Introduction

Recent epidemiologic studies have demonstrated that environmental factors play a significant role in the development of various respiratory diseases. The complex mixture of various gases, hydrocarbons and heavy metals in air aggravates pulmonary diseases. The role of ambient air pollutants in the development of symptoms of respiratory illness has been clearly illustrated by many studies (Brauer et al. 2002; Brunekreef et al. 1997; Ciccone et al. 1998; Gehring et al. 2002). There is an existence of a casual relationship between pollutant concentration and respiratory health that has raised concerns regarding public health (Hirsch et al. 1999; Van Vliet et al. 1997; Kramer et al. 2000; Livingstone et al. 1996; Oosterlee et al. 1996).

Respiratory illness is one of the major problem affecting young children. Acute respiratory infections (ARI), especially lower respiratory tract infections (LRTI), are the leading cause of death among children under 5 years of age and are estimated to be responsible for 1.9 million to 2.2 million childhood deaths globally (Jamison et al. 2006). The prevalence of respiratory illness among children has increased; hence, it has become an important cause of childhood morbidity and mortality in India (WHO 2005).

Many studies has shown that there is a relationship between exposure to ambient air pollutants and adverse effects on pulmonary health (Barraza-Villarreal et al. 2008; Gotschi et al. 2008; Liu et al. 2009; Chen et al. 2011). There is a causal association for traffic exposure and exacerbations of asthma in children (Health Effects Institute 2010). Hence, the respiratory health of children is crucial as damage to lungs during growth phase can be permanent.

Studies and research depicting a relationship between air pollution and pulmonary health of children are sparse in third world countries like India. The Indian capital, Delhi, is the largest metropolitan city in India with second highest population and a density of 9,340 persons/km2 (Ministry of Home Affairs 2011). Rapid urbanisation has lead to drastic escalation in number of transport vehicles which in turn has added to emission of higher amount of greenhouse gases and other air pollutants. Air pollution data obtained from the monitoring stations suggest that pollutant levels vary significantly between industrial region, residential area and commercial region, and this difference is ultimately expected to alter lung function of children living in the respective areas. Comparative study of population with same ethnic background living in areas with different land use pattern has revealed important environmental risk factors, especially ambient air pollution levels, which may play an important role in the development of asthma symptoms (Peters et al. 1999; Zhang et al. 2002). The varying composition of air pollutants in specific areas may gravely affect the pulmonary health of children. Given these backgrounds, present study was undertaken to understand the association of air pollution with respiratory health of school children residing in different locations in Delhi.

Methodology

Study design

The study involved assessment of air quality inside classrooms of the selected schools for major pollutants, i.e. nitrogen oxides (NOX), sulphur dioxide (SO2) and particulate matter of size ≤10 μM (PM10). Ambient air pollution data for these pollutants was obtained from the National Ambient Air Quality Monitoring (NAAQM) stations of Central Pollution Control Board (CPCB), Delhi. Respiratory effects in children were assessed using a new questionnaire designed based on the validated International Study of Asthma and Allergies in Childhood (ISAAC) questionnaire (Asher et al. 1995) for wheezing-related questions and the American Thoracic Society questionnaire (ATS-DLD-78-C) for other respiratory conditions (Hwang and Lee 2010). Further, lung function test was performed to support and validate the questionnaire data.

Site selection

Delhi, located in north India, is approximately 715 ft above the mean sea level. High concentration of pollutants is majorly contributed by vehicular activities, industries, thermal power plant and frequent dust storms (Ministry of Environment & Forests 1997). It is a rapidly growing centre of industry, trade and commerce. State Government has introduced various measures for the control of vehicular and manufacturing industry emissions. Even after introduction of these measures, the region’s air quality does not comply with the National Ambient Air Quality Standards (NAAQS) (Kandlikar 2007). Hence, three major locations in Delhi were selected for survey which were categorised on the basis of land usage pattern, i.e. Mayapuri (MP), an industrial area, Sarojini nagar (SN), a residential area, and Chandni Chowk (CC), a commercial area. Mayapuri has the highest cluster of small-scale industries in India (Rawat et al. 2003). The place is a combination of heavy metal factories, residential flats and automobile service stations. Sarojini nagar is one of the most developed and clean residential areas in Delhi with light traffic on roads and greener surroundings. Chandni Chowk is one of India’s largest wholesale markets. High levels of human activity and congested roads significantly contribute to pollutant levels in the area. Schools chosen for survey in these areas were financed by government bodies and situated within an aerial distance of 1 km from the NAAQM stations.

Indoor and ambient air pollution monitoring

The indoor sampling of NOX and SO2 was carried out for 6 h using the handy sampler for EnviroTech, Model APM 821 and estimated by standard laboratory chemical analysis method, while PM10 concentration was monitored using Environmental dust monitor (GRIMM make, Model 1.107). The sampling was done for an average of 4 days in each area. Also, the NAAQM data of outdoor concentrations of NOX, SO2 and PM10 for the same days were used for analysis.

Subject selection

Survey was approved by Directorate of Education, Delhi, and written consent was obtained from the school authorities. Students of age 12–16 years were invited to participate in the study. Majority of them were residing within 2-km radius of the schools and were belonging to low-income socio-economic groups. The survey questionnaire had socio-demographic information and respiratory health assessment section (Hansel et al. 2008; Langkulsen et al. 2006; Nishima et al. 2009). The first section included specific questions on age, sex, place of birth, number of years lived in current residence, types and characteristics of house, no. of persons residing in the house, distance of house from the main road, traffic load on the road, fuel used for cooking and heating, parent’s occupation, smoking status of parents and other household members, history of asthma in family and possession of pets. Respiratory health status of children was assessed from the well-validated international questionnaires mentioned earlier. Their awareness about allergy and asthma in general was also determined by personal interaction. Students were helped to complete the questionnaire which was followed by lung function test. The responses of questionnaire were recorded according to a standardised code and file structure.

Lung function test

Height and weight of children were measured and recorded according to the standard WHO protocols (WHO 1995). Lung function test was performed using a spirometer (Winspiro PRO ver.3.6.2 Medical International Research, Italy). Three reproducible and technically acceptable measurements of vital capacity (VC), forced vital capacity (FVC) and maximum voluntary ventilation (MVV) were made according to the guidelines of ATS (Miller et al. 2005). Highest values of the FEV1 by VC ratio were selected, and accordingly, the subject’s pulmonary health was categorised as severe obstruction or mild obstruction according to the ATS-GOLD definition (FEV (1)/FVC <0.70) (David et al. 2002).

Data analysis

The socio-demographic characteristics from questionnaire data and the overall lung function test results were examined using descriptive statistics. Chi-squared tests and analysis of variance (ANOVA) were used to compare the variables of different study populations of MP, CC and SN areas. SPSS 16, IBM Corporation software, was used to calculate anthropometric indicators of children. Using the SN area population as the reference group, odds ratios (OR) and 95 % confidence intervals (CI) were computed for selected respiratory symptoms/conditions. Potential confounders considered were sex, age, presence of pets in the house, overcrowding, distance of road from home, type of home, cooking fuel (wood, coal or kerosene) and presence of smokers in the house. A descendant stepwise logistic regression adjusted over potential confounding variables was carried out for the multivariate analysis.

Results

Indoor-outdoor air quality monitoring results

Indoor-outdoor PM monitoring data indicated the dominance of coarse particles, i.e. PM10 fraction in all schools (Table 1). The highest mean indoor and outdoor PM10 concentration was observed in CC schools, i.e. 815 ± 354.45 and 337 ± 85 μg/m3, respectively, which was high above the permissible limits (100 μg/m3) of the NAAQS, set by CPCB, Government of India. Indoor and outdoor mean PM10 concentrations at schools of MP and SN area were found to be 694.6 ± 322.9 and 274 ± 78 μg/m3 and 534.3 ± 94.22 and 197 ± 48 μg/m3, respectively, which was also higher than permitted levels. However, the indoor and outdoor mean levels of SO2 and NOX were observed below the permissible limits of 80 μg/m3 of in all three areas (Table 1).

Table 1 Distribution of average air pollutant concentrations (μg/m3) of three areas of Delhi
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Questionnaire survey results

Demographic characteristics

A total of 1,814 children participated in the survey. Median age was 15 years, and male to female ratio was 1.2. The socio-demographic characteristics of children in all three panels were almost similar. Most of the children (CC 78.3 %, SN 79.3 %, MP 69 %) were living in low-income group (LIG) houses. Overcrowding was a common aspect, but it was significantly high in CC area with 65.4 % children reporting that they lived with more than five members in a room. Majority of children (89.7 %) in CC reported living in their house for >10 years, while only 51.7 % in SN and 52.5 % in MP areas reported the same. Liquefied petroleum gas (LPG) was commonly used for cooking along with <5 % use of unclean fuels like kerosene and biomass. Exposure to second hand smoking (SHS) was reported in all three areas with highest percentage in CC panel of student (48.8 %). Most of the children (92.4 %) were living at a distance of <500 m, while the remaining 7.6 % were living within 1-km distance from the main traffic roads. Pets were reported living inside the house of 14.7 % children (Table 2).

Table 2 Socio-demographic characteristics of the children from three areas of Delhi
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Health characteristics—questionnaire based

The general health status of children which includes their body mass index (BMI) and respiratory health was recorded. The student panel of MP area showed highest percentage of lower BMI cases (41 %) as compared to 26 and 24 % respectively in CC and SN areas (Table 3). Questionnaire results regarding respiratory health indicated that many children in all three areas had a tendency to develop frequent cold and cough (more than four times in a year). The percentage occurrence of frequent cold and cough was highest in CC, i.e. 29.6 %, followed by MP (15.2 %) and least in SN area (14.7 %). Similarly, other symptoms of respiratory illnesses, i.e. “wheezing or whistling in the chest” with or without activity and “night cough and Phlegm”, were also reported highest (20.8 and 29 % respectively), in children of CC area (Table 4). The survey results indicated that chances of developing respiratory illnesses were more in children staying in CC area because of the large commercial activities, heavy traffic conditions and overcrowded homes. To strengthen and validate the findings of questionnaire survey, lung function test was performed on all children who completed the questionnaires.

Table 3 Health Status of children with BMI index with age
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Table 4 The selected respiratory symptoms of the study population
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Spirometry results

The lung function test results of children reveal that the percentage of severe obstruction cases was highest (32 %) in MP area compared to CC (15.7 %) and SN (19.1 %). The cases of mild obstruction in the lungs were maximum (18.8 %) among children of CC area, followed by MP (17.8 %) and then SN (13.5 %) area (Table 5). Overall, CC area has reported the highest number of cases with “respiratory illness” and maximum number of cases with mild obstruction. The chi-square test results for difference among the groups were statistically significant, indicating the difference in environmental conditions of these three areas. The other confounding factor, i.e. socio-economic status of selected children, was approximately similar in all three areas.

Table 5 Result of lung function test of the students
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The logistic regression analysis of association between PM10 and prevalence of respiratory symptoms of the three study panels after adjustment for potential confounders showed a strong positive association. Considering SN population as reference, the association of respiratory symptoms in other two areas was positively associated with PM10 levels. The strongest association was found with “wheezing during activity” (OR 3.15, 95 % CI 2.87–3.75) followed by “wheezing or whistling sound in chest ever” (OR 3.02, 95 % CI 2.53–3.24) in the CC population group. Hence, it could be deduced that air pollution has a significant effect on the pulmonary health (Table 6).

Table 6 Conditional logistic regression analysis of the association between chronic exposure to PM10 and respiratory symptoms
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Discussion

Air pollution exposure has become a major concern with evident adverse effect on the respiratory health. It is an important contributing factor along with infectious agents and tobacco smoke towards the development of respiratory illnesses, and hence it is important to assess its impact on children. This study analysed the respiratory health status of children exposed to different levels of pollutants residing in different regions in Delhi City.

Initial data collection inside the classrooms revealed that even though NOX and SO2 levels were below the NAAQM permissible limits of 80 μg/m3, PM10 concentrations were very high in all areas (Table 1). WHO recommends that 24-h PM10 concentrations should not exceed 50 mg/m3 (WHO 2005). Therefore, it seems possible that PM10, rather than SO2 or NOX, was primarily responsible for the abnormal responses recorded in children. In agreement with this, epidemiological studies have shown that particulate matter, but not SO2, is associated with increased prevalence of respiratory symptoms in urban children (Aekplakorn et al. 2003) and adolescents (Pierse et al. 2006). Asthma or wheeze prevalence for 10 mg/m3 change in pollutant concentration has shown a wide variation across studies (HEI 2010b). A study in four Chinese cities reported that an increase in 50 mg/m3 of PM2.5–10 was associated with increase in wheezing, persistent cough and persistent phlegm by a maximum of 1.57 times among school children (Zhang et al. 2002). Current wheezing reported by Turkish school children exposed to average NO2 levels of 24.8 mg/m3 was 22.9 %, while those who were exposed to average NO2 levels of 14.9 mg/m3 was 15.9 % (Gul et al. 2011). Upper and lower respiratory symptoms, found in excess in children of CC area, could also be a fallout of a greater interaction of the airways with allergens and pathogens and/or impairment in lung defence. The literature study on possible associations between air pollution and respiratory symptoms in children revealed that outdoor and indoor air pollution are positively associated with upper and lower respiratory tract infections in children (Chauhan et al. 2005). Available evidence conclusively supports the association between outdoor air pollution, including PM10, NOX and SO2, and increased upper/lower respiratory symptoms in children.

Most of the respiratory illness symptoms were found in CC area panel, which is a commercial area with highest ambient air pollution levels as compared to other two areas. The prevalence of “wheezing during activity”, “night cough/ phlegm” and “frequent cold and cough” was high (20.8, 29, and 29.6 %, respectively) among the children of CC area (Table 4). These findings could be linked with the reports of a study carried out by Romieu et al. 2002 which also have shown positive associations between air pollution and respiratory symptoms.

The second highest prevalence of respiratory symptoms was found in MP area, which is an industrial area, however, with more indoor air pollution levels. Apart from exposure to air pollutants, other reason for high prevalence of respiratory illnesses could be poverty and lower social status which in turn are associated with large family size, crowded living conditions, poor access to medical care, higher smoking rates, nutritional deficits and stressful living environments. These factors were common among the selected children in both CC and MP areas. Also, majority of children were living in houses very close to the roads with heavy traffic. These factors may contribute individually or perhaps interact among themselves to increase the susceptibility to respiratory diseases. In a highly polluted roadside area and general area of Bangkok, Thailand, persistent cough, defined as in this study, was reported in 5.1 and 8.2 % of children, respectively (Langkulsen et al. 2006); in four Chinese cities with different levels of air pollution, persistent cough was reported in 5.2–14.0 % of school children (Zhang et al. 2002). However, in the case of third site, i.e. SN area, located in south of Delhi, which is cleaner and less crowded with lower ambient and indoor air pollution levels with homes more distant from main traffic roads (>500 m), prevalence of such symptoms was less.

The literature shows a wide range of current prevalence of wheezing among school children between and within countries over the time, varying from 32.2 % among 13- to 14-year-old children in the UK to 1.7 % among 10- to 19-year old children in Ethiopia (Patel et al. 2008). These variations may be attributed to differences in air pollution exposure levels. Further, the existing condition of “wheezing” is of utmost importance for the identification of asthma in epidemiological studies, and it has shown that this symptom has reasonably good specificity and sensitivity for bronchial hyper-responsiveness compared to other symptoms in both children and adults (Patel et al. 2008).

Further, the lung function test findings revealed that a significant population in MP area has severe obstruction in their lungs (32.2 %), which is highest among all three areas (Table 5). In spite of the highest number of respiratory illness symptom cases recorded in CC area, lung function test recorded the maximum number of severe obstruction cases in MP area. This may be due to drastic alteration in lung morphology due to exposure to fumes emitted from industries at a younger age. The higher percentage of children with mild obstruction in CC area (18.8 %) may be predisposed to asthma. Finally, the study in essence depicts that exposure to air pollutants especially PM10 has significant adverse effect on the pulmonary health of children in their growing years.

The major limitation of the study was the gender distribution which was unequal in the selected areas. The pollution effects have been reported to be different in the males and females. Further, the selected areas and schools represent a very small percentage of the total population; hence, a larger sample size is to be considered for further validation of the reports. Seasonal variation also contributes to the outdoor pollution levels which were not considered in this study.

Conclusion

High levels of PM10 were strongly associated with wheezing symptom for the study group. This study hence suggests that CC, a commercial region with high traffic movement and human activity, contributes more PM10 which in turn impairs the respiratory health of children. It is imperative to take measures to reduce the effects of air pollution on young children in Delhi City.