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The influence of obesity on IOS parameters in asthma, COPD, and other lung diseases: analyzed by random forest

Thomas Ringbaek, Lars Froelund, Jann Mortensen*, Henrik H El Ali

*Corresponding author for this work
3 Citations (Scopus)

Abstract

BACKGROUND: This study investigates the impact of obesity on impulse oscillometry (IOS) parameters in individuals with asthma, chronic obstructive pulmonary disease (COPD), other lung diseases, and non-respiratory conditions. With rising obesity rates, understanding its effects on respiratory health is increasingly essential. We aimed to evaluate IOS parameters as predictors of respiratory dysfunction across different BMI categories, offering insights into managing complex cases involving obesity and lung disease.

METHODS: We retrospectively analyzed IOS data from 1,947 patients referred to a secondary care allergy and lung clinic. IOS parameters assessed included total and peripheral airway resistance (R5 and R5-20), resonant frequency (Fres), and reactance area (AX), examined relative to BMI. The cohort included patients with asthma, COPD, other lung diseases, and controls. A weighted random forest model was used to assess the impact of IOS parameters on BMI prediction accuracy, adjusting for imbalances in BMI and disease groups.

RESULTS: Obesity significantly affected IOS parameters, with R5-20, AX, and Fres emerging as key markers across all diagnostic groups. Elevated R5-20, AX and Fres values in obese patients, regardless of lung disease status, indicated increased small airway resistance and dysfunction. These IOS features demonstrated high predictive value in BMI-related outcomes, suggesting they capture airway impairments tied to obesity beyond conventional respiratory diagnoses.

CONCLUSIONS: IOS parameters, particularly R5-20, AX, and Fres are sensitive to obesity-associated airway changes and may serve as valuable markers for identifying respiratory impairment in obese individuals with or without lung disease.

Original languageEnglish
Article number218
JournalBMC Pulmonary Medicine
Volume25
Issue number1
ISSN1471-2466
DOIs
Publication statusPublished - 7 May 2025

Keywords

  • Body mass index
  • Impulse oscillometry
  • Obesity
  • Predictive modeling
  • Random forest analysis
  • Respiratory dysfunction

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