Evidence map›Paper›PMID 23571405›Full record

ArticleJournal of exposure science & environmental epidemiology

Effects of ambient air pollution measurement error on health effect estimates in time-series studies: a simulation-based analysis.

Matthew J Strickland, Katherine M Gass, Gretchen T Goldman, James A Mulholland

Abstract read
In one paragraph

Article in Journal of exposure science & environmental epidemiology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
–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

27 citing papers in PubMed.

  1. Article
  2. Article
  3. Measurement error correction for ambient PMEnvironmental research · 2023
    Article
  4. Article
  5. Assessing the health estimation capacity of air pollution exposure prediction models.Environmental health : a global access science source · 2022
    Article
  6. Association between ambient PMFrontiers in public health · 2022
    Article
  7. Article
  8. Article
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  10. Article
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  12. Article
  13. Review
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  15. Article
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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

4 authors.

Matthew J StricklandDepartment of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA.
Katherine M GassDepartment of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA.
Gretchen T GoldmanSchool of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA.
James A MulhollandSchool of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA.

Funding

Relationships between air pollutants and asthma exacerbations in a birth cohortK01ES019877 · NIEHS · EMORY UNIVERSITY · PI STRICKLAND, MATTHEW J. · 2010 to 2014
$639k
NIEHS NIH HHS K01 ES019877NIEHS NIH HHS K01ES019877
6 · The paper itself

Abstract

In this study, we investigated bias caused by spatial variability and spatial heterogeneity in outdoor air-pollutant concentrations, instrument imprecision, and choice of daily pollutant metric on risk ratio (RR) estimates obtained from a Poisson time-series analysis. Daily concentrations for 12 pollutants were simulated for Atlanta, Georgia, at 5 km resolution during a 6-year period. Viewing these as being representative of the true concentrations, a population-level pollutant health effect (RR) was specified, and daily counts of health events were simulated. Error representative of instrument imprecision was added to the simulated concentrations at the locations of fixed site monitors in Atlanta, and these mismeasured values were combined to create three different city-wide daily metrics (central monitor, unweighted average, and population-weighted average). Given our assumptions, the median bias in the RR per unit increase in concentration was found to be lowest for the population-weighted average metric. Although the Berkson component of error caused bias away from the null in the log-linear models, the net bias due to measurement error tended to be towards the null. The relative differences in bias among the metrics were lessened, although not eliminated, by scaling results to interquartile range increases in concentration.

Indexed as

BiasAir PollutantsAir PollutionComputer SimulationEnvironmental ExposureEnvironmental MonitoringGeorgiaHumansOdds RatioPoisson DistributionSpatial AnalysisUrban PopulationAir Pollutants

Identifiers

PMID23571405
PMCPMC4721572

What OpenQuestion holds

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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.