Sunil K Chhabra1, Rajeev Kumar, Vikas Mittal. 1. Department of Pulmonary Medicine, Vallabhbhai Patel Chest Institute, and *Department of Biostatistics and Medical Informatics, University College of Medical Sciences; Delhi, India. Correspondence to: Prof SK Chhabra, Department of Pulmonary Medicine, Vallabhbhai Patel Chest Institute, University of Delhi, Delhi 110 007, India. skchhabra@mailcity.com.
Abstract
OBJECTIVE: To develop prediction equations for spirometry for children from northern India using current international guidelines for standardization. DESIGN: Re-analysis of cross-sectional data from a single school. PARTICIPANTS: 670 normal children (age 6-17 y; 365 boys) of northern Indian parentage. METHODS: After screening for normal health, we carried out spirometry with recommended quality assurance according to current guidelines. We developed linear and nonlinear prediction equations using multiple regression analysis. We selected the final models on the basis of the highest coefficient of multiple determination (R2) and statistical validity. MAIN OUTCOME MEASURES: Spirometry parameters: FVC, FEV1, PEFR, FEF50, FEF75 and FEF25-75. RESULTS: The equations for the main parameters were as follows: Boys, Ln FVC = -1.687+0.016*height +0.022*age; Ln FEV1 = -1.748+0.015*height+0.031*age. Girls, Ln FVC = -9.989 +(2.018*Ln(height)) + (0.324*Ln(age)); Ln FEV1 = -10.055 +(1.990*Ln(height))+(0.358*Ln(age)). Nonlinear regression yielded substantially greater R2 values compared to linear models except for FEF50 for girls. Height and age were found to be the significant explanatory variables for all parameters on multiple regression with weight making no significant contribution. CONCLUSION: We developed prediction equations for spirometry for children from northern India. Nonlinear equations were superior to linear equations.
OBJECTIVE: To develop prediction equations for spirometry for children from northern India using current international guidelines for standardization. DESIGN: Re-analysis of cross-sectional data from a single school. PARTICIPANTS: 670 normal children (age 6-17 y; 365 boys) of northern Indian parentage. METHODS: After screening for normal health, we carried out spirometry with recommended quality assurance according to current guidelines. We developed linear and nonlinear prediction equations using multiple regression analysis. We selected the final models on the basis of the highest coefficient of multiple determination (R2) and statistical validity. MAIN OUTCOME MEASURES: Spirometry parameters: FVC, FEV1, PEFR, FEF50, FEF75 and FEF25-75. RESULTS: The equations for the main parameters were as follows: Boys, Ln FVC = -1.687+0.016*height +0.022*age; Ln FEV1 = -1.748+0.015*height+0.031*age. Girls, Ln FVC = -9.989 +(2.018*Ln(height)) + (0.324*Ln(age)); Ln FEV1 = -10.055 +(1.990*Ln(height))+(0.358*Ln(age)). Nonlinear regression yielded substantially greater R2 values compared to linear models except for FEF50 for girls. Height and age were found to be the significant explanatory variables for all parameters on multiple regression with weight making no significant contribution. CONCLUSION: We developed prediction equations for spirometry for children from northern India. Nonlinear equations were superior to linear equations.
Authors: Gerald Stanley Zavorsky; Ahmad Saleh Almamary; Mobarak Khalid Alqahtani; Shi Huh Samuel Shan; Douglas Shawn Gardenhire Journal: BMC Pulm Med Date: 2021-07-13 Impact factor: 3.317