Evidence map›Paper›PMID 36571380›Full record

ArticleMedical gas research

Quantitative risk assessment of respiratory exposure to acrylonitrile vapor in petrochemical industry by U.S. Environmental Protection Agency method: a cross-sectional study.

Ali Asghar Sajedian, Ali Karimi, Mohsen Sadeghi Yarandi, Vahid Ahmadi Moshiran, Aysa Ghasemi Koozekonan, Farideh Golbabaei

Abstract read
In one paragraph

Article in Medical gas research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Ali Asghar SajedianDepartment of Occupational Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Ali KarimiDepartment of Occupational Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Mohsen Sadeghi YarandiDepartment of Occupational Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Vahid Ahmadi MoshiranDepartment of Occupational Health Engineering, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran.
Aysa Ghasemi KoozekonanDepartment of Occupational Health Engineering, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Farideh GolbabaeiDepartment of Occupational Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acrylonitrile is a potential carcinogen for humans, and exposure to this substance can cause adverse effects for workers. This study aimed to carcinogenic and health risk assessment of acrylonitrile vapor exposure in exposed personnel of a petrochemical complex. This crosssectional study was performed in 2019 in a petrochemical complex. In this study, to sample and determine acrylonitrile's respiratory exposure, the method provided by the National Institute of Occupational Safety and Health (NIOSH 1601) was used, and a total of 45 inhaled air samples were sampled from men workers, aged 39.43 ± 9.37 years. All subjects' mean exposure to acrylonitrile vapors was 71.1 ± 122.8 μg/m

Indexed as

AcrylonitrileOccupational ExposureCarcinogensCross-Sectional StudiesHumansMaleRisk AssessmentUnited StatesUnited States Environmental Protection AgencyAcrylonitrileCarcinogensacrylonitrileEPA methodHazard Quotienthealth risk assessmentintegrated risk information systemlifetime cancer riskoccupational exposurepetrochemical

Identifiers

PMID36571380
PMCPMC9979210

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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.