{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,27]],"date-time":"2026-10-27T13:46:49Z","timestamp":1793108809631,"version":"4.5.0"},"reference-count":39,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,3,6]],"date-time":"2025-03-06T00:00:00Z","timestamp":1741219200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Endocrinol."],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>The neutrophil-percentage-to-albumin ratio (NPAR), as a low-cost and easily accessible inflammatory biomarker, has garnered considerable attention in various disease studies in recent years. Specifically, existing research has suggested a significant correlation between NPAR and diabetic retinopathy, indicating its potential relevance to diabetic complications. However, despite diabetic kidney disease (DKD) being a complication that severely affects the quality of life of diabetic patients, the association between the prevalence of DKD and NPAR remains to be elucidated. Therefore, this study aims to explore the potential link between NPAR and DKD in patients with type 2 diabetes mellitus.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We extracted complete data on neutrophil percentage, plasma albumin, serum creatinine, and urine albumin-to-creatinine ratio from the National Health and Nutrition Examination Survey database spanning from 2009 to 2018. Multivariable logistic regression models were employed to examine the relationship between NPAR levels and DKD, and conducted sensitivity tests, subsequently employing Generalized Additive Models combined with smooth curve fitting methods to explore the relationships among variables. Then, subgroup analyses were conducted on the association between NPAR and DKD to investigate changes in the relationship across different subgroups. Finally, Receiver operating characteristic curves were used to assess the predictive performance of the independent variable, NPAR, for the dependent variable, DKD.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>A total of 2,263 participants were enrolled in this cross-sectional study. After adjusting for confounding factors, the odds ratio for DKD was 1.44 (95% CI: 1.08-1.90) for the second quartile group, 1.75 (95% CI: 1.33-2.31) for the third quartile group, and 2.95 (95% CI: 2.22-3.93) for the fourth quartile group. Among patients with type 2 diabetes mellitus, a positive correlation was observed between NPAR and DKD. Results from subgroup analyses showed no significant differences among different populations. Receiver operating characteristic (ROC) analysis indicated that NPAR had good predictive performance for DKD.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The prevalence of DKD indicated a positive association with NPAR among individuals with T2DM. Additional large-scale prospective investigations may be helpful in corroborating these findings.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fendo.2025.1552772","type":"journal-article","created":{"date-parts":[[2025,3,6]],"date-time":"2025-03-06T05:11:03Z","timestamp":1741237863000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":18,"title":["Association between neutrophil-percentage-to-albumin ratio and diabetic kidney disease in type 2 diabetes mellitus patients: a cross-sectional study from NHANES 2009\u20132018"],"prefix":"10.3389","volume":"16","author":[{"given":"Hongying","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yue","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuhan","family":"Fan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziming","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hao","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lin","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yun","family":"Lu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yifan","family":"Miao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,3,6]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1097\/XCE.0000000000000210","article-title":"Estimating life years lost to diabetes: outcomes from analysis of National Diabetes Audit and Office of National Statistics data","volume":"9","author":"Heald","year":"2020","journal-title":"Cardiovasc Endocrinol Metab"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1016\/j.diabres.2021.109119","article-title":"IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045","volume":"183","author":"Sun","year":"2022","journal-title":"Diabetes Res Clin Pract"},{"key":"B3","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1111\/dom.14007","article-title":"An updated overview of diabetic nephropathy: Diagnosis, prognosis, treatment goals and latest guidelines","volume":"22","author":"Selby","year":"2020","journal-title":"Diabetes Obes Metab"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.1080\/0886022X.2022.2056053","article-title":"Development and internal validation of machine learning algorithms for end-stage renal disease risk prediction model of people with type 2 diabetes mellitus and diabetic kidney disease","volume":"44","author":"Zou","year":"2022","journal-title":"Ren Fai"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2023.1238927","article-title":"Tubular injury in diabetic kidney disease: molecular mechanisms and potential therapeutic perspectives","volume":"14","author":"Wang","year":"2023","journal-title":"Front Endocrinol"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.2337\/diacare.23.3.417","article-title":"Increased spontaneous adherence of neutrophils from type 2 diabetic patients with overt proteinuria: possible role of the progression of diabetic nephropathy","volume":"23","author":"Takahashi","year":"2000","journal-title":"Diabetes Care"},{"key":"B7","doi-asserted-by":"publisher","DOI":"10.1016\/0168-8227(93)90057-C","article-title":"Polymorphonuclear neutrophils adherence, superoxide anion. 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