been postulated to promote hypertension by contributing to systemic endothelial dysfunction and oxidative stress (24–26). Emerging evidence documents associations of insulin resistance and hyperglycemia with increased uric acid concentrations (13). Leyva et al. have postulated that insulin resistance may attenuate tubular secretion of urate and thus lead to hyperuricemia (27). There are several compelling mechanistic hypotheses that may explain consistently observed associations between uric acid and cardiovascular disease risk factors and additional longitudinal studies that clearly identify the temporal relation between changes in renal function according to changes in risk factors are needed to more thoroughly and empirically evaluate these mechanistic hypotheses.
Our study has several limitations. First, this study was cross-sectional in design, and thus did not permit the identification of a causal relationship between hyperuricemia and MetS. Second, our study has a higher proportion of women (72.8%) than men (27.2%). This may be due to the fact that women were more health conscious and assertive in seeking annual health examinations than men. Furthermore, the proportions of abnormal metabolic parameters in this study population were slightly higher than those from the National Health Survey in Thailand (28). Hence, results from our study may not be able to be generalized to Thai men and women who do not avail themselves of preventive medical services. Third, misclassification of MetS status may have occurred in our study because we did not have direct measurements of waist circumference and thus had to use BMI as a proxy measure of central adiposity. In sensitivity analyses, we noted that excluding BMI from the criteria for MetS did not alter the association between uric acid and the risk of MetS (data not shown). Fourth, we were not able to thoroughly evaluate hyperuricemia in relation to a broader range of behavioral and environmental characteristics of our study population. In particular, we did not have precise details concerning type and frequency of participants’ dietary habits, frequency and duration of physical activity, and pattern of adult weight gain. Conducting larger prospective cohort studies that employ validated data collection instruments and which integrates serial measurements of biological markers will likely overcome these noted limitations. In conclusion, we noted that serum uric acid concentrations were associated with clustered components of MetS in Thai men and women receiving routine health care in Bangkok, Thailand. The prevalence of hyperuricemia in this population was as high as in those of some developed and developing countries (15), but considerably lower than estimates reported for Japanese adults in Okinawa (16) and Taiwanese adults (17) who participated in the Nutritional and Health Survey in Taiwan. Our findings emphasize the
Table 5. Odds ratio (OR) and 95% confidence intervals (CI) for risk of metabolic syndrome according to uric acid concentration among Thai men and women Men Uric acid (mg/dL)* 1st Q (!5.1) 2nd Q (5.1–5.8) 3rd Q (5.9–6.7) 4th Q (O6.7) p for trend
Women
OR**
95% CI
1.00 1.83 5.72 3.91
Ref. 0.56–5.95 2.03–16.12 1.36–11.23 0.002
Uric acid (mg/dL)* 1st Q (!3.5) 2nd Q (3.5–4.0) 3rd Q (4.1–4.6) 4th Q (O4.6) p for trend
OR**
95% CI
1.00 0.98 2.37 4.86
Ref. 0.38–2.50 1.06–5.28 2.33–10.14 !0.001
Separate models were estimated for men and women. *Q refers to quartiles. **Odds ratios (OR) and 95% confidence intervals (95% CI) are adjusted for age (!40, 40–59, $60 years), smoking status (never smoker/ever smoker), and alcohol consumption status (never/ever drinker).
Prevalence of Hyperuricemia and its Relation to Metabolic Syndrome
need for additional studies to identify the determinants of hyperuricemia in Thais.
Acknowledgments This research was supported by Rachadapiseksompoj Faculty of Medicine Research Fund, Chulalongkorn University, Thailand, and National Institutes of Health. The research was completed while Dr. Vitool Lohsoonthorn was a Teaching Assistant-Consultant in Thailand for the 2005 Multidisciplinary International Research Training (MIRT) fellows. The MIRT Program of the University of Washington, School of Public Health and Community Medicine is supported by awards from the National Institutes of Health (T37-TW-00049 and T37-MD-100449). The authors wish to thank the staff of the Preventive Medicine Clinic, King Chulalongkorn Memorial Hospital in Bangkok, Thailand for their assistance in data collection and Mr. Bizu Gelaye for skillful technical assistance.
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11. Shiwaku K, Nogi A, Kitajima K, Anuurad E, Enkhmaa B, Yamasaki M, et al. Prevalence of the metabolic syndrome using the modified ATP III definitions for workers in Japan, Korea and Mongolia. J Occup Health 2005;47:126–135. 12. Hochberg MC, Smolen JS, Weinblatt ME, Weisman MH. Rheumatology, 3rd ed. New York: Mosby;2003. 13. Nagahama K, Iseki K, Inoue T, Touma T, Ikemiya Y, Takishita S. Hyperuricemia and cardiovascular risk factor clustering in a screened cohort in Okinawa, Japan. Hypertens Res 2004;27:227–233. 14. Rothman KJ, Greenland S. Modern Epidemiology, 2nd ed. Philadelphia: Lippincott-Raven;1998. 15. Al-Arfaj AS. Hyperuricemia in Saudi Arabia. Rheumatol Int 2001;20: 61–64. 16. Nagahama K, Inoue T, Iseki K, Touma T, Kinjo K, Ohya Y, Takishita S. Hyperuricemia as a predictor of hypertension in a screened cohort in Okinawa, Japan. Hypertens Res 2004;27:835–841. 17. Chang HY, Pan WH, Yeh WT, Tsai KS. Hyperuricemia and gout in Taiwan: results from the Nutritional and Health Survey in Taiwan (1993–96). J Rheumatol 2001;28:1640–1646. 18. Fang J, Alderman MH. Serum uric acid and cardiovascular mortality the NHANES I epidemiologic follow-up study, 1971–1992. National Health and Nutrition Examination Survey. JAMA 2000;283:2404– 2410. 19. Lindeberg S, Cordain L, Rastam L, Ahren B. Serum uric acid in traditional Pacific Islanders and in Swedes. J Intern Med 2004;255: 373–378. 20. Ishizaka N, Ishizaka Y, Toda E, Nagai R, Yamakado M. Association between serum uric acid, metabolic syndrome, and carotid atherosclerosis in Japanese individuals. Arterioscler Thromb Vasc Biol 2005;25: 1038–1044. 21. Costa A, Iguala I, Bedini J, Quinto L, Conget I. Uric acid concentration in subjects at risk of type 2 diabetes mellitus: relationship to components of the metabolic syndrome. Metabolism 2002;51:372–375. 22. 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;69:928–933. 23. Mazzali M, Kanellis J, Han L, Feng L, Xia YY, Chen Q, et al. Hyperuricemia induces a primary renal arteriolopathy in rats by a blood pressure-independent mechanism. Am J Physiol Renal Physiol 2002; 282:F991–F997. 24. Anker SD, Leyva F, Poole-Wilson PA, Kox WJ, Stevenson JC, Coats AJ. Relation between serum uric acid and lower limb blood flow in patients with chronic heart failure. Heart 1997;78:39–43. 25. WD Waring WS, Maxwell SRJ. Effect of local hyperuricemia on endothelial function in the human forearm vascular bed. Br J Clin Pharmacol 2000;49:511. 26. Vasquez-Vivar J, Santos AM, Junqueira VB, Augusto O. Peroxynitrite-mediated formation of free radicals in human plasma: EPR detection of ascorbyl, albumin-thiyl and uric acid-derived free radicals. Biochem J 1996;314:869–876. 27. Leyva F, Anker S, Swan JW, Godsland IF, Wingrove CS, Chua TP, et al. Serum uric acid as an index of impaired oxidative metabolism in chronic heart failure. Eur Heart J 1997;18:858–865. 28. National Statistics Office of Thailand. Report of the health and welfare survey. Bangkok: Office of the Prime Minister;1996.
ORIGINAL ARTICLE
Prevalence of Hyperuricemia and its Relationship with Metabolic Syndrome in Thai Adults Receiving Annual Health Exams Vitool Lohsoonthorn,a Bodi Dhanamun,a and Michelle A. Williamsb a
b
Department of Preventive and Social Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand Department of Epidemiology, Multidisciplinary International Research Training Program, University of Washington School of Public Health and Community Medicine, Seattle, Washington Received for publication October 25, 2005; accepted March 27, 2006 (ARCMED-D-05-00443).
Background. Associations between hyperuricemia, metabolic syndrome, cardiovascular disease and diabetes have been reported. Limited information, however, is available concerning the prevalence and correlates of hyperuricemia among Thai men and women. We sought to estimate the prevalence of hyperuricemia among a population of patients receiving annual health exams and to evaluate its relationship with metabolic syndrome (MetS). Methods. We conducted a cross-sectional study of 1,381 patients (376 men and 1,005 women) who first participated in annual health examinations at the Preventive Medicine Clinic of the King Chulalongkorn Memorial Hospital in Bangkok, Thailand during the period July 1999 through February 2000. Hyperuricemia was defined as O7.0 mg/dL in men and O6.0 mg/dL in women. MetS was defined using the modified ATP III criteria. Results. The overall prevalence of the hyperuricemia was 10.6%. The condition was more common in men than in women (18.4 vs. 7.8%). Among women, serum uric acid was statistically significantly correlated with body mass index (BMI), systolic and diastolic blood pressure, high-density lipoprotein-cholesterol, triglyceride and fasting plasma glucose (all p !0.05). Men with serum uric acid concentrations O6.7 mg/dL (upper quartile) had a 3.91-fold increased in risk of MetS (95% CI:1.36–11.23), as compared with those who had concentrations !5.1 mg/dL (lowest quartile). Among women, the risk of MetS increased at least 2-fold for concentration of serum uric acid concentrations O4.0 mg/dL ( p for trend !0.001). Conclusions. Hyperuricemia is prevalent among Thai men and women receiving routine health exams. Additionally, serum uric acid is positively associated with MetS. Ó 2006 IMSS. Published by Elsevier Inc. Key Words: Prevalence, Hyperuricemia, Metabolic syndrome.
Introduction Hyperuricemia is commonly detected in subjects with abnormal purine metabolism, including overproduction of uric acid and insufficient uric acid excretion from the kidney (1). Prolonged hyperuricemia, often associated with gout, is an important risk factor for damaged joint (2). Hyperurice-
Address reprint requests to: Dr. Vitool Lohsoonthorn, University of Washington, MIRT Program, Department of Epidemiology (Box 357236), 1959 NE Pacific Street (HSB, F-263), Seattle, WA 98195; E-mail: [email protected]
mia has been shown to be associated with several components of metabolic syndrome (MetS) and investigators have postulated that increased concentrations of uric acid may be another important component of the syndrome (3). In some epidemiologic studies, a close relationship between hyperuricemia and hypertension, insulin resistance and cardiovascular disease risk factors (such as obesity and smoking) has been reported (4–7). Hyperuricemia is diagnosed in 5–30% of the general population, although the prevalence is higher among some ethnic groups (e.g., Japanese) and appears to be increasing worldwide (8). Serum uric acid concentrations are known to increase with age
0188-4409/06 $–see front matter. Copyright Ó 2006 IMSS. Published by Elsevier Inc. doi: 10.1016/j.arcmed.2006.03.008
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and are further increased after menopause in women (9). Considering current increases in the incidence and prevalence of obesity and MetS worldwide, as well as emerging evidence documenting associations between hyperuricemia and cardiovascular complications, Conen and colleagues have called for increased emphasis to be placed on understanding the epidemiological characteristic of hyperuricemia in developing countries (4). Little information, however, exists concerning the prevalence and epidemiological characteristics of hyperuricemia in Thailand. We, therefore, conducted the present study to estimate the prevalence of hyperuricemia among Thai men and women receiving routine health examinations. We also sought to evaluate the extent to which, if at all, serum uric acid concentrations were associated with the risk of MetS.
Methods Study Population and Data Collection We conducted a cross-sectional study of 1,381 patients (376 men and 1,005 women) who first participated in annual health examinations at the Preventive Medicine Clinic of the King Chulalongkorn Memorial Hospital in Bangkok, Thailand during the period of July 1999 through February 2000. Participants were those with no previously diagnosed diabetes mellitus, hypertension, or gout and were not taking uric acid-, lipid- or blood pressure-lowering medication. During routine clinic visits participants were asked to provide information about their age, marital status, occupation, educational level, medical history, smoking status, alcohol consumption habits, participation in regular weekly physical exercise and other recreational physical activities. Participants underwent routine physical examinations that included determining their height, weight, resting blood pressure, and providing an overnight fasting venous blood sample. Standing height was measured without shoes to the nearest 0.5 cm. Weight was determined without shoes and with participants lightly clothed. Weight was measured using an automatic electronic scale (Seca, Inc., Hamburg, Germany) to the nearest 100 g. Blood pressure was determined using an automatic sphygmomanometer (UDEXIIa, UEDA Corporation, Tokyo, Japan). Participants were instructed to sit resting for 5 min before blood pressure measurements were determined. Laboratory Analyses Participants provided an overnight fasting venous blood sample. Serum samples were used to determine participants’ lipid profiles. Serum triglyceride (TG) concentration was determined by standardized enzymatic procedures using glycerol phosphate oxidase assay. High-density lipoprotein–cholesterol (HDL-C) was measured by a chemical
precipitation technique using dextran sulfate. Serum uric acid concentrations were measured using the Uricase EMST method. Plasma samples were used to determine participants’ fasting plasma glucose (FPG) using the hexakinase method. All laboratory assays were completed without knowledge of participants’ medical history. Lipid, lipoprotein, uric acid and plasma glucose concentrations were reported as mg/dL. All participants provided informed consent and the research protocol was reviewed and approved by the Ethical Committee of the Faculty of Medicine, Chulalongkorn University, and the Division of Human Subjects Research, University of Washington, Seattle, WA. Analytical Variable Specification MetS was defined using a modified version of the ATP III criteria (10). Briefly, four of the five MetS components were defined using the following ATP III categorizations: 1) high blood pressure $130/85 mmHg; 2) hypertriglyceridemia $150 mg/dL; 3) low high-density lipoprotein-cholesterol (HDL-C) !40 mg/dL for men and !50 mg/dL for women; 4) hyperglycemia or high fasting glucose $110 mg/dL. The fifth component was defined based on body mass index (BMI) rather than on waist circumference measurements to identify individuals with central adiposity because we did not have measurements of waist circumference (11). We classified participants with a BMI $25 kg/m2 as having high central obesity. Participants with three of any of the five components were classified as having MetS. We defined subjects as having hyperuricemia if their serum uric acid concentration was O7.0 mg/dL (in men) or O6.0 mg/dL (in women) (12,13). We also classified subjects according to categories of uric acid. Uric acid concentrations were categorized into approximate quartiles for men and women separately. The resulting four categories for men were 1) !5.1 mg/dL; 2) 5.1–5.8 mg/dL; 3) 5.9– 6.7 mg/dL; and 4) O6.7 mg/dL. The corresponding categories for women were as follows: 1) !3.5 mg/dL; 2) 3.5–4.0 mg/dL; 3) 4.1–4.6 mg/dL; and 4) O4.6 mg/dL. Statistical Analyses We first explored frequency distributions of sociodemographic, behavioral characteristics and medical histories. For categorical variables we used the chi-square test to evaluate differences in distribution of covariates for affected and unaffected patients. Pearson’s correlation coefficients were obtained for each of the MetS components and the respective uric acid concentration. Fasting plasma glucose and TG were skewed and were normalized by logarithmic transformation in all analyses. Mean uric acid concentrations were calculated across the categorized components of MetS. All mean values were adjusted for years of age, smoking status, drinking status and the other MetS components by means of a multiple linear regression
Prevalence of Hyperuricemia and its Relation to Metabolic Syndrome
model. Logistic regression procedures were used to examine the risks of having metabolic syndrome. Univariate and multiple variable logistic regression procedures were employed to calculate unadjusted odd ratios (OR) of potential risk factors associated with metabolic syndrome. Confidence intervals were also reported for each OR. Confounding factors were evaluated on the basis of their hypothesized relationship with covariates of interest and with metabolic syndrome. Confounding was assessed by entering potential cofounders into a logistic regression model one at a time and by comparing the adjusted and unadjusted ORs (14). Final logistic regression models included covariates that altered unadjusted ORs by at least 10%. All analyses were completed separately for male and female patients. Statistical analyses were performed using SPSS (version 13.0, SPSS Inc., Chicago, IL) software. All reported p values are two tailed, and confidence intervals were calculated at the 95% level.
Results Overall, the prevalence of hyperuricemia was 10.6% in this study population. Hyperuricemia was more common in men than in women (18.4 vs. 7.8%) (Table 1). Men with hyperuricemia, as compared to those without the condition, were older ( p 5 0.001), were more likely to have reported smoking ( p 5 0.019), and were former consumers of alcohol ( p 5 0.184). Women with hyperuricemia as compared with their counterparts without the condition were older ( p !0.001), less well educated ( p 5 0.004) and were less likely to report that they participated in regular exercise ( p 5 0.070). Participation in leisure-time activities, as well as occupation as a laborer, were not statistically significantly associated with hyperuricemia. As shown in Table 2, among men the prevalence of MetS increased across successive quartiles of serum uric acid concentrations. A similar linear gradient of increased prevalence of MetS across increasing quartile of uric acid was observed for women (4.0, 4.8, 11.4 and 22.6% for successive quartiles). Adjusted mean serum uric acid concentrations according to presence or absence of each of the five components of MetS are listed in Table 3. Women with MetS-defining abnormalities had higher serum uric acid concentrations than those without such abnormalities. This pattern of association was not evident among men. Women with BMI $25 kg/m2, high blood pressure, high FPG, high TG or low HDL-C had serum uric acid concentrations that were approximately 0.23–0.65 mg/dL higher than those without metabolic abnormalities ( p !0.05). Men with elevated TG had statistically significant higher serum uric acid concentration (0.65 mg/dL) ( p !0.001) than those without elevated TG. Table 4 summarizes Pearson’s correlation coefficients between each of the MetS-defining abnormalities and serum uric acid concentrations. Among men, uric acid
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concentrations were statistically significantly positively correlated ( p !0.01) with body mass index, diastolic blood pressure, and log-transformed serum triglyceride concentrations. Uric acid was negatively correlated with serum HDL-C and log-transformed fasting plasma glucose concentrations. Uric acid concentrations were most strongly correlated with serum triglyceride concentrations (r 5 0.35) and body mass index (r 5 0.27). Among women, statistically significant positive correlations were noted for the serum uric acid concentrations with body mass index, systolic and diastolic blood pressure, log-transformed triglyceride and log-transformed fasting plasma glucose concentrations. Uric acid concentrations were inversely correlated with serum HDL-C concentrations ( p !0.001). Among women, body mass index (r 5 0.37) and serum triglyceride concentrations (r 5 0.39) were most strongly correlated with uric acid concentrations. We next evaluated the relative risk of MetS in relation to varying concentrations of serum uric acid in men and women, respectively. For these analyses, we used multivariable logistic regression procedures to control for confounding factors. Results from these analyses are summarized in Table 5. There was some evidence of a linear component in risk of MetS in relation to uric acid concentrations ( p for trend 5 0.002). After adjusting for confounding by age, smoking status and recent alcohol consumption, we noted that men with uric acid concentrations in the highest quartile (O6.7 mg/dL) had a 3.91-fold increased in risk of MetS as compared with men with uric acid concentrations in the lowest quartile (!5.1 mg/dL) (OR 5 3.91, 95% CI: 1.36– 11.23). Among women, the risk of MetS increased in relation to serum uric acid concentrations O4.0 mg/dL, and a positive linear trend in risk across quartiles was noted ( p for trend !0.001). Women with uric acid concentrations in the third quartile (4.1–4.6 mg/dL), as compared with those with concentrations in the first quartile (!3.5 mg/dL), had a 2.37-fold increased risk of MetS (95% CI: 1.06–5.28). Women with concentrations O4.6 mg/dL (fourth quartile) had an almost 5-fold increased risk of MetS (OR 5 4.86, 95% CI: 2.33–10.14) as compared with women with value in the reference group (!3.5 mg/dL, first quartile).
Discussion The 10.6% prevalence of hyperuricemia noted among Thai men and women in our study is higher than estimates reported for several other populations. For instance, Al-Arfaj and colleagues reported that the prevalence of hyperuricemia was 8.4% among Saudi men and women (15). Notably, hyperuricemia was defined using the same criteria for both studies. The prevalence of hyperuricemia in our study population is lower, however, than estimates reported for Japanese men and women who participated in a community-based mass screening program in Okinawa, Japan. In their study
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Table 1. Characteristics of study population according to hyperuricemia status among Thai men and women receiving health exams
Characteristics
Men
Women
Hyperuricemia
Hyperuricemia
No (n 5 307)
No (n 5 927)
n
%
n
%
3 54 83 59 57 40 11
1.0 17.6 27.0 19.2 18.6 13.0 3.6
3 4 12 25 9 11 5
4.3 5.8 17.4 36.2 13.0 15.9 7.2
43.7 6 13.9
47.6 6 14.6
p value 0.001
n
%
n
%
9 131 229 277 190 77 14
1.0 14.1 24.7 29.9 20.5 8.3 1.5
1 2 12 20 21 19 3
1.3 2.6 15.4 25.6 26.9 24.4 3.8
43.1 6 12.1
0.036 0.981
84 125 93
27.8 41.4 30.8
20 28 21
29.0 40.6 30.4
42 264
13.7 86.3
9 60
13.0 87.0
110 196
35.9 64.1
19 50
27.5 72.5
163 143
53.3 46.7
26 43
37.7 62.3
158 147
51.8 48.2
31 38
44.9 55.1
202 102 64
66.4 33.6 20.9 112.1 6 52.8 126.8 6 76.0 1.1 6 0.4
50 19 20
72.5 27.5 29.0 107.1 6 33.0 175.6 6 114.6 1.2 6 0.4
Yes (n 5 78)
51.2 6 11.7
!0.001 0.004
441 250 218
48.5 27.5 24.0
51 17 8
67.1 22.4 10.5
121 805
13.1 86.9
11 67
14.1 85.9
708 216
76.6 23.4
64 14
82.1 17.9
868 54
94.1 5.9
72 6
92.3 7.7
319 602
34.6 65.4
35 43
44.9 55.1
576 350 130
62.2 37.8 14.0
46 32 28
59.0 41.0 35.9 110.8 6 31.9 192.0 6 144.5 0.9 6 0.3
0.881
0.795
0.184
0.274
0.019
0.512
0.302
0.070
0.335
0.146 0.448 0.001 0.004
p value !0.001
0.573
99.1 6 28.6 103.4 6 61.8 0.8 6 0.1
!0.001 0.001 !0.001 !0.001
Lohsoonthorn et al./ Archives of Medical Research 37 (2006) 883–889
Age (years) !20 20–29 30–39 40–49 50–59 60–69 $70 (Mean 6 SD) Education #Primary education !Bachelor degree $Bachelor degree Laborer occupation Yes No Drinking status Never drinker Ever drinker Smoking status Never smoker Ever smoker Exercise Yes No Recreational activities Yes No Hypertension (%) FPG (mean 6 SD) Triglyceride (mean 6 SD) Creatinine (mean 6 SD)
Yes (n 5 69)
Prevalence of Hyperuricemia and its Relation to Metabolic Syndrome Table 2. Prevalence of metabolic syndrome by quartiles of serum uric acid concentration among Thai men and women receiving health exams Men
Women
Uric acid (mg/dL)*
n
(%)
Uric acid (mg/dL)*
n
(%)
1st Q (!5.1) 2nd Q (5.1–5.8) 3rd Q (5.9–6.7) 4th Q (O6.7) Total
5 8 26 19 58
(5.8) (9.1) (24.1) (21.1) (15.4)
1st Q (!3.5) 2nd Q (3.5–4.0) 3rd Q (4.1–4.6) 4th Q (O4.6) Total
9 11 26 72 118
(4.0) (4.8) (11.4) (22.6) (11.7)
*Q refers to quartiles.
of 4,489 subjects, Nagahama and colleagues reported that 24.4% of participants were diagnosed with hyperuricemia. Hyperuricemia was defined as serum uric acid $7.0 mg/dL and $6.0 mg/dL in men and women, respectively (16). From the Nutritional and Health Survey in Taiwan (17), 26% of adult males ($19 years) either had hyperuricemia (serum uric acid O7.7 mg/dL) or were taking medication for it. The investigators also reported that approximately 17% of adult females had hyperuricemia (serum uric acid O6.6 mg/dL) or were taking medication for the condition. The prevalence of hyperuricemia is age dependent. In the present study, hyperuricemia was infrequent among younger subjects (!5% for both men and women in the 20- to 29-year-age group) but rose considerably to 36.2 and 25.6% for men and women, respectively, in the 40to 49-year-age group. Similar patterns of increased prevalence of hyperuricemia with increasing age have been reported by several other investigators (18,19). Consistent
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with observations recently reported by Ishizaka and colleagues, we noted a general increase in the prevalence of MetS with increased concentrations of serum uric acid (20). In our study population, serum uric acid concentrations were statistically significantly and positively correlated with body mass index, diastolic blood pressure and serum triglyceride concentrations; and statistically significant and inverse correlations were noted for serum uric acid and serum HDL-C concentrations. These associations were generally similar to those reported by other investigators (13,21,22). In addition to being correlated with individual cardiovascular disease risk factors such as obesity, hypertension, and dyslipidemia, investigators have noted that hyperuricemic subjects tend to have a clustering of these risk factors (16). Moreover, increased serum uric acid concentrations have been positively associated with cardiovascular mortality in non-Hispanic White and African-American populations in the U.S. (18). Although we were not able to evaluate the relation between serum uric acid and incident cardiovascular disease, we did note positive linear associations between risk of component of MetS and quartiles of serum uric acid concentrations in men and women in our study population. These finings are similar to those reported by Ishizaka et al. (20) who reported that the odds ratios for MetS increased across successive quartiles of serum uric acid concentrations (odds ratios for women with corresponding 95% confidence intervals were as follows: 1.00 (reference group), 1.06 (0.60–1.87), 2.18 (1.30–3.64), and 4.17 (2.56–6.79). The corresponding odds ratios and 95% confidence intervals for men were as follows: 1.00 (reference group), 0.92 (0.74–1.14), 1.52 (1.25–1.65), and 1.97 (1.61–2.40).
Table 3. Adjusted means of uric acid (mg/dL) among Thai men and women according to selected features of metabolic syndrome Men
Variables Obesity BMI $25 kg/m2 BMI !25 kg/m2 High blood pressure SBP $130 mmHg or DBP $85 mmHg SBP !130 mmHg and DBP !85 mmHg High fasting plasma glucose FPG $110 mg/dL FPG !110 mg/dL High triglyceride TG $150 mg/dL TG !150 mg/dL Low HDL-cholesterol HDL-C !40 mg/dL(men)/!50 mg/dL (women) HDL-C $40 mg/dL(men)/$50 mg/dL (women)
n
Means of uric acid (95% CI)
14 356
6.34 (5.62–7.06) 6.01 (5.87–6.15)
151 219
Women
n
Means of uric acid (95% CI)
0.377
86 909
4.90 (4.67–5.14) 4.25 (4.18–4.32)
!0.001
6.02 (5.79–6.25) 6.03 (5.84–6.21)
0.970
303 692
4.47 (4.34–4.60) 4.24 (4.16–4.32)
0.005
81 289
5.94 (5.63–6.25) 6.05 (5.89–6.21)
0.554
113 882
4.53 (4.32–4.74) 4.28 (4.21–4.35)
0.029
123 247
6.46 (6.21–6.72) 5.81 (5.63–5.98)
!0.001
197 798
4.65 (4.49–4.82) 4.23 (4.15–4.30)
!0.001
90 280
6.29 (6.00–6.57) 5.94 (5.78–6.10)
0.042
317 678
4.47 (4.35–4.59) 4.23 (4.15–4.32)
0.002
p value
p value
Separate models were estimated for men and women. Means of uric acid were adjusted for age, smoking status, drinking status, BMI, high blood pressure, high fasting plasma glucose, high triglyceride and low HDL-cholesterol.
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Table 4. Pearson’s correlation coefficients (r) for each component of metabolic syndrome in relation to uric acid concentrations (mg/dL) Men
Covariate Age (years) Body mass index (kg/m2) Systolic blood pressure (mmHg) Diastolic blood pressure (mmHg) HDL (mg/dL) Log-transformed triglyceride (mg/dL) Log-transformed FPG (mg/dL)
Women
Pearson Pearson correlation (r) p value correlation (r) p value 0.12 0.27
0.021 !0.001
0.28 0.37
!0.001 !0.001
0.06
0.285
0.24
!0.001
0.14
0.006
0.22
!0.001
20.15 0.35
0.005 !0.001
20.19 0.39
!0.001 !0.001
20.06
0.244
0.09
0.003
Biological mechanisms for the statistical associations observed in our study are presently unknown. However, results from several animal experimental studies suggest that hyperuricemia may affect blood pressure acutely through a rennin-dependent pathophysiological pathway (23). Additionally, hyperuricemia has been postulated to promote hypertension by contributing to systemic endothelial dysfunction and oxidative stress (24–26). Emerging evidence documents associations of insulin resistance and hyperglycemia with increased uric acid concentrations (13). Leyva et al. have postulated that insulin resistance may attenuate tubular secretion of urate and thus lead to hyperuricemia (27). There are several compelling mechanistic hypotheses that may explain consistently observed associations between uric acid and cardiovascular disease risk factors and additional longitudinal studies that clearly identify the temporal relation between changes in renal function according to changes in risk factors are needed to more thoroughly and empirically evaluate these mechanistic hypotheses.
Our study has several limitations. First, this study was cross-sectional in design, and thus did not permit the identification of a causal relationship between hyperuricemia and MetS. Second, our study has a higher proportion of women (72.8%) than men (27.2%). This may be due to the fact that women were more health conscious and assertive in seeking annual health examinations than men. Furthermore, the proportions of abnormal metabolic parameters in this study population were slightly higher than those from the National Health Survey in Thailand (28). Hence, results from our study may not be able to be generalized to Thai men and women who do not avail themselves of preventive medical services. Third, misclassification of MetS status may have occurred in our study because we did not have direct measurements of waist circumference and thus had to use BMI as a proxy measure of central adiposity. In sensitivity analyses, we noted that excluding BMI from the criteria for MetS did not alter the association between uric acid and the risk of MetS (data not shown). Fourth, we were not able to thoroughly evaluate hyperuricemia in relation to a broader range of behavioral and environmental characteristics of our study population. In particular, we did not have precise details concerning type and frequency of participants’ dietary habits, frequency and duration of physical activity, and pattern of adult weight gain. Conducting larger prospective cohort studies that employ validated data collection instruments and which integrates serial measurements of biological markers will likely overcome these noted limitations. In conclusion, we noted that serum uric acid concentrations were associated with clustered components of MetS in Thai men and women receiving routine health care in Bangkok, Thailand. The prevalence of hyperuricemia in this population was as high as in those of some developed and developing countries (15), but considerably lower than estimates reported for Japanese adults in Okinawa (16) and Taiwanese adults (17) who participated in the Nutritional and Health Survey in Taiwan. Our findings emphasize the
Table 5. Odds ratio (OR) and 95% confidence intervals (CI) for risk of metabolic syndrome according to uric acid concentration among Thai men and women Men Uric acid (mg/dL)* 1st Q (!5.1) 2nd Q (5.1–5.8) 3rd Q (5.9–6.7) 4th Q (O6.7) p for trend
Women
OR**
95% CI
1.00 1.83 5.72 3.91
Ref. 0.56–5.95 2.03–16.12 1.36–11.23 0.002
Uric acid (mg/dL)* 1st Q (!3.5) 2nd Q (3.5–4.0) 3rd Q (4.1–4.6) 4th Q (O4.6) p for trend
OR**
95% CI
1.00 0.98 2.37 4.86
Ref. 0.38–2.50 1.06–5.28 2.33–10.14 !0.001
Separate models were estimated for men and women. *Q refers to quartiles. **Odds ratios (OR) and 95% confidence intervals (95% CI) are adjusted for age (!40, 40–59, $60 years), smoking status (never smoker/ever smoker), and alcohol consumption status (never/ever drinker).
Prevalence of Hyperuricemia and its Relation to Metabolic Syndrome
need for additional studies to identify the determinants of hyperuricemia in Thais.
Acknowledgments This research was supported by Rachadapiseksompoj Faculty of Medicine Research Fund, Chulalongkorn University, Thailand, and National Institutes of Health. The research was completed while Dr. Vitool Lohsoonthorn was a Teaching Assistant-Consultant in Thailand for the 2005 Multidisciplinary International Research Training (MIRT) fellows. The MIRT Program of the University of Washington, School of Public Health and Community Medicine is supported by awards from the National Institutes of Health (T37-TW-00049 and T37-MD-100449). The authors wish to thank the staff of the Preventive Medicine Clinic, King Chulalongkorn Memorial Hospital in Bangkok, Thailand for their assistance in data collection and Mr. Bizu Gelaye for skillful technical assistance.
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