Related Experiment Video
Updated: May 20, 2026

Employing the Forced Oscillation Technique for the Assessment of Respiratory Mechanics in Adults
Published on: February 9, 2022
Regression equations for spirometry in children aged 6 to 17 years in Delhi region
S K Chhabra1, V K Vijayan, M Rahman
1Departments of Cardio-respiratory Physiology, Viswanathan Chest Hospital, Vallabhbhai Patel Chest Institute, University of Delhi, Delhi, India. skchhabra@mailcity.com
Background:
Most of the studies carried out in India to develop regression equations for spirometry in children are now several years-to-decades old and had used equipment and measurement protocols that have since changed. Prediction equations using the current standardisation protocols for spirometry are not available. The lung health of the population may have changed too.
Objective:
To develop regression equations for spirometry for children aged 6 to 17 years of north Indian origin in Delhi region.
Methods:
School children of north Indian origin, as determined by mother tongue and parentage, aged 6 to 17 years were screened by a health questionnaire and physical examination and those found "normal" underwent spirometry according to the standardised procedure recommended by the American Thoracic Society/European Respiratory Society (ATS/ERS) task force in 2005. Pearson's correlation analysis was carried out to identify the predictor variables for spirometric parameters. Prediction equations were developed using the multiple linear regression procedure. The independent variables were entered in sequence of height, age and weight. R2, adjusted R2 and R2 change, standard errors of the estimate (SEE), and estimates of regression coefficients were obtained and the goodness of fit was examined.
Results:
Data was obtained in 365 boys and 305 girls. Forced vital capacity (FVC), forced expiratory volume in one second (FEV1) peak expiratory flow rate (PEFR), forced expiratory flow rate at 50% and 75% exhalation of vial capacity (F50 and F75) and mean forced expiratory flow rate over the middle 50% of the vital capacity (F25-75) showed moderate to strong correlations with age, height and weight in both boys and girls. In both genders, the equations explained very high variability of FVC, FEV1 and PEFR as shown by the R2 values. The explained variability for flow rates was lesser, with that for F75 being the least.
Conclusions:
Regression equations for spirometry variables for children of north Indian origin in Delhi region have been developed. These represent the first such effort from India after the publication of the ATS/ERS task force 2005 guidelines on standardisation of spirometry.
Related Concept Videos
Pulmonary Function Tests
Pulmonary Function Tests are crucial diagnostic tools for assessing respiratory function, particularly in patients with chronic respiratory disorders. They comprehensively evaluate lung volumes, ventilatory function, breathing mechanics, diffusion, and gas exchange. These tests help diagnose pulmonary diseases and play a significant role in monitoring disease progression, evaluating disability, and assessing response to therapy.
PFTs involve using a spirometer, a...
Regression Analysis
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
Chronic Obstructive Pulmonary Disease-IV: Assessement and Diagnostic Studies
Medical History
Factors Affecting Pulmonary Ventilation
Alveolar Surface Tension
The alveolar fluid lines the luminal surface of the alveoli and exerts a force called surface tension. This force is caused by the polar water molecules in the liquid being more strongly attracted to each...
Respiratory Volumes and Capacities I
Respiratory Volumes
Tidal Volume (TV) Tidal volume (TV) is the air inhaled or exhaled in a...

