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Identifying occupational health inequities in the absence of suitable data: are there inequities in access to adequate bathrooms in US workplaces?
  1. Candice Y Johnson1,
  2. Kaori Fujishiro2
  1. 1Family Medicine and Community Health, Duke University, Durham, North Carolina, USA
  2. 2Division of Field Studies and Engineering, National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, Cincinnati, Ohio, USA
  1. Correspondence to Dr Candice Y Johnson, Family Medicine and Community Health, Duke University, Durham, NC, 27705, USA; candice.y.johnson{at}


Objectives Our research questions are often chosen based on the existence of suitable data for analysis or prior research in the area. For new interdisciplinary research areas, such as occupational health equity, suitable data might not yet exist. In this manuscript, we describe how we approached a research question in the absence of suitable data using the example of identifying inequities in adequate bathrooms in US workplaces.

Methods We created a conceptual model that hypothesises causal mechanisms for occupational health inequities, and from this model we identified a series of questions that could be answered using separate data sets to better understand inequities in adequate workplace bathrooms. Breaking up the analysis into multiple steps allowed us to use multiple data sources and analysis methods, which helped compensate for limitations in each data set.

Results Using the conceptual model as a guide, we were able to identify some jobs that likely have inadequate bathrooms as well as subpopulations potentially at higher risk for inadequate bathrooms. We also identified specific data gaps by reflecting on the challenges we faced in our multistep analysis. These gaps, which indicated future data collection needs, included difficulty finding data sources for some predictors of inadequate bathrooms that prevented us from fully investigating potential inequities.

Conclusions We share our conceptual model and our example analysis to motivate researchers to avoid letting availability of data limit the research questions they pursue.

  • Epidemiology
  • Occupational Health

Data availability statement

Data are available in a public, open access repository. The data used in this analysis are available from, and

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Data availability statement

Data are available in a public, open access repository. The data used in this analysis are available from, and

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  • Contributors CYJ and KF designed the study, interpreted the results, and drafted and critically reviewed the manuscript. CYJ conducted the statistical analyses. CYJ is the guarantor of the study.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.