Incidence of Diabetes in Children and Adolescents During the COVID-19 Pandemic: A Systematic Review and Meta-Analysis
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This systematic review and meta-analysis compares incidence rates of diabetes and diabetic ketoacidosis among children and adolescents before and during the COVID-19 pandemic.
Key Points
Question
Was there a change in the incidence of diabetes in children and adolescents after the onset of the COVID-19 pandemic?
Findings
In this systematic review and meta-analysis of 42 studies including 102 984 youths, the incidence of type 1 diabetes was higher during the COVID-19 pandemic compared with before the pandemic.
Meaning
The findings suggest the need to elucidate possible underlying mechanisms to explain temporal changes and increased resources and support for the growing number of children and adolescents with diabetes.
Abstract
Importance
There are reports of increasing incidence of pediatric diabetes since the onset of the COVID-19 pandemic. Given the limitations of individual studies that examine this association, it is important to synthesize estimates of changes in incidence rates.
Objective
To compare the incidence rates of pediatric diabetes during and before the COVID-19 pandemic.
Data Sources
In this systematic review and meta-analysis, electronic databases, including Medline, Embase, the Cochrane database, Scopus, and Web of Science, and the gray literature were searched between January 1, 2020, and March 28, 2023, using subject headings and text word terms related to COVID-19, diabetes, and diabetic ketoacidosis (DKA).
Study Selection
Studies were independently assessed by 2 reviewers and included if they reported differences in incident diabetes cases during vs before the pandemic in youths younger than 19 years, had a minimum observation period of 12 months during and 12 months before the pandemic, and were published in English.
Data Extraction and Synthesis
From records that underwent full-text review, 2 reviewers independently abstracted data and assessed the risk of bias. The Meta-analysis of Observational Studies in Epidemiology (
) reporting guideline was followed. Eligible studies were included in the meta-analysis and analyzed with a common and random-effects analysis. Studies not included in the meta-analysis were summarized descriptively.
Main Outcomes and Measures
The primary outcome was change in the incidence rate of pediatric diabetes during vs before the COVID-19 pandemic. The secondary outcome was change in the incidence rate of DKA among youths with new-onset diabetes during the pandemic.
Results
Forty-two studies including 102 984 incident diabetes cases were included in the systematic review. The meta-analysis of type 1 diabetes incidence rates included 17 studies of 38 149 youths and showed a higher incidence rate during the first year of the pandemic compared with the prepandemic period (incidence rate ratio [IRR], 1.14; 95% CI, 1.08-1.21). There was an increased incidence of diabetes during months 13 to 24 of the pandemic compared with the prepandemic period (IRR, 1.27; 95% CI, 1.18-1.37). Ten studies (23.8%) reported incident type 2 diabetes cases in both periods. These studies did not report incidence rates, so results were not pooled. Fifteen studies (35.7%) reported DKA incidence and found a higher rate during the pandemic compared with before the pandemic (IRR, 1.26; 95% CI, 1.17-1.36).
Conclusions and Relevance
This study found that incidence rates of type 1 diabetes and DKA at diabetes onset in children and adolescents were higher after the start of the COVID-19 pandemic than before the pandemic. Increased resources and support may be needed for the growing number of children and adolescents with diabetes. Future studies are needed to assess whether this trend persists and may help elucidate possible underlying mechanisms to explain temporal changes.
Introduction
Diabetes is a common chronic disease in children.
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Several studies have reported an increased incidence of types 1 and 2 diabetes in children since the COVID-19 pandemic.
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Some studies reported an association between SARS-CoV-2 infection and new-onset diabetes.
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However, given the challenges of ascertaining a SARS-CoV-2 infection, there are concerns about the validity of these studies. Furthermore, there is no clear mechanism by which COVID-19 could directly or indirectly lead to new-onset type 1 or 2 diabetes.
The pathophysiology of types 1 and 2 diabetes are distinct, as are the theoretical pathways by which COVID-19 might cause them
; therefore, it is important to determine whether there has been an increased incidence rate of 1 or both types of diabetes.
The examination of diabetes incidence rates during the pandemic is nuanced because there was a preexisting increase of 3% to 4% in the annual incidence rate of type 1 diabetes reported in European countries,
seasonality to diabetes incidence,
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and variability in the reported incidence rates between early and later months during the pandemic.
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It is important to establish whether the reported increased incidence rates of new-onset diabetes in children are overall higher and sustained or a result of a catch-up effect from a lower incidence rate early in the pandemic likely due to delays in diagnoses.
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A recent review and meta-analysis
that pooled results of 8 studies reported that the incidence rate of type 1 diabetes was higher during the pandemic in 2020 (32.39 per 100 000 children) compared with the same period prior to the pandemic in 2019 (19.73 per 100 000 children). An important limitation of that meta-analysis is that it only included studies conducted during the first wave of the pandemic. There may have been a lower incidence rate early in the pandemic and a higher incidence rate later in the pandemic due, in part, to the absence of an expected seasonal decline in summer months.
Importantly, the meta-analysis
only examined the incidence rate of type 1 diabetes in children. It is plausible that the increase in sedentary behavior observed during the COVID-19 pandemic due to school closures and lockdown measures was associated with the increased prevalence of childhood obesity, a known risk factor for type 2 diabetes.
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In addition to reports of an increased incidence rate of diabetes, there have also been consistent reports of an increased risk of diabetic ketoacidosis (DKA), a preventable and life-threatening condition, at diabetes onset in children during the pandemic.
,
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It is critical to know whether there was a sustained change in the incidence rates of both type 1 and type 2 diabetes in children because there are important implications for health resource planning for pediatric diabetes care, COVID-19–related and future pandemic-related public health measures, and immunization strategies. The primary objective of this systematic review and meta-analysis was to investigate whether there was a change in the incidence rate of types 1 and 2 diabetes in children and adolescents during the COVID-19 pandemic compared with before the pandemic. The secondary objective was to assess whether there was a change in the incidence rate of DKA among youths with new-onset diabetes during the COVID-19 pandemic.
Methods
We prospectively registered this systematic review and meta-analysis on the
database. The study followed the Meta-analysis of Observational Studies in Epidemiology (
) reporting guideline.
Data Sources and Search Strategy
We searched Medline (all segments), Embase, the Cochrane database, Scopus, and Web of Science for studies published from January 1, 2020, to March 28, 2023, in English. Our search strategy included subject headings and text word terms for COVID-19 and (diabetes type 1 or 2 or diabetic ketoacidosis) and incidence (eTable 1 in
). We also conducted a gray literature search to identify studies published on government websites by searching for a combination of COVID and diabetes and statistical terms. We hand-searched the reference lists of all included studies and relevant systematic reviews.
Eligibility Criteria
Studies were included if they (1) reported the number of incident cases of type 1 or 2 diabetes during the COVID-19 pandemic and before the pandemic in children and adolescents younger than 19 years, (2) had a minimum study period of 12 months prior to and during the COVID-19 pandemic, and (3) were published in English. Two reviewers (D.D., J.E.) used Covidence software
to determine study eligibility. Conflicts were resolved by consensus or, if needed, in discussion with a third reviewer (R.S.). Interrater agreement at the screening and full-text stages was 95% and 90%, respectively.
Data Extraction
We extracted the number of incident types 1 and 2 diabetes cases, study population size, and incidence rates of types 1 and 2 diabetes and DKA at diabetes diagnosis in the prepandemic and pandemic periods. The start of the pandemic period was defined according to the definition in each study. Two independent reviewers (D.D., J.E) extracted the data. Conflicts were resolved by consensus. Intercoder agreement was greater than 95%.
Risk of Bias
We used the Risk of Bias in Non-randomized Studies of Exposure
tool to assess the risk of bias in 7 domains (eTable 2 in
). Two independent reviewers (D.D., J.E.) assessed the risk of bias for each of the included studies; conflicts were resolved by consensus or by a third reviewer (R.S).
Statistical Analysis
We included studies in the meta-analysis if they reported the number of incident diabetes cases and the size of the study population for a minimum 12-month prepandemic period and a 12-month pandemic period. If those data were not reported, we contacted the corresponding author, requesting for them to share the data. If the study did not report the denominator (ie, study population) and we were unable to obtain it from the corresponding author, we included the study in a descriptive summary but excluded it from the meta-analysis because studies with missing denominators are likely to be of lower quality and, therefore, are not missing at random.
Also, we wanted to focus the meta-analysis on the highest-quality studies. Studies with both pediatric and adult participants but no subgroup analysis for individuals younger than 19 years were included in the descriptive summary.
The number of incident cases and the size of the study population during the 12 months preceding the start of the pandemic period and the first 12 months following the start of the pandemic period were used to calculate the incidence rate ratio (IRR), the pooled IRR, and the corresponding 95% CIs. We conducted a meta-analysis of IRRs using common and random-effects approaches. Statistical heterogeneity was measured using the I2 statistic, and we assessed the statistical significance of between-study variation using a 2-sided P value of <.05.
Although some studies reported diabetes incidence for longer than 12 months in the prepandemic period, we included only data from 12 months preceding the start of the pandemic period in the meta-analysis because prepandemic diabetes incidence is known to have followed a seasonal pattern.
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Studies that had pandemic periods longer than 12 months are described in the narrative summary. Because seasonality changed during the pandemic,
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we conducted a post hoc additional analysis including only studies that reported more than 12 months of pandemic data, in which we compared incidence in the 12 months before the pandemic vs the first 12 months of the pandemic vs the second 12 months of the pandemic or the end of follow-up, whichever came first. We used the meta package in R, version 4.2.2 (R Project for Statistical Computing) for data analysis.
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Results
We identified 10 757 records, of which 4353 were duplicates (
). After the abstract review, we retrieved 81 full-text articles to determine eligibility. Forty-two records met the full inclusion criteria.
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The manual search of the included studies’ reference lists did not yield additional studies.
Figure 1. Flow Diagram of Study Selection.
Study Characteristics
Among the 42 included studies, there were 102 984 incident diabetes cases across both the prepandemic and the pandemic periods (
). Twenty-four studies (57.1%) reported DKA incidence at diagnosis.
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Incident cases of type 1 and type 2 diabetes were reported in 36 studies (85.7%)
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and 9 studies (21.4%),
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respectively. Two studies (4.8%) did not distinguish between diabetes types.
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Thirty-two studies (76.2%) included children only,
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while the rest (10 [23.8%]) included both children and adults.
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Twenty-one studies (50.0%) were from Europe,
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12 (28.6%) from North America,
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7 (16.7%) from Asia,
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and 1 (2.4%) from Australia
; 1 study (2.4%)
included data from multiple countries across different continents. Nine studies (21.4%) reported either the race or ethnicity of the study population,
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and 1 study reported socioeconomic status.
All included studies were assessed to have an overall risk of bias rating of “some” (eTable 3 in
).
Table 1. Study Characteristics.
SourceCountryStudy type and settingType of diabetesPrepandemic periodPandemic periodAge, mean, yFemale, %Duration, mo (period)Sample sizeAge, mean, yFemale, %Duration, mo (period)Sample sizeAlexandre et al,
2021PortugalRetrospective cohort, single site110.05512 (Apr 2019 to Mar 2020)NR12.337.012 (Apr 2020 to Mar 2021)NRBoboc et al,
2021RomaniaRetrospective cohort, single site17.045.524 (Mar 2018 to Feb 2020)973 7507.249.012 (Mar 2020 to Feb 2021)973 750Dilek et al,
2021TurkeyRetrospective cohort, single site110.554.312 (Mar 2019 to Mar 2020)NR10.052.712 (Mar 2020 to Mar 2021)NRKostopoulou et al,
2021GreeceProspective during pandemic with retrospective prepandemic, multisite19.429.412 (Mar 2019 to Feb 2020)NR8.0 57.112 (Mar 2020 to Feb 2021)NRMameli et al,
2021ItalyRetrospective cohort, population based12017, 8.7; 2018, 8.7; 2019, 8.92017, 45.0; 2018, 46.1; 2019, 49.436 (Jan 2017 to Dec 2019)NR8.543.012 (Jan to 2020)Marks et al,
2021USRetrospective cohort, single site1 and 2Type 1: 1 y PP, 10.0; 2 y PP, 10.0; T2D: 1 y PP, 14.1; 2 y PP, 13.81 y PP, 48.1; 2 y PP, 46.7 for both types24 (Mar 2018 to Mar 2020)NRT1D, 10.0; T2D, 14.544.5 (Types 1 and 2)12 (Mar 2020 to Mar 2021)Mohamed Haniffa et al,
2021UKRetrospective cross-sectional, single site1PP, 9.8NR12 (Apr 2019 to Mar 2020)NR8.5NR12 (Apr 2020 to Mar 2021)NRMoon et al,
2021EnglandRetrospective cross -sectional, single site1NRNR48 (Mar 2016 to Mar 2020)NRNRNR12 (Mar 2020 to Mar 2021)NRVlad et al,
2021RomaniaRetrospective cohort, population based1All pediatric ageNR60 (Jan 2015 to Dec 2019)3 057 024-3 318 667All pediatric ageNR12 (Jan to Dec 2020)3 214 123-3 224 829Al-Abdulrazzaq et al,
2022KuwaitRetrospective cross-sectional, population based18.050.512 (Feb 2019 to Feb 2020)805 8518.273.412 (Feb 2020 to Feb 2021)805 970Al-Qahtani et al,
2022
Saudi ArabiaRetrospective cohort, single site1NR55.0 (All periods)36 (Jan 2017 to Dec 2019)NRNR55.0 (All periods)24 (Jan 2020 to Dec 2021)NRAlassaf et al,
2022JordanRetrospective cross-sectional, single site1Pediatric age51.912 (Mar 2019 to Mar 2020)NRPediatric age55.412 (Mar 2020 to Mar 2021)NRAnsar et al,
2022USRetrospective cohort, single site1 and 2Pediatric age; most 6-16NR24 (Mar 2018 to Feb 2020)NRPediatric age, most 6-16NR22 (Mar 2020 to Dec 2021)NRAustralian Institute of Health and Welfare,
2022AustraliaRetrospective database, population based1 and 2Age for T1D, 0-19, and for T2D, 10-39
NR for T1D60 (Jan 2015 to Dec 2019)T1D, 1 469 856-4 742 627; T2D, 27 210-28 517Age for T1D, 0-19, and for T2D, 10-39
NR12 (Jan to Dec 2020)T1D, 6 266 670; T2D, 26 881Caetano et al,
2022
PortugalRetrospective cohort, single site110.747.736 (Mar 2017 to Mar 2020)NR9.046.912 (Mar 2020 to Mar 2021)NRCinek et al,
2022CzechiaRetrospective cross-sectional, population based1NRNR60 (Jan 2015 to Dec 2019)1 623 716-1 710 202NRNR21 (Apr 2020 to Dec 2021)1 718 145-1 719 741Citron et al,
2022USRetrospective cross-sectional, single site1 and 2NRNR12 (Jan to Dec 2019)NRNRNR22 (Jan 2020 to Oct 2021)NRDeLacey et al,
2022USRetrospective cross-sectional, single site214.154.260; (May 2015 to Apr 2020)NR14.145.912 (May 2020 to Apr 2021)NRDonbaloğlu et al,
2022TurkeyRetrospective cohort, single site1NRNR24 (Apr 2018 to Apr 2020)NR9.471.012 (Apr 2020 to Apr 2021)NRKamrath et al,
2022
GermanyRetrospective cohort, population based19.844.260 (Jan 2015 to Dec 2019)NR9.745.018 (Jan 2020 to Jun 2021)NRGottesman et al,
2022USRetrospective cross-sectional, single site19.7NR60 (Mar 2015 to Mar 2020)1 405 967-1 410 7879.656.712 (Mar 2020 to Mar 2021)1 406 430Guo et al,
2022USRetrospective cohort, population based1 and 2T1D, 11.0; T2D, 12.5T1D, 48.7; T2D, 60.336 (Apr 2017 to Mar 2020)NRT1D, 11.0; T2D, 12.5T1D, 48.7; T2D, 60.3 12 (Apr 2020 to Mar 2021)NRKaya et al,
2022TurkeyRetrospective cohort, single site18.146.836 (Feb 2017 to Jan 2020)NR8.545.512 (Feb 2020 to Jan 2021)NRLeiva-Gea et al,
2022SpainRetrospective cross-sectional, multisite1NRNR60 (Jan 2015 to Dec 2019)NRNRNR15 (Jan 2020 to Mar 2021)NRMagge et al,
2022USRetrospective cross-sectional, multisite214.455.024 (Mar 2018 to Feb 2020)NR14.445.012 (Mar 2020 to Feb 2021)NRMessaaoui et al,
2022BelgiumRetrospective cohort, population based1Pediatric age3822 (Mar 2018 to Dec 2019)NRPediatric age5622 (Mar 2020 to Dec 2021)NRModarelli et al,
2022USRetrospective cohort, single site1 and 2T1D: 2 y PP, 9.9; 1 y PP, 10.4; T2D: 2 y PP, 9.9; 1 y PP, 9.9 yT1D: 2 y PP, 55.0; 1 y PP, 55.0; T2D: 2 y PP, 59.0; 1 y PP, 56.0 24 (Apr 2018 to Mar 2020)NRT1D, 10.5; T2D, 9.9T1D, 35.0; T2D, 53.012 (Apr 2020 to Mar 2021)NRPassanisi et al,
2022ItalyRetrospective cross-section, population based1Pediatric age only55.2 (All periods)12 (Jan to Dec 2019)252 792Pediatric age in all periods55.2 (All periods)24 (Jan 2020 to Dec 2021)245 602-247 723Pietrzak et al,
2022PolandRetrospective cross-sectional, multisite19.546.7 (All periods)12 (Mar 2019 to Mar 2020)6 454 7569.5 (All periods)46.7 (All periods)12 (Mar 2020 to Mar 2021)6 451 737Raicevic et al,
2022MontenegroRetrospective cohort, population based18.445.5 (All periods)48 (Jan 2016 to Dec 2019)111 475-113 3028.4 (All periods)45.5 (All periods)12 (Jan 2020 to Dec 2020)111 167Reschke et al,
2022GlobalRetrospective cohort, multisite11 y PP, 10.8; 2 y PP, 11.31 y PP, 46.2; 2 y PP, 47.624 (Jan 2018 to Dec 2019)NRYear 1, 10.6; year 2, 10.1Year 1, 47.2; year 2, 44.824 (Jan 2020 to Dec 2021)NRSchiaffini et al,
2022ItalyRetrospective cross-sectional, single site1NRNR36 (Jan 2017 to Dec 2019)NRNRNR24 (Jan 2020 to Dec 2021)NRSchmitt et al,
2022USRetrospective cross-sectional, single site213.359.8 (All periods)36 (Apr 2017 to Mar 2020)NR13.3 (All periods)59.8 (All periods)12 (Apr 2020 to Mar 2021)NRShulman et al,
2022
CanadaRetrospective cross-sectional, population based1 and 29.248.7 (All periods)36 (Jan 2017 to Dec 2019)2 913 386-2 934 3639.2 (All periods)48.7 (All periods)19 (Mar 2020 to Sep 2021)2 700 178van den Boom et al,
2022GermanyRetrospective cohort, population based1All pediatric agesNR48 (Jan 2016 to Dec 2019)15 221 437-15 330 502All pediatric ageNR24 (Jan 2020 to Dec 2021)15 334 574-15 433 915Vorgučin et al,
2022
SerbiaRetrospective cohort, multisite1Pediatric age only46.8 (All periods)36 (Jan 2017 to Dec 2019)NRPediatric age across all periods46.8 (All periods)24 (Jan 2020 to Dec 2021)NRWolf et al,
2022USRetrospective cohort, multisite110.648.712; (Jan to Dec 2019)NR10.246.312 (Jan to Dec 2020)NRBaechle et al,
2023GermanyRetrospective cohort, population based19.844.260 (Jan 2015 to Dec 2019)NR9.745.018 (Jan 2020 to Jun 2021)NRGesuita et al,
2023ItalyRetrospective cohort, population based1All pediatric ageNR372 (Jan 2015 to Dec 2019)718 593-762 431All pediatric ageNR24 (Jan 2020 to Dec 2021)692 884-703 704Giorda et al,
2023ItalyRetrospective cohort, multisite114.639.936 (Jan 2017 to Dec 2019)18 049-18 68514.6 39.924 (Jan 2020 to Dec 2021)19 031-19 309Matsuda et al,
2023JapanRetrospective cohort, population based1All pediatric ages48.9252; (Jan 1999 to Dec 2019)136 123All pediatric age48.924 (Jan 2020 to Dec 2021)136 123Sasidharan Pillai et al,
2023USRetrospective cohort, single site214.853.636 (Mar 2017 to Feb 2020)NR14.156.822 (Mar 2020 to Dec 2021)NRAbbreviations: NR, not reported; PP, prepandemic; T1D, type 1 diabetes; T2D, type 2 diabetes.
a
The denominator to calculate the incidence rate was the number of children presenting to the emergency department in each period.
b
The data for T2D were only included in the systematic review and were not meta-analyzed due to the inclusion of pediatric and adult persons.
c
This study contains duplicate data from a previous 2021 article published by the same authors. Only the more recent 2022 article was included in this systematic review.
d
This study was included in the systematic review but not the meta-analysis, as it contains partial duplicate data from the study by Baechle et al.
e
Approximately 95% of all diabetes cases were T1D in this population.
f
Census data from 2011 were used to identify the at-risk pediatric population during both the prepandemic and the pandemic periods.
Type 1 Diabetes Incidence Rate and Meta-Analysis
In a random-effects meta-analysis of pooled data from 17 studies (40.5%) including 38 149 children and adolescents with newly diagnosed type 1 diabetes, there was a higher incidence rate of type 1 diabetes during the first year of the pandemic period compared with the prepandemic period (IRR, 1.14; 95% CI, 1.08-1.21) (
A).
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We excluded 2 studies
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from the meta-analysis because they contained overlapping data with more recent studies included in the meta-analysis. The data used to calculate the IRRs are available in
. The unadjusted pooled IRR comparing the first year of the pandemic with the prepandemic period was 1.13 (95% CI, 1.11-1.16). Between-study heterogeneity was moderate (I2 = 66%).
In our post hoc additional analysis, among studies that reported more than 12 months after pandemic onset, there was an increased incidence of diabetes during months 13 to 24 of the pandemic compared with the prepandemic period (IRR, 1.27; 95% CI, 1.18-1.37) (
B).
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The results of the remaining 20 studies, which reported the number of incident type 1 diabetes cases but were not included in the meta-analysis because they did not report the size of the study population, are summarized in
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Of these, 15 (75.0%) reported an increase in the number of incident cases of type 1 diabetes during the first 12 months of the pandemic compared with during the 12 months before the pandemic.
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Figure 2. Forest Plots of Incidence Rate Ratios (IRRs).
Squares indicate IRRs, with horizontal lines indicating 95% CIs and the size of the squares representing weight; diamonds indicate pooled estimates, with outer points of the diamonds indicating 95% CIs. DKA indicates diabetic ketoacidosis; NA, not applicable; T1D, type 1 diabetes.
Table 2. Incident Cases of Pediatric Diabetes and DKA and IRRs for Studies Included in the Meta-Analyses.
Source1 y PrepandemicFirst-year postpandemic startSecond-year postpandemic startIncident diabetes cases, No.PopulationIncidence rate, per 100 000 individualsIncident diabetes cases, No.PopulationIncidence rate, per 100 000 individualsIRR vs prepandemicMonths, No.Incident diabetes cases, No.PopulationIncidence rate, per 100 000 individualsIRR vs prepandemicDiabetes incidence meta-analysisBoboc et al,
2021116973 75011.91147973 75015.101.27NRNRNRNRNRVlad et al,
20213673 231 43511.364333 224 82913.431.18124803 214 12314.931.31Al-Abdulrazzaq et al,
2022303805 85137.60324805 97040.201.07NRNRNRNRNRAustralian Institute of Health and Welfare,
202215106 280 83524.0414826 266 67023.650.98NRNRNRNRNRCinek et al,
20224091 710 20223.924681 719 74127.211.14124881 718 14528.401.19Gottesman et al,
20221191 406 3538.461871 406 43013.301.57NRNRNRNRNRGuo et al,
202212834 953 66825.9015414 572 70033.701.30NRNRNRNRNRPassanisi et al,
202243252 79217.0153247 72321.391.261258245 60223.621.39Pietrzak et al,
202213916 454 75621.5516716 451 73725.901.20NRNRNRNRNRRaicevic et al,
202222111 47519.7424111 16721.591.09NRNRNRNRNRShulman et al,
20228882 913 38630.488742 700 17832.371.0676962 700 17832.221.06van den Boom et al,
2022364615 330 50223.78404615 334 57426.381.1112415315 433 91526.911.13Vorgučin et al,
202240387 30210.3332387 3028.260.801267387 30217.301.67Baechle et al,
2023290314 160 97620.50333814 084 38823.701.1612370613 726 90827.001.32Gesuita et al,
2023143718 59319.90152703 70421.601.0912185692 88426.701.34Giorda et al,
202389535 17716.6395525 44218.081.0512126517 87924.331.46Matsuda et al,
20238136 1235.888136 1235.881.00128136 1235.881.00Pooled
13 28060 363 17622.0014 87559 652 42824.94NANA927136 072 88125.70NADKA incidence meta-analysisCaetano et al,
20216416538 787.88194443 181.821.11NRNRNRNRNRDilek et al,
2021274658 695.65687491 891.891.57NRNRNRNRNRKostopoulou et al,
202161735 294.12142166 666.671.89NRNRNRNRNRMameli et al,
202118450236 653.399120145 273.631.24NRNRNRNRNRMarks et al,
202114531046 774.1910518257 692.311.23NRNRNRNRNRMohamed Haniffa et al,
2021142850 000.00285352 830.191.06NRNRNRNRNRAl-Abdulrazzaq et al,
202111330337 293.7316632451 234.571.37NRNRNRNRNRAlassaf et al,
2021298334 939.76285451 851.851.48NRNRNRNRNRDonbaloğlu et al,
2022437855 128.21305653 571.430.97NRNRNRNRNRKaya et al,
2022327940 506.33304468 181.821.68NRNRNRNRNRLeiva-Gea et al,
2022377108534 746.5417235947 910.861.38NRNRNRNRNRModarelli et al,
2022316250 000.00234650 000.001.00NRNRNRNRNRPassanisi et al,
2022194344 186.05275346 846.851.0612255843 103.450.98Pietrzak et al,
2022521139137 455.07826167149 431.481.32NRNRNRNRNRWolf et al,
2022493127738 606.11599139942 816.301.11NRNRNRNRNRPooled2098546938 361.682226458148 592.011.27NRNRNRNRNRAbbreviations: DKA, diabetic ketoacidosis; IRR, incident rate ratio; NR, not reported.
a
Pooled data for the second year of the postpandemic period exclude the data from Shulman et al
due to insufficient duration of observation.
Table 3. Incident Types 1 and 2 Diabetes Cases Before and During the COVID-19 Pandemic Reported in Studies Not Included in the Meta-Analysis.
SourcePrepandemic periodPandemic periodDuration, moIncident cases, No.Duration, moIncident cases, No.Type 1 diabetesAlexandre et al,
202112271220Al-Qahtani et al,
20221226012167Dilek et al,
202112461274Kostopoulou et al,
202112171221Mameli et al,
20213662412256Marks et al,
20212431012182Mohamed Haniffa et al,
202112281253Moon et al,
20214819-28
1230Alassaf et al,
202212831254Ansar et al,
2022a24NR22NRCitron et al,
202212352082Donbaloğlu et al,
202224781256Kaya et al,
202236791244Leiva-Gea et al,
202260108515359Messaaoui et al,
2022228722147Modarelli et al,
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2022249090248190Schiaffini et al,
20223629024220Wolf et al,
2022121277121399Knip et al,
202354209618785Type 2 diabetesMarks et al,
20212410412141Ansar et al,
2022
24NR22NRAustralian Institute of Health and Welfare,
2022609330121540Citron et al,
20221282243DeLacey et al,
20226027112159Guo et al,
202236185212701Magge et al,
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20223640012232Sasidharan Pillai et al,
202338562288Abbreviation: NR, not reported.
a
Per year.
b
This study did not differentiate between types 1 and 2 diabetes cases when reporting incidence data.
Type 2 Diabetes
Ten of 42 studies (23.8%) reported the number of incident type 2 diabetes cases
,
,
,
,
,
,
,
,
,
; however, only 1 of those (10.0%) reported the size of the study populations.
Therefore, we were unable to conduct a meta-analysis comparing the incidence rate of type 2 diabetes between periods. We summarize the results of these studies in
. Eight studies (80.0%) reported an increase in the number of incident cases of type 2 diabetes during the first 12 months of the pandemic compared with during the 12 months before the pandemic.
,
,
,
,
,
,
,
DKA Incidence Rate Meta-Analysis
In a random-effects meta-analysis of pooled data from 15 studies (35.7%) including a total of 4324 children and adolescents with DKA, the incidence rate of DKA was higher during the pandemic period compared with the prepandemic period (IRR, 1.26; 95% CI, 1.17-1.36) (
C).
,
,
,
,
,
,
,
,
,
,
,
,
,
,
Between-study heterogeneity was minimal (I2 = 0%).
Discussion
In this systematic review and meta-analysis, in 17 studies including 38 149 children and adolescents with newly diagnosed type 1 diabetes,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
we found that the incidence rate of type 1 diabetes was 1.14 times higher in the first year and 1.27 times higher in the second year after the onset of the COVID-19 pandemic compared with before the pandemic. In 15 studies including a total of 4324 children and adolescents with DKA,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
we also found that the incidence rate of DKA at diagnosis was 1.26 times higher in the first year after the onset of the COVID-19 pandemic compared with before the pandemic. The magnitude of increase in the incidence rate of type 1 diabetes that we observed after the onset of the pandemic was greater than the expected 3% to 4% annual increase in the incidence rate based on prepandemic temporal trends in Europe.
Our findings are similar to those of another recent meta-analysis by Rahmati et al
that examined the incidence rate of type 1 diabetes and ketoacidosis in children during the COVID-19 pandemic in 2020 and during the same period in 2019. We compared the rate ratios reported in that meta-analysis by the length of their pandemic observation period. We found that studies with a pandemic period of 6 months or less had a lower estimated incidence rate compared with studies with a pandemic period of 12 months or greater (eFigure in
). Our systematic review adds important new information because it included studies that examined the incidence of both types 1 and 2 diabetes in children and adolescents, included additional data from later in the pandemic, and required at least 12 months of observation in both the pandemic and the prepandemic periods to account for the prepandemic seasonality of diabetes incidence and changes in seasonality during the pandemic that differed between Europe and North America.
,
We found substantial heterogeneity in the meta-analysis of diabetes incidence but not in the meta-analysis of DKA incidence. It is presumptive to assume why this occurred; however, some potential explanations include that higher within-study variation in the DKA meta-analysis may have resulted in a lower I2 value,
and other demographic, geographical, and methodologic factors may have led to increased heterogeneity between studies in the diabetes incidence meta-analysis.
Purported direct mechanisms to explain the association between new-onset diabetes and prior SARS-CoV-2 infection include evidence that the SARS-CoV-2 entry receptor ACE2 is expressed on insulin-producing β cells, SARS-CoV-2 infection contributes to dysregulation of glucose metabolism, and individuals who have an increased susceptibility to diabetes are especially vulnerable following SARS-CoV-2 infection because dysregulated glucose metabolism and direct viral damage to β cells impairs their compensatory mechanisms, leading to β-cell exhaustion.
However, there is no clear underlying mechanism explaining the association between SARS-CoV-2 infection and subsequent increased risk of incident diabetes.
,
While there are reports of an association between SARS-CoV-2 infection and subsequent increased risk of incident type 1 diabetes in children using routinely collected health record data,
,
,
there are concerns about the validity of such studies because the data sets used did not capture asymptomatic SARS-CoV-2 infections in children. Population-based studies that reported an increased incidence rate of type 1 diabetes in children and adolescents during the pandemic did not find an increase in the frequency of autoantibody-negative type 1 diabetes
,
,
; this suggests that the increase in incidence may be due to an immune-mediated mechanism.
Proposed indirect effects of the COVID-19 pandemic and containment measures that may be associated with diabetes incidence include changes in lifestyle, change in the pattern of pediatric non–COVID-19 infections, and increased stress and social isolation.
,
,
,
It has been proposed that frequent respiratory or enteric infections in children are potential triggers for islet autoimmunity, promote progression to overt type 1 diabetes, or are precipitating stressors.
Pandemic containment measures were associated with a decrease in viral respiratory and gastrointestinal tract infections among children.
Given this finding, the observed increased incidence rate of type 1 diabetes during the pandemic is contrary to what would be expected based on the decrease in viral infections among children during the pandemic.
There may have initially been a catch-up effect caused by lower incidence rates of pediatric diabetes early in the pandemic, possibly due to delays in diagnoses associated with hesitancy to seek care or barriers to access care.
,
,
However, the reported incidence of diabetes remained increased in studies that included data from beyond the first year of the pandemic.
,
,
,
,
,
,
,
,
Furthermore, there appears to have been a disruption to the historic seasonal pattern of autoantibody-positive diabetes incidence in children.
,
The reasons for this remain uncertain but may be related to the effects of COVID-19 containment strategies, such as lockdowns, both at the beginning of the pandemic and at subsequent times in different countries.
There are limited data about the change in the incidence rate of pediatric type 2 diabetes during the COVID-19 pandemic. The studies included in this systematic review and meta-analysis described an increase in the number of incident type 2 diabetes cases between periods but had insufficient data reported to assess whether there was also an increase in the incidence rate of childhood type 2 diabetes after the onset of the pandemic. Population-based studies that can measure the size of the study population (denominator) and therefore determine whether there has been a change in the incidence rate of type 2 diabetes in children and adolescents since the onset of the COVID-19 pandemic are needed.
We found an increased incidence rate of DKA at diabetes diagnosis among children and adolescents during the pandemic. This is concerning because DKA is preventable and an important cause of morbidity and mortality and is associated with long-term poor glycemic management.
,
An international study that used data from 13 pediatric diabetes registries reported a prevalence of DKA at diagnosis in 2020 and 2021 that was higher than the predicted prevalence based on prepandemic years 2006 to 2019.
A population-based study in Germany
found that the regional incidence of COVID-19 cases and deaths was associated with an increased risk of DKA at diagnosis, suggesting that the local severity of the pandemic, rather than the pandemic containment measures, may have led to delayed health care use and diagnosis. In Ontario, Canada, there was a higher DKA rate among those who had no precedent primary care visits and a pattern of fewer emergency department visits during the pandemic,
suggesting that delays in diagnosis of diabetes resulting in DKA may reflect hesitancy to seek care or barriers to access emergency care. Individuals living in areas with high COVID-19 positivity reported more hesitancy to seek emergency care for children.
Therefore, hesitancy to seek care may be an important factor in the observed increased risk of DKA during the pandemic.
There is concern about widespread negative consequences of the COVID-19 pandemic for child and adolescent health inequities.
However, relatively few studies examining changes in the incidence rate of pediatric diabetes since the onset of the COVID-19 pandemic have reported the socioeconomic status, race, or ethnicity of the study population. Such information would elucidate whether health disparities in the incidence rates of diabetes and DKA widened during the pandemic.
,
Implications
The results of our systematic review and meta-analysis demonstrated an increased incidence in childhood diabetes after the onset of the COVID-19 pandemic. The increased incidence rate of type 1 diabetes appeared to persist beyond the first year of the pandemic; this has important resource implications given the limited personnel resources in pediatric diabetes care to provide initial diabetes education at diagnosis and for long-term care. Future studies examining longer-term trends of incident types 1 and 2 diabetes may assess whether the increased incidence rate of type 1 diabetes continued and whether there was an increased incidence rate of pediatric type 2 diabetes. A better understanding of the possible direct effects of SARS-CoV-2 infection and the indirect effects of pandemic-related containment measures on incident diabetes in children is needed.
The increased prevalence of DKA at the time of diabetes diagnosis brings to light the need to identify the gaps in the pathway from the time when children develop signs of diabetes to subsequent diagnosis with DKA. This knowledge is needed to inform the development and implementation of effective strategies to prevent DKA at diagnosis in children. These may include public and health care professional–facing awareness campaigns and addressing hesitancy to seek emergency care.
,
Limitations
This study has limitations. Our search was restricted to studies published in English, and the included studies did not represent all regions of the world, limiting the generalizability of our findings worldwide. We included only studies that reported the incidence of DKA at diabetes diagnosis among studies that met our eligibility criteria, which required reporting incident diabetes cases in both study periods. Some studies included in our systematic review did not measure diabetes autoantibodies to confirm whether an individual had type 1 or another type of diabetes; thus, there may be a risk of misclassification of diabetes type.
Conclusions
This systematic review and meta-analysis found increased incidence rates of type 1 diabetes and DKA in children and adolescents during vs before the COVID-19 pandemic. Our findings underscore the need to dedicate resources to supporting an acute increased need for pediatric and ultimately young adult diabetes care and strategies to prevent DKA in patients with new-onset diabetes. Although prospective data examining whether this trend has persisted are needed, our findings suggest the need to elucidate possible underlying direct and indirect mechanisms to explain this increase. Furthermore, there is a paucity of data about socioeconomic, racial, and ethnic disparities in the incidence rate of diabetes during the COVID-19 pandemic; this gap must be filled to inform equitable strategies for intervention.
Supplement 1.
eTable 1. Subject Database and Gray Literature Search Strategies
eTable 2. Risk-of-Bias Evaluation Criteria Domains
eTable 3. Risk-of-Bias Assessments for Included Studies, Using the ROBINS-E Tool
eFigure. Rate Ratios Reported in the Meta-analysis by Rahmati et al, by Length of the Pandemic Observation Period
Supplement 2.
Data Sharing Statement
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplement 1.
eTable 1. Subject Database and Gray Literature Search Strategies
eTable 2. Risk-of-Bias Evaluation Criteria Domains
eTable 3. Risk-of-Bias Assessments for Included Studies, Using the ROBINS-E Tool
eFigure. Rate Ratios Reported in the Meta-analysis by Rahmati et al, by Length of the Pandemic Observation Period
Supplement 2.
Data Sharing Statement