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«by Johnathon P. Ehsani A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Health Behavior ...»

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The second level (intermediate license) allows teens to drive independently but with restrictions that limit their exposure to the highest risk driving conditions (i.e., driving with passengers and driving at night). Passenger restrictions limit the number and/or age of passengers a teen driver can carry during the first months of independent driving (typically for the first 6 months of intermediate licensure). Nighttime driving restrictions prohibit teens with intermediate licenses from any driving between certain hours, typically late night to early morning, when crash risk is known to be highest (Insurance Institute for Highway Safety 2011). The final stage of GDL gives teens, who have gained driving experience while fulfilling the requirements of learner and intermediate licenses, permission to drive with no restrictions.

Both passenger and nighttime driving restrictions are widely adopted components of states’ graduated licensing programs (Williams 2007). California was one of the first states to implement a passenger restriction as part of a comprehensive GDL program, when in July 1998, teen drivers were restricted from carrying any passengers below 20 years of age for the first six months of their intermediate license (Insurance Institute for Highway Safety 2012). Evaluations of the California law indicated substantial declines in fatal and non-fatal injury teen passenger crashes, which are defined as crashes resulting in a fatality or non-fatal injury where a passenger under age 20 was present in the vehicle of the teen driver (Masten and Hagge 2004; Rice, Peek-Asa et al.

2004; Cooper, Atkins et al. 2005; Zwicker, Williams et al. 2006). Beyond California, Chaudhary and colleagues reported significant declines in fatal/non-fatal injury teen passenger crashes in Massachusetts and Virginia following the introduction of passenger restrictions in January 1998 and July 2001, respectively (Chaudhary, Williams et al. 2007). National studies of GDL have also reported significant declines in passenger crashes subsequent to the introduction of passenger restrictions (Chen, Baker et al. 2006; Fell, Todd et al. 2011; Masten, Foss et al. 2011).

Nighttime restrictions were first implemented as city- or state-wide nighttime driving curfews in the late 1970s and early 1980s as stand alone policies for teen drivers (Preusser, Williams et al. 1984). In a study of four states’ nighttime driving curfew laws (Louisiana, Maryland, New York, and Pennsylvania), significant reductions in 16-year-old drivers’ nighttime crash involvements were observed in all four states (Preusser, Williams et al. 1984). Nighttime driving restrictions were later implemented as part of comprehensive GDL systems, and have demonstrated efficacy within this context in both state level and national evaluations (Ulmer, Preusser et al. 2000; Foss, Feaganes et al.

2001; Shope, Molnar et al. 2001; Shope and Molnar 2004; Chen, Baker et al. 2006;

Foss, Masten et al. 2007; McCartt, Teoh et al. 2010; Fell, Todd et al. 2011).

In the majority of instances when a passenger or nighttime driving GDL restriction has been introduced in the United States, it has been implemented along with at least one additional GDL component. However, state and national evaluations have rarely accounted for the confounding effect of multiple GDL components implemented simultaneously. Rather, these studies have assumed independent implementation of each component, which does not reflect the reality of how these laws were introduced.

Most evaluations of passenger and nighttime restrictions also used a pre- and post-GDL study design that is unable to distinguish if a decline in crashes was directly attributable to GDL, or the result of a preexisting downward trend (Elliott and Shope 2003; Sivak and Schoettle 2010). The purpose of this paper was to quantify the effects of passenger and nighttime driving restrictions using a sample of states that introduced them independently of any other GDL component, employing an analytical approach that accounts for long-term trends (Masten and Hagge 2004).

–  –  –

This study will test two hypotheses:

1. The introduction of a GDL restriction on driving with passengers will be followed by a reduction in teen drivers’ fatal passenger and overall fatal crash rates, reflecting a doseresponse relationship between duration of the passenger restriction or number of passengers allowed and a reduction in fatal passenger and overall fatal crash rates.

2. The introduction of a GDL nighttime driving restriction will be followed by a reduction in teen drivers’ fatal nighttime and overall fatal crash rates, reflecting a dose-response relationship between the length of the nighttime restriction and a reduction in fatal nighttime and overall fatal crash rates.

–  –  –

To test the first hypothesis, states that introduced a passenger restriction independently of other GDL components, during the period 1990 to 2009, were identified (Table 3.1). In these states, inferences regarding the effect of the restriction would be less confounded and more definitive than in situations where multiple GDL components were changed simultaneously. Eight states implemented passenger restrictions independently of other GDL components. Each state had existing GDL components in place when the intermediate license passenger restriction was introduced. States were excluded from the sample if they introduced multiple GDL components simultaneously with the component of interest, or had an intermediate license age below 16 years.

Because at least two years of data post-implementation were required to estimate a component’s effect, states introducing a passenger or nighttime driving restriction after December 2007 were excluded from the sample.

There was considerable variation among states in the three possible provisions of passenger restrictions (duration, number of passengers, and age of passengers).

Regarding the duration, Connecticut and Maine fixed the duration of the passenger restriction to the first three months of intermediate licensure, while Utah and New Hampshire fixed the duration of the passenger restriction to the first six months of intermediate licensure. Colorado, Missouri and Rhode Island each stipulated different passenger limits for the first 12 months, while North Carolina introduced a passenger restriction that lasted the duration of the intermediate license. Regarding the number of passengers, three states, Connecticut, Maine and Utah, allowed no passengers with the exception of parents or family members, when teen drivers are under the passenger restriction. New Hampshire, North Carolina and Rhode Island, permitted a single passenger. In Colorado and Missouri, the number of passengers allowed changed after the first six months of independent driving, from none to one passenger in Colorado, and from one to three passengers in Missouri. Regarding passenger age, two states, North Carolina and Rhode Island, specified the age of the passengers (limits applied to passengers under age 21), while the remainder did not.

To test the second hypothesis, states that introduced a nighttime driving restriction independently of other GDL components during the period 1990 to 2009, were sought. No states fulfilled that inclusion criterion, therefore, the criterion was modified to include those states where the nighttime restriction was introduced as the first intermediate license restriction of a GDL system, simultaneously with other components (e.g., minimum holding period) (Table 3.2). Nebraska and Utah introduced nighttime driving restrictions from 12 midnight to 6 a.m. as their first intermediate GDL components, along with supervised driving requirements for their learner phases.

Measures The primary measure of the effectiveness of an intermediate license restriction is the outcome that is specific to the restriction itself. In the case of the passenger restriction, the specific outcome is fatal passenger crashes, while for the nighttime driving restriction it is fatal nighttime crashes. Total fatal crashes will be used as a secondary outcome measure for both restrictions.

Monthly counts of fatal crashes, fatal passenger crashes, and fatal nighttime crashes involving at least one teen driver (aged 16 or 17 years) in cars, trucks/pickups, vans/minivans, and sports utility vehicles were obtained for the contiguous period 1990 to 2009 from the Fatality Analysis Reporting System (FARS) for the states being analyzed (National Highway Traffic Safety Administration 2010). FARS is a yearly census of fatal traffic crashes within the 50 states, the District of Columbia, and Puerto Rico. Every vehicle crash on a public roadway that results in at least one fatality is recorded in the FARS database with information retrieved from police crash reports (Guarino and Champaneri 2010). In FARS, a fatality is defined as a death occurring within 30 days of being injured in a crash on a public road involving at least one vehicle with an engine (National Highway Traffic Safety Administration 2010). A fatal passenger crash was defined as a crash involving at least one teen driver, where a passenger was present in the vehicle driven by a teen driving. A fatal nighttime crash was defined as a crash involving at least one teen driver during the nighttime driving restriction (12 midnight to 6 a.m.).

Ideally, the sample would include data from all injury crashes (not just fatal crashes) occurring in each candidate state; however, only a limited number of states make their injury crash data available to researchers (National Highway Traffic Safety Administration 2011), so that approach could not be taken for this study. Likewise, crash rates based on the number of licensed teen drivers would be the most precise estimate of the effect of the GDL restrictions on crashes. However, licensure data reported by the Federal Highway Administration underreport the actual number of licensed teens, and like crash data, licensure data are difficult to obtain from individual states (Insurance Institute for Highway Safety 2006). Miles driven by each teen would also be an ideal measure of exposure, but are difficult to measure and generally unavailable. Therefore, crash rates were based on the number of teens in the overall population of each state.

Annual population estimates by state and age were obtained from the United States Census Bureau (Bureau of the Census. U.S. Department of Commerce 1999; Bureau of the Census. U.S. Department of Commerce 2010). Monthly values were interpolated using cubic spline curves, which are the smoothest curves that exactly fit a set of data points (Bartels, Beatty et al. 1998). Age-group-specific monthly fatal crash involvement rates of 16- and 17-year-old drivers per 100,000 population were calculated using monthly fatal crash counts and monthly population estimates. Data for drivers younger than 16 years were excluded because only a few states allow unsupervised driving by 15-year-olds (Insurance Institute for Highway Safety 2012), making it difficult to compare findings among states.

Several states in the sample had relatively small populations, increasing the probability of a floor effect, where crash rates cannot take on a value lower than zero.

To compensate for this effect, states with a 16- to 17-year-old population below 85,000 (Maine, Nebraska, New Hampshire, Rhode Island, and Utah) were modeled using quarterly data. Quarterly fatal crash involvement rates were calculated using the monthly crash counts and population estimates.

Covariates Comparison population In each study state, monthly fatal crash rates, fatal passenger crash rates and fatal nighttime crash rates for drivers age 25 to 54 were used as covariates representing crashes for the typical adult driving population. Applying the identical method used to estimate 16- to 17-year-old fatal crash rates, age-group-specific fatal crash rates of 25to 54-year-old drivers per 100,000 population were calculated using overall, nighttime, and passenger monthly fatal crash counts and monthly population estimates. The purpose of the comparison population was to adjust for variability in the teen driver crash rates due to extraneous factors affecting drivers of all ages, and to test the effect of the GDL restrictions against a comparison population of persons unaffected by GDL.

Although time series analyses control for pre-existing secular trends in crash rates, the inclusion of the crash rates of another age group as a historical covariate to control for unmeasured factors that affect all drivers enhances the validity of the findings.

Gas prices An inverse relationship between gas prices and fatal crashes has been identified for drivers of all ages (Sivak and Schoettle 2010); however, research suggests that teen driving behavior may be more sensitive to higher gas prices relative to older drivers (Morrisey and Grabowski 2010). Monthly national average gas prices, obtained from the United States Energy Information Administration (U.S. Energy Information Administration 2011), were used as covariates in the analyses to adjust for their effects on the amount of driving exposure, and resulting crash risk level.

GDL laws For each state, indicator variables were included for GDL components that were introduced before or after the intermediate driving restrictions being studied.

Analytical Method To estimate the effects of each GDL component, monthly (and quarterly where needed) fatal crash rates per 100,000 population of 16- and 17-year-old drivers were analyzed using Auto-Regressive Integrated Moving Average (ARIMA) interrupted time series analysis (McCleary and Hay 1982) for each state. Interrupted time-series analyses compares observations before and after some identifiable event, with the goal of evaluating the impact of the intervention. The transfer function relates an intervention to its effect on fatality rates. In this analysis, the transfer function has two parameters.

The first parameter, !, is the magnitude of the asymptotic change (rise or fall) in level after the intervention. The second parameter, !, reflects the onset of the change. If the null hypothesis that ! is 0 is supported, there is no impact of the intervention. If ! is significant, the size of the change is ! (as a percentage) (Tabachnick and Fidell 2007).

For these analyses, ! was fixed at 0, meaning the anticipated change in fatal crash rates would be abrupt and lasting, referred to as a sudden impact permanent change model.

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