Ript Author Manuscript Author Manuscript Author ManuscriptJ Am Coll Cardiol. Author manuscript; offered in PMC 2017 March 21.Chen et al.PageFractional exhaled nitric oxide (FeNO)–FeNO is an established biomarker of respiratory inflammation, and has been extensively utilized in epidemiological research simply because of its higher sensitivity, specificity, and noninvasive nature (21). We measured FeNO levels employing a portable NIOX MINO machine (Aerocrine AB, Solna, Sweden) according to standardized procedures recommended by the American Thoracic Society as well as the European Respiratory Society.Author Manuscript Author Manuscript Author Manuscript Author ManuscriptStatistical analysesBecause the distributions in the health outcome variables have been all skewed, we logtransformed them before statistical analysis. To examine possible effects as a result of order of intervention, we compared health endpoints between the two groups with various therapy order utilizing the 2-sample Wilcoxon rank-sum (Mann-Whitney) test (19). To account for the repeated measurement of health endpoints below the two experimental scenarios, we applied linear mixed-effect models to investigate the impact of air purification on outcome variables (12).ZH8651 web This automatically permits each and every topic to serve as his/her personal handle more than time, and also adjusts for between-subject covariates that usually do not transform more than time. The intervention was coded as a dummy variable (i.e., 1 for true-purified situation and 0 for sham-purified situation) and was analyzed as a fixed impact in the model. We incorporated random intercepts for subjects to account for intraindividual correlations between repeated measurements, at the same time as interindividual correlations of repeated measures in each and every room (14). We also controlled for the following variables as fixed-effect covariates: age, sex, BMI, indoor temperature, and indoor relative humidity. Because the trial was completed in about half a month, we didn’t manage for the temporal trends on the health measurements. Furthermore, ambient gaseous air pollutants didn’t confound the analyses, as their concentrations were exactly the same amongst the 2 scenarios due to this 1:1 crossover design. Similarly, the potentially lagging confounding effects of ambient air pollution and temperature might also be excluded from the final models.35265-83-9 Formula We calculated the effect of air purification as a % transform in the geometric mean and its 95 self-assurance interval (CI) in a health endpoint comparing the true-purified air scenario with all the sham intervention.PMID:24456950 As a sensitivity analysis, we replaced the dummy variable on the intervention with indoor PM2.5 concentrations inside the above model to examine whether an empirical lower in indoor PM2.5 could lead to a adjust in overall health indicators. All statistical tests have been 2-sided with alpha = 0.05. All analyses were conducted employing the “lme4” package of R application (Version two.15.three; R Development Core Group).ResultsDescriptive statistics Study participants were 25 females and ten males with a imply age of 23 2 years and an typical BMI of 22 kg/m2. All participants completed this study. Based on the selfadministrated questionnaire, they stayed indoors nearly the entire time, and stayed within the central urban area of Shanghai throughout the washout period. Moreover, all participants remained healthy throughout the study period.J Am Coll Cardiol. Author manuscript; out there in PMC 2017 March 21.Chen et al.PageBefore the intervention, the typical PM2.5 concentration was.