Adapting a Prediction Rule for Metabolic Syndrome Risk Assessment Suitable for Developing Countries

Area of Science:

• Cardiology
• Endocrinology
• Public Health

Background:

• Metabolic syndrome (MetS) is a critical risk factor for cardiovascular diseases (CVD) and type 2 diabetes mellitus (DM).
• Early identification of individuals at high risk for MetS is crucial for prevention.
• The prevalence and determinants of MetS in Egypt were previously unknown.

Purpose of the Study:

• To determine the prevalence and identify determinants of MetS in urban and rural Egyptian adults.
• To develop and validate a predictive model for MetS in the Egyptian population.
• To assess the risk of associated conditions like ischemic heart disease (IHD), DM, and fatty liver.

Main Methods:

• A cross-sectional study involving 270 adults from urban and rural Alexandria, Egypt.
• Clinical evaluation, sociodemographic, lifestyle, and dietary data collection.
• MetS defined by AHA/NHLBI criteria; risk assessment using validated charts; multivariate logistic regression for prediction model development.

Main Results:

• MetS prevalence was 57.8%, with high associated risks for IHD, DM, and fatty liver.
• Key predictors of MetS included obesity (OR 16.3), morbid obesity (OR 21.7), unemployment (OR 2.05), and family history of chronic diseases (OR 4.38).
• Weekly caffeine consumption showed a protective effect (OR 0.036).

Conclusions:

• Central obesity and sedentary lifestyles are significant contributors to the high MetS rates in Egypt.
• A validated prediction model can aid in identifying at-risk individuals for MetS and related conditions.
• Targeted interventions are essential to mitigate the predisposition to cardiometabolic diseases in the Egyptian population.