BACKGROUND: Measurement of lung volumes, especially residual volume and total lung capacity are essential for assessment of restrictive lung disorders. Information regarding normative prediction values for lung volumes as measured by body plethysmography is scarce, and plethysmographic parameters are believed to be poorly reproducible. In this study, we report a comprehensive set of predictive equations for static lung volumes from a general population sample of urban Iranians as measured by body plethysmography. METHODS: Standardized measurements were carried out on 1487 healthy nonsmoking volunteers (845 men and 642 women), aged six to 85 years, living in Isfahan, Iran. Nonlinear multiple regression analysis was used to calculate prediction equations based on subjects' ages and heights for the subdivisions of lung volumes [total lung capacity, functional residual capacity, residual volume, and residual volume/total lung capacity (%)], separately for the two genders. The derived equations were used to calculate prediction values for the subjects. The two sets of predicted and measured values were compared by paired sample t-test. RESULTS: Prediction equations based on a new nonlinear model, (alpha(1) x age + alpha(2) x age(n) + beta x height + c) which best fitted our data are presented. The measured and predicted values closely resemble and there is no significant difference between the two sets. Since increments in total lung capacity, functional residual capacity, and residual volume disclose air trapping within the lungs, their upper limits of normal are as important as the lower limits. So, we have presented both for the equations. CONCLUSION: Despite the usual beliefs we found rather reproducible prediction equations with high coefficient of determination (r2) and low standard error of estimate (SEE) in Iranian population.
BACKGROUND: Measurement of lung volumes, especially residual volume and total lung capacity are essential for assessment of restrictive lung disorders. Information regarding normative prediction values for lung volumes as measured by body plethysmography is scarce, and plethysmographic parameters are believed to be poorly reproducible. In this study, we report a comprehensive set of predictive equations for static lung volumes from a general population sample of urban Iranians as measured by body plethysmography. METHODS: Standardized measurements were carried out on 1487 healthy nonsmoking volunteers (845 men and 642 women), aged six to 85 years, living in Isfahan, Iran. Nonlinear multiple regression analysis was used to calculate prediction equations based on subjects' ages and heights for the subdivisions of lung volumes [total lung capacity, functional residual capacity, residual volume, and residual volume/total lung capacity (%)], separately for the two genders. The derived equations were used to calculate prediction values for the subjects. The two sets of predicted and measured values were compared by paired sample t-test. RESULTS: Prediction equations based on a new nonlinear model, (alpha(1) x age + alpha(2) x age(n) + beta x height + c) which best fitted our data are presented. The measured and predicted values closely resemble and there is no significant difference between the two sets. Since increments in total lung capacity, functional residual capacity, and residual volume disclose air trapping within the lungs, their upper limits of normal are as important as the lower limits. So, we have presented both for the equations. CONCLUSION: Despite the usual beliefs we found rather reproducible prediction equations with high coefficient of determination (r2) and low standard error of estimate (SEE) in Iranian population.
Authors: Mascha K Rochat; Ruediger P Laubender; Daniela Kuster; Otto Braendli; Alexander Moeller; Ulrich Mansmann; Erika von Mutius; Johannes Wildhaber Journal: PLoS One Date: 2013-01-08 Impact factor: 3.240