286 J Contemp Med Sci | Vol. 7, No. 5, September–October 2021: 286–289 Original The Relationship Between Air Pollutants and Spirometric Indices in Schoolchildren of Five Areas in Tehran Siavash Kooranifar1, Gholamreza Alizadeh Attar1* , Atefeh Talebi1, Vahan Moradians1, Maryam Pourashraf2, Razieh Rostami3, Nima Bakhtiari4 1Department of Internal Medicine, School of Medicine, Iran University of Medical Sciences, Tehran, Iran. 2Department of Radiology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran. 3Department of Internal Medicine, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran. 4Pain Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran. *Correspondence to: Gholamreza Alizadeh Attar (E-mail: sanysasan2002@yahoo.com) (Submitted: 22 July 2021 – Revised version received: 06 August 2021 – Accepted: 29 August 2021 – Published online: 26 October 2021) Abstract Objectives: The adverse health effects of air pollution have been observed in many epidemiological studies. The aim of this research was to study the effects of air pollution on pulmonary functions in schoolchildren in Tehran city. Methods: A total number of 167 schoolchildren were selected to participate in this study. Data were analyzed using ANOVA and Generalized Estimating Equation (GEE) to determine the relationship of air pollution and lung function tests. Results: The result of this study showed that there are statistically significant differences in value of air pollution between areas. The results present that concentration of O 3 , PM 10 , NO 2 has a negative association with lung function tests but concentration of CO, PM 2.5 , and SO 2 had no association with decreased lung function tests. Time variable of air pollution was not statistically significant effect on lung function test. Conclusion: in this study, we conclude that air pollution in Tehran city can be decreased lung function test indexes that may be affected by short–time exposure to air pollutant. Keyword: Lung function, schoolchildren, air pollution, Tehran ISSN 2413–0516 Introduction Air pollutants produced by industrial activities and vehicles such as O3, SO2, NO2, CO, PM2.5, PM10 have adverse effects on the res- piratory system1,2. The adverse effects are more pronounced in children because they are more sensitive when exposed to con- taminated air. Children have a lower diameter of airways, and they generally breathe more air per kg of body weight than adults, so exposure to more air pollutants. Increased concentrations of air pollutants cause more inflammation in the respiratory system3,4. Children spend more time and more activity outdoor; hence more susceptible to exposure to air pollutants5. Numerous studies postulated that air pollution had adverse effects on the respiratory system that are more serious in large and industrial cities6. Spirometry has been used in sev- eral studies to show the effects of air pollution on the respira- tory system. Indicators measured by spirometry include FVC, FEV1/FVC, FEV1, MMEF2575, FEV1/FEV6. Most studies examining the short–term effects of air pollution on spiro- metric indices performed a single spirometry test and have not evaluated changes in spirometric indices during a period, time which are essential in determining the exact effect of air pol- lutants on the respiratory system7. Therefore, we decided to study the effect of air pollutants on the respiratory system of children by performing two spirometry tests for each child and to evaluate the changes in spirometric indices. Our study was performed in Tehran, the capital city of Iran, which is one of the most polluted cities in this country. Materials and Methods Study Design This was a prospective cohort study conducted between September 2018 and May 2019. Inclusion Criteria Students without a history of respiratory disease and recent illness and who were taking no medications were included in this study. Participants In this study, 167 male and female fifth-grade elementary school students, aged between 10 to 12 years old, participated. The students were randomly selected from 10 schools in five municipal districts of the city, which were less than 500 meters from air quality monitoring stations. The height and weight of all of the students were measured. A questionnaire, including questions on drug history, asthma, allergy, eczema, and parent smoking, was given to each student’s parents. The study pro- tocol was approved by the Ethics Committee The Iran Univer- sity of Medical Sciences. Data on the Levels of Air Pollutants The levels of air pollutants such as O3, SO2, NO2, CO, PM2.5, PM10 were obtained from the Tehran Air Pollution Assessment website8. In both first and second episodes of spirometry, the levels of air pollutants were recorded on the day of performing spirometry and five consecutive days before that. The changes in the levels of air pollutants between the first and second epi- sodes of performing spirometry were calculated. Less than 5% of data on the levels of air pollutants was missed due to tech- nical errors in air monitoring sensors. Lung Function Test Spirometry was performed with a portable spirometer (Spirolab mobile version, China). The spirometer was cali- brated using a 3-liter syringe each time before spirometry. Spirometry was performed by expert technicians. In the 287J Contemp Med Sci | Vol. 7, No. 5, September–October 2021: 286–289 S. Kooranifar et al. Original The Relationship Between Air Pollutants and Spirometric Indices in Schoolchildren of Five Areas in Tehran beginning, the spirometry method was fully explained to the students. Three to five spirometry maneuvers were acquired from each student, and the best maneuver was selected based on American Thoracic Society/European Respiratory Society (ERS) criteria. Statistical Analysis The mean daily concentration of air pollutants on the day of the first and second time of spirometry in 5 districts (lag 0) and 1–5 days before the first and second time of that (lag 1–5) were measured and compared between five studied sites. Per- centage of changes of air pollutant concentration and spiro- metric indices were calculated between first and second times. In this study, multiple regression using GEE (Generalized Esti- mating Equation) statistical models were used to determine the correlation between changes of lung function indices (FVC, FEV1, FEV1/FVC, FEV1/FEV6 and FEF25–75) and changes in air pollutants (0 days to 5 days before spirometry). Statistical analyses (GEE, ANOVA) were performed using SPSS software (version 22), and statistical significance for P-values < 0.05 were considered. Consent to Participate Written informed consent was obtained from participants before the study. Ethics Approval Ethical approval for the study was obtained by the Ethics Committee of Iran University of Medical Sciences (approval code IR.IUMS.FMD.REC.1397.073). All participants were provided written informed consent before the study and had the right to withdraw from the study at any stage. Results In total, 167 male and female fifth-grade elementary school stu- dents, aged between 10 to 12 years old, were included in this study. The students were randomly selected from 10 schools in five districts of the city. The students’ characteristics are shown in Table 1. The average and standard deviation (SD) of height, weight, age, and BMI were not different between students of five municipal districts. The results of the mean daily concentrations of air pollutants are displayed in Table 2. The spirometric indices and percentage of changes are presented in Table 3. The results using GEE (Generalized Estimating Equation) are shown in Table 4. Table 4 shows that a one ppb increase in O3 was associated with a change of –0.058 L in FEV1 (95%CI: –.099 – –.017 L) and –0.04 in FVC (95%CI: –.072– –.008L) and –0.085 Lit in FEF25–75 (95%CI: –.158– –.012L), after adjustment for gender and height. Our study demonstrates that 1 a ppb increase in NO2 was associated with a change of –0.106 Lit in FEV1 (95% CI: –.183– –.029L) and –0.087 Lit in FVC (95% CI: –.149– –.026L), after adjustment for gender and height. This study also displayed that 1 µg/m³ increase of PM10 was associated with a change of 0.037 Lit in FEV1 (95% CI: .010 – .065L) and 0.039 Lit in FVC (95% CI: .011 – .068L), after adjustment for gender and height. Other air pollutants had no significant effect on spirometric indices. Discussion The present study included 167 male and female fifth-grade elementary school students, aged between 10 to 12 years. This age range was chosen because of more inadequate cooperation in younger children. This study was conducted on healthy ele- mentary school students without any previous illness. Air pollutants produced by industrial activities and vehi- cles such as O3, SO2, NO2, CO, PM2.5, PM10 have adverse effects on the respiratory system2. Our study assessed the effects of the daily average concentration of air pollutants on spiro- metric indices. Previous studies have demonstrated that ele- vated air pollutants were associated with more decrease in lung function in children than adults5. Several previous studies have examined the associations between spirometric indices and air pollutants6,9–13 but those studies did not consider changes in spirometric indices in individuals. In those studies, the concentration of air pollutants in the days before spirom- etry was measured. Chang et al. investigated the effects of air pollution on lung function tests of adolescents aged 12 to 16 years and reported that FVC, had a significant adverse association with short-term exposure to O3 and PM10 measured on the day of spirometry testing13.FVC values also were reversely associated with means of CO, O3, NO2, PM10 and SO2 exposed 1 day ear- lier. An increase of 1-ppm CO was associated with the reduc- tion in FVC for 69.8 mL (95% CI: –115, –24.4 mL) or in FEV1 for 73.7 mL (95% CI: –118, –29.7 mL). Their study also showed that an increase in SO2 for 1 ppb was associated with the reductions in FVC and FEV1 for 12.9 mL (95% CI:–20.7, –5.09 mL) and 11.7 mL (95% CI:–19.3, –4.16 mL), respec- tively. Chang et al. similar to other previous studies did not evaluate changes in spirometric indices of each individual during a period, time. Another difference between The change study and ours was that they found the time lag between the air pollutant measurement and spirometry day, had a significant effect on spirometric indices. nevertheless in our study, there was no significant relationship between the time lag and air pollutant levels. Another study performed by Hashemzadeh et al. in Ahvaz, a major city in the southwest of Iran, demonstrated a Table 1. Demographic profile of the study participants P-valueTotal Region15Region7Region6Region5Region2Variables 1672537313737No 37.10%0%37.80%35.40%48.60%51.30%Male 62.90%100%62.10%64.50%51.30%48.60%Female p = 0.49152.0 ± 8.4153.2 ± 7.0151.3 ± 8.8150.2 ± 10.4153.4 ± 8.5152.6 ± 7.3Height (cm) p = 0.9248.7 ± 11.849.6 ± 9.547.4 ± 13.648.0 ± 11.349.5 ± 10.549.2 ± 13.4Weight (kg) p = 0.9020.9 ± 4.221.0 ± 2.620.4 ± 4.021.5 ± 5.320.9 ± 3.521.0 ± 5.0BMI 288 J Contemp Med Sci | Vol. 7, No. 5, September–October 2021: 286–289 The Relationship Between Air Pollutants and Spirometric Indices in Schoolchildren of Five Areas in Tehran Original S. Kooranifar et al. Table 2. The results of the mean daily concentrations of air pollutants Mean (SD)Mean (SD)Mean (SD)Mean (SD)Mean (SD)Mean (SD) SO 2 (ppb) 4.3 ± 2.14.1 ± 2.33.7 ± 2.43.5 ± 1.83.1 ± 1.43.5 ± 1.4 First time 3.9 ± 1.03.9 ± 1.13.5 ± 1.54.7 ± 1.84.3 ± 1.04.3 ± 1.2 Second time 37.6 ± 51.312.9 ± 59.516.5 ± 51.450.3 ± 55.460.4 ± 62.137.6 ± 51.3 Percentage of changes NO 2 (ppb) 47.2 ± 14.643.9 ± 10.445.5 ± 15.243.7 ± 9.242.9 ± 5.545.0 ± 5.0 First time 49.9 ± 9.044.8 ± 7.641.7 ± 10.847.7 ± 10.248.8 ± 6.749.0 ± 11.0 Second time 5.0 ± 43.42.3 ± 26.5–1.5 ± 28.313.2 ± 25.115.4 ± 18.910.2 ± 20.3 Percentage of changes CO (PPM) 1.7 ± 0.51.3 ± 0.41.5 ± 0.61.3 ± 0.51.3 ± 0.31.4 ± 0.3 First time 1.5 ± 0.91.4 ± 0.71.3 ± 0.41.4 ± 0.41.7 ± 0.51.7 ± 0.9 Second time –0.2 ± 60.21.3 ± 27.6–6.0 ± 32.017.3 ± 37.533.8 ± 47.223.7 ± 69.4 Percentage of changes O 3 (ppb) 17.0 ± 6.318.3 ± 7.420.9 ± 6.717.1 ± 8.522.6 ± 6.616.5 ± 5.5 First time 16.7 ± 7.017.9 ± 8.919.0 ± 10.718.3 ± 8.915.0 ± 7.516.3 ± 8.5 Second time 11.3 ± 47.7–3.9 ± 39.7–9.1 ± 50.7–10.8 ± 43.5–32 ± 31.5–9.3 ± 43.4 Percentage of changes PM 2.5 (µg/m³) 25.7 ± 13.824.9 ± 11.625.7 ± 14.523.1 ± 12.5125.5 ± 5.118.1 ± 6.9 First time 24.5 ± 16.725.0 ± 15.325.6 ± 16.125.8 ± 16.427.2 ± 12.529.8 ± 12.6 Second time 28.4 ± 95.710.0 ± 44.66.4 ± 38.922.5 ± 67.287.1 ± 84.472.2 ± 54.2 Percentage of changes PM 10 (µg/m³) 53.9 ± 27.056.8 ± 23.254.6 ± 25.443.2 ± 20.835.2 ± 13.839.3 ± 16.2 First time 51.8 ± 30.154.3 ± 28.051.2 ± 24.154.4 ± 28.754.1 ± 21.762.6 ± 29.0 Second time 25.1 ± 98.9–3.8 ± 46.5–3.7 ± 38.642.3 ± 96.070.2 ± 76.278.7 ± 91.9 Percentage of changes Table 3. The spirometric indices and percentage of changes Mean (SD)Mean (SD)Mean (SD) –0.5 (–61.3, 95.2)2.0 (0.88, 3.02)2.1 (0.85, 3.12)FEV1 (L) –2.0 (–40.82, 57.95)2.2 (1.1 – 3.2)2.3 (1.21, 3.42)FVC (L) 1.6 (–54.3, 89.8)90.5 (40.6, 100.0)90.5 (40.6, 100.0)FEV1/FVC (%) 1.4 (–54.3, 89.8)91.2 (41.3, 100.0)90.6 (40.6, 100.0)FEV1/FEV6 (%) 5.1 (–71.5, 160.0)2.6 (0.6, 5.3)2.7 (0.5, 4.99)FEF25–75 (L) Table4. The results obtained by Generalized Estimating Equation (GEE) P-valueBP-valueBP-valueBP-valueBP-valueB 0.170.7840.1990.2430.1890.2530.520.1780.1770.425Time 0.023–0.0850.178–0.0170.145–0.0180.013–0.040.006–0.058O 3 0.5160.0190.3330.0090.3370.0090.78–0.0050.8560.003CO 0.167–0.1340.614–0.0140.531–0.0180.005–0.0870.007–0.106NO 2 0.460.0250.1350.0170.1390.0170.4620.0110.1270.028SO 2 0.3440.0250.611–0.0040.679–0.0030.0070.0390.0080.037PM 10 0.3710.0260.1420.0120.1170.0130.222–0.0210.616–0.009PM 2.5 289J Contemp Med Sci | Vol. 7, No. 5, September–October 2021: 286–289 S. Kooranifar et al. Original The Relationship Between Air Pollutants and Spirometric Indices in Schoolchildren of Five Areas in Tehran significant correlation between the increase of mean concen- tration of NO2 in 1 to 4 days before sampling day and decreased FVC and FEV114. In this regard, by increasing the mean NO2 concentration to 6.5 ppb, the values of FVC and FEV1 decreased by 12 and 19 mL; and by increasing the mean con- centration of PM2.5 to 13 µg/m³ on the same day of sampling (lag 0), the values of FVC and FEV1 decreased by 131 and 110 ml. However, similar to most previous studies, they did not evaluate spirometric changes within a period, time. In our study, Ozone harmed FEV1, FVC and FEF25–75, with the most significant effect on FEF25–75.It should be noted that although these effects are statistically significant, they are clinically insignificant and they did not cause symp- toms in the students. In normal subjects,the cut-off for clinically significant week-to-week changes of FEV1 and FVC were more than 12% and 11%, respectively. In our study, 61.6% of the subjects had FEV1 change less than 12% and 63.4% had FVC change less than 11%. In fact, in most subjects, although the percentage of spirometric changes was statistically significant, the indices remained within the normal range. Conclusion Our research suggests that air pollution in Tehran city can lead to decreased lung function test indices which may be affected by short-time exposure to air pollutants.Traffic-related air pol- lutants show acute and subacute adveres effects on the respira- tory system in school children. Accordingly, our research suggests air pollution changes are associated with changes in lung function in a healthy subject. These findings can help improve understanding adverse effects of air pollution on the respiratory system, and may also implicatemore targeted and effective pollution regulations to reduce traffic emission pollutants. Acknowledgment This work would not have been possible without the financial support of the Pasargad Teb IrsaCompany Award. Declarations Funding/Support: This research was funded by Iran University of medical sciences by grant number 805 as part of thesis of Gholamreza Alizadeh Attar. Competing Interests: The authors have no conflict of interest. Data Availability: The datasets used in the present study are available from the corresponding author on reasonable request. Authors’ Contributions: All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Gholamreza Alizadeh Attar. 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