OBJECTIVES: We aimed to assess the serum folate, vitamin B12, and homocysteine status in Korean adolescents and adults using national data. METHODS: Blood samples were collected from participants aged ≥10 years in the Korea National Health and Nutrition Examination Survey 2013-2015. The stored serum samples were used to measure folate, vitamin B12, and homocysteine concentrations. A total of 8,016 participants were included in this analysis. Unweighted descriptive statistics and adjusted geometric means of the B vitamins and homocysteine concentrations were estimated. RESULTS: Females had higher serum folate and vitamin B12 concentrations and lower serum homocysteine concentrations than males. Folate deficiency (<6.8 nmol/L) and hyperhomocysteinemia (>15 μmol/L) were found in 8.6% and 11.8% of males, respectively. Approximately 3% of males had low or marginally low vitamin B12 status (≤221 pmol/L). Folate and vitamin B12 deficiencies and hyperhomocysteinemia were found in <2% of females. Suboptimal folate status was prevalent among adolescents and young adults, while suboptimal vitamin B12 status and hyperhomocysteinemia were relatively higher in older adults. Adjusted mean homocysteine concentrations were sharply decreased from the first to second decile of serum folate in males. CONCLUSIONS In the Korean population, the proportion of males who achieved desirable folate and homocysteine concentrations were lower than those of females. Although most Koreans have adequate vitamin B12, a suboptimal folate status is common, particularly among adolescents and young adults. These findings could establish a foundation for public health initiatives aimed at improving folate levels in the Korean population.

OBJECTIVES: We examined the association between the adherence to dietary guidelines for breast cancer survivors and health-related quality of life in a cross-sectional study of Korean breast cancer survivors. METHODS: A total of 157 women aged 21 to 79 years who had been diagnosed with stage I to III breast cancers according to the American Joint Committee on Cancer (AJCC) and had breast cancer surgery at least 6 months before the baseline were included. We used a Korean version of the Core 30 (C30) and Breast cancer 23 (BR23) module of the European Organization for Research and Treatment Cancer Quality of Life Questionnaire (EORTC-QLQ), both of which have been validated for Koreans. Participants were asked about their adherence to dietary guidelines for breast cancer survivors, suggested by the Korean breast cancer society, using a 5-point Likert scale. We summed dietary guideline adherence scores for each participant and calculated the least squares means of health-related quality of life according to dietary guideline adherence scores using the generalized linear model. RESULTS: Breast cancer survivors who had higher adherence to dietary guidelines for breast cancer survivors had lower constipation scores than those with lower adherence (p for trend=0.01). When we stratified by the stage at diagnosis, this association was limited to those who had been diagnosed with stage II or III breast cancers. Also, sexual functioning scores increased significantly with increasing adherence scores of dietary guidelines among those with stage II or III breast cancers (p for trend < 0.001). However, among those who had been diagnosed with stage I, higher scores of dietary guidelines were associated with higher scores of pain (p for trend=0.03) and breast symptoms (p for trend=0.05). CONCLUSIONS: Our study suggested that the health-related quality of life levels of breast cancer survivors are associated with the adherence to dietary guidelines and may differ by the stage of the breast cancer.
Breast ; Breast Neoplasms* ; Constipation ; Cross-Sectional Studies ; Diagnosis ; Female ; Humans ; Joints ; Least-Squares Analysis ; Linear Models ; Nutrition Policy* ; Quality of Life* ; Surveys and Questionnaires ; Survivors*

OBJECTIVES: We conducted a qualitative study to explore the feasibility of mobile applications for self-monitoring of diet. METHODS: We conducted in-depth and focus group interviews with eight laymen who had used mobile dietary applications and eight experts. Interviews were audio-recorded and analyzed using an open coding method. RESULTS: The qualitative data of our study revealed two key themes: (1) perceptions, opinions and attitudes towards mobile applications of self-monitoring of diet and (2) future directions to improve mobile applications. CONCLUSIONS: Our qualitative study suggested the potential use of mobile applications as a food-tracking and dietary monitoring tool and the need for improved mobile applications for self-monitoring of diet. The results of our study may provide insights into how to technically improve mobile applications for self-monitoring of diet, how to utilize dietary data generated through mobile applications, and how to improve individual's health though mobile applications.
Clinical Coding ; Diet ; Focus Groups ; Methods ; Mobile Applications

OBJECTIVES: We conducted a qualitative study to explore the feasibility of mobile applications for self-monitoring of diet. METHODS: We conducted in-depth and focus group interviews with eight laymen who had used mobile dietary applications and eight experts. Interviews were audio-recorded and analyzed using an open coding method. RESULTS: The qualitative data of our study revealed two key themes: (1) perceptions, opinions and attitudes towards mobile applications of self-monitoring of diet and (2) future directions to improve mobile applications. CONCLUSIONS: Our qualitative study suggested the potential use of mobile applications as a food-tracking and dietary monitoring tool and the need for improved mobile applications for self-monitoring of diet. The results of our study may provide insights into how to technically improve mobile applications for self-monitoring of diet, how to utilize dietary data generated through mobile applications, and how to improve individual's health though mobile applications.
Clinical Coding ; Diet ; Focus Groups ; Methods ; Mobile Applications

BACKGROUND/OBJECTIVES: This study aimed to examine the reproducibility of food frequency questionnaires (FFQs) designed for young female nurses in the Korea Nurses' Health Study. SUBJECTS/METHODS: The reproducibility of web-based, self-administered FFQs was evaluated among 243 Korean female nurses. The first FFQ (FFQ1) was administered from March 2014 to February 2019 and the second FFQ (FFQ2) from November 2019, with a mean interval of 2.8 years between the FFQs (range, 9 months–5.6 years). Pearson and Spearman correlation coefficients (r values) and quartile agreements between FFQ1 and FFQ2 were calculated for intakes of energy, nutrients, and foods. RESULTS: Pearson correlation coefficients ranged from 0.41 to 0.55 (median r = 0.51) for energy and raw nutrients and from 0.16 to 0.46 (median r = 0.36) for energy-adjusted nutrients. Spearman correlation coefficients ranged from 0.25 to 0.72 (median r = 0.41) for food items. The percentages of women who were classified into the same or adjacent quartile were 77% to 84% (median = 82%) for raw nutrients and 69% to 86% (median = 78%) for foods. CONCLUSIONS The results indicated that the web-based FFQ used in the Korea Nurses' Health Study has acceptable reproducibility.

OBJECTIVES: We aimed to examine levels of physical activity, anthropometric features, and health-related quality of life (HRQoL) among Korean breast cancer survivors who reported changes in their diet after diagnosis. METHODS: A total of 380 women who had been diagnosed with stage I to III breast cancer and had breast cancer surgery at least six months before the interview were included. Participants provided information on dietary change after diagnosis, post-diagnostic diet, physical activity, anthropometric measures, and HRQoL through face-to-face interview. We assessed HRQoL levels of breast cancer survivors using a validated Korean version of European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30) and Breast Cancer Module (BR23). We used the logistic regression and generalized linear models to identify the associations of dietary changes in relation with physical activity, anthropometry, and HRQoL. RESULTS: The majority of participants (72.6%) reported that they have changed their diet to a healthier diet after diagnosis. Breast cancer survivors who reported to have change to a healthy diet had higher intakes of vegetables and fruits and lower intakes of red and processed meats, and refined grains than those who did not. Also, survivors with a healthy change in their diet were more likely to engage in physical activity (top vs. bottom tertile: odds ratio [OR], 1.85; 95% confidence interval [95% CI], 1.02-3.36) and have lower body mass index (BMI) (OR, 0.90; 95% CI, 0.82-0.98 for one kg/m² increment in BMI) compared to those who did not. We found that a healthy change in diet was associated with higher scores of physical functioning (p=0.02) and lower scores of constipation (p=0.04) and diarrhea (p=0.006) compared to those who did not. CONCLUSIONS: Healthy changes in diet after breast cancer diagnosis may be associated with lower levels of BMI, and higher levels of physical activity and HRQoL.
Anthropometry* ; Body Mass Index ; Breast Neoplasms* ; Breast* ; Constipation ; Diagnosis* ; Diarrhea ; Diet ; Female ; Fruit ; Humans ; Linear Models ; Logistic Models ; Meat ; Motor Activity* ; Odds Ratio ; Quality of Life* ; Survivors* ; Vegetables

BACKGROUND/OBJECTIVES: The aim of this study was to examine the validity and reproducibility of a food frequency questionnaire (FFQ) developed in Korea for breast cancer survivors. SUBJECTS/METHODS: Ninety-nine breast cancer survivors who completed an FFQ twice and three 3-day dietary records (DRs) between 2016–2017 were included. Energy and 14 nutrient intakes were calculated from FFQs and DRs. To determine the validity of the FFQ, energyadjusted de-attenuated Pearson correlations between two FFQ assessments and the average of the three 3-day DRs were calculated, and to determine reproducibility, energy-adjusted Pearson correlations and degrees of agreement were calculated between the first and second FFQ assessments. RESULTS: Correlation coefficients of validity ranged from 0.29 (protein) to 0.47 (fat) (median value = 0.36) for the FFQ assessment and from 0.20 (riboflavin) to 0.53 (calcium) (median value = 0.37) for the second. Correlation coefficients of reproducibility ranged from 0.22 (sodium) to 0.62 (carbohydrate) (median value = 0.36). Regarding FFQ reproducibilities, percentage classifications of exact agreements for energy-adjusted nutrients ranged from 27.3% (sodium) and 45.5% (fat). A median 76.8% of participants were classified into the same or adjacent quartiles, while a median of 5.6% of participants were classified in extreme quartiles. Bland–Atman plots for the majority of data points of three macronutrients, calcium and vitamins A and C fell within limits of agreement. CONCLUSIONS These results indicated that the newly developed FFQ for Korean breast cancer survivors has acceptable validity and reproducibility as compared with three 3-day DRs collected over a one-year period.

BACKGROUND/OBJECTIVES: This study aimed to use plasma metabolites to identify clusters of breast cancer survivors and to compare their dietary characteristics and health-related factors across the clusters using unsupervised machine learning. SUBJECTS/METHODS: A total of 419 breast cancer survivors were included in this crosssectional study. We considered 30 plasma metabolites, quantified by high-throughput nuclear magnetic resonance metabolomics. Clusters were obtained based on metabolites using 4 different unsupervised clustering methods: k-means (KM), partitioning around medoids (PAM), self-organizing maps (SOM), and hierarchical agglomerative clustering (HAC). The t-test, χ2 test, and Fisher’s exact test were used to compare sociodemographic, lifestyle, clinical, and dietary characteristics across the clusters. P-values were adjusted through a false discovery rate (FDR). RESULTS: Two clusters were identified using the 4 methods. Participants in cluster 2 had lower concentrations of apolipoprotein A1 and large high-density lipoprotein (HDL) particles and smaller HDL particle sizes, but higher concentrations of chylomicrons and extremely large very-low-density-lipoprotein (VLDL) particles and glycoprotein acetyls, a higher ratio of monounsaturated fatty acids to total fatty acids, and larger VLDL particle sizes compared with cluster 1. Body mass index was significantly higher in cluster 2 compared with cluster 1 (FDR adjusted-PKM < 0.001; PPAM = 0.001; PSOM < 0.001; and PHAC = 0.043). CONCLUSION The breast cancer survivors clustered on the basis of plasma metabolites had distinct characteristics. Further prospective studies are needed to investigate the associations between metabolites, obesity, dietary factors, and breast cancer prognosis.

BACKGROUND/OBJECTIVES: This study aimed to use plasma metabolites to identify clusters of breast cancer survivors and to compare their dietary characteristics and health-related factors across the clusters using unsupervised machine learning. SUBJECTS/METHODS: A total of 419 breast cancer survivors were included in this crosssectional study. We considered 30 plasma metabolites, quantified by high-throughput nuclear magnetic resonance metabolomics. Clusters were obtained based on metabolites using 4 different unsupervised clustering methods: k-means (KM), partitioning around medoids (PAM), self-organizing maps (SOM), and hierarchical agglomerative clustering (HAC). The t-test, χ2 test, and Fisher’s exact test were used to compare sociodemographic, lifestyle, clinical, and dietary characteristics across the clusters. P-values were adjusted through a false discovery rate (FDR). RESULTS: Two clusters were identified using the 4 methods. Participants in cluster 2 had lower concentrations of apolipoprotein A1 and large high-density lipoprotein (HDL) particles and smaller HDL particle sizes, but higher concentrations of chylomicrons and extremely large very-low-density-lipoprotein (VLDL) particles and glycoprotein acetyls, a higher ratio of monounsaturated fatty acids to total fatty acids, and larger VLDL particle sizes compared with cluster 1. Body mass index was significantly higher in cluster 2 compared with cluster 1 (FDR adjusted-PKM < 0.001; PPAM = 0.001; PSOM < 0.001; and PHAC = 0.043). CONCLUSION The breast cancer survivors clustered on the basis of plasma metabolites had distinct characteristics. Further prospective studies are needed to investigate the associations between metabolites, obesity, dietary factors, and breast cancer prognosis.

BACKGROUND/OBJECTIVES: This study aimed to use plasma metabolites to identify clusters of breast cancer survivors and to compare their dietary characteristics and health-related factors across the clusters using unsupervised machine learning. SUBJECTS/METHODS: A total of 419 breast cancer survivors were included in this crosssectional study. We considered 30 plasma metabolites, quantified by high-throughput nuclear magnetic resonance metabolomics. Clusters were obtained based on metabolites using 4 different unsupervised clustering methods: k-means (KM), partitioning around medoids (PAM), self-organizing maps (SOM), and hierarchical agglomerative clustering (HAC). The t-test, χ2 test, and Fisher’s exact test were used to compare sociodemographic, lifestyle, clinical, and dietary characteristics across the clusters. P-values were adjusted through a false discovery rate (FDR). RESULTS: Two clusters were identified using the 4 methods. Participants in cluster 2 had lower concentrations of apolipoprotein A1 and large high-density lipoprotein (HDL) particles and smaller HDL particle sizes, but higher concentrations of chylomicrons and extremely large very-low-density-lipoprotein (VLDL) particles and glycoprotein acetyls, a higher ratio of monounsaturated fatty acids to total fatty acids, and larger VLDL particle sizes compared with cluster 1. Body mass index was significantly higher in cluster 2 compared with cluster 1 (FDR adjusted-PKM < 0.001; PPAM = 0.001; PSOM < 0.001; and PHAC = 0.043). CONCLUSION The breast cancer survivors clustered on the basis of plasma metabolites had distinct characteristics. Further prospective studies are needed to investigate the associations between metabolites, obesity, dietary factors, and breast cancer prognosis.