Evidence map›Paper›PMID 40400775›Full record

ArticleInternational journal of population data science2023

Laura Scott, Yan Weigang, Marcella Ucci, Jessica Sheringham

Abstract read
In one paragraph

Article in International journal of population data science, 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

4 authors.

Laura ScottLondon Borough of Islington, Public Health Directorate, London N1 2UD, England.
Yan WeigangLondon Borough of Islington, Public Health Directorate, London N1 2UD, England.
Marcella UcciUniversity College London, Bartlett School Env, Energy & Resources, London WC1E 6BT, England.
Jessica SheringhamUniversity College London, Institute of Epidemiology and Healthcare, London WC1E 6BT, England.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This project in one urban local authority in London (England) sought to assess the feasibility of generating locally-derived indices of overcrowding using data available to local councils on the population and their homes.We merged data at household level using the Unique Property Reference Number from publicly available Energy Performance Certificates and commercial property platforms, with data available to councils on the population and their housing characteristics, drawn from multiple sources including council tax bands and council housing databases. Multiple imputation was used to address missing data. Using the dataset, it was possible to generate two indices of overcrowding for households with dependent children, based on the bedroom standard and the space standard, which could be compared with nationally derived estimates. Data challenges: We encountered three challenges with data. 1. Individuals in the population were excluded through linkage with household-level data. 2. Definitions of overcrowding are ambiguous and variably applied. 3. Many local areas face high proportions of missing household data, particularly numbers of bedrooms. We discuss how we addressed such problems and illustrate with a local example how they could affect estimates of overcrowding prevalence. Lessons learned: Further clarity is needed in how bedrooms are defined to compare overcrowding prevalence generated locally and nationally. Access to national records on bedroom numbers would facilitate local areas to identify overcrowding in their own populations. Despite these challenges, we demonstrate it is feasible to generate overcrowding indices that can be useful for researchers and local policy makers seeking to develop or evaluate strategies to address household overcrowding.

Indexed as

CrowdingFamily CharacteristicsHousingHumansLondonadministrative datadata linkagehousingovercrowdingpublic health

Identifiers

PMID40400775
PMCPMC12093136

What OpenQuestion holds

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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.