Metabolic syndrome impact on pulmonary function of women

Diabetes Metab Syndr. 2019 Jan-Feb;13(1):630-635. doi: 10.1016/j.dsx.2018.11.044. Epub 2018 Nov 14.

Abstract

Background: The presence of metabolic syndrome (MetS) and its components may induce structural and physiological changes that exacerbate the impairment of the respiratory function. The aim of the study is to evaluate the impact of metabolic syndrome and its components on lung function in women.

Methods: This is cross-sectional study. A total of 121 women aged 20-75 years were assisted in two primary health centers of Brazil. These women were divided into two groups according to the presence of metabolic syndrome. Waist circumference and blood pressure measurements, high density low-cholesterol (HDL-c) and triglycerides analysis and pulmonary function tests by spirometry were performed.

Results: Metabolic syndrome prevalence was 46.3%. Systemic arterial pressure (BP) and waist circumference (WC) were identified with higher eigenvalues in the main components explaining 26.78% of the variance. The multiple regression analysis showed an inverse relationship between forced expiratory volume in the first second predicted (FEV1%) (β = -6.0, p = 0.03) and predicted forced vital capacity (FVC%) (β = -7, 02, p = 0.004) with the presence of MetS. PA (β = -8.50, p = 0.003) and WC (β = -0.24, p = 0.001) it presented an inverse relationship with FVC% when was adjusted for age, smoking history, menopausal BMI.

Conclusions: WC and PA were considered the parameters most related to MetS by principals components analysis. The diagnosis of MetS presented an inverse relation with the spirometrics parameters. Elevation of BP and WC were the predictors of the CFV% reduction.

Keywords: Metabolic syndrome; Pulmonary function test; Women.

MeSH terms

  • Adult
  • Aged
  • Brazil / epidemiology
  • Cross-Sectional Studies
  • Female
  • Forced Expiratory Volume
  • Humans
  • Metabolic Syndrome / epidemiology
  • Metabolic Syndrome / physiopathology*
  • Middle Aged
  • Principal Component Analysis
  • Regression Analysis
  • Respiratory Function Tests*
  • Risk Factors
  • Waist Circumference