Background/Objectives: Both adiposity and nutritional–inflammatory status influence glucose metabolism; however, their longitudinal associations with glycemic changes in non-diabetic populations remain unclear. We examined the independent, interactive, and joint associations of body mass index (BMI) and prognostic nutritional index (PNI) with the 3-year change in HbA1c (ΔHbA1c). PNI, a composite marker of serum albumin and peripheral lymphocyte count, reflects both protein nutritional status and systemic immune competence. We hypothesized that BMI and PNI would each independently predict ΔHbA1c and that their joint profiling would identify higher-risk subgroups. Methods: A total of 9414 non-diabetic adults from the Shanghai Suburban Adult Cohort were included. Participants with diabetes at baseline (defined as fasting plasma glucose ≥ 7.0 mmol/L, 2-h post-load glucose ≥ 11.1 mmol/L, HbA1c ≥ 6.5%, or self-reported physician diagnosis of diabetes or use of glucose-lowering medications) were excluded. BMI was measured, and PNI was calculated as serum albumin + 5 × lymphocyte count. ΔHbA1c was assessed over a 3-year period. Multivariable linear regression, interaction testing, and joint stratification were performed. Covariate selection was guided by prior biological plausibility, and model adequacy was evaluated using the Akaike Information Criterion (AIC). Results: Both BMI (β = 0.013% per kg/m2, 95% CI: 0.011–0.016, p < 0.001) and PNI (β = 0.002% per unit, 95% CI: 0.000–0.004, p = 0.019) were independently and positively associated with ΔHbA1c. No significant interaction was observed (p = 0.431). High BMI (≥24 kg/m2) was associated with glycemic worsening irrespective of PNI level (β ≈ 0.075%, p < 0.001). Among normal-weight individuals, higher PNI was associated with a modest increase in ΔHbA1c (β = 0.031%, p = 0.007). Conclusions: Although the absolute effect sizes were modest at the individual level, BMI was consistently and independently associated with glycemic deterioration therefore, even small per-unit increases may translate into meaningful risk at the population level given the high prevalence of overweight and obesity. PNI showed a small positive association, suggesting that in relatively healthy populations a higher PNI may partly capture subtle pro-glycemic factors—such as low-grade inflammation or higher protein intake—rather than representing unambiguous nutritional benefit. The absence of interaction suggests that BMI and PNI act through largely independent pathways. These findings extend prior evidence by demonstrating that PNI provides modest additional glycemic information beyond BMI in non-diabetic community-dwelling adults, particularly among those of normal weight.
Yu et al. (Fri,) studied this question.