Citation

Yang Y, Langellier BA, Stankov I, Purtle J, Nelson KL, Diez Roux AV. Aging Ment. Health 2019; 23(6): 743-751.

Affiliation

Urban Health Collaborative, Dornsife School of Public Health , Drexel University , Philadelphia , Pennsylvania , USA.

Copyright

(Copyright © 2019, Informa - Taylor and Francis Group)

DOI

10.1080/13607863.2018.1450832

PMID

29543502

Abstract

OBJECTIVES: Daily transport may impact depression risk among older adults through several pathways including facilitating the ability to meet basic needs, enabling and promoting contact with other people and nature, and promoting physical activity (e.g. through active transportation such as walking or walking to public transit). Both daily transport and depression are influenced by the neighborhood environment. To provide insights into how transport interventions may affect depression in older adults, we developed a pilot agent-based model to explore the contribution of daily transport and neighborhood environment to older adults' depression in urban areas.

METHOD: The model includes about 18,500 older adults (i.e. agents) between the ages of 65 and 85 years old, living in a hypothetical city. The city has a grid space with a number of neighborhoods and locations. Key dynamic processes in the model include aging, daily transport use and feedbacks, and the development of depression. Key parameters were derived from US data sources. The model was validated using empirical studies.

RESULTS: An intervention that combines a decrease in bus fares, shorter bus waiting times, and more bus lines and stations is most effective at reducing depression. Lower income groups are likely to be more sensitive to the public transit-oriented intervention.

CONCLUSION: Preliminary results suggest that promoting public transit use may be a promising strategy to increase daily transport and decrease depression. Our results may have implications for transportation policies and interventions to prevent depression in older adults.

Language: en

Keywords

Depression; agent-based model; aging; daily transport; older adults