Prediction equations for pulmonary function values in healthy young Iranians aged 8–18 years

Abstract

Pulmonary function test (PFT) variables are dependent on height, age and gender. In addition, there is evidence of PFT variation in different ethnic groups. Prediction equations for PFT from a healthy, non-smoking, urban young population in the city of Mashhad (north-east Iran) have been derived. Prediction equations for normal pulmonary function were derived from 336 healthy, non-smoking subjects, including 187 males (height 103-188.5 cm) and 149 females (height 104-183 cm) aged 8-18 years. The subjects underwent measurement of spirometric flow and volume. The following variables were measured: FVC, FEV1, maximal mid-expiratory flow (MMEF), PEF, maximal expiratory flow at 75, 50 and 25% of the FVC (MEF75, MEF50, and MEF25, respectively), tidal volume (VT), inspiratory reserve volume (IRV), expiratory reserve volume (ERV), inspiratory capacity (IC), and vital capacity (VC). Regression analysis using height and age as independent variables was applied to provide predicted values for both genders. There were positive correlations for each pulmonary function variable with height and age. The largest positive correlations were found for FEV1 with height and age, in both genders. Comparison of PFT variables derived from the equations obtained in the present study showed significant differences to those calculated from several previously published equations (P < 0.001 for most variables). For example, the values of FVC and FEV1 derived from the equations obtained in the present study were 2.83 +/- 0.99 and 2.50 +/- 0.89 for males, and 2.41 +/- 0.54 and 2.19 +/- 0.53 for females, while the values derived from the equations of the European Community for Steel and Coal study were 3.12 +/- 1.06 and 2.62 +/- 0.89 for males and 2.79 +/- 0.67 and 3.35 +/- 0.57 for females, respectively. A set of PFT reference values and prediction equations for both genders has been derived using a relatively large, healthy, non-smoking Iranian young population, and has generated results that differ from several other prediction equations.