Adiposity Indices and Depression Risk in Type 2 Diabetes: Evaluating Predictive Utility beyond Body Mass Index

Abstract

Introduction: Depression is a frequent comorbidity in type 2 diabetes mellitus (T2DM), yet evidence on the predictive utility of adiposity indices beyond body mass index (BMI) remains limited, particularly in Nigeria, where the dual burden of diabetes and mental health disorders is rising. Aim:This study evaluated the association and diagnostic performance of adiposity indices in predicting depression among T2DM patients at Ahmadu Bello University Teaching Hospital, Zaria. Methods: A cross-sectional study was conducted among 400 T2DM patients. Depression status was determined using the Patient Health Questionnaire-9 (PHQ-9), with participants divided equally into depressed and non-depressed groups. Seven adiposity indices were assessed: body adiposity index (BAI), BMI, waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), conicity index (CI), a body shape index (ABSI), and skinfold thickness (SF). Binary logistic regression was used to assess associations, while diagnostic performance was evaluated using receiver operating characteristic (ROC) curves and the Youden Index (YI). Results: The logistic regression model demonstrated a good fit (χ² = 275.47, df = 18, p < 0.001; Hosmer–Lemeshow test: p = 0.55). BAI was positively associated with higher odds of depression (odds ratio (OR) = 2.17, 95% CI: 1.08–4.40, p < 0.05). WHR, WHtR, CI, ABSI, and SF showed negative associations with reduced odds of depression, with SF showing the strongest protective relationship (OR = 0.14, 95% CI: 0.06–0.31, p < 0.05). BMI showed no significant association with depression (OR = 0.96, CI: 0.44–2.08, p > 0.05). WHR, CI, and ABSI had moderate predictive value (AUCs = 0.59, 0.57, and 0.58, respectively; p < 0.05). WHR provided the best diagnostic performance (72% sensitivity, 58% specificity, YI = 0.30). Conclusion: WHR and ABSI outperformed BMI in predicting depression risk among Nigerian T2DM patients. Incorporating these indices into clinical screening may strengthen early detection and management of comorbid depression.