• ExpoQual: Evaluating measured and modeled human exposure data

      O'Mahony, C.; Armstrong, T.; LaKind, Judy S. (Elsevier, 2019)
      Recent rapid technological advances are producing exposure data sets for which there are no available data quality assessment tools. At the same time, regulatory agencies are moving in the direction of data quality assessment for environmental risk assessment and decision-making. A transparent and systematic approach to evaluating exposure data will aid in those efforts. Any approach to assessing data quality must consider the level of quality needed for the ultimate use of the data. While various fields have developed approaches to assess data quality, there is as yet no general, user-friendly approach to assess both measured and modeled data in the context of a fit-for-purpose risk assessment. Here we describe ExpoQual, an instrument developed for this purpose which applies recognized parameters and exposure data quality elements from existing approaches for assessing exposure data quality. Broad data streams such as quantitative measured and modeled human exposure data as well as newer and developing approaches can be evaluated. The key strength of ExpoQual is that it facilitates a structured, reproducible and transparent approach to exposure data quality evaluation and provides for an explicit fit-for-purpose determination. ExpoQual was designed to minimize subjectivity and to include transparency in aspects based on professional judgment. ExpoQual is freely available on-line for testing and user feedback (exposurequality.com). © 2019
    • Exposure to a Multilevel, Multicomponent Obesity Prevention Intervention (OPREVENT2) in Rural Native American Communities: Variability and Association with Change in Diet Quality

      Estradé, Michelle; van Dongen, Ellen J I; Trude, Angela C B; Poirier, Lisa; Fleischhacker, Sheila; Wensel, Caroline R; Redmond, Leslie C; Pardilla, Marla; Swartz, Jacqueline; Treuth, Margarita S; et al. (MDPI AG, 2021-11-19)
      The OPREVENT2 obesity prevention trial was a multilevel multicomponent (MLMC) intervention implemented in rural Native American communities in the Midwest and Southwest U.S. Intervention components were delivered through local food stores, worksites, schools, community action coalitions, and by social and community media. Due to the complex nature of MLMC intervention trials, it is useful to assess participants' exposure to each component of the intervention in order to assess impact. In this paper, we present a detailed methodology for evaluating participant exposure to MLMC intervention, and we explore how exposure to the OPREVENT2 trial impacted participant diet quality. There were no significant differences in total exposure score by age group, sex, or geographic region, but exposure to sub-components of the intervention differed significantly by age group, sex, and geographical region. Participants with the highest overall exposure scores showed significantly more improvement in diet quality from baseline to follow up compared to those who were least exposed to the intervention. Improved diet quality was also significantly positively associated with several exposure sub-components. While evaluating exposure to an entire MLMC intervention is complex and imperfect, it can provide useful insight into an intervention's impact on key outcome measures, and it can help identify which components of the intervention were most effective.
    • Minimizing pharmacotherapy-related healthcare worker exposure to SARS-CoV-2

      Barlow, Brooke; Barlow, Ashley; Thompson Bastin, Melissa L; Berger, Karen; Dixit, Deepali; Heavner, Mojdeh S (American Society of Health-System Pharmacists, 2020-09-04)