Association Between Neutrophil Percentage–Albumin Ratio and Biological Aging in Rheumatoid Arthritis in the United States: A Cross‐Sectional Study of NHANES

TL;DR

This study finds that a blood marker called NPAR is linked to faster biological aging in rheumatoid arthritis patients, suggesting it could help identify those at higher risk.

Contribution

The study is the first to systematically validate the association between NPAR and biological aging in rheumatoid arthritis patients.

Findings

Higher NPAR values are significantly associated with increased biological aging acceleration in RA patients.

Nonlinear analysis shows that NPAR above certain thresholds sharply increases aging risk.

NPAR has moderate predictive power for biological aging acceleration with an AUC of 0.71–0.75.

Abstract

The accelerating process of global aging has made the burden of age‐related diseases increasingly severe, and traditional chronological age fails to reflect individual heterogeneity in aging. The neutrophil percentage‐to‐albumin ratio (NPAR), is a multidimensional health assessment index composed of inflammatory markers (neutrophils) and nutritional markers (albumin) to reflect inflammation and nutritional status, has shown unique potential in rheumatoid arthritis (RA) research. However, its association with biological age (BA; such as Klemera–Doubal method [KDM] age and phenotypic age, PhenoAge) has not yet been systematically validated in RA patients. By evaluating NPAR indicators in patients with RA, this study intends to reveal its value as a potential biomarker for predicting biological aging and its acceleration.

This study was based on the National Health and Nutrition Survey 1999–2018 cycle database, and a cross‐sectional analysis of 1053 adult patients with RA was included. Core variable definitions include: neutrophil–albumin ratio (NPAR) = percentage of neutrophils (%)/albumin (g/dL); BA was calculated by the KDM (including 10 biomarkers) and the PhenoAge algorithm, respectively. Accelerated aging is quantified as the difference between BA and chronological age. The statistical analysis used a multi‐model validation strategy: 1) multivariate linear regression to evaluate the association between NPAR and continuous aging acceleration indicators; 2) the restricted cubic spline (RCS) model explores the nonlinear relationship; 3) stratified subgroup analysis to test for effect heterogeneity. All models were stratified for sociodemographic characteristics (age, sex, and ethnicity), lifestyle factors (smoking, alcohol consumption, and physical activity), and clinical covariates (body mass index [BMI], hypertension, and history of diabetes).

In an analysis of 1053 RA patients in the United States, women accounted for 56.48% and men for 43.52%; the group with the highest NPAR (T3) showed more significant aging characteristics (≥65 years old 34.75%, females 62.80%, and diabetes 27.69%) and higher biological aging acceleration rates (KDM acceleration 42.81% vs. low group 25.81%; PhenoAge acceleration 62.13% vs. 37.74%; all p  < 0.001). After adjustment for multiple factors, the BA of KDM increased by 0.86 years for every 1 unit increase in NPAR (95% confidence interval [CI]: 0.39–1.32, p  < 0.001), and PhenoAge increased by 1.32 years (95% CI: 0.93–1.71, p  < 0.001). Taking the lowest NPAR group (T1) as the reference group, the highest NPAR group (T3) had an increased risk of accelerated aging of KDM by 149% (OR = 2.49, 95% CI: 1.44–4.31), and the risk of PhenoAge increased sharply by 259% (OR = 3.59, 95% CI: 2.17–5.95). Nonrestrictive spline curve analysis further revealed that there was a nonlinear positive correlation between the NPAR index and biological aging. When NPAR > 13.128, the growth rate of biological aging was significantly accelerated (p for nonlinear = 0.05), while when NPAR > 14.512, the risk of phenotypic aging accelerated sharply (p for nonlinear = 0.002). Area under the curve (AUC) of NPAR in the combined model for predicting biological senescence acceleration was 0.71–0.75.

Elevated NPAR is significantly associated with accelerated biological aging in RA patients, and the mechanism may involve neutrophil migration dysfunction, oxidative damage caused by albumin deficiency, and chronic inflammatory pathways (such as NF‐κB activation). As a low‐cost inflammatory marker, NPAR holds promise for integration into clinical aging risk assessment systems to identify high‐risk RA populations requiring early intervention. The study’s limitations include the inability to infer causality due to the cross‐sectional design and a relatively small sample size, necessitating further validation through cohort studies in the future.

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