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ATS International Journal
Editor in Chief: Prof. Alessandro Calvi
Address: Via Vito Volterra 62,
00146, Rome, Italy.
Mail to: alessandro.calvi@uniroma3.it

Investigating the socio-demographic determinants of medical travel burden in the U.S.: insights from the 2017 National Household Travel Survey

A.D. Lidbe, M. Dutta, M. Cheshire, E.K. Adanu, X. Li, P. Penmetsa
Pages: 89-110

Abstract:

Medical travel burden is a significant challenge for vulnerable subgroups in the United States, particularly rural residents, low-income individuals, and racial minorities, who often face longer travel distances and limited access to healthcare services. This study aims to investigate and identify the various socio-demographic factors associated with medical travel burden trips using the 2017 National Household Travel Survey (NHTS). The study specifically focuses on intricate interplay of demographic, socio-economic, spatial, and temporal factors that influence whether individuals perceive medical travel as a burden. To this end, a random parameter multinomial logit model was developed to examine the exogenous factors impacting medical travel burden. This study applies a Random Parameters Multinomial Logit (RPMNL) model to national-level household travel data, allowing us to capture unobserved heterogeneity that traditional models overlook. The findings reveal significant gender differences, with more females than males making medical trips. Regarding race and ethnicity, the white population accounted for the majority of medical trips, followed by Hispanics and then African Americans. Households with income less than $50,000 predominantly undertook these medical trips. The results indicate that individuals with poor health conditions, low-income households, single-adult households, rural residents, and households without vehicles are more likely to experience travel burden in accessing healthcare. To address these disparities, future interventions aimed at improving health-related transportation should focus on these vulnerable subgroups, thereby mitigating the existing gaps in healthcare accessibility and health outcomes.
Keywords: medical care; travel burden; NHTS; random parameter logit model; healthcare access

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