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Abstract
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Background
Changes to the transportation system that promote active transportation - walking, cycling, public transit - can promote important population health gains. However, these potential benefits may not impact everyone equally. We do not know how much they may address, or conversely widen, existing racial and socioeconomic health disparities. This study aims to review existing research that investigates the distribution of health impacts of active transportation interventions across indicators of race, ethnicity, or socioeconomic status.
Methods
We conducted a scoping review of peer-reviewed literature and other significant research to identify studies using a longitudinal design to evaluate the health outcomes of an active transportation intervention, and to compare differences between groups based on race, ethnicity, or socioeconomic status. We searched PubMed, Scopus, Web of Science, and Transport Research International Documentation between January 1, 2000 and October 21, 2020.
Results
Our search resulted in 7226 records that we screened for keyword relevance by title. We identified 3246 abstracts to review further but ultimately found only 10 studies meeting all our inclusion criteria. These 10 studies evaluated behavior change programs, pedestrian and cycling infrastructure improvements, and increased transit infrastructure or access. Eight of these studies found that the intervention had a positive impact on health outcomes overall. When compared across indicators of participant race, ethnicity, or socioeconomic status, nine found either no significant difference or a favorable impact of the intervention on the health outcome for disadvantaged groups studied.
Conclusion
A significant gap in the literature persists, representing missed opportunities to further our understanding of how health inequities might be mitigated or addressed through changes in active transportation infrastructure, promotional campaigns, and policies. We call for researchers to include equity in the development of conceptual models, interventions, study design, and data analysis.
Language: en |