The DOI matches its Crossref record; 76 of the 76 references it cites were found in a registry or an index.
Diabetes Fact Sheet in Korea, 2016: An Appraisal of Current Status
Open accessAbstract
BACKGROUND: This study aimed to investigate the recent prevalence, management, and comorbidities of diabetes among Korean adults aged ≥30 years by analyzing nationally representative data. METHODS: This study used data from the Korea National Health and Nutrition Examination Survey from 2016 to 2018, and the percentage and total number of people ≥30 years of age with diabetes and impaired fasting glucose (IFG) were estimated. RESULTS: In 2018, 13.8% of Korean adults aged ≥30 years had diabetes, and adults aged ≥65 years showed a prevalence rate of 28%. The prevalence of IFG was 26.9% in adults aged ≥30 years. From 2016 to 2018, 35% of the subjects with diabetes were not aware of their condition. Regarding comorbidities, 53.2% and 61.3% were obese and hypertensive, respectively, and 72% had hypercholesterolemia as defined by low-density lipoprotein cholesterol (LDL-C) ≥100 mg/dL in people with diabetes. Of the subjects with diabetes, 43.7% had both hypertension and hypercholesterolemia. With regard to glycemic control, only 28.3% reached the target level of <6.5%. Moreover, only 11.5% of subjects with diabetes met all three targets of glycosylated hemoglobin, blood pressure, and LDL-C. The percentage of energy intake from carbohydrates was higher in diabetes patients than in those without diabetes, while that from protein and fat was lower in subjects with diabetes. CONCLUSION: The high prevalence and low control rate of diabetes and its comorbidities in Korean adults were confirmed. More stringent efforts are needed to improve the comprehensive management of diabetes to reduce diabetes-related morbidity and mortality.
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Wang, L., Peng, W., Zhao, Z., Zhang, M., Shi, Z., Song, Z., Zhang, X., Li, C., Huang, Z., Sun, X., et al. (2021) · JAMA · doi:10.1001/jama.2021.22208 · Cited by 961
Prediction of Type 2 Diabetes Based on Machine Learning Algorithm
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Present and Future of Digital Health in Diabetes and Metabolic Disease
Rhee, S. Y., Kim, C., Shin, D. W., & Steinhubl, S. R. (2020) · Diabetes & Metabolism Journal · doi:10.4093/dmj.2020.0088 · Cited by 47
Development of various diabetes prediction models using machine learning techniques
Shin, J., Kim, J., Lee, C., Yoon, J. Y., Kim, S., Song, S., & Kim, H.-S. (2022) · Diabetes & Metabolism Journal · doi:10.4093/dmj.2021.0115 · Cited by 29
Self-citation
Metadata
- Authors
- Won, J. C., Lee, J. H., Kim, J. H., Kang, E. S., Won, K. C., Kim, D. J., & Lee, M.-K.
- Venue
- Diabetes & Metabolism Journal
- Publisher
- Korean Diabetes Association
- Published
- 2018
- Volume
- 42
- Issue
- 5
- Pages
- 415
- ISSN
- 2233-6079 (ISSN-L)
- 2233-6087
- OpenAlex
- W2887288752
- Cited by
- 299
- References
- 76
- FWCI
- 26.78
- Type
- journal article
- Language
- en
- Open access
- gold
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