Clinical model forecasting the influence of alpha-1-Acid Glycoprotein on depression in U.S. adult women

Background: Depression among adult women remains a significant public health concern, yet comprehensive predictive models incorporating sociodemographic and clinical factors are limited, and it is not yet clear how the inflammatory marker α-1-acid glycoprotein affects depression. This investigation sought to identify key predictors of depression and construct a clinical prediction framework through logistic regression and nomogram analysis. Methods: The study utilized data from a nationally representative NHANES cohort (August 2021–August 2023) including 1,085 adult women, with depressive severity measured by the Patient Health Questionnaire-9(PHQ-9). The dataset was randomly split (6:4 ratio) into training/validation subsets, with baseline variables compared. Depressive status was defined as a binary outcome via PHQ-9. Covariate data reflecting sociodemographic characteristics, together with the biomarkers C-reactive protein (CRP), alpha-1-acid glycoprotein (AGP), and 25-hydroxyvitamin D3 (VD3), were retrieved from the database and underwent systematic analytical evaluation. Multivariable logistic regression identified independent depression risk factors. Leveraging their ability to visualize complex models through individualized probabilities, depression risk nomograms were constructed using logistic regression results. Multiple validation methods assessed nomogram predictive performance. Results: Multivariable logistic regression analysis uncovered significant independent associations between depression and several key factors: never-married status (OR = 2.38, 95% CI 1.47 - 3.86, p < 0.001), some college education (OR = 2.02, 95% CI 1.16 - 3.53, p = 0.013), and elevated AGP levels (OR = 2.34, 95% CI 1.01 - 5.42, p = 0.047). Furthermore, the ratio of family income to poverty exhibited a marginally non-significant inverse relationship (OR = 0.86, 95% CI 0.72 – 1.02, p = 0.077). The predictive model demonstrated moderate discriminative capacity, with an AUC of 0.696 (95% CI: 0.645 – 0.747) in the training cohort and 0.673 (95% CI: 0.612 – 0.734) in the validation cohort, suggesting reasonable generalizability. Conclusion: These findings underscore the significance of marital status, educational level, and inflammatory markers in the stratification of depression risk among adult women in the United States. The developed nomogram serves as a practical tool for clinicians to evaluate individual depression risk, potentially aiding in the implementation of early intervention strategies for high-risk populations.