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Can SARS-CoV-2 infection cause diabetes?

Can SARS-CoV-2 infection cause diabetes?

In a recent study published within the journal JAMA Network Open, researchers performed a cohort study between January 1, 2020, and December 31, 2021, in British Columbia, Canada, to evaluate 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 / Shutterstock


During its acute phase, SARS-CoV-2 infection mainly affects the respiratory system. In the long run, it leads to numerous acute and chronic sequelae through which other organ systems might become involved. Studies suggest that SARS-CoV-2) infection is perhaps related to worsening symptoms in individuals with diabetes.

Nevertheless, it’s unknown whether coronavirus disease 2019 (COVID-19) is related to transient hyperglycemia during energetic infection or whether these metabolic alterations persist over time, increasing the danger of incident diabetes amongst infected individuals. Most published studies evaluating the association between SARS-CoV-2 infection and incident diabetes used relatively small samples and fetched limited consequence ascertainment.

In regards to the study

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

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

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

The first exposure and consequence 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 consequence, patient death, or end of the study.

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


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

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

Within the study cohort, the incidence diabetes rate per 100,000 person-years was markedly higher within 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. On the population level, it contributed to a 3% to five% excess burden of diabetes, which is perhaps enough to overburden healthcare systems.

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


This massive, population-based cohort study demonstrated that SARS-CoV-2 infection was related to a better risk of incident diabetes overall. Male sex and disease severity further heightened the danger of diabetes in all participants, no matter gender. Thus, it highlighted that public health agencies and clinicians must remain aware of the potential long-term COVID-19 sequelae and constantly monitor SARS-CoV-2-infected individuals for new-onset diabetes to offer them with the perfect and most timely diagnosis and treatment.


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