Evidence map›Paper›PMID 35329265›Full record

ArticleInternational journal of environmental research and public health2022

Daily Associations of Air Pollution and Pediatric Asthma Risk Using the Biomedical REAI-Time Health Evaluation (BREATHE) Kit.

Hua Hao, Sandrah P Eckel, Anahita Hosseini, Eleanne D S Van Vliet, Eldin Dzubur, Genevieve Dunton, Shih Ying Chang, Kenneth Craig, Rose Rocchio, Theresa Bastain and 6 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Observational
  4. Article
  5. Article
  6. Prediction of Asthma Exacerbations in Children.Journal of personalized medicine · 2023
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Hua HaoDepartment of Population and Public Health Sciences, University of Southern California, Los Angeles, CA 90039, USA.
Sandrah P EckelDepartment of Population and Public Health Sciences, University of Southern California, Los Angeles, CA 90039, USA.
Anahita HosseiniDepartment of Computer Science, University of California Los Angeles, Los Angeles, CA 90095, USA.
Eleanne D S Van VlietHealth Effects Institute, Boston, MA 02110, USA.
Eldin DzuburDepartment of Population and Public Health Sciences, University of Southern California, Los Angeles, CA 90039, USA.
Genevieve DuntonDepartment of Population and Public Health Sciences, University of Southern California, Los Angeles, CA 90039, USA.
Shih Ying ChangSonoma Technology, Inc., Petaluma, CA 94954, USA.
Kenneth CraigSonoma Technology, Inc., Petaluma, CA 94954, USA.
Rose RocchioMobilize Labs, University of California Los Angeles, Los Angeles, CA 90095, USA.
Theresa BastainDepartment of Population and Public Health Sciences, University of Southern California, Los Angeles, CA 90039, USA.
Frank GillilandDepartment of Population and Public Health Sciences, University of Southern California, Los Angeles, CA 90039, USA.
Sande OkeloDepartment of Pediatrics, University of California Los Angeles, Los Angeles, CA 90095, USA.
Mindy K RossDepartment of Pediatrics, University of California Los Angeles, Los Angeles, CA 90095, USA.ORCID 0000-0001-7974-4309
Majid SarrafzadehDepartment of Computer Science, University of California Los Angeles, Los Angeles, CA 90095, USA.
Alex A T BuiMedical & Imaging Informatics Group, Department of Radiological Sciences, University of California Los Angeles, Los Angeles, CA 90095, USA.
Rima HabreDepartment of Population and Public Health Sciences, University of Southern California, Los Angeles, CA 90039, USA.ORCID 0000-0003-2103-1706

Funding

Translational Research Support CoreP30ES007048 · NIEHS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI ROB S MCCONNELL · 1996 to 2026
$46.4M
The Los Angeles PRISMS Center: The Biomedical REAl-Time Health Evaluation (BREATHE) PlatformU54EB022002 · NIBIB · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI BUI, ALEX · 2015 to 2016
$6.1M
Pediatric Research using Integrated Sensor Monitoring Systems (PRISMS): Data and Software Coordination and Integration Center (DSCIC)U24EB021996 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI AMBITE, JOSE LUIS, ECKEL, SANDRAH PROCTOR · 2015 to 2015
$5.2M
NIBIB NIH HHS U24 EB021996NIBIB NIH HHS U54 EB022002NIH HHS P30 ES007048
6 · The paper itself

Abstract

Background: Exposure to air pollution is associated with acute pediatric asthma exacerbations, including reduced lung function, rescue medication usage, and increased symptoms; however, most studies are limited in investigating longitudinal changes in these acute effects. This study aims to investigate the effects of daily air pollution exposure on acute pediatric asthma exacerbation risk using a repeated-measures design. Methods: We conducted a panel study of 40 children aged 8−16 years with moderate-to-severe asthma. We deployed the Biomedical REAI-Time Health Evaluation (BREATHE) Kit developed in the Los Angeles PRISMS Center to continuously monitor personal exposure to particulate matter of aerodynamic diameter < 2.5 µm (PM2.5), relative humidity and temperature, geolocation (GPS), and asthma outcomes including lung function, medication use, and symptoms for 14 days. Hourly ambient (PM2.5, nitrogen dioxide (NO2), ozone (O3)) and traffic-related (nitrogen oxides (NOx) and PM2.5) air pollution exposures were modeled based on location. We used mixed-effects models to examine the association of same day and lagged (up to 2 days) exposures with daily changes in % predicted forced expiratory volume in 1 s (FEV1) and % predicted peak expiratory flow (PEF), count of rescue inhaler puffs, and symptoms. Results: Participants were on average 12.0 years old (range: 8.4−16.8) with mean (SD) morning %predicted FEV1 of 67.9% (17.3%) and PEF of 69.1% (18.4%) and 1.4 (3.5) puffs per day of rescue inhaler use. Participants reported chest tightness, wheeze, trouble breathing, and cough symptoms on 36.4%, 17.5%, 32.3%, and 42.9%, respectively (n = 217 person-days). One SD increase in previous day O3 exposure was associated with reduced morning (beta [95% CI]: −4.11 [−6.86, −1.36]), evening (−2.65 [−5.19, −0.10]) and daily average %predicted FEV1 (−3.45 [−6.42, −0.47]). Daily (lag 0) exposure to traffic-related PM2.5 exposure was associated with reduced morning %predicted PEF (−3.97 [−7.69, −0.26]) and greater odds of “feeling scared of trouble breathing” symptom (odds ratio [95% CI]: 1.83 [1.03, 3.24]). Exposure to ambient O3, NOx, and NO was significantly associated with increased rescue inhaler use (rate ratio [95% CI]: O3 1.52 [1.02, 2.27], NOx 1.61 [1.23, 2.11], NO 1.80 [1.37, 2.35]). Conclusions: We found significant associations of air pollution exposure with lung function, rescue inhaler use, and “feeling scared of trouble breathing.” Our study demonstrates the potential of informatics and wearable sensor technologies at collecting highly resolved, contextual, and personal exposure data for understanding acute pediatric asthma triggers.

Indexed as

Air PollutantsAir PollutionAsthmaOzoneChildEnvironmental ExposureHumansNitrogen DioxideParticulate MatterAir PollutantsNitrogen DioxideOzoneParticulate MatterGPSmobile healthpediatric asthmapersonal air pollutionPRISMSsensors

Identifiers

PMID35329265
PMCPMC8950308

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.