Michael Sivak1, Brandon Schoettle. 1. The University of Michigan Transportation Research Institute, Ann Arbor, Michigan 48109-2150, USA. sivak@umich.edu
Abstract
BACKGROUND: From 2005 to 2009, U.S. road fatalities dropped by 22 percent (from 43,510 to 33,963). A reduction of such magnitude over such a short time has not occurred since road safety statistics were first kept (starting in 1913), except for the reductions during World War II. OBJECTIVE: The study was performed to contribute to our understanding about the mechanisms that could be responsible for this unprecedented drop in road fatalities by analyzing the detailed information from the Fatality Analysis Reporting System (FARS)-a census of all U.S. crashes that involve a fatality. METHOD: The study compared the data for 2005 (the recent peak year in terms of road fatalities) with the data for 2008 (the latest year for which detailed data are available). The focus was on identifying those conditions that showed the largest reductions and those that showed the smallest reductions (or increases of any magnitude). The analysis involved an examination of the variables in the FARS database, which is divided into accident, vehicle, driver, occupant, and nonmotorist subsets. RESULTS: The report highlights the most interesting patterns of changes for 19 variables.
BACKGROUND: From 2005 to 2009, U.S. road fatalities dropped by 22 percent (from 43,510 to 33,963). A reduction of such magnitude over such a short time has not occurred since road safety statistics were first kept (starting in 1913), except for the reductions during World War II. OBJECTIVE: The study was performed to contribute to our understanding about the mechanisms that could be responsible for this unprecedented drop in road fatalities by analyzing the detailed information from the Fatality Analysis Reporting System (FARS)-a census of all U.S. crashes that involve a fatality. METHOD: The study compared the data for 2005 (the recent peak year in terms of road fatalities) with the data for 2008 (the latest year for which detailed data are available). The focus was on identifying those conditions that showed the largest reductions and those that showed the smallest reductions (or increases of any magnitude). The analysis involved an examination of the variables in the FARS database, which is divided into accident, vehicle, driver, occupant, and nonmotorist subsets. RESULTS: The report highlights the most interesting patterns of changes for 19 variables.
Authors: Ian R H Rockett; Michael D Regier; Nestor D Kapusta; Jeffrey H Coben; Ted R Miller; Randy L Hanzlick; Knox H Todd; Richard W Sattin; Leslie W Kennedy; John Kleinig; Gordon S Smith Journal: Am J Public Health Date: 2012-09-20 Impact factor: 9.308