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- Publisher
- Oxford University Press
- Copyright
- © Association of Military Surgeons of the United States 2018. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
- ISSN
- 0026-4075
- eISSN
- 1930-613X
- DOI
- 10.1093/milmed/usy097
- Publisher site
- See Article on Publisher Site
Abstract
Abstract Introduction Hyperuricemia (HUA) is associated with metabolic syndrome (MetS) in the general population. Military individuals who perform high-intensity physical training might have lower rates of MetS. The present study aimed to investigate whether HUA might be associated with the prevalence of MetS in military individuals. Material and Methods We retrospectively collected data from the annual military exam and randomly selected a single unit to represent the overall study population. The study population consisted of 460 military individuals between January 2016 and December 2016. We divided this cohort into the HUA group and the normouricemic group. Hyperuricemia is defined as a serum uric acid level of 7 mg/dL or more in men or 6 mg/dL or more in women. Results The cohort consisted of 460 individuals with a mean age of 35.9 yr old; 80% were male and 15% were diagnosed with MetS between January 1, 2016 and December 31, 2016. The prevalence of MetS was greater in the HUA group than in the normouricemic group (32.5% vs. 8.8%, p < 0.001). HUA was independently associated with the prevalent MetS after adjusting for age, gender, creatinine, alanine transaminase, and hemoglobin (adjusted OR: 4.305, 95% CI: 2.370–7.818, p < 0.001). Given that the cohort was predominantly male, we divided the cohort into men and women for a subgroup analysis. A significant association was found in men but not in women (adjusted OR: 3.59 95% CI: 1.905–6.765, p < 0.001 for men and adjusted OR: 16.7 95% CI: 0.295–946, p = 0.172 for women, respectively). Conclusion Hyperuricemia was independently associated with the prevalence of metabolic syndrome in a military cohort from Taiwan. Future studies should look at whether hyperuricemia in individuals without metabolic syndrome can predict the future onset of metabolic syndrome. INTRODUCTION Serum uric acid (SUA), a metabolite of purine in humans, has inflammatory properties and produces insulin resistance, endothelial dysfunction, and reactive oxidative stress,1 and is associated with an increased risk of metabolic syndrome (MetS).2 Hyperuricemia (HUA) is known to be associated with MetS across all ages, including in children and adolescents, young and middle-aged adults, and the elderly.2–7 Furthermore, HUA is reportedly associated with increased risks of hospitalization due to gout, chronic kidney disease, cardiovascular disease and it also increases all-cause mortality.8 Additionally, patients with an elevated SUA level of 8 mg/dL had medical costs that were double those of patients with an SUA level of 6 mg/dL; the additional payment for HUA was approximately $1,938 per patient annually.8 However, some research showed no association between HUA and MetS in specific populations.9 In military individuals, MetS was present in 5% of Greek navy recruits,10 9% of French military personnel,11 9.9% of Korean military aviators,12 20.8% of Saudi adult soldiers,13 24.7% of American military Service Members,14 and 33.3% of Indian military aircrew members,15 though the exact prevalence might be affected by the definition of MetS and ethnicities in these studies. The impact of MetS on personal health in military individuals resembled the impact of MetS in the general population. However, little research has directly discussed the association between SUA and MetS in military personnel.12 Whether elevated SUA is associated with MetS in military individuals is unknown. Therefore, we retrospectively conducted a cross-sectional study to investigate whether HUA is associated with the prevalence of MetS in military individuals. METHODS Our hospital, a military hospital located in the northern Taiwan, performs an annual health exam in apparently healthy soldiers with an estimated screening number of approximately 20,000 individuals. The routine exam includes measurements of body height, body weight, blood pressure, visual and acoustic acuity, physical examinations, basic blood tests, urine analyses, chest radiography, and electrocardiography. The blood tests were performed after individuals fasted for at least 8 h. Individuals with any abnormal results underwent a clinical examination at an outpatient department for safety issues, ensuring the accuracy of the data. All data were registered prospectively. The study protocol was approved by Tri-service General Hospital with the institutional review board number of TSGH 2-106-05–148. We retrospectively collected data from the annual military exam and randomly selected a single unit to represent the overall study population. The study population consisted of 460 individuals in a single unit between January 2016 and December 2016. We divided this cohort into the HUA group and the normouricemic group. Hyperuricemia is defined as a SUA level of 7 mg/dL or more in men or 6 mg/dL or more in females, as is widely used in clinical practice. Based on the Taiwan criteria, MetS must fulfill at least three of the five following criteria: (1) waist circumference more than 90 cm in men or more than 80 cm in women; (2) blood pressure of more than 130/85 mmHg; (3) fasting glucose of 100 mg/dL or more; (4) triglyceride level of 150 mg/dL or more; (5) high-density lipoprotein cholesterol of 40 mg/dL or less in men or 50 mg/dL or less in women.16 Statistical analyses The study end point was the presence of MetS. Categorical variables were expressed as number and percentage; continuous variables were expressed as the mean and standard deviation (SD). The relationship among SUA and the components of MetS was calculated by the Pearson’s correlation coefficient. Then we used univariate logistic regression analyses to estimate the association among variables and MetS. If any variables were significantly associated with MetS, they would be considered either predictors of MetS or confounders. Multivariate logistic regression analyses were used to evaluate the association between HUA and MetS with a proper adjustment for confounders. We did not include waist circumference, systolic and diastolic blood pressure, fasting glucose, total cholesterol, high- and low-density lipoprotein cholesterol, and triglyceride level in the statistical model, as they directly relate to the diagnosis of MetS. A p-value of 0.05 or less was considered statistically significant. We performed statistical analyses with R, version 3.4.1 (The R Project for Statistical Computing). RESULTS These 460 individuals had an average age of 35.9 yr (SD 5.9), a body mass index of 24.8 kg/m2 (SD 3.5) and 80.2% of them were male; the overall prevalence of HUA and MetS was 26.1% and 15%, respectively. The HUA group had more males compared with the control group (96.3% vs. 74.4%, p < 0.001). The values for waist circumference, body mass index, systolic and diastolic blood pressure were significantly different. All biomarker values were significantly greater in the HUA group than in the control group, except alanine transaminase (shown in Table I). The HUA group had a higher rate of MetS than the control group (32.5% vs. 8.8%, p < 0.001). SUA was positively correlated with waist circumference (r = 0.455, p < 0.001), systolic blood pressure (r = 0.342, p < 0.001), diastolic blood pressure (r = 0.363, p < 0.001), triglyceride (r = 0.313, p < 0.001), and inversely correlated with high-density lipoprotein cholesterol (r = −0.357, p < 0.001). No significant relationship was found between SUA and fasting glucose (r = 0.057, p = 0.221). Table I. Baseline Characteristics, Laboratory Data, and the Prevalence of MetS in the Military Individuals Overall n = 460 NUA n = 340 HUA n = 120 p-Value Mean SD Mean SD Mean SD Age 35.9 (5.9) 35.6 (5.8) 36.5 (6.1) 0.187 Malea 369 (80.2) 253 (74.4) 116 (96.0) <0.001 Body mass index (kg/m2) 24.8 (3.5) 24.0 (3.2) 27.0 (3.4) 0.000 Waist circumference (cm) 80.5 (9.8) 78.8 (9.7) 85.4 (8.2) 0.000 SBP (mmHg) 123.6 (13.5) 121.5 (13.8) 129.7 (10.8) 0.000 DBP (mmHg) 75.4 (11.1) 73.5 (10.9) 80.8 (9.9) 0.000 Fasting glucose (mg/dL) 75.4 (16.9) 92.4 (16.6) 96.1 (17.5) 0.047 SUA (mg/dL) 6.2 (1.4) 5.5 (1.0) 7.9 (0.9) 0.000 Total cholesterol (mg/dL) 183 (33) 180 (33) 191 (32) 0.001 HDL-C (mg/dL) 50 (12) 51 (12) 46 (10) 0.000 LDL-C (mg/dL) 113 (30) 110 (30) 120 (28) 0.001 Triglyceride (mg/dL) 115 (88) 102 (71) 150 (117) 0.000 Creatinine (mg/dL) 0.92 (0.17) 0.89 (0.18) 1.01 (0.13) 0.000 ALT (IU/L) 29 (56) 27 (63) 35 (27) 0.053 Hemoglobin (g/dL) 14.9 (1.4) 14.7 (1.4) 15.4 (1.3) 0.000 Metabolic syndromea 69 (15.0) 30 (8.8) 39 (32.5) <0.001 Overall n = 460 NUA n = 340 HUA n = 120 p-Value Mean SD Mean SD Mean SD Age 35.9 (5.9) 35.6 (5.8) 36.5 (6.1) 0.187 Malea 369 (80.2) 253 (74.4) 116 (96.0) <0.001 Body mass index (kg/m2) 24.8 (3.5) 24.0 (3.2) 27.0 (3.4) 0.000 Waist circumference (cm) 80.5 (9.8) 78.8 (9.7) 85.4 (8.2) 0.000 SBP (mmHg) 123.6 (13.5) 121.5 (13.8) 129.7 (10.8) 0.000 DBP (mmHg) 75.4 (11.1) 73.5 (10.9) 80.8 (9.9) 0.000 Fasting glucose (mg/dL) 75.4 (16.9) 92.4 (16.6) 96.1 (17.5) 0.047 SUA (mg/dL) 6.2 (1.4) 5.5 (1.0) 7.9 (0.9) 0.000 Total cholesterol (mg/dL) 183 (33) 180 (33) 191 (32) 0.001 HDL-C (mg/dL) 50 (12) 51 (12) 46 (10) 0.000 LDL-C (mg/dL) 113 (30) 110 (30) 120 (28) 0.001 Triglyceride (mg/dL) 115 (88) 102 (71) 150 (117) 0.000 Creatinine (mg/dL) 0.92 (0.17) 0.89 (0.18) 1.01 (0.13) 0.000 ALT (IU/L) 29 (56) 27 (63) 35 (27) 0.053 Hemoglobin (g/dL) 14.9 (1.4) 14.7 (1.4) 15.4 (1.3) 0.000 Metabolic syndromea 69 (15.0) 30 (8.8) 39 (32.5) <0.001 NUA, normouricemia; HUA, hyperuricemia; SBP, systolic blood pressure; DBP, diastolic blood pressure; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; ALT, alanine transaminase. aMale and metabolic syndrome were expressed as number (percentage). Table I. Baseline Characteristics, Laboratory Data, and the Prevalence of MetS in the Military Individuals Overall n = 460 NUA n = 340 HUA n = 120 p-Value Mean SD Mean SD Mean SD Age 35.9 (5.9) 35.6 (5.8) 36.5 (6.1) 0.187 Malea 369 (80.2) 253 (74.4) 116 (96.0) <0.001 Body mass index (kg/m2) 24.8 (3.5) 24.0 (3.2) 27.0 (3.4) 0.000 Waist circumference (cm) 80.5 (9.8) 78.8 (9.7) 85.4 (8.2) 0.000 SBP (mmHg) 123.6 (13.5) 121.5 (13.8) 129.7 (10.8) 0.000 DBP (mmHg) 75.4 (11.1) 73.5 (10.9) 80.8 (9.9) 0.000 Fasting glucose (mg/dL) 75.4 (16.9) 92.4 (16.6) 96.1 (17.5) 0.047 SUA (mg/dL) 6.2 (1.4) 5.5 (1.0) 7.9 (0.9) 0.000 Total cholesterol (mg/dL) 183 (33) 180 (33) 191 (32) 0.001 HDL-C (mg/dL) 50 (12) 51 (12) 46 (10) 0.000 LDL-C (mg/dL) 113 (30) 110 (30) 120 (28) 0.001 Triglyceride (mg/dL) 115 (88) 102 (71) 150 (117) 0.000 Creatinine (mg/dL) 0.92 (0.17) 0.89 (0.18) 1.01 (0.13) 0.000 ALT (IU/L) 29 (56) 27 (63) 35 (27) 0.053 Hemoglobin (g/dL) 14.9 (1.4) 14.7 (1.4) 15.4 (1.3) 0.000 Metabolic syndromea 69 (15.0) 30 (8.8) 39 (32.5) <0.001 Overall n = 460 NUA n = 340 HUA n = 120 p-Value Mean SD Mean SD Mean SD Age 35.9 (5.9) 35.6 (5.8) 36.5 (6.1) 0.187 Malea 369 (80.2) 253 (74.4) 116 (96.0) <0.001 Body mass index (kg/m2) 24.8 (3.5) 24.0 (3.2) 27.0 (3.4) 0.000 Waist circumference (cm) 80.5 (9.8) 78.8 (9.7) 85.4 (8.2) 0.000 SBP (mmHg) 123.6 (13.5) 121.5 (13.8) 129.7 (10.8) 0.000 DBP (mmHg) 75.4 (11.1) 73.5 (10.9) 80.8 (9.9) 0.000 Fasting glucose (mg/dL) 75.4 (16.9) 92.4 (16.6) 96.1 (17.5) 0.047 SUA (mg/dL) 6.2 (1.4) 5.5 (1.0) 7.9 (0.9) 0.000 Total cholesterol (mg/dL) 183 (33) 180 (33) 191 (32) 0.001 HDL-C (mg/dL) 50 (12) 51 (12) 46 (10) 0.000 LDL-C (mg/dL) 113 (30) 110 (30) 120 (28) 0.001 Triglyceride (mg/dL) 115 (88) 102 (71) 150 (117) 0.000 Creatinine (mg/dL) 0.92 (0.17) 0.89 (0.18) 1.01 (0.13) 0.000 ALT (IU/L) 29 (56) 27 (63) 35 (27) 0.053 Hemoglobin (g/dL) 14.9 (1.4) 14.7 (1.4) 15.4 (1.3) 0.000 Metabolic syndromea 69 (15.0) 30 (8.8) 39 (32.5) <0.001 NUA, normouricemia; HUA, hyperuricemia; SBP, systolic blood pressure; DBP, diastolic blood pressure; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; ALT, alanine transaminase. aMale and metabolic syndrome were expressed as number (percentage). In a univariate analysis, HUA was significantly associated with MetS (crude OR: 4.975, 95% confidence interval [CI]: 2.914–8.496, p < 0.001). Age, male gender, total cholesterol, creatinine, and hemoglobin were associated with MetS except for low-density lipoprotein cholesterol and alanine transaminase (shown in Table II). In a multivariate analysis, the association between HUA and MetS was significant (adjusted OR: 4.305, 95% CI: 2.370–7.818, p < 0.001). Table III demonstrates the association among HUA, covariates, and MetS. We further stratified the overall study population by gender; the significant association existed in the men but not in the women (adjusted OR: 3.59 95% CI: 1.905–6.765, p < 0.001 for men and adjusted OR: 16.7 95% CI: 0.295–946, p = 0.172 for women, respectively). Table II. The Association Among Covariates and MetS in a Univariate Logistic Regression Analysis Variable Odds ratio 95% confidence interval p-Value Age (years old) 1.087 1.037 −1.139 <0.001 Male 4.650 1.648 −13.120 0.004 Hyperuricemia (≥7 mg/dL vs. <7 mg/dL) 4.975 2.914 −8.496 <0.001 Total cholesterol (mg/dL) 1.013 1.006 −1.021 0.001 LDL-C (mg/dL) 1.008 1.000 −1.017 0.051 Creatinine (mg/dL) 8.064 1.710 −38.010 0.008 ALT (IU/L) 1.009 0.999 −1.019 0.080 Hemoglobin (g/dL) 1.863 1.450 −2.393 <0.001 Variable Odds ratio 95% confidence interval p-Value Age (years old) 1.087 1.037 −1.139 <0.001 Male 4.650 1.648 −13.120 0.004 Hyperuricemia (≥7 mg/dL vs. <7 mg/dL) 4.975 2.914 −8.496 <0.001 Total cholesterol (mg/dL) 1.013 1.006 −1.021 0.001 LDL-C (mg/dL) 1.008 1.000 −1.017 0.051 Creatinine (mg/dL) 8.064 1.710 −38.010 0.008 ALT (IU/L) 1.009 0.999 −1.019 0.080 Hemoglobin (g/dL) 1.863 1.450 −2.393 <0.001 SBP, systolic blood pressure; DBP, diastolic blood pressure; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; ALT, alanine transaminase. Table II. The Association Among Covariates and MetS in a Univariate Logistic Regression Analysis Variable Odds ratio 95% confidence interval p-Value Age (years old) 1.087 1.037 −1.139 <0.001 Male 4.650 1.648 −13.120 0.004 Hyperuricemia (≥7 mg/dL vs. <7 mg/dL) 4.975 2.914 −8.496 <0.001 Total cholesterol (mg/dL) 1.013 1.006 −1.021 0.001 LDL-C (mg/dL) 1.008 1.000 −1.017 0.051 Creatinine (mg/dL) 8.064 1.710 −38.010 0.008 ALT (IU/L) 1.009 0.999 −1.019 0.080 Hemoglobin (g/dL) 1.863 1.450 −2.393 <0.001 Variable Odds ratio 95% confidence interval p-Value Age (years old) 1.087 1.037 −1.139 <0.001 Male 4.650 1.648 −13.120 0.004 Hyperuricemia (≥7 mg/dL vs. <7 mg/dL) 4.975 2.914 −8.496 <0.001 Total cholesterol (mg/dL) 1.013 1.006 −1.021 0.001 LDL-C (mg/dL) 1.008 1.000 −1.017 0.051 Creatinine (mg/dL) 8.064 1.710 −38.010 0.008 ALT (IU/L) 1.009 0.999 −1.019 0.080 Hemoglobin (g/dL) 1.863 1.450 −2.393 <0.001 SBP, systolic blood pressure; DBP, diastolic blood pressure; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; ALT, alanine transaminase. Table III. The Association Among Covariates and MetS in a Multivariate Logistic Regression Analysis Variable Adjusted Odds Ratio 95% Confidence Interval p-Value Age (years old) 1.080 1.026 −1.136 0.003 Male 1.410 0.302 −6.592 0.662 Hyperuricemia (≥7 mg/dL vs. <7 mg/dL) 4.305 2.370 −7.818 <0.001 Creatinine (mg/dL) 0.284 0.024 −3.342 0.317 ALT (IU/L) 1.004 1.000 −1.008 0.059 Hemoglobin (g/dL) 1.667 1.228 −2.264 0.001 Variable Adjusted Odds Ratio 95% Confidence Interval p-Value Age (years old) 1.080 1.026 −1.136 0.003 Male 1.410 0.302 −6.592 0.662 Hyperuricemia (≥7 mg/dL vs. <7 mg/dL) 4.305 2.370 −7.818 <0.001 Creatinine (mg/dL) 0.284 0.024 −3.342 0.317 ALT (IU/L) 1.004 1.000 −1.008 0.059 Hemoglobin (g/dL) 1.667 1.228 −2.264 0.001 ALT, alanine transaminase; SBP, systolic blood pressure; DBP, diastolic blood pressure; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol. Table III. The Association Among Covariates and MetS in a Multivariate Logistic Regression Analysis Variable Adjusted Odds Ratio 95% Confidence Interval p-Value Age (years old) 1.080 1.026 −1.136 0.003 Male 1.410 0.302 −6.592 0.662 Hyperuricemia (≥7 mg/dL vs. <7 mg/dL) 4.305 2.370 −7.818 <0.001 Creatinine (mg/dL) 0.284 0.024 −3.342 0.317 ALT (IU/L) 1.004 1.000 −1.008 0.059 Hemoglobin (g/dL) 1.667 1.228 −2.264 0.001 Variable Adjusted Odds Ratio 95% Confidence Interval p-Value Age (years old) 1.080 1.026 −1.136 0.003 Male 1.410 0.302 −6.592 0.662 Hyperuricemia (≥7 mg/dL vs. <7 mg/dL) 4.305 2.370 −7.818 <0.001 Creatinine (mg/dL) 0.284 0.024 −3.342 0.317 ALT (IU/L) 1.004 1.000 −1.008 0.059 Hemoglobin (g/dL) 1.667 1.228 −2.264 0.001 ALT, alanine transaminase; SBP, systolic blood pressure; DBP, diastolic blood pressure; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol. DISCUSSION The present study showed that the presence of HUA was independently associated with MetS in military individuals. We also provided complementary evidence of the association between HUA and MetS to the only study that enrolled military individuals.12 Military individuals are generally thought to undergo strenuous exercise and high-intensity physical training, and to have a lower prevalence of MetS and HUA. In individuals of the same ethnicity, the prevalence of MetS was actually comparable between military individuals and the general population in the present study,17 consistent with another study.15 However, the conflicting result of a Korean study showed that the prevalence of MetS was slightly lower in military aviators than in the general population.12 These results of epidemiologic studies indicate that capacities of exercise and physical training are greater in military individuals, but risk factors of cardiovascular and metabolic diseases were not less than in the general population. SUA appears to have a causal role in MetS,18 possibly through inhibiting endothelial function.19 Elevated SUA was reported to be independently associated with increased risks of sudden cardiac death and cardiovascular events.20 Therefore, HUA might be a useful predictor to stratify the higher risks of sudden cardiac death in military individuals who undergo strict training. We used the strict definition of HUA in the study, whereas other studies used elevated SUA, generally greater quartile or quintile, to investigate the association between elevated SUA and specific diseases. The utility of SUA for risk stratification has advantages, including the ease of access in clinical practice. Elevated SUA plays a major role in inflammation in many systemic diseases, is associated with atrial fibrillation, has an increased mortality of acute myocardial infarction and has a greater incidence of sudden cardiac death, which might seriously interfere with the stability of manpower in the military.21–24 Although it was reported that elevated SUA was independently associated with interleukin-6 (IL-6), IL-1 receptor antagonist, IL-18, and tumor necrotizing factor-α,25 it only produced low-grade inflammation.26 The inflammatory properties of HUA have also been reported in patients with mild ST-segment elevation myocardial infarction.23 Elevated SUA was previously thought to be correlated with prothrombotic and pro-inflammatory states in patients with concomitant MetS and coronary artery disease.27 Similarly, the interaction was discovered between elevated SUA and MetS in association with a diagnosis of diastolic heart failure.28 The detrimental effect of HUA on cardiovascular events might be accentuated in individuals with MetS, therefore inducing more cardiovascular events than in people without MetS. Both elevated SUA and MetS generated reactive oxygen species through xanthine oxidase (XO) and induced endothelial dysfunction.1,19 In patients with heart failure, uricosuric agents were not associated with an improvement in endothelial dysfunction or hemodynamic impairment.29,30 Although allopurinol and probenecid exhibited similar levels of SUA reduction, only allopurinol was significantly associated with an improvement of endothelial function due to an increase in forearm blood flow.29 These results might indicate that SUA lowering therapy without anti-inflammation properties led to little improvement in endothelial function. Considering the stronger inflammatory responses in individuals with concomitant HUA and MetS compared with individuals with HUA alone, anti-inflammatory agents, such as XO inhibitors or colchicine, may be a potential therapeutic strategy other than SUA lowering therapies alone.31 The sodium-glucose linked transporter-2 inhibitor has multiple effects on lowering blood glucose, blood pressure, body weight and SUA and is associated with a decreased risk of cardiovascular events in diabetic patients; this might be considered a therapeutic option for selected individuals with concomitant HUA and MetS.32 STUDY LIMITATIONS Selection bias might be one of the major limitations in the present study. Although we randomly selected a single unit with 460 candidates from approximately 20,000 individuals, the prevalence of MetS may vary in different Army services, which might be a critical confounding factor for the association between HUA and MetS. Hereafter, we will enroll more candidates to avoid the problem of selection bias (ClinicalTrials.gov number, NCT03473951). Second, we have no data on dietary intake, physical activity, and military training in the present study; these factors might interfere with the development of MetS. HUA was independently associated with MetS in the present study, but the ratio of females was only 20%. We also failed to show a significant association in the female subgroup due to the small number of cases; it is also possible there would be no association regardless of the number of cases. Whether HUA independently predicts MetS in women is unknown. Hyperuricemia may ultimately offer a predictive value of cardiovascular events in military individuals, but it was beyond the results of our study. We only used the prevalence of MetS and did not longitudinally follow the cardiovascular outcomes of the study individuals. CONCLUSION Hyperuricemia was independently associated with the prevalence of MetS in a military cohort from Taiwan. Future studies should look at whether hyperuricemia in individuals without MetS can predict the future onset of metabolic syndrome. Funding The study was supported by research grant with the number NMMS-1050009923 of from Ministry of National Defense, Republic of China (Taiwan). The authors designed the study, collected data, performed analyses, wrote the report and made the decision to submit the article for publication. The funding source had no involvements. References 1 Liu Z , Que S , Zhou L , Zheng S : Dose-response relationship of serum uric acid with metabolic syndrome and non-alcoholic fatty liver disease incidence: a meta-analysis of prospective studies . Sci Rep 2015 ; 5 : 14325 . doi: 10.1038/srep14325 . 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Google Scholar Crossref Search ADS PubMed Author notes The views expressed are solely those of the authors and do not reflect the official policy or position of the Taiwan Army, Taiwan Navy, Taiwan Air Force, the Department of Defense, or the Taiwan Government. © Association of Military Surgeons of the United States 2018. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)
Journal
Military Medicine – Oxford University Press
Published: Nov 5, 2018