Local Infrastructure and Economy Predicts Traffic Related Fatalities in Children
Expert / Speaker
Zane J. Hellmann
Operating Room
Timestops
00:00:12
Introduction to the study and methodology using the National Walk Index.
Introduction to the study and methodology using the National Walk Index.
00:00:28
Direct question leading to the study's key findings.
Direct question leading to the study's key findings.
00:00:30
Key finding: 7% decrease in child traffic deaths per walkability score increase.
Key finding: 7% decrease in child traffic deaths per walkability score increase.
00:00:39
Transition to explaining the reasons behind the correlation.
Transition to explaining the reasons behind the correlation.
00:00:41
Explanation of why walkable areas reduce fatalities (lower speed limits, better intersections).
Explanation of why walkable areas reduce fatalities (lower speed limits, better intersections).
00:00:52
Discussion of the implications of the research findings
Discussion of the implications of the research findings
00:00:54
Call to action: Urban planners should prioritize walkability.
Call to action: Urban planners should prioritize walkability.
Topic overview
Zane J. Hellmann ∙ Elena Graetz ∙ Shahyan Rehman ∙ Miranda Moore ∙ Eric B. Schneider ∙ Emily R. Christison-Lagay ∙ Daniel G. Solomon
Purpose
Previous research on pediatric motor vehicle collisions (MVC) and fatalities has primarily focused on patient demographics and crash specific information. This study evaluates whether various measures of local infrastructure, including the National Walk Index (NWI), population density, and public school density, or macroeconomic forces, encapsulated in Social Vulnerability Index (SVI) and food area deprivation (PFA) can predict which counties are most at risk for pediatric traffic fatalities.
Methods
Counties with more than 100,000 children in the most recent US census and ≥1 pediatric traffic fatality as identified in the Fatality Analysis Reporting System (FARS) between 2017 and 2021 were included in the study. Poisson regression modeling was used to identify county level infrastructure and macroeconomic forces that predicted increasing MVC related average annual mortality rate per 100,000 children.
Results
There were 158 counties that met inclusion criteria. Univariate Poisson regression demonstrated that NWI, SVI, PFA, population density, and school density each individually correlated with MVC related mortality rate (p < 0.001 for all predictors). When controlling for SVI and population density, multivariable Poisson regression demonstrated that each decile increase in walkability was associated with a 7 % decrease in MVC related mortality rate (IRR 0.93, 95 % CI 0.91–0.96).
Conclusion
Areas with poor walkability predict the likelihood of pediatric traffic fatality. These findings highlight tangible local and state policy changes that could be implemented to decrease the likelihood of traffic-related child fatality rates in specific counties.
Intended audience: Healthcare professionals and clinicians.
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Transcript
Speaker: Zane J. Hellmann
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