Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2018 Jan 1.
Published in final edited form as: J Allergy Clin Immunol Pract. 2016 Sep 15;5(1):154–159.e3. doi: 10.1016/j.jaip.2016.07.018

School Environmental Intervention to Reduce Particulate Pollutant Exposures for Children with Asthma

Iny Jhun 1, Jonathan M Gaffin 1,2, Brent A Coull 3, Michelle F Huffaker 1,4, Carter R Petty 5, William J Sheehan 1,4, Sachin N Baxi 1,4, Peggy S Lai 1,6,7, Choong-Min Kang 7, Jack M Wolfson 7, Diane R Gold 1,7,8, Petros Koutrakis 7, Wanda Phipatanakul 1,4
PMCID: PMC5222771  NIHMSID: NIHMS812811  PMID: 27641483

Abstract

Background

Home-based interventions to improve indoor air quality have demonstrated benefits for asthma morbidity, yet little is known about the effect of environmental interventions in the school setting.

Objective

We piloted the feasibility and effectiveness of a classroom-based air cleaner intervention to reduce particulate pollutants in classrooms of children with asthma.

Methods

In this pilot randomized controlled trial, we assessed the effect of air cleaners on indoor air particulate pollutant concentrations in 18 classrooms (9 control, 9 intervention) in 3 urban elementary schools. We enrolled 25 asthmatic children (13 control, 12 intervention) aged 6–10 years old. Classroom air pollutant measurements and spirometry were completed once prior to and twice after randomization. Asthma symptoms were surveyed every 3 months.

Results

Baseline classroom levels of fine particulate matter (PM2.5) and black carbon (BC) were 6.3 μg/m3 and 0.41 μg/m3, respectively. When comparing the intervention to the control group, classroom PM2.5 levels were reduced by 49% and 42%, and BC levels were reduced by 58% and 55% in the first and second follow-up periods, respectively (p < 0.05 for all comparisons). When comparing the children randomized to intervention and control classrooms, there was a modest improvement in peak flow, but no significant changes in forced expiratory volume in 1 second (FEV1) and asthma symptoms.

Conclusion

In this pilot study, a classroom-based air cleaner intervention led to significant reductions in PM2.5 and BC. Future large-scale studies should comprehensively evaluate the effect of school-based environmental interventions on pediatric asthma morbidity.

Keywords: Asthma, indoor air quality, environmental intervention, air cleaner

INTRODUCTION

Asthma is one of the most common chronic diseases of childhood in the US, affecting 15% of children living in urban areas.1 Every year, asthma accounts for over 10 million missed school days in the US.1 Urban minority populations experience greater asthma morbidity and have higher asthma-related mortality rates.2 The relationship between air pollution (e.g., fine particulate matter [PM2.5], black carbon [BC]) and asthma morbidity in children is well-established.3, 4 Local and regional traffic pollution are important sources of PM2.5 and BC, which can penetrate indoors and contribute to poor indoor air quality.

In contrast to homes, schools have fewer indoor sources of pollutants, as most schools no longer have active kitchens and smoking is prohibited. However, traffic emissions are an important source, as schools are often centrally located within a community and consequently are closer to heavy traffic routes. In addition, there are many idling cars and buses for pick-up and drop-off. Indoor classroom pollutant exposures may be an important risk factor for asthma morbidity in children5, as children spend a large portion of their day in school.

Previous studies of home-based environmental interventions using air cleaners have resulted in reduced particulate pollutant exposures and improved asthma symptoms in children.6,7 Much less is known about the potential role of classroom-based interventions in improving air quality and asthma morbidity for children. In this study, our primary goal was to pilot the effect of an air cleaner intervention to reduce indoor particulate pollutants in classrooms of asthmatic children. Our secondary goal was to determine the effect of reduced pollutant levels on asthma morbidity.

METHODS

Study Population

We recruited 25 children with asthma, aged 6 to 10 years, from 18 unique classrooms in three urban elementary schools in the northeastern United States from 2013 to 2014 (see flow diagram in Figure E1 in Online Repository). Inclusion and exclusion criteria utilized in other urban studies were adapted for this study as previously described.8 Inclusion criteria included physician-diagnosed asthma for at least one year and at least one of the following: current daily preventative asthma medication, wheezing in the past year, or an unscheduled medical visit for asthma in the past year. Exclusion criteria included lung disease other than asthma, cardiovascular disease, beta blocker use, and enrollment in another asthma or allergy clinical trial. The study was approved by the local institutional review board and the participating school system. Informed consent was obtained from each participant’s parent or legal guardian, and assent was obtained from each participant.

Study Recruitment and Baseline Study Visit

Validated screening survey questionnaires8 were distributed in the spring of 2013 to the parents of students to determine eligibility for enrollment (see Figure 1 for study overview). During the summer of 2013, 25 students were enrolled and completed a baseline clinical assessment. This included a baseline demographic, medical, and symptom survey as well as spirometry performed according to American Thoracic Society guidelines9 (Koko spirometer, Ferraris 141 Respiratory, Louisville, CO).

Figure 1. Study design schema.

Figure 1

Open in a new tab

18 classrooms (25 students) in 3 schools were randomized to an air cleaner intervention or a sham filter control. 6 classrooms from 1 school also received IPM in the fall. Baseline study visits were completed prior to the start of school. Baseline classroom pollutant levels were measured during the fall semester prior to randomization.

Follow-up Questionnaires and School Visits

Follow-up asthma symptom surveys were performed through phone interviews at 3, 6, 9, and 12 months after the baseline visit. Follow-up spirometry was conducted in the fall and spring during school visits.

Exposure Assessment

Environmental exposure assessment for indoor PM2.5, BC, and settled dust allergen levels was completed at baseline prior to randomization and twice during the academic year (once in the winter and once in the spring). Air sampling for PM2.5 and BC concentration was performed by placing Personal Exposure Monitors (PEMs) 1.5 m above the floor in each classroom for one week, as far away from the air cleaner exhaust as possible. Sampling devices were set to an automatic timer that turned off after school and turned on when school started to restrict measurements to school-hours. Each PEM includes an inertial impactor (H-PEM, BGI Inc., Waltham, MA)10 to collect PM2.5 on 37 mm Teflon membrane filters at a flowrate of 1.8 L/min. The Teflon filters were weighed before and after sample collection on an electronic microbalance (MT-5 Mettler Toledo, Columbus, OH). Indoor BC concentrations were measured by the reflectance method on the collected Teflon filters using a smoke stain reflectometer (model EEL M43D, Diffusion Systems Ltd., United Kingdom).

Classroom settled dust samples were collected using a hand-held vacuum with a special dust collector (DACI lab, Johns Hopkins, Baltimore, MD) using a standardized protocol.11 For each sample, standardized vacuum sampling was performed for 3 minutes on the floor and 3 minutes on desk/chair surfaces. Dust samples were analyzed using a multiplex array for indoor allergens (MARIA, Indoor Biotechnologies, Charlottesville, VA)12 that simultaneously measured the following allergens: cockroach (Bla g 2), cat (Fel d 1), dog (Can f 1), mouse (Mus m 1), and dust mite (Der f 1).

Intervention

Eighteen classrooms (for the 25 participants) were randomized in a 1:1 ratio by school to receive High Efficiency Particulate Air (HEPA) cleaners. This resulted in 9 intervention classrooms with 12 children and 9 control classrooms with 13 children. We used a commercial air cleaner (AP-1013A, Coway, Korea) with a HEPA filter. A total of 4 air cleaners were placed on the floor in each intervention classroom in the same position throughout the study period: near the hallway, next to windows, and front and back of the classroom. To achieve a minimal impact on classroom activities, each air cleaner was adjusted to a noise level of 50 dB, corresponding to an air delivery rate of 3.7 m3/min. For the control group, sham air cleaners were constructed by removing the filters and adding a sound generator (Zohne, Marpac, Wilmington, NC). In a blind test, the noise level of each sham air cleaner was adjusted to same level as an active air cleaner. The children, teachers, and school officials were blinded to the status (active vs. sham) of the air cleaners in each classroom. As the recommended time for replacing the HEPA filter is 12 months, we did not change the filter during the study period.

Simultaneously, we also piloted the feasibility of an integrated pest management (IPM) intervention in these schools. Due to limited resources, a partial IPM was conducted once in the fall semester for 6 classrooms from one school. The IPM consisted of vacuuming and filling holes and cracks with copper mesh and caulk sealant.

Asthma Symptoms and Lung Function

Frequency of asthma symptoms were based on caregiver responses to the questions about daytime and nighttime symptoms in the past 2 weeks, and interference with the child’s activities in the past 2 weeks based on a validated questionnaire.8 Experiencing any of the above symptoms was considered as having an “any symptom” day, a dichotomous metric that has been used in other asthma studies.13 Spirometry was completed at baseline and two follow-up visits, and results reviewed for quality by a pediatric pulmonologist.14 Spirometry results were analyzed only in participants with a valid baseline measurement and at least one valid follow-up measurement.

Statistical Analysis

Summary statistics were computed for demographic characteristics and baseline air quality and asthma morbidity outcomes. For the primary outcome (classroom PM2.5 and BC levels), linear mixed-effects models were applied in order to account for correlation due to repeated measures, with classroom-specific random intercepts to allow baseline pollutant levels to vary by classroom (see Appendix A in Online Repository for more details). Baseline pollutant levels were compared between the intervention and control classrooms in each school using the Wilcoxon rank sum test. Dust allergen levels were evaluated using a similar model with log-transformed allergen levels, given their log-normal distribution. Baseline allergen levels were compared between the intervention and control groups using the Wilcoxon rank sum test.

For the secondary outcomes, linear mixed-effects models similar to the aforementioned model were used to estimate the effect of the intervention on lung function (e.g., forced expiratory volume in 1 second [FEV1], peak expiratory flow [PEF]). An analogous generalized mixed effects model was used to evaluate the effect of the intervention on the presence or absence of asthma symptoms in the prior 2 week period. Subject-specific random intercepts were included in these models. All analyses were performed using SAS (version 9.2; SAS Institute, Cary, NC). A p-value < 0.05 was considered statistically significant.

RESULTS

School and Classroom Characteristics

We recruited participants from 18 classrooms in three urban inner city elementary schools in the US (Table 1). The schools were built in 1959 to 1975, and the oldest school did not have a central heating, ventilating, air conditioning (HVAC) system. The classrooms were randomized to the control and intervention group in a 1:1 ratio within each school. Classroom floor level and number of classrooms facing the drop-off/pick-up area was comparable between the control and intervention group in each school. At baseline, there were no statistically significant differences between the control and intervention classrooms within each school for both fine particulate matter (PM2.5) and black carbon (BC).

Table 1.

School and Classroom Characteristics

A B C
Year Built 1975 1959 1969
Classrooms (No.) Control 4 2 3
Intervention 4 2 3
Students (No.) Control 5 2 5
Intervention 6 3 4
Classroom Floor Control 3 (1,4) 0 (0,0) 2 (2,2)
Median (range) Intervention 3.5 (2,4) 0.5 (0,1) 2 (2,2)
Classrooms Facing Control 2 0 0
Dropoff/Pickup Area Intervention 2 2 0
PM2.5 Control 5.8 (5.7,6.1) 6.9 (6.6,7.2) 6.7 (6,7.3)
Mean (range) Intervention 5.5 (4.8,5.9) 7.1 (6.8,7.5) 6.2 (5.1,6.8)
BC Control 0.47 (0.4,0.55) 0.28 (0.14,0.42) 0.41 (0.33,0.47)
Mean (range) Intervention 0.39 (0.31,0.52) 0.34 (0.28,0.4) 0.48 (0.45,0.51)
Open in a new tab

Baseline Participant Characteristics

A total of 25 children were enrolled in the study (see flow diagram in Figure E1 in the Online Repository). Children in the treatment and control groups had similar sociodemographic and health characteristics (Table 2). The mean age of children was 8.1 years (range, 6.0 to 10.9 years) and 60% were female. The majority of children identified as black (60%) or Hispanic (24%) with 80% percent having Medicaid as their primary health insurance.

Table 2.

Baseline sociodemographic and health characteristics by group.

Control Group
(n=12)		 Air Cleaner Group
(n=13)
Girls, no. (%)   7 (58)   8 (62)
Age (y), mean (SD) 8.4 (1.5) 7.8 (1.2)
Race, no. (%)
 Black 7 (58) 8 (62)
 Hispanic 2 (17) 4 (31)
 Other 3 (25) 1 (8)  
Medicaid, no. (%) 8 (67) 12 (92)  
Family history of asthma, no. (%) 10 (83) 10 (77)  
Home tobacco smoke exposure, no. (%) 3 (25) 3 (23)
Asthma controller medication use, no. (%) 11 (92) 12 (92)  
Open in a new tab

At baseline, 44% of the children reported daytime asthma symptoms in the previous 2 weeks (mean, 1.5 of 14 days), 20% reported nighttime asthma symptoms (mean, 1.0 of 14 days), and 48% reported asthma-related interference with activities (mean, 1.2 of 14 days). In addition, 92% of the children took daily controller medications. Of note, 80% of the children had a family history of asthma. Spirometry measurements were valid in 16 participants. Baseline FEV1 percent predicted was 88% ± 12% and PEF was 3.0 L/s ± 0.8 L/s.

Classroom Pollutant Levels

Prior to randomization, baseline mean ± SD classroom levels of fine particulate matter (PM2.5) and black carbon (BC) were 6.3 μg/m3 ± 0.8 μg/m3 and 0.41 μg/m3 ± 0.10 μg/m3, respectively. There were no differences in PM2.5 and BC levels between the control and intervention classrooms (PM2.5, p=0.63; BC, p=0.92).

In the control group, mean PM2.5 concentrations decreased from 6.4 μg/m3 ± 0.6 μg/m3 at baseline to 4.8 μg/m3 ± 1.1 μg/m3 and 5.0 μg/m3 ± 0.8 μg/m3 at the first and second follow-up visits, respectively. In the intervention group, mean PM2.5 concentrations decreased from 6.2 μg/m3 ± 0.9 μg/m3 at baseline to 2.4 μg/m3 ± 0.6 μg/m3 and 2.6 μg/m3 ± 1.0 μg/m3 at the first and second follow-up visits, respectively. The intervention group had greater reductions in PM2.5 levels compared to the control group by 2.3 μg/m3 (95% confidence interval (CI): −3.5, −1.0; p=0.003) at the first follow-up and 2.2 μg/m3 (95% CI: −3.4, −1.1; p=0.002) at the second follow up, which correspond to a 49% and 42% reduction, respectively (Figure 2).

Figure 2. Classroom particulate pollutant levels.

Figure 2

Open in a new tab

Classroom PM2.5 (μg/m3) and BC (μg/m3) levels at baseline and follow-up visits in the intervention and control groups. Mean and standard errors shown.

In the control group, mean BC concentrations decreased from 0.41 μg/m3 ± 0.12 μg/m3 at baseline to 0.30 μg/m3 ± 0.21 μg/m3 and 0.33 μg/m3 ± 0.12 μg/m3 at the first and second follow up visits, respectively. In the intervention group, mean BC concentrations decreased from 0.41 μg/m3 ± 0.09 μg/m3 at baseline to 0.13 μg/m3 ± 0.07 μg/m3 and 0.15 μg/m3 ± 0.12 μg/m3 at the first and second follow-up visits, respectively. The intervention group had greater reductions in BC levels compared to the control group by 0.17 μg/m3 (95% CI: −0.32, −0.03; p=0.03) at the first follow-up and 0.19 μg/m3 (95% CI: −0.32, −0.05; p=0.001) at the second follow-up, which correspond to a 58% and 55% reduction, respectively. The PM2.5 and BC reductions achieved by the air cleaner intervention were comparable between schools (Table E1 in Online Repository).

Allergen Levels

Baseline mouse allergen (Mus m 1) levels ranged from 0.04 μg/g to 25.5 μg/g. The partial IPM intervention did not show an effect on Mus m 1 levels and other allergens. Of note, the baseline Mus m 1 levels were significantly lower in the 6 classrooms that received IPM compared to the 12 classrooms that did not receive IPM (p = 0.004). In the control group, median Mus m 1 levels were 3.3 μg/g (range: 0.4, 25.5) at baseline and 0.7 μg/g (range: 0.2, 8.4) and 16.4 μg/g (range: 0.05, 54.5) at the first and second follow-up visits, respectively. In the intervention group, median Mus m 1 levels were 0.1 μg/g (range: 0.04, 1.4) at baseline and 0.5 μg/g (range: 0.1, 0.8) and 0.3 μg/g (range: 0.1, 1.5) at the first and second follow-up visits, respectively. There were minimal changes in the other allergens.

Symptoms

At baseline, 52% of the children reported asthma symptoms in the previous 2 weeks. Six months after randomization, 23% (3 out of 13) of children in the intervention group and 33% (4 out of 12) of children in the control group reported asthma symptoms. During the trial, the proportion of children reporting asthma symptoms was slightly lower in the intervention group than the control group, but these differences were not statistically significant (Figure E2 in Online Repository). Out of 25 children, 16 had spirometry measurements suitable for analyses. There were no differences in baseline FEV1 and PEF between children in the control and intervention groups. The intervention group had a greater improvement in PEF compared with the control group by 0.46 L/s (95% CI: 0.09, 0.83; p=0.03) at the first follow-up, which corresponds to a 16% improvement. There were no differences in other measures of lung function between the intervention and control groups.

DISCUSSION

In this pilot study, we demonstrated that a classroom-based air cleaner intervention significantly reduced classroom levels of two important indoor particulate pollutants; PM2.5 and BC. Importantly, these reduced pollutant levels were sustained throughout the academic year in the intervention group in all schools. There was modest evidence of improvement in lung function and asthma symptoms in participants of the intervention classrooms. It is well-established that exposures to air pollutants increase asthma morbidity in children.3 Prior home-based studies have used air cleaners to improve indoor air quality and assess asthma symptoms in children,6,7 but there are no studies on the efficacy of an air cleaner intervention in schools.

In the intervention classrooms, PM2.5 and BC levels were significantly reduced compared to the control classrooms that received a sham air filter. The air cleaner intervention reduced PM2.5 and BC levels by up to 49% and 58%, respectively. These reductions were within the range of previously reported air cleaner removal efficacy of indoor particulate pollutants.7,13,15 Eggleston et al. 2005 demonstrated that an air cleaner intervention in homes led to a significant decrease in room PM2.5 levels from 38 μg/m3 to 24 μg/m3 over 12 months. Butz et al. 2003 found a similar effect, with a decrease in room PM2.5 levels from 34 μg/m3 to 18 μg/m3 at 6 months. Majority of homes in these studies had smokers at home, which leads to higher PM2.5 levels compared to the average classroom PM2.5 level of 6 μg/m3 in our study—a concentration far below the EPA standard of 35 μg/m3 for daily outdoor PM2.5. Even though classroom PM2.5 levels were lower, the air cleaners achieved similar particle removal effectiveness as the home-based studies. In addition, the low pollutant levels were sustained throughout the school year in the intervention group. This study focused on particulate pollutants, which are more effectively removed by HEPA cleaners than gaseous pollutants, such as ozone and nitrogen dioxide. Furthermore, in schools where there are no active kitchens and smoking is prohibited, there are minimal indoor sources of gaseous pollutants.

The decreases in PM2.5 and BC in the intervention group were within the range that has been associated with significant changes in lung function and asthma symptoms in prior epidemiological studies.5,16,17 Many previous intervention studies have measured PM2.5, but not BC. BC is a marker of local and regional traffic pollutants and measured as the light-absorbing component of particulate matter. BC exposure is associated with airway inflammation18 and time-series studies have found significant effects of BC exposure on pediatric asthma hospital admissions.4 Furthermore, exposure to BC have been associated with decreased cognitive function and attention in urban children.19–21 This further makes reducing BC desirable in the classroom setting. As the pollutant levels in our study were lower than noted in similar home-based studies, it will be important to determine in larger cohort studies if changes in low level exposures have clinically relevant impact.

In addition to the air cleaner intervention, we aimed to demonstrate the feasibility of implementing an IPM intervention in the school setting. The IPM intervention is expected to be more effective in reducing settled dust allergens than the air cleaners, which remove airborne particles. In previous studies, we have demonstrated that school mouse allergen levels were consistently higher compared to homes of children with asthma.22,23 We also previously demonstrated the efficacy of a home-based IPM intervention in reducing dust mouse allergens when performed multiple times over several months.24 Due to limited resources, we were only able to implement a partial IPM in six classrooms from the same school and only once during the fall. Furthermore, by chance, the classrooms assigned to receive IPM had significantly lower mouse allergen levels at baseline compared to the classrooms that did not receive IPM. Given these limitations, we were unable to assess the efficacy of the IPM intervention on dust mouse allergen levels, but demonstrated that the IPM can be feasibly conducted as part of an environmental intervention strategy in schools.

Small sample size limits the interpretation of the health outcomes, which were secondary outcomes of interest in this study. However, we were encouraged in this pilot to observe modest improvements in lung function. A 16% improvement in PEF was observed at the first follow-up. Despite known limitations of peak flow data, studies have shown that PEF measures capture lung function decrements associated with clinically important asthma symptoms in children.25 We did not observe any differences in the second follow-up. One possibility is that children spend more time outdoors during the warmer months (May-June), which may reduce the efficacy of improvement in indoor air quality. A larger study is needed to verify these relationships. Although we did not detect differences in asthma symptoms in this pilot, some evidence of improvement was noted.

This study has other additional limitations. We did not measure classroom ventilation (air exchange) rate, which is an important determinant of indoor particulate pollutant levels. Greater ventilation (i.e., opening windows) may increase particulate pollutants infiltrating from outdoors. Therefore, potential differences between ventilation rates in intervention and control classrooms could affect estimates of the air cleaner effectiveness. Since baseline particulate pollutant levels were very close between the intervention and control groups, ventilation rates were likely similar with minimal impact on our results.

Our pilot study demonstrates that an air cleaner intervention in classrooms can be effective in reducing particulate pollutants in inner-city schools, and that an integrated air cleaner and IPM intervention can be implemented in a school setting. With the exception of work in public housing, most previous studies have focused on environmental remediation for individual asthmatic children in single homes. The school environment can be considered as an efficient target for reduction of asthma morbidity, as classroom/school-based interventions may reduce exposures for many children in a community. Further large-scale studies are needed to comprehensively evaluate the effectiveness of school-based environmental interventions in reducing asthma morbidity in children.

Supplementary Material

HIGHLIGHTS.

1. What is already known about this topic?

Air cleaner interventions to reduce particulate pollutants at homes have been successful improving indoor air quality and asthma morbidity in children. However, less is known about the school environment.

2. What does this article add to our knowledge?

This study illustrates the feasibility and efficacy of a school-based air cleaner intervention to reduce classroom particulate pollutants. We found modest evidence of improved lung function.

3. How does this study impact current management guidelines?

Air cleaners can reduce exposures to asthma exacerbating pollutants present in indoor environments. This supports further evaluation of air cleaners as a classroom-based intervention to produce clinically meaningful improvements in asthma morbidity in children.

Acknowledgments

Funding

This work was supported by Harvard Medical School Scholars in Medicine, grants U01 AI 110397, R01 AI 073964, K24 AI 106822, U10 HL 098102, K23 AI 106945, K23 AI 104780, and P03ES000002 from the National Institutes of Health. This work was conducted with the support from Harvard Catalyst/The Harvard Clinical and Translational Science Center (NIH Award UL1 TR000170) and financial contributions from Harvard University and its affiliated academic healthcare centers. The content is solely the responsibility of the authors and does not necessarily represent the official views of Harvard Catalyst, Harvard University and its affiliated academic healthcare centers, the National Center for Research Resources, or the National Institutes of Health. This work was also supported in part by: American Lung Association, American Academy of Allergy, Asthma, and Immunology, Respiratory Diseases Faculty Award, and the Deborah Munroe Noonan Memorial Award. We also thank Coway Co., LTD for their funding and for donating the air cleaners used in this study.

clinicaltrials.gov: NCT01913795

ABBREVIATIONS

BC

black carbon

FEV1

forced expiratory volume in 1 second

HEPA

high efficiency particulate air

HVAC

heating, ventilating, air conditioning

IPM

integrated pest management

PEF

peak expiratory flow

PEM

personal exposure monitor

PM2.5

fine particulate matter

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. 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.

References

  • 1.Moorman J, et al. National Surveillance of Asthma: United States, 2001–2010. Vital Heal Stat. 2012;3 [PubMed] [Google Scholar]
  • 2.Price JH, Khubchandani J, McKinney M, Braun R. Racial/ethnic disparities in chronic diseases of youths and access to health care in the United States. Biomed Res Int. 2013;2013:787616. doi: 10.1155/2013/787616. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Zheng XY, et al. Association between Air Pollutants and Asthma Emergency Room Visits and Hospital Admissions in Time Series Studies: A Systematic Review and Meta-Analysis. PLoS One. 2015;10:e0138146. doi: 10.1371/journal.pone.0138146. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Hua J, et al. Acute effects of black carbon and PM2.5 on children asthma admissions: a time-series study in a Chinese city. Sci Total Environ. 2014;481:433–8. doi: 10.1016/j.scitotenv.2014.02.070. [DOI] [PubMed] [Google Scholar]
  • 5.Habre R, et al. The effects of PM2.5 and its components from indoor and outdoor sources on cough and wheeze symptoms in asthmatic children. J Expo Sci Environ Epidemiol. 2014;24:380–7. doi: 10.1038/jes.2014.21. [DOI] [PubMed] [Google Scholar]
  • 6.Lanphear BP, et al. Effects of HEPA air cleaners on unscheduled asthma visits and asthma symptoms for children exposed to secondhand tobacco smoke. Pediatrics. 2011;127:93–101. doi: 10.1542/peds.2009-2312. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Butz A, et al. A Randomized Trial of Air Cleaners and a Health Coach to Improve Indoor Air Quality for Inner-City Children With Asthma and Secondhand Smoke Exposure. Arch Pediatr Adolesc Med. 2011;165:741–748. doi: 10.1001/archpediatrics.2011.111. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Phipatanakul W, et al. The school inner-city asthma study: design, methods, and lessons learned. J Asthma. 2011;48:1007–14. doi: 10.3109/02770903.2011.624235. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Miller MR, et al. Standardisation of spirometry. Eur Respir J. 2005;26:319–38. doi: 10.1183/09031936.05.00034805. [DOI] [PubMed] [Google Scholar]
  • 10.Demokritou P, Kavouras IG, Ferguson ST, Koutrakis P. Development and Laboratory Performance Evaluation of a Personal Multipollutant Sampler for Simultaneous Measurements of Particulate and Gaseous Pollutants. Aerosol Sci Technol. 2001;35:741–752. [Google Scholar]
  • 11.Mitchell H, et al. Design and methods of the National Cooperative Inner-City Asthma Study. Pediatr Pulmonol. 1997;24:237–52. doi: 10.1002/(sici)1099-0496(199710)24:4<237::aid-ppul3>3.0.co;2-h. [DOI] [PubMed] [Google Scholar]
  • 12.King EM, et al. A multi-center ring trial of allergen analysis using fluorescent multiplex array technology. J Immunol Methods. 2013;387:89–95. doi: 10.1016/j.jim.2012.09.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Eggleston Pa, et al. Home environmental intervention in inner-city asthma: a randomized controlled clinical trial. Ann Allergy Asthma Immunol. 2005;95:518–24. doi: 10.1016/S1081-1206(10)61012-5. [DOI] [PubMed] [Google Scholar]
  • 14.National Asthma Education and Prevention Program Expert Panel. Guidelines for the diagnosis and management of asthma – update on selected topics. 2007 [PubMed] [Google Scholar]
  • 15.Du L, et al. Particle Concentrations and Effectiveness of Free-Standing Air Filters in Bedrooms of Children with Asthma in Detroit, Michigan. Build Env. 2011;46:2303–2313. doi: 10.1016/j.buildenv.2011.05.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Rice MB, et al. Short-term exposure to air pollution and lung function in the Framingham Heart Study. Am J Respir Crit Care Med. 2013;188:1351–7. doi: 10.1164/rccm.201308-1414OC. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Zora JE, et al. Associations between urban air pollution and pediatric asthma control in El Paso, Texas. Sci Total Environ. 2013;448:56–65. doi: 10.1016/j.scitotenv.2012.11.067. [DOI] [PubMed] [Google Scholar]
  • 18.De Prins S, et al. Airway oxidative stress and inflammation markers in exhaled breath from children are linked with exposure to black carbon. Environ Int. 2014;73:440–6. doi: 10.1016/j.envint.2014.06.017. [DOI] [PubMed] [Google Scholar]
  • 19.Chiu YM, Bellinger DC, Coull BA, Anderson S, Barber R. Associations between Traffic-Related Black Carbon Exposure and Attention in a Prospective Birth Cohort of Urban Children. Environ Health Perspect. 2013;121:859–864. doi: 10.1289/ehp.1205940. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Forns J, et al. Traffic-Related Air Pollution, Noise at School, and Behavioral Problems in Barcelona Schoolchildren: A Cross-Sectional Study. Environ Health Perspect. 2015 doi: 10.1289/ehp.1409449. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Dadvand P, et al. Green spaces and cognitive development in primary schoolchildren. PNAS. 2015;112:7937–42. doi: 10.1073/pnas.1503402112. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Permaul P, et al. Predictors of indoor exposure to mouse allergen in inner-city elementary schools. Ann Allergy, Asthma, Immunol. 2013;111:299–301.e1. doi: 10.1016/j.anai.2013.07.028. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Sheehan WJ, et al. Mouse allergens in urban elementary schools and homes of children with asthma. Ann Allergy, Asthma, Immunol. 2009;102:125–130. doi: 10.1016/S1081-1206(10)60242-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Phipatanakul W, et al. Effect of environmental intervention on mouse allergen levels in homes of inner-city Boston children with asthma. Ann allergy, asthma Immunol. 2004;92:420–5. doi: 10.1016/S1081-1206(10)61777-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Meltzer EO, et al. Efficacy and safety of budesonide administered by pressurized metered-dose inhaler in children with asthma. Ann Allergy Asthma Immunol. 2015 doi: 10.1016/j.anai.2015.09.007. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

NIHMS812811-supplement-supplement_1.pdf (290.4KB, pdf)

RESOURCES