Why the study?
How do five validated risk assessment tools compare in identifying T2DM and MetS risk among young Syrian university students?
Cross-Sectional (n=248)
How do five validated risk assessment tools compare in identifying T2DM and MetS risk among young Syrian university students?
Young Syrians have a substantial risk of T2DM and MetS, but significant discrepancies between validated risk tools highlight the need for culturally adapted screening models.
Type 2 diabetes (T2DM) and metabolic syndrome (MetS) are rising globally and regionally, with Syria showing alarming prevalence among youth due to conflict-related lifestyle and healthcare challenges. This study compares five predictive tools to assess T2DM and MetS risk and explore sex and lifestyle-related differences. A cross-sectional study was conducted among Syrian university students using structured questionnaires, anthropometric measurements, and clinical assessments. Five validated risk assessment tools were applied. Statistical methods included descriptive statistics, comparative analysis, and ordinal logistic regression to evaluate predictors of higher risk classification. Among 248 students (129 females, 52%), High-risk classification differed across tools: The Australian Type 2 Diabetes Risk Assessment (AUSDRISK) Tool identifies the largest proportion ( n = 45, 18.1%), followed by Leicester Risk Assessment (LRA) ( n = 42, 16.9%), Japanese Metabolic Syndrome Risk Score (JAMRISC) ( n = 32, 12.9%), diabetes risk score of Oman (OMANI) ( n = 25, 10.1%), and FINDRISC ( n = 19, 7.6%). Pairwise agreement between tools ranged from slight to moderate (κ = 0.154–0.588). Using a consensus of ≥ 3 tools, 10.4% were high risk. Family history increased the odds of a higher risk by more than 40-fold (OR = 40.47; 95%CI: 12.47–131.6; P < 0.001), whereas exercise was strongly protective (OR = 0.17; 95%CI: 0.06–0.47; P = 0.001). This study demonstrated that young Syrians have a substantial risk of T2DM and MetS when assessed with multiple tools. Men’s unhealthy habits led to a greater at-risk classification, particularly JAMRISC, while FINDRISC showed minimal sex differences. Tool discrepancies suggest that relying on a single model may miss cases. Our findings emphasize the need for culturally adapted screening models in Syria.
No takes yet. Share an insight, caveat, or question.
Khaloof et al. (2026) conducted a cross-sectional in Type 2 diabetes and metabolic syndrome risk (n=248). Family history vs. No family history was evaluated on Higher risk classification (OR 40.47, 95% CI 12.47-131.6, p=<0.001).
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: