BACKGROUND/OBJECTIVES: The coronavirus disease 2019 (COVID-19) pandemic has affected the entire world population in many ways. This study aimed to analyze the patterns of changes in eating, food purchasing and preparation, physical activity, and subjective health after COVID-19 outbreak by various sociodemographic factors and to understand the factors associated with changes in subjective health. SUBJECTS/METHODS: A cross-sectional survey using a representative sample from Seoul was used for the analysis. The data collection was conducted from September to October 2020. A total of 3,833 citizens aged more than 18 years old participated in the Seoul Food Survey. Descriptive statistics and generalized ordinal logistic regression models were used to understand the changes in health behaviors, health indicators, and subjective general health by various socioeconomic status. RESULTS: It was shown that the changes in household income, food expenditure, food consumption and physical activities differed significantly by age, education, occupation, income, weight, and food security status. Low-income and food-insecure households were affected more severely by the pandemic. Older age, household food insecurity, income reduction, increased home cooking and frequency of having instant foods, decreased physical activity and weight gain were significant factors explaining worse perceived health during the COVID-19 pandemic. CONCLUSIONS The results suggest that focusing on older populations and low-income families with food insecurity should be prioritized during infectious disease outbreaks. In addition, the role of physical activities and instant food consumption in explaining perceived health should be investigated further in this prolonged battle with the pandemic situation.

BACKGROUND/OBJECTIVES: Although adherence to a higher diet quality may help prevent cognitive decline in older adults, literature for this in a Korean population is limited. Thus, the aim of this study was to examine the association between diet quality indices and the risk of mild cognitive impairment (MCI) in Korean older adults. SUBJECTS/METHODS: This cross-sectional study included 806 community-dwelling people aged 60 yrs and over in Korea. Diet quality was assessed via the revised Recommended Food Score (RFS) and alternate Mediterranean Diet Score (aMDS). Cognitive function was measured using a Korean version of the Mini-Mental State Examination (MMSE-KC).Associations between diet quality indices and MMSE-KC score were assessed with a general linear model after adjusting for covariates. Logistic regression was used to determine the association between diet quality indices and the risk of MCI. RESULTS: The prevalence of MCI was 35.3%. There were no significant trends between MMSE-KC scores and RFS and aMDS after adjusting for age, gender, education, exercise, living status, social activity, and alcohol drinking. Among total subjects, RFS was inversely associated with the risk of MCI after adjusting for covariates (Q5 vs. Q1; odds ratio [OR], 0.49; 95% confidence interval [CI], 0.28–0.83). Among total subjects and men, aMDS was inversely related to the risk of MCI after adjusting for covariates (Q5 vs. Q1; OR, 0.51; 95% CI, 0.29–0.89 for total subjects; Q5 vs. Q1; OR, 0.36; 95% CI, 0.15–0.83 for men). CONCLUSIONS Our results demonstrate that high diet quality evaluated by RFS and aMDS is inversely associated with the risk of MCI. Thus, high quality diet may reduce or retard cognitive decline in the old population. Longitudinal studies are needed to determine the causal relationship between diet quality and the risk of MCI in the elderly.

BACKGROUND/OBJECTIVES: Food literacy (FL) is a crucial skill for selecting sustainable and healthy food options, necessitating the identification of vulnerable groups in the community using valid measurement tools. Identifying weak domains in FL is essential for enhancing the overall FL. This study examined the FL levels of Seoul citizens based on their sociodemographic characteristics and assessed the relationship between FL, food intake, and weight status. SUBJECTS/METHODS: This study utilized the data from the Seoul Food Survey, a crosssectional study employing representative samples of Seoul citizens. Data collection occurred from September to October 2021, with 4,039 citizens aged 18 yrs and above participating in face-to-face surveys. Thirty-three FL items were assessed, comprising 14 items in the nutrition and safety (NS) domain, eight items in the cultural and relational (CR) domain, and 11 items in the socio-ecological (SE) domain. In addition, data on food intake sufficiency and obesity status were collected. The descriptive statistics, t-tests, analysis of variance, and logistic regression analysis were used for analysis. RESULTS: Men, students, young adults, older citizens, and people experiencing food insecurity had the lowest scores for all the FL domains. The highest quartile group of NS scores had a higher probability of consuming adequate servings of vegetables and fruits, with significant linear trends observed (P for trend < 0.05). In all three FL domains, the odds ratio for obesity was significantly lower in the groups with high FL scores (P < 0.05). CONCLUSIONS A close relationship was observed between low FL, obesity, and food intake, even after controlling for other covariates. Vulnerable groups with low FL were also identified. Therefore, it is essential to develop programs to improve FL and the health and well-being of these groups.

Objectives: Recent epidemiological data reported that young adults in their 20 ~ 30s are a vulnerable population with unhealthy dietary practices and a few signs of deteriorated health indicators. However, there are no dietary guidelines that are specifically developed for the young adult population. This study introduces some data collection tools that are mostly used in the service design field, and demonstrates how these tools can be used in nutrition research for developing dietary guidelines for specific target groups. Methods: To understand the context of food choices among young people, 39 people were enrolled to complete a probes booklet. Thematic analysis and word cloud were performed to capture the main themes from the probes and a persona was developed based on the findings. Results: Data from the probes enabled us to grasp the various contextual meanings of eating practices among young people. Most participants understand what a healthy diet is and often have a willingness to practice it. However, there were very few participants who were following the practices. We created four types of persona for developing dietary guidelines: healthy eating, emotional eating, convenient eating, and trendy eating. Conclusions Probes and persona were used in order to understand the lives of young adults and develop targeted messages. We hope that this introduction will be helpful to researchers who are looking for new ways of understanding their target population in the field of community nutrition.

Purpose: This study was conducted to evaluate the validity of the Gene-Health application in terms of estimating energy and macronutrients. Methods: The subjects were 98 health adults participating in a weight-control intervention study. They recorded their diets in the Gene-Health application, took photographs before and after every meal on the same day, and uploaded them to the Gene-Health application. The amounts of foods and drinks consumed were estimated based on the photographs by trained experts, and the nutrient intakes were calculated using the CAN-Pro 5.0 program, which was named ‘Photo Estimation’. The energy and macronutrients estimated from the Gene-Health application were compared with those from a Photo Estimation. The mean differences in energy and macronutrient intakes between the two methods were compared using paired t-test. Results: The mean energy intakes of Gene-Health and Photo Estimation were 1,937.0 kcal and 1,928.3 kcal, respectively. There were no significant differences in intakes of energy, carbohydrate, fat, and energy from fat (%) between two methods. The protein intake and energy from protein (%) of the Gene-Health were higher than those from the Photo Estimation. The energy from carbohydrate (%) for the Photo Estimation was higher than that of the Gene-Health. The Pearson correlation coefficients, weighted Kappa coefficients, and adjacent agreements for energy and macronutrient intakes between the two methods ranged from 0.382 to 0.607, 0.588 to 0.649, and 79.6% to 86.7%, respectively. Conclusion The Gene-Health application shows acceptable validity as a dietary intake assessment tool for energy and macronutrients. Further studies with female subjects and various age groups will be needed.