Biomedical subjects

David T Levy

Publications and source records attributed to David T Levy.

24 records · Page 2Linked to original sources

PubMed2002

The use of simulation models for the surveillance, justification and understanding of tobacco control policies.

Debates over national tobacco legislation and the use of state settlement funds demonstrate a need for information on the effects of tobacco control policies. Computer simulation models that are based on empirical evidence and that account for the variety of influences on tobacco use can be useful tools for informing policy makers. They can identify the effects of different policies, convey the importance of policy approaches to tobacco control, and help policy planners and researchers to better understand policies. This paper examines the role of simulation models in public policy, and discusses several recent models and limitations of those models.

Adolescent↗

PubMed2002

Blood alcohol content (BAC)-negative victims in alcohol-involved injury incidents.

AIMS: To understand better how often BAC-negative victims suffer fatal and non-fatal alcohol-involved injuries. DESIGN: We analyzed 1988-1993 data from Oklahoma surveillance systems that track all people killed or hospitalized due to burns, submersions and spinal cord injuries (SCIs) and investigate alcohol use by victims and any others who contributed to their injuries. MEASUREMENTS: Percentage of victims BAC-positive and percentage of victims BAC-negative in alcohol-involved incidents. FINDINGS: Of 5107 cases studied, alcohol involvement was known for 4773 (93%), 1882 fire burns (93%), 1560 scald and other burns (97%), 698 submersions (92%) and 967 spinal cord injuries (89%). By type of injuries, BAC-negative victims were 4%, 13%, 6% and 8% of alcohol-involved cases, respectively. CONCLUSION: A sizeable number of BAC-negative victims suffer alcohol-involved injuries. Although alcohol is not the cause of some of these injuries, alcohol policy changes probably could avert others.

Adolescent↗

PubMed2002

Reductions in smoking prevalence and cigarette consumption associated with mass-media campaigns.

This paper examines reductions in smoking prevalence and cigarette consumption associated with state and local mass-media campaigns. We review the findings of the empirical literature on campaigns targeted at the general population. We then discuss the findings on state- and community-level youth-oriented campaigns. The results suggest that well-funded and implemented mass-media campaigns targeted at the general population and implemented at the state level, in conjunction with a comprehensive tobacco control program, are associated with reduced smoking rates among both adults and youth. Studies of youth-oriented interventions specifically have shown more mixed results, particularly for smaller, community-level media programs, but they indicate strong potential to influence underage smoking rates. We conclude by examining issues that warrant additional research. The scale and duration of expenditures, the content of ad messages, and other tobacco control polices are aspects of media programs that may help explain differences among study results. In particular, tobacco control polices that are implemented during the campaign often make it difficult to identify the specific influence of media campaigns alone.

Adolescent↗

PubMedDate not supplied

The effects of tobacco control policies on smoking rates: a tobacco control scorecard.

This article reviews studies of the effect of tobacco control policies on smoking rates with the aim of providing guidance on the importance of different policies. Based on past studies, we estimate the magnitude of effects of major tobacco control policies, how their effects depend on the manner in which the policies are implemented, the relationship between the different policies, and the barriers to implementation. The most successful campaigns have implemented a combination of tobacco control policies. Of those policies, substantial evidence indicates that higher taxes and clean air laws can have a large impact on smoking rates. Evidence also indicates that media campaigns when implemented with other policies are important. Research on greater access to treatment and telephone support hotlines indicates a strong potential to increase quit rates and may be important in affecting heavier smokers. Direct evidence on the effects of advertising bans and health warnings is mixed, but these policies appear to be important in some of the countries that have had success in reducing smoking rates. School education programs and limits on retail sales are not likely to have much impact if implemented alone, but may be more important when combined with other policies.

Humans↗

PubMedDate not supplied

The role of public policies in reducing smoking prevalence and deaths caused by smoking in Arizona: results from the Arizona tobacco policy simulation model.

Arizona was one of the first few states to implement a comprehensive tobacco control program. The effect of that program is examined using a computer-simulation model (SimSmoke) developed for the purposes of evaluation, planning, and justifying policies. This approach assesses the impact to date of tobacco control policies on smoking prevalence and generates predictions about the effects of tobacco control policies on past and future smoking prevalence and associated future premature mortality. SimSmoke estimates indicate that tobacco control policies reduced smoking rates in Arizona by about 20 percent over the period 1993-2002. A previous CDC study obtains similar effects, but does not net out the effects of individual policies. SimSmoke attributes much of the reduction, about 61 percent, to price increases and attributes 38 percent of the overall effect to media policies, leaving only a small percentage of the smoking reductions attributed to quitlines, youth access policies, and the weak clean air laws. Tobacco control policies implemented as comprehensive strategies have significantly affected smoking rates in Arizona, which leads to large reductions in deaths attributable to smoking. It will be important to maintain these efforts over time to reduce or keep smoking prevalence down and to minimize smoking-attributable deaths.

Adult↗

PubMedDate not supplied

A simulation model of policies directed at treating tobacco use and dependence.

OBJECTIVES: The authors develop a simulation model to predict the effects on quit rates and cost-effectiveness of different smoking treatment policies. METHODS: A decision theoretic model of quit behavior is first developed that incorporates the decision to quit and the choice of treatment. A policy model then examines the effect on quit attempts and quit rates of policies to cover the costs of different combinations of treatments and to require health care providers to conduct brief interventions. The model incorporates substitution between treatments and effects of policies on treatment effectiveness. The cost per quit is also calculated for each policy. RESULTS: The model of quit behavior predicts a 1-year quit rate of 4.5% for the population of smokers. The policy model predicts a 37% increase in quit rates from a policy that combines mandated brief interventions with coverage of all proven tobacco treatments. Smaller effects are predicted from policies that provide more restricted coverage of treatments, especially those limited to behavioral treatment. Payments for brief interventions alone increase quit rates by about 7%. Brief intervention and behavioral therapy policies had lower costs per quit but yield substantially fewer additional quits than policies that cover pharmacotherapy. There is, however, considerable variation around these estimates depending on assumptions about the effects of policy on treatment use, substitution between treatments, and treatment effectiveness. CONCLUSION: Tobacco treatment policies, especially those with broad and flexible coverage, have the potential to substantially increase smoking quit rates. However, further research is needed on the effect of payment policies on the use and effectiveness of tobacco treatments.

Computer Simulation↗