Association of lower hemoglobin-to-RDW ratio with sarcopenia: Insights from a nationally representative NHANES 2011–2018 study in the United States

Lifestyle changes have led to a rising incidence of sarcopenia, which adversely affects quality of life and health. Inflammation and malnutrition play key roles in its development. The hemoglobin-to-red cell distribution width ratio (HRR) is a blood marker reflecting these factors. This study explores the relationship between HRR and sarcopenia risk and its potential as a predictive tool. We utilized National Health and Nutrition Examination Survey datasets spanning 2011 to 2018, comprising 10,492 adults aged 20 years and older. Sarcopenia was defined according to standard criteria for muscle mass. HRR was divided into 4 quartile groups (Q1 to Q4). We conducted multivariate logistic regression to examine the relationship between HRR and the risk of sarcopenia. To assess potential nonlinear associations, restricted cubic spline models were applied. Additionally, subgroup analyses were carried out to test the stability of the results. We identified 931 cases of sarcopenia, representing 8.87% of all participants. Multivariable logistic regression showed that HRR as a continuous variable was significantly inversely associated with sarcopenia risk (Model 3: odds ratio [OR] = 0.39, 95% confidence interval: 0.24–0.66, P < .001). Compared with the Q1 group, the Q3 and Q4 groups had significantly lower risks of sarcopenia (Q3: OR = 0.78, P = .029; Q4: OR = 0.68, P = .002). The trend tests were statistically significant in all models ( P for trend < .001). Restricted cubic spline analysis revealed no significant nonlinear relationship, indicating a linear inverse association between HRR and sarcopenia. Subgroup analysis revealed no significant interactions, supporting the robustness of the results. Lower HRR levels may be an independent risk factor for sarcopenia. HRR might contribute to the early recognition and risk assessment of populations prone to sarcopenia. Prospective investigations are essential to substantiate its predictive capacity and reveal the mechanisms involved.