European Journal of Cardiovascular Medicine

Air pollution is an escalating global health crisis, particularly in low- and middle-income countries where urbanization and industrial activities continue to surge without proportional environmental safeguards [1]. Among the various health effects of air pollution, respiratory morbidity in children has emerged as a critical concern due to their heightened vulnerability. Anatomically and physiologically, children have narrower airways, higher minute ventilation per body weight, and immature detoxification systems, making them more susceptible to airborne toxicants [2]. Their frequent outdoor activities and time spent in school environments further increase the risk of exposure.

The Air Quality Index (AQI), a composite metric incorporating concentrations of major pollutants such as PM₂.₅, PM₁₀, NO₂, SO₂, CO, and O₃, has been widely adopted to monitor and communicate ambient air quality [3]. Numerous studies have highlighted a direct relationship between elevated AQI levels and acute respiratory symptoms, exacerbation of asthma, and reduced lung growth trajectories in children [4]. Long-term exposure to air pollution has also been associated with impaired pulmonary function and structural lung changes [5].

Spirometry remains the most reliable and widely used method for non-invasive assessment of lung function. Parameters such as Forced Vital Capacity (FVC), Forced Expiratory Volume in 1 second (FEV₁), and Peak Expiratory Flow Rate (PEFR) serve as objective indicators of airway health [6]. Variations in these spirometric indices have been correlated with air pollutant levels in multiple epidemiological studies, particularly in pediatric populations residing in polluted urban settings [7].

India, especially in its rapidly growing southern states, is experiencing a marked increase in vehicular emissions, biomass combustion, and industrial pollutants. While several national surveys have documented AQI trends across metropolitan regions, there remains a lack of localized data linking these trends to measurable health outcomes in children [8]. Schoolchildren represent a sentinel population for environmental exposure studies due to the cumulative and prolonged nature of their exposure during critical periods of lung development.

Despite global awareness, there exists a considerable gap in empirical data linking region-specific AQI patterns to functional respiratory impairment in Indian children. Moreover, most existing literature fails to integrate real-time air quality data with standardized spirometric evaluations, especially in rural and peri-urban areas [9]. Addressing this gap is essential for informed public health interventions and policy frameworks that protect pediatric health.

This study was undertaken to evaluate the relationship between ambient air quality and lung function among schoolchildren in the coastal town of Muttum, Tamil Nadu.

Study Design and Setting

A cross-sectional observational study was conducted by the Department of Community Medicine at Kanyakumari Medical Mission Research Centre, Muttum, Tamil Nadu, over a one-year period from January 2024 to December 2024. The study involved schoolchildren from three co-educational institutions within a 10-kilometer radius, selected to represent varying levels of air pollution exposure based on proximity to major roads, industrial zones, and green belts.

Study Population and Sample Size

A total of 400 schoolchildren aged between 8 and 14 years were recruited using stratified random sampling. Inclusion criteria included children attending regular school hours, with no history of chronic respiratory illness, congenital cardiopulmonary anomalies, or recent acute infections within two weeks prior to spirometry. Written informed consent was obtained from parents or guardians, along with verbal assent from the participating children.

Exposure Assessment

Ambient air quality data were collected daily from Tamil Nadu Pollution Control Board (TNPCB) air monitoring stations located nearest to each school. AQI was calculated based on concentrations of PM₂.₅, PM₁₀, SO₂, NO₂, and O₃, using the Central Pollution Control Board (CPCB) formula. Each child’s residence and school were geocoded and classified into three exposure categories:

• Good air quality (AQI < 50)
• Moderate air quality (AQI 51–100)
• Unhealthy air quality (AQI > 100)

Exposure levels were averaged over the previous 30 days prior to lung function assessment.

Lung Function Assessment

Spirometry was performed by trained technicians using a calibrated portable spirometer (MIR Spirolab III) following American Thoracic Society (ATS) guidelines. Parameters recorded included Forced Vital Capacity (FVC), Forced Expiratory Volume in 1 second (FEV₁), FEV₁/FVC ratio, and Peak Expiratory Flow Rate (PEFR). Each child performed three acceptable maneuvers, and the highest value was recorded for analysis. Pre-bronchodilator values were used.

Data Collection and Quality Control

A pre-tested questionnaire was administered to collect demographic data (age, gender, height, weight), residential characteristics (urban/rural), and history of environmental exposures (passive smoking, biomass use). Anthropometric measurements were obtained using standardized instruments. All data were anonymized and entered into a password-protected database.

Statistical Analysis

Data were analyzed using SPSS version 26. Continuous variables were expressed as mean ± standard deviation, and categorical variables as frequencies and percentages. Comparisons between AQI exposure groups were made using one-way ANOVA for continuous variables and Chi-square test for categorical data. Pearson’s correlation was applied to assess relationships between AQI levels and lung function indices. Multiple linear regression was used to adjust for potential confounders such as age, sex, BMI, and passive smoke exposure. A p-value of <0.05 was considered statistically significant.

Ethical Considerations

The study protocol was approved by the Institutional Ethics Committee. Confidentiality was maintained throughout the study, and participation was entirely voluntary

Table 1: Demographic Characteristics of Study Participants (n = 400)

Table 2: Lung Function Parameters Across AQI Exposure Categories

 Table 3: Comparative Analysis of Lung Function by AQI Exposure (ANOVA)

Table 4: Correlation Between AQI and Lung Function Parameters (n = 400)

Table 5: Multivariate Linear Regression Analysis (Adjusted for Age, Gender, BMI, Smoke Exposure)

Fig 1: Lung function parameters by AQI exposure category

The data demonstrate a clear inverse relationship between air pollution levels and lung function among schoolchildren. As presented in Table 2, children residing in areas with good air quality (AQI < 50) had the highest mean FEV₁ (1.72 ± 0.37 L), FVC (2.00 ± 0.41 L), and PEFR (242.3 ± 40.8 L/min). In contrast, those exposed to unhealthy air (AQI > 100) recorded significantly reduced values for FEV₁ (1.36 ± 0.42 L), FVC (1.61 ± 0.44 L), and PEFR (190.6 ± 45.2 L/min), indicating compromised pulmonary function.

Statistical analysis using one-way ANOVA (Table 3) revealed highly significant differences across AQI categories for all three lung function parameters: FEV₁ (F = 12.65, p < 0.001), FVC (F = 10.92, p < 0.001), and PEFR (F = 15.23, p < 0.001), confirming that declining air quality was associated with reduced lung performance.

Correlation analysis (Table 4) demonstrated a moderate but statistically significant negative relationship between AQI and FEV₁ (r = -0.47, p < 0.001), FVC (r = -0.41, p < 0.001), and PEFR (r = -0.52, p < 0.001). These values substantiate the linear trend observed in the graphical representation and reinforce the detrimental effect of air pollution on respiratory function.

Finally, the multivariate regression model (Table 5) showed that AQI independently predicted declines in all lung function parameters after adjusting for age, sex, BMI, and exposure to passive smoking. The beta coefficient for AQI was -0.012 for FEV₁ (95% CI: -0.016 to -0.008), -0.011 for FVC (95% CI: -0.015 to -0.007), and -0.960 for PEFR (95% CI: -1.23 to -0.69), all with p-values < 0.001, confirming a statistically robust and clinically meaningful impact.

Air pollution poses a significant threat to respiratory health, especially among children whose lungs are still in the developmental phase. This study evaluated the association between ambient air quality and spirometry-based lung function in school-aged children residing in a coastal region of southern India. The findings demonstrate a consistent and statistically significant reduction in pulmonary function among children exposed to higher AQI levels, indicating a pressing public health concern.

The rationale for this investigation was grounded in the growing evidence that pediatric populations are disproportionately affected by environmental pollutants due to their immature immune systems, increased respiratory rate, and higher outdoor exposure time [10]. Previous studies conducted in highly urbanized Indian cities have extensively reported similar associations, but evidence from semi-urban or rural coastal settings remains limited. By incorporating real-time AQI data and spirometry, this study addressed a regional evidence gap.

The findings align closely with those of Gauderman et al., who observed significantly diminished lung function growth among children exposed to NO₂ and PM₂.₅ in southern California [11]. Comparable results were found in an Indian cohort study by Patra et al., where elevated PM₁₀ levels correlated negatively with FEV₁ and PEFR in schoolchildren in Bhubaneswar [12]. Our results further validate these patterns, with children in the ‘Unhealthy’ AQI group showing a mean FEV₁ of only 1.36 ± 0.42 L compared to 1.72 ± 0.37 L in the ‘Good’ AQI group.

Beyond confirming existing trends, this study's multivariate regression analysis contributes novel insight by quantifying the specific effect size of AQI on lung indices after adjusting for confounders — a methodological approach rarely emphasized in Indian pediatric literature [13]. The observed beta coefficient of –0.012 for FEV₁, for instance, underscores a meaningful decrement in lung function for every unit rise in AQI, a finding with direct public health implications.

Clinically, the reduced FEV₁ and PEFR values point toward subclinical airway inflammation or obstruction in apparently healthy children. These early functional impairments could escalate into chronic respiratory conditions such as asthma or COPD if sustained exposure continues [14]. The implications are especially severe in light of projections that ambient air pollution will be a top contributor to pediatric disability-adjusted life years in South Asia by 2030 [15].

Nonetheless, certain limitations must be acknowledged. The cross-sectional design restricts causal inference. Indoor air pollutants and allergen exposures were not separately quantified. Additionally, longitudinal spirometry and seasonal AQI variations were beyond the current scope. Future studies should adopt cohort-based designs and explore interventions like classroom-based air purifiers or mask usage.

Despite these constraints, the present study highlights a crucial pediatric health risk and strengthens the call for enforcing region-specific environmental regulations and school-centered preventive strategies.

This cross-sectional study underscores a significant inverse relationship between ambient air pollution and pulmonary function among school-aged children in southern India. Children exposed to higher AQI levels exhibited markedly reduced FEV₁, FVC, and PEFR values, with statistical significance confirmed through ANOVA, correlation, and regression analyses. These findings highlight the urgent need for targeted public health policies, environmental regulations, and school-level interventions to mitigate the long-term respiratory effects of air pollution in vulnerable pediatric populations. Strengthening air quality surveillance and promoting awareness among caregivers and educators can play a crucial role in reducing future respiratory morbidity. Further longitudinal and intervention-based studies are recommended to establish causality and evaluate the efficacy of protective strategies.

Acknowledgement

The authors express sincere gratitude to the school administrations and the participating children and parents for their cooperation.

Conflicts of Interest

The authors declare no conflicts of interest.

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