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. 2024 Dec 2;179(2):122–128. doi: 10.1001/jamapediatrics.2024.5049

Respiratory Benefits of Multisetting Air Purification in Children

A Cluster Randomized Crossover Trial

Jian Lei 1,2, Qinghua Sun 3, Renjie Chen 1, Yixiang Zhu 1, Lu Zhou 1, Xiaowei Xue 1, Jianlong Fang 3, Yanjun Du 3, Yanwen Wang 3, Tiantian Li 3,✉, Haidong Kan 1,4,✉
PMCID: PMC11612917  PMID: 39621320

Key Points

Question

Does prolonged and multisetting air purification benefit the respiratory health of school-aged children?

Findings

This randomized crossover trial including 79 children found that air purification reduced 45.14% of time-weighted personal fine particulate matter concentrations, improved the pulmonary function indicators, and alleviated airway inflammation levels among children.

Meaning

These findings underline the importance of indoor air quality improvement in regions with high air pollution levels.

This cluster randomized crossover trial assesses respiratory outcomes among children exposed to air purification at school and in their bedrooms.

Abstract

Importance

Particulate matter exposure has been linked to impaired respiratory health in children, but the respiratory benefits of air purification have not been fully elucidated.

Objectives

To assess the respiratory health outcomes among children exposed to multisetting air purification vs sham purification.

Design, Setting, and Participants

This cluster randomized, double-blind, crossover trial was conducted among healthy school-aged children (10-12 years) in China from April to December 2021. Data were analyzed from December 2021 to July 2024.

Interventions

A multisetting (both in classrooms and bedrooms) air purification intervention compared with sham purification in a 2-stage intervention with more than 2 months (76 days) for each period and a washout period (88 days) to estimate the respiratory benefits of air purification.

Main Outcomes and Measures

The primary outcomes were pulmonary function, airway inflammation markers, and metabolites in exhaled breath condensate (EBC) before and after the air purification intervention. Linear mixed-effects models were used to estimate the respiratory benefits of children related to air purification. Differential metabolites in EBC were identified using metabolomics analysis to explore their possible mediation roles.

Results

A total of 79 children (38 male [48%]; mean [SD] age, 10.3 [0.5] years) were included in the statistical analyses. During the study period, the mean (SD) concentration of outdoor fine particulate matter (PM2.5) at the school site was 32.53 (24.06) μg/m3. The time-weighted personal PM2.5 concentration decreased by 45.14% during the true air purification period (mean [SD], 21.49 [8.72] μg/m3) compared with the sham air purification period (mean [SD], 39.17 [14.25] μg/m3). Air purification improved forced expiratory volume in 1 second by 8.04% (95% CI, 2.15%-13.93%), peak expiratory flow by 16.52% (95% CI, 2.76%-30.28%), forced vital capacity (FVC) by 5.73% (95% CI, 0.48%-10.98%), forced expiratory flow at 25% to 75% of FVC by 17.22% (95% CI, 3.78%-30.67%), maximal expiratory flow at 75% of FVC by 14.60% (95% CI, 0.35%-28.85%), maximal expiratory flow at 50% of FVC by 17.86% (95% CI, 3.65%-32.06%), and maximal expiratory flow at 25% of FVC by 18.22% (95% CI, 1.73%-34.70%). Fractional exhaled nitric oxide in the true air purification group decreased by 22.38% (95% CI, 2.27%-42.48%). Several metabolites in EBC (eg, L-tyrosine and β-alanine) were identified to mediate the effect of air purification on respiratory health.

Conclusions and Relevance

This randomized clinical trial provides robust and holistic evidence that indoor air purification notably improved pulmonary health in children, highlighting the importance of intensified indoor air purification in regions with high air pollution levels.

Trial Registration

ClinicalTrials.gov Identifier: NCT04835337.

Introduction

Respiratory diseases, including acute infectious processes and chronic disease conditions, are the most common causes of mortality for children.1 Ambient air pollution, especially fine particulate matter (PM2.5), has been linked to increased morbidity and mortality risks of respiratory diseases.1,2,3 Several observational epidemiological studies have demonstrated that air pollution exposure could impair children’s respiratory health and decrease pulmonary function.4,5 Moreover, the respiratory system of children is at the vital growing stage for the pulmonary barrier and immune function development,6 which appears to be at a particular vulnerability stage to air pollution exposure compared with that of adults.3,7,8 Stymied pulmonary development induced by air pollution exposure during childhood may result in far-reaching influences, such as lung impairment in adults.6,9 Thus, the impact of air pollution on children’s respiratory health deserves heightened public concerns.1

Air purification interventions have been reported to alleviate respiratory inflammation and improve pulmonary function in adults.10,11 For example, several quasiexperimental studies indicated that decreased PM2.5 exposure could improve respiratory biomarkers and decrease respiratory disease hospitalizations.10,11,12 Furthermore, a few randomized clinical trials (RCTs) based on exposure chambers also demonstrated that decreased air pollution levels could immediately improve a range of respiratory health indicators, including lung function, exhaled nitric oxide, and systemic inflammatory factors.13,14,15 Nevertheless, these experimental or quasiexperimental studies were mostly conducted in adults, and no study of this kind has focused on children, to our knowledge. On the other hand, chamber-based RCTs among children would be subject to major ethical concerns and also unable to reflect the functional health benefits of air pollution reduction. Alternatively, air purifiers with a high-efficiency particulate air (HEPA) filter can remove indoor airborne particulate matter.16 Thus, they are commonly used in studies to estimate the health benefits of reducing particulate matter exposure. However, previous RCTs with air purifiers focused on short-term (days- or weeks-long) interventions, and the interventions were typically performed only at home or in workplaces.16,17 It remains unclear how prolonged air purification in multiple living environments could benefit children’s respiratory health and whether the metabolites in exhaled breath condensate (EBC) could mediate the effect of air purification on respiratory benefits.

Therefore, we performed a cluster randomized, double-blind, crossover trial with multisetting air purification to estimate the potential respiratory benefits in terms of pulmonary function and airway inflammation in school-aged children. Additionally, we explored the mechanisms underlying the potential respiratory benefits associated with air purification through metabolomics in EBC.

Methods

This cluster randomized crossover trial was approved by the Ethical Review Committee of the National Institute of Environmental Health, Chinese Center for Disease Control and Prevention. All children and their guardians provided written informed consent at enrollment. The trial protocol and statistical analysis plan are presented in Supplement 1. This study is reported following the Consolidated Standards of Reporting Trials (CONSORT) reporting guideline.

Study Design and Participants

We designed a randomized, double-blind, crossover trial with multisetting air purification in a Chinese city (Mengzhou City, Henan Province) with severe air pollution. The trial was conducted at an elementary school from April to December 2021, and consists of 2-stage intervention periods over 2 months (76 days) and a washout and crossover period (88 days). During the study period, the mean (SD) concentration of PM2.5 in the school site was 32.53 (24.06) μg/m3. The schematic diagram and design of the air purification intervention are shown in the eFigure in Supplement 2. We performed health measurements immediately before and after each of the intervention periods. We initially recruited all 105 pupils aged 10 to 12 years in 2 classes of the primary school (deemed as 2 groups) after excluding pupils who had a history of physician-diagnosed chronic disease (eg, asthma, childhood diabetes, childhood hypertension), had plans to relocate residence in the following year, or refused to participate. Participants received a feedback report on the results of their medical examination, an air pollution exposure monitoring report, personalized protection advice, and a small gift (approximate value, ¥100 [US $14]) to thank them for participating.

To ensure that all the children could receive sufficient coverage of air purification, we designed a multisetting air quality intervention program (eFigure in Supplement 2). In the classroom setting, there were 2 fresh air ventilators (model AT320; Airtao) with a clean air delivery rate (CADR) of 320 m3/h and 2 air purifiers (model KJ901; Lexy) with CADR of 850 m3/h, which were operated during school time. In the home setting, 1 air purifier (Model KJ210F-A180A, Haier) with a CADR of 220 m3/h was installed in each child’s bedroom. The air purifier was operated during home time. To ensure the efficiency of air purification, all windows and doors were closed during the air purification period. The schematic diagram of the multisetting air purification can be found in the eFigure in Supplement 2, and the operating scheme is in eTable 1 in Supplement 2. All air purification devices were operated under remote real-time monitoring, which could report the operating status of the air purification devices during the study period.

To ensure the feasibility of the trial and adherence of the participants, we applied cluster randomization for the order of the true and sham air purification interventions at the class level. Children received identical air purification in a randomized order at each intervention period, separated by a more than 2-month washout period (summer holidays). For simplicity, we defined group 1 as the class that received true air purification for the first intervention stage and sham purification for the second intervention stage; group 2 was the class that received sham air purification for the first intervention stage and true purification for the second intervention stage. The true air purifiers (with HEPA filter) or sham air purifiers (without HEPA filter) were masked to the children, field personnel, and designers of this trial.

PM Exposure Assessment

We chose PM2.5 as the main air pollutant of interest, as its health impacts have been well documented. We used automatic monitoring equipment (model B3-L2; Hike) to measure PM2.5 concentrations and meteorological parameters (air temperature and relative humidity) in the classrooms and bedrooms of each participant as well as the outdoor environment (at the rooftop of the school building) with a recording interval of 5 minutes.18 We also validated and calibrated the PM2.5 measurements with MicroPEM samplers (RTI International) and the detailed results have been provided elsewhere.19 The daily time-weighted concentrations of PM2.5 for each participant were calculated by combining the measurements in classrooms, bedrooms, and outdoor environments of the school site based on the time-location pattern of the participants. Because almost all the children lived within a 1.5-km radius of the school and they usually went to and from home and school by cycling or walking with a short commuting time, the outdoor measurements at the school site were likely representative of the exposures of PM2.5 and meteorological factors affecting children during their commutes between home and school.

Health Outcome Measurement

We conducted health examinations immediately before and after each intervention period. In each round of health assessment, we collected demographic information (such as age, sex, height, and weight), tested the pulmonary functions, airway inflammation markers, and collected EBC biospecimens. Pulmonary function was measured with a smart spirometer (model A1, BreathHome) using the standard operating guidance and supervised by trained medical staff.20,21 The primary outcomes of this analysis include 8 pulmonary function indicators and 2 airway inflammation biomarkers. To avoid the impact of circadian rhythms on respiratory outcomes, we performed health measurements in the 2 classes at the same hour (8:00-9:00 am) on 2 consecutive days before and after the true or sham air purification interventions. We calculated the absolute changes of the primary outcomes by subtracting the individual measurements before the air purification intervention from the measurements after the air purification intervention. The relative changes were calculated by dividing the absolute changes by the measurements before air purification interventions and expressed as percentage changes. The pulmonary function indicators include forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), FEV1:FVC ratio, peak expiratory flow (PEF), forced expiratory flow at 25% to 75% of FVC (FEF25%-75%), maximal expiratory flow at 75% of FVC (MEF75%), maximal expiratory flow at 50% of FVC (MEF50%), and maximal expiratory flow at 25% of FVC (MEF25%). We measured fractional exhaled nitric oxide (Feno) and fractional exhaled carbon monoxide (Feco) to evaluate the airway inflammation levels.22,23 The concentration of Feno was tested by NIOX VERO (Model Aerocrine); Feco and carboxyhemoglobin (coHb) were tested by a Breath CO Monitor (Model piCO), following the corresponding standard operating procedures.24,25

Biological Sample Collection and Metabolomics Analysis

As a noninvasive biospecimen, EBC is particularly useful in epidemiological studies for exploring the biological mechanisms of respiratory impairment.26,27,28 We applied metabolomics analysis to identify the differentially expressed metabolites in EBC related to air purification and explored the mechanisms underlying the potential respiratory benefits associated with air purification. The detailed methods of metabolomics analysis are provided in the eMethods in Supplement 2.

Statistical Analysis

We conducted a main analysis for the primary outcomes (ie, pulmonary function, Feno, and Feco) and a supplementary analysis for the secondary health outcomes (ie, EBC-based metabolome). By virtue of the crossover design in this study, each child would experience complete true and sham air purification periods and serve as their own control. Thus, we analyzed the effects of air purification intervention on primary respiratory health indicators using the linear mixed-effect model adjusted for a binary variable for the true vs sham air purification intervention and a random intercept for each participant to account for the correlation in repeated measurements of the same participant. We also adjusted for demographic characteristics, including age, sex, and body mass index to control for individual-level confounders.29,30 Meteorological factors were also controlled for by introducing time-weighted mean temperature and relative humidity 3 days prior to the health assessment and during the intervention periods using natural splines with 6 and 3 df, respectively. We additionally adjusted the model for the time-weighted mean PM2.5 concentration 3 days prior to the health assessment to account for the acute impact of short-term air pollution variations. Finally, we adjusted for the order effect by introducing a factor variable indicating the order of the air purification intervention (ie, true air purification first or sham air purification first).

To identify the differentially expressed metabolites in EBC samples related to air purification, we log-transformed the ion intensities of each metabolite and fitted a separate linear mixed-effect model using the same covariates as the main model. We further explored the possible mediating roles of differential metabolites in the association between air purification and improved respiratory health outcomes using mediation analysis. The detailed methods of mediation analysis are shown in the eMethods in Supplement 2.

The statistical analyses in this study were performed using R software version 3.6.3 (R Project for Statistical Computing). We used the lmer package to fit the linear mixed-effect model. We used 2-sided P values, and P < .05 was considered to be statistically significant. Data were analyzed from December 2021 to July 2024.

Results

Descriptive Results

The inclusion and exclusion procedures of this randomized, double-blind, crossover trial are presented in Figure 1. Initially, we recruited 105 children to participate in our study. Two participants withdrew from the trial due to illness or to transfer to another school after the first intervention period. After the washout period and second intervention period, 4 participants withdrew from this study. In total, 99 children completed both intervention stages. We excluded 20 pupils with poor adherence with at-home air purifications (offline rate of air purifiers in the bedroom >30% during the intervention periods) and family members who smoke at home. Finally, 79 children (38 male [48%]; mean [SD] age, 10.3 [0.5] years) were included in the statistical analyses, with 36 children in group 1 and 43 children in group 2. Baseline characteristics of the children in both groups are presented in Table 1.

Figure 1. Participant Enrollment and Study Flowchart.

Figure 1.

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Table 1. Baseline Characteristics of Included Children.

Characteristic Group
True purification first (n = 36) Sham purification first (n = 43)
Age, mean (SD), y 10.3 (0.6) 10.3 (0.4)
Sex, No. (%)
Male 14 (38.9) 24 (55.8)
Female 22 (61.1) 19 (44.2)
BMI, mean (SD) 19.0 (4.2) 18.5 (3.0)
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Abbreviation: BMI, body mass index (calculated as weight in kilograms divided by height in meters squared).

During the entire study period (April to December 2021), the mean (SD) outdoor concentration of PM2.5 at the school site was 32.53 (24.06) μg/m3 (eTable 2 in Supplement 2). During the sham air purification periods, the time-weighted personal concentration of PM2.5 was 39.17 (14.25) μg/m3, which was significantly higher than during the true air purification periods, at 21.49 (8.72) μg/m3 (Table 2). The air purification intervention reduced 45.14% of the time-weighted personal PM2.5 concentrations.

Table 2. Time-Weighted Concentrations of PM2.5 and Meteorological Data by Study Periods.

Period Mean (SD) Minimum Percentile Maximum
25th 50th 75th
PM2.5, μg/m3
True air purification 21.49 (8.72) 7.68 14.97 20.10 25.53 49.25
Sham air purification 39.17 (14.25) 16.40 27.95 35.49 50.37 85.60
Temperature, ° C
True air purification 22.67 (5.74) 14.32 17.28 20.82 28.42 32.83
Sham air purification 24.19 (5.64) 13.28 18.99 27.69 29.16 32.05
Relative humidity, %
True air purification 48.12 (8.93) 29.26 42.74 45.57 51.84 82.07
Sham air purification 45.92 (7.83) 35.18 41.37 43.93 48.61 79.03
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Abbreviation: PM2.5, fine particulate matter.

Changes in Respiratory Health Indicators Related to Air Purification

The descriptive statistics of the pulmonary function and airway inflammation indicators among pupils before and after the true and sham air purification intervention periods are displayed in eTable 3 in Supplement 2. As illustrated in Figure 2, children had significant improvement in pulmonary function measures during the true air purification intervention period. Specifically, FEV1 increased by 8.04% (95% CI, 2.15%-13.93%), PEF increased by 16.52% (95% CI, 2.76%-30.28%), FVC increased by 5.73% (95% CI, 0.48%-10.98%), FEF25%-75% increased by 17.22% (95% CI, 3.78%-30.67%), MEF75% increased by 14.60% (95% CI, 0.35%-28.85%), MEF50% increased by 17.86% (95% CI, 3.65%-32.06%), and MEF25% increased by 18.22% (95% CI, 1.73%-34.70%). The absolute changes of pulmonary function indicators related to air purification are shown in Figure 2 and eTable 4 in Supplement 2. The airway inflammation levels among children were also generally alleviated after air purification. As shown in Table 3, relative Feno decreased by 22.38% (95% CI, 2.27%-42.48%).

Figure 2. Absolute Changes and Relative Changes in Pulmonary Function Indicators Related to Air Purification Among Children.

Figure 2.

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The linear mixed-effect model was adjusted for a binary variable for true or sham air purification intervention, a random intercept for each participant, age, sex, body mass index, temperature and relative humidity during each intervention period and the previous 3 days, time-weighted mean fine particulate matter concentration previous 3 days, and a variable indicating the ordering of sham air purification first or true air purification first. Numeric data are presented in eTable 4 in Supplement 2. The pulmonary function indicators were measured before and after each of the true or sham air purification intervention. FEF25%-75% indicates forced expiratory flow at 25%-75% of forced vital capacity (FVC); FEV1, forced expiratory volume in 1 second; PEF, peak expiratory flow; MEF25%, maximal expiratory flow at 25% of FVC; MEF50%, maximal expiratory flow at 50% of FVC; MEF75%, maximal expiratory flow at 75% of FVC.

Table 3. Absolute and Relative Changes in Airway Inflammation Indicators During Air Purification Period.

Measure Change, % (95% CI)a
Absolute Relative
Feno, ppb −4.54 (−8.77 to −0.31) −22.38 (−42.48 to −2.27)
Feco, ppm −0.49 (−2.51 to 1.55) −45.21 (−112.05 to 21.62)
coHb, % −0.08 (−0.43 to 0.25) −11.51 (−35.70 to 12.67)
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Abbreviations: coHb, carboxyhemoglobin; Feco, fractional exhaled carbon monoxide; Feno, fractional exhaled nitric oxide.

a

The linear mixed-effect model was adjusted for a binary variable for true or sham air purification intervention, a random intercept for each participant, age, sex, body mass index, temperature and relative humidity during each intervention period and the previous 3 days, time-weighted mean fine particulate matter concentration previous 3 days, and a variable indicating the ordering of sham air purification first or true air purification first. The airway inflammation indicators were measured before and after each of the true and sham air purification interventions.

In EBC-based metabolomic analysis, we identified 41 metabolites that were differentially expressed between true and sham air purification intervention groups (eTable 5 in Supplement 2). The differential metabolites were enriched in D-amino acid metabolism; β-alanine metabolism; histidine metabolism; pantothenate and CoA biosynthesis; alanine, aspartate, and glutamate metabolism; and phenylalanine, tyrosine, and tryptophan biosynthesis (eTable 6 in Supplement 2). In the mediation analysis, we identified several metabolites (ie, L-tyrosine, oxypurinol, sebacic acid, and β-alanine) that may mediate the effect of air purification intervention on respiratory outcomes (ie, PEF, MEF75%, Feno). Detailed results of metabolomics analysis and mediation analysis can be found in eAppendix 1 in Supplement 2.

Discussion

In this cluster randomized, double-blind, crossover trial, we explored the respiratory benefits of long-duration and wide-coverage indoor air purification for children. Our study provides robust evidence of notably improved pulmonary function and alleviated airway inflammation in children after prolonged air purification. We also identified several metabolites that mediated the effect of air purification on respiratory health. Our study highlights the necessity of reducing PM2.5 exposure among children to safeguard respiratory health.

Our study provides evidence that air purification has a beneficial effect in pulmonary functions. A 2021 randomized crossover trial among students found that after air purification for 5 days, FEV1 increased by 4.4%.10 The estimate from the study by Wang et al10 was smaller in magnitude than our finding (8.04%), which could be due to the shorter duration and air purification in a single setting (classroom).31 Notably, the benefits of pulmonary function estimated in our study are consistently higher (ranging from a 2- to 5-fold increase) than those reported in several previous randomized crossover trials among teenagers and older individuals in China.10,17,32 Childhood is a vital stage for the growth, barrier, and immune development of the respiratory system,6,7,8 which may contribute to the higher respiratory benefits from air purification in our study population compared with older populations. Combined evidence from cohort studies also highlighted that reduced air pollution exposure could improve respiratory growth and function in children.6,33 The benefits in pulmonary function associated with air purification could be biologically plausible. Due to its small aerodynamic diameter, PM2.5 can enter the small airway and deposit in the pulmonary alveolus,34 which may induce local oxidative stress as well as small-airway inflammation and dysfunction.35,36 Consequently, these early detrimental changes in small airways constitute the pathological basis of respiratory diseases.36 The HEPA in air purifiers can dislodge PM2.5 in indoor air and reduce the inhalation of PM2.5 for children. Considering the vulnerability of the respiratory system in children and the far-reaching adverse impacts of childhood air pollution exposure, it is vital to protect children from hazardous PM2.5 exposure.37

Our findings indicated that air purification could alleviate airway inflammation levels in children, manifesting as reduced Feno levels. Feno level is regarded as an indirect marker for elevated airway inflammation, reflecting the inflammatory status of both the upper and lower airways.22 A higher Feno typically represents a higher level of airway inflammation38 and is widely observed to be associated with PM2.5 exposure.39,40 Several RCTs among children found that single-setting (dormitory or classroom) air purification could reduce concentration of Feno approximately 14.37% to 14.70%,10,31 which is smaller than our estimate (22.38%). We also found that the Feno reduction in children due to air purification was greater compared with previous findings obtained in trials among adults.10,32 According to the EBC-based metabolomic analysis, we identified that β-alanine, L-tyrosine, sebacic acid, and oxypurinol may mediate the respiratory benefits of air purification. These metabolites have been linked to PM2.5 exposure in several observational studies.41,42 A detailed discussion on Feno and metabolome is provided in eAppendix 2 in Supplement 2.

Our study presents notable strengths. First, the randomized crossover trial design could facilitate the causality in our findings regarding air purification and respiratory benefits among children. Second, we designed a multisetting (including classroom and bedroom) air purification to achieve a wider coverage of air quality intervention and longer duration, allowing for a more effective and comprehensive capturing of the respiratory benefits associated with air purification. Third, we tested metabolomics based on EBC samples, which could allow for a more extensive exploration of the underlying mechanisms.

Limitations

This study has several limitations. First, this study excluded some unqualified participants in the final statistical analyses, which may add some statistical uncertainty. Second, this trial only recruited healthy pupils in a Chinese city, so our findings may not be easily generalizable to other populations, such as those with chronic diseases. Third, due to the lack of personal 24-hour continuous monitoring, exposures in outdoor environment and indoor environments other than classrooms and bedrooms may not be accurately evaluated. However, these exposure measurement errors were not likely to introduce substantial confounding, as all children lived in a very small area around the school, and these exposure errors could be largely balanced by our crossover design. Fourth, the collected volume of EBC biospecimens was only enough for metabolomics analysis, and the remaining volume was not sufficient to conduct further laboratory analyses, including validating the identified metabolites and exploring other biomarkers.

Conclusions

This double-blind, cluster randomized clinical trial presents robust and holistic evidence that indoor air purification improved respiratory health among children. The notable respiratory benefits estimated in our study highlight the necessity for children to receive sustained and intensified indoor air purification in regions with high air pollution levels.

Supplement 1.

Trial Protocol and Statistical Analysis Plan

jamapediatr-e245049-s001.pdf (249.9KB, pdf)
Supplement 2.

eMethods.

eAppendix 1. Supplementary Results

eAppendix 2. Supplementary Discussion

eReferences

eFigure. Schematic Diagram and Design of the Multisetting Air Purification Intervention

eTable 1. Operation Scheme of Fresh Air Ventilations and Air Purifiers During the Air Purification Periods

eTable 2. Descriptive Statistics of PM2.5 and Temperature and Relative Humidity of the Outdoor Environment of the School Site in Different Study Periods

eTable 3. Descriptive Statistics of the Pulmonary Function and Airway Inflammation Indicators Among Children Before and After the True or Sham Air Purification

eTable 4. Absolute Changes and Relative Changes of Pulmonary Function Indicators Related to Air Purification Among Children

eTable 5. Different Expressed Metabolites in EBC Samples for true Air Purification Compared With Sham Air Purification

eTable 6. Metabolic Pathways Associated With Air Purification in the EBC Samples of Children

jamapediatr-e245049-s002.pdf (719.7KB, pdf)
Supplement 3.

Data Sharing Statement

jamapediatr-e245049-s003.pdf (15.2KB, pdf)

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Associated Data

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

Supplementary Materials

Supplement 1.

Trial Protocol and Statistical Analysis Plan

jamapediatr-e245049-s001.pdf (249.9KB, pdf)
Supplement 2.

eMethods.

eAppendix 1. Supplementary Results

eAppendix 2. Supplementary Discussion

eReferences

eFigure. Schematic Diagram and Design of the Multisetting Air Purification Intervention

eTable 1. Operation Scheme of Fresh Air Ventilations and Air Purifiers During the Air Purification Periods

eTable 2. Descriptive Statistics of PM2.5 and Temperature and Relative Humidity of the Outdoor Environment of the School Site in Different Study Periods

eTable 3. Descriptive Statistics of the Pulmonary Function and Airway Inflammation Indicators Among Children Before and After the True or Sham Air Purification

eTable 4. Absolute Changes and Relative Changes of Pulmonary Function Indicators Related to Air Purification Among Children

eTable 5. Different Expressed Metabolites in EBC Samples for true Air Purification Compared With Sham Air Purification

eTable 6. Metabolic Pathways Associated With Air Purification in the EBC Samples of Children

jamapediatr-e245049-s002.pdf (719.7KB, pdf)
Supplement 3.

Data Sharing Statement

jamapediatr-e245049-s003.pdf (15.2KB, pdf)

Articles from JAMA Pediatrics are provided here courtesy of American Medical Association

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