Evidence map›Paper›PMID 28946686›Full record

ArticleInternational journal of environmental research and public health2017

Using Structural Equation Modeling to Assess the Links between Tobacco Smoke Exposure, Volatile Organic Compounds, and Respiratory Function for Adolescents Aged 6 to 18 in the United States.

Bonnie E Shook-Sa, Ding-Geng Chen, Haibo Zhou

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.3field-weighted citation impact, top 39% of its field
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

5 citing papers in PubMed, 11 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Bonnie E Shook-SaDepartment of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. bshooksa@live.unc.edu.
Ding-Geng ChenDepartment of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. dinchen@email.unc.edu.
Haibo ZhouDepartment of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. zhou@bios.unc.edu.
University of North Carolina at Chapel Hill · US

Funding

Statistical Methods for Cancer Clinical TrialsP01CA142538 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI DAVIDIAN, MARIE, KOSOROK, MICHAEL R · 2010 to 2019
$21.3M
Statistical Methods for Outcome-Dependent SamplingR01ES021900 · NIEHS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ZHOU, HAIBO · 2013 to 2016
$1.1M
NCI NIH HHS P01 CA142538NIEHS NIH HHS R01 ES021900
6 · The paper itself

Abstract

Asthma is an inflammatory airway disease that affects 22 million Americans in the United States. Research has found associations between impaired respiratory function, including asthma and increased symptoms among asthmatics, and common indoor air pollutants, including tobacco smoke exposure and volatile organic compounds (VOCs). However, findings linking VOC exposure and asthma are inconsistent and studies are of mixed quality due to design limitations, challenges measuring VOC exposure, small sample sizes, and suboptimal statistical methodologies. Because of the correlation between tobacco smoke exposure and VOCs, and associations between both tobacco smoke and VOCs with respiratory function, it is crucial that statistical methodology employed to assess links between respiratory function and individual air pollutants control for these complex relationships. This research uses Structural Equation Modeling (SEM) to assess the relationships between respiratory function, tobacco smoke exposure, and VOC exposure among a nationally-representative sample of adolescents. SEM allows for multiple outcome variables, the inclusion of both observed and latent variables, and controls the effects of confounding and correlated variables, which is critically important and is lacking in earlier studies when estimating the effects of correlated air pollutants on respiratory function. We find evidence of associations between respiratory function and some types of VOCs, even when controlling for the effects of tobacco smoke exposure and additional covariates. Furthermore, we find that poverty has an indirect effect on respiratory function through its relationships with tobacco smoke exposure and some types of VOCs. This analysis demonstrates how SEM is a robust analytic tool for assessing associations between respiratory function and multiple exposures to pollutants.

Indexed as

AdolescentAir Pollution, IndoorChildEnvironmental ExposureEnvironmental MonitoringHumansModels, TheoreticalRespirationTobacco Smoke PollutionUnited StatesVolatile Organic CompoundsTobacco Smoke PollutionVolatile Organic Compoundsasthmastructural equation modelingtobaccovolatile organic compounds

Identifiers

PMID28946686
PMCPMC5664613
OpenAlexW2759428422

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.