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Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder characterized by insulin resistance, in which target tissues such as the liver, muscle, and adipose tissue respond poorly to insulin. It is also associated with inadequate compensatory insulin secretion, where pancreatic β-cells fail to produce sufficient insulin. Together, these abnormalities lead to persistent hyperglycemia.EtiologyT2DM develops through a complex interaction of genetic predisposition and environmental or...
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Metabolic Syndrome in the Amazon: Customizing Diagnostic Methods for Urban Communities.

José M Alcaide-Leyva1,2, Manuel Romero-Saldaña1,2, María García-Rodríguez3

  • 1Department of Nursing, Pharmacology and Physiotherapy, Faculty of Medicine and Nursing, University of Cordoba, 14014 Cordoba, Spain.

Nutrients
|February 13, 2025
PubMed
Summary

A new diagnostic model effectively detects metabolic syndrome using systolic blood pressure and very-low-density lipoprotein cholesterol. This cost-effective tool aids early intervention in urbanizing populations.

Keywords:
clinical decision treediagnostic modelearly detectionmetabolic syndromepublic healthurban Amazonian population

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Area of Science:

  • Public Health
  • Cardiovascular Health
  • Metabolic Disorders

Background:

  • Metabolic syndrome prevalence is rising in urbanizing areas like the Peruvian Amazon due to lifestyle changes.
  • Early detection is crucial for managing metabolic disorders and preventing chronic diseases.

Purpose of the Study:

  • Develop and validate a simple, cost-effective diagnostic model for early metabolic syndrome detection.
  • Target the urban population of San Juan Bautista, Iquitos.

Main Methods:

  • Cross-sectional study of 251 adults (>18 years).
  • Collected anthropometric, body composition, and biochemical data.
  • Used logistic regression and decision trees to identify predictors and build the model.

Main Results:

  • Metabolic syndrome prevalence was 47.9%.
  • Systolic blood pressure, triglycerides, and very-low-density lipoprotein cholesterol were key predictors.
  • The model (VLDL cholesterol + systolic blood pressure) showed 91.6% sensitivity and 78.5% specificity.

Conclusions:

  • The developed model is a practical, low-cost tool for early metabolic syndrome detection in resource-limited urban settings.
  • Further validation is needed due to sample size and lack of external testing.
  • Implementation in primary care can facilitate timely interventions for vulnerable populations.