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This study examines the effect of state driving age, learning permit, driver's education, and curfew laws on 15–17‐year‐old driver fatality rates. A multivariate regression model is estimated for 47 states and nine years. The minimum legal driving age and curfew laws are found to be important determinants of fatalities. Driver's education and learning permits have smaller effects. The relationship between rates of licensure and driving age, education, and curfew laws is also examined. In each case, a more restrictive policy is found to reduce licensure of 15–17 year olds. The results suggest that the imposition of curfew laws and higher minimum driving ages are particularly effective traffic safety policies.SUMMARY AND CONCLUSIONThis study examines the effects of state driving age, learners permit, curfew, and driver's education laws on traffic fatalities of 15–17 year olds. The empirical results indicate that each of the laws has statistically significant effects on both multivehicle and single‐vehicle driver fatality rates. An important part of the effect of curfew laws, driving education laws, and, of course, driving age laws appears to occur through their effect on discouraging early licensure.In interpreting these results, certain potential limitations deserve mention. Correlation does not imply casuality; the effects of the laws might be due to other underlying causes. By including a variable for the 25–29‐year‐old fatality rate, the estimation equation does include a control for the fatality propensity in a particular state and year. However, the state laws might still reflect a reaction to 15–17 year old fatalities rates or to those factors that affect these rates. To the extent that states react to high 15–17‐year‐old fatalities by making youth traffic fatalities more stringent, the estimated effects of the laws will tend to be biased downward. Second, the estimates are average effects of laws across states and time. The nature of coverage for each law (e.g., the time of day covered by curfew laws) and the degree of enforcement efforts differs among states. Consequently, effects may vary for a particular law in different states. Finally, this study did not consider experience effects, i.e., the potential increase in fatalities when first year (inexperienced) drivers begin to drive.18 However, early studies by Levy(6) Robertson(5) and Williams et al.(2) indicate that experience effects do not significantly counteract the effects of raising driving ages.In sum, the results suggest that state laws, especially driving age laws, have important effects on youth fatalities. As earlier work also indicates (e.g., Ref. 2), raising the driving age merits serious consideration as a policy measure. The results on curfew laws are consistent with the earlier study by Preusser et al.(3) and are not surprising considering that young driver's spend a disproportionately larger amount of time than other age groups on the road.19 Unlike many early studies, the results here suggest that mandatory education laws have some salutory effect, where the alternative is the same minimum driving age but without a driver's education requirement. However, as suggested in other studies (e.g., Ref. 4), they are a poor substitute for raising the driving age. A final, albeit limited, measure is raising the age at which a learning permit can be obtained.

Since the mid-1970s, numerous states have raised their minimum legal drinking age in an effort to reduce alcohol-related traffic accidents. The determinants of a variety of traffic fatality rates are examined at the state level for 1978, with particular attention to drinking age & drinking experience. The legal drinking age has no perceptible influence on fatalities, but inexperience in drinking is an apparent risk factor independent of age. The findings suggest that the effectiveness of higher drinking ages as a safety policy tool probably has been overstated. 5 Tables. HA

The age‐period‐cohort model is known to provide an excellent description of the temporal trends in lung cancer incidence and mortality. This analytic approach is extended to include the contribution of carcinogenesis models for smoking. Usefulness of this strategy is that it offers a way to temporally calibrate a model that is fitted to population data and it can be readily adopted for the consideration of many different models. In addition, it provides diagnostics that can suggest temporal limitations of a particular carcinogenesis model in describing population rates. Alternative carcinogenesis models can be embedded within this framework. The two‐stage clonal expansion model is implemented here. The model was used to estimate the impact of tobacco control after dissemination of knowledge of the harmful effects of cigarette smoking by comparing the observed number of lung cancer deaths to those expected if there had been no control compared to an ideal of complete control in 1965. Results indicate that 35.2% and 26.5% of lung cancer deaths that could have been avoided actually were for males and females, respectively.

Past studies have examined the relationship of lung cancer to smoking using longitudinal data for select samples. This study applies the two‐stage clonal expansion (TSCE) model to U.S. +xsmoking data over a 25‐year period. Smoking Base Case (SBC) data on actual smoking duration and intensity from the years 1975–2000 are applied by gender to separate TSCE models, which are then calibrated to historical trends in lung cancer death rates using regression analysis. The uncalibrated and calibrated TSCE models are also applied to SBC data for two scenarios: (1) no tobacco control and (2) complete tobacco control. The results are used to develop estimates of the number of lives saved as a result of tobacco control and how many lives would be saved if cigarette use had ceased in 1965. Predictions of lung cancer from the TSCE models with CPS‐II and the CPS‐I data for males and especially females are considerably below historical rates with the deviations from historical rates increasing over time. Residual trends unrelated to the smoking models were also found. Tobacco control activities saved approximately 625,000 lives between the years 1975 and 2000. An additional 2,110,000 lives would have been saved if all smoking was stopped in 1965. Tobacco control has successfully prevented lung cancer deaths, but many more lives could be saved with further reductions in smoking rates. Systematic biases were observed from TSCE models using CPS‐I and CPS‐II data to estimate smoking‐related lung cancer deaths.

Background: A consortium of six research groups estimated the impact on lung cancer mortality of changes in smoking behavior that began around the publication of the Surgeon General's report (SGR). This chapter presents the results of that effort. We quantified the cumulative impact of changes in smoking behaviors on lung cancer mortality in the United States over the period 1975–2000. Methods: The six groups used common inputs and independent models to estimate the number of U.S. lung cancer deaths averted over the period 1975–2000 as a result of changes in smoking behavior beginning in the mid fifties, and the number of deaths that could have been averted if tobacco control had completely eliminated all smoking following issuance of the first SGR on Smoking and Health in 1964. Results: Approximately 795,000 deaths (550,000 men and 245,000 women) were averted over the period 1975–2000 as a result of changes in smoking behavior since in 1950s. In the year 2000 alone approximately 70,000 lung cancer deaths were averted (44,000 among men and 26,000 among women). However, these represent approximately 30% of lung cancer deaths that could have potentially been averted over the period 1975–2000 if smoking was eliminated completely. In the 10‐year period 1991–2000, this fraction increased to about 37%. Conclusions: Our results show the substantial impact of changes in smoking behavior since the 1950s. Despite a major impact of changing smoking behaviors, tobacco control effort are still needed to further reduce the burden of this disease.

To better understand the contribution of cigarette smoking, and its changing role in lung cancer, this article provides an introduction to a special issue of Risk Analysis, which considers the relationship between smoking and lung cancer death rates during the period 1975–2000 for U.S. men and women aged 30–84 years. Six models are employed, which are part of a consortium of lung cancer modelers funded by National Cancer Institute's Cancer Intervention and Surveillance Modeling Network (CISNET). Starting with birth‐cohort‐specific smoking histories derived from National Health Interview Surveys, three scenarios are modeled: Actual Tobacco Control (observed trends in smoking), Complete Tobacco Control (a counterfactual lower bound on smoking rates that could have been achieved had all smoking ceased after the first Surgeon General's report in 1964), and No Tobacco Control (a counterfactual upper bound on smoking rates if smoking patterns that prevailed before the first studies in the 1950s began to inform the public about the hazards of smoking). Using these three scenarios and the lung cancer models, the number and percentage of lung cancer deaths averted from 1975–2000, among all deaths that could have been averted if tobacco control efforts been immediate and perfect, can be estimated. The variability of the results across multiple models provides a measure of the robustness of the results to model assumptions and structure. The results provide not only a portrait of the achieved impact of tobacco control on lung cancer mortality, but also the bounds of what still needs to be achieved.