Explaining state-to-state differences in seat belt use: A multivariate analysis of cultural variables.
There is considerable variation in seat belt use within the United States despite extensive evidence that the use of seat belts saves lives. Previous studies have identified some important factors that affect belt use rates, including gender, age, race, vehicle type, seat-belt enforcement laws, and amount of fine for belt-use law violation. In this study, we examined the influence of additional socio-demographic factors on state-level use rates: education (percentage of high school educated population), racial composition (percentage White), median household income, political leaning (percentage Democrat), and a measure of religiosity. These variables, which collectively characterize the 'culture' of a state, have received little attention in seat-belt studies. The paper reports results from a multiple regression analysis of data from the 2008 Fatality Analysis Reporting System (FARS). Many of the use rate patterns in FARS data were consistent with those found in other data sets, suggesting that conclusions based on FARS data are likely to hold for the population-at-large. Of the five cultural factors considered in the study, three were identified as important in explaining the differences in seat belt use at the state level: religiosity, race (percentage White), and political leaning (percentage Democrat). The other two variables - income and education - were not significant. Hold-out analyses confirmed that this conclusion was consistent across different subsets of data. The findings from this study are preliminary and have to be confirmed on other data sets. Nevertheless, they demonstrate the potential usefulness of cultural factors in explaining state-to-state variation in seat belt use rates. If factors such as religiosity are indeed important, they can be used to develop culturally appropriate programs for increasing belt use.
University of Michigan Transportation Research Institute, Ann Arbor, MI, USA.
Lisa J
LJ
Molnar
David W
DW
Eby
Kohinoor
K
Dasgupta
Yang
Y
Yang
Vijayan N
VN
Nair
Stephen M
SM
Pollock
D000367:Age Factors; D001334:Automobile Driving / Q000331:legislation & jurisprudence / Q000523:psychology / Q000706:statistics & numerical data; D003710:Demography; D005260:Female; D007722:Health Knowledge, Attitudes, Practice / Q000208:ethnology*; D006801:Humans; D008297:Male; D015999:Multivariate Analysis; D011057:Politics; D012622:Seat Belts / Q000331:legislation & jurisprudence / Q000706:statistics & numerical data*; D012737:Sex Factors; D012959:Socioeconomic Factors; D014481:United States / Q000453:epidemiology