Background: Although excessive physical activity (PA) does not always confer additional health benefits, there is a paucity of studies that have quantitatively examined the doseresponse relationship between PA and type 2 diabetes. Therefore, this study investigated the relationship between the type 2 diabetes prevalence and intensity, frequency, and metabolic equivalent of task (MET) score of PA in a large population sample. Methods: We conducted a nationwide cross-sectional analysis examining sociodemographic variables, PA habits, and type 2 diabetes prevalence in 2,428,448 participants included in the Korea Community Health Survey. The non-linear association between MET score and odds ratios (ORs) for type 2 diabetes prevalence was plotted using a weighted generalized additive model. Categorical analysis was used to examine the joint association of moderate-intensity PA (MPA) and vigorous-intensity PA (VPA), and the influence of PA frequency. Results: MET score and diabetes prevalence revealed a non-linear association with the nadir at 1,028 MET-min/week, beyond which ORs increased with additional PA. Joint analysis of MPA and VPA showed the lowest OR of 0.79 (95% confidence interval, 0.75–0.84) for those engaging in 300–600 MET-min/week of MPA and > 600 MET-min/week of VPA concurrently, corresponding with World Health Organization recommendations. Additionally, both “weekend warriors” and “regularly active” individuals showed lower ORs compared to the inactive, although no significant difference was noted between the active groups. Conclusion In a large South Korean sample, higher PA is not always associated with a lower prevalence of type 2 diabetes, as the association follows a non-linear pattern; differences existed across sociodemographic variables. Considering the joint association, an adequate combination of MPA and VPA is recommended. The frequency of PA does not significantly influence the type 2 diabetes prevalence.

Background: Although excessive physical activity (PA) does not always confer additional health benefits, there is a paucity of studies that have quantitatively examined the doseresponse relationship between PA and type 2 diabetes. Therefore, this study investigated the relationship between the type 2 diabetes prevalence and intensity, frequency, and metabolic equivalent of task (MET) score of PA in a large population sample. Methods: We conducted a nationwide cross-sectional analysis examining sociodemographic variables, PA habits, and type 2 diabetes prevalence in 2,428,448 participants included in the Korea Community Health Survey. The non-linear association between MET score and odds ratios (ORs) for type 2 diabetes prevalence was plotted using a weighted generalized additive model. Categorical analysis was used to examine the joint association of moderate-intensity PA (MPA) and vigorous-intensity PA (VPA), and the influence of PA frequency. Results: MET score and diabetes prevalence revealed a non-linear association with the nadir at 1,028 MET-min/week, beyond which ORs increased with additional PA. Joint analysis of MPA and VPA showed the lowest OR of 0.79 (95% confidence interval, 0.75–0.84) for those engaging in 300–600 MET-min/week of MPA and > 600 MET-min/week of VPA concurrently, corresponding with World Health Organization recommendations. Additionally, both “weekend warriors” and “regularly active” individuals showed lower ORs compared to the inactive, although no significant difference was noted between the active groups. Conclusion In a large South Korean sample, higher PA is not always associated with a lower prevalence of type 2 diabetes, as the association follows a non-linear pattern; differences existed across sociodemographic variables. Considering the joint association, an adequate combination of MPA and VPA is recommended. The frequency of PA does not significantly influence the type 2 diabetes prevalence.

Background: Although excessive physical activity (PA) does not always confer additional health benefits, there is a paucity of studies that have quantitatively examined the doseresponse relationship between PA and type 2 diabetes. Therefore, this study investigated the relationship between the type 2 diabetes prevalence and intensity, frequency, and metabolic equivalent of task (MET) score of PA in a large population sample. Methods: We conducted a nationwide cross-sectional analysis examining sociodemographic variables, PA habits, and type 2 diabetes prevalence in 2,428,448 participants included in the Korea Community Health Survey. The non-linear association between MET score and odds ratios (ORs) for type 2 diabetes prevalence was plotted using a weighted generalized additive model. Categorical analysis was used to examine the joint association of moderate-intensity PA (MPA) and vigorous-intensity PA (VPA), and the influence of PA frequency. Results: MET score and diabetes prevalence revealed a non-linear association with the nadir at 1,028 MET-min/week, beyond which ORs increased with additional PA. Joint analysis of MPA and VPA showed the lowest OR of 0.79 (95% confidence interval, 0.75–0.84) for those engaging in 300–600 MET-min/week of MPA and > 600 MET-min/week of VPA concurrently, corresponding with World Health Organization recommendations. Additionally, both “weekend warriors” and “regularly active” individuals showed lower ORs compared to the inactive, although no significant difference was noted between the active groups. Conclusion In a large South Korean sample, higher PA is not always associated with a lower prevalence of type 2 diabetes, as the association follows a non-linear pattern; differences existed across sociodemographic variables. Considering the joint association, an adequate combination of MPA and VPA is recommended. The frequency of PA does not significantly influence the type 2 diabetes prevalence.

Background: Although excessive physical activity (PA) does not always confer additional health benefits, there is a paucity of studies that have quantitatively examined the doseresponse relationship between PA and type 2 diabetes. Therefore, this study investigated the relationship between the type 2 diabetes prevalence and intensity, frequency, and metabolic equivalent of task (MET) score of PA in a large population sample. Methods: We conducted a nationwide cross-sectional analysis examining sociodemographic variables, PA habits, and type 2 diabetes prevalence in 2,428,448 participants included in the Korea Community Health Survey. The non-linear association between MET score and odds ratios (ORs) for type 2 diabetes prevalence was plotted using a weighted generalized additive model. Categorical analysis was used to examine the joint association of moderate-intensity PA (MPA) and vigorous-intensity PA (VPA), and the influence of PA frequency. Results: MET score and diabetes prevalence revealed a non-linear association with the nadir at 1,028 MET-min/week, beyond which ORs increased with additional PA. Joint analysis of MPA and VPA showed the lowest OR of 0.79 (95% confidence interval, 0.75–0.84) for those engaging in 300–600 MET-min/week of MPA and > 600 MET-min/week of VPA concurrently, corresponding with World Health Organization recommendations. Additionally, both “weekend warriors” and “regularly active” individuals showed lower ORs compared to the inactive, although no significant difference was noted between the active groups. Conclusion In a large South Korean sample, higher PA is not always associated with a lower prevalence of type 2 diabetes, as the association follows a non-linear pattern; differences existed across sociodemographic variables. Considering the joint association, an adequate combination of MPA and VPA is recommended. The frequency of PA does not significantly influence the type 2 diabetes prevalence.

Gestational diabetes mellitus (GDM) poses significant health risks to both mothers and newborns, requiring rigorous self-management and frequent medical consultations. Advances in information and communications technology (ICT) have shown promising results in reducing the number of in-person visits for GDM management. ICT enhances patient self-care engagement, with some studies reporting reductions in average blood glucose and HbA1c levels. ICT for GDM management has demonstrated benefits such as fewer in-person visits, improved adherence to self-monitoring of blood glucose, increased global user satisfaction, and maintenance of blood glucose control and perinatal outcomes. Common barriers to ICT for GDM include technological literacy, inadequate education, limited technical support, the additional burden of non-customized applications, and restricted interoperability. Further research is needed on the impact of technology on GDM management to optimize digital health solutions.

Gestational diabetes mellitus (GDM) poses significant health risks to both mothers and newborns, requiring rigorous self-management and frequent medical consultations. Advances in information and communications technology (ICT) have shown promising results in reducing the number of in-person visits for GDM management. ICT enhances patient self-care engagement, with some studies reporting reductions in average blood glucose and HbA1c levels. ICT for GDM management has demonstrated benefits such as fewer in-person visits, improved adherence to self-monitoring of blood glucose, increased global user satisfaction, and maintenance of blood glucose control and perinatal outcomes. Common barriers to ICT for GDM include technological literacy, inadequate education, limited technical support, the additional burden of non-customized applications, and restricted interoperability. Further research is needed on the impact of technology on GDM management to optimize digital health solutions.

Gestational diabetes mellitus (GDM) poses significant health risks to both mothers and newborns, requiring rigorous self-management and frequent medical consultations. Advances in information and communications technology (ICT) have shown promising results in reducing the number of in-person visits for GDM management. ICT enhances patient self-care engagement, with some studies reporting reductions in average blood glucose and HbA1c levels. ICT for GDM management has demonstrated benefits such as fewer in-person visits, improved adherence to self-monitoring of blood glucose, increased global user satisfaction, and maintenance of blood glucose control and perinatal outcomes. Common barriers to ICT for GDM include technological literacy, inadequate education, limited technical support, the additional burden of non-customized applications, and restricted interoperability. Further research is needed on the impact of technology on GDM management to optimize digital health solutions.

Background: Liver disease causes over two million deaths annually worldwide, comprising approximately 4% of all global fatalities. We aimed to analyze liver disease-related mortality trends from 1990 to 2021 using the World Health Organization (WHO) Mortality Database and forecast global liver disease-related mortality rates up to 2050. Methods: This study examined age-standardized liver disease-related death rates from 1990 to 2021, employing data from the WHO Mortality Database across 112 countries across five continents. The rates over time were calculated using a locally weighted scatter plot smoother curve, with weights assigned based on the population of each country. Furthermore, this study projected liver disease-related mortality rates up to 2050 using a Bayesian age-periodcohort (BAPC) model. Additionally, a decomposition analysis was conducted to discern influencing factors such as population growth, aging, and epidemiological changes. Results: The estimated global age-standardized liver disease-related mortality rates surged significantly from 1990 to 2021 across 112 countries, rising from 103.4 deaths per 1,000,000 people (95% confidence interval [CI], 88.16, 118.74) in 1990 to 173.0 deaths per 1,000,000 people (95% CI, 155.15, 190.95) in 2021. This upward trend was particularly pronounced in low- and middle-income countries, in Africa, and in populations aged 65 years and older.Moreover, age-standardized liver disease-related mortality rates were correlated with a lower Human Development Index (P < 0.001) and sociodemographic index (P = 0.001). According to the BAPC model, the projected trend indicated a sustained and substantial decline in liver disease-related mortality rates, with an estimated decrease from 185.08 deaths per 1,000,000 people (95% CI, 179.79, 190.63) in 2021 to 156.29 (112.32, 214.77) in 2050. From 1990 to 2021, age-standardized liver disease-related deaths surged primarily due to epidemiological changes, whereas from 1990 to 2050, the impact of population aging and growth became the primary contributing factors to the overall increase. Conclusion Global age-standardized liver disease-related mortality has increased significantly and continues to emerge as a crucial global public health issue. Further investigation into liver disease-related mortality rates in Africa is needed, and updating policies is necessary to effectively manage the global burden of liver disease.

Background: Liver disease causes over two million deaths annually worldwide, comprising approximately 4% of all global fatalities. We aimed to analyze liver disease-related mortality trends from 1990 to 2021 using the World Health Organization (WHO) Mortality Database and forecast global liver disease-related mortality rates up to 2050. Methods: This study examined age-standardized liver disease-related death rates from 1990 to 2021, employing data from the WHO Mortality Database across 112 countries across five continents. The rates over time were calculated using a locally weighted scatter plot smoother curve, with weights assigned based on the population of each country. Furthermore, this study projected liver disease-related mortality rates up to 2050 using a Bayesian age-periodcohort (BAPC) model. Additionally, a decomposition analysis was conducted to discern influencing factors such as population growth, aging, and epidemiological changes. Results: The estimated global age-standardized liver disease-related mortality rates surged significantly from 1990 to 2021 across 112 countries, rising from 103.4 deaths per 1,000,000 people (95% confidence interval [CI], 88.16, 118.74) in 1990 to 173.0 deaths per 1,000,000 people (95% CI, 155.15, 190.95) in 2021. This upward trend was particularly pronounced in low- and middle-income countries, in Africa, and in populations aged 65 years and older.Moreover, age-standardized liver disease-related mortality rates were correlated with a lower Human Development Index (P < 0.001) and sociodemographic index (P = 0.001). According to the BAPC model, the projected trend indicated a sustained and substantial decline in liver disease-related mortality rates, with an estimated decrease from 185.08 deaths per 1,000,000 people (95% CI, 179.79, 190.63) in 2021 to 156.29 (112.32, 214.77) in 2050. From 1990 to 2021, age-standardized liver disease-related deaths surged primarily due to epidemiological changes, whereas from 1990 to 2050, the impact of population aging and growth became the primary contributing factors to the overall increase. Conclusion Global age-standardized liver disease-related mortality has increased significantly and continues to emerge as a crucial global public health issue. Further investigation into liver disease-related mortality rates in Africa is needed, and updating policies is necessary to effectively manage the global burden of liver disease.

Background: Liver disease causes over two million deaths annually worldwide, comprising approximately 4% of all global fatalities. We aimed to analyze liver disease-related mortality trends from 1990 to 2021 using the World Health Organization (WHO) Mortality Database and forecast global liver disease-related mortality rates up to 2050. Methods: This study examined age-standardized liver disease-related death rates from 1990 to 2021, employing data from the WHO Mortality Database across 112 countries across five continents. The rates over time were calculated using a locally weighted scatter plot smoother curve, with weights assigned based on the population of each country. Furthermore, this study projected liver disease-related mortality rates up to 2050 using a Bayesian age-periodcohort (BAPC) model. Additionally, a decomposition analysis was conducted to discern influencing factors such as population growth, aging, and epidemiological changes. Results: The estimated global age-standardized liver disease-related mortality rates surged significantly from 1990 to 2021 across 112 countries, rising from 103.4 deaths per 1,000,000 people (95% confidence interval [CI], 88.16, 118.74) in 1990 to 173.0 deaths per 1,000,000 people (95% CI, 155.15, 190.95) in 2021. This upward trend was particularly pronounced in low- and middle-income countries, in Africa, and in populations aged 65 years and older.Moreover, age-standardized liver disease-related mortality rates were correlated with a lower Human Development Index (P < 0.001) and sociodemographic index (P = 0.001). According to the BAPC model, the projected trend indicated a sustained and substantial decline in liver disease-related mortality rates, with an estimated decrease from 185.08 deaths per 1,000,000 people (95% CI, 179.79, 190.63) in 2021 to 156.29 (112.32, 214.77) in 2050. From 1990 to 2021, age-standardized liver disease-related deaths surged primarily due to epidemiological changes, whereas from 1990 to 2050, the impact of population aging and growth became the primary contributing factors to the overall increase. Conclusion Global age-standardized liver disease-related mortality has increased significantly and continues to emerge as a crucial global public health issue. Further investigation into liver disease-related mortality rates in Africa is needed, and updating policies is necessary to effectively manage the global burden of liver disease.