Lung function parameters improve prediction of VO2peak in an elderly population: The Generation 100 study
Author(s) -
Erlend Hassel,
Dorthe Stensvold,
Thomas Halvorsen,
Ulrik Wisløff,
Arnulf Langhammer,
Sigurd Steinshamn
Publication year - 2017
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0174058
Subject(s) - spirometry , diffusing capacity , medicine , population , linear regression , vital capacity , pulmonary function testing , cardiology , lung volumes , hemoglobin , physical therapy , lung , statistics , mathematics , lung function , environmental health , asthma
Peak oxygen uptake (VO 2peak ) is an indicator of cardiovascular health and a useful tool for risk stratification. Direct measurement of VO 2peak is resource-demanding and may be contraindicated. There exist several non-exercise models to estimate VO 2peak that utilize easily obtainable health parameters, but none of them includes lung function measures or hemoglobin concentrations. We aimed to test whether addition of these parameters could improve prediction of VO 2peak compared to an established model that includes age, waist circumference, self-reported physical activity and resting heart rate. We included 1431 subjects aged 69-77 years that completed a laboratory test of VO 2peak , spirometry, and a gas diffusion test. Prediction models for VO 2peak were developed with multiple linear regression, and goodness of fit was evaluated. Forced expiratory volume in one second (FEV 1 ), diffusing capacity of the lung for carbon monoxide and blood hemoglobin concentration significantly improved the ability of the established model to predict VO 2peak . The explained variance of the model increased from 31% to 48% for men and from 32% to 38% for women (p<0.001). FEV 1 , diffusing capacity of the lungs for carbon monoxide and hemoglobin concentration substantially improved the accuracy of VO 2peak prediction when added to an established model in an elderly population.
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