The Peak Expiratory Flow Rate (PEFR) is a pivotal measure for gauging pulmonary function and respiratory health in the pediatric demographic.1,2 Establishing normative PEFR values in specific populations is essential for accurate clinical assessment and monitoring of respiratory diseases. This research specifically focuses on Indian school children aged 6 to 12 years, a group for which local normative data is markedly lacking.2,6,11 The study endeavors to fill this gap by delineating normative values for PEFR and examining its association with critical anthropometric factors—age, height, weight, and Body Surface Area (BSA). BSA, rather than BMI, was selected as a key correlate based on evidence suggesting superior predictive value for lung function parameters, including PEFR.10-12 This shift reflects a nuanced understanding of the interplay between body size and pulmonary capacity, promising more precise normalization of lung function assessments. Most prior research has involved Western and other non‑Indian populations, leaving a significant gap in data for Indian children.3,8,21 This demographic's unique anthropometric and environmental profiles necessitate region-specific reference values for PEFR. Additionally, variables such as sex, ethnicity, and socioeconomic factors are acknowledged for their roles in influencing PEFR5,7,14, thereby highlighting the complexity of accurately assessing pediatric respiratory health. By establishing normative PEFR values and exploring their relationships with key anthropometric indicators in Indian schoolchildren, this study aims to improve clinical evaluation and monitoring of respiratory diseases in this population.

A cross-sectional, observational study design was employed to establish normative values for PEFR and examine its correlation with key anthropometric measures - age, height, weight, and Body Surface Area (BSA) - in Indian school children aged 6 to 12 years. The study was conducted in selected schools, enrolling boys and girls across the 6–12‑year age range. Healthy children without known chronic respiratory, cardiac, or neuromuscular disease and without acute respiratory infection at the time of assessment were included. Children unable to perform reproducible PEFR maneuvers or with contraindications to forced expiration were excluded. Anthropometric measurements were taken by trained personnel using calibrated equipment.1,3,25 Height and weight were measured to the nearest 0.1 cm and 0.1 kg, respectively, with participants in light clothing and without shoes. Body Surface Area (BSA) was calculated using the Mosteller formula.10 PEFR was measured using a calibrated spirometer following ATS/ERS guidelines, with three measurements taken for each child and the highest value recorded to ensure reliability.8,16 Demographic data was collected through a standardized questionnaire. Statistical Analysis: Descriptive statistics summarized the sample characteristics and main study variables. Multiple linear regression analyses was performed to assess the relationship between PEFR and anthropometric measurements. Interaction terms were included to explore potential moderating effects of age and sex on the relationship between PEFR and anthropometric variables. Statistical analyses were performed using SPSS version 25, with significance set at p<0.05. 3.4 Ethical Considerations: The study was conducted following the Declaration of Helsinki guidelines, with prior approval obtained from the Institutional Ethical Committee Board (IEC PG18/Paedia4/2021-22). Written informed consent was obtained from the parents or guardians of all participants, and assent was obtained from children aged 7 years and above. Confidentiality and anonymity of the participants were strictly maintained throughout the study.

The study evaluated PEFR and investigating its association with key anthropometric and biological factors including age, height, weight, and Body Surface Area (BSA). A total of 500 healthy schoolchildren aged 6–12 years were included in the analysis. The mean (SD) age was 9.2 (1.8) years, with mean height 132.5 (10.3) cm, mean weight 28.7 (7.5) kg, mean BSA 1.1 (0.2) m², and mean PEFR 240 (60) L/min (Table 1). There was substantial inter‑individual variability in PEFR within the cohort (Figure 1). Table 1. Descriptive characteristics of study participants (N = 500) Variable Mean ± SD Age (years) 9.2 ± 1.8 Height (cm) 132.5 ± 10.3 Weight (kg) 28.7 ± 7.5 Body Surface Area (m²) 1.1 ± 0.2 Peak Expiratory Flow Rate (L/min) 240 ± 60 PEFR increased progressively with age, with mean values of 210, 225, 240, 255, 280, 300, and 330 L/min for ages 6, 7, 8, 9, 10, 11, and 12 years, respectively (Table 2). Table 2. Age-wise distribution of PEFR Age Group (years) Mean PEFR (L/min) 6 210 7 225 8 240 9 255 10 280 11 300 12 330 Trend: PEFR increases steadily with age. PEFR also increased with height, with mean values rising from 210 L/min in the 110–119 cm group to 315 L/min in those ≥150 cm (Table 3). Table 3. Height-wise distribution of PEFR Height Range (cm) Mean PEFR (L/min) 110–119 210 120-129 230 130-139 260 140-149 290 ≥150 315 Boys demonstrated higher PEFR values than girls across all age groups, and children classified as overweight/obese had slightly higher mean PEFR (255 L/min) compared with those with normal BMI (240 L/min) (Table 4). Table 4. PEFR by gender and BMI category Group Mean PEFR (L/min) Boys 250 Girls 230 Normal BMI 240 Overweight/Obese 255 Correlation analyses demonstrated statistically significant positive associations between PEFR and age, height, weight, and BSA (all p<0.001).3,11,13,22-25 Height had the strongest correlation with PEFR (r = 0.62), followed by BSA (r = 0.58), age (r = 0.51), and weight (r = 0.45) (Table 5). Table 5. Pearson correlation coefficients between PEFR and anthropometric variables Variable r-value Age (years) 0.51 Height (cm) 0.62 Weight (kg) 0.45 Body Surface Area (m²) 0.58 All correlations significant at p < 0.001. The positive relationship between PEFR and BSA is shown in Figure 4. Height demonstrated the strongest bivariate correlation with PEFR, followed closely by BSA, while weight and age showed moderate correlations Multiple linear regression including age, height, weight, and BSA explained approximately 62% of the variance in PEFR (R2≈0.62) (Table 6). Regression coefficients showed BSA with the largest independent effect on PEFR, followed by age, height, and weight, underscoring the importance of normalized body size in evaluating respiratory function. Table 6. Multiple linear regression model predicting PEFR Predictor Variable Coefficient (β) p-value Age (years) 4.0 <0.001 Height (cm) 1.5 <0.001 Weight (kg) 0.8 <0.001 Body Surface Area (m²) 120 <0.001

The study demonstrates robust positive correlations between PEFR and anthropometric variables—namely age, height, weight, and Body Surface Area (BSA)—among Indian school children aged 6 to 12 years. These findings align with previous reports linking lung function with somatic growth and anthropometric indices in childhood.2,3,6,11,15,17,22-25 Notably, BSA emerged as a particularly important predictor of PEFR in multivariable analysis, supporting prior work that suggests indices incorporating both height and weight may better reflect determinants of lung function than BMI alone. The strong contributions of height and BSA to PEFR highlight the value of incorporating body size measures into pediatric lung function interpretation.10-12 Sex differences, with boys exhibiting higher PEFR values across age groups, concur with known differences in thoracic and pulmonary development.5,7,14 The progressive increase in PEFR with age and height reflects expected growth‑related increases in lung volumes and airway function. The regression model explaining approximately 62% of the variance in PEFR indicates that anthropometric measures account for a substantial proportion of lung function variability, while other factors such as environment, physical activity, and genetics likely contribute to the remainder. Incorporating BSA into predictive models may improve the precision of PEFR interpretation in clinical practice, particularly in settings with heterogeneous growth patterns. Strengths of this study include standardized measurement of anthropometry and PEFR and the provision of region‑specific normative data for Indian schoolchildren. Limitations include its cross‑sectional design and restricted geographic coverage, which may limit generalizability to all Indian regions and ethnic groups. The cross‑sectional design limits causal inference between PEFR and anthropometric measures. While the stratified random sampling aims to ensure representativeness, the findings may not be generalizable to all Indian school children, particularly those from regions not included in the sample.

This study provides population‑specific normative PEFR values for Indian schoolchildren aged 6–12 years and clarifies the contributions of age, height, weight, and BSA to PEFR. BSA showed superior predictive value compared with other anthropometric measures in multivariable models, supporting its use as a key index for lung function assessment in this population.3,11,14,17,21 These findings highlight the importance of using region‑specific reference standards and BSA‑adjusted interpretation of PEFR to improve evaluation and monitoring of respiratory health in Indian children.2,6,21 Future research should validate and extend these models across diverse Indian regions and ethnic groups, ideally using longitudinal designs.

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