GRAPHICAL ABSTRACT

Highlights

• This study analyzed trends in T2DM among young adults in Korea, 2010–2020.

• T2DM prevalence in young adults rose from 1.02% to 2.02%, sharply in ages 30–39.

• In 2020, among young adults with T2DM, 67.8% had BMI ≥25 kg/m², and 31.6% had BMI ≥30 kg/m².

• Hypertension, dyslipidemia, and fatty liver prevalence were 34.2%, 79.8%, and 78.9%.

• SGLT2 inhibitor and GLP-1RA use rose among young adults, but treatment stayed low.

INTRODUCTION

Diabetes mellitus (DM) is a chronic metabolic disease that affects multiple organs and leads to vascular complications if not adequately managed [1]. Traditionally, DM—particularly type 2 diabetes mellitus (T2DM)—has been considered a disease that predominantly affects middle-aged and older individuals. However, the prevalence of T2DM in younger populations is increasing worldwide [2,3]. While definitions of early-onset T2DM vary, it is generally accepted that a diagnosis made before the age of 40 years represents a distinct clinical entity compared to later-onset T2DM [2,4]. Early-onset T2DM is further subdivided into T2DM diagnosed in childhood (age ≤18 years) and early adulthood (age 19 to 39 years) [2]. Young people with T2DM often have difficulty achieving adequate glycemic control and are at increased risk of developing complications [5], highlighting the need for targeted interventions.

Globally, the estimated number of people with T2DM aged 20 to 39 years increased from 63 million in 2013 to 260 million in 2021 [2]. The incidence and prevalence of T2DM in younger populations show regional and ethnic variations [6,7]. In particular, Asian countries have reported a marked increase in T2DM prevalence among younger individuals, in part due to a greater susceptibility to developing T2DM at lower body mass index (BMI) levels compared to Western populations [8-10]. Despite the global increase in T2DM among young adults, the epidemiology and clinical characteristics of this population in South Korea remain understudied.

To address this gap, we collaborated with the Korean Diabetes Association to estimate the prevalence and incidence of T2DM among young adults (aged 19 to 39 years) in South Korea. In addition, we assessed the changes in metabolic characteristics, comorbidities, vascular complications, and antidiabetic medication prescriptions among young adults with T2DM.

METHODS

Data sources

To obtain reliable and representative estimates of young adults (aged 19 to 39 years) with T2DM in South Korea, data from 2010 to 2020 in the Korean National Health Insurance Service (NHIS)-Customized Database were analyzed. The NHIS database covers almost all South Korean citizens, and provide a longitudinal data set that includes demographic information, disease diagnoses based on the International Classification of Diseases, 10th Revision (ICD-10), prescription records, hospital admissions, procedure details, and health examination results including laboratory tests and anthropometric measurements [11-17]. As supporting information, we further analyzed data from the Korea National Health and Nutrition Examination Survey (KNHANES, from 2012 to 2022), a series of cross-sectional surveys designed to assess the health status of the Korean population using a multistage clustered probability sampling design [18,19].

This study received ethical approval from the Institutional Review Board (IRB) of Korea University Anam Hospital (IRB number: 2022AN0531). Informed consent was not required because the databases used did not contain personally identifiable information.

Definition of diabetes mellitus and patient selection

In the NHIS-Customized Database, T2DM was defined as the presence of ICD-10 codes E11–E14 or a fasting plasma glucose (FPG) level ≥126 mg/dL. Individuals who subsequently received an ICD-10 code E10 with insulin prescriptions was considered to have type 1 diabetes mellitus (T1DM) and were excluded. We allocated at least 1 year for the exclusion process. The database identified all individuals aged 19 to 39 years who met the aforementioned diagnostic criteria for T2DM, with 225,497 in 2010 and 372,726 in 2020. The evaluation of the prevalence, incidence, metabolic characteristics, comorbidities, vascular complications, and pharmacological treatment rate was based on these populations. The number of total population aged 19 to 39 years in South Korea was determined using data from the National Statistical Office.

Prediabetes was defined as an FPG level of 100 to 125 mg/dL in the absence of ICD-10 codes E10–E14 or use of antidiabetic medications. Individuals aged 19 to 39 years who met the criteria for prediabetes were identified among those who underwent a national health examination, tailoring 3,498,371 in 2010 and 4,087,713 in 2020. Of these, 543,437 met the definition of prediabetes in 2010 and 855,310 in 2020.

In additional analyses using the KNHANES database, DM was defined as having an FPG level ≥126 mg/dL, or a glycosylated hemoglobin (HbA1c) level ≥6.5%, or a previous diagnosis of DM in the questionnaire, or the use of antidiabetic medication [20-23]. The number of patients meeting these criteria was 30 out of a total population of 1,474 in 2012 and 26 out of 1,222 in 2022. The type of DM was not specified in this database. Prediabetes was defined as having an FPG level of 100 to 125 mg/dL or an HbA1c level of 5.7% to 6.4% without meeting the criteria for DM.

Metabolic parameters, comorbidities, and vascular complications

We examined changes in BMI, waist circumference (WC), and the prevalence of comorbidities including hypertension, dyslipidemia, fatty liver disease and vascular complications including myocardial infarction (MI), ischemic stroke, heart failure, end-stage kidney disease (ESKD), and proliferative diabetic retinopathy (PDR), in young adults with T2DM over a 10-year period (2010 to 2020). Additionally, we investigated the trends in the characteristics of individuals newly diagnosed with T2DM at the time of diagnosis.

BMI was categorized using cut-off points of 23.0, 25.0, 30.0, 35.0, and 40.0 kg/m² [24,25]. Central obesity was defined as a WC ≥90 cm in men or ≥85 cm in women. Hypertension was defined as having a systolic blood pressure ≥140 mm Hg, a diastolic blood pressure ≥90 mm Hg, or the use of antihypertensive medication. Dyslipidemia was defined as a low-density lipoprotein cholesterol level ≥100 mg/dL or the use of lipidlowering medications [26]. Fatty liver disease was determined by a fatty liver index (FLI) ≥30. The FLI was calculated as follows [27,28]:

[e^{0.953×loge(triglycerides)+0.139×BMI+0.718×loge(gamma-glutamyl transpeptidase)+0.053× WC−15.745}]/

[1+e^{0.953×loge(triglycerides)+0.139×BMI+0.718×loge(gamma-glutamyl transpeptidase)+ 0.053×WC−15.745}]×100.

MI was defined as hospitalization with ICD-10 codes I21– I22. Ischemic stroke was identified as hospitalization with ICD-10 codes I63–I64 accompanied by brain imaging studies. Heart failure was defined as hospitalization with a diagnosis of heart failure (ICD-10 code I50). ESKD was defined by the receipt of special exemption codes V001 (hemodialysis), V003 (peritoneal dialysis), or V005 (kidney transplant). PDR was defined as undergoing photocoagulation (procedure codes S5160 or S5161) and having an ICD-10 diagnosis code of H36.0 (diabetic retinopathy) within the year prior to the procedure.

Use of antidiabetic medication

Antidiabetic medication prescription among young adults with T2DM was evaluated from 2010 to 2020. We examined the pharmacological treatment rate, defined as the proportion of individuals taking antidiabetic medications. Further analyses were conducted among those receiving antidiabetic medications. The classes of antidiabetic medications were categorized as follows: insulin, metformin, sulfonylurea (SU), meglitinide, thiazolidinedione (TZD), α-glucosidase inhibitor, dipeptidyl peptidase-4 (DPP-4) inhibitor, sodium-glucose cotransporter-2 (SGLT2) inhibitor, and glucagon-like peptide-1 receptor agonist (GLP-1RA). Insulin was counted if it was prescribed at least three times during the year, while the other medications were counted if prescribed at least once during the year. In addition, patterns of combination therapy excluding insulin were examined and categorized as monotherapy, dual combination, triple combination, and quadruple or higher combinations.

Statistical analysis

The prevalence and incidence rates of T2DM were calculated annually, and trend tests were performed to evaluate changes over time. Analyses focused on individuals aged 19–39 years, stratified into two age groups (19–29 and 30–39 years) and by sex (men and women). We examined whether the two age groups and sex groups exhibited different patterns of change over time, with the results presented as P values for interactions. Annual assessments of metabolic parameters, the prevalence of comorbidities and vascular complications, and antidiabetic drug prescription among young adults with T2DM were also performed. Additionally, the trends in characteristics at the time of diagnosis of incident T2DM were investigated. Statistical analyses were performed with SAS version 9.4 (SAS Institute Inc., Cary, NC, USA).

RESULTS

The characteristics of the incident T2DM patients are summarized in the Supplementary Table 1. Over the study period, the mean age at diagnosis of T2DM decreased (33.2 years in 2010 and 32.3 years in 2020, P<0.001). The male-to-female ratio consistently showed that approximately twice as many men were diagnosed with T2DM. The mean BMI at diagnosis increased significantly over time (25.4 kg/m² in 2010 and 28.3 kg/m² in 2020, P<0.001), accompanied by increasing rates of general and abdominal obesity. The prevalence of comorbid hypertension, dyslipidemia, and fatty liver disease increased over time. Fatty liver disease, as indicated by the FLI, had the highest prevalence, affecting 83.1% of young people with newly diagnosed T2DM in 2020.

Prevalence and incidence of T2DM in young adults

Between 2010 and 2020, the prevalence rate of T2DM among young adults increased significantly, from 1.02% to 2.02% (P<0.001), and the number of affected individuals increased from 225,497 to 372,726 (Fig. 1A, Supplementary Table 2). Throughout the period, prevalence rates were consistently higher in men than in women, increasing from 1.22% to 2.30% in men and from 0.81% to 1.71% in women (Fig. 1B). When stratified by age, the prevalence of T2DM in individuals aged 19–29 years increased from 0.73% to 1.54%, whereas the prevalence in individuals aged 30–39 years increased from 2.09% to 3.90%, resulting in a prevalence more than doubled in the 30–39 years age group by 2020 (Fig. 1C).

The incidence rate of T2DM among young adults remained relatively stable, ranging from 0.36% to 0.45% annually between 2010 and 2020 (Fig. 1D, Supplementary Table 3). Similar to prevalence trends, incidence rates were higher in men than in women and more than twice as high in individuals aged 30– 39 years compared with those aged 19–29 years.

Trends in the prevalence of DM was also estimated from the KNHANES database, although the type of DM was not specified in this dataset. The prevalence of DM showed fluctuations between 1.5% and 2.5% from 2012 to 2022, probably due to small sample sizes (Supplementary Fig. 1A). From the most recent integrated KNHANES database from 2019 to 2022, the prevalence of DM in young adults was 2.2%. As in the NHISCustomized Database, the prevalence rate of DM was higher in men (2.7%) compared with women (1.7%) (Supplementary Fig. 1B). In addition, the prevalence in individuals aged 30–39 years (3.4%) was more than three times higher than that observed in those aged 19–29 years (1.1%).

Prevalence of prediabetes in young adults

From NHIS-Customized Database (2010 to 2020), the prevalence of prediabetes among young adults aged 19–39 years who underwent national health examinations steadily increased from 15.53% to 20.92%, with an estimated 3,865,194 affected individuals in 2020 (Fig. 2). Analysis of the KNHANES database (2019–2022) revealed a prediabetes prevalence of prediabetes of 21.8%, with higher rates in men (26.5%) compared with women (16.7%) (Supplementary Fig. 2). The prevalence of prediabetes was more than twice as high in the 30–39 age group (29.8%), compared to those aged 19–29 years (14.3%).

Obesity in young adults with T2DM

Between 2010 and 2020, the mean±standard deviation (SD) BMI of young adults with T2DM increased from 25.5±4.3 to 27.6±5.6 kg/m², while the mean±SD WC increased from 84.5±10.9 to 89.1±14.0 cm (P<0.001 for both) (Fig. 3A, Supplementary Table 4). Throughout the study period, the mean BMI of men was consistently higher than that of women. In men, the mean BMI increased from 26.0±4.0 in 2010 to 28.4± 5.1 kg/m² in 2020, whereas in women, it increased from 23.7± 4.9 to 26.0±6.2 kg/m² (Fig. 3B). The proportion of young adults with obesity also increased significantly over this period (Fig. 3C). The percentage of patients with stage 1 obesity or higher (BMI ≥25 kg/m²) increased from 53.8% to 67.8%, while stage 2 obesity or higher (BMI ≥30 kg/m²) increased from 14.8% to 31.6%. The prevalence of stage 3 obesity (BMI ≥35 kg/m²) reached 10.1% in 2020, and 2.6% of patients had a BMI of ≥40 kg/m². When the proportion of obesity in young adult with T2DM was analyzed separately by sex, the proportion of stage 1 obesity or higher increased from 58.5% to 75.1% in men and from 36.2% to 52.4% in women (Fig. 3D). The prevalence of stage 2 obesity or higher (BMI ≥30 kg/m²) increased from 15.5% to 34.1% in men and from 12.6% to 26.4% in women.

Comorbidities and vascular complications

Between 2010 and 2020, the prevalence rates of hypertension, dyslipidemia, and fatty liver disease in young adults with T2DM showed an increasing trend, reaching 34.2%, 79.8%, and 78.9%, respectively, by 2020 (P<0.001 for all) (Fig. 4A, Supplementary Table 5). The prevalence of vascular complications is displayed in Fig. 4B, Supplementary Table 5. The prevalence of vascular complications among young adults with T2DM was less than 1%. While the prevalence of ESKD has been gradually decreasing, the prevalence of heart failure has shown an increasing trend. The most common comorbid vascular disease in 2020 was heart failure, followed by ESKD, PDR, MI, and ischemic stroke.

Antidiabetic medication patterns in young adults with T2DM

Fig. 5A shows the pharmacological treatment rate of young adults with T2DM, the proportion of patients receiving antidiabetic medication. The treatment rate was very low at 28.7% in 2010, increasing slightly to 33.0% in 2020. Among those receiving antidiabetic medication, Fig. 5B shows the prescription patterns of pharmacologic treatments. There has been an increase in the prescription rates of metformin, SGLT2 inhibitors, and GLP-1RA since 2015. In particular, the prescription rate for SGLT2 inhibitors showed the most significant increase, with 32.0% of patients using these agents by 2020. Metformin remained the most commonly prescribed medication throughout the study period, with a steady increase in used to reach 91.2% of patients in 2020. While the prescription rate of DPP-4 inhibitors declined after 2016, it remained the second most commonly prescribed medication in 2020. Conversely, the prescription rates of SU and TZD showed a gradual decline over time. Fig. 5C highlights the patterns of drug regimen combinations excluding insulin. A notable trend was the decrease in the use of monotherapy and the increase in the use of triple and quadruple or higher combination therapies. Specifically, the proportion of patients receiving triple combination therapy increased from 17.8% in 2010 to 32.4% in 2020, while those receiving quadruple or higher combination therapy increased from 4.0% to 8.8% over the same period.

DISCUSSION

This study demonstrated an increasing prevalence of T2DM among young adults in South Korea, and unique characteristics of affected individuals with distinct disease phenotypes. In the decade from 2010 to 2020, the prevalence of T2DM among individuals aged 19 to 39 years nearly doubled, with approximately 400,000 young adults affected by 2020. One of the most notable findings was the significant increase in obesity rates among young adults with T2DM, reflected in a mean BMI of 27.6 kg/m² in 2020. This increase in obesity correlates with increased prescribing of antidiabetic medications that promote weight loss, such as SGLT2 inhibitors and GLP-1RAs.

The increasing prevalence of T2DM in Korean young adults is consistent with global trends, particularly in the Western Pacific and Southeast Asian regions, where the burden of earlyonset T2DM is substantial [4]. Reports from the Joint Asia Diabetes Evaluation (JADE) program estimate that 10% to 25% of T2DM patients in Asia are diagnosed before the age of 40 [29]. In South Korea, previous studies using sample-based databases such as KNHANES and NHIS-National Sample Cohort have shown similar trends [30]. In a study using the KNHANES database, the prevalence of T2DM increased from 0.5% in 2005 to 1.0% in 2016–2018 among individuals aged 20–29 years, and from 1.2% to 2.4% among individuals aged 30–39 years. A NHIS-National Sample Cohort (2006 to 2015) analysis showed that DM prevalence increased from 0.3% to 0.4% and from 1.1% to 1.4% among individuals aged 20–29 and 30–39 years, respectively. Our study, based on the NHIS-Customized Database with an actual number of affected individuals, provided a comprehensive view and showed that the prevalence of T2DM increased from 1.02% in 2010 to 2.02% in 2020 among individuals aged 19 to 39 years. In particular, prevalence increased more rapidly in the 30 to 39 age group, reaching 3.90% in 2020. Despite limitations in the KNHANES data due to small sample sizes, the estimated DM prevalence of 2.2% during 2019 to 2022 are consistent with findings from the NHIS-Customized Database, strengthening the validity of our findings. Gender differences in T2DM prevalence were consistently observed, with higher rates in men compared to women. This disparity is likely influenced by the higher prevalence of obesity in men, as well as systematic health screening during mandatory physical examinations for military enlistment.

While the prevalence of T2DM has increased, the incidence rate among young adults has remained relatively stable. It increased steadily from 0.36% to 0.45% between 2012 and 2019, but decreased to 0.41% in 2020, likely due to reduced healthcare utilization during the coronavirus disease 2019 (COVID-19) pandemic. In an earlier study, there was a gradual increase in DM incidence from 2006 to 2015 [30].

Obesity is an established risk factor for T2DM [31]. The association between T2DM and obesity is particularly pronounced in younger populations, with earlier age of diagnosis associated with higher BMI. For example, a United States study reported that patients diagnosed with DM in their 30s or younger had a mean BMI of 38.3 kg/m², compared with 28.8 kg/m² in those diagnosed at age 70 or older [32]. Similarly, previous South Korean data showed that the proportion of young diabetic patients with a BMI ≥25 kg/m² increased from 51.4% in 2006 to 72.4% in 2015 [30]. In our study, 67.8% of young adults with T2DM had a BMI ≥25 kg/m², 31.6% had a BMI ≥30 kg/m², and 10.1% had a BMI ≥35 kg/m² in 2020. The prevalence of obesity observed in our study was relatively lower compared to that reported in a previous study [30], likely due to differences in the operational definition of T2DM. Specifically, our study included both individuals who were on antidiabetic medications and those who were not, whereas the previous study included only those receiving antidiabetic medications. When we applied a similar definition, including only individuals with ICD-10 codes E11 to E14 and concurrent use of antidiabetic medications, the mean BMI increased to 29.3 kg/m², and the prevalence of obesity increased to 80.4% in 2020 (Supplementary Fig. 3). However, regardless of the operational definition of T2DM, it is evident that the prevalence of obesity is increasing among young adults with T2DM. In addition, the prevalence of central obesity, as reflected by increased WC, further underscores the metabolic risk in this population. Moreover, the prevalence of obesity and central obesity also increased among those newly diagnosed with T2DM (Supplementary Table 1). These findings suggest both rising obesity rates among newly diagnosed young T2DM patients and inadequate obesity management in prevalent cases.

The striking prevalence of obesity provides insight into the management and prevention of T2DM in young adults, emphasizing the need to prioritize obesity treatment. Although there was an increasing trend in the prescription of antidiabetic drugs with weight-reducing benefits, the proportion of young adults with T2DM treated with GLP-1RAs still remained low (3.4% in 2020). Clinicians should consider the impact of antidiabetic medications on weight when prescribing them while actively encouraging patients to adopt lifestyle modifications [24,25]. Moreover, when counseling obese young adults who have not yet been diagnosed with T2DM, it is essential to actively screen for T2DM [21] and aggressively manage obesity to prevent T2DM. Considering that anti-obesity drugs are currently not covered by insurance and the use of antidiabetic drugs with weight-reducing effects is largely limited by current insurance coverage criteria, policies expanding insurance coverage for young adults with T2DM and morbid obesity may be needed.

Another important finding of this study is the high prevalence of metabolic comorbidities in young adults with T2DM. Approximately 80% had dyslipidemia and fatty liver disease, and 34.2% had hypertension. The co-occurrence of these conditions increases the risk of cardiovascular disease and other long-term complications, underscoring the need for a comprehensive, multidisciplinary approach to diabetes management. Among vascular complications, the prevalence of heart failure has substantially increased, becoming the most common complication in 2020. Incorporating routine screening for comorbidities and complications, along with early intervention, could mitigate the progression of these conditions.

Analysis of pharmacological treatment patterns has revealed a shift over the past decade toward newer antidiabetic agents, such as SGLT2 inhibitors and GLP-1RAs. These medications, which offer cardiovascular and renal protection [33-37], have gained prominence in treatment regimens, reflecting adherence to evolving clinical guidelines [21]. In particular, the prescription rate for SGLT2 inhibitors has increased significantly, reaching 32.0% in 2020. Despite these advances, metformin remained the most commonly prescribed drug throughout the study period, with 91.2% of patients using it in 2020. The increasing use of metformin, SGLT2 inhibitors and GLP-1RAs— all of which are associated with weight management benefits— appears to reflect growing clinical recognition of the interplay between DM and obesity in this population. However, the proportion of patients receiving antidiabetic agents was low, at 33.0% in 2020. Analysis of the KNHANES database from 2019 to 2022 revealed a similar treatment rate of 34.6%, consistent with findings from the NHIS-Customized Database. The low pharmacological treatment rate among young patients with T2DM warrants attention and further intervention.

To the best of our knowledge, this is the largest study investigating the epidemiology of young adults with T2DM in South Korea, encompassing nearly the entire population using the NHIS-Customized Database. While the KNHANES dataset has commonly been used to evaluate diabetes prevalence, the number of young adults with T2DM in KNHANES was low, with approximately 30 cases per year. Therefore, we utilized the NHIS-Customized Database, presenting data from KNHANES as supporting information. The NHIS-Customized Database allows us to report the actual number of young adults with T2DM and comprehensively analyze their characteristics, including metabolic features, comorbidities, vascular complications, and use of antidiabetic medications.

This study has several limitations. First, the accuracy of T2DM diagnoses in the NHIS database may be compromised because diagnoses were based on corresponding codes and FPG levels without mandatory confirmation by antidiabetic medication use. This approach was chosen because of the low awareness and treatment rates of DM in young adults, which remain below 50%. Additionally, we excluded patients who received an ICD-10 code E10 (T1DM) diagnosis with insulin prescriptions after initially being assigned ICD-10 codes E11 (T2DM) to E14. As a result, individuals with an unclear diabetes type may have been excluded from the current analysis. However, without this exclusion process, we believed that a substantial portion of the study population would have included T1DM patients, given their age. Second, the prevalence estimates of prediabetes may be imprecise because they were derived only from individuals undergoing national health examinations, potentially excluding a significant portion of the population. Third, the vascular complications identified in this study should be interpreted as comorbid conditions rather than true complications, as they were assessed cross-sectionally each year.

In conclusion, the results of this study highlight a worrisome increase in T2DM prevalence among young adults in South Korea, which is strongly associated with increasing obesity and related metabolic comorbidities. Although the pharmacological treatment rate was low, the evolving treatment patterns and increasing complexity of therapeutic regimens reflect the challenges of managing this condition in younger populations. These findings underscore the need for multifaceted strategies that include prevention, early diagnosis, and comprehensive management to address the growing burden of T2DM in young adults.

SUPPLEMENTARY MATERIALS

NOTES

CONFLICTS OF INTEREST

Seung-Hyun Ko has been the executive editor of the Diabetes & Metabolism Journal since 2022. Sung Hee Choi has been an associate editor of the Diabetes & Metabolism Journal since 2022. They were not involved in the review process of this article. Otherwise, there was no conflict of interest.

AUTHOR CONTRIBUTIONS

Conception or design: J.Y.K., N.H.K.

Acquisition, analysis, or interpretation of data: all authors.

Drafting the work or revising: J.Y.K., N.H.K.

Final approval of the manuscript: N.H.K.

FUNDING

None

ACKNOWLEDGMENTS

We acknowledge the Korean Diabetes Association for supporting this study.

Fig. 1.

Prevalence and incidence rate of type 2 diabetes mellitus (T2DM) in young adults (2010 to 2020). (A) Trends in number and prevalence rate of T2DM in young adults. (B) Trends in the prevalence rate of T2DM in young adults by sex. (C) Trends in the prevalence rate of T2DM in young adults by age group. (D) Trends in the incidence rate of T2DM in young adults.

Fig. 2.

Prevalence rate and estimated number of prediabetes in young adults (2010 to 2020). M, million.

Fig. 3.

Obesity in young adults with type 2 diabetes mellitus (T2DM). (A) Trends in mean body mass index (BMI) and waist circumference (WC) in young adults with T2DM. (B) Trends in mean BMI by sex. (C) Trends in the proportion of individuals with a BMI of ≥25, ≥30, ≥35, and ≥40 kg/m² among young adults with T2DM. (D) Trends in the proportion of individuals with a BMI of ≥25 and ≥30 kg/m² among young adults with T2DM, analyzed by sex.

Fig. 4.

Trends in comorbidities and vascular complications in young adults with type 2 diabetes mellitus (2010 to 2020). (A) Prevalence of hypertension, dyslipidemia, and fatty liver disease. (B) Prevalence of vascular complications. MI, myocardial infarction; ESKD, end-stage kidney disease; PDR, proliferative diabetic retinopathy.

Fig. 5.

Trends in antidiabetic medication use among young adults with type 2 diabetes mellitus. (A) Pharmacological treatment rate. (B) Prescription patterns for pharmacological treatments among those receiving antidiabetic medications. (C) Patterns of drug regimen combinations excluding insulin among those receiving antidiabetic medications. SU, sulfonylurea; TZD, thiazolidinedione; AGI, alpha-glucosidase inhibitor; DPP-4i, dipeptidyl peptidase-4 inhibitor; SGLT2i, sodium-glucose cotransporter-2 inhibitor; GLP-1RA, glucagon-like peptide-1 receptor agonist.

REFERENCES

• 1. DeFronzo RA, Ferrannini E, Groop L, Henry RR, Herman WH, Holst JJ, et al. Type 2 diabetes mellitus. Nat Rev Dis Primers 2015;1:15019.PubMed
• 2. Misra S, Ke C, Srinivasan S, Goyal A, Nyriyenda MJ, Florez JC, et al. Current insights and emerging trends in early-onset type 2 diabetes. Lancet Diabetes Endocrinol 2023;11:768-82.ArticlePubMed
• 3. Kim JY, Park S, Park M, Kim NH, Kim SG. Income-related disparities in mortality among young adults with type 2 diabetes. JAMA Netw Open 2024;7:e2443918.ArticlePubMedPMC
• 4. Lascar N, Brown J, Pattison H, Barnett AH, Bailey CJ, Bellary S. Type 2 diabetes in adolescents and young adults. Lancet Diabetes Endocrinol 2018;6:69-80.ArticlePubMed
• 5. Yang YS, Han K, Sohn TS, Kim NH. Young-onset type 2 diabetes in South Korea: a review of the current status and unmet need. Korean J Intern Med 2021;36:1049-58.ArticlePubMedPMCPDF
• 6. Todd JN, Srinivasan S, Pollin TI. Advances in the genetics of youth-onset type 2 diabetes. Curr Diab Rep 2018;18:57.ArticlePubMedPMCPDF
• 7. Bjornstad P, Chao LC, Cree-Green M, Dart AB, King M, Looker HC, et al. Youth-onset type 2 diabetes mellitus: an urgent challenge. Nat Rev Nephrol 2023;19:168-84.ArticlePubMedPDF
• 8. Shaw JE, Sicree RA, Zimmet PZ. Global estimates of the prevalence of diabetes for 2010 and 2030. Diabetes Res Clin Pract 2010;87:4-14.ArticlePubMed
• 9. Kim JH, Lim JS. Trends of diabetes and prediabetes prevalence among Korean adolescents from 2007 to 2018. J Korean Med Sci 2021;36:e112.ArticlePubMedPMCPDF
• 10. Yoon KH, Lee JH, Kim JW, Cho JH, Choi YH, Ko SH, et al. Epidemic obesity and type 2 diabetes in Asia. Lancet 2006;368:1681-8.ArticlePubMed
• 11. Seong SC, Kim YY, Park SK, Khang YH, Kim HC, Park JH, et al. Cohort profile: the National Health Insurance Service-National Health Screening Cohort (NHIS-HEALS) in Korea. BMJ Open 2017;7:e016640.ArticlePubMedPMC
• 12. Kyoung DS, Kim HS. Understanding and utilizing claim data from the Korean National Health Insurance Service (NHIS) and Health Insurance Review & Assessment (HIRA) database for research. J Lipid Atheroscler 2022;11:103-10.ArticlePubMedPDF
• 13. Kim MK, Han K, Lee SH. Current trends of big data research using the Korean National Health Information Database. Diabetes Metab J 2022;46:552-63.ArticlePubMedPMCPDF
• 14. Cho SW, Kim JH, Choi HS, Ahn HY, Kim MK, Rhee EJ. Big data research in the field of endocrine diseases using the Korean National Health Information Database. Endocrinol Metab (Seoul) 2023;38:10-24.ArticlePubMedPMCPDF
• 15. Kim KS, Hong S, Han K, Park CY. Clinical characteristics of patients with statin discontinuation in Korea: a nationwide population-based study. J Lipid Atheroscler 2024;13:41-52.ArticlePubMedPDF
• 16. Kim NH, Kim JY, Choi J, Kim SG. Associations of omega-3 fatty acids vs. fenofibrate with adverse cardiovascular outcomes in people with metabolic syndrome: propensity matched cohort study. Eur Heart J Cardiovasc Pharmacother 2024;10:118-27.ArticlePubMedPDF
• 17. Kim KS, Kim B, Han K. Big data research for diabetes-related diseases using the Korean National Health Information Database. Diabetes Metab J 2025;49:13-21.ArticlePubMedPMCPDF
• 18. Oh K, Kim Y, Kweon S, Kim S, Yun S, Park S, et al. Korea National Health and Nutrition Examination Survey, 20th anniversary: accomplishments and future directions. Epidemiol Health 2021;43:e2021025.ArticlePubMedPMC
• 19. Jin ES, Shim JS, Kim SE, Bae JH, Kang S, Won JC, et al. Dyslipidemia fact sheet in South Korea, 2022. J Lipid Atheroscler 2023;12:237-51.ArticlePubMedPMCPDF
• 20. Bae JH, Han KD, Ko SH, Yang YS, Choi JH, Choi KM, et al. Diabetes fact sheet in Korea 2021. Diabetes Metab J 2022;46:417-26.ArticlePubMedPMCPDF
• 21. Moon JS, Kang S, Choi JH, Lee KA, Moon JH, Chon S, et al. 2023 Clinical practice guidelines for diabetes management in Korea: full version recommendation of the Korean Diabetes Association. Diabetes Metab J 2024;48:546-708.ArticlePubMedPMCPDF
• 22. Jung CH, Son JW, Kang S, Kim WJ, Kim HS, Kim HS, et al. Diabetes fact sheets in Korea, 2020: an appraisal of current status. Diabetes Metab J 2021;45:1-10.ArticlePubMedPMCPDF
• 23. Kim BY, Won JC, Lee JH, Kim HS, Park JH, Ha KH, et al. Diabetes fact sheets in Korea, 2018: an appraisal of current status. Diabetes Metab J 2019;43:487-94.ArticlePubMedPMCPDF
• 24. Kim KK, Haam JH, Kim BT, Kim EM, Park JH, Rhee SY, et al. Evaluation and treatment of obesity and its comorbidities: 2022 update of clinical practice guidelines for obesity by the Korean Society for the Study of Obesity. J Obes Metab Syndr 2023;32:1-24.ArticlePubMedPMC
• 25. Haam JH, Kim BT, Kim EM, Kwon H, Kang JH, Park JH, et al. Diagnosis of obesity: 2022 update of clinical practice guidelines for obesity by the Korean Society for the Study of Obesity. J Obes Metab Syndr 2023;32:121-9.ArticlePubMedPMC
• 26. Yang YS, Kim HL, Kim SH, Moon MK; Committee of Clinical Practice Guideline; Korean Diabetes Association; Clinical Practice Guideline Committee; Korean Society of Lipid and Atherosclerosis. Lipid management in Korean people with type 2 diabetes mellitus: Korean Diabetes Association and Korean Society of Lipid and Atherosclerosis Consensus Statement. J Lipid Atheroscler 2023;12:12-22.ArticlePubMedPMCPDF
• 27. Bedogni G, Bellentani S, Miglioli L, Masutti F, Passalacqua M, Castiglione A, et al. The fatty liver index: a simple and accurate predictor of hepatic steatosis in the general population. BMC Gastroenterol 2006;6:33.ArticlePubMedPMCPDF
• 28. Han E, Han KD, Lee YH, Kim KS, Hong S, Park JH, et al. Fatty liver & diabetes statistics in Korea: nationwide data 2009 to 2017. Diabetes Metab J 2023;47:347-55.ArticlePubMedPMCPDF
• 29. Yeung RO, Zhang Y, Luk A, Yang W, Sobrepena L, Yoon KH, et al. Metabolic profiles and treatment gaps in young-onset type 2 diabetes in Asia (the JADE programme): a cross-sectional study of a prospective cohort. Lancet Diabetes Endocrinol 2014;2:935-43.ArticlePubMed
• 30. Choi HH, Choi G, Yoon H, Ha KH, Kim DJ. Rising incidence of diabetes in young adults in South Korea: a national cohort study. Diabetes Metab J 2022;46:803-7.ArticlePubMedPMCPDF
• 31. Kwak SH, Park KS. Pathophysiology of type 2 diabetes in Koreans. Endocrinol Metab (Seoul) 2018;33:9-16.ArticlePubMedPMCPDF
• 32. Hillier TA, Pedula KL. Characteristics of an adult population with newly diagnosed type 2 diabetes: the relation of obesity and age of onset. Diabetes Care 2001;24:1522-7.PubMed
• 33. McGuire DK, Shih WJ, Cosentino F, Charbonnel B, Cherney DZ, Dagogo-Jack S, et al. Association of SGLT2 inhibitors with cardiovascular and kidney outcomes in patients with type 2 diabetes: a meta-analysis. JAMA Cardiol 2021;6:148-58.ArticlePubMed
• 34. Sattar N, Lee MM, Kristensen SL, Branch KR, Del Prato S, Khurmi NS, et al. Cardiovascular, mortality, and kidney outcomes with GLP-1 receptor agonists in patients with type 2 diabetes: a systematic review and meta-analysis of randomised trials. Lancet Diabetes Endocrinol 2021;9:653-62.ArticlePubMed
• 35. Cho YK, Lee YL, Jung CH. The cardiovascular effect of tirzepatide: a glucagon-like peptide-1 and glucose-dependent insulinotropic polypeptide dual agonist. J Lipid Atheroscler 2023;12:213-22.ArticlePubMedPMCPDF
• 36. Kim NH, Kim NH. Renoprotective mechanism of sodiumglucose cotransporter 2 inhibitors: focusing on renal hemodynamics. Diabetes Metab J 2022;46:543-51.ArticlePubMedPMCPDF
• 37. Kim JY, Kim SG. SGLT2 inhibitors and diabetes: where does it come from and where does it go? J Korean Diabetes 2024;25:9-15.ArticlePDF

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Kim JY, Lee J, Moon JH, Park SE, Ko SH, Choi SH, Kim NH. Prevalence, Incidence, and Metabolic Characteristics of Young Adults with Type 2 Diabetes Mellitus in South Korea (2010–2020). Diabetes Metab J. 2025;49(2):172-182.

Received: Dec 18, 2024; Accepted: Feb 12, 2025

DOI: https://doi.org/10.4093/dmj.2024.0826.

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