Factors associated with elderly mobility: Examination of immigrant status and access to public transit

Abstract

This study examined how immigrant status and access to public transit were related to elderly mobility. As the number of individuals who outlive the traditional driving span increases, there will be more older adults with limited mobility. Using the 2001 National Household Travel Survey (NHTS) dataset, a cross-sectional design was used to answer two research questions: (1) Is immigrant status related to elderly mobility? (2) Is access to public transit related to elderly public transit utilization patterns? In addition, Geographic Information Systems (GIS) was used to calculate the level of public transit access among the study respondents. Social ecological theory provided the conceptual framework for the study. To examine how immigrant status is associated with elderly mobility, individuals who were 65 or older (n=18,801) from the 2001 NHTS were included in the first research question. Descriptive statistics, t-test, multiple and logistic regressions were performed to analyze the data. To study how access to public transit influences older adults' transit utilization patterns, a Baltimore City subsample (n=580) was used to address the second research question. GIS buffer analyses were performed for spatial data and logistic regression analysis was performed for statistical data. Findings indicated that both immigrant status and access to public transit were important predictors of elderly mobility. Immigrant elderly were more likely to have lower levels of mobility, as measured by trip frequency, log of trip miles and driving status. It was also found that the level of access to public transit was positively associated with older adults' public transit use. Those who live in areas with a higher percentage of public transit service access were more likely to be transit users. This study contributes to elderly mobility literature by addressing understudied topics. The study findings generated implications for broader social work issues such as policy, research, theory, practice and education. It is hoped that some of the techniques used in this study benefit other researchers by setting examples of how to deal with data issues and using GIS techniques in social work research.