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

Ekram W Abd El-Wahab1, Hanan Z Shatat1, Fahmy Charl2

  • 1Department of Tropical Health, High Institute of Public Health, Alexandria University, Egypt.

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|October 31, 2019
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Metabolic syndrome (MetS) affects over half of Egyptians studied, increasing risks for heart disease and diabetes. Obesity and inactivity are key drivers, necessitating public health interventions.

Keywords:
Egyptcardiovascular diseasediabetesfatty livermetabolic syndromepredictionrisk assessmentrisk factors

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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.