Evidence map›Paper›PMID 34531034›Full record

ReviewEnvironment international2021

New urban models for more sustainable, liveable and healthier cities post covid19; reducing air pollution, noise and heat island effects and increasing green space and physical activity.

Mark J Nieuwenhuijsen

Abstract readReview
In one paragraph

Review in Environment international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 3 pooled it
–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

52 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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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

1 author.

Mark J NieuwenhuijsenISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain; Mary MacKillop Institute for Health Research, Melbourne, Australia. Electronic address: mark.nieuwenhuijsen@isglobal.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cities are centres of innovation and wealth creation, but also hotspots of air pollution and noise, heat island effects and lack of green space, which are all detrimental to human health. They are also hotspots of COVID19. COVID19 has led to a rethink of urban public space. Therefore, is it time to re-think our urban models and reduce the health burden? We provide a narrative meta-review around a number of cutting edge and visionary urban models that that may affect health and that have been reported over the past few years. New urban concepts such as the Superblocks, the low traffic neighbourhood, 15 Minute city, Car free city or a mixture of these that may go some way in reducing the health burden related to current urban and transport practices. They will reduce air pollution and noise, heat island effects and increase green space and physical activity levels. What is still lacking though is a thorough evaluation of the effectiveness and acceptability of the schemes and the impacts on not only health, but also liveability and sustainability, although they are expected to be positive. Finally, the COVID19 pandemic may accelerate these developments and stimulus funding like the EU Next Generation funding should be used to make these changes.

Indexed as

Air PollutionCOVID-19CitiesCity PlanningExerciseHot TemperatureHumansNoiseParks, RecreationalSARS-CoV-215-minute cityAir pollutionCar free cityCitiesCOVID19Green spaceHeatLow traffic neighbourhoodsNoisePhysical activitySuperblocksTrafficTransportUrban planning

Identifiers

PMID34531034
PMCPMC8457623

What OpenQuestion holds

Textmetadata
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.