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Objective <p>To evaluate the associations of the weight-adjusted waist index (WWI) and plasma lipocalin-2 (LCN2) with Montreal Cognitive Assessment (MoCA) -defined mild cognitive impairment (MCI) and to develop a risk prediction model in patients with type 2 diabetes mellitus (T2DM).</p> Methods <p>In this cross-sectional study, 410 patients were included. Anthropometric parameters, metabolic indices, plasma LCN2 levels, and neuropsychological test data were collected. Participants were randomly divided into a training cohort (70%) and a validation cohort (30%). Cognitive function was assessed using neuropsychological tests. MCI was defined based on MoCA scores (&lt; 26). Predictors selected using LASSO regression were subsequently entered into multivariable logistic models. Model performance—including discrimination, calibration, and clinical utility—was evaluated in both cohorts.</p> Results <p>WWI and plasma LCN2 levels were significantly higher in participants with MCI than in those with normal cognition (both P &lt; 0.01). After adjustment for demographic and metabolic factors, WWI (OR = 1.753, 95% CI 1.337–2.299) and plasma LCN2 (per SD increase; OR = 1.680, 95% CI 1.255–2.248) remained independently associated with MCI. A multivariable model incorporating age, gender, education, WWI, and LCN2 demonstrated satisfactory discrimination [area under the curve (AUC) = 0.745 (95% CI 0.688–0.802) in the training cohort and 0.774 (95% CI 0.693–0.854) in the validation cohort], with acceptable calibration in both cohorts. The model showed higher discrimination than models based on individual predictors alone.</p> Conclusion <p>WWI and LCN2 are independently and jointly associated with MCI in T2DM, and their integration may improve risk stratification for cognitive impairment. These obesity- and inflammation-related markers may serve as complementary indicators to support cognitive risk assessment in diabetes care.</p>

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Development and validation of a risk prediction model integrating WWI and lipocalin-2 for cognitive impairment in patients with type 2 diabetes

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月4日

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  • Kunyu Liu,
  • Tong Niu,
  • Junru Zhou,
  • Ruoyu Sun,
  • Shaohua Wang,
  • Yang Yuan

摘要

Objective

To evaluate the associations of the weight-adjusted waist index (WWI) and plasma lipocalin-2 (LCN2) with Montreal Cognitive Assessment (MoCA) -defined mild cognitive impairment (MCI) and to develop a risk prediction model in patients with type 2 diabetes mellitus (T2DM).

Methods

In this cross-sectional study, 410 patients were included. Anthropometric parameters, metabolic indices, plasma LCN2 levels, and neuropsychological test data were collected. Participants were randomly divided into a training cohort (70%) and a validation cohort (30%). Cognitive function was assessed using neuropsychological tests. MCI was defined based on MoCA scores (< 26). Predictors selected using LASSO regression were subsequently entered into multivariable logistic models. Model performance—including discrimination, calibration, and clinical utility—was evaluated in both cohorts.

Results

WWI and plasma LCN2 levels were significantly higher in participants with MCI than in those with normal cognition (both P < 0.01). After adjustment for demographic and metabolic factors, WWI (OR = 1.753, 95% CI 1.337–2.299) and plasma LCN2 (per SD increase; OR = 1.680, 95% CI 1.255–2.248) remained independently associated with MCI. A multivariable model incorporating age, gender, education, WWI, and LCN2 demonstrated satisfactory discrimination [area under the curve (AUC) = 0.745 (95% CI 0.688–0.802) in the training cohort and 0.774 (95% CI 0.693–0.854) in the validation cohort], with acceptable calibration in both cohorts. The model showed higher discrimination than models based on individual predictors alone.

Conclusion

WWI and LCN2 are independently and jointly associated with MCI in T2DM, and their integration may improve risk stratification for cognitive impairment. These obesity- and inflammation-related markers may serve as complementary indicators to support cognitive risk assessment in diabetes care.