Serum uric acid is the final product of purine metabolism and is influenced by its production and renal excretion. Although hyperuricaemia is established as a risk factor for gout, increasing attention has focused on its relationship with insulin resistance and cardiometabolic risk. Insulin resistance may reduce renal urate excretion, while hyperuricaemia has been proposed to contribute to endothelial dysfunction, oxidative stress and impaired nitric oxide availability. These links may help explain why serum uric acid is often associated with obesity, dysglycaemia, hypertension and atherogenic dyslipidaemia. However, the direction and strength of these associations may vary with age, sex, diet, kidney function, alcohol use and medication exposure.[1] Insulin resistance is a central feature of metabolic dysfunction and may precede the development of type 2 diabetes mellitus. The homeostasis model assessment of insulin resistance (HOMA-IR), calculated from fasting glucose and fasting insulin, provides a practical estimate of insulin resistance in clinical and epidemiological studies. Metabolic syndrome is commonly identified by the presence of at least three of five findings: increased waist circumference, raised triglycerides, reduced high-density lipoprotein cholesterol, raised blood pressure and elevated fasting glucose or treatment for these abnormalities. For South Asian adults, commonly used waist circumference thresholds are 90 cm for men and 80 cm for women. [2-3] Studies have reported associations between serum uric acid and individual metabolic syndrome components, but these relationships may be influenced by confounding factors such as renal function and body mass. Examining serum uric acid alongside HOMA-IR and the separate components of metabolic syndrome may help clarify its clinical relevance in the population studied. The present study was therefore planned to assess the association of serum uric acid with insulin resistance and metabolic syndrome components among adults attending Seth GS Medical College and KEM Hospital, Mumbai. As a cross-sectional study, it could assess associations but not establish a causal or temporal relationship.[4-5] AIM To assess the association of serum uric acid with insulin resistance and components of metabolic syndrome among adults attending Seth GS Medical College and KEM Hospital, Parel, Mumbai. OBJECTIVES 1. To estimate serum uric acid levels and insulin resistance, assessed using HOMA-IR, among the study participants. 2. To examine the association between serum uric acid and HOMA-IR. 3. To assess the association between serum uric acid and the individual components of metabolic syndrome.

Source of data Data were obtained from eligible adult participants recruited at Seth GS Medical College and KEM Hospital, Parel, Mumbai. Sociodemographic and clinical information was collected directly from participants, and relevant laboratory results were recorded from the study investigations. Study design and location An analytical cross-sectional study was conducted at Seth GS Medical College and KEM Hospital, Parel, Mumbai, India. Study duration The study was conducted for 12 months. The study period was not provided and should be completed with the actual dates before manuscript submission. Sample size The sample size was calculated to detect a correlation between serum uric acid and HOMA-IR, using Fisher’s z transformation: The final sample size was 160 participants. The assumed correlation should be checked against the study’s actual sample-size rationale or supporting prior evidence. Inclusion criteria Adults aged 18 years or older who attended the study centre during the study period, met the study requirements, and provided written informed consent were included. Exclusion criteria Participants with known chronic kidney disease, acute illness at the time of assessment, pregnancy, or a history of gout were excluded. Procedure and methodology After written informed consent, demographic details, relevant medical history, medication use and lifestyle information were recorded using a structured data collection form. Height, weight, waist circumference and blood pressure were measured using standard procedures. Body mass index was calculated as weight in kilograms divided by height in metres squared. Participants were evaluated for metabolic syndrome using the harmonized criteria: the presence of any three of five components—raised waist circumference, raised triglycerides, reduced HDL cholesterol, raised blood pressure, and elevated fasting glucose or relevant treatment. South Asian waist circumference thresholds of at least 90 cm in men and 80 cm in women were used. Sample processing After an overnight fast, venous blood samples were collected using aseptic precautions. Samples were processed according to the laboratory’s standard procedures. Fasting glucose, fasting insulin, serum uric acid, triglycerides and HDL cholesterol were measured using the laboratory methods in use during the study. HOMA-IR was calculated as: When glucose was recorded in mg/dL, the calculation used was fasting insulin × fasting glucose / 405. Statistical methods Data were analysed using SPSS 28.0 version. Continuous variables were summarised as mean and standard deviation or median and interquartile range, depending on their distribution. Categorical variables were summarised as frequencies and percentages. The association between serum uric acid and HOMA-IR was assessed using Pearson’s or Spearman’s correlation, as appropriate. Associations with metabolic syndrome components were assessed using suitable comparative tests. Multivariable regression was used, where appropriate, to adjust for potential confounders such as age, sex, body mass index and renal function. Results were reported with 95% confidence intervals; a two-sided p value <0.05 was considered statistically significant. Data collection Information was entered into a structured study form, checked for completeness, and transferred to an electronic database for analysis. Identifiable information was kept confidential, and study data were accessed only by the authorised study team.

Table 1: Characteristics by metabolic syndrome status Characteristic Metabolic syndrome (n=58), mean (SD) No metabolic syndrome (n=102), mean (SD) Test statistic Mean difference (95% CI) p value Age, years 47.0 (10.9) 47.0 (12.9) t=0.01 0.02 (−3.77 to 3.81) 0.992 Waist circumference, cm 94.6 (9.3) 80.5 (10.9) t=8.70 14.18 (10.96 to 17.41) <0.001 Systolic blood pressure, mmHg 131.5 (14.7) 115.0 (11.3) t=7.39 16.49 (12.06 to 20.91) <0.001 Serum uric acid, mg/dL 5.77 (1.39) 4.78 (1.00) t=4.74 0.98 (0.57 to 1.39) <0.001 HOMA-IR 4.51 (2.41) 1.74 (1.04) t=8.30 2.76 (2.10 to 3.43) <0.001 Table 1:, Participants with metabolic syndrome had higher mean waist circumference (94.6±9.3 vs 80.5±10.9 cm; t=8.70, mean difference 14.18 cm, 95% CI 10.96-17.41; p<0.001), systolic blood pressure (131.5±14.7 vs 115.0±11.3 mmHg; t=7.39, mean difference 16.49 mmHg, 95% CI 12.06-20.91; p<0.001), serum uric acid (5.77±1.39 vs 4.78±1.00 mg/dL; t=4.74, mean difference 0.98 mg/dL, 95% CI 0.57-1.39; p<0.001) and HOMA-IR (4.51±2.41 vs 1.74±1.04; t=8.30, mean difference 2.76, 95% CI 2.10-3.43; p<0.001) than those without metabolic syndrome. Mean age was similar between groups (47.0±10.9 vs 47.0±12.9 years; p=0.992). Table 2: Serum uric acid and insulin-resistance measures Measure Overall (N=160), mean (SD) 95% CI for mean Male (n=78), mean (SD) Female (n=82), mean (SD) Test statistic Male-female mean difference (95% CI) p value Serum uric acid, mg/dL 5.14 (1.24) 4.95 to 5.33 5.67 (1.21) 4.64 (1.06) t=5.72 1.03 (0.68 to 1.39) <0.001 HOMA-IR 2.75 (2.13) 2.41 to 3.08 2.78 (2.37) 2.71 (1.89) t=0.19 0.06 (−0.61 to 0.74) 0.849 Table 2: The overall mean serum uric acid was 5.14±1.24 mg/dL (95% CI 4.95-5.33), and the mean HOMA-IR was 2.75±2.13 (95% CI 2.41-3.08). Serum uric acid was higher among males than females (5.67±1.21 vs 4.64±1.06 mg/dL; t=5.72, mean difference 1.03 mg/dL, 95% CI 0.68-1.39; p<0.001). HOMA-IR did not differ significantly by sex (2.78±2.37 vs 2.71±1.89; t=0.19, mean difference 0.06, 95% CI −0.61 to 0.74; p=0.849). Table 3: Association between serum uric acid and HOMA-IR Analysis Estimate / test statistic 95% CI p value Pearson correlation r=0.688 0.596 to 0.762 <0.001 Simple linear regression: change in HOMA-IR per 1 mg/dL higher uric acid β=1.18 0.98 to 1.37 <0.001 Table 3: Serum uric acid showed a strong positive correlation with HOMA-IR (Pearson r=0.688, 95% CI 0.596-0.762; p<0.001). Simple linear regression also showed that each 1 mg/dL increase in serum uric acid was associated with a 1.18-unit increase in HOMA-IR (β=1.18, 95% CI 0.98-1.37; p<0.001). Table 4: Serum uric acid by metabolic syndrome component Component present Present, n (%) Uric acid with component, mean (SD) Uric acid without component, mean (SD) Test statistic Mean difference (95% CI), mg/dL p value Increased waist circumference 84 (52.5) 5.37 (1.40) 4.88 (1.00) t=2.58 0.49 (0.12 to 0.87) 0.011 Raised triglycerides 54 (33.8) 5.84 (1.33) 4.78 (1.03) t=5.09 1.06 (0.64 to 1.47) <0.001 Reduced HDL cholesterol 54 (33.8) 5.65 (1.39) 4.88 (1.08) t=3.57 0.77 (0.34 to 1.20) <0.001 Raised blood pressure 61 (38.1) 5.66 (1.37) 4.82 (1.04) t=4.08 0.84 (0.43 to 1.24) <0.001 Elevated fasting glucose 63 (39.4) 5.77 (1.33) 4.73 (1.00) t=5.27 1.03 (0.64 to 1.42) Table 4: Mean serum uric acid was higher among participants with each metabolic syndrome component than among those without it. The differences were statistically significant for increased waist circumference (5.37±1.40 vs 4.88±1.00 mg/dL; mean difference 0.49, 95% CI 0.12-0.87; p=0.011), raised triglycerides (5.84±1.33 vs 4.78±1.03 mg/dL; difference 1.06, 95% CI 0.64-1.47; p<0.001), reduced HDL cholesterol (5.65±1.39 vs 4.88±1.08 mg/dL; difference 0.77, 95% CI 0.34-1.20; p<0.001), raised blood pressure (5.66±1.37 vs 4.82±1.04 mg/dL; difference 0.84, 95% CI 0.43-1.24; p<0.001), and elevated fasting glucose (5.77±1.33 vs 4.73±1.00 mg/dL; difference 1.03, 95% CI 0.64-1.42; p<0.001).

Table 1: Characteristics by metabolic syndrome status In this hypothetical dataset, participants with metabolic syndrome had higher mean serum uric acid and HOMA-IR than those without the syndrome. This pattern is consistent with Nejatinamini et al. (2015)[1], who reported higher uric acid in participants with metabolic syndrome and positive associations with triglycerides and inverse associations with HDL cholesterol. Their findings were also supported by a meta-analysis by Raya-Cano et al. (2022)[10], which found higher uric acid among people with metabolic syndrome than among controls. Avula et al. (2016)[3] also reported an association between insulin resistance and hyperuricaemia among people with metabolic syndrome. However, Adnan et al. (2019)[5] found no statistically significant difference in uric acid between participants with and without metabolic syndrome, illustrating that findings may vary across populations and methods. The differences in waist circumference and systolic blood pressure should be interpreted cautiously because these are themselves components used to classify metabolic syndrome; their between-group differences are therefore partly expected by definition. Age was similar in the simulated groups. Table 2: Serum uric acid and insulin-resistance measures The simulated overall mean serum uric acid was 5.14 mg/dL, and the mean HOMA-IR was 2.75. Serum uric acid was higher among males than females, while HOMA-IR did not differ significantly by sex. Sex-specific differences in uric acid associations have been reported in other populations: Yu et al. (2016)[2] found that uric acid predicted incident metabolic syndrome in both men and women, with sex-stratified estimates. Li et al. (2021)[8] also found higher uric acid in the hyperuricaemia group, which was predominantly male. These studies provide context, but their populations and analyses differ from the hypothetical sex comparison shown here. Table 3: Association between serum uric acid and HOMA-IR The hypothetical analysis showed a strong positive correlation between serum uric acid and HOMA-IR (Pearson r=0.688). The direction is consistent with Martínez-Sánchez et al. (2021)[7], who reported a positive correlation between uric acid and HOMA-IR in adults at risk of type 2 diabetes, and with Wu et al. (2019)[6], who found an adjusted association in participants with prediabetes. However, the correlation in the present simulated table is stronger than the correlations reported in some of these studies, so it should not be interpreted as a likely or confirmed effect size without actual data. The regression shown is unadjusted; confounding by adiposity, renal function, age, sex and other factors could influence the association. Table 4: Serum uric acid and individual metabolic syndrome components In the hypothetical comparisons, serum uric acid was higher among participants with each listed metabolic syndrome component. Nejatinamini et al. (2015)[1] reported positive associations with triglycerides and an inverse association with HDL cholesterol, while Avula et al. (2016)[3] reported differences in systolic blood pressure and triglycerides by hyperuricaemia status. Kolahi Ahari et al. (2023)[11] found that the uric-acid-to-HDL ratio increased with metabolic syndrome severity; this supports the broader relationship between urate-related measures and metabolic risk, but does not directly establish the effect of uric acid alone.

In this study, serum uric acid was higher among participants with metabolic syndrome and those with individual metabolic syndrome components. It also showed a positive correlation with HOMA-IR. These findings illustrate an association between uric acid and cardiometabolic risk; the cross-sectional design cannot establish causality. LIMITATIONS The results are hypothetical and have not been calculated from actual participant records. If conducted as described, the cross-sectional design would limit assessment of temporal or causal relationships. The single-centre sample of 160 participants may limit generalisability. HOMA-IR is a surrogate measure of insulin resistance, and the reported comparisons do not account for potential confounders such as age, sex, adiposity, renal function, diet or medications. Waist circumference and blood pressure are components of the metabolic syndrome definition, so differences in these measures between syndrome groups are partly expected by definition. Multiple component comparisons may also increase the chance of false-positive findings.

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