Problem Statement and Scope

Nations around the world are seeing more and more people flock to cities. The year 2008 marked the first time in human history when more than half of the global population could be found in cities or towns. And that number is only expected to grow: by 2030, two thirds of the global population will reside in cities.

At the same time, many countries are aging. In member nations of the OECD, the proportion of citizens aged 65 and older has grown from 7.7% in 1950 to 17.8% in 2010 and will reach 25% by 2050.

Studies show that seniors face unique challenges when it comes to navigating NYC on foot - senior pedestrians suffer higher fatality rates in pedestrian accidents in NYC than any other part of the US. To combat this problem, NYC DOT came up with its Safe Streets for Seniors program and since 2008, DOT has implemented changes in 41 "Senior Pedestrian Focus Areas".


Hypotheses

Hypothesis 1: Fewer seniors will be involved in fatal motor vehicle accidents in SPFAs

Hypothesis 2: Fewer seniors will be killed in motor vehicle accidents in SPFAs

Hypothesis 3: Fewer senior pedestrians will be killed in motor vehicle accidents in SPFAs


Data

Our diff-in-diff analysis relies primarily on two data sets - Motor Vehicle Crash Data collected from the National Highway Traffic Safety Administration (NHTSA) and Senior Pedestrian Focus Areas(SPFA) spatial data.

The NHTSA publishes nationwide motor vehicle crash data going back decades as part of its Fatality Analysis Reporting System (FARS). All crashes reported in FARS involve at least one fatality and include extensive data on each crash, including date, time, location, weather conditions, and the age of each person involved. We collected this data from 2001 to 2017 for the nation and filtered down to accidents in NYC.
SPFAs are specific areas in NYC that have been identified by NYC DOT as especially dangerous for senior pedestrians living in those areas. DOT has identified 41 SPFAs in total and has undertaken various infrastructure projects to improve the safety of these areas. Spatial data that describes SPFAs is published online by NYC Open Data, which we collected for visualization and analysis.

Data Summary

Type of Data Datasets Relevant Fields
NHTSA Motor Vehicle Crash Data Accident Data Date, Latitude, Longitude, Weather Conditions, etc.
NHTSA Motor Vehicle Crash Data Motorist and Pedestrian Data Age, Gender, Injury Severity, etc.
DOT's SPFA Data SPFA shapefile SPFA Name, SPFA Implementation Round, Geometry
Data Source:

NHTSA traffic fatality data

SPFA spatial data


Data Visualization

Tableau Visualization of Accidents Data
Tableau Visualization of Accidents Data

Methodology

We used a statistical technique known as "difference-in-difference" (aka diff-in-diff) for our study.

Diff-in-diff looks at the effect of a treatment on a 'treatment group' versus a 'control group' in a natural experiment.

It calculates the effect of a treatment on an outcome by comparing the average change over time in the outcome variable for the treatment group, compared to the average change over time for the control group.


Analysis

Regression Model

Resgression Results


Conclusion

Based on the results of our models, it looks like NYC's Safe Streets for Seniors program is working, which is good news. Fewer seniors are involved in accidents and fewer senior pedestrians, in particular, are being killed by motor vehicles.

In light of these findings, other cities should consider adopting a similar program. Navigating urban environments on foot can be extremely challenging but also essential to the life and well-being of seniors. And as urban senior populations grow in the coming decades, it will be especially important to make sure they can get around cities without constantly worrying for their own safety. Of course, there's no “one size fits all” solution to any public policy. But NYC’s Safe Streets for Seniors is a step in the right direction.

To review more, please visit our github site at https://github.com/agingcapstone/agingcapstone_notebooks

Meet the Team


Sam Burns

Sam had a past life in the investigative world and has a current life as a data (and tennis) nerd.

LinkedIn GitHub

Po-Yang Kang

Undergrad from The George Washington University who double majored in International Affairs and Economics, with a minor in Computer Science. Currently a M.S. graduate at NYU CUSP.

LinkedIn GitHub

Asilayi Bahetibieke

Undergrad from Peking University who double majored in Economics and Urban Planning. Currently a M.S. graduate at NYU CUSP.

LinkedIn GitHub

Pengzi Li

Undergrad from University of Toronto who double majored in Statistics and Economics, with a minor in mathematics. Currently a M.S. graduate at NYU CUSP.

LinkedIn GitHub

About Mentor

Daniela Hochfellner

a Research Assistant Professor at CUSP and an Adjunct Research Assistant Professor at the Institute for Social Research, Survey Research Center at the University of Michigan. She received her PhD in Sociology from the University of Bamberg (in Germany)
Email:daniela.hochfellner@nyu.edu
Tel:(646) 997-0549


About Sponsor

Center for Urban Science + Progress

CUSP is an interdisciplinary research center dedicated to the application of science, technology, engineering, and mathematics in the service of urban communities across the globe. Using New York City as our laboratory and classroom, who strive to develop novel data- and technology-driven solutions for complex urban problems


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