Evidence map›Paper›PMID 27315241›Full record

ArticleEnvironmental health perspectives2017

Associations between Source-Specific Fine Particulate Matter and Emergency Department Visits for Respiratory Disease in Four U.S. Cities.

Jenna R Krall, James A Mulholland, Armistead G Russell, Sivaraman Balachandran, Andrea Winquist, Paige E Tolbert, Lance A Waller, Stefanie Ebelt Sarnat

Abstract read
In one paragraph

Article in Environmental health perspectives, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed, 3 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

58 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Chemical constituents of PMEuropean journal of pediatrics · 2025
    Pooled it
  3. Pooled it
  4. Article
  5. Article
  6. Article
  7. Associations of PMThe Journal of international medical research · 2026
    Article
  8. Assessing PMEnvironmental research letters : ERL [Web site] · 2025
    Article
  9. Article
  10. PMEnvironment & health (Washington, D.C.) · 2025
    Article
  11. Review
  12. Article
  13. Article
  14. Comparison of the rate of healthcare encounters for influenza from source-specific PMJournal of exposure science & environmental epidemiology · 2025
    Article
  15. Article
  16. Review
  17. Impact of Chemical Speciation Network method changes on time series ion and carbon species concentrations.Aerosol science and technology : the journal of the American Association for Aerosol Research · 2024
    Article
  18. Article
  19. Article
  20. Article
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

8 authors.

Jenna R KrallDepartment of Biostatistics and Bioinformatics, Emory University, Atlanta, Georgia, USA.
James A Mulholland
Armistead G Russell
Sivaraman Balachandran
Andrea Winquist
Paige E Tolbert
Lance A Waller
Stefanie Ebelt Sarnat

Funding

Environmental Biostatistics Training GrantT32ES012160 · NIEHS · EMORY UNIVERSITY · PI WALLER, LANCE A · 2006 to 2015
$1.3M
Multiple Pollutants and Cardiorespiratory OutcomesR01ES011294 · NIEHS · EMORY UNIVERSITY · PI TOLBERT, PAIGE E · 2002 to 2005
$1.1M
NIEHS NIH HHS R01 ES011294NIEHS NIH HHS T32 ES012160
6 · The paper itself

Abstract

backgroundShort-term exposure to ambient fine particulate matter (PM2.5) concentrations has been associated with increased mortality and morbidity. Determining which sources of PM2.5 are most toxic can help guide targeted reduction of PM2.5. However, conducting multicity epidemiologic studies of sources is difficult because source-specific PM2.5 is not directly measured, and source chemical compositions can vary between cities.

objectivesWe determined how the chemical composition of primary ambient PM2.5 sources varies across cities. We estimated associations between source-specific PM2.5 and respiratory disease emergency department (ED) visits and examined between-city heterogeneity in estimated associations.

methodsWe used source apportionment to estimate daily concentrations of primary source-specific PM2.5 for four U.S. cities. For sources with similar chemical compositions between cities, we applied Poisson time-series regression models to estimate associations between source-specific PM2.5 and respiratory disease ED visits.

resultsWe found that PM2.5 from biomass burning, diesel vehicle, gasoline vehicle, and dust sources was similar in chemical composition between cities, but PM2.5 from coal combustion and metal sources varied across cities. We found some evidence of positive associations of respiratory disease ED visits with biomass burning PM2.5; associations with diesel and gasoline PM2.5 were frequently imprecise or consistent with the null. We found little evidence of associations with dust PM2.5.

conclusionsWe introduced an approach for comparing the chemical compositions of PM2.5 sources across cities and conducted one of the first multicity studies of source-specific PM2.5 and ED visits. Across four U.S. cities, among the primary PM2.5 sources assessed, biomass burning PM2.5 was most strongly associated with respiratory health. Citation: Krall JR, Mulholland JA, Russell AG, Balachandran S, Winquist A, Tolbert PE, Waller LA, Sarnat SE. 2017. Associations between source-specific fine particulate matter and emergency department visits for respiratory disease in four U.S. cities. Environ Health Perspect 125:97-103; http://dx.doi.org/10.1289/EHP271.

Indexed as

Air PollutantsAir PollutionCitiesCoalDustEmergency Service, HospitalEnvironmental ExposureEnvironmental MonitoringGasolineHumansParticulate MatterRespiration DisordersRespiratory Tract DiseasesUnited StatesVehicle EmissionsAir PollutantsCoalDustGasolineParticulate MatterVehicle Emissions

Identifiers

PMID27315241
PMCPMC5226704

What OpenQuestion holds

Textmetadata
LicenceCC0
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.