Abstract
Background: Indoor air pollution has globally known as the risk factor of acute respiratory infection in young children. The exposure to indoor particulate matter 2.5 (PM2.5) and nitrogen dioxide (NO2) at house or school can be a potential risk to children’s health. This study aimed to examine the association between indoor PM2.5 and NO2 with oxidative stress markers in junior high school students.
Design and methods: This study was conducted using a cross sectional study with 75 students collected randomly from four junior high schools in Jakarta. PM2.5 and NO2 were measured in classrooms and school yards. The schools were categorized based on the exposure level of PM2.5 and NO2 in classrooms. Superoxide dismutase (SOD) and reduced glutathione (GSH) were examined from the blood sample. All students were interviewed with questionnaires to determine upper respiratory tract infection, smoking family members, mosquito repellent usage, and dietary supplement consumption.
Results: Mean concentration of indoor PM2.5 and NO2 were 0.125±0.036 mg m-3 and 36.37±22.33 μg m-3, respectively. The schools which located near to highway showed lower PM2.5 and higher NO2 level indicated the emission of traffic activity. Mean activity of SOD was 96.36±50.94 U mL-1 and mean concentration of GSH was of 0.62±0.09 μg mL-1. Most of the students reported upper respiratory tract infection history, smoking family member, use mosquito repellent at home, and do not consume dietary supplement.
Conclusions: The level of oxidative stress markers and the exposure categories of classroom PM2.5 and NO2 was not significantly different, however there were significant correlation with cigarette smoke and mosquito repellent at home. Nevertheless, the exposure of indoor PM2.5 and NO2 increased the risk of the exposure to cigarette smoke and mosquito repellent at home. Further study on the air pollution at school and home is needed to affirm association towards student’s health and to design strategic control efforts.
Significance for public health.
Indoor air pollution has globally known as one of public health problem and the risk factor of acute respiratory infection in young children. The exposure to indoor particulate matter 2.5 (PM2.5) and nitrogen dioxide (NO2) at house or school can be a potential risk to children’s health. This study aimed to examine the association between indoor PM2.5 and NO2 with oxidative stress markers in junior high school students and help affirm association towards student’s health and to design strategic control efforts.
Key words: School, particulate matter, indoor air quality, oxidative stress, antioxidant
Introduction
Indoor air pollution is one of the major health risk factors responsible for nearly 1.6 million excess deaths annually and about 3% of the global burden of disease.1 Outdoor air pollution strongly influences indoor air quality especially due to human activities such as traffic and industrial activities.2,3.Previous study reported that, based on the guideline of World Health Organization, most of the municipality of Jakarta province had poor air quality from 2011 to 2017 and was reported to be associated with respiratory infection among population in Jakarta.4,5 Traffic activity is one of the major sources of air pollutants such as particulate matters (PM2.5) and nitrogen dioxide (NO2) in Jakarta. Particulate matter with diameter of less than 2.5 μm or PM2.5 is a major component of air pollution that can be inhaled up to systemic circulation.6,7 Meanwhile, NO2 gas is mainly emitted from traffic activity that involves fuel burning and directly combines with the oxygen in the atmosphere.8,9
Vigorous development activities in Jakarta have increased air pollution source points such as highways or toll roads into adjacent school buildings, impacted to increase the exposure risk of PM2.5 and NO2 to students in school environment.2,10 School-age children are vulnerable to environmental exposure due to their immature immune and respiratory system. During school time, this group spends most of their time six to eight hours at school.11,12 Several studies reported that high exposure of PM2.5 and NO2 in classroom were associated with respiratory problems in children such as asthma, decreased of lung function, and respiratory tract and lung inflammation.11,13-15 Several studies have reported that airborne air pollutants can induce oxidative stress resulted to increase the risk of respiratory problems.8,16 Inhaled air pollutants such as PM2.5 and NO2 initiate reactive oxygen species (ROS) production that induce inflammation response in lung resulting oxidative stress indicated by depletion of specific antioxidants or elevation of antioxidant activity such as superoxide dismutase (SOD).8,16 Superoxide dismutase (SOD) plays as an enzymatic antioxidant to catalyze the dismutation of superoxide anion radical to molecular oxygen and harmless hydrogen peroxide which is then to be scavenged by glutathione (GSH) through enzymatic reactions. GSH is the most important hydrophilic antioxidant that protects cells against free radicals. Disorder of antioxidants level has been implicated in the etiology or development of various diseases. 6,17 However, study on oxidative stress effects to the inflammation of respiratory tract on school-age children in Jakarta has not well understood, particularly the production of SOD and GSH. Thus, a study on antioxidant levels of SOD and GSH was suggested to early determination on the health risk of PM2.5 and NO2 exposure towards students in Jakarta.
Design and methods
This study was conducted from December 2010 to January 2020 in Jakarta Special Region, Indonesia, using a cross-sectional design. Four junior high schools were selected randomly from four municipalities in Jakarta. Parental and student informed consents were distributed randomly to 200 first grade of junior high school students living around five kilometers from the school. Students who were willing and permitted to participate from their parents underwent examination by medical doctors to fulfill the inclusion and exclusion criteria. This research excluded students with the history of chronic respiratory disease and who were experiencing symptoms of health problems on the day of blood sampling.
Data collection
Interview was conducted to collect demographic and health information. We conducted structural interview to 75 students using standard questionnaires adapted from a set of validated questionnaires by International Study of Asthma and Allergies in childhood (ISAAC) and food frequency questionnaires. The questionnaire was used to determine history of upper respiratory tract infection, tobacco smoke exposure at home, mosquito repellent usage, and dietary supplement intake. The same questionnaire was used in previous school studies in Depok, West Java.10,18 The selected students were interviewed by researchers based on the questionnaire.
Indoor air samples
We collected ambient air samples at each school to measure PM2.5, NO2, temperature, and humidity. Samples were collected both indoor (one classroom) and outdoor (one school yard) during school time. PM2.5 concentration was measured using DustTrak II Aerosol Monitor which monitored continuously for 8 hours (8 am to 4 pm) in one school day. The inlet flow was positioned at one meter above the ground level and distant to walls and doors to represent the actual children’s respiration zone.19,20 NO2 was monitored for one hour (8 am to 9 am) in one school day using Impinger according to the standardized Griess-Saltzman method by National Standardization Agency of Indonesia to measure absorbed NO2.21 In addition, we also measured the classroom’s physical conditions (i.e., temperature and humidity) and observed the classroom condition. Each school was assessed in different week due to school permit, academic activities, and availability of the instruments.
Superoxide dismutase (SOD) and glutathione (GSH) level in blood
Blood samples were collected from the students who have agreed to the term and conditions of the study. Around 5 ml blood samples were collected using sterile syringe by experienced paramedic. Blood samples were then centrifuged to separate plasma and stored into vial. Samples were then kept in refrigerator at 4°C. SOD enzyme concentration was assayed by using RanSOD Kit and read by RX-Monza. This measurement aimed to get the dismutation of the toxic superoxide anion to hydrogen peroxide and oxygen. Xanthine and Xanthine oxidase were used to generate superoxide anion radicals. It reacts with 2-(4-iodoponhenyl)-3-(4-nitrophenol)- 5-phenyltetrazolium chloride (I.N.T) to create a red formazan dye. SOD activity was measured by inhibition degree of the reaction22.
GSH was measured using spectrophotometric method. GSH was oxidized by 5,5′-dithiobis-(2-nitrobenzoic acid) (DTNB) resulting in the formation of oxidized glutathione (GSSG) and 5- thio-2-nitrobenzoic acid (TNB). GSSG then was reduced to GSH by glutathione reductase (GR) using reducing equivalent provided by NADPH. The rate of TNB formation was proportional to the sum of GSH and GSSG presented in the sample and was determined by measuring the formation of TNB at 412 nm.23 The analysis was done in Biochemistry Laboratory, Faculty of Medicine, Universitas Indonesia.
Statistical analysis
All data in this study were analyzed using statistical analysis software package. The Skewness-Kurtosis method was used to test data normality. Students’ demographic data, nutrition status, upper respiratory tract infection history, home tobacco smoke exposure, mosquito repellent usage, and dietary supplement intake were analyzed descriptively. Schools were categorized into highly exposed and low exposed categories based on mean levels of indoor PM2.5 and NO2. To evaluate association between the exposure and oxidative stress marker, the mean values of SOD and GSH between exposure categories were compared using t-test and Mann Whitney test, with p-value <0.05 considered statistically significant. The mean of SOD and GSH between the categories of students’ demographic, nutrition status, upper respiratory tract infection history, home tobacco smoke exposure, mosquito repellent usage, and dietary supplement intake were also compared using ttest and Mann Whitney test.
Results
Subjects and location characterization
All corresponding schools in this study open in five school days per week at 6:30 am to 2:15 pm. Besides that, extracurricular activities were also performed until around 4:00 pm. Two of the four schools (school A and D) were located next to the highway, while school B was located about 100 m from the main highway, and school C was in a residential area (Table 1). All classrooms were floored without carpets and were naturally ventilated with additional fans. All classrooms were furnished with wooden desks, chairs, and whiteboards. All school yards have cement or asphalt flooring.
A total of 75 students from the four schools voluntary participated as subject and met the inclusion and exclusion requirements for the study (Table 2). The mean age of the subject was 13.06- year-old which most subjects were female students. Most of the students had smoking family member, used mosquito repellent, and did not consume dietary supplement at least once per week in last one month. Our results found that 76% students have upper respiratory tract history in last six months.
Exposure of PM2.5 and NO2
The mean PM2.5 concentrations in four schools were 0.125 mg/m3 in classroom and 0.090 mg/m3 in school yard (Table 3). School C (residential area) had the highest PM2.5 concentration for both inside and outside of the classroom. All schools have higher PM2.5 concentrations inside the classroom compared to the yard. Based on the mean PM2.5 concentrations, school B and C were categorized as high PM2.5/ low NO2.
The mean concentrations of NO2 were 36.37 mg/m3 and 19.24 mg/m3 in in classroom and school yard, respectively. School A has the highest NO2 concentration (62.54 mg/m3) in classroom. All schools, except for School D, showed higher NO2 concentrations in classroom compared to school yard. Meanwhile, NO2 concentration in School D showed no difference concentration for both inside classroom and in school yard. School D had higher NO2 concentration than the other schools. Based on the mean concentrations, school A and C were highly exposed to NO2 which then categorized as high NO2/low PM2.5. PM2.5 and NO2 measurements were carried out in the rainy season with clear or cloudy weather patterns in the morning until noon and cloudy or rainy in the afternoon. All classrooms have higher humidity levels and lower temperatures compared to school yard. PM2.5 and NO2 concentrations were also found to be higher in the classroom than in school yard.
Table 1.
School characteristic.
| School | Location | Sampling sites | Classroom shape | Classroom area (m2) | Number of students/ class | Environment condition |
|---|---|---|---|---|---|---|
| A | Pasar Baru, Central Jakarta | 1st floor classroom (1) and school yard (1) | Rectangle | 62.01 | 32 | City center, business and office areas, next to main highway, near the intersection of red lights and the train station. |
| B | Lubang Buaya, East Jakarta | 3rd floor classroom (1) and school yard (1) | Rectangle | 64.8 | 36 | Suburban, office and business areas, 100 m from the main highway and red light intersections. |
| C | Cipedak, South Jakarta | 3rd floor classroom (1) and school yard (1) | Rectangle | 64.74 | 36 | Suburban, residential areas, and next to golf courses. |
| D | Kebon Jeruk, West Jakarta | 3rd floor classroom (1) and school yard (1) | Rectangle | 56.15 | 36 | Suburban, business and residential areas, next to main highway, and the intersection of red lights. |
Table 2.
Subject characteristic.
| Characteristic | Description | |
|---|---|---|
| Age (year) | ||
| Mean±SD | 13.06±0.48* | |
| Sex (n, %) | ||
| Female | 58 | 77.33 |
| Male | 17 | 22.67 |
| Nutrition status (n, %) | ||
| Thin | 3 | 4.00 |
| Normal | 48 | 64.00 |
| Fat | 24 | 32.00 |
| Upper respiratory tract infection history (last 6 months) (n, %) | ||
| Yes | 57 | 76.00 |
| No | 18 | 24.00 |
| Smoking family member (n, %) | ||
| Yes | 43 | 57.33 |
| No | 32 | 42.67 |
| Dietary supplement consumption (at least once per week in last month) (n, %) | ||
| Yes | 32 | 42.67 |
| No | 43 | 57.33 |
| Mosquito repellent usage (n, %) | ||
| Yes | 42 | 56.00 |
| No | 33 | 44.00 |
| SOD (U mL-1) | ||
| Mean±SD | 96.36±50.94 | |
| Median | 84.97# | |
| GSH (μg mL-1) | ||
| Mean±SD | 0.62±0.09* | |
| Median | 0.63 |
*Normal distribution
#skewed distribution.
Oxidative stress marker
The mean SOD activity from all samples was 96.36 U mL-1 and the mean concentration of plasma GSH was 0.62 μg mL-1 (Table 4). Based on our statistical analysis, there was no significant difference of GSH and SOD levels between high PM2.5 schools and high NO2 schools. w. However, schools with high NO2 exposure in the classroom had lower levels of GSH and higher SOD activity (Table 5). Meanwhile, mean SOD activity and GSH concentration between sex (p=0.889; 0.819), nutritional status (p=0.368; 0.612), history of upper respiratory tract infection (p=300; 0.190), and dietary supplement consumption (p=0.213; 0.617), were not statistically different. However, there was a statistically significant difference of mean SOD activity (p=0.001) and mean GSH concentration (p=0.036) between cigarette exposure and non-cigarette exposure at home. The usage of mosquito repellent resulted in a significant difference in GSH concentration (p=0.035).
Discussion
Airborne particulate matter and nitrogen dioxide
The concentration of PM2.5 in four schools was similar to a previous study conducted in schools in Depok, Indonesia and several studies in India.18,24,25 Several other studies conducted in Germany, Italy, Portugal, and Malaysia reported that PM2.5 concentrations that exceeded WHO guideline values, but still lower than our current study.11,12,26,2. According to the previous studies, high PM2.5 levels in the classroom might be caused by poor ventilation, poor classroom hygiene, occupant activities, and other outdoor sources.11,26,28 However, we did not make further observation for these factors in this study. In contrast to the studies in Germany and Malaysia, this study found that schools located in suburban settlements (far from the highway or industry) had the highest PM2.5 concentrations.26,29 another study conducted in kindergarten in Portugal reported a similar results with this study.11,12 Higher PM2.5 concentrations in a residential area might be caused by public activities such as biomass burning and cooking, open yards or land without cement layering, and surrounding activities such as traffic and industry.30,31
The PM2.5 concentration in this study showed that rainy season did not influence the air quality in the school environment. Studies in tropical and subtropical countries reported a decreasing pattern of outdoor particulate levels which related to the increase of humidity and rainfall during rainy season. Indoor particulate level can increase during the rainy season due to student’s activity in the classroom and poor ventilation openings.11,25,26,28,30
The mean NO2 concentration in four schools did not exceed the threshold values set by the Indonesian government for one hour (400 μg m-3, 1 hour) and WHO (200 μg m-3, 1 hour). A similar study by Wispriyono et al.10 on indoor air pollution in Jakarta reported lower indoor and outdoor NO2 than our results. Other studies conducted in the United States and Brazil measured NO2in the school environment reported there was association of NO2 in air and respiratory disorders.15,32,33 Whereas studies in India and Australia reported higher NO2 and correlated with respiratory disorders, even though they did not exceeded the WHO threshold value.25,34
Table 3.
Level of pollutants in schools.
| Parameter | Mean ± SD | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Classroom | School yard | Classroom School Yard | ||||||||
| School A | School B | School C | School D | School A | School B | School C | School D | (n=4) | (n=4) | |
| PM2.5 (mg m-3) | 0.095 | 0.128 | 0.175 | 0.103 | 0.092 | 0.109 | 0.095 | 0.065 | 0.125±0.036 | 0.090±0.018 |
| NO2 (μg m-3) | 62.54 | 24.5 | 12.37 | 46.05 | 23.72 | 4.33 | 2.87 | 46.05 | 36.37±22.33 | 19.24±20.24 |
| Humidity (%) | 73.5 | 71.43 | 77.03 | 76.77 | 69.53 | 56.83 | 68.77 | 72.73 | 75.24±2.65 | 68.73±7.21 |
| Temperature (°C) | 31.57 | 31.00 | 30.37 | 30.63 | 32.23 | 37.10 | 34.87 | 32.17 | 30.74±0.57 | 33.36±2.62 |
Table 4.
Level of oxidative stress markers in students.
| Antioxidant | School A | School B | School C | School D | All schools |
|---|---|---|---|---|---|
| n=21 | n=23 | n=16 | n=15 | n=75 | |
| SOD (Uml) | |||||
| Mean ± SD | 84.31±23.11 | 76.81±47.39 | 139.82±71.32* | 96.86±31.17* | 96.36±50.94 |
| Median | 83.86# | 62.27# | 129.21 | 101.88 | 84.97# |
| CI 95% | 73.79-94.83 | 56.32-97.31 | 101.82-177.82 | 79.59-114.13 | 48.64-108.08 |
| Min-Max | 45.58-124.09 | 39.62-262.44 | 39.62-273.45 | 43.01-133.78 | 39.62-273.45 |
| GSH (μg/ml) | |||||
| Mean ± SD | 0.52±0.08* | 0.61±0.05* | 0.66±0.0.06* | 0.72±0.05* | 0.62±0.09* |
| Median | 0.51 | 0.61 | 0.66 | 0.72 | 0.63 |
| CI 95% | 0.48-0.56 | 0.59-0.63 | 0.63-0.70 | 0.69-0.74 | 0.60-0.64 |
| Min-Max | 0.33-0.68 | 0.51-0.73 | 0.57-0.83 | 0.51-0.73 | 0.33-0.83 |
*Normal distribution
#skewed distribution.
Table 5.
Oxidative stress marker association to various variables.
| Variable | Antioxidants level | |||||
|---|---|---|---|---|---|---|
| SOD (U ml-1) | GSH (μg ml-1) | |||||
| n=75 | Mean±SD/Median (IQR) | p-value | n=5 | Mean±SD/Median (IQR) | p-value | |
| PM2.5 and NO2 exposure | ||||||
| High PM2.5/low NO2 | 39 | 83.03(69.49) | 0.714 | 39 | 0.63±0.06 | 0.197 |
| Low PM2.5/high NO2 | 36 | 89.54(51.42) | 36 | 0.60±0.12 | ||
| Sex | ||||||
| Female | 58 | 83.44(60.10) | 0.889 | 58 | 0.62±0.09 | 0.819 |
| Male | 17 | 93.92(60.17) | 17 | 0.62±0.10 | ||
| Nutrition status (BMI age) | ||||||
| Normal | 27 | 83.03(53.35) | 0.368 | 27 | 0.63±0.09 | 0.662 |
| Abnormal (thin and fat) | 48 | 88.23(63.68) | 48 | 0.61±0.10 | ||
| Upper respiratory tract infection history (last 6 months) | ||||||
| Yes | 57 | 80.29(59.09) | 0.300 | 57 | 0.61±0.10 | 0.190 |
| No | 18 | 104.25(64.57) | 18 | 0.65±0.09 | ||
| Smoking family member | ||||||
| Yes | 43 | 110.71(62.96) | 0.001 | 43 | 0.64±0.09 | 0.036 |
| No | 32 | 68.99(36.44) | 32 | 0.59±0.10 | ||
| Dietary supplement consumption (at least once per week last month) | ||||||
| Yes | 32 | 92.93(43.94) | 0.213 | 32 | 0.60±0.10 | 0.617 |
| No | 43 | 98.93(55.97) | 43 | 0.63±0.09 | ||
| Mosquito repellent usage | ||||||
| Yes | 42 | 89.82(53.44) | 0.601 | 42 | 0.60±0.10 | 0.035 |
| No | 33 | 84.87(73.19) | 33 | 0.64±0.08 | ||
The existence of NO2 in ambient air was specifically related to outdoor air pollutants sources such as traffic activities, thus related to the increase of NO2 concentration in classroom and yard in school A and D. This results indicated that outdoor air pollutants affected the indoor air quality in the classroom.25,33 Beside that, the lowest NO2 concentration was detected in school C (suburban settlement) indicated that buildings which located far from highway or main road received less NO2 pollution. Previous studies also suggested that NO2 levels was relatively lower in the rainy season and increase during the dry season.25
SOD and GSH levels
At the time of data collection, subjects had just enrolled in the school for six months, thus these results represent the exposure of the last six months before data collection. The median SOD activity in this study was higher than a study conducted among healthy, asthma, and down syndrome children, but was similar to a study among workers in the ready-mix concrete factory exposed to PM2.5.35,36 The production of SOD activity occurred in response to oxidative stress due to an increase in superoxide reactive species. This can be mediated by air pollutants exposure, such as particulates or nitrogen dioxide.22,37 Our results found that the students with high NO2 exposure had slightly higher SOD activity and slightly lower GSH concentration than the students with low NO2 exposure. A previous study by Bernard et al. (2016) also reported lower GSH concentration and no significant correlation was observed between GSH in adults and NO2 (higher than 40 μg m- 3).38 However, the mean plasma GSH concentration of all students in this study was lower than some other studies conducted in healthy children.39,40 The increased in reactive species levels in a certain concentration and time will pose to the depletion of GSH concentration resulted in the decrease of cell capability against oxidative stress. Depleted GSH has been reported to be associated with health risk of respiratory system disorder such as chronic pulmonary disease, acute respiratory distress syndrome, neonatal lung damage and asthma.8,17,40,41 In this study, the students with reported upper respiratory tract infection showed lower GSH level but there was no significant correlation between GSH and upper respiratory tract infection.
Despite f the exposure to air pollutants in schools, the level of antioxidants might be associated with the exposure to air pollutants at home such as mosquito repellent or cigarette smoke.42-44 In this study, students who were exposed to mosquito repellent at home showed significantly lower GSH levels. Previous studies on pyrethroid-based mosquito repellent and antioxidants in mice showed the decrease of GSH level in the brain.42,45 Mosquito repellent contains pyrethroid compounds that produce reactive species during the metabolism process and induce oxidative stress in a certain time and concentration.42,46,47 Meanwhile, the mean GSH concentration and SOD activity showed significant different between students exposed to and not exposed to cigarette smoke at home. Cigarette smoke typically contains more reactive species which easily induce oxidative stress easily resulted in the decrease of antioxidant levels in the human body.38,48 However, in this study, SOD activity and GSH concentrations were higher in students exposed to cigarette smoke. Research by Yokus et al.49 on oxidative stress among active and passive smokers suggested that SOD activity will increase as an adaptive response to the oxidative load of cigarette smoke and clean up excess superoxide reactive species. Adaptive response of GSH will also increase gradually to achieve their normal level in a certain period of time.50 However, the adaptive response can be disrupted or decrease with increase in age.49,50
Limitations
This study did not record the number of daily cigarettes and periods of smoking among family members so the frequency of exposure could not be further explained specifically.
Conclusion
The concentration of PM2.5 and NO2 showed higher level in the schools located near to highway or main road. The relation between PM2.5 and NO2 exposure with antioxidant level showed no significant correlation. However, there was a significant difference between SOD and GSH concentration with the students who were exposed to cigarette smoke and mosquito repellent. The upper respiratory tract infection history in students suggested that students had been exposed to poor air quality in both school and house. Further study should be improved to measure other airborne pollutants which related to the increase of oxidative stress by determining other potential factors.
Acknowledgements
Authors would like to thank the government of DKI Jakarta Province, Education Office of DKI Jakarta Province, teachers, students, and parents for supporting this study. This study was funded by International Research Collaboration Grant 2019 [Hibah Kolaborasi Riset lnternasional Tahun 2019 No. NKB-1 938/UN2.R3.1/HKP.05.00/2019].
References
- 1.World Health Organization. Guidelines for indoor air quality: selected pollutants. 2010. Available from: https://apps.who.int/iris/handle/10665/260127 [PubMed] [Google Scholar]
- 2.Haryanto B, Franklin P. Air pollution: A tale of two countries. Rev Environ Health 2011;26:53-9. [DOI] [PubMed] [Google Scholar]
- 3.Ismail M, Zafirah N, Sofian M, Abdullah AM. Indoor Air quality in selected samples of primary schools in Kuala Terengganu, Malaysia. Environ Asia 2010;3:103-8. [Google Scholar]
- 4.Kashima S, Yorifuji T, Tsuda T, et al. Effects of traffic-related outdoor air pollution on respiratory illness and mortality in children, taking into account indoor air pollution, in Indonesia. J Occup Environ Med 2010;52:340-5. [DOI] [PubMed] [Google Scholar]
- 5.Rita Aprishanty R, Fauzi R. Air quality index calculation in Jakarta using different. Ecolab 2018;12:32-41. [Google Scholar]
- 6.Kim HJ, Choi MG, Park MK, Seo YR. Predictive and prognostic biomarkers of respiratory diseases due to particulate matter exposure. J Cancer Prev 2017;22:6-15. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Zwoździak A, Sówka I, Worobiec A, et al. The contribution of outdoor particulate matter (PM1, PM2.5, PM10) to school indoor environment. Indoor Built Environ. 2015;24:1038-47. [Google Scholar]
- 8.Kelly FJ. Oxidative stress: Its role in air pollution and adverse health effects. Occup Env Med 2003;60:612-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Agency for Toxic Substances and Disease Registry (ATSDR). Nitrogen oxides (NO, NO 2, and others) CAS 10102-43-9 ; UN 1660 (NO) CAS 10102-44-0 ; UN 1067 (NO 2) UN 1975 (Mixture). 1975. Available from: https://www.atsdr.cdc.gov/MHMI/mmg175.pdf [Google Scholar]
- 10.Wispriyono B, Yulaeva E, Hartono B, Pratama S. Indoor air pollution (carbon dioxide and total volatile organic compound) and pulmonary disorders in junior high school students in Depok, West Java. Glob J Health Sci 2019;11:45-54. [Google Scholar]
- 11.Alves C, Nunes T, Silva J, Duarte M. Comfort parameters and particulate matter (PM10 and PM2.5) in school classrooms and outdoor air. Aerosol Air Qual Res 2013;13:1521-35. [Google Scholar]
- 12.Madureira J, Paciência I, Rufo J, et al. Indoor air quality in schools and its relationship with children’s respiratory symptoms. Atmos Environ 2015;118:145-56. [Google Scholar]
- 13.Asrul S, Juliana J. Indoor air quality and its association with respiratory health among preschool children in urban and suburban area. Malaysian J Public Health 2017;Special Vol:78-88. [Google Scholar]
- 14.Chithra VS, Nagendra SMS. Indoor air quality investigations in a naturally ventilated school building located close to an urban roadway in Chennai, India. Build Environ 2012;54:159-67. [Google Scholar]
- 15.Gaffin JM, Hauptman M, Petty CR, et al. Nitrogen dioxide exposure in school classrooms of inner-city children with asthma. J Allergy Clin Immunol 2018;141:2249-55. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Lushchak VI. Free radicals, reactive oxygen species, oxidative stress and its classification. Chem Biol Interact 2014;224:164-75. [DOI] [PubMed] [Google Scholar]
- 17.Rahman Q, Abidi P, Afaq F, et al. Glutathione redox system in oxidative lung injury. Crit Rev Toxicol 1999;29:543-68. [DOI] [PubMed] [Google Scholar]
- 18.Pakpahan S, Wispriyono B, Hartono B, Jalaludin J. School indoor air quality and health risk on the junior high schools students in Depok, Indonesia. Malaysian J Med Health Sci 2019;15:114-23. [Google Scholar]
- 19.Nazariah SSN, Juliana J, Abdah MA. Interleukin-6 via sputum induction as biomarker of inflammation for indoor particulate matter among primary school children in Klang Valley, Malaysia. Glob J Health Sci 2013;5:93-105. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Kamaruddin AS, Jalaludin J, Choo CP. Indoor air quality and its association with respiratory health among malay preschool children in Shah Alam and Hulu Langat, Selangor. Adv Environ Biol 2015;9:17-26. [Google Scholar]
- 21.National Standardization Agency. [Udara ambien – Bagian 3: Cara Uji Kadar Nitrogen Dioksida (NO2) Dengan Metode Griess-Saltzman Menggunakan Spektrofotometer (Ambient Air – Part 3: How to test nitrogen dioxide (NO2) levels using the Griess-Saltzman method using a spectrophotometer)].[In Indonesian]. Jakarta: National Standardization Agency; 2017. [Google Scholar]
- 22.Fitriani A, Achmadi UF, Hartono B, et al. The effect of PM2.5 exposure on workers’ enzymatic superoxide dismutase (SOD) concentration at a ready-mix concrete factory in 2018. Indian J Public Heal Res Dev 2019;10:344-50. [Google Scholar]
- 23.Tipple TE, Rogers LK. Methods for the determination of plasma or tissue glutathione levels. Methods Mol Biol 2012;889:315-24. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Gadkari NM. Study of personal-indoor-ambient fine particulate matters among school communities in mixed urban-industrial environment in India. Environ Monit Assess 2010;165:365-75. [DOI] [PubMed] [Google Scholar]
- 25.Jan R, Roy R, Yadav S, Satsangi PG. Exposure assessment of children to particulate matter and gaseous species in school environments of Pune, India. Build Environ 2017;111:207-17. [Google Scholar]
- 26.Fromme H, Twardella D, Dietrich S, et al. Particulate matter in the indoor air of classrooms-exploratory results from Munich and surrounding area. Atmos Environ 2007;41:854-66. [Google Scholar]
- 27.Razali NYY, Latif MT, Dominick D, et al. Concentration of particulate matter, CO and CO2 in selected schools in Malaysia. Build Environ 2015;87:108-16. [Google Scholar]
- 28.Jyethi DS, Khillare PS, Sarkar S. Risk assessment of inhalation exposure to polycyclic aromatic hydrocarbons in school children. Environ Sci Pollut Res Int 2014;21:366-78. [DOI] [PubMed] [Google Scholar]
- 29.Choo CP, Jalaludin J, Hamedon TR, Adam NM. Preschools’ Indoor air quality and respiratory health symptoms among preschoolers in Selangor. Procedia Environ Sci 2015;30:303-8. [Google Scholar]
- 30.Chuersuwan N, Nimrat S, Lekphet S, Kerdkumrai T. Levels and major sources of PM2.5 and PM10 in Bangkok Metropolitan Region. Environ Int 2008;34:671-7. [DOI] [PubMed] [Google Scholar]
- 31.Pegas PN, Nunes T, Alves CA, et al. Indoor and outdoor characterisation of organic and inorganic compounds in city centre and suburban elementary schools of Aveiro, Portugal. Atmos Environ 2012;55:80-9. [Google Scholar]
- 32.Zora JE, Sarnat SE, Raysoni AU, et al. Associations between urban air pollution and pediatric asthma control in El Paso, Texas. Sci Total Environ 2013;448:56-65. 7 [DOI] [PubMed] [Google Scholar]
- 33.Godoi RHM, Godoi AFL, Goncalves Junior SJ, et al. Healthy environment — indoor air quality of Brazilian elementary schools nearby petrochemical industry. Sci Total Environ 2013;463-464:639-46. [DOI] [PubMed] [Google Scholar]
- 34.Nitschke M, Pilotto LS, Attewell RG, et al. A cohort study of indoor nitrogen dioxide and house dust mite exposure in asthmatic children. J Occup Environ Med 2006;48:462-9. [DOI] [PubMed] [Google Scholar]
- 35.Kurniasih A, Julia M, Setyati A. Superoxide dismutase levels and peak expiratory flow in asthmatic children. Paediatr Indones 2015;55:309-14. [Google Scholar]
- 36.Agustia M, Chundrayeti E, Lipoeto NI. [Hubungan Kadar Superoksida Dismutase dengan Tingkat Intelegensi Anak Sindrom Down (The relationship between superoxide dismutase levels and Down syndrome children’s intelligence level)]. Sari Pediatr 2018;20:202-6. [Google Scholar]
- 37.Mustafa MG, Tierney DF. Biochemical and metabolic changes in the lung with oxygen, ozone, and nitrogen dioxide toxicity. Am Rev Respir Dis 1978;118:1061-90. [DOI] [PubMed] [Google Scholar]
- 38.Bernard N, Saintot M, Astre C, et al. Personal exposure to nitrogen dioxide pollution and effect on plasma antioxidants personal exposure to nitrogen dioxide pollution and effect on plasma antioxidants. Arch Environ Health 2016;9896:122-8. [DOI] [PubMed] [Google Scholar]
- 39.Michelet F, Gueguen R, Leroy P, et al. Blood and plasma glutathione measured in healthy subjects by HPLC: Relation to sex, aging, biological variables, and life habits. Clin Chem 1995;41:1509-17. [PubMed] [Google Scholar]
- 40.Fitzpatrick AM, Jones DP, Brown LAS. Glutathione redox control of asthma: From molecular mechanisms to therapeutic opportunities. Antioxid Redox Signal 2012;17:375-408. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Franco R, Schoneveld OJ, Pappa A, Panayiotidis MI. The central role of glutathione in the pathophysiology of human diseases. Arch Physiol Biochem 2007;113:234-58. [DOI] [PubMed] [Google Scholar]
- 42.Sinha C, Seth K, Islam F, et al. Behavioral and neurochemical effects induced by pyrethroid-based mosquito repellent exposure in rat offsprings during prenatal and early postnatal period. Neurotoxicol Teratol 2006;28:472-81. [DOI] [PubMed] [Google Scholar]
- 43.Ghio AJ, Carraway MS, Madden MC. Composition of air pollution particles and oxidative stress in cells, tissues, and living systems. J Toxicol Environ Health B Crit Rev 2012;15:1-21. [DOI] [PubMed] [Google Scholar]
- 44.Delfino RJ, Staimer N, Vaziri ND. Air pollution and circulating biomarkers of oxidative stress. Air Qual Atmos Health 2013;4:37-52. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Gupta A, Nigam D, Gupta A, et al. Effect of pyrethroid-based liquid mosquito repellent inhalation on the blood-brain barrier function and oxidative damage in selected organs of developing rats. J Appl Toxicol 1999;19:67-72. [DOI] [PubMed] [Google Scholar]
- 46.Abdollahi M, Ranjbar A, Shadnia S, Nikfar S. Pesticides and oxidative stress : a review. Med Sci Monit 2004;10:141-8. [PubMed] [Google Scholar]
- 47.Kale M, Rathore N, John S, Bhatnagar D. Lipid peroxidative damage on pyrethroid exposure and alterations in antioxidant status in rat erythrocytes : a possible involvement of reactive oxygen species. Toxicol Lett 1999;105:197-205. [DOI] [PubMed] [Google Scholar]
- 48.Pryor WA, Stone K. Oxidants in cigarette smoke. Ann NY Acad Sci 1993;686:12-27. [DOI] [PubMed] [Google Scholar]
- 49.Yokus B, Mete N, Cakir U, Toprak G. Effects of active and passive smoking on antioxidant enzymes and antioxidant micronutrients. Biotechnol Biotech Eq 2015;19:117-23. [Google Scholar]
- 50.Gould NS, Min E, Gauthier S, et al. Lung glutathione adaptive responses to cigarette smoke exposure. Respir Res 2011;12:133. [DOI] [PMC free article] [PubMed] [Google Scholar]