Global burden of type 2 diabetes attributable to SARS-CoV-2 infection
5 affiliations
- 1Institute of Evidence-Based Medicine, Heping Hospital Affiliated to Changzhi Medical College
- 2Department of Clinical Laboratory, Heping Hospital Affiliated to Changzhi Medical College
- 3Department of Public Health and Preventive Medicine, Changzhi Medical College
- 4Department of Medical Statistics, School of Public Health, Zhejiang Chinese Medical University
- 5School of Public Health, Southern Medical University
Abstract
Objective: We aimed to quantify the association between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the risk of incident diabetes. We also aimed to estimate the global burden of incident type 2 diabetes (T2D) attributable to SARS-CoV-2 infection.
Methods: We conducted a systematic review and meta-analysis of cohort studies identified through PubMed, Embase, Web of Science and CENTRAL from inception to 29 January 2026. Adjusted relative risks (RRs) for incident T2D and type 1 diabetes (T1D) following SARS-CoV-2 infection were pooled using random-effects models. Population attributable fractions (PAFs) and attributable T2D cases were estimated by integrating pooled risk estimates with Global Burden of Disease (GBD) 2023 data on COVID-19 prevalence and T2D incidence.
Results: Fifteen cohort studies involving approximately 48.9 million participants were included. SARS-CoV-2 infection was associated with an increased risk of incident T2D (13 studies; pooled RR, 1.25 [95% CI, 1.16–1.34]), although substantial heterogeneity was observed and the 95% prediction interval (PI) included the null (0.94–1.66). In subgroup analysis, the association was confined to mixed-variant studies (RR, 1.29 [95% CI, 1.23–1.36]; 95% PI, 1.09–1.54), whereas studies evaluating a single variant (Delta or Omicron) showed no excess risk (RR, 1.00 [95% CI, 0.97–1.03]). The association with incident T1D did not reach conventional statistical significance (10 studies; pooled RR, 1.13 [95% CI, 0.99–1.30]). Globally, 24.53 million incident T2D cases occurred in 2023. The PAF attributable to COVID-19 of 1.12% (95% CI 0.90, 1.35), corresponding to 274,889 (95% CI 220,360, 331,698) incident T2D cases attributable to SARS-CoV-2 infection. The largest attributable burdens were observed in India, the USA, and China.
Conclusions: SARS-CoV-2 infection was associated with a modest increase in pooled T2D risk. This association was primarily observed in mixed-variant studies, for which the 95% PI excluded the null. However, the overall pooled estimated was accompanied by substantial between-study heterogeneity, and its 95% PI crossing the null, indicating uncertainty in the association across populations and settings. At the population level, this excess risk translated into an estimated 275,000 incident T2D cases attributable to COVID-19 worldwide in 2023, highlighting the need for ongoing metabolic surveillance following infection.
Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD420261307969 , identifier CRD420261307969.
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BibTeX
@article{li2026global,
title = {{Global burden of type 2 diabetes attributable to SARS-CoV-2 infection}},
author = {Jingjing Li and Guangming Liu and Jianzhou Yang and Haimiao Ma and Xiaoyan Wang and Ziying Jiang and Yuanhao Liang and Xiaofeng He},
journal = {Frontiers in Immunology},
year = {2026},
month = oct,
doi = {10.3389/fimmu.2026.1969341},
url = {https://www.frontiersin.org/articles/10.3389/fimmu.2026.1969341/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Global burden of type 2 diabetes attributable to SARS-CoV-2 infection
AU - Jingjing Li
AU - Guangming Liu
AU - Jianzhou Yang
AU - Haimiao Ma
AU - Xiaoyan Wang
AU - Ziying Jiang
AU - Yuanhao Liang
AU - Xiaofeng He
PY - 2026
DA - 2026/10/16
JO - Frontiers in Immunology
DO - 10.3389/fimmu.2026.1969341
UR - https://www.frontiersin.org/articles/10.3389/fimmu.2026.1969341/full
AB - Objective: We aimed to quantify the association between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the risk of incident diabetes. We also aimed to estimate the global burden of incident type 2 diabetes (T2D) attributable to SARS-CoV-2 infection. Methods: We conducted a systematic review and meta-analysis of cohort studies identified through PubMed, Embase, Web of Science and CENTRAL from inception to 29 January 2026. Adjusted relative risks (RRs) for incident T2D and type 1 diabetes (T1D) following SARS-CoV-2 infection were pooled using random-effects models. Population attributable fractions (PAFs) and attributable T2D cases were estimated by integrating pooled risk estimates with Global Burden of Disease (GBD) 2023 data on COVID-19 prevalence and T2D incidence. Results: Fifteen cohort studies involving approximately 48.9 million participants were included. SARS-CoV-2 infection was associated with an increased risk of incident T2D (13 studies; pooled RR, 1.25 [95% CI, 1.16–1.34]), although substantial heterogeneity was observed and the 95% prediction interval (PI) included the null (0.94–1.66). In subgroup analysis, the association was confined to mixed-variant studies (RR, 1.29 [95% CI, 1.23–1.36]; 95% PI, 1.09–1.54), whereas studies evaluating a single variant (Delta or Omicron) showed no excess risk (RR, 1.00 [95% CI, 0.97–1.03]). The association with incident T1D did not reach conventional statistical significance (10 studies; pooled RR, 1.13 [95% CI, 0.99–1.30]). Globally, 24.53 million incident T2D cases occurred in 2023. The PAF attributable to COVID-19 of 1.12% (95% CI 0.90, 1.35), corresponding to 274,889 (95% CI 220,360, 331,698) incident T2D cases attributable to SARS-CoV-2 infection. The largest attributable burdens were observed in India, the USA, and China. Conclusions: SARS-CoV-2 infection was associated with a modest increase in pooled T2D risk. This association was primarily observed in mixed-variant studies, for which the 95% PI excluded the null. However, the overall pooled estimated was accompanied by substantial between-study heterogeneity, and its 95% PI crossing the null, indicating uncertainty in the association across populations and settings. At the population level, this excess risk translated into an estimated 275,000 incident T2D cases attributable to COVID-19 worldwide in 2023, highlighting the need for ongoing metabolic surveillance following infection. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD420261307969 , identifier CRD420261307969.
SN - 1664-3224
ER -