Burden of Metabolic Syndrome Among a Low-Income Population in China: A Population-Based Cross-Sectional Study

DIABETES METABOLIC SYNDROME AND OBESITY-TARGETS AND THERAPY(2022)

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摘要
Introduction: Metabolic syndrome (MetS) is a chronic and complex disease associated with all-cause mortality, cardiovascular disease, and type 2 diabetes. The present study aimed to evaluate the prevalence of MetS and its risk factors among middle-aged and older adults in low-income, low-education rural areas with a high incidence of stroke.Methods: This cross-sectional study of the general population was performed from April 2019 to June 2019 in rural areas of Tianjin, China. All eligible residents aged >= 45 years and without active malignant tumors, hepatic failure, and severe renal disease underwent routine medical examinations, which included a questionnaire, physical examination, and routine blood and biochemical tests. The modified International Diabetes Federation criteria for the Asian population was used to identify patients with MetS.Results: A total of 3175 individuals (44.8% men, 55.2% women) were included in the final analysis. The prevalence of MetS was 52.8%, with higher prevalence in women than in men (62.4%and 40.9%, respectively). Of the five MetS components, high blood pressure and abdominal obesity were the two most prevalent in both women and men, accounting for 89.3% and 62.0%, respectively, followed by elevated fasting plasma glucose, low high-density lipoprotein cholesterol, and elevated triglycerides. Multivariate logistic regression analysis revealed the following traits to be risk factors for MetS: female sex, self-reported smoking, self-reported snoring, high body mass index, high waist-to-hip ratio, and high serum urate level.Conclusion: The prevalence of MetS was quite high in rural areas with a low-income, low-education population. Implementing preventive and therapeutic interventions based on these risk factors is essential to prevent metabolic abnormalities.
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metabolic syndrome, epidemiology, risk factors, population-based, cross-sectional study
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