Cross-sectional associations between ambient air pollution and respiratory signs and symptoms among young children in Tehran

Journal Pre-proof Cross-sectional associations between ambient air pollution and respiratory signs and symptoms among young children in Tehran Zahra Namvar, Masud Yunesian, Mansour Shamsipour, Mohammad Sadegh Hassanvand, Kazem Naddafi, Elahe Shahhosseini PII:

S1352-2310(20)30010-8

DOI:

https://doi.org/10.1016/j.atmosenv.2020.117268

Reference:

AEA 117268

To appear in:

Atmospheric Environment

Received Date: 21 February 2019 Revised Date:

2 January 2020

Accepted Date: 5 January 2020

Please cite this article as: Namvar, Z., Yunesian, M., Shamsipour, M., Hassanvand, M.S., Naddafi, K., Shahhosseini, E., Cross-sectional associations between ambient air pollution and respiratory signs and symptoms among young children in Tehran, Atmospheric Environment (2020), doi: https:// doi.org/10.1016/j.atmosenv.2020.117268. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier Ltd.

Manuscript title: “Cross-sectional associations between ambient air pollution and respiratory signs and symptoms among young children in Tehran”

Credit Author Statement Zahra Namvar: Investigation, Writing - Original Draft. Masud Yunesian: Conceptualization, Project administration. Mansour Shamsipour: Formal analysis, Writing - Review & Editing. Mohammad Sadegh Hassanvand: Conceptualization, Methodology, Writing - Review & Editing. Kazem Naddafi: Methodology. Elahe Shahhosseini: Investigation.

3

Cross-sectional associations between ambient air pollution and respiratory signs and symptoms among young children in Tehran

4 5

Zahra Namvar a, Masud Yunesian a,b, Mansour Shamsipour c,*, Mohammad Sadegh Hassanvand b,**, Kazem Naddafi a,b, Elahe Shahhosseini a

6 7

a

8 9

b

10 11

c

12

*Correspondence author

13

** Co-correspondence author

14

Abstract:

15

Exposure to ambient air pollutants may significantly affect the incidence of respiratory symptoms and lung function in children. The present study examined the associations between exposure to ambient air pollutants and respiratory symptoms in children. In this cross-sectional study, 1070 children under the age of seven years were recruited from 61 day-care centers of Tehran in 2015. Initially, day-care centers were selected at a radius of 2 km from the air pollution monitoring stations, and subsequently all the children attending these day-care centers were interviewed. The data on the respiratory complaints of children were obtained by using the ATS questionnaire (ATS-DLD-78-C). Moreover, the annual average concentration of pollutants was calculated based on the time children spent at home and at the day-care center using the air pollution monitoring stations. Crude and adjusted logistic regression analysis was conducted. The findings indicated that ambient air SO2 and NO2 concentrations near home were associated with current asthma for 1 part per billion (ppb) increase with an OR of 1.20 (1.00 to 1.45) and 1.08 (1.01 to 1.15), respectively. The odds of developing persistent phlegm for each unit (ppm) of raise in the average annual concentration of CO in ambient air near home (OR 1.40; 1.09 to 1.81) increased as well. The daily mean concentration of PM2.5, PM10, and SO2 was higher than the limits provided in the World Health Organization (WHO) air quality guidelines (AQGS). Moreover, the

1 2

16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33

Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran Department of Research Methodology and Data Analysis, Institute for Environmental Research, Tehran University of Medical Sciences, Tehran, Iran

37

prevalence of severe wheezing, asthma history, and bronchitis was higher in boys. Therefore, long-term exposure to ambient air pollutants such as SO2, NO2, and CO may be associated with an increase in current asthma and persistent phlegm in children.

38

Keywords: Respiratory symptoms, Air pollution, Day-care centers

39

1. Introduction

40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61

Air pollution is a global problem and the most important environmental risk factor for human health (Schultz et al., 2017). According to the World Health Organization (WHO) 2016 report, air pollution is affecting all areas of the world, and about seven million people annually lose their lives due to pollution. Approximately 90% of the air breathed by humans does not match the WHO quality guidelines. Epidemiologic evidence and air quality data on the health effects of pollutants are rapidly growing (World Health Organization, 2016). Ambient air pollution has significant effects on bronchitis or symptoms such as cough, phlegm, and asthma and asthmatic symptoms, including wheezing (Hoek et al., 2012). From among different air pollutants, particulate matter (PM) has become a major concern for human health (Ma et al., 2008, Pope III, 2007). Numerous studies have reported the association between PM concentration and increased respiratory symptoms (Ma et al., 2008, Hasunuma et al., 2018, Linares et al., 2010, Hoek et al., 2012) and reduced pulmonary function (Hoek et al., 2012, Roy et al., 2012, Yoda et al., 2018). Many of these studies have investigated PM with an aerodynamic diameter of <10 µm (PM10), indicating that particles are associated with respiratory symptoms and lung function (Ma et al., 2008, Roy et al., 2012, Hoek et al., 2012). Nitrogen dioxide (NO2) is associated with an increase in respiratory symptoms such as asthma exacerbation, wheezing, and bronchitis (Shima and Adachi, 2000). Sulfur dioxide (SO2) also increases respiratory symptoms in susceptible and allergic children and impacts lung function (Dong et al., 2011).

62 63 64 65 66 67 68

A recent study in 2016 estimated about 41,000 deaths (95% uncertainty interval [UI] 35634, 47014) and about 3,000,000 years of life lost (YLL) (95% UI: 2632101, 3389342) attributable to the long-term exposure to PM2.5 in Iran (Shamsipour et al., 2019). Tehran, the capital of Iran, is the largest city in the country with a population of about 9 million (Faridi et al., 2018), facing serious air pollution like other large cities (Naddafi et al., 2012). In general, 20% of the total energy in Iran is consumed in Tehran (Naddafi et al., 2012).

34 35 36

69 70 71 72 73 74 75 76 77 78 79 80 81

From among different age groups, children are more vulnerable to air pollution effects because their lung volume-body ratio is larger and their airway epithelium has a higher permeability to air pollutants (Roy et al., 2012); furthermore, longterm exposure to ambient air pollution can be linked to the incidence of respiratory symptoms and lung function in children (Hoek et al., 2012). According to various studies, the association between ambient air pollutants and respiratory symptoms differs depending on the type of pollutants and respiratory symptoms (Dong et al., 2011, Hwang and Lee, 2010, Gao et al., 2014), which may be due to different sources of air pollutants. Therefore, illumination of the impact of air pollutants on respiratory systems requires more studies in various locations and on different populations. The present study aimed to assess the association between chronic exposure to PM10, PM2.5, NO2, SO2, and CO and children's respiratory symptoms in the megacity of Tehran.

82

2. Materials and Methods

83

2.1. Study area and period This cross-sectional study was conducted in 2015 on children under the age of seven years in the day-care centers of Tehran. 2.2. Selection of day-care centers To select the day-care centers, a list of Tehran’s day-care centers was first prepared and their phone numbers were obtained from Tehran’s Welfare Organization. Then, by handing the phone numbers to the Geographic and Spatial Information Office, the geographical coordinates of all the day-care centers were obtained. These coordinates were determined by GIS software on the map of Tehran. Of all the day-care centers, those located less than 2000 m away from air quality monitoring stations were initially chosen. The final day-care centers for sampling the children were selected based on their distance from the stations and the volume of data recorded by the stations. Accordingly, records from monitoring stations of the Tehran Air Quality Control Company (Fig. 1) were collected in three-year intervals, and stations with more than 50% hourly data per year were chosen. From all the available stations, only eight stations met the above-mentioned criteria. Therefore, all day-care centers at a radius of 2 km from the eight monitoring stations with more than 50% hourly data per year were included in this study.

84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105

2.3. Exposure assessment The mean daily concentrations for all pollutants were calculated based on hourly means registered in monitoring stations. In order to estimate missed data, i.e. the mean daily concentrations, the method developed by Rückerl et al. (Rückerl et al., 2014) and Berglind et al. (Berglind et al., 2009) was adopted. Briefly, the missing

106 107

data from monitoring stations were estimated with the following equations (Rückerl et al., 2014, Berglind et al., 2009):

108

=

109

̅ = ∑

110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129

+ ̅

(1) (2)

where is the imputed daily mean of each air pollutant concentration on timepoint i of monitor j, denotes the average for all non-missing days of monitor j, represents the standard deviation (SD) of each air pollutant concentration of monitor j, ̅ indicates the average standardized value of day i over all monitoring stations which recorded the data of day i, is daily concentration on time-point i of monitor k, shows the average for all days of monitor k, and represents the SD of each air pollutant concentration of monitor k. Finally, the remaining missing daily data were provided by using the average of the daily averages before and after the missing data. Children's exposure assessment was performed in two parts: exposure to ambient air pollutants (including PM10, PM2.5, NO2, SO2, and CO) in day-care centers and at home. To this end, children's parents were requested to provide the researchers with the current and previous locations of their houses. Subsequently, their exposure was estimated based on the air pollution concentration at the nearest outdoor monitoring station. As for the children’s exposure assessment in day-care centers, because children had changed their day-care centers every year, the address of all the previous day-care centers was not available. Thus, the address for the last day-care center was taken into account. The distribution of children's houses and monitoring stations is depicted in Fig. 1. Details on day-care centers and home exposure assessment are presented below.

130 131

2.3.1. Exposure assessment at the day-care centers

132 133 134 135 136 137

The mean daily concentrations of ambient air pollutants over the last year at the nearest monitoring station (at a radius of 2 km of the day-care center) was considered as the level of exposure for all children at that day-care center. In some cases where two or more stations were located at a radius of 2 km of the day-care center, the mean daily concentrations (in the past year) of two or three monitoring stations were used to determine pollutant exposure.

138

2.3.2. Exposure assessment at home

139 140 141 142 143 144

The mean daily concentrations of all pollutants over the past three years at the nearest outdoor monitoring station (while considering their current and previous residence) were regarded as the children's exposure level. For children aged less than three years, the mean daily concentrations of ambient air pollutants at the nearest station from the beginning of birth to the time of the interview were considered as the level of exposure.

145 146 147 148 149 150

Based on the information provided in the questionnaire about the phone numbers and zip code of the children's houses in the current and previous addresses (from the birth of the child), the coordinates of the children's current and previous houses were determined by referring to the Geographic and Spatial Information Office or manually by using the map of Tehran available on the Municipality of Tehran website.

151 152 153 154 155 156 157

Of the 1528 children participating in this study, the houses of 1070 children were located at a radius of 2 km from the eight stations, and the residences of 458 children were around stations other than the eight selected ones. Therefore, the analysis was performed on 1070 children. Since some children resided in places other than their birthplaces, different scenarios were defined to determine their exposure to pollutants while considering these displacements as well as the proximity to the stations.

158 159 160 161 162 163 164 165 166 167 168 169

In the first scenario, for children whose houses remained unchanged since birth and were located at a radius of 2 km from a station, the average concentration of the same station was regarded as the child’s home exposure. In the second scenario, for children whose residence remained unchanged at a 2 km radius between two stations, the two stations’ data were employed to determine the average concentration of pollutants. In other cases, the average concentration of exposure to ambient concentrations near the house was determined according to the previous and current address of the houses around the stations. In the third scenario, the current address was within the radius of a station, and the previous address was within the radius of another station. In the fourth scenario, the current address was at a radius of 2 km from two stations and the previous address was at a radius of 2 km from one station.

170 171 172 173

174 175 176

177 178

Fig. 1. The map of air pollution monitoring stations and children’ houses

179

2.4. Definition of symptoms

180 182

The ATS questionnaire (ATS-DLD-78-C) (Ferris, 1978) was employed to collect data on respiratory symptoms and childhood disease history. The definition of symptoms is presented in Table 1.

183

Table 1. Definition of symptoms

181

Respiratory symptoms

Definition

Persistent cough

Does the child cough most days during the cold or non-cold period (four days or more per week) for three months of the year?

Persistent phlegm

Does the child have congestion in the chest or bring up phlegm on most days during the cold or non-cold period (four days or more per week) for about three months of the year?

Mild wheezing

Has your child ever had a wheeze during a cold or non-cold period?

Severe wheezing

Has your child ever had a wheeze mostly during the day or at night?

Cough spells and chest Has the child ever had cough spells, chest pain, or sputum for a week pain or more during a year? Current asthma

Does the child receive medication for asthma?

Asthma history Bronchitis

Has the child ever had wheeze spells leading to shortness of breath? Has any physician ever told you that the child has asthma? Has the child ever been hospitalized before two years of age for severe chest diseases or acute bronchitis?

184 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201

2.5. Validity and reliability assessment of the outcome assessment instrument The ATS questionnaire was first translated into Persian, and then the Persian version was translated into English by another person who was an expert in the English language. Subsequently, the back-translated questionnaire was compared with the original English questionnaire by a third person, and content validity was verified by a group of experts in the field, including a pediatrician, two epidemiologists, and two environmental health professionals. Finally, the Persian questionnaire was prepared. To assess the comprehensiveness and reliability of the questionnaire, the translated Persian questionnaire was evaluated by the test-retest method on 20 children. To this end, the questionnaire was delivered to parents in two stages with a two-week interval. On the first page of the questionnaire, a consent form was attached to explain the purpose of the study, and the parents completed the questionnaire after signing the form. The questionnaires were delivered to the day-care centers at the beginning of the week and were collected at the end of the week. Kappa coefficient was used to assess the correspondence between the responses of parents to the questions in two steps. The data on parental smoking and that of other family members were obtained through questionnaires.

202

2.6. Statistical analysis

203 204 205 206 207 208 209 210 211

The characteristics of the participants were described by mean ± SD or frequencies in number and percentage. Pearson Chi-Square and t test were run to test the association between sex, respiratory symptoms, and age. Crude and adjusted logistic regression analyses were performed to assess the association between air pollutants and respiratory symptoms. Age, sex, and secondhand smoke covariates were considered as adjusted variables. Odds ratios (ORs) with 95% confidence intervals (CIs) per 1 unit increase in the concentration of air pollutants were also taken into consideration, and P-values <0.05 were regarded as statistically significant.

212

3. Results and Discussion

213

In the present study, 61 out of 121 day-care centers that met the eligibility criteria were included. In these day-care centers, 3639 questionnaires were distributed and 1811 completed questionnaires were collected with a response rate of 49.7%. Since 300 questionnaires were incomplete, the researchers attempted to resolve the

185

214 215 216

217 218 219 220 221 222 223

deficiencies by telephone interviews, and 200 questionnaires were thus completed and added to the valid questionnaires. As the coordinates of about 44 locations could not be determined, they were excluded from the study. Moreover, since 597 locations were located out of the stations’ coverage area, these were also excluded. The data included in the final analysis belonged to 1070 children, including 590 boys and 480 girls. The progress of day-care centers and individuals through the phases of the study is presented in Fig. 2.

224

225 226 227

Fig. 2. Flow diagram of the progress of day-care centers and individuals through the phases of the study

228

232

Based on Table 2, there were more boys than girls in the sample, and the majority of children (59%) belonged to the age group of four to five years. The prevalence of father’s smoking was more than that of mothers, and also fathers smoked more than mothers in the presence of children.

233

Table 2. Descriptive/demographic characteristics

229 230 231

Characteristic

n (%)

Participants

1070

Sex boy girl Age groups 0-3 years 4-5 years

590(55.14) 480(44.86) 296(27.66) 635(59.34) 139(13)

>5 years

Smoking Father’s smoking Mother’s smoking Other family members’ smoking Father smoking in the presence of the child Mother smoking in the presence of the child

189 (17.66) 25(2.33) 83(7.76) 78(2.29) 12(1.12)

234 235 236 237 238 239 240 241

Table 3 presents the total and sex specific prevalence of different respiratory symptoms. Evidently, the prevalence of severe wheezing, asthma history, and bronchitis significantly differs for boys and girls. Peters et al. observed that the prevalence of asthma was increased in girls but not in boys (Peters et al., 1999). Moreover, in Liu’s study, the prevalence of respiratory symptoms was higher in boys (Liu et al., 2013). There was no statistically significant association between sex and age in the present study.

242 243

Table 3. Prevalence of respiratory symptoms (n=1070)

Characteristic

Children Boy(590)

Girl (480)

Total (1070)

P-value

143(24.24) 143(24.24) 94(15.93) 70(11.86) 151(25.59) 8(1.36) 78(13.22) 29(4.92) 4.24(±1.23)

112(23.33) 99(20.63) 62(12.92) 39(8.13) 106(22.08) 4(0.83) 39(8.13) 11(2.29) 4.14(±1.20)

255(23.83) 242(22.62) 156(14.58) 109(10.19) 257(24.02) 12(1.12) 117(10.93) 40(3.74) 4.20(±1.22)

0.730 0.160 0.164 0.044* 0.181 0.419 0.008* 0.024* 0.196

Respiratory symptoms

244

Persistent cough n(%) Persistent phlegm n(%) Mild wheezing n(%) Severe wheezing n(%) Cough spells and chest pain n(%) Current asthma n(%) Asthma history n(%) Bronchitis n(%) Age(year) *p-value<0.05

255

Table 4 gives the descriptive statistics (mean ± SD) of the participants’ exposure to ambient air pollutants near the day-care centers and homes. The estimated mean ± SD of ambient pollutants’ concentration near the day-care centers and homes was almost close to each other. On the other hand, the maximum concentration of ambient pollutants, including PM10, PM2.5, NO2, SO2, and CO, was higher near the houses than the day-care center. Daily mean concentration of PM2.5 (day-care center: 27.9±5.1 µg/m3, home: 29.3±5.9 µg/m3), PM10 (day-care center: 66.5±14.1 µg/m3, home: 68.2±13.8 µg/m3), and SO2 (day-care center: 48.21±7.59 µg/m3, home: 50.83±11.52 µg/m3) was higher than the limits presented in the WHO air quality guidelines (AQGS) (Guerreiro et al., 2016) (PM2.5=25 µg/m3, PM10=50 µg/m3, SO2=20 µg/m3).

256 257

Table 4. Summary of statistics for the exposure concentration of children to ambient air pollutants near the day-care centers and homes

245 246 247 248 249 250 251 252 253 254

Place

Mean

SD*

Min

Max

PM2.5 (µg/m3) PM10 (µg/m3) SO2 (ppb) NO2 (ppb) CO (ppm)

27.9 66.5 18.4 48.9 3.0

5.1 14.1 2.9 13.6 0.6

21.2 49.9 14.4 33.6 1.8

37.7 93.2 23.9 72.4 3.8

PM2.5 (µg/m3) PM10 (µg/m3) Homeb SO2 (ppb) NO2 (ppb) CO (ppm) *SD: standard deviation

29.3 68.2 19.4 47.5 3.2

5.9 13.8 4.4 11.9 0.8

1.4 2.8 0.8 1.6 0.9

46.9 104.7 28.6 80.1 4.7

Day-care centera

258 259 260

a b

Air pollutant

mean daily concentrations of pollutants over the last year. mean daily concentrations of pollutants over three years.

261 262 263 264 265

The proportion of hourly mean coverage through stations is presented in Table 5. Overall, the stations had an acceptable coverage. The highest percentage of station coverage belonged to CO and NO2 significant gaseous air pollutants, whereas the lowest percentage belonged to SO2 pollutant.

266

Table 5. The coverage of hourly average at stations (%) Stations S1 S2 S3 S4 S5 S6 S7 S8

PM2.5 68.60 ~ 50 65.31 57.07 ~ 50 ~ 50 59.80 67.82

PM10 69.25 76.90 70.48 74.59 ~ 50 68.56 78.08 73.60

Air pollutants SO2 ~ 50 67.85 63.03 50 ~ 50 ~ 50 75.84 ~ 50

NO2 74.29 63.97 67.97 82.72 53.71 58.34 84.81 82.39

CO 70.17 76.58 71.97 76.84 80.37 81.47 79.89 86.54

267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291

The association between ambient air pollutants and respiratory symptoms was also examined using crude and adjusted regression analysis. Because no association was found between ambient air pollutants and respiratory symptoms in the crude models, only the results of the adjusted models are reported. Based on Table 6, in the adjusted model (adjusted with age, sex, and secondhand smoke variables),no statistically significant associations were found between exposure to PM2.5, PM10, SO2, NO2, and CO ambient concentration near the day-care centers with any respiratory symptom such as persistent cough and phlegm, mild and severe wheezing, cough spells and chest pain, current asthma, asthma history, and bronchitis. Nevertheless, significant associations were found between exposure to SO2, NO2, and CO, and respiratory symptoms near houses. Results of some studies on the same topic showed that air pollution can significantly affect respiratory function (Ma et al., 2008, Clark et al., 2010, Bernstein, 2012). The findings of the present study revealed a positive association between SO2 and current asthma. However, Clark et al. observed a statistically significant association between increased asthma and daily exposure to PM10, NO, NO2, SO2, and CO (Clark et al., 2009). In another study, there was a significant association between SO2 and persistent cough, persistent phlegm, and current asthma (Pan et al., 2010). Furthermore, a significant association was observed between the NO2 concentrations of ambient air near houses with current asthma (OR 1.08 (1.011.15)), while there was no association between NO2 ambient concentration near the day-care centers and houses with other respiratory symptoms. In a cohort study, the findings revealed that the increase of each unit exposure to NO2 (ppb) increased

292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320

wheezing and asthma with odds ratios of 1.76 (1.04-3.23) and 2.10 (1.10-4.75), respectively (Shima and Adachi, 2000). On the other hand, Hwang and Lee in a cross-sectional study reported that NO2 was related to the prevalence of bronchitis with an OR of 1.81(1.14-2.86) (Hwang and Lee, 2010). In contrast, in some studies, no association was observed between ambient air NO2 and the incidence of respiratory diseases in children (Zhao et al., 2008, Zhang et al., 2002). Moreover, in Braun-Fahrlander’s study, no association was observed between NO2 and respiratory symptoms (Braun-Fahrlander et al., 1992). Another pollutant investigated here was CO, which showed a positive association with persistent phlegm, with the odds ratios of 1.40 (1.09 to 1.81); however, there was no statistically significant association between CO and other respiratory symptoms. This finding is inconsistent with the result reported by Hwang and Lee (Hwang and Lee, 2010) who concluded that CO was positively associated with the prevalence of bronchitis (Hwang and Lee, 2010). There was also a significant association between SO2, NO2, and CO concentrations of ambient air near hoses with current asthma, persistent phlegm, and current asthma, respectively. Nevertheless, these patterns were not the same for day-care center ambient levels.

321 322

323

Table 6. The association between ambient air pollution near the day-care centers and homes with respiratory symptom Pollutant

PM2.5

PM10

SO2

NO2

CO

0.98(0.95-1.01) 0.98(0.95-1.01 0.97(0.94-1.01) 0.97(0.93-1.01) 0.97(0.94-1.00) 0.96(0.85-1.09) 0.96(0.92-1.00) 1.01(0.95-1.08)

1.01(0.99-1.04) 1.01(0.99-1.04) 1.00(0.97-1.03) 1.00(0.96-1.03) 1.00(0.98-1.03) 1.01(0.90-1.12) 1.02(0.99-1.05) 0.98(0.93-1.03)

1.11(0.98-1.26) 1.10(0.96-1.24) 1.00(0.87-1.16) 0.97(0.82-1.15) 1.05(0.93-1.19) 1.18(0.68-2.04) 1.09(0.92-1.29) 0.95(0.73-1.24)

1.03(1.00-1.06) 1.02(0.99-1.05) 1.01(0.97-1.04) 0.99(0.96-1.04) 1.01(0.98-1.04) 1.04(0.92-1.18) 1.02(0.98-1.07) 0.98(0.92-1.04)

0.81(0.52-1.26) 0.87(0.55-1.37) 0.84(0.49-1.43) 0.92(0.47-1.78) 0.89(0.56-1.39) 0.87(0.16-4.53) 0.84(0.46-1.53) 0.74(0.27-1.97)

0.98(0.95-1.01) 1.02(0.99-1.06) 1.00(0.96-1.04) 1.00(0.96-1.05) 0.99(0.95-1.02) 0.92(0.75-1.12) 0.98(0.93-1.03) 1.00(0.92-1.07)

0.99(0.97-1.00) 0.99(0.98-1.01) 0.99(0.98-1.01) 0.99(0.97-1.01) 1.00(0.98-1.01) 1.03(0.96-1.10) 1.01(0.99-1.03) 1.00(0.97-1.03)

0.97(0.93-1.03) 0.97(0.93-1.01) 0.97(0.92-1.02) 0.96(0.91-1.02) 1.00(0.96-1.04) 1.20(1.00-1.45)* 1.00(0.94-1.07) 0.97(0.89-1.06)

1.00(0.98-1.01) 1.00(0.98-1.01) 1.00(0.98-1.02) 1.00(0.97-1.02) 1.00(0.99-1.02) 1.08(1.01-1.15)* 1.01(0.98-1.03) 0.98(0.94-1.02)

0.95(0.74-1.22) 1.40(1.09-1.81)* 1.08(0.8-1.46) 1.17(0.83-1.66) 1.05(0.82-1.35) 0.65(0.17-2.50) 1.14(0.8-1.61) 1.03(0.59-1.79)

Day-care center Persistent cough Persistent phlegm Mild wheezing Severe wheezing Cough spells and chest pain Current asthma Asthma history Bronchitis

Home Persistent cough Persistent phlegm Mild wheezing Severe wheezing Cough spells and chest pain Current asthma Asthma history Bronchitis

324

Multivariate model: adjusted for sex, age, and secondhand smoke

325

*p-value<0.05

326 327 328 329

330 331 332 333 334 335 336

There were some limitations to the presentstudy. The first limitation was the lack of access to the address of the mothers’ houses during pregnancy or early childhood. Therefore, the association between ambient air pollutants and respiratory symptoms was studied since birth for children younger than three years and in the last three years for children over three years of age. In some cases, due to the lack of access to the children’s previous home address, the participants had to be excluded from the study. The second limitation was the lack of personal

340

exposure assessment, similar to many other studies in this domain. The third limitation was moderate participation (participation rate of 49.7%), while the participation rate was 91.68% and 87%, respectively, in Liu’s study (Liu et al., 2013) and Hwang and Lee’s study (Hwang and Lee, 2010).

341

4. Conclusion

342

347

The findings of this study indicated that the daily mean concentration of ambient air pollutants is higher than the limits of WHO air quality guidelines. Also, ambient air pollution is associated with respiratory symptoms, from among which an association is detected between NO2 and SO2 concentrations with current asthma, and CO concentration with persistent phlegm. Moreover, the prevalence of wheezing, bronchitis, and asthma is higher in boys as compared to girls.

348

Competing interests

349

There is no actual or potential conflict of interest among the authors.

350

Acknowledgments

351

355

The authors acknowledge the Institute for Environmental Research (IER) of the Tehran University of Medical Sciences for financially supporting this research (grant number 94-01-46-28285). The authors also thank the Air Quality Control Company for air pollutants data and appreciate the day-care centers for their cooperation.

356

References

357 358 359 360 361

Berglind, N., Bellander, T., Forastiere, F., Von Klot, S., Aalto, P., Elosua, R., Kulmala, M., Lanki, T., Löwel, H. & Peters, A. 2009. Ambient Air Pollution And Daily Mortality Among Survivors Of Myocardial Infarction. Epidemiology, 110-118. https://doi.org/10.1097/EDE.0b013e3181878b50. Bernstein, D. I. 2012. Traffic-Related Pollutants And Wheezing In Children. Journal Of Asthma, 49, 5-7. https://doi.org/10.3109/02770903.2011.641049.

337 338 339

343 344 345 346

352 353 354

362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411

Braun-Fahrlander, C., Ackermann-Liebrich, U., Schwartz, J., Gnehm, H. P., Rutishauser, M. & Wanner, H. 1992. Air Pollution And Respiratory Symptoms In Preschool Children1-3. The American Review Of Respiratory Disease, 145, 42-47. https://doi.org/10.1164/ajrccm/145.1.42. Clark, N. A., Demers, P. A., Karr, C. J., Koehoorn, M., Lencar, C., Tamburic, L. & Brauer, M. 2010. Effect Of Early Life Exposure To Air Pollution On Development Of Childhood Asthma. Environmental Health Perspectives, 118, 284. https://doi.org/10.1289/ehp.0900916. Dong, G.-H., Chen, T., Liu, M.-M., Wang, D., Ma, Y.-N., Ren, W.-H., Lee, Y. L., Zhao, Y.-D. & He, Q.C. 2011. Gender Differences And Effect Of Air Pollution On Asthma In Children With And Without Allergic Predisposition: Northeast Chinese Children Health Study. Plos One, 6, E22470. https://doi.org/10.1371/journal.pone.0022470. Faridi, S., Shamsipour, M., Krzyzanowski, M., Künzli, N., Amini, H., Azimi, F., Malkawi, M., Momeniha, F., Gholampour, A. & Hassanvand, M. S. 2018. Long-Term Trends And Health Impact Of Pm 2.5 And O 3 In Tehran, Iran, 2006–2015. Environment International, 114, 37-49. https://doi.org/10.1016/j.envint.2018.02.026. FERRIS, B. 1978. Epidemiology standardization project. II. Recommended respiratory disease questionnaires for use with adults and children in epidemiological research. Am Rev Respir Dis, 118, 7-53. Gao, Y., Chan, E. Y., Li, L., Lau, P. W. & Wong, T. W. 2014. Chronic Effects Of Ambient Air Pollution On Respiratory Morbidities Among Chinese Children: A Cross-Sectional Study In Hong Kong. Bmc Public Health, 14, 105. https://doi.org/10.1186/1471-2458-14-105. GUERREIRO, C., ORTIZ, A. G., DE LEEUW, F., VIANA, M. & HORÁLEK, J. 2016. Air quality in Europe-2016 report, Publications Office of the European Union. Hasunuma, H., Yamazaki, S., Tamura, K., Hwang, Y. H., Ono, R., Amimoto, Y., Askew, D. J. & Odajima, H. 2018. Association Between Daily Ambient Air Pollution And Respiratory Symptoms In Children With Asthma And Healthy Children In Western Japan. Journal Of Asthma, 1-7. https://doi.org/10.1080/02770903.2017.1369988. Hoek, G., Pattenden, S., Willers, S., Antova, T., Fabianova, E., Braun-Fahrländer, C., Forastiere, F., Gehring, U., Luttmann-Gibson, H. & Grize, L. 2012. Pm10 And Children's Respiratory Symptoms And Lung Function In The Paty Study. European Respiratory Journal, Erj000262011. https://doi.org/10.1183/09031936.00002611 Hwang, B.-F. & Lee, Y. L. 2010. Air Pollution And Prevalence Of Bronchitic Symptoms Among Children In Taiwan. Chest, 138, 956-964. https://doi.org/10.1378/chest.09-2600. Linares, B., Guizar, J. M., Amador, N., Garcia, A., Miranda, V., Perez, J. R. & Chapela, R. 2010. Impact Of Air Pollution On Pulmonary Function And Respiratory Symptoms In Children. Longitudinal Repeated-Measures Study. Bmc Pulmonary Medicine, 10, 62. https://doi.org/10.1186/1471-246610-62. LIU, M.-M., WANG, D., ZHAO, Y., LIU, Y.-Q., HUANG, M.-M., LIU, Y., SUN, J., REN, W.-H., ZHAO, Y.-D. & HE, Q.-C. 2013. Effects of outdoor and indoor air pollution on respiratory health of Chinese children from 50 kindergartens. Journal of epidemiology, 23, 280-287. https://doi.org/10.2188/jea.JE20120175. Ma, L., Shima, M., Yoda, Y., Yamamoto, H., Nakai, S., Tamura, K., Nitta, H., Watanabe, H. & Nishimuta, T. 2008. Effects Of Airborne Particulate Matter On Respiratory Morbidity In Asthmatic Children. Journal Of Epidemiology, 18, 97-110. https://doi.org/10.2188/jea.JE2007432. Naddafi, K., Hassanvand, M. S., Yunesian, M., Momeniha, F., Nabizadeh, R., Faridi, S. & Gholampour, A. 2012. Health Impact Assessment Of Air Pollution In Megacity Of Tehran, Iran. Iranian Journal Of Environmental Health Science & Engineering, 9, 28. https://doi.org/10.1186/17352746-9-28. World Health Organization. 2016. Ambient Air Pollution: A Global Assessment Of Exposure And Burden Of Disease.

412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448

PAN, G., ZHANG, S., FENG, Y., TAKAHASHI, K., KAGAWA, J., YU, L., WANG, P., LIU, M., LIU, Q. & HOU, S. 2010. Air pollution and children's respiratory symptoms in six cities of Northern China. Respiratory medicine, 104, 1903-1911. https://doi.org/10.1016/j.rmed.2010.07.018. PETERS, J. M., AVOL, E., NAVIDI, W., LONDON, S. J., GAUDERMAN, W. J., LURMANN, F., LINN, W. S., MARGOLIS, H., RAPPAPORT, E. & GONG JR, H. 1999. A study of twelve Southern California communities with differing levels and types of air pollution: I. Prevalence of respiratory morbidity. American journal of respiratory and critical care medicine, 159, 760-767. https://doi.org/10.1164/ajrccm.159.3.9804143. POPE III, C. A. 2007. Mortality effects of longer term exposures to fine particulate air pollution: review of recent epidemiological evidence. Inhalation toxicology, 19, 33-38. https://doi.org/10.1080/08958370701492961. Roy, A., Hu, W., Wei, F., Korn, L., Chapman, R. S. & Zhang, J. J. 2012. Ambient Particulate Matter And Lung Function Growth In Chinese Children. Epidemiology (Cambridge, Mass.), 23, 464. https://doi.org/10.1097/EDE.0b013e31824cbd6d. Rückerl, R., Hampel, R., Breitner, S., Cyrys, J., Kraus, U., Carter, J., Dailey, L., Devlin, R. B., DiazSanchez, D. & Koenig, W. 2014. Associations Between Ambient Air Pollution And Blood Markers Of Inflammation And Coagulation/Fibrinolysis In Susceptible Populations. Environment International, 70, 32-49. https://doi.org/10.1016/j.envint.2014.05.013. Schultz, E. S., Litonjua, A. A. & Melén, E. 2017. Effects Of Long-Term Exposure To Traffic-Related Air Pollution On Lung Function In Children. Current Allergy And Asthma Reports, 17, 41. https://doi.org/10.1007/s11882-017-0709-y. SHAMSIPOUR, M., HASSANVAND, M. S., GOHARI, K., YUNESIAN, M., FOTOUHI, A., NADDAFI, K., SHEIDAEI, A., FARIDI, S., AKHLAGHI, A. A. & RABIEI, K. 2019. National and sub-national exposure to ambient fine particulate matter (PM2. 5) and its attributable burden of disease in Iran from 1990 to 2016. Environmental Pollution, 255, 113173. https://doi.org/10.1016/j.envpol.2019.113173. Shima, M. & Adachi, M. 2000. Effect Of Outdoor And Indoor Nitrogen Dioxide On Respiratory Symptoms In Schoolchildren. International Journal Of Epidemiology, 29, 862-870. https://doi.org/10.1093/ije/29.5.862. Yoda, Y., Takagi, H., Wakamatsu, J., Ito, T. & Shima, M. Effects Of Particulate Air Pollution On Pulmonary Function Among Healthy Students. Isee Conference Abstracts, 2018. Zhang, J. J., Hu, W., Wei, F., Wu, G., Korn, L. R. & Chapman, R. S. 2002. Children's Respiratory Morbidity Prevalence In Relation To Air Pollution In Four Chinese Cities. Environmental Health Perspectives, 110, 961. https://doi.org/10.1289/ehp.02110961. Zhao, Z., Zhang, Z., Wang, Z., Ferm, M., Liang, Y. & Norbäck, D. 2008. Asthmatic Symptoms Among Pupils In Relation To Winter Indoor And Outdoor Air Pollution In Schools In Taiyuan, China. Environmental Health Perspectives, 116, 90. https://doi.org/10.1289/ehp.10576.

Highlights (for review): • Ambient air pollution in Tehran increase respiratory symptoms in children under the age of seven • Long-term exposure to NO2, SO2 and CO ambient air near the home increases current asthma and persistent phlegm in children • The respiratory signs and symptoms of severe wheezing, asthma history, and bronchitis were more common in boys.

All authors have approved the manuscript and agree with its submission to the Atmospheric

Environment and there exists no potential conflict of interest among authors.

Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: