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HOME > Endocrinol Metab > Volume 39(5); 2024 > Article
Editorial
Diabetes, obesity and metabolism Combining Nationwide Cohorts to Unveil the Predictive Role of Insulin Resistance and Impaired Insulin Secretion in Diabetes
Bukyung Kimorcid
Endocrinology and Metabolism 2024;39(5):699-700.
DOI: https://doi.org/10.3803/EnM.2024.2189
Published online: October 23, 2024

Division of Endocrinology and Metabolism, Department of Internal Medicine, Kosin University College of Medicine, Busan, Korea

Corresponding author: Bukyung Kim. Division of Endocrinology and Metabolism, Department of Internal Medicine, Kosin University College of Medicine, 262 Gamcheon-ro, Seo-gu, Busan 49267, Korea Tel: +82-51-990-6102, Fax: +82-51-248-5686, E-mail: 79kyung@daum.net
• Received: October 6, 2024   • Accepted: October 13, 2024

Copyright © 2024 Korean Endocrine Society

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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See the Original "Insulin Resistance and Impaired Insulin Secretion Predict Incident Diabetes: A Statistical Matching Application to the Two Korean Nationwide, Population-Representative Cohorts" on page 711.
Type 2 diabetes is a progressive disease characterized by increasing insulin resistance over an extended period before the condition is formally diagnosed. To compensate for this resistance, the beta cells in the pancreas produce additional insulin. However, these cells eventually cannot maintain this increased output, leading to a gradual decline in their function. It is at this stage, when the beta cells start to fail, that blood glucose levels begin to rise, culminating in the onset of diabetes. This highlights the critical balance between insulin secretion and resistance, the disruption of which leads to the development of the disease [1,2].
The paper entitled “Insulin resistance and impaired insulin secretion predict incident diabetes: a statistical matching application to the two Korean nationwide, population-representative cohorts” provides a comprehensive analysis of how insulin resistance and impaired insulin secretion serve as meaningful predictors of diabetes in the Korean population [3].
This paper has significant value from two major perspectives.
First, it demonstrates that future diabetes onset can be predicted using homeostasis model assessment of insulin resistance and homeostasis model assessment of β-cell function values, which are easily measurable in a clinical setting. While various methods exist to assess insulin resistance, practical options suitable for real-world clinical practice are limited. This study aligns with the conclusions of previous cohort studies, thereby reinforcing its validity [4-6]. Therefore, the research highlights the importance of early prevention and management strategies for high-risk groups, particularly those exhibiting both insulin resistance and impaired β-cell function. These findings can inform public health policies in Korea and other similar populations, ultimately enhancing the effectiveness of diabetes prevention efforts. Further research is necessary to determine the exact cutoff values for clinical application.
Second, this study introduced a methodological innovation. The key innovation of this study is the use of statistical matching to combine cross-sectional data from Korea National Health and Nutrition Examination Survey (KNHANES) with longitudinal data from National Health Insurance Service-National Health Screening Cohort (NHIS-HEALS). This approach overcame the limitations posed by strict privacy regulations that prohibit the direct linkage of these datasets. The researchers generated synthetic data from KNHANES and used statistical techniques to match it with NHIS-HEALS, thereby creating a new cohort. This methodological approach is particularly significant because it demonstrates that large-scale national health data can be utilized in a way that ensures privacy protection while still producing meaningful and robust results. Cohort studies are considered the most reliable method for determining causal relationships between exposure factors and the onset of disease. However, conducting cohort studies is challenging due to the immense time and cost involved in obtaining results from the start of the study until its completion. This study successfully combined two large population-representative datasets from Korea—KNHANES and NHIS-HEALS—using statistical matching techniques. In this aspect, this study could be a crucial milestone, demonstrating the potential to use this method to present results from various cohort studies in the future.
In conclusion, this paper introduces a groundbreaking approach to diabetes research within the Korean population, employing statistical matching and synthetic data to navigate privacy constraints and investigate the relationship between insulin resistance and β-cell dysfunction in the onset of diabetes. This innovative methodology not only deepens our understanding of diabetes risk in Korea but also provides a robust framework for future large-scale health data research. It sets a new standard for addressing privacy challenges while ensuring scientifically rigorous results.

CONFLICTS OF INTEREST

No potential conflict of interest relevant to this article was reported.

  • 1. Adams LA, Waters OR, Knuiman MW, Elliott RR, Olynyk JK. NAFLD as a risk factor for the development of diabetes and the metabolic syndrome: an eleven-year follow-up study. Am J Gastroenterol 2009;104:861–7.ArticlePubMed
  • 2. Kahn SE, Cooper ME, Del Prato S. Pathophysiology and treatment of type 2 diabetes: perspectives on the past, present, and future. Lancet 2014;383:1068–83.ArticlePubMed
  • 3. Jo H, Ahn S, Ohn JH, Shin CM, Ji E, Kim D, et al. Insulin resistance and impaired insulin secretion predict incident diabetes: a statistical matching application to the two Korean nationwide, population-representative cohorts. Endocrinol Metab (Seoul) 2024;39:711–21.ArticlePubMedPMCPDF
  • 4. Wang T, Lu J, Shi L, Chen G, Xu M, Xu Y, et al. Association of insulin resistance and β-cell dysfunction with incident diabetes among adults in China: a nationwide, population-based, prospective cohort study. Lancet Diabetes Endocrinol 2020;8:115–24.ArticlePubMed
  • 5. Morimoto A, Tatsumi Y, Deura K, Mizuno S, Ohno Y, Miyamatsu N, et al. Impact of impaired insulin secretion and insulin resistance on the incidence of type 2 diabetes mellitus in a Japanese population: the Saku study. Diabetologia 2013;56:1671–9.ArticlePubMedPDF
  • 6. Yabe D, Seino Y. Type 2 diabetes via β-cell dysfunction in east Asian people. Lancet Diabetes Endocrinol 2016;4:2–3.ArticlePubMed

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      Combining Nationwide Cohorts to Unveil the Predictive Role of Insulin Resistance and Impaired Insulin Secretion in Diabetes
      Combining Nationwide Cohorts to Unveil the Predictive Role of Insulin Resistance and Impaired Insulin Secretion in Diabetes
      Endocrinol Metab : Endocrinology and Metabolism
      © Korean Endocrine Society.
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