The Committee of Clinical Practice Guidelines of the Korean Diabetes Association revised and updated the 6th Clinical Practice Guidelines in 2019. Targets of glycemic, blood pressure, and lipid control in type 2 diabetes mellitus (T2DM) were updated. The obese and overweight population is increasing steadily in Korea, and half of the Koreans with diabetes are obese. Evidence-based recommendations for weight-loss therapy for obesity management as treatment for hyperglycemia in T2DM were provided. In addition, evidence from large clinical studies assessing cardiovascular outcomes following the use of sodium-glucose cotransporter-2 inhibitors and glucagon-like peptide 1 receptor agonists in patients with T2DM were incorporated into the recommendations.

Recently, medical research using big data has become very popular, and its value has become increasingly recognized. The Korean National Health Information Database (NHID) is representative of big data that combines information obtained from the National Health Insurance Service collected for claims and reimbursement of health care services and results obtained from general health examinations provided to all Korean adults. This database has several strengths and limitations. Given the large size, various laboratory data, and questionnaires obtained from medical check-ups, their longitudinal nature, and long-term accumulation of data since 2002, carefully designed studies may provide valuable information that is difficult to obtain from other forms of research. However, consideration of possible bias and careful interpretation when defining causal relationships is also important because the data were not collected for research purposes. After the NHID became publicly available, research and publications based on this database have increased explosively, especially in the field of diabetes and metabolism. This article reviews the history, structure, and characteristics of the Korean NHID. Recent trends in big data research using this database, commonly used operational diagnosis, and representative studies have been introduced. We expect further progress and expansion of big data research using the Korean NHID.

Blood pressure (BP) is directly and causally associated with body size in the general population. Whether muscle mass is an important factor that determines BP remains unclear. To investigate whether sarcopenia is associated with hypertension in older Koreans. We surveyed 2,099 males and 2,747 females aged 60 years or older. Sarcopenia was defined as an appendicular skeletal muscle mass divided by body weight (ASM/Wt) that was <1 SD below the gender-specific mean for young adults. Obesity was defined as a body mass index (BMI) ≥25 kg/m². Subjects were divided into four groups based on presence or absence of obesity or sarcopenia. Hypertension was defined as a systolic BP (SBP) ≥140 mmHg, a diastolic BP (DBP) ≥90 mmHg, or a self-reported current use of antihypertensive medications. The overall prevalence of hypertension in the four groups was as follows 49.7% for non-obese non-sarcopenia, 60.9% for non-obese sarcopenia, 66.2% for obese non-sarcopenia and 74.7% for obese sarcopenia. After adjustment for age, gender, regular activity, current smoking and alcohol use, the odds ratio (OR) for having hypertension was 1.5 (95% confidence interval (CI) = 1.23–1.84) in subjects in the non-obese sarcopenia group, 2.08 (95% CI = 1.68–2.57) in the obese non-sarcopenia group and 3.0 (95% CI = 2.48–3.63) in the obese sarcopenia group, compared with the non-obese non-sarcopenia group (p for trend <0.001). Controlling further for body weight and waist circumference did not change the association between hypertension and sarcopenia. The association between sarcopenia and hypertension was more robust in the subjects with diabetes mellitus. Body composition beyond BMI has a considerable impact on hypertension in elderly Koreans. Subjects with sarcopenic obesity appear to have a greater risk of hypertension than simply obese or sarcopenia subjects.

There is growing evidence that patients with type 2 diabetes mellitus (DM) have an increased risk of developing Parkinson’s disease (PD) and share similar dysregulated pathways. We aimed to determine whether the risk of PD increases as diabetes progresses among patients with type 2 DM. Using a nationally representative database from the Korean National Health Insurance System, 2,362,072 individuals (≥40 years of age) with type 2 DM who underwent regular health checkups during 2009–2012 were followed up until the end of 2018. The diabetes severity score parameters included the number of oral hypoglycemic agents, diabetes duration, insulin use, or presence of chronic kidney disease, diabetic retinopathy, or cardiovascular disease. Each of these characteristics was scored as one unit of diabetes severity and their sum was defined as a diabetes severity score from 0–6. We identified 17,046 incident PD cases during the follow-up. Each component of the diabetes severity score showed a similar intensity for the risk of PD. Compared with subjects with no parameters, HR values (95% confidence intervals) of PD were 1.09 (1.04–1.15) in subjects with one diabetes severity score parameter, 1.28 (1.22–1.35) in subjects with two parameters, 1.55 (1.46–1.65) in subjects with three parameters, 1.96 (1.82–2.11) in subjects with four parameters, 2.08 (1.83–2.36) in subjects with five parameters, and 2.78 (2.05–3.79) in subjects with six parameters. Diabetes severity was associated with an increased risk of developing PD. Severe diabetes may be a risk factor for the development of PD.

The Korean National Health Information Database (NHID) contains big data combining information obtained from the National Health Insurance Service and health examinations. Data are provided in the form of a cohort, and the NHID can be used to conduct longitudinal studies and research on rare diseases. Moreover, data on the cause and date of death are provided by Statistics Korea. Research and publications based on the NHID have increased explosively in the field of endocrine disorders. However, because the data were not collected for research purposes, studies using the NHID have limitations, particularly the need for the operational definition of diseases. In this review, we describe the characteristics of the Korean NHID, operational definitions of endocrine diseases used for research, and an overview of recent studies in endocrinology using the Korean NHID.

Variability in biological parameters has been reported to be associated with adverse health outcomes. We aimed to investigate the composite effect of the visit-to-visit variability in blood pressure, glucose, cholesterol, and body mass index on the risk of dementia. A population-based cohort study including 2,930,816 subjects without a history of dementia, hypertension, diabetes mellitus, and dyslipidemia who underwent ≥ 3 health examinations was performed. The coefficient of variation (CV), standard deviation, and variability independent of the mean were calculated as variability indices. High variability was defined as having values in the highest quartile for each parameter. A total of 32,901 (1.12%) participants developed dementia, of which 74.4% and 11.0% were attributable to Alzheimer’s disease and vascular dementia, respectively, during the median follow-up of 5.5 years. Individuals with higher variability of each parameter were at higher risk of future dementia. In the multivariable adjusted model, the hazard ratios and 95% confidence intervals of all-cause dementia were 1.22 (1.19–1.26) for one parameter, 1.39 (1.35–1.43) for two parameters, 1.54 (1.48–1.60) for three parameters, and 1.73 (1.60–1.88) for four parameters compared with subjects having no parameters of high variability measured as the CV. Consistent results were noted for Alzheimer’s disease and vascular dementia, using other indices of variability and in various sensitivity and subgroup analyses. There was a linear association between the number of high variability parameters and risk of dementia. Reducing variability of metabolic parameters would be a target to preserve cognitive reserve in the general population.