Evidence map›Paper›PMID 28983855›Full record

ReviewCurrent environmental health reports2017

Incorporating Measurement Error from Modeled Air Pollution Exposures into Epidemiological Analyses.

Evangelia Samoli, Barbara K Butland

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current environmental health reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

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

  1. Mortality and Morbidity Effects of Long-Term Exposure to Low-Level PMResearch report (Health Effects Institute) · 2021
    Pooled it
  2. Review
  3. Comparison of High Spatial Resolution PMEnvironmental science & technology · 2026
    Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Assessment of Spatial Variability across Multiple Pollutants in Auckland, New Zealand.International journal of environmental research and public health · 2019
    Article
  18. Review
  19. Bayesian network-based framework for exposure-response study design and interpretation.Environmental health : a global access science source · 2019
    Article
  20. 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

2 authors.

Evangelia SamoliDepartment of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, 75 Mikras Asias Str, 115 27, Athens, Greece. esamoli@med.uoa.gr.
Barbara K ButlandPopulation Health Research Institute and MRC-PHE Centre for Environment and Health, St George's, University of London, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewOutdoor air pollution exposures used in epidemiological studies are commonly predicted from spatiotemporal models incorporating limited measurements, temporal factors, geographic information system variables, and/or satellite data. Measurement error in these exposure estimates leads to imprecise estimation of health effects and their standard errors. We reviewed methods for measurement error correction that have been applied in epidemiological studies that use model-derived air pollution data. RECENT

findingsWe identified seven cohort studies and one panel study that have employed measurement error correction methods. These methods included regression calibration, risk set regression calibration, regression calibration with instrumental variables, the simulation extrapolation approach (SIMEX), and methods under the non-parametric or parameter bootstrap. Corrections resulted in small increases in the absolute magnitude of the health effect estimate and its standard error under most scenarios. Limited application of measurement error correction methods in air pollution studies may be attributed to the absence of exposure validation data and the methodological complexity of the proposed methods. Future epidemiological studies should consider in their design phase the requirements for the measurement error correction method to be later applied, while methodological advances are needed under the multi-pollutants setting.

Indexed as

Epidemiologic Research DesignResearch DesignAir PollutantsAir PollutionEnvironmental ExposureEnvironmental MonitoringHumansSpatial AnalysisAir PollutantsAir pollutionBootstrapHealthMeasurement errorRegression calibrationSIMEX

Identifiers

What OpenQuestion holds

Textmetadata
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.