Evidence map›Paper›PMID 38274545›Full record

ArticleFrontiers in public health2023

Health damage assessment of commuters and staff in the metro system based on field monitoring-A case study of Nanjing.

Shu Su, Shuhao Li, Yujie Ding, Peng Mao, Dan Chong

Abstract read
In one paragraph

Article in Frontiers in public health, 2023. 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

5 authors.

Shu SuDepartment of Construction and Real Estate, School of Civil Engineering, Southeast University, Nanjing, China.
Shuhao LiDepartment of Construction and Real Estate, School of Civil Engineering, Southeast University, Nanjing, China.
Yujie DingDepartment of Construction and Real Estate, School of Civil Engineering, Southeast University, Nanjing, China.
Peng MaoDepartment of Engineering Management, School of Civil Engineering, Nanjing Forestry University, Nanjing, China.
Dan ChongDepartment of Management Science and Engineering, School of Management, Shanghai University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The metro has emerged as a major mode of transportation. A significant number of commuters and staff in the metro system are exposed to air pollutants because of its shielded environment, and substantial health damage requires quantitative assessment. Previous studies have focused on comparing the health impacts among different transportation modes, overlooking the specific population characteristics and pollutant distribution in metro systems. Methods: To make improvements, this study implements field monitoring of the metro's air environment utilizing specialized instruments and develops a health damage assessment model. The model quantifies health damage of two main groups (commuters and staff) in metro systems at three different areas (station halls, platforms, and metro cabins) due to particulate matter 10 and benzene series pollution. Conclusion: A case study of Nanjing Metro Line 3 was conducted to demonstrate the applicability of the model. Health damage at different metro stations was analyzed, and the health damage of commuters and staff was assessed and compared. This study contributes to enhancing research on health damage in the metro systems by providing a reference for mitigation measures and guiding health subsidy policies.

Indexed as

Air PollutantsAir PollutionEnvironmental MonitoringHumansParticulate MatterTransportationAir PollutantsParticulate Matterair pollutioncase analysisfield monitoringhealth damage assessmentmetro station

Identifiers

PMID38274545
PMCPMC10808693

What OpenQuestion holds

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LicenceCC BY
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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.