Association of novel inflammation markers derived from high-sensitivity C-reactive protein with anemia: a cross-sectional study based on NHANES 2015–2018

This study aimed to investigate the associations of the high-sensitivity C-reactive protein to high-density lipoprotein cholesterol ratio (HCHR) and the high-sensitivity C-reactive protein to lymphocyte ratio (HCLR) with anemia in the general population. A cross-sectional analysis was conducted using data from 8638 adults enrolled in the National Health and Nutrition Examination Survey (NHANES) 2015–2018. Anemia was defined according to the World Health Organization (WHO) criteria. HCHR and HCLR were calculated based on laboratory measurements. Multivariable logistic regression models were applied to estimate the associations between HCHR, HCLR, and anemia. Subgroup analyses and smooth curve fitting were performed to assess effect modification and potential nonlinear relationships. Sensitivity analyses were also performed to assess the robustness of the results. Among the 8638 participants, 930 individuals had anemia. Compared with non-anemic participants, those with anemia had significantly higher median levels of HCHR (p < 0.001) and HCLR (p < 0.001). In fully adjusted models, higher HCHR (OR = 1.007, 95% CI: 1.002–1.011, p = 0.012) and HCLR (OR = 1.027, 95% CI: 1.013–1.042, p = 0.004) were independently associated with an increased risk of anemia. Compared with the lowest quartile, participants in the highest quartile of both HCHR and HCLR had significantly greater odds of anemia (P for trend < 0.05). Subgroup analyses confirmed the consistency of the associations between HCHR, HCLR, and anemia. Smooth curve fitting revealed nonlinear relationships between HCHR, HCLR, and anemia risk. Higher HCHR and HCLR were significantly associated with an increased risk of anemia among U.S. adults, underscoring the potential utility of inflammation-based composite biomarkers in anemia risk stratification. Nevertheless, further prospective studies are warranted to confirm causality and evaluate clinical applicability. Not applicable.