Prediction model for peak expiratory flow in North Indian population

Area of Science:

• Respiratory Medicine
• Public Health
• Biostatistics

Background:

• Peak expiratory flow rate (PEFR) is a key indicator of lung function.
• Establishing population-specific prediction models is crucial for accurate clinical assessment.
• North Indian population data for PEFR prediction models were previously limited.

Purpose of the Study:

• To develop and validate a predictive model for PEFR in a healthy North Indian population.
• To assess age and sex-specific differences in PEFR.
• To provide a tool for estimating normal PEFR values in this demographic.

Main Methods:

• A cross-sectional study involving 897 healthy non-smokers (males and females, aged 10-60 years).
• PEFR was measured using a Mini Wrights peak flow meter.
• Regression analysis was employed to develop predictive models using age, height, and weight.

Main Results:

• Highest PEFR readings were observed in males aged 20-24 and females aged 25-29.
• Distinct prediction models were established for males and females aged 19-60, with a common model for ages 10-18.
• The models demonstrated high predictive power, explaining 80% (males) and 82% (females) of the variation in PEFR.

Conclusions:

• A validated PEFR prediction model for the North Indian population (ages 10-60) was developed.
• Sex-specific models are necessary for adults (19-60 years), while a unified model is suitable for adolescents (10-18 years).
• These models can aid in the clinical assessment of respiratory health in North India.