title: Predicting future protection of respirator users: Statistical approaches and practical implications.
abstract: The purpose of this article is to describe a statistical approach for predicting a respirator user's fit factor in the future based upon results from initial tests. A statistical prediction model was developed based upon joint distribution of multiple fit factor measurements over time obtained from linear mixed effect models. The model accounts for within-subject correlation as well as short-term (within one day) and longer-term variability. As an example of applying this approach, model parameters were estimated from a research study in which volunteers were trained by three different modalities to use one of two types of respirators. They underwent two quantitative fit tests at the initial session and two on the same day approximately six months later. The fitted models demonstrated correlation and gave the estimated distribution of future fit test results conditional on past results for an individual worker. This approach can be applied to establishing a criterion value for passing an initial fit test to provide reasonable likelihood that a worker will be adequately protected in the future; and to optimizing the repeat fit factor test intervals individually for each user for cost-effective testing.
authors.affiliation: a Department of Epidemiology and Biostatistics , Mel and Enid Zuckerman College of Public Health, University of Arizona , Tucson , Arizona.
authors.forename: Chengcheng
authors.initials: C
authors.lastname: Hu
authors.affiliation: b Department of Community, Environment, and Policy , Mel and Enid Zuckerman College of Public Health, University of Arizona , Tucson , Arizona.
authors.forename: Philip
authors.initials: P
authors.lastname: Harber
authors.affiliation: c Ventana Medical Systems , Tucson , Arizona.
authors.forename: Jing
authors.initials: J
authors.lastname: Su
mesh_terms: D000328:Adult; D004867:Equipment Design; D005145:Face; D005544:Forecasting; D006801:Humans; D008422:Materials Testing; D015233:Models, Statistical; D016273:Occupational Exposure / Q000517:prevention & control*; D015203:Reproducibility of Results; D012134:Respiratory Protective Devices
keywords: Fit factor; prediction; respirator; respiratory protection; statistical model