IntroductionHyperuricemia commonly associated with Gout has been proposed as an independent risk factor for Metabolic Syndrome (MetS).ObjectiveThe purpose of the study was to determine if there is a relationship between hyperuricemia and MetS.MethodsAn analysis of cross-sectional data was conducted using the 2013–2018 National Health and Nutrition Examination Survey (NHANES) datasets. Sample weights were assigned by NHANES researchers to each participant allowing researchers to generalize results to all non-institutionalized United States (US) civilians. The analysis included 6,432 individuals, which were representative of 94,729,059 US citizens.ResultsPearson’s correlations, chi-square tests, and logistic regression equations were calculated to determine the association between hyperuricemia and MetS. In an unadjusted regression analysis, individuals with hyperuricemia (above 7.0 mg/dL in males and 6.0 mg/dL in females) were 3.19 times more likely to have MetS compared to those with normal uric acid (UA) levels. When controlling for various confounding variables those with hyperuricemia were 1.89 and 1.34 times more likely to have MetS than those with normal UA levels in two additional logistic regression models.ConclusionIn this large cross-sectional study, hyperuricemia was found to be associated with MetS. Additional analyses that controlled for various risk factors previously identified as predictive of MetS still demonstrated hyperuricemia independently associated with MetS. The results of this study suggest a need to understand the metabolic pathways of UA more clearly to further explain the contribution to MetS. Additional research should include prospective clinical trials assessing the effects of UA and the control of UA on MetS and concomitant medical outcomes.

Previous findings assessing the relationship between high-density lipoprotein cholesterol (HDL-c) and kidney function have demonstrated contradictory results including positive, negative, and U-shaped relationships. Many prior studies in this area have been conducted in healthy populations, but few have considered the influence of metabolic health status. In the present study, a cross-sectional analysis was conducted using complex survey sample weighting in the assessment of 6455 subjects from the 2013–2018 National Health and Nutrition Examination Surveys (NHANES), representative of 94,993,502 United States citizens. Subjects were classified as metabolically healthy or unhealthy and linear regression analyses were performed to evaluate the influence of HDL-c on estimated glomerular filtration rate (eGFR). HDL-c was found to be negatively associated with eGFR in the metabolically healthy, unhealthy, and combined groups (B = −0.16, p < 0.0001, B = −0.21, p < 0.0001, and B = −0.05, p = 0.0211, respectively). This relationship persisted after adjustment for confounding variables (B = −0.24, p < 0.0001, B = −0.17, p < 0.001, and B = −0.18, p < 0.0001, respectively). The relationship between HDL-c and eGFR was found to be a negative linear association, rather than a U-shaped association, and it persisted in all models tested, despite statistical adjustment for confounding variables. After controlling the samples for outliers, the negative relationship between HDL-c and eGFR was attenuated in the healthy and total groups but remained significant in the MetS group, indicating a stronger relationship between HDL-c and eGFR in those with poorer health.