Evidence map›Paper›PMID 35608861›Full record

ArticleJAMA network open2022

Air Pollution, Socioeconomic Status, and Age-Specific Mortality Risk in the United States.

Antonio Fernando Boing, Priyanka deSouza, Alexandra Crispim Boing, Rockli Kim, S V Subramanian

Abstract read
In one paragraph

Article in JAMA network open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Equity in the Distribution of Regulatory PMEnvironmental science & technology · 2025
    Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Review
  18. PMThe Lancet regional health. Western Pacific · 2024
    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

5 authors.

Antonio Fernando BoingPost-Graduate Program in Public Health, Federal University of Santa Catarina, Florianópolis, Brazil.
Priyanka deSouzaUrban and Regional Planning Department, University of Colorado Denver, Denver.
Alexandra Crispim BoingPost-Graduate Program in Public Health, Federal University of Santa Catarina, Florianópolis, Brazil.
Rockli KimDivision of Health Policy and Management, College of Health Sciences, Korea University, Seoul, South Korea.
S V SubramanianHarvard Center for Population and Development Studies, Cambridge, Massachusetts.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Prior studies on the association between fine particulate matter with diameters 2.5 μm or smaller (PM2.5) and probability of death have not applied multilevel analysis disaggregating data for US census tract, states, and counties, nor tested its interaction by socioeconomic status (SES). Such an approach could provide a more refined identification and targeting of populations exposed to increased risk from PM2.5. Objective: To assess the association between PM2.5 and age-specific mortality risk (ASMR) using disaggregated data at the census tract level and evaluate such association according to census tract SES. Design, Setting, and Participants: This nationwide cross-sectional study used a linkage of 3 different data sets. ASMR for the period of 2010 to 2015 was obtained from the National Center for Health Statistic, SES data covering a period from 2006 to 2016 came from the American Community Survey, and mean PM2.5 exposure levels from 2010 to 2015 were derived from well-validated atmospheric chemistry and machine learning models. Data were analyzed in April 2021. Exposures: The main exploratory variable was mean census tract-level long-term exposure to PM2.5 from 2010 to 2015. Main Outcomes and Measures: The primary outcome was census tract-level ASMR. Multilevel models were used to quantify the geographic variation in ASMR at levels of census tract, county, and state. Additional analysis explored the interaction of SES in the association of ASMR with PM2.5 exposure. Results: Data from 67 148 census tracts nested in 3087 counties and 50 states were analyzed. The association between exposure to PM2.5 and ASMR varied substantially across census tracts. The magnitude of such association also varied across age groups, being higher among adults and older adults. Census tracts accounted for most of the total geographic variation in mortality risk (range, 77.0%-94.2%). ASMR was higher in deciles with greater PM2.5 concentration. For example, ASMR for age 75 to 84 years was 54.6 per 1000 population higher in the decile with the second-highest PM2.5 concentration than in the decile with the lowest PM2.5 concentration. The ASMR, PM2.5 concentrations, and magnitude of the association between both were higher in the census tracts with the lowest SES. Conclusions and Relevance: This cross-sectional study found that census tracts with lower SES presented higher PM2.5 concentrations. ASMR and air pollution varied substantially across census tracts. There was an association between air pollution and ASMR across all age groups in the United States. These findings suggest that equitable public policies aimed at improving air quality are needed and important to increase life expectancy.

Indexed as

Air PollutantsAir PollutionAgedAged, 80 and overAge FactorsCross-Sectional StudiesEnvironmental ExposureHumansParticulate MatterSocial ClassUnited StatesAir PollutantsParticulate Matter

Identifiers

PMID35608861
PMCPMC9131742

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.