Associations of adiposity, atherogenic lipid phenotypes, systemic immune-inflammatory indices, and vascular aging markers with depression in US adults: NHANES 2005-2020.

The biological mechanisms linking cardiometabolic health, immune-inflammatory activation, and vascular aging with depression remain incompletely understood. We aimed to examine the associations of body mass index (BMI), atherogenic lipid phenotypes, systemic immune-inflammatory indices, and vascular aging markers with the risk of moderate-to-severe depression among US adults. We analyzed data from 17,011 participants in the National Health and Nutrition Examination Survey (NHANES) 2005-2020. Depression was defined as a Patient Health Questionnaire-9 score ≥ 10. Independent predictors included BMI, atherogenic lipid profiles (atherogenic index of plasma, high-density lipoprotein cholesterol [HDL-C], triglyceride/HDL-C, non-HDL-C, Castelli indices), immune-inflammatory indices (systemic immune-inflammation index, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, neutrophil-to-platelet ratio), and vascular aging markers (estimated pulse wave velocity, urinary albumin-to-creatinine ratio). Weighted logistic regression and receiver operating characteristic analyses assessed associations and predictive performance. Among 17,011 participants, 8477 were women and 8534 were men. Moderate-to-severe depression prevalence was 10.9% in women and 6.2% in men. In fully adjusted models, higher BMI, atherogenic index of plasma, triglyceride/HDL-C, Castelli indices, systemic immune-inflammation index, neutrophil-to-lymphocyte ratio, neutrophil-to-platelet ratio, estimated pulse wave velocity, and urinary albumin-to-creatinine ratio were significantly associated with greater odds of depression. HDL-C showed an inverse association in women. Associations were generally stronger in women than in men, particularly for atherogenic lipid indices and inflammatory markers. Predictive models incorporating these indices improved classification of moderate-to-severe depression beyond sociodemographic and clinical factors, with area under the curve increases of 0.024 to 0.045 (all P < .05). Adiposity, dyslipidemia, systemic immune-inflammatory activation, and vascular aging were independently associated with depression. These findings support the role of cardiometabolic and inflammatory pathways in depression pathogenesis and highlight potential avenues for prevention and intervention.