Obesity indicators mediate the association between the aggregate index of systemic inflammation (AISI) and type 2 diabetes mellitus (T2DM) - Ziying Su; Lei Cao; Hailong Chen; Peng Zhang; Chunwei Wu; Jing Lu; Ze He (Lipids in Health and Disease)
Abstract Objective This study analyzes data from the 2009–2018 National Health and Nutrition Examination Survey (NHANES) to explore the relationship between the Aggregate Index of Systemic Inflammation (AISI), also referred to as the pan-immune-inflammation value (PIV), and Type 2 Diabetes Mellitus (T2DM) among adults in the United States. Furthermore, it evaluates the mediating effect of obesity indicators on this association. Methods This study included 9,947 individuals from NHANES and applied appropriate weighting techniques. To examine the relationship between AISI and T2DM, we used various statistical models, including weighted multivariable logistic regression, smooth curve fitting, threshold effect analysis, subgroup analysis, trend tests, mediation analysis, and Shapley additive explanations (SHAP) models. Results This research included a total of 9,947 participants, with 3,220 diagnosed with T2DM, while 6,727 remained undiagnosed. Weighted multiple logistic regression with all covariates adjusted indicated that with every one-unit increment in AISI/1000, there was an 88.3% likelihood of T2DM occurrence (OR: 1.883, 95% CI: 1.378–2.571). The stratified analysis identified significant differences in this association based on age, biological sex, level of education, poverty-income ratio (PIR), tobacco consumption status, and body mass index (BMI). Interaction tests revealed a positive association between AISI and T2DM, apart from PIR, BMI, age, education attainment, race, gender, tobacco use status, Estimated Glomerular Filtration Rate(eGFR), platelet count, and high blood pressure, with none of the interaction p-values falling below 0.05. Nevertheless, the occurrence of cardiovascular disease (CVD) among participants may affect the strength of this relationship, where an interaction p-value was less than 0.05. Additionally, smoothing curve fitting revealed a nonlinear relationship between AISI and T2DM, marking a significant change at AISI/1000 of 0.21. Mediation analysis indicated that five obesity-related indicators—LAP, VAI, WHtR, WWI and ABSI — partly mediated the association between AISI/1000 and T2DM. Conclusion An increase in AISI is associated with an elevated probability of T2DM, with obesity indicators potentially mediating this relationship. Reducing AISI and managing obesity may help prevent T2DM. However, with the cross-sectional design of this study, causal relationships cannot be established. Future research should utilize longitudinal studies to confirm these findings. Graphical Abstract