Identifying occupational health inequities in the absence of suitable data: are there inequities in access to adequate bathrooms in U.S. workplaces?

Abstract

ABSTRACTObjectivesOur 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 project in the absence of suitable data, using the example of identifying inequities in adequate bathrooms in U.S. workplaces.MethodsWe created a conceptual model that explained the causation of occupational health inequities, and from this model identified a series of questions that could be answered using separate datasets. Breaking up the analysis into multiple steps allowed us to use multiple data sources and analysis methods, which helped compensate for limitations in each dataset.ResultsUsing the conceptual model as a guide, we were able to identify 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 multi-step analysis.ConclusionsWe share our conceptual model and our example analysis to motivate epidemiologists to avoid letting availability of data limit the research questions they pursue.What is already known on this topicConducting research in interdisciplinary research areas, such as occupational health equity, can be challenging because suitable data often do not exist.What this study addsWe created a conceptual model that explains the causation of occupational health inequities, which helps conduct analyses with less than optimal data.How this study might affect research, practice or policyUsing this approach allows researchers to combine multiple data sources and analysis methods to answer a single research question, expanding the research questions that can be addressed with existing data.