Associations Between Depression Severity, Antidepressant Use, and Metabolic Syndrome Components Among Chinese Adults: A Cross-Sectional Study Based on Historical Medical Records

Abstract

Background: Depression affects approximately 280 million people globally and often co-occurs with metabolic syndrome (MetS), a cluster of cardiometabolic risks that increase cardiovascular and diabetes events. This study investigates the associations among depression severity, antidepressant use and MetS components in Chinese adults.

Methods: In this cross-sectional study from a Chinese hospital (2018–2025), electronic medical records of 585 adults (aged ≥18 years, 61.54% female) were analysed using convenience sampling. Depression severity was assessed via Patient Health Questionnaire-9 (PHQ-9) scores (normal: 0–4; mild: 5–9; moderate: 10–14; severe: 15–27). MetS was defined in accordance with the National Cholesterol Education Program Adult Treatment Panel III criteria (≥three components: hypertension ≥130/85 mmHg, triglycerides >150 mg/dL, high-density lipoprotein cholesterol (HDL-C) <40/50 mg/dL, waist circumference >102/88 cm for men/women and glucose ≥100 mg/dL). Logistic regression was applied to evaluate associations, including serotonin reuptake inhibitors (SSRIs) versus serotonin-norepinephrine reuptake inhibitors (SNRIs).

Results: In this hospital-based cohort, patients with severe depression exhibited a substantially increased odds for clustered MetS (adjusted odds ratio [OR] = 13.461, 95% confidence interval [CI]: 2.461–253.037, p = 0.015 for one MetS component and OR = 2.129, 95% CI: 1.080–4.130, p = 0.027 for two components). Severe depressive symptoms were significantly associated with multiple MetS components, specifically hyperglycaemia (adjusted OR = 2.022, 95% CI: 1.033–4.068, p = 0.043), increased triglycerides (adjusted OR = 2.460, 95% CI: 1.304–4.661, p = 0.005) and reduced HDL-C (adjusted OR = 2.653, 95% CI: 1.397–5.102, p = 0.003). Antidepressant use increased MetS odds (central obesity OR = 3.098, 95% CI: 2.098–4.614, p < 0.001; hyperglycaemia OR = 2.312, 95% CI: 1.566–3.446, p < 0.001), with SSRIs (95.2%, n = 317) being predominant over SNRIs (4.8%, n = 16) but having similar metabolic impacts in subgroups.

Conclusions: Depression severity and antidepressant use are significantly associated with individual components of MetS and their clustering, underscoring the need for personalised metabolic screening in affected patients. Recognising and addressing metabolic abnormalities in individuals with depression are essential to optimise treatment outcomes and mitigate long-term cardiometabolic risks.