Association Between Albumin-Corrected Anion Gap and Prevalent Prediabetes or Diabetes Mellitus: A Cross-Sectional Analysis of NHANES 2005-2010.
The objective of this study was to explore the cross-sectional association between albumin-corrected anion gap (ACAG) and the composite outcome of prediabetes or diabetes mellitus (PD-DM) using data from the National Health and Nutrition Examination Survey (NHANES) 2005-2010.
A cross-sectional analysis was conducted, comprising 3937 adult participants aged ≥ 20 years, who were categorized into two groups: those with PD-DM and those without PD-DM. 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-sectional relationship between ACAG and PD-DM. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were computed to assess whether ACAG offered incremental predictive value for PD-DM.
Participants with PD-DM exhibited higher ACAG levels (15.02 vs. 14.14, p < 0.01). Each unit increase in ACAG was associated with 1.16-fold higher odds of PD-DM after full adjustment (odds ratio [OR] = 1.16, 95% confidence interval [CI]: 1.09-1.23; p < 0.01). RCS showed that ACAG was linearly associated with PD-DM (p for nonlinearity = 0.48). Subgroup analyses revealed a stronger association in females and lower poverty income ratio (PIR) groups (p for interaction < 0.05). NRI and IDI analyses confirmed that incorporating ACAG into the baseline model significantly improved risk discrimination and reclassification for PD-DM (all p < 0.01). Sensitivity analyses confirmed robustness.
This cross-sectional study demonstrated that ACAG is positively associated with PD-DM, especially among females and lower PIR participants. ACAG also showed significant incremental predictive value for PD-DM risk prediction. Because of the cross-sectional design, causal inference cannot be established. Further large-scale prospective studies are still needed to elucidate the role of ACAG in the development of PD-DM.
A cross-sectional analysis was conducted, comprising 3937 adult participants aged ≥ 20 years, who were categorized into two groups: those with PD-DM and those without PD-DM. 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-sectional relationship between ACAG and PD-DM. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were computed to assess whether ACAG offered incremental predictive value for PD-DM.
Participants with PD-DM exhibited higher ACAG levels (15.02 vs. 14.14, p < 0.01). Each unit increase in ACAG was associated with 1.16-fold higher odds of PD-DM after full adjustment (odds ratio [OR] = 1.16, 95% confidence interval [CI]: 1.09-1.23; p < 0.01). RCS showed that ACAG was linearly associated with PD-DM (p for nonlinearity = 0.48). Subgroup analyses revealed a stronger association in females and lower poverty income ratio (PIR) groups (p for interaction < 0.05). NRI and IDI analyses confirmed that incorporating ACAG into the baseline model significantly improved risk discrimination and reclassification for PD-DM (all p < 0.01). Sensitivity analyses confirmed robustness.
This cross-sectional study demonstrated that ACAG is positively associated with PD-DM, especially among females and lower PIR participants. ACAG also showed significant incremental predictive value for PD-DM risk prediction. Because of the cross-sectional design, causal inference cannot be established. Further large-scale prospective studies are still needed to elucidate the role of ACAG in the development of PD-DM.