BackgroundBecause the world population is aging, it has become increasingly important to focus on and meet the healthcare needs of elderly individuals. This study aims to evaluate the relationships among common symptoms experienced by the elderly, including fatigue, pain, sleep disturbance, indigestion, and depression/anger/anxiety, and to assess how these symptoms affect health-related quality of life (HRQoL) in the elderly population after adjusting for sociodemographic characteristics and diagnosed diseases.MethodsIn a cross-sectional study conducted in 2014 in a rural area of Korea, we extracted data on 1328 elderly individuals aged 60 years or older. Their HRQoL was assessed using the EuroQol Five-Dimension (EQ-5D) questionnaire. The pairwise associations between each symptom and the influence of the symptoms on HRQoL were measured using logistic regression and multiple regression analysis.ResultsEach symptom was positively correlated with the other symptoms. The strongest association was observed between fatigue and pain (adjusted odds ratio = 8.127), and the weakest correlation was observed between sleep and indigestion (adjusted odds ratio = 2.521). Of the individuals experiencing symptoms other than sleep disturbance, those who reported comorbid symptoms tended to report higher symptom severity and a higher prevalence of symptoms persisting for ≥ 3 days compared with individuals who reported only one symptom. The number of symptoms was significantly correlated with the EQ-5D index (Spearman correlation coefficient = −0.370, p < 0.01) and the EQ Visual Analog Scale (EQ VAS) scores (Spearman correlation coefficient = −0.226, p < 0.01). Fatigue, pain, and sleep disturbance showed negative effects on all dimensions of EQ-5D. In multiple regression analysis, fatigue (β = −0.073, p < 0.01), pain (β = −0.140, p < 0.01), sleep disturbance (β = −0.061, p < 0.05), and depression/anger/anxiety (β = −0.065, p < 0.05) showed significant independent effects on the EQ-5D index when we adjusted for socioeconomic characteristics and diagnosed diseases.ConclusionsFatigue, pain, sleep disturbance, and depression/anger/anxiety were correlated with one another, and they presented significant independent effects on the HRQoL of elderly individuals. Thus, multidisciplinary healthcare programs are required to address these common symptoms.

BackgroundThe trend toward patient- or consumer-centered healthcare has been accelerated by advances in technology, consumer empowerment, and a shift from infectious to chronic diseases. The purpose of this study was to examine the growing self-care market by analyzing self-care patterns.MethodsWe conducted a cross-sectional, web-based survey involving adults from nine major cities in the UK, the USA, Australia, and Japan. This study examined the extent and frequency of self-care, self-care expenditure, sources of self-care information, and reasons for self-care in each country.ResultsThe results showed that the prevalence of self-care was highest in Japan (54.9%), followed by the UK (43.1%), the USA (42.5%), and Australia (40.4%). The primary reason for practicing self-care was “to manage my healthcare myself” (cited by 45.7%, 59.5%, 49.2%, and 4.1% of participants in Australia, Japan, the UK, and the USA, respectively). Significant linear associations were observed between age and the prevalence of self-care in all countries (p < 0.05), indicating that self-care prevalence decreased with age in the UK, the USA, and Australia, and increased with age in Japan. The frequency with which self-care was practiced was positively correlated with age in the USA (p < 0.05), Australia (p < 0.01), and Japan (p < 0.05). In addition to acquaintances, internet search engines and information obtained from pharmacies were considered reliable and widely used sources of self-care information.ConclusionWhen developing self-care products or services, healthcare providers and policymakers should consider self-care patterns.

BackgroundComplementary and alternative medicine treatment for insomnia has been sought due to the possible adverse effects of conventional pharmacotherapies. We performed a preliminary evaluation of the feasibility of using, and of the effect of a herbal tea (HT002), based on Traditional East Asian Medicine, in mild-to-moderate insomnia.MethodsPatients (n = 40) with mild-to-moderate insomnia were randomized to the HT002 (n = 20) or waitlist (n = 20) groups. The HT002 group consumed HT002 twice daily for 4 weeks. Outcomes were assessed using the Insomnia Severity Scale (ISI), Pittsburgh Sleep Quality Index (PSQI), and 12-item Short Form Health Survey (SF-12) at baseline and after 4 and 8 weeks.ResultsThe ISI score differences from baseline at weeks 4 and 8 were significantly greater in the HT002 than that in the waitlist group (week 4: −4.0 ± 0.8 vs. −0.4 ± 0.8, p < 0.05; week 8: −4.8 ± 0.7 vs. −0.9 ± 0.7, p < 0.05). Changes in PSQI and SF-12 physical component scores in the HT002 group were significantly greater at weeks 4 and 8 (p < 0.05), while SF-12 mental component scores were only significantly larger at 4 weeks (p < 0.05). HT002 was well-tolerated, with only one (5.0%) dropout, and no significant mean liver and renal function test changes post-treatment.ConclusionOur preliminary results suggest that a 4-week treatment with HT002 may reduce the severity of insomnia symptoms and improve the quality of life. Further studies devoid of the limitations of our protocol may provide stronger conclusions.Trial registrationClinical Research Information Service (CRIS), KCT0001900.

BackgroundThis study aimed to investigate the extent to which Korean Medicine doctors consider cold and heat pattern identification when prescribing herbal treatment for a disease.MethodsA survey was sent by e-mail to 15,841 members of the Association of Korean Medicine for whom member information was registered. Of these, 699 (4.4%) members participated in the survey. The survey included questions regarding the frequency of use of cold and heat pattern identification in deciding a herbal treatment prescription, the diseases for which cold and heat pattern identification-related herbal treatment was most efficacious, the type of herbal treatment prescribed, and the duration of the treatment.ResultsOf the 699 respondents, 591 (84.5%) reported that they considered cold and heat when prescribing herbal treatment. The diseases for which consideration of cold and heat patterns was effective were, in order, menopausal disorder (124, 18.3%), chronic rhinitis (98, 14.5%), dyspepsia (94, 13.9%), hwa-byung (92, 13.6%), diarrhea (83, 12.3%), dysmenorrhea (61, 9.0%), headache (59, 8.7%), inflammation in the digestive tract (58, 8.6%), coldness in hands and feet (58, 8.6%), and atopic dermatitis (55, 8.1%). The typical treatment duration differed widely for different diseases: atopic dermatitis was most frequently treated for >2 months (38, 34.5%), whereas diarrhea was most frequently treated for ≤ 10 days (73, 43.6%).ConclusionThese findings indicate that cold and heat pattern identification is a useful tool employed by Korean Medicine doctors. This study may provide a basis for clinical research investigating the effect of pattern identification-based treatment of diseases.

Background. Korean medicine (KM) patterns such as cold, heat, deficiency, and excess patterns have been associated with alterations of resting metabolic rate (RMR). However, the association of KM patterns with accurately measured body metabolic rate has not been investigated. Methods. Data on cold (CP), heat (HP), spleen-qi deficiency (SQDP), and kidney deficiency (KDP) patterns were extracted by a factor analysis of symptoms experienced by 954 participants. A multiple regression analysis was conducted to determine the association between KM patterns and RMR measured by an indirect calorimeter. Results. The CP and SQDP scores were higher and the HP score was lower in women. The HP and SQDP scores decreased with age, while KDP scores increased with age. A multiple regression analysis revealed that CP and SQDP scores were negatively associated with RMR independently of gender and age, and the CP remained significantly and negatively associated with RMR even after adjustment for fat-free mass. Conclusions. The underlying pathology of CP and SQDP might be associated with the body's metabolic rate. Further studies are needed to investigate the usefulness of RMR measurement in pattern identification and the association of CP and SQDP with metabolic disorders.

Background. Machine learning may be a useful tool for predicting metabolic syndrome (MetS), and previous studies also suggest that the risk of MetS differs according to Sasang constitution type. The present study investigated the development of MetS prediction models utilizing machine learning methods and whether the incorporation of Sasang constitution type could improve the performance of those prediction models. Methods. Participants visiting a medical center for a health check-up were recruited in 2005 and 2006. Six kinds of machine learning were utilized (K-nearest neighbor, naive Bayes, random forest, decision tree, multilayer perceptron, and support vector machine), as was conventional logistic regression. Machine learning-derived MetS prediction models with and without the incorporation of Sasang constitution type were compared to investigate whether the former would predict MetS with higher sensitivity. Age, sex, education level, marital status, body mass index, stress, physical activity, alcohol consumption, and smoking were included as potentially predictive factors. Results. A total of 750/2,871 participants had MetS. Among the six types of machine learning methods investigated, multiplayer perceptron and support vector machine exhibited the same performance as the conventional regression method, based on the areas under the receiver operating characteristic curves. The naive-Bayes method exhibited the highest sensitivity (0.49), which was higher than that of the conventional regression method (0.39). The incorporation of Sasang constitution type improved the sensitivity of all of the machine learning methods investigated except for the K-nearest neighbor method. Conclusion. Machine learning-derived models may be useful for MetS prediction, and the incorporation of Sasang constitution type may increase the sensitivity of such models.

Patients with amyotrophic lateral sclerosis (ALS) sometimes consider complementary and alternative medicine (CAM) because of ineffective treatment. This study investigated the prevalence and utilization pattern of CAM among patients with ALS in South Korea. Participants were recruited through homecare services for mechanical ventilation in South Korea. This study comprised a face-to-face cross-sectional survey with staff members available to address any queries. Fifty-five participants were included; all had used >1 CAM treatment option for ALS symptoms. Dietary treatments were most common, followed by functional food and massages. Most participants had obtained relevant information from family members or friends. The main reason for CAM use was an expectation that symptoms will improve with CAM; most patients were unsure of the effects. CAM use was previously discontinued by the majority of patients because of unsatisfactory effects. The mean expenditure on CAM was 288,385.28 ± 685,265.14 won per month, and the mean duration of CAM use was 11.54 ± 20.09 months. The results indicate that there is a high prevalence of CAM use among ALS patients. Healthcare providers should inquire about CAM use and openly provide accurate CAM information. Further evidence of CAM efficacy is required, as is specific guidance for consulting ALS patients regarding CAM.

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