Investigating nonlinear associations between neutrophil percentage to albumin ratio and cardiovascular disease: a nationally representative cross-sectional study

• Published in: Scientific reports Vol. 14; no. 1; pp. 23632 - 10
• Main Authors: Wang, Run, Tao, Weijun, Chen, Houliang, Ma, Tianyu, Cheng, Xiaobing
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 09.10.2024; Nature Publishing Group; Nature Portfolio
• Subjects: 692/53; 692/699/75; 692/700/478; Adult; Aged; Albumin; Cardiovascular disease; Cardiovascular diseases; Cardiovascular Diseases - blood; Cardiovascular Diseases - epidemiology; Cross-Sectional Studies; Female; Generalized linear models; Humanities and Social Sciences; Humans; Inflammation; Leukocyte Count; Leukocytes (neutrophilic); Male; Middle Aged; multidisciplinary; Neutrophil percentage to albumin ratio; Neutrophils; NHANES; Nonlinear systems; Nutrition Surveys; Prevalence; Regression analysis; Science; Science (multidisciplinary); Sensitivity analysis; Serum Albumin - analysis; Cardiovascular disease; Inflammation; NHANES; Neutrophil percentage to albumin ratio
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-024-75111-y

While the negative consequences of particular illnesses have been associated with the neutrophil percentage to albumin ratio (NPAR), its association with cardiovascular disease (CVD) is still lacking in the broader public. This study examines the relationship between NPAR and CVD prevalence using information from the National Health and Nutrition Examination Survey (NHANES), with particular attention to potential nonlinear associations. This analysis included 26,225 adults from NHANES 2011–2020. We investigated the association between NPAR levels and CVD using weighted generalized linear models, subgroup analysis, threshold effects, receiver operating characteristic (ROC) curves, and sensitivity analysis. Restricted cubic splines were used to assess potential nonlinearity in the NPAR-CVD association. Elevated NPAR levels were significantly associated with increased CVD prevalence ( P  < 0.001). In model 3, individuals in the highest NPAR quartile had a 46% greater CVD prevalence compared to those in the lowest quartile [OR: 1.46 (1.16, 1.83), P  = 0.002], a finding consistent across unweighted logistic regression models. This association remained unchanged by various factors ( P  > 0.05). While restricted cubic spline analysis indicated potential nonlinearity, it did not significantly improve model fit over the linear model ( P  > 0.05). This study identifies a significant association between NPAR and CVD prevalence among the broader populace, suggesting the potential influence of inflammation on cardiovascular disease.