Evidence map›Paper›PMID 35259180›Full record

SynthesisPloS one2022

Potential health benefits of eliminating traffic emissions in urban areas.

Shahram Heydari, Masoud Asgharian, Frank J Kelly, Rahul Goel

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 45% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. 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 4 institutions in 3 countries.

Shahram HeydariDepartment of Civil, Maritime, and Environmental Engineering, University of Southampton, Southampton, United Kingdom.ORCID 0000-0001-5497-4909
Masoud AsgharianDepartment of Mathematics and Statistics, McGill University, Montreal, Canada.
Frank J KellyHumphrey Battcock Chair of Community Health & Policy, Environmental Research Group, School of Public Health, Faculty of Medicine, Imperial College London, London, United Kingdom.
Rahul GoelTransportation Research and Injury Prevention Centre, Indian Institute of Technology Delhi, New Delhi, India.
Imperial College London · GBIndian Institute of Technology Delhi · INMcGill University · CAUniversity of Southampton · GB

Funding

Medical Research Council MR/L01341X/1
6 · The paper itself

Abstract

Traffic is one of the major contributors to PM2.5 in cities worldwide. Quantifying the role of traffic is an important step towards understanding the impact of transport policies on the possibilities to achieve cleaner air and accompanying health benefits. With the aim of estimating potential health benefits of eliminating traffic emissions, we carried out a meta-analysis using the World Health Organisation (WHO) database of source apportionment studies of PM2.5 concentrations. Specifically, we used a Bayesian meta-regression approach, modelling both overall and traffic-related (tailpipe and non-tailpipe) concentrations simultaneously. We obtained the distributions of expected PM2.5 concentrations (posterior densities) of different types for 117 cities worldwide. Using the non-linear Integrated Exposure Response (IER) function of PM2.5, we estimated percent reduction in different disease endpoints for a scenario with complete removal of traffic emissions. We found that eliminating traffic emissions results in achieving the WHO-recommended concentration of PM2.5 only for a handful of cities that already have low concentrations of pollution. The percentage reduction in premature mortality due to cardiovascular and respiratory diseases increases up to a point (30-40 ug/m3), and above this concentration, it flattens off. For diabetes-related mortality, the percentage reduction in mortality decreases with increasing concentrations-a trend that is opposite to other outcomes. For cities with high concentrations of pollution, the results highlight the need for multi-sectoral strategies to reduce pollution. The IER functions of PM2.5 result in diminishing returns of health benefits at high concentrations, and in case of diabetes, there are even negative returns. The results show the significant effect of the shape of IER functions on health benefits. Overall, despite the diminishing results, a significant burden of deaths can be prevented by policies that aim to reduce traffic emissions even at high concentrations of pollution.

Indexed as

Air PollutantsAir PollutionBayes TheoremCitiesEnvironmental MonitoringParticulate MatterVehicle EmissionsAir PollutantsParticulate MatterVehicle Emissions

Identifiers

PMID35259180
PMCPMC8903244
OpenAlexW4220821208

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.