Scientific Reports (Nov 2024)

Association between neutrophil-percentage-to-albumin ratio (NPAR) and metabolic syndrome risk: insights from a large US population-based study

  • Wei Ji,
  • Hongwei Li,
  • Yue Qi,
  • Wenshuo Zhou,
  • Yu Chang,
  • Dongsheng Xu,
  • Yuxi Wei

DOI
https://doi.org/10.1038/s41598-024-77802-y
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 10

Abstract

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Abstract Metabolic syndrome (MetS) is a cluster of conditions that increase the risk of cardiovascular disease and diabetes. This study aimed to investigate the association between Neutrophil-Percentage-to-Albumin Ratio (NPAR) and MetS in a large, nationally representative US population. We analyzed data from 28,178 participants in the National Health and Nutrition Examination Survey (NHANES) 2005–2018. Logistic regression models were used to evaluate the association between NPAR and MetS. Restricted cubic spline (RCS) models were employed to assess the dose-response relationship. Mediation analyses were conducted to explore potential mediating effects of serum uric acid and triglyceride-glucose (TyG) index. After adjusting for confounders, participants in the highest NPAR quartile had a 14% higher risk of MetS compared to those in the lowest quartile (OR 1.14, 95%CI 1.03–1.27, P = 0.010). RCS models revealed a monotonic increasing trend between NPAR and MetS risk (P for overall association = 0.002). Mediation analyses showed that serum uric acid and TyG index mediated 14.93% and 29.45% of the total effect of NPAR on MetS, respectively. Subgroup analyses indicated that the positive association between NPAR and MetS was more pronounced in Mexican Americans, individuals aged 20–65 years, those with lower income, males, current smokers, and moderate drinkers. Higher NPAR is associated with increased risk of MetS in the US adult population. This association is partially mediated by serum uric acid and TyG index. These findings suggest that NPAR may serve as a novel biomarker for MetS risk assessment and provide insights into potential mechanisms linking inflammation and metabolic disorders.

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