Evidence map›Paper›PMID 28975928›Full record

SynthesisJournal of exposure science & environmental epidemiology2018

Meta-analysis of job-exposure matrix data from multiple sources.

Wenting Cheng, Benjamin Roberts, Bhramar Mukherjee, Richard L Neitzel

Open access · greenAbstract readMeta-Analysis
In one paragraph

Synthesis in Journal of exposure science & environmental epidemiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
3.1field-weighted citation impact, top 9% of its field
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

5 citing papers in PubMed, 15 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Imputation of missing values in a large job exposure matrix using hierarchical information.Journal of exposure science & environmental epidemiology · 2018
    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

4 authors at 1 institution in 1 country.

Wenting ChengDepartment of Biostatistics, University of Michigan, School of Public Health, Ann Arbor, Michigan, USA.
Benjamin RobertsDepartment of Environmental Health Sciences, University of Michigan, School of Public Health, Ann Arbor, Michigan, USA.
Bhramar MukherjeeDepartment of Biostatistics, University of Michigan, School of Public Health, Ann Arbor, Michigan, USA.
Richard L NeitzelDepartment of Environmental Health Sciences, University of Michigan, School of Public Health, Ann Arbor, Michigan, USA.
University of Michigan–Ann Arbor · US

Funding

Development of a US/Canadian Job Exposure Matrix for NoiseR21OH010482 · OH · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI NEITZEL, RICHARD L · 2013 to 2014
$404k
NIOSH CDC HHS R21 OH010482
6 · The paper itself

Abstract

The objectives of this study were to determine the heterogeneity of data sources used to construct a job-exposure matrix (JEM) for occupational noise, and to calculate pooled exposure estimates for different job titles using different sources. The JEM was populated with measurements from government databases, private industry, and the published literature. Data were organized by job title using the US standard occupational classification (SOC). Using data from the literature as prior information, adjusted mean exposure was calculated for both the government and industry data following a simple Bayesian approach. A meta-analysis was conducted to measure data heterogeneity across sources and to calculate a pooled exposure estimate for each SOC and SOC group. In total, 715,867 measurements across 259 SOCs were analyzed. Using the data from literature as a prior, 15 of 28 applicable SOCs in the government and industry data had adjusted mean exposures above the OSHA action level (85 dBA). The meta-analysis showed that 63% of SOCs, and 78% of SOC groups, had moderate to high heterogeneity. Fifty-one percent of SOCs and 43% of SOC groups had pooled estimated exposures >85 dBA. The pooled estimates suggested that workers in 131 of 259 SOCs (51%) were exposed beyond the threshold of 85 dBA.

Indexed as

Bayes TheoremDatabases, FactualEnvironmental MonitoringEpidemiologic MethodsHumansOccupational ExposureOccupationsRisk AssessmentUnited States

Identifiers

PMID28975928
PMCPMC9936531
OpenAlexW2762890935

What OpenQuestion holds

Textmetadata
LicenceTDM
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.