Prevalence of Obesity and Metabolic Syndrome in the High Cardiovascular Risk Setting of Rural Western Honduras

Ethn Dis. 2024 Apr 10;33(2-3):124-129. doi: 10.18865/ed.33.2-3.124. eCollection 2023 Apr.

Abstract

Objective: To determine the prevalence of obesity and metabolic syndrome (MS) in the population older than 45 years in rural Western Honduras and contribute to the limited literature on MS in Central America.

Methods: Descriptive cross-sectional study conducted in the District of Copan. The study includes 382 men and women aged 45 to 75 years. With proper consent, anthropometric parameters, blood pressure, blood sugar, and lipid profile were evaluated. MS was diagnosed by using the National Cholesterol Education Program Criteria - Adult Panel Treatment III (NCEP-ATP III). Data were stored in REDCap (Research Electronic Data Capture) and analyzed with STATA14.

Results: Data were collected on 382 patients; of these, 38% were male and 62% female. The prevalence of obesity was 24.1% for both sexes. The prevalence of MS was 64.9%. Prevalence in males and females was 54% and 71%, respectively. Notable parameters were elevated triglycerides (71%), low High-density lipoprotein cholesterol (HDL-C) (63.4%), and abdominal obesity (56.8%). In men, the distribution of MS was more homogeneous, with a mean result of 80% amongst all ages.

Conclusions: The overall prevalence of obesity and MS is severely underestimated in rural Honduras. The most remarkable parameter for MS was high triglycerides (71%). Sixty-nine percent of the population has above-normal Body Mass Index (BMI). Public health efforts to control comorbidities and tackle risk factors in this population should take utmost priority.

Keywords: Diabetes; Hypertension; Metabolic Syndrome; Obesity; Public Health.

MeSH terms

  • Aged
  • Cardiovascular Diseases / epidemiology
  • Cross-Sectional Studies
  • Female
  • Honduras / epidemiology
  • Humans
  • Male
  • Metabolic Syndrome* / epidemiology
  • Middle Aged
  • Obesity* / epidemiology
  • Prevalence
  • Risk Factors
  • Rural Population* / statistics & numerical data