Objective: To provide scientific evidence supporting the efficacy of forest bathing as a natural therapy for human hypertension.
Methods: Twenty-four elderly patients with essential hypertension were randomly divided into two groups of 12. One group was sent to a broad-leaved evergreen forest to experience a 7-day/7-night trip, and the other was sent to a city area in Hangzhou for control. Blood pressure indicators, cardiovascular disease-related pathological factors including endothelin-1, homocysteine, renin, angiotensinogen, angiotensin II, angiotensin II type 1 receptor, angiotensin II type 2 receptor as well as inflammatory cytokines interleukin-6 and tumor necrosis factor α were detected. Meanwhile, profile of mood states (POMS) evaluation was used to assess the change of mood state of subjects. In addition, the air quality in the two experimental sites was monitored during the 7-day duration, simultaneously.
Results: The baselines of the indicators of the subjects were not significantly different. Little alteration in the detected indicators in the city group was observed after the experiment. While subjects exposed to the forest environment showed a significant reduction in blood pressure in comparison to that of the city group. The values for the bio-indicators in subjects exposed to the forest environment were also lower than those in the urban control group and the baseline levels of themselves. POMS evaluation showed that the scores in the negative subscales were lowered after exposure to the forest environment. Besides, the air quality in the forest environment was much better than that of the urban area evidenced by the quantitative detection of negative ions and PM10 (particulate matter < 10 μm in aerodynamic diameter).
Conclusion: Our results provided direct evidence that forest bathing has therapeutic effects on human hypertension and induces inhibition of the renin-angiotensin system and inflammation, and thus inspiring its preventive efficacy against cardiovascular disorders.
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http://dx.doi.org/10.1016/j.jjcc.2012.08.003 | DOI Listing |
Environ Health Perspect
January 2025
Centre for Environment, Fisheries and Aquaculture Science (CEFAS), Weymouth, UK.
Background: Environmental change in coastal areas can drive marine bacteria and resulting infections, such as those caused by , with both foodborne and nonfoodborne exposure routes and high mortality. Although ecological drivers of in the environment have been well-characterized, fewer models have been able to apply this to human infection risk due to limited surveillance.
Objectives: The Cholera and Other Illness Surveillance (COVIS) system database has reported infections in the United States since 1988, offering a unique opportunity to both explore the forecasting capabilities machine learning could provide and to characterize complex environmental drivers of infections.
Science
January 2025
School of Informatics, Computing and Cyber Systems, Northern Arizona University, Flagstaff, AZ, USA.
Environ Monit Assess
January 2025
School of Earth Sciences, East China University of Technology, Nanchang, 330013, China.
Investigating the effects of urbanization at the county level on the balance of the carbon budget is essential for progress toward achieving "dual carbon" objectives at the county scale. Based on land use and economic data, this study elucidates the spatiotemporal evolution of urbanization and carbon budget balance ratio in 84 counties in Jiangxi Province from 1980 to 2020. Optimal geographic detectors and geographically weighted random forests were used to explore the impact of urbanization on the carbon budget balance ratio.
View Article and Find Full Text PDFIntegr Environ Assess Manag
January 2025
Programa de Biologia Marinha e Ambientes Costeiros, Universidade Federal Fluminense (PBMAC-UFF), Niterói, Rio de Janeiro, Brazil.
Road activities are recognized sources of pollution that affect the hydrochemistry of nearby water bodies. This study evaluated the Water Quality Monitoring Program in the Soberbo and Iconha rivers in the Guapi-Macacu watershed, which is affected by the BR-116 highway. The Rio-Teresópolis Concessionaire from 2009 to 2016 carried out quarterly sampling.
View Article and Find Full Text PDFFront Public Health
January 2025
Karolinska Institutet, Department of Medicine Solna, Division of Clinical Epidemiology, Stockholm, Sweden.
Background: Mexico has one of the highest global incidences of paediatric overweight and obesity. Public health interventions have shown only moderate success, possibly from relying on knowledge extracted using limited types of statistical data analysis methods.
Purpose: To explore if multimodal machine learning can enhance identifying predictive features from obesogenic environments and investigating complex disease or social patterns, using the Mexican National Health and Nutrition Survey.
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