Purpose: This study assessed the validity of the hospital standardized mortality ratio (HSMR) risk-adjusted model by comparing models that include clinical information and the current model based on administrative information in South Korea. Materials and Methods: The data of 53976 inpatients were analyzed. The current HSMR risk-adjusted model (Model 1) adjusts for sex, age, health coverage, emergency hospitalization status, main diagnosis, surgery status, and Charlson Comorbidity Index (CCI) using administrative data. As candidate variables, among clinical information, the American Society of Anesthesiologists score, Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 3, present on admission CCI, and cancer stage were collected. Surgery status, intensive care in the intensive care unit, and CCI were selected as proxy variables among administrative data. In-hospital death was defined as the dependent variable, and a logistic regression analysis was performed. The statistical performance of each model was compared using C-index values. Results: There was a strong correlation between variables in the administrative data and those in the medical records. The C-index of the existing model (Model 1) was 0.785; Model 2, which included all clinical data, had a higher C-index of 0.857. In Model 4, in which APACHE II and SAPS 3 were replaced with variables recorded in the administrative data from Model 2, the C-index further increased to 0.863. Conclusion The HSMR assessment model improved when clinical data were adjusted. Simultaneously, the validity of the evaluation method could be secured even if some of the clinical information was replaced with the information in the administrative data.

Purpose: This study assessed the validity of the hospital standardized mortality ratio (HSMR) risk-adjusted model by comparing models that include clinical information and the current model based on administrative information in South Korea. Materials and Methods: The data of 53976 inpatients were analyzed. The current HSMR risk-adjusted model (Model 1) adjusts for sex, age, health coverage, emergency hospitalization status, main diagnosis, surgery status, and Charlson Comorbidity Index (CCI) using administrative data. As candidate variables, among clinical information, the American Society of Anesthesiologists score, Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 3, present on admission CCI, and cancer stage were collected. Surgery status, intensive care in the intensive care unit, and CCI were selected as proxy variables among administrative data. In-hospital death was defined as the dependent variable, and a logistic regression analysis was performed. The statistical performance of each model was compared using C-index values. Results: There was a strong correlation between variables in the administrative data and those in the medical records. The C-index of the existing model (Model 1) was 0.785; Model 2, which included all clinical data, had a higher C-index of 0.857. In Model 4, in which APACHE II and SAPS 3 were replaced with variables recorded in the administrative data from Model 2, the C-index further increased to 0.863. Conclusion The HSMR assessment model improved when clinical data were adjusted. Simultaneously, the validity of the evaluation method could be secured even if some of the clinical information was replaced with the information in the administrative data.

Purpose: This study assessed the validity of the hospital standardized mortality ratio (HSMR) risk-adjusted model by comparing models that include clinical information and the current model based on administrative information in South Korea. Materials and Methods: The data of 53976 inpatients were analyzed. The current HSMR risk-adjusted model (Model 1) adjusts for sex, age, health coverage, emergency hospitalization status, main diagnosis, surgery status, and Charlson Comorbidity Index (CCI) using administrative data. As candidate variables, among clinical information, the American Society of Anesthesiologists score, Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 3, present on admission CCI, and cancer stage were collected. Surgery status, intensive care in the intensive care unit, and CCI were selected as proxy variables among administrative data. In-hospital death was defined as the dependent variable, and a logistic regression analysis was performed. The statistical performance of each model was compared using C-index values. Results: There was a strong correlation between variables in the administrative data and those in the medical records. The C-index of the existing model (Model 1) was 0.785; Model 2, which included all clinical data, had a higher C-index of 0.857. In Model 4, in which APACHE II and SAPS 3 were replaced with variables recorded in the administrative data from Model 2, the C-index further increased to 0.863. Conclusion The HSMR assessment model improved when clinical data were adjusted. Simultaneously, the validity of the evaluation method could be secured even if some of the clinical information was replaced with the information in the administrative data.

Purpose: This study assessed the validity of the hospital standardized mortality ratio (HSMR) risk-adjusted model by comparing models that include clinical information and the current model based on administrative information in South Korea. Materials and Methods: The data of 53976 inpatients were analyzed. The current HSMR risk-adjusted model (Model 1) adjusts for sex, age, health coverage, emergency hospitalization status, main diagnosis, surgery status, and Charlson Comorbidity Index (CCI) using administrative data. As candidate variables, among clinical information, the American Society of Anesthesiologists score, Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 3, present on admission CCI, and cancer stage were collected. Surgery status, intensive care in the intensive care unit, and CCI were selected as proxy variables among administrative data. In-hospital death was defined as the dependent variable, and a logistic regression analysis was performed. The statistical performance of each model was compared using C-index values. Results: There was a strong correlation between variables in the administrative data and those in the medical records. The C-index of the existing model (Model 1) was 0.785; Model 2, which included all clinical data, had a higher C-index of 0.857. In Model 4, in which APACHE II and SAPS 3 were replaced with variables recorded in the administrative data from Model 2, the C-index further increased to 0.863. Conclusion The HSMR assessment model improved when clinical data were adjusted. Simultaneously, the validity of the evaluation method could be secured even if some of the clinical information was replaced with the information in the administrative data.

Purpose: This study assessed the validity of the hospital standardized mortality ratio (HSMR) risk-adjusted model by comparing models that include clinical information and the current model based on administrative information in South Korea. Materials and Methods: The data of 53976 inpatients were analyzed. The current HSMR risk-adjusted model (Model 1) adjusts for sex, age, health coverage, emergency hospitalization status, main diagnosis, surgery status, and Charlson Comorbidity Index (CCI) using administrative data. As candidate variables, among clinical information, the American Society of Anesthesiologists score, Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 3, present on admission CCI, and cancer stage were collected. Surgery status, intensive care in the intensive care unit, and CCI were selected as proxy variables among administrative data. In-hospital death was defined as the dependent variable, and a logistic regression analysis was performed. The statistical performance of each model was compared using C-index values. Results: There was a strong correlation between variables in the administrative data and those in the medical records. The C-index of the existing model (Model 1) was 0.785; Model 2, which included all clinical data, had a higher C-index of 0.857. In Model 4, in which APACHE II and SAPS 3 were replaced with variables recorded in the administrative data from Model 2, the C-index further increased to 0.863. Conclusion The HSMR assessment model improved when clinical data were adjusted. Simultaneously, the validity of the evaluation method could be secured even if some of the clinical information was replaced with the information in the administrative data.

OBJECTIVES: This study examined trends in the dietary intake and food sources of long-chain polyunsaturated fatty acids (LC-PUFAs) in Korean adults from 2007 to 2018. METHODS: In total, 46,307 adults (aged 19-64 years) were selected from the 2007-2018 Korea National Health and Nutrition Examination Surveys. Dietary data were obtained using 24-hour dietary recall. Intake levels and food sources of LC-PUFAs, including alpha-linolenic acid (ALA), eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), and linoleic acid (LA), were evaluated across the survey years and assessed based on compliance with dietary recommendations over the 2007-2018 period. Linear trends in LC-PUFAs intake levels over time were examined through multiple linear regression analysis. RESULTS: From 2007 to 2018, ALA and LA consumption increased from 1.1 g (0.5% of energy) to 1.4 g (0.6% of energy) and from 8.6 g (3.9% of energy) to 10.0 g (4.5% of energy), respectively. EPA intake decreased from 0.14 g to 0.12 g, and EPA+DHA intake showed a decreasing trend. The proportion of individuals who did not meet the recommended intake of EPA+DHA (250 mg/day) increased (64.4 to 68.4%). Regarding changes in food sources of ALA and LA, the contributions from mayonnaise, eggs, and bread increased, while those from plant food sources decreased. Among food sources of EPA and DHA, anchovy, saury, and Atka mackerel showed lower contributions over time. CONCLUSIONS Our findings suggest that strategies to encourage the consumption of EPA and DHA from healthy food sources are necessary to improve cardiovascular health in the Korean population.

Background: Recent studies have reported that chronic mental health problems often emerge in young adulthood. This study elucidated the independent effects of smoking and drinking on depressed mood in young adults by sex. Methods: We used Data from the Korea National Health and Nutrition Examination Surveys conducted in 2014, 2016, and 2018. A total of 3,391 participants aged 19–35 years, without serious chronic diseases, were recruited for this study. Depression was evaluated using the Patient Health Questionnaire (PHQ-9). Results: Smoking behavior, current smoking, and number of days smoked were significantly associated with higher PHQ-9 scores in both men and women (all P<0.05). However, past and ever smoking were positively associated with PHQ-9 scores only in women (all P<0.001). Regarding alcohol consumption, the age at which drinking first began was negatively associated with PHQ-9 scores in both men and women (all P<0.001), but the amount of alcohol consumed at 1 time was positively associated with PHQ-9 scores only in women (P=0.013). Men who drank 2–4 times a month and women who had not drunk during the past year had the lowest PHQ-9 scores. Conclusion Smoking and alcohol consumption were independently associated with depressed mood in young Korean adults, which was more pronounced in women, and exhibited sex-specific characteristics.

This study was undertaken to identify dietary patterns of Korean elderly people living alone, and to compare the quality of diet consumed. Data of 821 elderly people aged 65 years or older who were living alone, was obtained from the 2016∼2018 National Health and Nutrition Survey. The percentage energy intake from 24 food groups was calculated, and a cluster analysis was applied to identify dietary patterns. General characteristics, energy and nutrient intake, nutrient adequacy ratio (NAR), mean adequacy ratio (MAR), and index of nutritional quality (INQ) were analyzed. Dietary variety score (DVS) and dietary diversity score (DDS) were subsequently calculated. The rice-centered diet group and mixed diet group were characterized as consuming higher intake of rice and a wider variety of food groups, respectively. The mean age and percentage of participants living in rural areas were higher, whereas education level and monthly income were lower, in the rice-centered diet group (P＜0.001 for all). Intakes of energy and all other nutrients (except carbohydrate and thiamine) were lower in the rice-centered diet group (P＜0.001 for all). The NAR for all nutrients (except thiamine), MAR, and INQs (except thiamine and iron) were significantly lower in the rice-centered diet group (P＜0.001 for all). The rice-centered diet group had significantly lower DVS (P＜0.001) and DDS (P＜0.001), as compared with the mixed diet group (P＜0.001). Due to the insufficient energy and nutrient intake in the rice-centered diet group, it is necessary to develop nutritional monitoring and customized nutrition policies for these individuals.

BACKGROUND/OBJECTIVES: The study was performed to investigate the degree of perceived stress by sex in middle-aged people, and to provide basic data for appropriate nutrition education and interventional measures for middle-aged subjects through comparative analysis of association between stress and dietary habits, emotional eating behavior, and insomnia. SUBJECTS/METHODS: A survey was conducted in 670 middle-aged subjects (320 men and 350 women) aged 40–64 years, resided in Seoul and Gyeonggi area. Collected data were analyzed using SPSS WIN 25.0 program. RESULTS: Perceived stress in middle-aged subjects was not different by sex. Stress was higher in men with low dietary habits level compared to other groups (P < 0.001), and was higher in women with low and moderate dietary habits level compared to women with high dietary habits level (P < 0.05). Stress in men was higher in the group with emotional eaters (P < 0.05), and the same result was shown in women (P < 0.001). Stress was higher in both men and women with poor sleep quality (P < 0.001). Stress score was positively correlated with emotional dietary behavior and insomnia (P < 0.001) and negatively correlated with dietary habits (P < 0.001). CONCLUSIONS It is considered that proper nutrition education and interventional measures according to sex are needed for stress control and proper dietary behavior and lifestyle in middle-aged people population, along with projects and policies at the national level.

BACKGROUND/OBJECTIVES: This study analyzed the quality of lunches provided in senior leisure service (SLS) facilities and compared institutional foodservice (IF) and noninstitutional foodservice (non-IF). SUBJECTS/METHODS: Data of 390 adults aged 65 years or older who ate lunches in SLS facilities were analyzed using the information from the 2013–2017 Korea National Health and Nutrition Examination Survey. The participants were classified into IF (n = 129) and non-IF (n = 261) groups according to meal type provided. The intake of major food groups, energy and nutrients, and nutrient adequacy ratio (NAR) and mean adequacy ratio (MAR) were analyzed. The diversity of meals was evaluated by food group patterns, dietary diversity score (DDS) and dietary variety score (DVS). Energy intake was adjusted in model 1, while energy and sex were adjusted in model 2. All confounding variables were adjusted in model 3. RESULTS: The intake of seafoods (P < 0.001 in models 1, 2, and 3), seaweeds (P < 0.01 in models 1 and 2), and dairy products (P < 0.05 in models 1, 2, and 3) was significantly higher in the IF group. No significant difference existed in energy intake; however, the intake of all nutrients except carbohydrate and vitamin C was significantly higher in the IF group. NAR of all nutrients, excluding vitamin C, was higher in the IF group, and MAR was also higher in the IF group (P < 0.001 in models 1, 2, and 3). The IF group had significantly higher DDS and DVS than the non-IF group (P < 0.001). CONCLUSIONS The lunches provided in SLS facilities were better in terms of quantity and quality when provided through IF than through non-IF. More systematic foodservice programs should be implemented in SLS facilities, especially in facilities wherein users prepare their own meals.