Evidence map›Paper›PMID 32962012›Full record

ReviewToxics2020

Environmental Health Surveillance System for a Population Using Advanced Exposure Assessment.

Wonho Yang, Jinhyeon Park, Mansu Cho, Cheolmin Lee, Jeongil Lee, Chaekwan Lee

Abstract readReview
In one paragraph

Review in Toxics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Wonho YangDepartment of Occupational Health, Daegu Catholic University, Gyeongsan-si, Gyeongbuk 38430, Korea.ORCID 0000-0003-2776-5989
Jinhyeon ParkCenter of Environmental Health Monitoring, Daegu Catholic University, Gyeongsan-si, Gyeongbuk 38430, Korea.ORCID 0000-0002-9181-6739
Mansu ChoDepartment of Occupational Health, Daegu Catholic University, Gyeongsan-si, Gyeongbuk 38430, Korea.
Cheolmin LeeDepartment of Nano and Biological Engineering, Seo Kyeong University, Seoul 02713, Korea.
Jeongil LeeKorea Testing and Research Institute, Gwacheon-si, Gyeonggi-do 13810, Korea.
Chaekwan LeeDepartment of Occupational and Environmental Medicine, Busan Paik Hospital and Institute of Environmental and Occupational Medicine, Inje University, Busan 47392, Korea.

Funding

Korea Environmental Industry and Technology Institute 2018001350001
6 · The paper itself

Abstract

Human exposure to air pollution is a major public health concern. Environmental policymakers have been implementing various strategies to reduce exposure, including the 10th-day-no-driving system. To assess exposure of an entire population of a community in a highly polluted area, pollutant concentrations in microenvironments and population time-activity patterns are required. To date, population exposure to air pollutants has been assessed using air monitoring data from fixed atmospheric monitoring stations, atmospheric dispersion modeling, or spatial interpolation techniques for pollutant concentrations. This is coupled with census data, administrative registers, and data on the patterns of the time-based activities at the individual scale. Recent technologies such as sensors, the Internet of Things (IoT), communications technology, and artificial intelligence enable the accurate evaluation of air pollution exposure for a population in an environmental health context. In this study, the latest trends in published papers on the assessment of population exposure to air pollution were reviewed. Subsequently, this study proposes a methodology that will enable policymakers to develop an environmental health surveillance system that evaluates the distribution of air pollution exposure for a population within a target area and establish countermeasures based on advanced exposure assessment.

Indexed as

air pollutionenvironmental health surveillance systemexposure assessmentpopulation exposure

Identifiers

PMID32962012
PMCPMC7560317

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.