Evidence map›Paper›PMID 42115979›Full record

ArticleBMC infectious diseases2026

Incident diabetes within the first two years after SARS-CoV-2 infection: a population-based retrospective cohort study of the Agency for Health Protection of Milan, Italy.

Cristina Mazzali, Pietro Magnoni, Maria Grazia Valsecchi, Daria Vigani, Claudio Lucifora, Antonio Giampiero Russo, PASCNET study group

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Article in BMC infectious diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Cristina MazzaliEpidemiology Unit, Agency for Health Protection of Milan, Via Conca del Naviglio 45, 20123, Milan, MI, Italy.
Pietro MagnoniEpidemiology Unit, Agency for Health Protection of Milan, Via Conca del Naviglio 45, 20123, Milan, MI, Italy. pmagnoni@ats-milano.it.ORCID http://orcid.org/0000-0002-6431-6261
Maria Grazia ValsecchiSchool of Medicine and Surgery and Bicocca Bioinformatics Biostatistics and Bioimaging Centre (B4), University of Milano-Bicocca, Milan, Italy.
Daria ViganiDepartment of Economics and Finance, Catholic University of the Sacred Heart, Milan, Italy.
Claudio LuciforaDepartment of Economics and Finance, Catholic University of the Sacred Heart, Milan, Italy.
Antonio Giampiero RussoEpidemiology Unit, Agency for Health Protection of Milan, Via Conca del Naviglio 45, 20123, Milan, MI, Italy.
PASCNET study group

Funding

Fondazione Cariplo 2021-4388
6 · The paper itself

Abstract

backgroundPostacute sequelae of SARS-CoV-2 infection (PASC), including persistent symptoms and acute and chronic diagnoses, have become a major research focus. Diabetes mellitus, beyond its established link to COVID-19 severity, is increasingly recognized as a potential long-term outcome. This study investigated the association between SARS-CoV-2 infection and incident diabetes using population-level health administrative data (HAD) from the Agency for Health Protection of Milan, where the epicenter of the pandemic in Italy took place.

methodsThis retrospective cohort study included adult residents without a history of diabetes who underwent SARS-CoV-2 testing between 1 March and 31 December 2020. Test-positive individuals were matched 1:1 to test-negative individuals based on sex, age, and testing week. The cohort was followed through 31 December 2021. The incidence of diabetes, identified using an HAD-based case-detection algorithm, was compared between the two groups, and in stratified analyses by sex and age, using weighted Cox models adjusted for chronic comorbidities, area-level deprivation, influenza and pneumococcal vaccinations. Weights were calculated via the inverse probability weighting approach. Effect estimates are presented as hazard ratios (HRs).

resultsOur final cohort included 248,176 residents (124,026 test-negative, 124,150 test-positive). Over a median follow-up time of 415 days, 739 positive (0.60%) and 657 negative (0.53%) individuals were newly identified with diabetes. The incidence among positive individuals was 572.82 per 100,000 person-years (CI 531.52-614.12), and that among negative individuals was 509.50 per 100,000 person-years (CI 470.54-548.46). The overall HR was 1.13 (CI 1.02-1.25). In stratified analyses, this effect was prominent in women aged 41-60 years (HR 1.31; CI 1.02-1.68).

conclusionsThis study provides population-based evidence supporting an association between SARS-CoV-2 infection and newly detected diabetes. These findings contribute to understanding the long-term health impact of COVID-19 and may inform public health strategies for PASC prevention and management.

Indexed as

COVID-19Diabetes MellitusAdultAgedFemaleHumansIncidenceItalyMaleMiddle AgedPost-Acute COVID-19 SyndromeRetrospective StudiesSARS-CoV-2Young AdultDiabetesEpidemiologyLong CovidPASCPopulation cohort studySARS-CoV-2

Identifiers

PMID42115979
PMCPMC13335262

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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 OpenQuestion graph.