The Korean National Health Information Database (NHID), which contains nationwide real-world claims data including sociodemographic data, health care utilization data, health screening data, and healthcare provider information, is a powerful resource to test various hypotheses. It is also longitudinal in nature due to the recommended health checkup every 2 years and is appropriate for long-term follow-up study as well as evaluating the relationships between health outcomes and changes in parameters such as lifestyle factors, anthropometric measurements, and laboratory results. However, because these data are not collected for research purposes, precise operational definitions of diseases are required to facilitate big data analysis using the Korean NHID. In this review, we describe the characteristics of the Korean NHID, operational definitions of diseases used for research related to diabetes, and introduce representative research for diabetes-related diseases using the Korean NHID.

The Korean National Health Information Database (NHID), which contains nationwide real-world claims data including sociodemographic data, health care utilization data, health screening data, and healthcare provider information, is a powerful resource to test various hypotheses. It is also longitudinal in nature due to the recommended health checkup every 2 years and is appropriate for long-term follow-up study as well as evaluating the relationships between health outcomes and changes in parameters such as lifestyle factors, anthropometric measurements, and laboratory results. However, because these data are not collected for research purposes, precise operational definitions of diseases are required to facilitate big data analysis using the Korean NHID. In this review, we describe the characteristics of the Korean NHID, operational definitions of diseases used for research related to diabetes, and introduce representative research for diabetes-related diseases using the Korean NHID.

The Korean National Health Information Database (NHID), which contains nationwide real-world claims data including sociodemographic data, health care utilization data, health screening data, and healthcare provider information, is a powerful resource to test various hypotheses. It is also longitudinal in nature due to the recommended health checkup every 2 years and is appropriate for long-term follow-up study as well as evaluating the relationships between health outcomes and changes in parameters such as lifestyle factors, anthropometric measurements, and laboratory results. However, because these data are not collected for research purposes, precise operational definitions of diseases are required to facilitate big data analysis using the Korean NHID. In this review, we describe the characteristics of the Korean NHID, operational definitions of diseases used for research related to diabetes, and introduce representative research for diabetes-related diseases using the Korean NHID.

The Korean National Health Information Database (NHID), which contains nationwide real-world claims data including sociodemographic data, health care utilization data, health screening data, and healthcare provider information, is a powerful resource to test various hypotheses. It is also longitudinal in nature due to the recommended health checkup every 2 years and is appropriate for long-term follow-up study as well as evaluating the relationships between health outcomes and changes in parameters such as lifestyle factors, anthropometric measurements, and laboratory results. However, because these data are not collected for research purposes, precise operational definitions of diseases are required to facilitate big data analysis using the Korean NHID. In this review, we describe the characteristics of the Korean NHID, operational definitions of diseases used for research related to diabetes, and introduce representative research for diabetes-related diseases using the Korean NHID.

OBJECTIVES: We aimed to evaluate the association between early-life weight status and urinary tract infection (UTI) risk in children. METHODS: A nationwide study was conducted using Korean National Health Screening (NHS) data and National Health Insurance Service data. A sample cohort was selected using data from the 2014 and 2015 NHS for infants and children (4-71 months) and followed up until the end of 2017. Participants were divided into 4 groups (underweight, normal weight, overweight, and obese) based on the weight-for-age (< 2 years) or body mass index (≥ 2 years). Hazard ratios (HRs) with 95% confidence intervals (CIs) for developing UTIs, cystitis, and acute pyelonephritis (APN) were calculated using a Cox proportional hazard model. RESULTS: Of 1,653,106 enrolled children, 120,142 (7.3%) developed UTIs, cystitis, and APN during follow-up. The underweight, overweight, and obese groups had higher risks of UTIs than the reference group after adjusting for age, sex, birth weight, and preterm birth. Between 2 years and 6 years of age, boys with underweight had a high risk of UTI and APN, while girls with overweight and obesity revealed elevated risks of UTIs, cystitis, and APN. The HRs for APN in boys with underweight and in girls with obesity were 1.46 (95% CI, 1.03 to 2.07) and 1.41 (95% CI, 1.13 to 1.75), respectively, after adjusting for age, sex, birth weight, and preterm birth. The incidence of APN did not decrease with age in underweight and obese children aged 2-6 years. CONCLUSIONS Children with underweight, overweight, and obesity may be at high risk for UTIs.

OBJECTIVES: We aimed to evaluate the association between early-life weight status and urinary tract infection (UTI) risk in children. METHODS: A nationwide study was conducted using Korean National Health Screening (NHS) data and National Health Insurance Service data. A sample cohort was selected using data from the 2014 and 2015 NHS for infants and children (4-71 months) and followed up until the end of 2017. Participants were divided into 4 groups (underweight, normal weight, overweight, and obese) based on the weight-for-age (< 2 years) or body mass index (≥ 2 years). Hazard ratios (HRs) with 95% confidence intervals (CIs) for developing UTIs, cystitis, and acute pyelonephritis (APN) were calculated using a Cox proportional hazard model. RESULTS: Of 1,653,106 enrolled children, 120,142 (7.3%) developed UTIs, cystitis, and APN during follow-up. The underweight, overweight, and obese groups had higher risks of UTIs than the reference group after adjusting for age, sex, birth weight, and preterm birth. Between 2 years and 6 years of age, boys with underweight had a high risk of UTI and APN, while girls with overweight and obesity revealed elevated risks of UTIs, cystitis, and APN. The HRs for APN in boys with underweight and in girls with obesity were 1.46 (95% CI, 1.03 to 2.07) and 1.41 (95% CI, 1.13 to 1.75), respectively, after adjusting for age, sex, birth weight, and preterm birth. The incidence of APN did not decrease with age in underweight and obese children aged 2-6 years. CONCLUSIONS Children with underweight, overweight, and obesity may be at high risk for UTIs.

Objective: We compared the effects of high-intensity statin monotherapy versus moderateintensity statin and ezetimibe combination therapy on major adverse cardiovascular events (MACE) in patients with acute myocardial infarction (AMI). Methods: Using the Korean National Health Insurance Service database, we screened 82,941 patients with AMI who underwent percutaneous coronary intervention (PCI) between 2013 and 2016. Among them, we identified 9,908 patients treated with atorvastatin 40 mg (A40, n=4,041), atorvastatin 20 mg + ezetimibe 10 mg (A20+E10, n=233), rosuvastatin 20 mg (R20, n=5,251), or rosuvastatin 10 mg + ezetimibe 10 mg (R10+E10, n=383). The primary outcome was MACE, a composite of all-cause death, non-fatal myocardial infarction undergoing PCI, repeat revascularization, and ischemic stroke. Multivariable analyses were performed using the inverse probability of treatment weighting method. Results: The incidence rate of MACE in the overall population was 42.97 cases per 1,000 person-years. There was no significant difference in the risk of composite outcomes of MACE between the groups. However, the R10+E10 group showed a higher risk of all-cause death (hazard ratio, 2.07; 95% confidence interval, 1.08–3.94) than the A40 group (reference group) in the weighted multivariable model. Conclusions In this study, there was no significant difference in the composite outcome of MACE between high-intensity statin monotherapy and moderate-intensity statin and ezetimibe combination therapy.

Background/Aims: This study aimed to evaluate the impact of steatotic liver disease severity on the cumulative incidence of lung cancer utilizing data from the Korea National Health Insurance Service (NHIS). Methods: This study examined the risk of lung cancer in the general population in conjunction with the incidence of steatotic liver disease. The study population consisted of 3,261,438 individuals aged 20 years or older who underwent a general health examination in 2009. Results: Individuals with fatty liver index (FLI) of 30–59 exhibited a 1.08-fold increased risk of lung cancer (95% CI: 1.04–1.11), while FLI ≥ 60 was associated with a 1.22-fold elevated risk of lung cancer (95% CI: 1.17–1.28) compared to those with FLI < 30. The risk varied with smoking status; in current smokers, the adjusted HR for the FLI 30–59 group was 1.05 (95% CI: 1.00–1.10), while that in the FLI ≥ 60 group was 1.11 (95% CI: 1.04–1.18). In never- or past-smokers, the adjusted HR for the FLI 30–59 group was 1.10, and that for the FLI ≥ 60 group was 1.31. Subgroup analysis revealed an incidence rate of 1.06 per 1,000 person-years in the consistently high FLI group compared to 1.15 in those with improved FLI. Improving FLI over time was associated with a 0.93-fold decrease in lung cancer risk. Conclusions Our study demonstrated a correlational relationship between lung cancer incidence and the severity of steatotic liver disease as measured by FLI.

Background/Aims: This study aimed to evaluate the impact of steatotic liver disease severity on the cumulative incidence of lung cancer utilizing data from the Korea National Health Insurance Service (NHIS). Methods: This study examined the risk of lung cancer in the general population in conjunction with the incidence of steatotic liver disease. The study population consisted of 3,261,438 individuals aged 20 years or older who underwent a general health examination in 2009. Results: Individuals with fatty liver index (FLI) of 30–59 exhibited a 1.08-fold increased risk of lung cancer (95% CI: 1.04–1.11), while FLI ≥ 60 was associated with a 1.22-fold elevated risk of lung cancer (95% CI: 1.17–1.28) compared to those with FLI < 30. The risk varied with smoking status; in current smokers, the adjusted HR for the FLI 30–59 group was 1.05 (95% CI: 1.00–1.10), while that in the FLI ≥ 60 group was 1.11 (95% CI: 1.04–1.18). In never- or past-smokers, the adjusted HR for the FLI 30–59 group was 1.10, and that for the FLI ≥ 60 group was 1.31. Subgroup analysis revealed an incidence rate of 1.06 per 1,000 person-years in the consistently high FLI group compared to 1.15 in those with improved FLI. Improving FLI over time was associated with a 0.93-fold decrease in lung cancer risk. Conclusions Our study demonstrated a correlational relationship between lung cancer incidence and the severity of steatotic liver disease as measured by FLI.

Background/Aims: This study aimed to evaluate the impact of steatotic liver disease severity on the cumulative incidence of lung cancer utilizing data from the Korea National Health Insurance Service (NHIS). Methods: This study examined the risk of lung cancer in the general population in conjunction with the incidence of steatotic liver disease. The study population consisted of 3,261,438 individuals aged 20 years or older who underwent a general health examination in 2009. Results: Individuals with fatty liver index (FLI) of 30–59 exhibited a 1.08-fold increased risk of lung cancer (95% CI: 1.04–1.11), while FLI ≥ 60 was associated with a 1.22-fold elevated risk of lung cancer (95% CI: 1.17–1.28) compared to those with FLI < 30. The risk varied with smoking status; in current smokers, the adjusted HR for the FLI 30–59 group was 1.05 (95% CI: 1.00–1.10), while that in the FLI ≥ 60 group was 1.11 (95% CI: 1.04–1.18). In never- or past-smokers, the adjusted HR for the FLI 30–59 group was 1.10, and that for the FLI ≥ 60 group was 1.31. Subgroup analysis revealed an incidence rate of 1.06 per 1,000 person-years in the consistently high FLI group compared to 1.15 in those with improved FLI. Improving FLI over time was associated with a 0.93-fold decrease in lung cancer risk. Conclusions Our study demonstrated a correlational relationship between lung cancer incidence and the severity of steatotic liver disease as measured by FLI.