Evidence map›Paper›PMID 31980846›Full record

ArticleDiabetologia2020

Childhood type 1 diabetes: an environment-wide association study across England.

Annalisa Sheehan, Anna Freni Sterrantino, Daniela Fecht, Paul Elliott, Susan Hodgson

Open access · hybridAbstract read
In one paragraph

Article in Diabetologia, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 2 pooled it
3.1field-weighted citation impact, top 9% 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

23 citing papers in PubMed, 2 syntheses or guidelines pooled it, 33 citations in OpenAlex.

  1. Pooled it
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  17. Critical Overview on Endocrine Disruptors in Diabetes Mellitus.International journal of molecular sciences · 2023
    Review
  18. Review
  19. Adult-onset autoimmune diabetes.Nature reviews. Disease primers · 2022
    Review
  20. 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

5 authors at 3 institutions in 1 country.

Annalisa SheehanMRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, St Mary's Campus, Norfolk Place, London, W2 1PG, UK.
Anna Freni SterrantinoMRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, St Mary's Campus, Norfolk Place, London, W2 1PG, UK.
Daniela FechtMRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, St Mary's Campus, Norfolk Place, London, W2 1PG, UK.
Paul ElliottMRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, St Mary's Campus, Norfolk Place, London, W2 1PG, UK.
Susan HodgsonMRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, St Mary's Campus, Norfolk Place, London, W2 1PG, UK. susan.hodgson@imperial.ac.uk.ORCID 0000-0001-8519-8586
Imperial College London · GBKing's College London · GBNIHR Imperial Biomedical Research Centre · GB

Funding

Medical Research Council MR/L01341X/1Natural Environment Research Council NE/L002485/1Wellcome TrustWellcome Trust 200682/Z/16/Z
6 · The paper itself

Abstract

aims/hypothesisType 1 diabetes is an autoimmune disease affecting ~400,000 people across the UK. It is likely that environmental factors trigger the disease process in genetically susceptible individuals. We assessed the associations between a wide range of environmental factors and childhood type 1 diabetes incidence in England, using an agnostic, ecological environment-wide association study (EnWAS) approach, to generate hypotheses about environmental triggers.

methodsWe undertook analyses at the local authority district (LAD) level using a national hospital episode statistics-based incident type 1 diabetes dataset comprising 13,948 individuals with diabetes aged 0-9 years over the period April 2000 to March 2011. We compiled LAD level estimates for a range of potential demographic and environmental risk factors including meteorological, land use and environmental pollution variables. The associations between type 1 diabetes incidence and risk factors were assessed via Poisson regression, disease mapping and ecological regression.

resultsCase counts by LAD varied from 1 to 236 (median 33, interquartile range 24-46). Overall type 1 diabetes incidence was 21.2 (95% CI 20.9, 21.6) per 100,000 individuals. The EnWAS and disease mapping indicated that 15 out of 53 demographic and environmental risk factors were significantly associated with diabetes incidence, after adjusting for multiple testing. These included air pollutants (particulate matter, nitrogen dioxide, nitrogen oxides, carbon monoxide; all inversely associated), as well as lead in soil, radon, outdoor light at night, overcrowding, population density and ethnicity. Disease mapping revealed spatial heterogeneity in type 1 diabetes risk. The ecological regression found an association between type 1 diabetes and the living environment domain of the Index of Multiple Deprivation (RR 0.995; 95% credible interval [CrI] 0.991, 0.998) and radon potential class (RR 1.044; 95% CrI 1.015, 1.074). CONCLUSIONS/

interpretationOur analysis identifies a range of demographic and environmental factors associated with type 1 diabetes in children in England.

Indexed as

Diabetes Mellitus, Type 1EnglandEnvironmental ExposureHumansIncidenceParticulate MatterRisk FactorsParticulate MatterChildhood diabetesDisease mappingEnvironmental exposuresEnvironment-wide association studyHospital episode statisticsRoutine health dataType 1 diabetes

Identifiers

PMID31980846
PMCPMC7145790
OpenAlexW3002152021

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.