We developed two distinct forest therapy programs (FTPs) and compared their effects on dementia prevention and related health problems for older adults. One was focused on Qigong practice in the forest (QP) and the other involved active walking in the forest (WP). Both FTPs consisted of twelve 2-h sessions over six weeks and were conducted in an urban forest. We obtained data from 25, 18, and 26 participants aged 65 years or above for the QP, WP, and control groups, respectively. Neuropsychological scores via cognition (MoCA), geriatric depression (GDS) and quality of life (EQ-5D), and electrophysiological variables (electroencephalography, bioimpedance, and heart rate variability) were measured. We analyzed the intervention effects with a generalized linear model. Compared to the control group, the WP group showed benefits in terms of neurocognition (increases in the MoCA score, and alpha and beta band power values in the electroencephalogram), sympathetic nervous activity, and bioimpedance in the lower body. On the other hand, the QP group showed alleviated depression and an increased bioimpedance phase angle in the upper body. In conclusion, both active walking and Qigong in the forest were shown to have distinctive neuropsychological and electrophysiological benefits, and both had beneficial effects in terms of preventing dementia and relieving related health problems for elderly individuals.

This is an Open Access article distributed under the terms of the Creative Commons Attribution NoDerivs License. (http://creativecommons.org/licenses/by-nd/4.0)If the original work is properly cited and retained without any modification or reproduction, it can be used and re-distributed in any format and medium. Purpose: To identify the effects of a smart program for the patients who underwent percutaneous coronary intervention (SP-PCI) on coronary disease-related knowledge, health behaviors, and quality of life. Methods: A nonequivalent control group with a non-synchronized design was utilized and 48 participants (experimental=22, control=26) were recruited from a university hospital in Gyeongsang area from May to December, 2016. The 12-week SP-PCI consisted of self-study of health information using smart phone applications (1/week), walking exercise (>5/week) using smart band, feedback using Kakao talk (2/week), and telephone counseling (1/week). Patients in the control group received usual care from their primary health care providers and a brief health education with basic self-management brochure after the PCI. Data were analyzed using the SPSS 21.0 program through descriptive statistics, c 2 test, and t-test. Results: After the 12-week SP-PCI, the experimental group showed higher levels of coronary disease-related knowledge (t=2.43, p=.019), heart-related health behaviors (t=5.96, p<.001), regular exercise (Z=-4.47, p<.001), and quality of life-MCS (t=3.04, p=.004) and showed lower levels of stress (Z=-3.53, p<.001) and sodium intake (t=-4.43, p<.001) than those in the control group. There were no significant group differences in medication adherence and food intake in total energy, lipids, and cholesterol. Conclusion: The suggested SP-PCI provided easy access and cost-effective intervention for patients after PCI and improved their knowledge of the disease, performance of health behaviors, and quality of life. Further study with a wider population is needed to evaluate the effects of SP-PCI on disease recurrence and quality of life for patients after PCI.

Background: Since chronic kidney disease (CKD) is caused by genetic and environmental factors, biomarker development through metabolomic analysis, which reflects gene-derived downstream effects and host adaptation to the environment, is warranted. Methods: We measured the metabolites in urine samples collected from 789 patients at the time of kidney biopsy and from urine samples from 147 healthy subjects using nuclear magnetic resonance (NMR). The composite outcome was defined as a 30% decline in estimated glomerular filtration rate (eGFR), doubling of serum creatinine levels, or end-stage kidney disease. Results: Among the 28 candidate metabolites, we identified 7 metabolites showing 1) good discrimination between healthy controls and patients with stage 1 CKD and 2) a consistent change in pattern from controls to patients with advanced-stage CKD. Among the 7 metabolites, betaine, choline, glucose, fumarate, and citrate showed significant associations with the composite outcome after adjustment for age, sex, eGFR, the urine protein-creatinine ratio, and diabetes. Furthermore, adding choline, glucose, or fumarate to traditional biomarkers, including eGFR and proteinuria, significantly improved the ability of the net reclassification improvement (P<0.05) and integrated discrimination improvement (P<0.05) to predict the composite outcome. Conclusion: Urinary metabolites, including betaine, choline, fumarate, citrate, and glucose, were found to be significant predictors of the progression of CKD. As a signature of kidney injury-related metabolites, it would be warranted to monitor to predict the renal outcome.