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 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: Identifying risk factors for postpartum type 2 diabetes in women with gestational diabetes mellitus (GDM) is crucial for effective interventions. We examined whether changes in insulin sensitivity after delivery affects the risk of type 2 diabetes in women with GDM. Methods: This prospective cohort study included 347 women with GDM or gestational impaired glucose tolerance, who attended the follow-up visits at 2 months postpartum and annually thereafter. Changes in insulin sensitivity were calculated using the Matsuda index at GDM diagnosis and at 2 months postpartum (ΔMatsuda index). After excluding women with pregestational diabetes or those followed up only once, we analyzed the risk of postpartum type 2 diabetes based on the ΔMatsuda index tertiles. Results: The incidence of type 2 diabetes at the two-month postpartum visit decreased with increasing ΔMatsuda index tertiles (16.4%, 9.5%, and 1.8%, P=0.001). During a 4.1-year follow-up, 26 out of 230 women who attended more than two follow-up visits (11.3%) developed type 2 diabetes. Compared to the lowest tertile, subjects in the highest ΔMatsuda index tertile showed a significantly reduced risk of type 2 diabetes (hazard ratio, 0.33; 95% confidence interval, 0.12 to 0.93; P=0.036) after adjusting for confounders. Conclusion Improvement in insulin sensitivity after delivery is associated with a reduced risk of postpartum type 2 diabetes in women with GDM. Postpartum changes in insulin sensitivity could be a useful prediction for future type 2 diabetes development in women with GDM.