Evidence map›Paper›PMID 22475217›Full record

ArticleThe Science of the total environment2012

An analysis of asthma hospitalizations, air pollution, and weather conditions in Los Angeles County, California.

Paul L Delamater, Andrew O Finley, Sudipto Banerjee

Abstract read
In one paragraph

Article in The Science of the total environment, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 2 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

25 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
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  5. Review
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  11. The externalities of energy production in the context of development of clean energy generation.Environmental science and pollution research international · 2020
    Review
  12. Article
  13. Article
  14. Article
  15. Early-life exposure to PMEnvironmental health : a global access science source · 2018
    Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Inflammasome Activity in Non-Microbial Lung Inflammation.Journal of environmental immunology and toxicology · 2014
    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

3 authors.

Paul L DelamaterDepartment of Geography at the Michigan State University, East Lansing, MI 48824-1222, USA.
Andrew O Finley
Sudipto Banerjee

Funding

Hierarchical spatial process models for estimating and predicting health effectsRC1GM092400 · NIGMS · UNIVERSITY OF MINNESOTA · PI BANERJEE, SUDIPTO · 2009 to 2010
$610k
NIGMS NIH HHS 1-RC1-GM092400-01NIGMS NIH HHS RC1 GM092400
6 · The paper itself

Abstract

There is now a large body of literature supporting a linkage between exposure to air pollutants and asthma morbidity. However, the extent and significance of this relationship varies considerably between pollutants, location, scale of analysis, and analysis methods. Our primary goal is to evaluate the relationship between asthma hospitalizations, levels of ambient air pollution, and weather conditions in Los Angeles (LA) County, California, an area with a historical record of heavy air pollution. County-wide measures of carbon monoxide (CO), nitrogen dioxide (NO(2)), ozone (O(3)), particulate matter<10 μm (PM(10)), particulate matter<2.5 μm (PM(2.5)), maximum temperature, and relative humidity were collected for all months from 2001 to 2008. We then related these variables to monthly asthma hospitalization rates using Bayesian regression models with temporal random effects. We evaluated model performance using a goodness of fit criterion and predictive ability. Asthma hospitalization rates in LA County decreased between 2001 and 2008. Traffic-related pollutants, CO and NO(2), were significant and positively correlated with asthma hospitalizations. PM(2.5) also had a positive, significant association with asthma hospitalizations. PM(10), relative humidity, and maximum temperature produced mixed results, whereas O(3) was non-significant in all models. Inclusion of temporal random effects satisfies statistical model assumptions, improves model fit, and yields increased predictive accuracy and precision compared to their non-temporal counterparts. Generally, pollution levels and asthma hospitalizations decreased during the 9 year study period. Our findings also indicate that after accounting for seasonality in the data, asthma hospitalization rate has a significant positive relationship with ambient levels of CO, NO(2), and PM(2.5).

Indexed as

WeatherAir PollutionAsthmaBayes TheoremCaliforniaCarbon MonoxideEnvironmental MonitoringEpidemiological MonitoringHospitalizationHumansModels, StatisticalNitrogen DioxideOzoneParticulate MatterCarbon MonoxideNitrogen DioxideOzoneParticulate Matter

Identifiers

PMID22475217
PMCPMC4451222

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Registered trials

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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.