Insulin Resistance and Impaired Insulin Secretion Predict Incident Diabetes: A Statistical Matching Application to the Two Korean Nationwide, Population-Representative Cohorts.
Hyemin Jo, Soyeon Ahn, Jung Hun Ohn, Cheol Min Shin, Eunjeong Ji, Donggil Kim, Sung Jae Jung, Joongyub Lee
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引用次数: 0
Abstract
Backgruound: To evaluate whether insulin resistance and impaired insulin secretion are useful predictors of incident diabetes in Koreans using nationwide population-representative data to enhance data privacy.
Methods: This study analyzed the data of individuals without diabetes aged >40 years from the Korea National Health and Nutrition Examination Survey (KNHANES) 2007-2010 and 2015 and the National Health Insurance Service-National Health Screening Cohort (NHIS-HEALS). Owing to privacy concerns, these databases cannot be linked using direct identifiers. Therefore, we generated 10 synthetic datasets, followed by statistical matching with the NHIS-HEALS. Homeostasis model assessment of insulin resistance (HOMA-IR) and homeostasis model assessment of β-cell function (HOMA-β) were used as indicators of insulin resistance and insulin secretory function, respectively, and diabetes onset was captured in NHIS-HEALS.
Results: A median of 4,580 (range, 4,463 to 4,761) adults were included in the analyses after statistical matching of 10 synthetic KNHANES and NHIS-HEALS datasets. During a mean follow-up duration of 5.8 years, a median of 4.7% (range, 4.3% to 5.0%) of the participants developed diabetes. Compared to the reference low-HOMA-IR/high-HOMA-β group, the high-HOMA-IR/low- HOMA-β group had the highest risk of diabetes, followed by high-HOMA-IR/high-HOMA-β group and low-HOMA-IR/low- HOMA-β group (median adjusted hazard ratio [ranges]: 3.36 [1.86 to 6.05], 1.81 [1.01 to 3.22], and 1.68 [0.93 to 3.04], respectively).
Conclusion: Insulin resistance and impaired insulin secretion are robust predictors of diabetes in the Korean population. A retrospective cohort constructed by combining cross-sectional synthetic and longitudinal claims-based cohort data through statistical matching may be a reliable resource for studying the natural history of diabetes.
期刊介绍:
The aim of this journal is to set high standards of medical care by providing a forum for discussion for basic, clinical, and translational researchers and clinicians on new findings in the fields of endocrinology and metabolism. Endocrinology and Metabolism reports new findings and developments in all aspects of endocrinology and metabolism. The topics covered by this journal include bone and mineral metabolism, cytokines, developmental endocrinology, diagnostic endocrinology, endocrine research, dyslipidemia, endocrine regulation, genetic endocrinology, growth factors, hormone receptors, hormone action and regulation, management of endocrine diseases, clinical trials, epidemiology, molecular endocrinology, neuroendocrinology, neuropeptides, neurotransmitters, obesity, pediatric endocrinology, reproductive endocrinology, signal transduction, the anatomy and physiology of endocrine organs (i.e., the pituitary, thyroid, parathyroid, and adrenal glands, and the gonads), and endocrine diseases (diabetes, nutrition, osteoporosis, etc.).