Evidence map›Paper›PMID 34574793›Full record

ArticleInternational journal of environmental research and public health2021

Application of Standardized Proportional Mortality Ratio to the Assessment of Health Risk in Relatively Healthy Populations: Using a Study of Cancer Risk in Telecommunication Workers with Excess Exposure to Acid Mists as an Example.

Ying-Fong Ker, Perng-Jy Tsai, How-Ran Guo

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 42% 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 3 citations in OpenAlex.

  1. Pooled it
  2. Big Data, Decision Models, and Public Health.International journal of environmental research and public health · 2022
    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 at 3 institutions in 2 countries.

Ying-Fong KerDepartment of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan.
Perng-Jy TsaiDepartment of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan.
How-Ran GuoDepartment of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan.ORCID 0000-0003-3343-3446
Los Angeles County Department of Public Health · USNational Cheng Kung University · TWNational Cheng Kung University Hospital · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

When a study population is relatively healthy, such as an occupational population, epidemiological studies are likely to underestimate risk. We used a case study on the cancer risk of workers with exposure to acid mists, a well-documented carcinogen, to demonstrate that using proportional mortality ratios (PMRs) is more appropriate than mortality ratios in assessing risk in terms of mortality. The study included 10,229 employees of a telecommunication company who worked in buildings with battery rooms. In these buildings, the battery rooms had the highest levels of sulfuric acid in the air (geometric mean = 10.7 μg/m

Indexed as

NeoplasmsOccupational DiseasesOccupational ExposureTelecommunicationsCause of DeathHumansTaiwanacid misthealthy worker effectneoplasmoccupational exposurestandardized mortality ratiostandardized proportional mortality ratiostomach neoplasmssulfuric acid

Identifiers

PMID34574793
PMCPMC8469327
OpenAlexW3200982586

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.