Association of Neutrophil-Percentage-To-Albumin Ratio(NPAR) with depression symptoms in U.S. adults: a NHANES study from 2011 to 2018

Abstract

BackgroundInflammation is crucial in the development of depression. This study aims to examine the potential association between the Neutrophil-Percentage-to-Albumin Ratio(NPAR) and depression symptoms.MethodsThis study adopted a cross-sectional design, involving patients with depression symptoms and those without depression symptoms with comprehensive NPAR data originated from the National Health and Nutrition Examination Survey(NHANES) spanning 2011 to 2018. The research utilized weighted multivariate logistic regression models and multivariate linear regression to investigate the linear relationship between NPAR levels and depression symptoms and its severity scores. The characterization of nonlinear relationships was accomplished by employing fitted smoothing curves. Furthermore, subgroup analyses and interaction assessments were conducted to offer additional insights.ResultsThis study involved a total of 10,829 participants, and the prevalence of depression among them was found to be 15.08%. The multiple logistic regression analysis revealed a statistically significant positive association between the continuum of NPAR and depression symptoms[OR:1.03, 95% CI: (1.00, 1.05)], as well as depression severity scores[β: 0.08, 95% CI: (0.04,0.11)]. Stratifying NPAR into quartiles, we found that higher NPAR associated with increased odds of depression symptoms. Furthermore, in subgroup analysis, there were no significant differences in the relationship between NPAR levels and depression symptoms or its severity scores within populations with or without diabetes and cardiovascular diseases. Additionally, the use of a two-stage linear regression model uncovered a non-linear relationship between NPAR and depression symptoms.ConclusionsOur research indicates that NPAR levels were associated with depression symptoms. To corroborate our findings, larger prospective studies are warranted to elucidate nonlinear associations in greater detail.