This review examines the challenges associated with occupational disease surveillance in Korea, particularly emphasizing the limitations of current data sources such as the Industrial Accident Compensation Insurance (IACI) statistics and special health examinations. The IACI system undercounts cases due to its emphasis on severe diseases and restrictions on approvals. Special health examinations, although they cover a broad workforce, are constrained by their annual scheduling, which leads to missed acute illnesses and subclinical conditions. The paper also explores the history of occupational disease surveillance in Korea, highlighting the fragmented and disease-specific approach of earlier systems. The authors introduce the newly established Korea Occupational Disease Surveillance Center (KODSC), a comprehensive nationwide system designed to gather, analyze, and interpret data on occupational diseases through a network of regional centers. By incorporating hospital-based surveillance and focusing on acute poisonings and other sentinel events, the KODSC aims to overcome the limitations of previous systems and promote collaboration with various agencies. Although it is still in the early stages of implementation, the KODSC demonstrates potential for improving data accuracy and contributing valuable insights for public health policy.

This review examines the challenges associated with occupational disease surveillance in Korea, particularly emphasizing the limitations of current data sources such as the Industrial Accident Compensation Insurance (IACI) statistics and special health examinations. The IACI system undercounts cases due to its emphasis on severe diseases and restrictions on approvals. Special health examinations, although they cover a broad workforce, are constrained by their annual scheduling, which leads to missed acute illnesses and subclinical conditions. The paper also explores the history of occupational disease surveillance in Korea, highlighting the fragmented and disease-specific approach of earlier systems. The authors introduce the newly established Korea Occupational Disease Surveillance Center (KODSC), a comprehensive nationwide system designed to gather, analyze, and interpret data on occupational diseases through a network of regional centers. By incorporating hospital-based surveillance and focusing on acute poisonings and other sentinel events, the KODSC aims to overcome the limitations of previous systems and promote collaboration with various agencies. Although it is still in the early stages of implementation, the KODSC demonstrates potential for improving data accuracy and contributing valuable insights for public health policy.

Background: Gestational diabetes mellitus (GDM) affects women with diverse pathological phenotypes, but little is known about the effects of this variation on perinatal outcomes. We explored the metabolic phenotypes of GDM and their impact on adverse pregnancy outcomes. Methods: Women diagnosed with gestational glucose intolerance or GDM were categorized into subgroups according to their prepregnancy body mass index (BMI) and the median values of the gestational Matsuda and Stumvoll indices. Logistic regression analysis was employed to assess the odds of adverse pregnancy outcomes, such as large-for-gestational age (LGA), small-for-gestational age, preterm birth, low Apgar score, and cesarean section. Results: A total of 309 women were included, with a median age of 31 years and a median BMI of 22.3 kg/m2. Women with a higher pre-pregnancy BMI had a higher risk of LGA newborns (adjusted odds ratio [aOR] for pre-pregnancy BMI ≥25 kg/m2 compared to 20–23 kg/m2, 4.26; 95% confidence interval [CI], 1.99 to 9.12; P<0.001; P for trend=0.001), but the risk of other adverse pregnancy outcomes did not differ according to pre-pregnancy BMI. Women with insulin resistance had a higher risk of LGA (aOR, 1.88; 95% CI, 1.02 to 3.47; P=0.043) and cesarean section (aOR, 2.12; 95% CI, 1.29 to 3.50; P=0.003) than women in the insulin-sensitive group. In contrast, defective β-cell function did not affect adverse pregnancy outcomes. Conclusion Different metabolic phenotypes of GDM were associated with heterogeneous pregnancy outcomes. Women with obesity and those with insulin resistance are at greater risk of adverse outcomes and might need strict glycemic management during pregnancy.

Background: Gestational diabetes mellitus (GDM) affects women with diverse pathological phenotypes, but little is known about the effects of this variation on perinatal outcomes. We explored the metabolic phenotypes of GDM and their impact on adverse pregnancy outcomes. Methods: Women diagnosed with gestational glucose intolerance or GDM were categorized into subgroups according to their prepregnancy body mass index (BMI) and the median values of the gestational Matsuda and Stumvoll indices. Logistic regression analysis was employed to assess the odds of adverse pregnancy outcomes, such as large-for-gestational age (LGA), small-for-gestational age, preterm birth, low Apgar score, and cesarean section. Results: A total of 309 women were included, with a median age of 31 years and a median BMI of 22.3 kg/m2. Women with a higher pre-pregnancy BMI had a higher risk of LGA newborns (adjusted odds ratio [aOR] for pre-pregnancy BMI ≥25 kg/m2 compared to 20–23 kg/m2, 4.26; 95% confidence interval [CI], 1.99 to 9.12; P<0.001; P for trend=0.001), but the risk of other adverse pregnancy outcomes did not differ according to pre-pregnancy BMI. Women with insulin resistance had a higher risk of LGA (aOR, 1.88; 95% CI, 1.02 to 3.47; P=0.043) and cesarean section (aOR, 2.12; 95% CI, 1.29 to 3.50; P=0.003) than women in the insulin-sensitive group. In contrast, defective β-cell function did not affect adverse pregnancy outcomes. Conclusion Different metabolic phenotypes of GDM were associated with heterogeneous pregnancy outcomes. Women with obesity and those with insulin resistance are at greater risk of adverse outcomes and might need strict glycemic management during pregnancy.

This review examines the challenges associated with occupational disease surveillance in Korea, particularly emphasizing the limitations of current data sources such as the Industrial Accident Compensation Insurance (IACI) statistics and special health examinations. The IACI system undercounts cases due to its emphasis on severe diseases and restrictions on approvals. Special health examinations, although they cover a broad workforce, are constrained by their annual scheduling, which leads to missed acute illnesses and subclinical conditions. The paper also explores the history of occupational disease surveillance in Korea, highlighting the fragmented and disease-specific approach of earlier systems. The authors introduce the newly established Korea Occupational Disease Surveillance Center (KODSC), a comprehensive nationwide system designed to gather, analyze, and interpret data on occupational diseases through a network of regional centers. By incorporating hospital-based surveillance and focusing on acute poisonings and other sentinel events, the KODSC aims to overcome the limitations of previous systems and promote collaboration with various agencies. Although it is still in the early stages of implementation, the KODSC demonstrates potential for improving data accuracy and contributing valuable insights for public health policy.

This review examines the challenges associated with occupational disease surveillance in Korea, particularly emphasizing the limitations of current data sources such as the Industrial Accident Compensation Insurance (IACI) statistics and special health examinations. The IACI system undercounts cases due to its emphasis on severe diseases and restrictions on approvals. Special health examinations, although they cover a broad workforce, are constrained by their annual scheduling, which leads to missed acute illnesses and subclinical conditions. The paper also explores the history of occupational disease surveillance in Korea, highlighting the fragmented and disease-specific approach of earlier systems. The authors introduce the newly established Korea Occupational Disease Surveillance Center (KODSC), a comprehensive nationwide system designed to gather, analyze, and interpret data on occupational diseases through a network of regional centers. By incorporating hospital-based surveillance and focusing on acute poisonings and other sentinel events, the KODSC aims to overcome the limitations of previous systems and promote collaboration with various agencies. Although it is still in the early stages of implementation, the KODSC demonstrates potential for improving data accuracy and contributing valuable insights for public health policy.

Background: Gestational diabetes mellitus (GDM) affects women with diverse pathological phenotypes, but little is known about the effects of this variation on perinatal outcomes. We explored the metabolic phenotypes of GDM and their impact on adverse pregnancy outcomes. Methods: Women diagnosed with gestational glucose intolerance or GDM were categorized into subgroups according to their prepregnancy body mass index (BMI) and the median values of the gestational Matsuda and Stumvoll indices. Logistic regression analysis was employed to assess the odds of adverse pregnancy outcomes, such as large-for-gestational age (LGA), small-for-gestational age, preterm birth, low Apgar score, and cesarean section. Results: A total of 309 women were included, with a median age of 31 years and a median BMI of 22.3 kg/m2. Women with a higher pre-pregnancy BMI had a higher risk of LGA newborns (adjusted odds ratio [aOR] for pre-pregnancy BMI ≥25 kg/m2 compared to 20–23 kg/m2, 4.26; 95% confidence interval [CI], 1.99 to 9.12; P<0.001; P for trend=0.001), but the risk of other adverse pregnancy outcomes did not differ according to pre-pregnancy BMI. Women with insulin resistance had a higher risk of LGA (aOR, 1.88; 95% CI, 1.02 to 3.47; P=0.043) and cesarean section (aOR, 2.12; 95% CI, 1.29 to 3.50; P=0.003) than women in the insulin-sensitive group. In contrast, defective β-cell function did not affect adverse pregnancy outcomes. Conclusion Different metabolic phenotypes of GDM were associated with heterogeneous pregnancy outcomes. Women with obesity and those with insulin resistance are at greater risk of adverse outcomes and might need strict glycemic management during pregnancy.

This review examines the challenges associated with occupational disease surveillance in Korea, particularly emphasizing the limitations of current data sources such as the Industrial Accident Compensation Insurance (IACI) statistics and special health examinations. The IACI system undercounts cases due to its emphasis on severe diseases and restrictions on approvals. Special health examinations, although they cover a broad workforce, are constrained by their annual scheduling, which leads to missed acute illnesses and subclinical conditions. The paper also explores the history of occupational disease surveillance in Korea, highlighting the fragmented and disease-specific approach of earlier systems. The authors introduce the newly established Korea Occupational Disease Surveillance Center (KODSC), a comprehensive nationwide system designed to gather, analyze, and interpret data on occupational diseases through a network of regional centers. By incorporating hospital-based surveillance and focusing on acute poisonings and other sentinel events, the KODSC aims to overcome the limitations of previous systems and promote collaboration with various agencies. Although it is still in the early stages of implementation, the KODSC demonstrates potential for improving data accuracy and contributing valuable insights for public health policy.

Background: Gestational diabetes mellitus (GDM) affects women with diverse pathological phenotypes, but little is known about the effects of this variation on perinatal outcomes. We explored the metabolic phenotypes of GDM and their impact on adverse pregnancy outcomes. Methods: Women diagnosed with gestational glucose intolerance or GDM were categorized into subgroups according to their prepregnancy body mass index (BMI) and the median values of the gestational Matsuda and Stumvoll indices. Logistic regression analysis was employed to assess the odds of adverse pregnancy outcomes, such as large-for-gestational age (LGA), small-for-gestational age, preterm birth, low Apgar score, and cesarean section. Results: A total of 309 women were included, with a median age of 31 years and a median BMI of 22.3 kg/m2. Women with a higher pre-pregnancy BMI had a higher risk of LGA newborns (adjusted odds ratio [aOR] for pre-pregnancy BMI ≥25 kg/m2 compared to 20–23 kg/m2, 4.26; 95% confidence interval [CI], 1.99 to 9.12; P<0.001; P for trend=0.001), but the risk of other adverse pregnancy outcomes did not differ according to pre-pregnancy BMI. Women with insulin resistance had a higher risk of LGA (aOR, 1.88; 95% CI, 1.02 to 3.47; P=0.043) and cesarean section (aOR, 2.12; 95% CI, 1.29 to 3.50; P=0.003) than women in the insulin-sensitive group. In contrast, defective β-cell function did not affect adverse pregnancy outcomes. Conclusion Different metabolic phenotypes of GDM were associated with heterogeneous pregnancy outcomes. Women with obesity and those with insulin resistance are at greater risk of adverse outcomes and might need strict glycemic management during pregnancy.

This study investigated the clinical characteristics and kidney outcomes of childhood-onset lupus nephritis (LN), and risk factors associated with prognosis. Methods: We enrolled 216 patients with histologically diagnosed LN during childhood. The Korean Society of Pediatric Nephrology organized a retrospective cohort study of childhood-onset LN in 13 major pediatric nephrology centers in South Korea. Results: The mean age at kidney biopsy was 13.2 ± 3.22 years. The main forms of presentation were nephrotic syndrome and/or hematuria in 152 patients (70.4%), and the most common histological finding was World Health Organization (WHO) class IV in 138 patients (63.9%), followed by WHO class III in 34 patients (15.7%). In the outcome analysis, the mean follow-up period of the patients was 7.8 ± 5.11 years. At last follow-up, 32 patients (14.8%) developed advanced chronic kidney disease (CKD). Male sex and failure to achieve remission at 12 months of treatment were significant risk factors for developing advanced CKD (hazard ratio of 2.57 and 2.29, respectively). Conclusion: Our study demonstrated the clinical characteristics and long-term outcomes of patients with childhood-onset LN. Male sex and failure to achieve remission in the first year of treatment were predictive of advanced CKD. Therefore, prompt awareness and close monitoring of these high-risk patients are needed, which may further improve the prognosis of children with LN.