Scholarlink

Background <p>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.</p> Methods <p>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.</p> Results <p>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 (<i>n</i> = 45, 18.1%), followed by Leicester Risk Assessment (LRA) (<i>n</i> = 42, 16.9%), Japanese Metabolic Syndrome Risk Score (JAMRISC) (<i>n</i> = 32, 12.9%), diabetes risk score of Oman (OMANI) (<i>n</i> = 25, 10.1%), and FINDRISC (<i>n</i> = 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; <i>P</i> &lt; 0.001), whereas exercise was strongly protective (OR = 0.17; 95%CI: 0.06–0.47; <i>P</i> = 0.001).</p> Conclusion <p>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.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Diabetes mellitus and metabolic syndrome risk assessment in young syrians using five validated risk tools: a cross-sectional study

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月26日

查看全文
  • Stephani Khaloof,
  • Lama M. Taha,
  • Ayman Abdeen,
  • Nour M. Kandakji,
  • Alaa Jabr,
  • Weam Aldiban

摘要

Background

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.

Methods

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.

Results

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).

Conclusion

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.