Background: We investigated whether nutritional intake is associated with physical activity (PA) and handgrip strength (HGS) in individuals with airflow limitation. Methods: This study analyzed data from the 2014 and 2016 Korean National Health and Nutrition Examination Survey. We assessed total protein intake (g/day), caloric intake (kcal/day), and other nutritional intakes, using a 24-hour dietary recall questionnaire. HGS was measured three times for each hand using a digital grip strength dynamometer, and PA was assessed as health-enhancing PA. Airflow limitation was defined as a forced expiratory volume/forced vital capacity ratio of 0.7 in individuals over 40 years of age. Participants were categorized into groups based on their PA levels and HGS measurements: active aerobic PA vs. non-active aerobic PA, and normal HGS vs. low HGS. Results: Among the 622 individuals with airflow limitation, those involved in active aerobic PA and those with higher HGS had notably higher total food, calorie, water, protein, and lipid intake. The correlations between protein and caloric intake with HGS were strong (correlation coefficients=0.344 and 0.346, respectively). The forest plots show that higher intakes of food, water, calories, protein, and lipids are positively associated with active aerobic PA, while higher intakes of these nutrients are inversely associated with low HGS. However, in the multivariate logistic regression analysis, no significant associations were observed between nutritional intake and active aerobic PA or HGS. Conclusion Nutritional intake was found to not be an independent factor associated with PA and HGS. However, the observed correlations suggest potential indirect effects that warrant further investigation.

Background: We investigated whether nutritional intake is associated with physical activity (PA) and handgrip strength (HGS) in individuals with airflow limitation. Methods: This study analyzed data from the 2014 and 2016 Korean National Health and Nutrition Examination Survey. We assessed total protein intake (g/day), caloric intake (kcal/day), and other nutritional intakes, using a 24-hour dietary recall questionnaire. HGS was measured three times for each hand using a digital grip strength dynamometer, and PA was assessed as health-enhancing PA. Airflow limitation was defined as a forced expiratory volume/forced vital capacity ratio of 0.7 in individuals over 40 years of age. Participants were categorized into groups based on their PA levels and HGS measurements: active aerobic PA vs. non-active aerobic PA, and normal HGS vs. low HGS. Results: Among the 622 individuals with airflow limitation, those involved in active aerobic PA and those with higher HGS had notably higher total food, calorie, water, protein, and lipid intake. The correlations between protein and caloric intake with HGS were strong (correlation coefficients=0.344 and 0.346, respectively). The forest plots show that higher intakes of food, water, calories, protein, and lipids are positively associated with active aerobic PA, while higher intakes of these nutrients are inversely associated with low HGS. However, in the multivariate logistic regression analysis, no significant associations were observed between nutritional intake and active aerobic PA or HGS. Conclusion Nutritional intake was found to not be an independent factor associated with PA and HGS. However, the observed correlations suggest potential indirect effects that warrant further investigation.

Background: We investigated whether nutritional intake is associated with physical activity (PA) and handgrip strength (HGS) in individuals with airflow limitation. Methods: This study analyzed data from the 2014 and 2016 Korean National Health and Nutrition Examination Survey. We assessed total protein intake (g/day), caloric intake (kcal/day), and other nutritional intakes, using a 24-hour dietary recall questionnaire. HGS was measured three times for each hand using a digital grip strength dynamometer, and PA was assessed as health-enhancing PA. Airflow limitation was defined as a forced expiratory volume/forced vital capacity ratio of 0.7 in individuals over 40 years of age. Participants were categorized into groups based on their PA levels and HGS measurements: active aerobic PA vs. non-active aerobic PA, and normal HGS vs. low HGS. Results: Among the 622 individuals with airflow limitation, those involved in active aerobic PA and those with higher HGS had notably higher total food, calorie, water, protein, and lipid intake. The correlations between protein and caloric intake with HGS were strong (correlation coefficients=0.344 and 0.346, respectively). The forest plots show that higher intakes of food, water, calories, protein, and lipids are positively associated with active aerobic PA, while higher intakes of these nutrients are inversely associated with low HGS. However, in the multivariate logistic regression analysis, no significant associations were observed between nutritional intake and active aerobic PA or HGS. Conclusion Nutritional intake was found to not be an independent factor associated with PA and HGS. However, the observed correlations suggest potential indirect effects that warrant further investigation.

Background: We investigated whether nutritional intake is associated with physical activity (PA) and handgrip strength (HGS) in individuals with airflow limitation. Methods: This study analyzed data from the 2014 and 2016 Korean National Health and Nutrition Examination Survey. We assessed total protein intake (g/day), caloric intake (kcal/day), and other nutritional intakes, using a 24-hour dietary recall questionnaire. HGS was measured three times for each hand using a digital grip strength dynamometer, and PA was assessed as health-enhancing PA. Airflow limitation was defined as a forced expiratory volume/forced vital capacity ratio of 0.7 in individuals over 40 years of age. Participants were categorized into groups based on their PA levels and HGS measurements: active aerobic PA vs. non-active aerobic PA, and normal HGS vs. low HGS. Results: Among the 622 individuals with airflow limitation, those involved in active aerobic PA and those with higher HGS had notably higher total food, calorie, water, protein, and lipid intake. The correlations between protein and caloric intake with HGS were strong (correlation coefficients=0.344 and 0.346, respectively). The forest plots show that higher intakes of food, water, calories, protein, and lipids are positively associated with active aerobic PA, while higher intakes of these nutrients are inversely associated with low HGS. However, in the multivariate logistic regression analysis, no significant associations were observed between nutritional intake and active aerobic PA or HGS. Conclusion Nutritional intake was found to not be an independent factor associated with PA and HGS. However, the observed correlations suggest potential indirect effects that warrant further investigation.

Background: We investigated whether nutritional intake is associated with physical activity (PA) and handgrip strength (HGS) in individuals with airflow limitation. Methods: This study analyzed data from the 2014 and 2016 Korean National Health and Nutrition Examination Survey. We assessed total protein intake (g/day), caloric intake (kcal/day), and other nutritional intakes, using a 24-hour dietary recall questionnaire. HGS was measured three times for each hand using a digital grip strength dynamometer, and PA was assessed as health-enhancing PA. Airflow limitation was defined as a forced expiratory volume/forced vital capacity ratio of 0.7 in individuals over 40 years of age. Participants were categorized into groups based on their PA levels and HGS measurements: active aerobic PA vs. non-active aerobic PA, and normal HGS vs. low HGS. Results: Among the 622 individuals with airflow limitation, those involved in active aerobic PA and those with higher HGS had notably higher total food, calorie, water, protein, and lipid intake. The correlations between protein and caloric intake with HGS were strong (correlation coefficients=0.344 and 0.346, respectively). The forest plots show that higher intakes of food, water, calories, protein, and lipids are positively associated with active aerobic PA, while higher intakes of these nutrients are inversely associated with low HGS. However, in the multivariate logistic regression analysis, no significant associations were observed between nutritional intake and active aerobic PA or HGS. Conclusion Nutritional intake was found to not be an independent factor associated with PA and HGS. However, the observed correlations suggest potential indirect effects that warrant further investigation.

Background: The objective of this study was to investigate whether alcohol consumption might affect the quality of life (QOL), depressive mood, and metabolic syndrome in patients with obstructive lung disease (OLD). Methods: Data were obtained from the Korean National Health and Nutrition Examination Survey from 2014 and 2016. OLD was defined as spirometry of forced expiratory volume in 1 second/forced vital capacity <0.7 in those aged more than 40 years. QOL was evaluated using the European Quality of Life Questionnaire-5D (EQ-5D) index. Patient Health Questionnaire-9 (PHQ-9) was used to assess the severity of depressive mood. Alcohol consumption was based on a history of alcohol ingestion during the previous month. Results: A total of 984 participants with OLD (695 males, 289 females, age 65.8±9.7 years) were enrolled. The EQ-5D index was significantly higher in alcohol drinkers (n=525) than in non-alcohol drinkers (n=459) (0.94±0.11 vs. 0.91±0.13, p=0.002). PHQ- 9 scores were considerably lower in alcohol drinkers than in non-alcohol drinkers (2.15±3.57 vs. 2.78±4.13, p=0.013). However, multiple logistic regression analysis showed that alcohol consumption was not associated with EQ-5D index or PHQ-9 score. Body mass index ≥25 kg/m2, triglyceride ≥150 mg/dL, high-density lipoprotein <40 mg/dL in men and <50 mg/dL in women, and blood pressure ≥130/85 mm Hg were significantly more common in alcohol drinkers than in non-alcohol drinkers (all p<0.05). Conclusion Alcohol consumption did not change the QOL or depressive mood of OLD patients. However, metabolic syndrome-related factors were more common in alcohol drinkers than in non-alcohol drinkers.

Longitudinal data can provide important evidence with the potential to stimulate innovation and affect policies in medical education and can serve as a driving force for further developments in medical education through evidence-based decisions. Tracking and observing cohorts of students and graduates using longitudinal data can be a way to link the past, present, and future of medical education. This study reviewed practical methods and technical, administrative, and ethical considerations for the establishment and operation of a longitudinal database and presented examples of longitudinal databases. Cohort study design methods and previous examples of research using longitudinal databases to explore major topics in medical education were also reviewed. The implications of this study are as follows: (1) a systematic design process is required to establish longitudinal data, and each university should engage in ongoing deliberation about this issue; (2) efforts are needed to alleviate “survey fatigue” among respondents and reduce the administrative burden of those conducting data collection and analysis; (3) it is necessary to regularly review issues of personal information protection, data security, and ethics regarding the survey respondents; and (4) a system should be established that integrates and manages a longitudinal database of medical education at the national level. The hope is that establishing longitudinal data and cohorts at individual medical schools will not be a temporary phenomenon, but rather that they will be well utilized at the national level to innovate and implement ongoing changes in medical education.

The purpose of this study was to establish a model for constructing longitudinal data for medical school, and to structure cohort and longitudinal data using data from Yonsei University College of Medicine (YUCM) according to the established input-environment-output (I-E-O) model. The study was conducted according to the following procedure. First, the data that YUCM has collected was reviewed through data analysis and interviews with the person in charge of each questionnaire. Second, the opinions of experts on the validity of the I-E-O model were collected through the first expert consultation, and as a result, a model was established for each stage of medical education based on the I-E-O model. Finally, in order to further materialize and refine the previously established model for each stage of medical education, secondary expert consultation was conducted. As a result, the survey areas and time period for collecting longitudinal data were organized according to the model for each stage of medical education, and an example of the YUCM cohort constructed according to the established model for each stage of medical education was presented. The results derived from this study constitute a basic step toward building data from universities in longitudinal form, and if longitudinal data are actually constructed through this method, they could be used as an important basis for determining major policies or reorganizing the curricula of universities. These research results have implications in terms of the management and utilization of existing survey data, the composition of cohorts, and longitudinal studies for many medical schools that are conducting surveys in various areas targeting students, such as lecture evaluation and satisfaction surveys.

Background/Aims: The effect of hyperammonemia on the mortality in patients with liver cirrhosis is well documented. However, little is known about the impact of hyperammonemia on mortality among intensive care unit patients without hepatic disease. We aimed to investigate factors associated with non-hepatic hyperammonemia among intensive care unit patients and to evaluate the factors related to the 7- and 90-day mortality. Methods: Between February 2016 and February 2020, 948 patients without hepatic disease who had 972 episodes of admission to the intensive care unit were retrospectively enrolled and classified as hyperammonemia grades 0 (≤ 80 µg/dL; 585 [60.2%]), 1 (≤ 160 µg/dL; 291 [29.9%]), 2 (≤ 240 µg/dL; 55 [5.7%]), and 3 (> 240 µg/dL; 41 [4.2%]). Factors associated with hyperammonemia and the 7- and 90-day mortality were evaluated by multivariate logistic regression analysis and Cox regression analysis, respectively. Kaplan-Meier survival curves for the 7- and 90-day mortality were constructed. Results: The independent risk factors for hyperammonemia were male sex (odds ratio, 1.517), age (0.984/year), acute brain failure (2.467), acute kidney injury (1.437), prothrombin time-international normalized ratio (2.272/unit), and albumin (0.694/g/dL). The 90-day mortality rate in the entire cohort was 24.3% and gradually increased with increasing hyperammonemia grade at admission (17.9%, 28.2%, 43.6%, and 61.0% in patients with grades 0, 1, 2, and 3, respectively). Additionally, non-hepatic hyperammonemia was an independent predictor of the 90- day mortality in intensive care unit patients. Conclusions Non-hepatic hyperammonemia is common (39.8%) and associated with the 90-day mortality among intensive care unit patients.