A low-cost hematologic biomarker for evaluating peripheral arterial disease risk: Derived neutrophil–lymphocyte ratio in NHANES 1999–2004 adults

Peripheral arterial disease (PAD), which affects over 200 million individuals globally, signifies systemic atherosclerosis with significant morbidity and healthcare burden. Chronic inflammation underpins its pathogenesis, and highlights the need for accessible biomarkers. The derived neutrophil-lymphocyte ratio (dNLR) offers a cost-effective inflammatory indicator, but remains underexplored for PAD association in population-based studies. This cross-sectional analysis utilized the 1999-2004 National Health and Nutrition Examination Survey (NHANES) data from 5223 adults aged ≥40 years. PAD was defined as an ankle-brachial index < 0.90. dNLR quartiles were established, and multivariable logistic regression was used to evaluate the dNLR-PAD relationship across progressively adjusted models: model 1 (unadjusted), model 2 (demographics/socioeconomic factors/physical activity), model 3 (model 2 + metabolic markers), and model 4 (model 3 + comorbidities). Subgroup analyses were used to assess consistency. Higher dNLR quartiles showed a significantly reduced PAD prevalence (Q1: 8.1% vs Q4: 4.8%; P = .004). After full adjustment (model 4), each unit increase in the dNLR conferred 11% greater PAD odds (odds ratio [OR]: 1.11; 95% confidence interval: 1.03-1.19; P = .006). Participants in the highest quartile (Q4) had a 49% elevated PAD risk versus Q1 (OR: 1.49; 95% confidence interval: 1.05-2.11; P = .025), demonstrating a dose-dependent trend (P trend = .015). Stratified analyses confirmed robust associations across demographics and clinical subgroups, with pronounced effects in Mexican-Americans (OR: 1.44). Elevated dNLR is independently associated with higher PAD prevalence in a representative US cohort, supporting its utility as an economical, routinely obtainable inflammatory biomarker for risk stratification. Prospective studies should validate the optimal dNLR thresholds and integrate nutritional indices to refine PAD risk paradigms.