Endocrinol Metab.  2024 Oct;39(5):711-721. 10.3803/EnM.2024.1986.

Insulin Resistance and Impaired Insulin Secretion Predict Incident Diabetes: A Statistical Matching Application to the Two Korean Nationwide, Population-Representative Cohorts

• Jo H
• Ahn S
• Ohn JH
• Shin CM
• Ji E
• Kim D
• Jung SJ
• Lee J

• KMID: 2560280
• DOI: http://doi.org/10.3803/EnM.2024.1986

Abstract

Background
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.

Keyword

Diabetes; Insulin resistance; Synthetic data; Statistical matching

Figure

• 

  Fig. 1. Flow chart of the study. This figure illustrates the matching process between the National Health Interview Survey (NHIS) data and the synthetic data generated from the Korea National Health and Nutrition Examination Survey (KNHANES). Initially, 10 synthetic datasets (m1, ..., m10) were created from the KNHANES data. Subsequently, each of these synthetic datasets was matched with the NHIS source data, resulting in the 10 matched datasets (M1, ..., M10). Specifically, a statistically matched dataset (M10) was incorporated by linking KNHANES synthetic data (m10) with the National Health Insurance Service-National Health Screening Cohort (NHIS-HEALS) dataset. In total, 24,617 individuals from the m10 dataset, which includes 2,512, 5,919, 6,542, and 4,421 participants in the years 2007, 2008, 2009, 2010, and 2015, respectively, and 514,866 individuals from NHIS-HEALS, including 186,980, 227,656, 223,551, 226,276, and 217,477 examinees in 2007, 2008, 2009, 2010, and 2015, respectively, were linked using statistical matching method. The participants in the same year of NHIS-HEALS and KNHANES were matched to ensure high-quality matching. As NHIS data includes tests that patients can undergo annually, duplication of the data may occur; thus, the previous year’s NHIS-KNHANES matched data were removed before the corresponding year’s matching. Using the same method above, M1–M9 were constructed by concatenating the KNHANES synthetic datasets m1–m9 and the NHIS-HEALS dataset, respectively—diabetes mellitus (DM) and fasting blood glucose (FBS). HOMA-IR, homeostasis model assessment of insulin resistance; HOMA-β, homeostasis model assessment of -βcell function. aExclusion criteria: (1) missing values, (2) previous DM history (questionnaire, FBS ≥126 mg/dL), (3) medical beneficiaries, (4) age <80 years; bExclusion criteria: (1) missing values, (2) previous DM history (questionnaire, FBS ≥126 mg/dL), (3) age <40 years.

• 

  Fig. 2. Kaplan-Meier curve of the risk for diabetes according to homeostasis model assessment of insulin resistance (HOMA-IR) and homeostasis model assessment of β-cell function (HOMA-β) statuses (representative matched dataset of Korea National Health and Nutrition Examination Survey synthetic dataset m10 and National Health Insurance Service-National Health Screening Cohort [NHIS-HEALS] dataset, M10).

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  Fig. 3. Forrest plot of the risk of diabetes according to the baseline homeostasis model assessment of insulin resistance (HOMA-IR) and homeostasis model assessment of β-cell function (HOMA-β) status (matched dataset of Korea National Health and Nutrition Examination Survey synthetic dataset m1–m10 and National Health Insurance Service-National Health Screening Cohort [NHIS-HEALS] dataset: M1–M10). Adjusted hazard ratios (HRs) of the low–HOMA-IR/low–HOMA-β group (orange), the high–HOMA-IR/high–HOMA-β group (green), and the high–HOMA-IR/low–HOMA-β group (blue) were calculated using the low–HOMA-IR/high–HOMA-β group as a reference.

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