Evidence map›Paper›PMID 40110549›Full record

ReviewF1000Research2024

The epidemiologic case for urban health: conceptualizing and measuring the magnitude of challenges and potential benefits.

Michael D Garber, Tarik Benmarhnia, Audrey de Nazelle, Mark Nieuwenhuijsen, David Rojas-Rueda

Abstract readReview
In one paragraph

Review in F1000Research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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.

Michael D GarberScripps Institution of Oceanography, University of California San Diego, San Diego, California, USA.
Tarik BenmarhniaScripps Institution of Oceanography, University of California San Diego, San Diego, California, USA.
Audrey de NazelleMRC Centre for Environment and Health, Imperial College London School of Public Health, London, England, UK.
Mark NieuwenhuijsenCIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
David Rojas-RuedaColorado State University, Colorado School of Public Health, Colorado, USA.ORCID https://orcid.org/0000-0001-5854-2484

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We discuss how epidemiology has been and can continue to be used to advance understanding of the links between urban areas and health informed by an existing urban-health conceptual framework. This framework considers urban areas as contexts for health, determinants of health and modifiers of health pathways, and part of a complex system that affects health. We highlight opportunities for descriptive epidemiology to inform the context of urban health, for example, by characterizing the social and physical environments that give rise to health and the actions that change those conditions. We then describe inferential tools for evaluating the impact of group-level actions (e.g., interventions, policies) on urban health, providing some examples, and describing assumptions and challenges. Finally, we discuss opportunities and challenges of applying systems thinking and methods to advance urban health. While different conceptual frames lead to different insights, each perspective demonstrates that urban health is a major and growing challenge. The effectiveness of urban health knowledge, action, and policy as the world continues to urbanize can be informed by applying and expanding upon research and surveillance methods described here.

Indexed as

Urban HealthHumansEpidemiologyGlobal healthPolicy evaluationPublic health surveillanceUrban health

Identifiers

PMID40110549
PMCPMC11920689

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.