Evidence map›Paper›PMID 42108424›Full record

ArticleDiabetes, obesity & metabolism2026

Variations in the Risk of New-Onset Diabetes Following COVID-19 Infection Across Body Mass Index, Deprivation, Ethnicity and Geographic Regions: Population-Based Cohort Study in 42 Million People in England.

Sharmin Shabnam, Cameron Razieh, John Nolan, Nazrul Islam, Genevieve Cezard, Yogini V Chudasama, Clare L Gillies, Amitava Banerjee, Angela Wood, Kamlesh Khunti and 2 more

Abstract read
In one paragraph

Article in Diabetes, obesity & metabolism, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

12 authors.

Sharmin ShabnamLeicester Real World Evidence Unit, Leicester Diabetes Centre, Leicester, UK.ORCID https://orcid.org/0000-0002-2519-1240
Cameron RaziehLeicester Real World Evidence Unit, Leicester Diabetes Centre, Leicester, UK.
John NolanBritish Heart Foundation Data Science Centre, Health Data Research UK, London, UK.
Nazrul IslamPrimary Care Research Centre, University of Southampton, Southampton, UK.
Genevieve CezardDepartment of Public Health and Primary Care, University of Cambridge, Cambridge, UK.ORCID https://orcid.org/0000-0002-3011-7416
Yogini V ChudasamaLeicester Real World Evidence Unit, Leicester Diabetes Centre, Leicester, UK.ORCID https://orcid.org/0000-0002-6777-0064
Clare L GilliesLeicester Real World Evidence Unit, Leicester Diabetes Centre, Leicester, UK.
Amitava BanerjeeInstitute of Health Informatics, University College London, London, UK.
Angela WoodBritish Heart Foundation Data Science Centre, Health Data Research UK, London, UK.
Kamlesh KhuntiLeicester Real World Evidence Unit, Leicester Diabetes Centre, Leicester, UK.ORCID https://orcid.org/0000-0003-2343-7099
Francesco ZaccardiLeicester Real World Evidence Unit, Leicester Diabetes Centre, Leicester, UK.
CVD‐COVID‐UK/COVID‐IMPACT Consortium

Funding

National Institute for Health Research (NIHR) Applied Research Collaboration East Midlands (ARC EM)
6 · The paper itself

Abstract

aimsEvidence suggests that COVID-19 may be associated with an increased risk of diabetes. We aimed to examine this association by investigating the role of socioeconomic and metabolic factors on the risk of new-onset type 2 (T2D) and type 1 (T1D) diabetes after COVID-19 diagnosis. MATERIALS AND

methodsWe conducted a retrospective, population-based cohort study using linked electronic health records from NHS England's Secure Data Environment for England via the CVD-COVID-UK/COVID-IMPACT consortium. Adults (≥ 18 years), alive, registered with a general practice within 1 January 2020 and 28 May 2024 were included. Exposed individuals with confirmed COVID-19 diagnosis and no prior diabetes were matched to up to three unexposed individuals without COVID-19 and diabetes on age, sex, region and deprivation. Flexible parametric survival models were used to estimate associations between COVID-19 and incident diabetes by sex and across age, BMI, deprivation, ethnicity, and region.

resultsOf 50 156 810 eligible individuals, 12 859 545 with a COVID-19 diagnosis and no prior diabetes were matched to 29 221 285 without COVID-19; the median follow-up was 2.4 years. Although BMI was strongly and positively associated with the risk of T2D, differences between exposed and unexposed individuals were little to none, with the excess risk concentrated in the first year (e.g., in 70-year-old men with BMI 35 kg/m

conclusionsIn this cohort, COVID-19 was associated with a modest, short-term increase in T2D risk and showed no meaningful association with T1D. Established metabolic, demographic and socioeconomic factors-including age, BMI, deprivation and ethnicity-were more strongly associated with T2D incidence than COVID-19 exposure.

Indexed as

COVID-19Diabetes Mellitus, Type 1Diabetes Mellitus, Type 2AdultAgedBody Mass IndexCohort StudiesEnglandEthnic and Racial MinoritiesFemaleHumansIncidenceMaleMiddle AgedRetrospective StudiesRisk FactorsBMIcohort studyCOVID‐19deprivationdiabeteselectronic health recordsEnglandethnicityregion

Identifiers

PMID42108424
PMCPMC13341393

What Socratic holds

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Registered trials

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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 Socratic graph.