Evidence map›Paper›PMID 32656485›Full record

ArticleEnvironmental epidemiology (Philadelphia, Pa.)2020

Estimating long-term pollution exposure effects through inverse probability weighting methods with Cox proportional hazards models.

Joshua D Higbee, Jacob S Lefler, Richard T Burnett, Majid Ezzati, Julian D Marshall, Sun-Young Kim, Matthew Bechle, Allen L Robinson, C Arden Pope

Abstract read
In one paragraph

Article in Environmental epidemiology (Philadelphia, Pa.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Review
  2. Long-term exposure to ambient PMEnvironmental epidemiology (Philadelphia, Pa.) · 2025
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Observational
  11. Article
  12. Parental relationship status and age at autism spectrum disorder diagnosis of their child.Autism : the international journal of research and practice · 2021
    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

9 authors.

Joshua D HigbeeDepartment of Economics, University of Chicago, Chicago, Illinois.
Jacob S LeflerDepartment of Agricultural and Resource Economics, University of California - Berkeley, Berkeley, California.
Richard T BurnettHealth Canada, Ottawa, Ontario, Canada.
Majid EzzatiMRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.
Julian D MarshallDepartment of Civil and Environmental Engineering, University of Washington, Seattle, Washington.
Sun-Young KimDepartment of Cancer Control and Population Health, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang-si, Gyeonggi-do, Korea.
Matthew BechleDepartment of Civil and Environmental Engineering, University of Washington, Seattle, Washington.
Allen L RobinsonEngineering and Public Policy, Carnegie Mellon University, Pittsburgh, Pennsylvania.
C Arden PopeDepartment of Economics, Brigham Young University, Provo, Utah.

Funding

EPA R835873Medical Research Council MR/S019669/1Wellcome Trust 209376/Z/17/Z
6 · The paper itself

Abstract

backgroundFine particulate matter (PM

methodsTwenty-nine years of data from the National Health Interview Survey (NHIS) was compiled and linked to modeled annual average outdoor PM

resultsCovariate-adjusted estimated relative risks per 10 μg/m

conclusionsThese results provide evidence that long-term exposure to PM

Indexed as

Fine particulate matterInverse probability of treatment weightingMortalityNational Health Interview SurveyPollution

Identifiers

PMID32656485
PMCPMC7319228

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.