Serum Uric Acid Level as a Harbinger of Type 2 Diabetes: A Prospective Observation in Taiwan

Association of Serum Uric Acid with Indices of Insulin Resistance: Proposal of a New Model with Reference to Gender Differences

Background

Insulin resistance (IR) is a key feature of type 2 diabetes (T2D) and an independent risk factor for metabolic syndrome. Previous studies have linked elevated serum uric acid (SUA) to an increased risk of T2D.

Aim

The purpose of this study was to investigate the relationship between SUA and IR. At the same time, the correlation between New model and SUA compared with other IR alternatives was compared, so as to provide a simple and effective new indicator for early detection and prediction of IR risk and early prevention of T2D.

Methods

The first cohort was the Discovery Cohort, which included 318 obese patients. And the second cohort was the Verification Cohort, which included a total of 4333 subjects who underwent a routine health checkup at our hospital. Spearman correlation analysis and binary logistic regression analysis were used to discuss the correlation between SUA and IR.

Results

Regardless of sex, fasting insulin (FINS) and IR replacement markers increased with SUA (P<0.001). In both cohorts, SUA was associated with IR alternatives, especially with New model, and differed between men and women in all correlation analyses. After adjusting for confounding factors, SUA was still associated with IR (P<0.001).

Conclusion

The correlation between SUA and IR was significantly stronger in women than in men. And the correlation between SUA and New model is stronger than other IR replacement models. However, the causal relationship between SUA and IR has not been clearly established.

What is the relationship between serum uric acid level and insulin resistance?: A case-control study

Diabetes, arises from either an absolute or relative insufficiency of insulin or insulin resistance of peripheral tissues. For assessing long-term blood glucose concentration and insulin resistance, the utilization of glycosylated hemoglobin (HbA1c) and the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) is widespread. Insulin resistance can lead to hyperuricemia by reducing the kidney ability to excrete urate, thus increasing sodium reabsorption. The aim of this study was to investigate the possible relationship between serum uric acid levels and insulin resistance. This was a retrospective case-control study. A total of 2530 applications in 2-year time were included in the study. Patient, known hypertension status, fasting plasma glucose, insulin, uric acid, HDL, low-density lipoprotein (LDL), triglyceride/Tg, HbA1c laboratory values and Tg/HDL ratio were examined. A statistically significant difference existed in the median uric acid values between the insulin-resistant and insulin-sensitive groups (P < .001). Additionally, a weak positive statistical correlation was identified between uric acid and HOMA-IR values (R = 0.299; P < .001) and uric acid and Tg/HDL values (R = 0.357; P < .001). This study concludes that there is a positive correlation between serum uric acid levels and insulin resistance.

Relationship between baseline and changed serum uric acid and the incidence of type 2 diabetes mellitus: a national cohort study

Objective

To explore the correlation between baseline serum uric acid (SUA) and SUA changes with the incidence of type 2 diabetes mellitus (T2DM) among middle-aged and older individuals.

Method

Binary logistic regression was used to calculate the odds ratio (ORs) and 95% confidence intervals (CIs) of the effects of baseline and changes in SUA on the incidence of T2DM. Stratified analysis was conducted based on sex, and the SUA levels were classified into four quartiles to assess the effect of baseline and relative changes in SUA on the incidence of T2DM. Furthermore, interaction analysis was performed between body mass index (BMI) and SUA, age and SUA, and sex and SUA.

Results

In the cohort study, the highest quartiles of SUA were significantly correlated with an increased incidence of T2DM among females in model 1 [OR = 2.231 (1.631, 3.050)], model 2 [OR = 2.090 (1.523, 2.867)], model 3 [OR = 2.075 (1.511, 2.849)], and model 4 [OR = 1.707 (1.234, 2.362)]. The highest quartiles of SUA had a statistically significant effect on the incidence of T2DM among all participants in model 1 [OR = 1.601 (1.277, 2.008)], model 2 [OR = 1.519 (1.204, 1.915)], model 3 [OR = 1.597 (1.257, 2.027)], and model 4 [OR = 1.380 (1.083, 1.760)]. Regarding the relative change of SUA, the highest quantiles of SUA were significantly correlated with an increased incidence of T2DM among females in model 1 [OR = 1.409 (1.050, 1.890)], model 2 [OR = 1.433 (1.067, 1.926)], and model 3 [OR = 1.420 (1.056, 1.910)], and there was a statistically significant correlation with incident T2DM among all participants in model 4 [OR = 1.346 (1.079, 1.680)] after adjusting for all covariates. However, there was no significant correlation between baseline, relative, and absolute changes in SUA and the incidence of T2DM among males. The interaction analysis demonstrated that sex, BMI, and the relative changes in SUA had a combined effect on the incidence of T2DM, while age and the changes in SUA had a joint effect on the incidence of T2DM only in females.

Conclusion

There was a positive association between SUA and the incidence of T2DM for all participants. However, significant sex differences in incidence were observed only in women, not men.

A nationwide wastewater-based assessment of metformin consumption across Australia

Metformin is the most widely used drug to treat type 2 diabetes. Monitoring spatial patterns of metformin use could provide new insights into treatment of type 2 diabetes and the distribution among populations. This study applied a wastewater-based epidemiological (WBE) approach to estimate metformin use in different populations across Australia and compared these estimates with traditional approaches of surveys and prescription data. Twenty-four-hour influent samples were collected from 75 wastewater treatment plants (WWTPs) across Australia in 2016 and analysed for metformin. Metformin was detected in all samples ranging in concentration from 8.2 to 191 µg/L (median 58 µg/L). Concentrations were converted to population-weighted average consumption at the national level, resulting in an average consumption of 28.6 g/day/1000 people across Australia, which was within 7% of estimates from national prescription statistics. In addition, results for five out of seven states had an estimated prevalence of type 2 diabetes within 20% compared to the traditional epidemiology surveys. Spatial patterns were also observed between urban and rural settings, with higher consumption rates of metformin found in Major Cities (22.5 ± 10.9 g/d/1000 people) and Inner Regional cities (25.4 ± 13.4 g/d/1000 people) than in Outer Regional (17.0 ± 8.1 g/d/1000 people) and Remote areas (15.1 ± 7.4 g/d/1000 people). Consumption estimates were also correlated against socioeconomic factors of the specific catchment areas. Greater metformin use was correlated with populations of lower education and income levels, while positive correlations were found between metformin consumption and consumption of allopurinol, caffeine and venlafaxine. Our study provides more evidence on the distribution of metformin use across Australia, which can be used to develop public health strategies to reduce the overall burden of type 2 diabetes in specific regions.

Tea Consumption is Associated with an Increased Risk of Hyperuricemia in an Occupational Population in Guangdong, China

Purpose

Chronic hyperuricemia leads to long-term deposition of monosodium urate crystals that may damage the joint structure and affect quality of life. Although hyperuricemia prevalence varies, most studies indicate increased cases of hyperuricemia worldwide. The relationship between hyperuricemia and tea consumption is uncertain. This cross-sectional study investigated the effect of tea consumption on the risk of hyperuricemia in the working population in Guangdong, China.

Patients and Methods

Data on weight, height, blood pressure, laboratory test results, and health questionnaire responses of 7644 adults aged ≥18 years were obtained from the health examinee dataset of Nanfang Hospital. The characteristics of subjects with and without hyperuricemia were compared using t-tests or non-parametric Mann–Whitney U-tests for continuous variables and chi-square tests for categorical variables. Relationships between hyperuricemia and participant characteristics (sex, age, education level, smoking history, alcohol consumption, hypertension, body mass index, tea consumption, and other dietary factors) were examined using univariate and multivariate logistic regression models to identify independent risk factors for hyperuricemia.

Results

Tea consumption was associated with a higher risk of hyperuricemia in the crude model (odds ratio [OR] 1.74, 95% confidence interval [CI] 1.48–2.05, once a month through twice a week vs never, P<0.001; OR 2.44, 95% CI 2.07–2.89, ≥3 times a week vs never, P<0.001). The adjusted OR for hyperuricemia was 1.30 (95% CI 1.08–1.56, P=0.006) in participants who consumed tea once a month through twice a week and 1.35 (95% CI 1.11–1.64, P=0.003) in those who consumed tea ≥3 times a week compared with the “never” reference group after adjusting for sociodemographic factors, anthropometric and biochemical indices, and dietary factors. This relationship remained significant in men but not women in subgroup analysis.

Conclusion

Tea consumption is an independent risk factor for hyperuricemia and is more pronounced in men than women.

Time course of serum uric acid accumulation and the risk of diabetes mellitus

Background

The impact of long-term serum uric acid (SUA) exposure and time course of SUA accumulation on diabetes mellitus (DM) is unknown. This study aimed to evaluate the association of cumulative SUA (cumSUA) exposure and its accumulation time course with risk of DM.

Methods

This prospective study included 46,434 participants without DM and underwent three examinations at 2006, 2008, and 2010. CumSUA from 2006 to 2010 was calculated, multiplying mean values between consecutive examinations by time intervals between visits. Time course of SUA accumulation was categorized as the slope of SUA versus time from 2006 to 2010, or by splitting the overall accumulation into an early (cumSUA_06-08) and late accumulation (cumSUA_08-10).

Results

During 6.99 years of follow-up, we identified 2971 incident DM cases. In the fully adjusted model, a higher risk of DM was observed in participants with the highest quartile of cumSUA (hazard ratio [HR], 1.31; 95% confidence interval [CI], 1.17–1.46), cumulative burden >0 (HR, 1.23; 95% CI, 1.08–1.40), and with 6 year of hyperuricemia exposure duration (HR, 1.25; 95% CI, 1.01–1.55). When considering the time course of SUA accumulation, participants with a negative slope (HR, 1.05; 95% CI, 1.01–1.12), or combined with cumSUA ≥ median and a negative slope had elevated risk of DM (HR, 1.58; 95% CI, 1.18–2.11).

Conclusions

Incident DM risk depends on cumulative exposure of SUA and time course of SUA accumulation. Early SUA accumulation resulted in a greater risk increase compared with later accumulation, emphasizing the importance of optimal SUA control early in life.

Obesity-Induced Insulin Resistance Is Mediated by High Uric Acid in Obese Children and Adolescents

Objective

This study aimed to evaluate whether serum uric acid (SUA) plays a mediating role in the development of insulin resistance (IR) in obese children and adolescents.

Methods

A total of 369 participants aged 4-17 years with obesity who attended the Nutrition Outpatient Clinic for Obesity at Xinhua Hospital from January 2012 to January 2019 were recruited for this retrospective study. We classified participants into two groups on the basis of HOMA-IR values: the low HOMA-IR group (< 3.16) (n = 222) and the high HOMA-IR group (≥ 3.16) (n = 147).

Results

The univariate analysis found that the high HOMA-IR group had higher BMI, SUA, and fasting insulin (FINS) (P < 0.05). Multiple linear regression analysis and mediating effect analysis indicated that body mass index (BMI) could directly regulate FINS and HOMA-IR (both P < 0.05). The results from the mediating effect analysis found that UA partially played an indirect role in the link between BMI, FINS and HOMA-IR (both P < 0.05) but had no effect on fasting blood glucose (P > 0.05).

Conclusions

SUA should be investigated in obesity and plays a partial mediating role in insulin resistance induced by obesity in obese children and adolescents.

Tea consumption and serum uric acid levels among older adults in three large-scale population-based studies in China

Background and aims

The association between serum uric acid (SUA) and tea consumption has been studied in previous work, and there were arguments among various population group employed as well as different statistical approaches. The aim of this work is to investigate the tea effect on SUA levels among older adults by comparing three large-scale populations with both cross-sectional and longitudinal analyses.

Method

We examined the relationship between intake and SUA levels among older adults using linear regression. All the studies include the parameters SUA levels, tea intake, age, sex, education level, smoking status, alcohol drinking status, body mass index (BMI), and health history (diabetes, hypertension, and fasting plasma glucose). The cross-sectional analyses were conducted with 4579 older adults in the Weitang Geriatric Diseases Study (WGDS, ≥60 years), 2440 in the China Health and Nutrition Survey (CHNS, ≥60 years) and 1236 in the Chinese Longitudinal Healthy Longevity Survey (CLHLS, ≥62 years); and the longitudinal analyses were performed with 3870 (84.5%) in the WGDS and 420 (34.0%) in the CLHLS. Multivariable linear regression analyses were performed in both cross-sectional and longitudinal studies.

Results

Cross-sectional studies showed that tea consumers tended to have higher SUA levels than non-tea consumers in all the three datasets (P < 0.05). However, longitudinal associations of SUA levels with tea consumption had no statistical significance (P>0.05). The results of sex-stratified analyses were consistent with those of the whole datasets.

Conclusions

This work implied that any possible association between tea consumption and SUA levels could be very weak.

Relationship of Serum Uric Acid to Hematoma Volume and Prognosis in Patients with Acute Supratentorial Intracerebral Hemorrhage

BACKGROUND

Oxidative stress and inflammation play important roles in the neuronal injury caused by intracerebral hemorrhage (ICH). Uric acid (UA), an important natural antioxidant, might reduce the neuronal injury caused by ICH. Delineating the relationship between UA and ICH will enhance our understanding of antioxidative mechanisms in recovery from ICH.

METHODS

We conducted a retrospective study of 325 patients with acute supratentorial ICH to investigate the relationship between serum UA levels and hematoma volumes and prognosis. A hematoma volume of ≥30 mL was defined as a large hematoma. An unfavorable outcome was defined as a modified Rankin scale score of 4-6 on day 30.

RESULTS

The serum UA level was significantly lower in the patients with a large hematoma volume (median, 306 μmol/L; 25th to 75th percentile, 243-411 μmol/L) than in those with a small hematoma volume (median, 357 μmol/L; 25th to 75th percentile, 271-442 μmol/L; P = 0.012). Similarly, the unfavorable outcome group had had lower serum UA levels (median, 309 vs. 363 μmol/L; P = 0.009) compared with the favorable outcome group. The results of the multivariate logistic analysis indicated that a lower serum UA level was associated with a larger hematoma volume (odds ratio, 0.996; P = 0.006) and an unfavorable outcome (odds ratio, 0.997; P = 0.030).

CONCLUSIONS

The results from the present study have indicated that in patients with acute supratentorial ICH, a low serum UA level might indicate that the patient has a large hematoma volume and might be a risk factor for a poor day 30 functional prognosis.