Exploring the relationship between the uric acid to high-density lipoprotein cholesterol ratio and depression: a cross-sectional study from NHANES

Depression is one of the most burdensome diseases worldwide, garnering significant attention. The uric acid to high-density lipoprotein cholesterol ratio (UHR) is a novel and easily obtainable indicator used to assess the body's inflammatory and metabolic status. It has attracted interest due to its potential role in the prevention and treatment of depression. This study aims to explore the potential correlation between UHR and depression. A cross-sectional study was conducted using data from the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018. Depression occurrence was defined as the dependent variable, and UHR was defined as the independent variable. Multivariable logistic regression was performed to assess the relationship between the independent and dependent variables. Smooth curve fitting and threshold effect analyses were used to evaluate the nonlinear relationship and effect size between UHR and depression. Subgroup and sensitivity analyses were conducted to determine the stability of the results. This study included 24,272 adults based on NHANES data. Multivariable logistic regression analysis showed that, in the fully adjusted model, individuals with the highest UHR had a 42% increased likelihood of depression compared to those with the lowest UHR (OR = 1.42; 95% CI, 1.23-1.64; P < 0.001). Subgroup analyses indicated no significant interaction between UHR and specific subgroups (all interaction P > 0.05). Moreover, there is a nonlinear association between UHR and depression. When the UHR level was>10.21, the correlation between UHR and depression increased by 3% (OR = 1.03; 95% CI, 1.01-1.04; P < 0.01). The study found that UHR is significantly associated with a higher risk of depression among American adults. However, further prospective studies are needed to accurately elucidate the causal relationship between elevated UHR levels and depression risk. Therefore, larger cohort studies are required to support these findings.