An anti-inflammatory diet has many beneficial effects on cardiometabolic diseases. Constitution type of traditional Korean medicine can predict cardiometabolic risk factors. We examined the relationship between vegetable consumption and the high-sensitive C-reactive protein (hs-CRP) level on cardiometabolic risk factors in Korean adults by constitution types. Data from 1,983 eligible participants (mean age, 44.3 years) were included in the present cross-sectional study. The inflammatory status of the participants was categorized into low- (<3.0 mg/L) or high-risk (≥3.0 mg/L) groups based on their constitution types. Cardiometabolic risk factors (abdominal obesity, elevated triglycerides, reduced high-density lipoprotein-cholesterol, elevated blood pressure, elevated fasting plasma glucose, and ≥2 concurrent cardiovascular diseases (CVDs) risk factors) and dietary assessment of the participants were assessed. A total of 11.1% of Tae-eumin (TE) and 4.9% of non-TE groups had a higher hs-CRP level (TE: 6.6 ± 0.2, non-TE: 8.4 ± 0.3) than a low hs-CRP level TE and non-TE (TE: 0.9 ± 0.1, non-TE: 0.6 ± 0.1). Vegetable consumption of <91.5 g/day was highly associated with a high-risk hs-CRP level (adjusted odds ratio (ORs): second tertile (T2): 2.290, (95% confidence interval (CI): 1.285–4.082); first tertile (T1): 2.474 (95% CI: 1.368–4.475), ) compared with that of the highest (T3) in TE. Low (T1 and T2) vegetable consumption was associated with a 54–63% increased prevalence of more than two concurrent CVDs risk factors compared with that of the highest in the TE group . Higher vegetable consumption greatly decreased the prevalence of CVDs risk factors by 63–86% in the low-risk and high-risk hs-CRP TE groups. Our results highlight the cardioprotective effects of higher consumption of vegetables in Korean adults with TE. Evidence-based clinical risk factor management and multifaceted approaches at the community and population levels targeting prevention in high-burden groups are recommended to reduce the premature mortality attributed to CVD.

Dietary protein sources and protein adequacy are crucial modulators of muscle quality and body composition. We investigated the association between dietary protein sources (and their adequacy) and body composition and the risk of sarcopenic obesity (SO) in South Korean populations. The participants (n = 1967) were classified into SO, obese, sarcopenia, and normal groups. A cross-sectional survey was conducted using the KS-15 questionnaire, short-form food frequency questionnaire, and anthropometric measurements. The percentage of body fat (male: 35.36 ± 0.51%; female: 44.14 ± 0.36%) was significantly high, while appendicular skeletal muscle (ASM; male: 36.39 ± 0.30%, female: 30.32 ± 0.19%) was low in the SO group. Beef and pork consumption was negatively associated with ASM (%) but positively associated with body fat (%) in the normal group and positively associated with ASM (kg/m²: beta = 0.002, p = 0.02) and BFM (kg: beta = 0.012, p = 0.03) in the SO group, respectively. The highest quintile (Q5: 173.6 g/day) showed a decreased risk of SO prevalence (AORs: 0.46, CI: 0.22–0.94) compared with that in the lowest quintile (Q1: 21.6 g/day) among the people with inadequacy protein intake. Daily poultry and egg intake was positively linked with body composition in the participants with SO, while red meat showed a negative effect on imbalanced body composition in participants in the normal and SO groups. Furthermore, a lower intake of poultry and eggs was strongly associated with SO prevalence in people who consumed inadequate amounts of daily dietary protein.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Mobile health (mHealth) is a major source of health management systems such as health promotion behavior, chronic disease, and mental illness. Moreover, mHealth, a new model of digital healthcare in need of change due to the COVID-19 pandemic, will increase and demand for use worldwide. Accordingly, interest in health care in everyday life and the importance of mobile health are growing. Objective: We developed a MibyeongBogam (MBBG) application that evaluates the user’s subhealth status by use of a smartphone and provides a health management method based on that user’s subhealth status for use in everyday life. The primary objective of this study was to compare health status awareness after the use of the MBBG application between the intervention and control groups, and to evaluate the application’s practicality. Methods: This study was a prospective, open-label, parallel group, randomized controlled trial as an intervention for MBBG. The study was conducted at two hospitals in Korea with 150 healthy people in their 30s and 40s, at a 1:1 allocation ratio. Participants visited the hospital three times: pre-intervention, intermediate visit six weeks after intervention, and final visit 12 weeks after intervention. Key endpoints were measured at the first visit before intervention and at 12 weeks after intervention. The primary outcome was the awareness of subhealth status and secondary outcomes were health status, health-promoting behaviors, and motivation for healthy behaviors. Results: The primary outcome, subhealth awareness, tended to slightly increase in both groups after the uncompensated intervention, but there was no significant difference between groups (MBBG group = 23.69±0.25, control group = 23.1±0.25, p=0.088). In the case of secondary outcomes, only some variables of subhealth status showed significant differences between the two groups after intervention, and the intervention group showed an improvement in the total score of subhealth (p = 0.025), sleep disturbance (p = 0.024), depression (p = 0.003), anger (p = 0.01), and anxiety symptoms (p = 0.009) compared to the control group. Conclusions: In this study, the MBBG application showed positive potential for improving the health, especially the mental health, of individuals without particular health problems. However, the effects of the application on health-promoting behaviors were not clearly evaluated. Therefore, further studies to assess improvements in health after the use of personalized health management programs provided by the MBBG application would need to be performed. It is thought that the MBBG application would be useful for the general public, who are not diagnosed with a disease but cannot enjoy an optimal daily life due to discomfort, to seek strategies that can improve their health. Clinical Trial: Clinical Research Information Service, KCT0003488. (https://cris.nih.go.kr/cris/search/search_result_st01.jsp?seq=14379)

Sleep disturbances are associated with cold hypersensitivity (CH) and characterized by excessive cold sensation in specific body parts and cold thermal discomfort. This study investigated the effects of short-term sleep restriction followed by a recovery phase on subjective health status, inflammation, and lipid metabolism in different types of CH. A total of 118 healthy adults aged 35 to 44 years without sleep disturbances were enrolled. Participants underwent 4-hour sleep restrictions per day for 3 days at a hospital and then returned to their daily lives for 4 days of rest. CH was assessed using a structured questionnaire with eight characteristic symptoms. A questionnaire and blood tests were administered baseline, after sleep restriction, and follow-up to assess cortisol, lipid profiles, and self-reported stress and quality of life (QOL). Participants were divided into CH (44.1%) and non-CH (55.9%) groups. The CH group showed increased stress, impaired QOL, and decreased low-density lipoprotein-cholesterol (LDL-C) levels compared to the non-CH group after sleep restriction. The variance for QOL (effect size = 0.07), subjective stress (effect size = 0.053), and LDL-C (effect size = 0.029) among time points depended on the group. Short-term sleep restriction was associated with deterioration of subjective health and reduced lipid metabolism; such changes were more evident in the CH group. Our findings suggest the need to consider an individual’s CH status to assess the clinical risk associated with insufficient sleep.

Sasang constitutional medicine is a traditional customized medicine in Korea that classifies people into four types: Taeeumin (TE), Taeyangin (TY), Soeumin (SE), and Soyangin (SY). This study explored whether Sasang constitution (SC) types combined with general obesity could be risk factors for prediabetes mellitus (pre-DM). This study was cross-sectional and was conducted from November 2007 to July 2011 in 23 Korean medical clinics. In total, 2185 eligible subjects participated. A t test, one-way ANOVA with Scheffé’s post hoc analysis, the chi-square test and multinomial logistic regression were used. Significance was indicated by p < 0.05. The numbers of participants with normal fasting plasma glucose (FPG) levels and pre-DM were 405 (75.3%) and 133 (24.7%) in the SE, 516 (70.3%) and 218 (29.7%) in the SY, and 590 (64.6%) and 323 (35.4%) in the TE (p < 0.001) groups, respectively. There was a significant difference in the proportion of each SC type among people with pre-DM and normal FPG levels in the normal BMI group. The odds ratios (ORs) of the TE type were significantly different from those of the SE type in the crude and Model 1. The distribution of the normal FPG and pre-DM individuals between the obese and normal BMI groups only for the SY type was significantly different. The SY type combined with general obesity had a higher OR (1.846, 95% CI 1.286–2.649) than that combined with normal BMI among participants with pre-DM, and this higher OR remained after adjusting for covariates (OR, 1.604, 95% CI, 1.093–2.354). This study revealed that the TE type might be a risk factor for pre-DM in the normal BMI group, and the SY type with general obesity could be a risk factor for pre-DM compared with the SY type with normal BMI. Accordingly, SC and BMI should be considered when managing pre-DM. To clarify the risk of SC and BMI, further study including epigenetic factors is needed.

Objectives: Facial diagnosis is an important part of clinical diagnosis in traditional East Asian Medicine. In this paper, we proposed a model to quantitatively classify cold sensitivity using a fully automated facial image analysis system.Methods: We investigated cold sensitivity in 452 subjects. Cold sensitivity was determined using a questionnaire and the Cold Pattern Score (CPS) was used for analysis. Subjects with a CPS score below the first quartile (low CPS group) belonged to the cold non-sensitivity group, and subjects with a CPS score above the third quartile (high CPS group) belonged to the cold sensitivity group. After splitting the facial images into train/validation/test sets, the train and validation set were input into a convolutional neural network to learn the model, and then the classification accuracy was calculated for the test set.Results: The classification accuracy of the low CPS group and high CPS group using facial images in all subjects was 76.17%. The classification accuracy by sex was 69.91% for female and 62.86% for male. It is presumed that the deep learning model used facial color or facial shape to classify the low CPS group and the high CPS group, but it is difficult to specifically determine which feature was more important.Conclusions: The experimental results of this study showed that the low CPS group and the high CPS group can be classified with a modest level of accuracy using only facial images. There was a need to develop more advanced models to increase classification accuracy.