The effects of forest therapy on public mental health and circular economy: A policy support model in Japan.

Background: Forest therapy has gained popularity in Japan and even other nations/regions due to its health benefits. In addition, forest therapy has contributed to the development of circular economy and industrial upgrading. Japanese successful practice can serve as a model for other countries in the Asia-Pacific region. To this end, the aim of this study was to determine whether forest therapy can improve the whole well-being of the participants and has a positive effect on the development of circular economy in the region. Methods: Both empirical and inductive research methods were used; empirical approach was conducted to perform comparative analysis of regional data that was retrieved from the research project of Japanese Forestry Agency in 2015. Specifically, the efficacy of forest therapy on physical (blood glucose, blood pressure, body weight) and mental (sleep quality e.g.,) health outcomes among 815 participants was investigated. Regional data are from the statistics of Iiyama City from 1990 to 2005. After the concept of forest therapy became popular in the late 1990s, this element had a great positive impact on the economic benefits of Ishiyama City and other major forest scenic areas. We summarize and analyze a series of policies made by relevant departments of the Japanese government in the years from 2019 to 2021 to promote forest therapy and related circular industry development. Results: Significant (pre-to-post participation) changes in physical measure was observed. Firstly, mean weight of those overweight participants decreased across three different time points (pre-test/enrollment = 79.7 kg, 3-month participation = 77.2, and 6-month participation = 76.8 kg), while overall mean weight of the participants decreased to 61, 60.5, and 60.4 kg, respectively. Secondly, Participant with normal weight showed a decrease on mean HbA1C (from 6.09 to 6.06) at Week 24, while overweight participants demonstrated a slight change 6.03-6.01 after 6 months the average HOMA-IR for overweight participants decreased from 3.5 to 2.5 at Week 24, while participants with normal weight demonstrated a decrease from 2.2 to 1.7 at Week 24. Forest Therapy has emerged in Japan since Mid-1990s and has attracted a large number of tourists all over the world due to its unique health benefits. Conclusion: Forest therapy in Japan has positive effects on whole well-being of Japanese residents and it has helped public mental health promotion and economic growth. Under the guidance and support of government policies, it can promote the development of circular economy and industrial transformation and set a model of Japanese forest therapy development for other countries in the Asia-Pacific region.

Assessment of Use and Fit of Face Masks Among Individuals in Public During the COVID-19 Pandemic in China.

Importance: Face masks are recommended to prevent transmission of coronavirus disease 2019 (COVID-19); however, there is scarce evidence on their protection efficacy and ways to improve it. Objective: To determine the proportion of improper face mask use, the factors associated with face mask protection efficacy, and ways to improve efficacy. Design, Setting, and Participants: This population-based cross-sectional study was conducted in China from July to August 2020 in 5 kinds of public places. Participants included convenience samples of individuals wearing face masks and able to taste the check solution. Exposures: Demographic and socioeconomic characteristics, including sex, age, and education level; information on face mask model and the worn duration was recorded. Main Outcomes and Measures: The main outcome as airtightness, assessed by detecting face-to-face mask gaps, movement of cotton fiber placed at the face mask edges, and using a qualitative fit test with a bitter solution spray. Masks were further assessed for whether sealing the upper face mask edge with an adhesive tape strip was associated with improved face mask airtightness. Results: Among 6003 face mask wearers enrolled, the mean (SD) age of participants was 31.1 (13.7) years, and 3047 participants (50.8%) were female. The first qualitative fit test found air leakage in 2754 participants (45.9%; 95% CI, 44.6%-47.1%), which was mostly attributable to gaps at the upper face mask edge. After sealing the upper face mask edge with an adhesive tape strip, 69.7% (95% CI, 68.0%-71.5%) of masks that had exhibited leakage became airtight in the second qualitative fit test, and the rate of airtightness reached 96.2% (95% CI, 95.4%-96.8%) in a third qualitative fit test after new surgical face masks with tape on the upper edge were provided to those who had not converted initially. The tape was well tolerated; overall, 6 participants (1.2%) reported a rash and 24 participants (5.8%) reported significant discomfort. Conclusions and Relevance: In this study of face mask fit among participants in China, although most people used face masks in public places, compromised protection due to suboptimal airtightness was common. The simple approach of sealing the upper edge of the face mask with an adhesive tape strip was associated with substantially improved its airtightness.

Assessment of Multifactor Gene-Environment Interactions and Ovarian Cancer Risk: Candidate Genes, Obesity, and Hormone-Related Risk Factors.

BACKGROUND: Many epithelial ovarian cancer (EOC) risk factors relate to hormone exposure and elevated estrogen levels are associated with obesity in postmenopausal women. Therefore, we hypothesized that gene-environment interactions related to hormone-related risk factors could differ between obese and non-obese women. METHODS: We considered interactions between 11,441 SNPs within 80 candidate genes related to hormone biosynthesis and metabolism and insulin-like growth factors with six hormone-related factors (oral contraceptive use, parity, endometriosis, tubal ligation, hormone replacement therapy, and estrogen use) and assessed whether these interactions differed between obese and non-obese women. Interactions were assessed using logistic regression models and data from 14 case-control studies (6,247 cases; 10,379 controls). Histotype-specific analyses were also completed. RESULTS: SNPs in the following candidate genes showed notable interaction: IGF1R (rs41497346, estrogen plus progesterone hormone therapy, histology = all, P = 4.9 × 10(-6)) and ESR1 (rs12661437, endometriosis, histology = all, P = 1.5 × 10(-5)). The most notable obesity-gene-hormone risk factor interaction was within INSR (rs113759408, parity, histology = endometrioid, P = 8.8 × 10(-6)). CONCLUSIONS: We have demonstrated the feasibility of assessing multifactor interactions in large genetic epidemiology studies. Follow-up studies are necessary to assess the robustness of our findings for ESR1, CYP11A1, IGF1R, CYP11B1, INSR, and IGFBP2 Future work is needed to develop powerful statistical methods able to detect these complex interactions. IMPACT: Assessment of multifactor interaction is feasible, and, here, suggests that the relationship between genetic variants within candidate genes and hormone-related risk factors may vary EOC susceptibility. Cancer Epidemiol Biomarkers Prev; 25(5); 780-90. ©2016 AACR.

The association between socioeconomic status and tumour stage at diagnosis of ovarian cancer: A pooled analysis of 18 case-control studies.

PURPOSE: Socioeconomic status (SES) is a known predictor of survival for several cancers and it has been suggested that SES differences affecting tumour stage at diagnosis may be the most important explanatory factor for this. However, only a limited number of studies have investigated SES differences in tumour stage at diagnosis of ovarian cancer. In a pooled analysis, we investigated whether SES as represented by level of education is predictive for advanced tumour stage at diagnosis of ovarian cancer, overall and by histotype. The effect of cigarette smoking and body mass index (BMI) on the association was also evaluated. METHODS: From 18 case-control studies, we obtained information on 10,601 women diagnosed with epithelial ovarian cancer. Study specific odds ratios (ORs) with corresponding 95% confidence intervals (CI) were obtained from logistic regression models and combined into a pooled odds ratio (pOR) using a random effects model. RESULTS: Overall, women who completed ≤high school had an increased risk of advanced tumour stage at diagnosis compared with women who completed >high school (pOR 1.15; 95% CI 1.03-1.28). The risk estimates for the different histotypes of ovarian cancer resembled that observed for ovarian cancers combined but did not reach statistical significance. Our results were unchanged when we included BMI and cigarette smoking. CONCLUSION: Lower level of education was associated with an increased risk of advanced tumour stage at diagnosis of ovarian cancer. The observed socioeconomic difference in stage at diagnosis of ovarian cancer calls for further studies on how to reduce this diagnostic delay.

Candidate gene analysis using imputed genotypes: cell cycle single-nucleotide polymorphisms and ovarian cancer risk.

Polymorphisms in genes critical to cell cycle control are outstanding candidates for association with ovarian cancer risk; numerous genes have been interrogated by multiple research groups using differing tagging single-nucleotide polymorphism (SNP) sets. To maximize information gleaned from existing genotype data, we conducted a combined analysis of five independent studies of invasive epithelial ovarian cancer. Up to 2,120 cases and 3,382 controls were genotyped in the course of two collaborations at a variety of SNPs in 11 cell cycle genes (CDKN2C, CDKN1A, CCND3, CCND1, CCND2, CDKN1B, CDK2, CDK4, RB1, CDKN2D, and CCNE1) and one gene region (CDKN2A-CDKN2B). Because of the semi-overlapping nature of the 123 assayed tagging SNPs, we performed multiple imputation based on fastPHASE using data from White non-Hispanic study participants and participants in the international HapMap Consortium and National Institute of Environmental Health Sciences SNPs Program. Logistic regression assuming a log-additive model was done on combined and imputed data. We observed strengthened signals in imputation-based analyses at several SNPs, particularly CDKN2A-CDKN2B rs3731239; CCND1 rs602652, rs3212879, rs649392, and rs3212891; CDK2 rs2069391, rs2069414, and rs17528736; and CCNE1 rs3218036. These results exemplify the utility of imputation in candidate gene studies and lend evidence to a role of cell cycle genes in ovarian cancer etiology, suggest a reduced set of SNPs to target in additional cases and controls.