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Updated: Sep 30, 2026

Investigation into Deep Breathing through Measurement of Ventilatory Parameters and Observation of Breathing Patterns
Published on: September 16, 2019
The impact of body-weight components on forced spirometry in healthy italians
E I Mohamed1, C Maiolo, L Iacopino
1Division of Human Physiology, University of Rome Tor Vergata, Via Montpellier 1, Italy.
Abstract:
Many studies have investigated lung function in relation to age and height among Caucasians, however, most of these studies did not consider the individual components of body weight. The objective of the present study was to study the effect of body weight components [bone-free lean body mass (BF-LBM), bone mineral content (BMC), and fat mass (FM)] measured by dual x-ray absorptiometry (DXA) on the lung-function variables (FVC, FEV1, and PEF) and to derive prediction equations for these variables in healthy adult Italians. Dynamic spirometric tests and body composition analysis by DXA were performed on 58 nonsmoking males, mean age ( +/-SE) 26.72 +/- 1.98 years and BMI 25.51 +/- 0.64 kg/m2, and 60 nonsmoking females matched for age and BMI (29.61 +/- 1.65 years and 26.45 +/- 1.05 kg/m2, respectively). Bivariate linear regression analysis showed the variables age, height, BF-LBM, BMC, and the interaction term BF-LBM*Height, but not weight and FM, to correlate significantly with lung-function variables for males and for females separately. Multiple linear regression analysis showed that sex, age, height, and BF-LBM*Height were significantly associated with FVC, FEV1, and PEF. The prediction equations developed for FVC, FEV1, and PEF on the basis of the independent variables i.e. sex, age (y), height (m), and BF-LBM*Height (kg. m) had a significantly higher cumulative correlation coefficient and a lower SEE compared with those based on age and height only. The present report suggests that the BF-LBM, expressed independently from height, can be considered for predicting lung-function variables.
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