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.
Keywords: Epidemiology; Occupational Health.
© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.