{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,19]],"date-time":"2026-09-19T07:13:45Z","timestamp":1789802025419,"version":"4.0.1"},"reference-count":51,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2026,9,18]],"date-time":"2026-09-18T00:00:00Z","timestamp":1789689600000},"content-version":"vor","delay-in-days":260,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Diabetes Research"],"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>The objective of this study was to explore the cross\u2010sectional association between albumin\u2010corrected anion gap (ACAG) and the composite outcome of prediabetes or diabetes mellitus (PD\u2010DM) using data from the National Health and Nutrition Examination Survey (NHANES) 2005\u20132010.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A cross\u2010sectional analysis was conducted, comprising 3937 adult participants aged \u2265\u200920 years, who were categorized into two groups: those with PD\u2010DM and those without PD\u2010DM. The baseline characteristics were compared using the most appropriate statistical tests. Logistic regression analyses, restricted cubic spline (RCS), subgroup analyses, interaction tests, and sensitivity analyses were performed to investigate the cross\u2010sectional relationship between ACAG and PD\u2010DM. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were computed to assess whether ACAG offered incremental predictive value for PD\u2010DM.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Participants with PD\u2010DM exhibited higher ACAG levels (15.02 vs. 14.14,\n                      <jats:italic>p<\/jats:italic>\n                      &lt; 0.01). Each unit increase in ACAG was associated with 1.16\u2010fold higher odds of PD\u2010DM after full adjustment (odds ratio [OR] = 1.16, 95% confidence interval [CI]: 1.09\u20131.23;\n                      <jats:italic>p<\/jats:italic>\n                      &lt; 0.01). RCS showed that ACAG was linearly associated with PD\u2010DM (\n                      <jats:italic>p<\/jats:italic>\n                      for nonlinearity = 0.48). Subgroup analyses revealed a stronger association in females and lower poverty income ratio (PIR) groups (\n                      <jats:italic>p<\/jats:italic>\n                      for interaction &lt; 0.05). NRI and IDI analyses confirmed that incorporating ACAG into the baseline model significantly improved risk discrimination and reclassification for PD\u2010DM (all\n                      <jats:italic>p<\/jats:italic>\n                      &lt; 0.01). Sensitivity analyses confirmed robustness.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>This cross\u2010sectional study demonstrated that ACAG is positively associated with PD\u2010DM, especially among females and lower PIR participants. ACAG also showed significant incremental predictive value for PD\u2010DM risk prediction. Because of the cross\u2010sectional design, causal inference cannot be established. Further large\u2010scale prospective studies are still needed to elucidate the role of ACAG in the development of PD\u2010DM.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1155\/jdr\/3632830","type":"journal-article","created":{"date-parts":[[2026,9,19]],"date-time":"2026-09-19T06:16:07Z","timestamp":1789798567000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Association Between Albumin\u2010Corrected Anion Gap and Prevalent Prediabetes or Diabetes Mellitus: A Cross\u2010Sectional Analysis of NHANES 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