A socio-spatial analysis of pedestrian falls in Aotearoa New Zealand

A. Watkins, A. Curl, S. Mavoa, M. Tomintz, V. Todd, B. Dicker

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Falls are a leading cause of injury and accidental death, particularly amongst older people. Evidence of environmental risk factors for pedestrian falls among older adults could support age-friendly urban design and contribute to efforts to reduce the incidence of pedestrian falls and support outdoor mobility among older adults. Yet investigation of the environment in which pedestrian falls occur is often hampered by its reliance on participant recall and self-report information. We identified the point locations of falls occurring on the road or street among adults that were attended by an ambulance in New Zealand over a two-year period (2016–2018) and connected these to a range of social (e.g. deprivation) and environmental (e.g. slope, greenspace) risk factors. Three types of analysis were used: a descriptive analysis of fall rates, logistic regression assessing whether a patient was transported to hospital following a fall, and a negative binomial regression analysis of the pedestrian falls by small area. We found a number of differences in the built environment surrounding fall locations between age groups. Compared with younger age groups, older adults showed high fall rates closer to home, and higher fall rates in areas with many types of destinations nearby. Additionally, our results showed a higher rate of pedestrian falls in more deprived areas. People who live in more deprived areas also fell over more frequently, but the pattern is stronger based on deprivation at the fall location, rather than home location. Residents of more deprived areas were less likely to be transported to hospital following a fall. Thus, our findings have equity implications for both environments and patient experience. These patterns could not have been identified without the novel use of spatially specific fall data.

Original languageEnglish
Article number113212
Pages (from-to)1-9
Number of pages9
JournalSocial Science and Medicine
Volume288
DOIs
Publication statusPublished - Nov 2021
Externally publishedYes

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