Can SARS-CoV-2 infection cause diabetes?

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In a recent study published in the journal JAMA Network Open, researchers performed a cohort study between January 1, 2020, and December 31, 2021, in British Columbia, Canada, to assess the association between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and incident diabetes.

Study: Association of COVID-19 Infection With Incident Diabetes. Image Credit: Design_Cells / ShutterstockStudy: Association of COVID-19 Infection With Incident Diabetes. Image Credit: Design_Cells / Shutterstock


During its acute phase, SARS-CoV-2 infection mainly affects the respiratory system. In the long term, it leads to various acute and chronic sequelae in which other organ systems might get involved. Studies suggest that SARS-CoV-2) infection might be associated with worsening symptoms in individuals with diabetes.

However, it is unknown whether coronavirus disease 2019 (COVID-19) is associated with transient hyperglycemia during active infection or whether these metabolic alterations persist over time, increasing the risk of incident diabetes among infected individuals. Most published studies evaluating the association between SARS-CoV-2 infection and incident diabetes used relatively small samples and fetched limited outcome ascertainment.

About the study

In the present study, researchers used population-based registries and administrative data sets of the British Columbia COVID-19 Cohort, a public health surveillance system, to evaluate the potential association between COVID-19, its severity, and diabetes incidence. This system encompasses data on the outpatient department (OPD) and emergency department (ED) visits, hospitalizations, prescription drugs, chronic health conditions, and other vital statistics of the British Columbia population.

In addition, the team computed the population-attributable fraction (PAF) to estimate the population-level burden of diabetes due to COVID-19 while controlling for potential confounders.

All eligible adult (aged ≥18 years) participants tested COVID-19-positive during the study duration on a real-time reverse transcription-polymerase chain reaction (RT-PCR) assay. The team created a matched control cohort with people who tested COVID-19-negative based on sociodemographic variables, such as gender, age (±3 years), and RT-PCR sample collection date (±7 days) at a 1:4 ratio. Other covariates measured in this analysis were preexisting chronic conditions and vaccination status.

The primary exposure and outcome of interest were RT-PCR–confirmed COVID-19 and incident diabetes, identified nearly a month after the index date, i.e., the RT-PCR sample collection date, to the earliest identification of any of the study outcome, patient death, or end of the study.

The researchers calculated events of incident diabetes and person-days for each study group, which they used to compute diabetes incidence rates, i.e., number of events/100,000 person-years. They used the Kaplan-Meier method to draw cumulative incidence curves and Cox proportional hazards regression models to compare diabetes risk in all participants due to their exposure status, accounting for matched data.


The final analytic sample of this study comprised 629,935 individuals with a median age of 32 years. Of these, 51.2% were females, and the rest were males. The number of individuals exposed to SARS-CoV-2 was 125,987, while the remaining 503,948 individuals remained unexposed.

The team followed up with all the study participants for an average of 257 days. They recorded incident diabetes events among 2472 individuals, including 608 (0.5%) exposed individuals and 1,864 (0.4%) unexposed individuals. Among individuals with incident diabetes, 1,393 were females, and 1,079 were males.

In the study cohort, the incidence diabetes rate per 100,000 person-years was markedly higher in the exposed vs. unexposed group (672.2 vs. 508.7 incidents; 95% CI), with an overall adjusted hazard ratio (HR) of 1.17. The authors noted an association between COVID-19 and an elevated risk of incident diabetes. At the population level, it contributed to a 3% to 5% excess burden of diabetes, which might be enough to overburden healthcare systems.

Further, the authors noted a correlation between SARS-CoV-2 exposure and non–insulin-dependent diabetes only in sensitivity analysis classifying diabetes as insulin-dependent and insulin-independent, with HR=1.17. Furthermore, the vaccine status-stratified analysis suggested a correlation between SARS-CoV-2 exposure and incident diabetes in the unvaccinated cohort but not in partially and fully vaccinated cohorts.


This large, population-based cohort study demonstrated that SARS-CoV-2 infection was associated with a higher risk of incident diabetes overall. Male sex and disease severity further heightened the risk of diabetes in all participants, irrespective of gender. Thus, it highlighted that public health agencies and clinicians must remain aware of the potential long-term COVID-19 sequelae and continuously monitor SARS-CoV-2-infected individuals for new-onset diabetes to provide them with the best and most timely diagnosis and treatment.

Journal reference:
Neha Mathur

Written by

Neha Mathur

Neha is a digital marketing professional based in Gurugram, India. She has a Master’s degree from the University of Rajasthan with a specialization in Biotechnology in 2008. She has experience in pre-clinical research as part of her research project in The Department of Toxicology at the prestigious Central Drug Research Institute (CDRI), Lucknow, India. She also holds a certification in C++ programming.


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