Is seat belt use associated with fewer days of lost work after motor vehicle collisions?
BACKGROUND
Seat belt use has consistently been shown to reduce motor vehicle collision (MVC)-related morbidity and mortality. The goal of this study is to determine whether seat belt use is associated with fewer lost workdays among occupants involved in MVCs.


METHODS
The 1995 to 2000 National Automotive Sampling System (NASS) data files were used. The NASS is a national probability sample of passenger vehicles involved in police-reported tow-away MVCs. Occupants' lost workdays, which are routinely collected as part of an NASS investigation, were compared according to seat belt use.


RESULTS
During 1995 to 2000 in the United States, surviving occupants involved in MVCs lost a total of 42.1 million workdays (approximately 7.0 million lost workdays per year; 2.4 lost workdays per person). The overall difference in lost workdays between the belted and unbelted occupants was 1.59 days (1.99 days vs. 3.58 days, respectively; p < 0.001). After adjusting for potentially confounding factors, belted occupants had 1.52 fewer lost workdays compared with unbelted occupants (p < 0.001). This translates to an estimated 7.3 million lost workdays and an associated $566 million in lost wages and $1.25 billion in work-place costs attributable to lack of seat belt use in the United States during 1995 to 2000.


CONCLUSIONS
Lost workdays attributable to MVCs in the United States have sizable financial implications. Furthermore, seat belt use significantly reduces lost time at work and is associated with a significant cost savings. The national impact of unbelted driving on work productivity is dramatic, and further efforts to promote appropriate seat belt use should continue as part of the national safety agenda.
Metzger
Jesse
J
Center for Injury Sciences at the University of Alabama at Birmingham, Birmingham, Alabama, USA.
McGwin
Gerald
G
MacLennan
Paul A
PA
Rue
Loring W
LW
D015998:Abbreviated Injury Scale; D000041:Absenteeism; D000063:Accidents, Traffic / Q000191:economics / Q000401:mortality / Q000517:prevention & control / Q000706:statistics & numerical data; D000328:Adult; D001336:Automobiles / Q000706:statistics & numerical data; D015986:Confounding Factors, Epidemiologic; D017046:Cost Savings; D017281:Cost of Illness; D017598:Efficiency, Organizational; D005260:Female; D006801:Humans; D016014:Linear Models; D008297:Male; D008390:Markov Chains; D008875:Middle Aged; D009010:Monte Carlo Method; D009017:Morbidity; D011159:Population Surveillance; D012456:Salaries and Fringe Benefits / Q000706:statistics & numerical data; D012622:Seat Belts / Q000191:economics / Q000706:statistics & numerical data*; D014481:United States / Q000453:epidemiology; D017132:Workplace / Q000706:statistics & numerical data; D014947:Wounds and Injuries / Q000191:economics / Q000453:epidemiology / Q000209:etiology / Q000517:prevention & control