4.7 Article

Gender differences in elderly mobility in the United States

期刊

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.tra.2021.10.015

关键词

Elderly people; Older adults; Women; Gender gap; Mobility; Clustering analysis; Structural equation modeling

资金

  1. University of California Institute of Transportation Statewide Transportation Research Program

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This study revealed gender gaps in mobility patterns of older adults in the US, with significant differences across different clusters. Some clusters showed substantial gender gaps, while others exhibited positive differences. The findings can help transportation planners and policymakers understand the characteristics of the elderly population and develop measures to reduce gender disparities.
Mobility is a critical element of one's quality of life regardless of one's age. Although the challenges for women are more significant than those for men as they age, far less is known about the gender differences in mobility patterns of older adults, especially in the United States (US) context. This paper reports on a study that examined potential gender gaps in mobility patterns of older adults (aged 65 years and over) in the US by analyzing data from the 2017 National Household Travel Survey. Elderly respondents were first classified into one of six clusters based on socio-demographic variables. A Structural Equation Model (SEM) was then estimated and showed that gender gaps existed in the mobility patterns of the elderly, and the differences were diverse across the different clusters. The most substantial gender gap was found in the Senior Elder with Medical Condition(s) cluster, followed by the High-income Workers cluster and the Middle-income Urban Residents cluster. In contrast, females in the Low-Income Single Elder cluster enjoyed statistically significant positive mobility differences with their male counterparts. Our results also found that female elderly in the Senior Elder with Medical Condition(s) and the Low-income Family Elder clusters suffered most after the cessation of driving, with the largest mobility gender gap in the Middle-income Urban Resident cluster. This study will help transportation planners and policymakers understand gender and other socio-demographic differences in elderly mobility. Thus, it will facilitate the development of measures to improve elderly mobility and reduce gender gaps by recognizing and addressing specific target groups' mobility characteristics and needs rather than treating the elderly as a single potential user group.

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