Diffusion of Impaired Driving Laws Among US States

State-level factors associated with implementation of prescription drug monitoring program integration and mandatory use policies, United States, 2009-2020

BACKGROUND

Prescription drug monitoring programs (PDMPs) have been widely adopted as a tool to address the prescription opioid epidemic in the United States. PDMP integration and mandatory use policies are 2 approaches states have implemented to increase use of PDMPs by prescribers. While the effectiveness of these approaches is mixed, it is unclear what factors motivated states to implement them. This study examines whether opioid dispensing, adverse health outcomes, or other non-health-related factors motivated implementation of these PDMP approaches.

METHODS

Time-to-event analysis was performed using lagged state-year covariates to reflect values from the year prior. Extended Cox regression estimated the association of states' rates of opioid dispensing, prescription opioid overdose deaths, and neonatal opioid withdrawal syndrome with implementation of PDMP integration and mandatory use policies from 2009 to 2020, controlling for demographic and economic factors, state government and political factors, and prior opioid policies.

RESULTS

In our main model, prior opioid dispensing (HR 2.31, 95% CI 1.17, 4.57), neonatal opioid withdrawal syndrome hospitalizations (HR 1.55, 95% CI 1.09, 2.19), and number of prior opioid policies (HR 2.13, 95% CI 1.13, 4.00) were associated with mandatory use policies. Prior prescription opioid overdose deaths (HR 1.21, 95% CI 1.08, 1.35) were also associated with mandatory use policies in a model that did not include opioid dispensing or neonatal opioid withdrawal syndrome. No study variables were associated with implementation of PDMP integration.

CONCLUSION

Understanding state-level factors associated with implementing PDMP approaches can provide insights into factors that motivate the adoption of future public health interventions.

Policy diffusion theory, evidence-informed public health, and public health political science: a scoping review

OBJECTIVES

Our aim was to synthesize published scholarship that applies policy diffusion-a theory of the policy process that considers the interdependence of government-level public health policy choices. We paid particular attention to the role of scientific evidence in the diffusion process, and to identifying challenges and gaps towards strengthening the intersection of public health, public policy, and political science.

METHODS

We systematically searched 17 electronic academic databases. We included English-language, peer-reviewed articles published between 2000 and 2021. For each article, we extracted the following information: public health policy domain, geographic setting, diffusion directions and mechanisms, the role of scientific evidence in the diffusion process, and author research discipline.

SYNTHESIS

We identified 39 peer-reviewed, primary research articles. Anti-smoking and tobacco control policies in the United States (n = 9/39) were the most common policy domain and geographic context examined; comparatively fewer studies examined policy diffusion in the Canadian context (n = 4/39). In terms of how policies diffuse, we found evidence of five diffusion mechanisms (learning, emulation, competition, coercion, and social contagion), which could moreover be conditional on internal government characteristics. The role of scientific evidence in the diffusion process was unclear, as only five articles discussed this. Policy diffusion theory was primarily used by public policy and political science scholars (n = 19/39), with comparatively fewer interdisciplinary authorship teams (n = 6/39).

CONCLUSION

Policy diffusion theory provides important insights into the intergovernmental factors that influence public health policy decisions, thus helping to expand our conceptualization of evidence-informed public health. Despite this, policy diffusion research in the Canadian public health context is limited.

Following the Science? Examining the Issuance of Stay-At-Home Orders Related to COVID-19 by U.S. Governors

Informed by the public health policymaking literature, this study's objective is to identify scientific, political, social, economic, and external factors related to U.S. governors' decisions to issue stay-at-home orders (SAHOs) in response to the first wave of the COVID-19 pandemic. Public health experts advocate for social distancing to slow the spread of infectious diseases, but government mandates to social distance can impose substantial social and economic costs. This study uses event history analysis to investigate the issuance of COVID-19-related gubernatorial SAHOs during a 41-day period in the 50 U.S. states. The findings indicate that scientific, political, and economic factors were associated with the issuance of SAHOs, but that external considerations played the largest role, particularly those related to the timing of other governors' decisions. This study offers evidence about how some U.S. political leaders balance public health concerns against other considerations and, more broadly, how state governments address crisis-level issues.

What factors drive state firearm law adoption? An application of exponential-family random graph models

Guns are a ubiquitous feature of contemporary US culture, driven, at least partly, by firearms' constitutional enshrinement. However, the majority of laws intended to restrict or expand firearm access and use are formulated and passed in the states, leading to 50 different firearm-related legal environments. To date, little is known about why some states pass more restrictive or permissive firearm laws than others. In this article, we identify patterns of firearm law adoption across states, by framing the problem as a bipartite network (states connected to laws and laws connected to states) that is the result of a complex, and interconnected system of unobserved forces. We employ Exponential-family Random Graph Models (ERGMs), a class of statistical network models that allow for the dispensing of the assumptions of statistical independence, to identify factors that increase or decrease the likelihood of states adopting permissive or restrictive firearms laws over the period 1979 to 2020. Results show that more progressive state governments are associated with a higher chance of enacting restrictive firearm laws, and a lower chance of enacting permissive ones. Conservative state governments are associated with the analogous reversed association. States are more likely to adopt laws if bordering states have also adopted that law. For both restrictive and permissive laws the presence of a law in a neighboring state increased the conditional likelihood of a state having that law, that is laws diffuse across state borders. High levels of homicides are associated with a state having adopted more permissive, but not more restrictive, firearm laws. In summary, these results point to a complex interplay of state internal and external factors that seem to drive different patterns of firearm law adoption Based on these results, future work using related classes of models that take into account the time evolution of the network structure may provide a means to predict the likelihood of future law adoption.

Predictors of US states' adoption of naloxone access laws, 2001-2017

BACKGROUND

The opioid crisis has put an increasing strain on US states over the last two decades. In response, all states have passed legislation to implement a portfolio of policies to address the crisis. Although effects of some of these policies have been studied, research into factors associated with state policy adoption decisions has largely been lacking. We address this gap by focusing on factors associated with adoption of naloxone access laws (NAL), which aim to increase the accessibility and availability of naloxone in the community as a harm reduction strategy to reduce opioid-related morbidity and mortality.

METHODS

We used event history analysis (EHA) to identify predictors of the diffusion of naloxone access laws (NAL) from 2001, when the first NAL was passed, to 2017, when all states had adopted NAL. A variety of state characteristics were included in the model as potential predictors of adoption.

RESULTS

We found that state adoption of NAL increased gradually, then more rapidly starting in 2013. Consistent with this S-shaped diffusion process, the strongest predictor of adoption was prior adoption by neighboring states. Having a more conservative political ideology and having a higher percentage of residents who identified as evangelical Protestants were associated with later adoption of NAL.

CONCLUSION

States appear to be influenced by their neighbors in deciding whether and when to adopt NAL. Advocacy for harm reduction policies like NAL should take into account the political and religious culture of a state.

Identifying factors associated with the issuance of coronavirus-related stay-at-home orders in the Middle East and North Africa Region

The COVID-19 pandemic has not spared the Middle East and North Africa (MENA) Region. MENA is one of the most politically, socially, and economically heterogeneous regions in the world, a characteristic reflected in its governments' responses to COVID-19. About two-thirds of these governments issued coronavirus-related stay-at-home orders (SAHOs), one of the most effective tools public health officials have for slowing the spread of infectious diseases. While SAHOs are very effective in terms of countering infectious diseases, they are extremely disruptive in nonhealth domains. The objective of this study is to identify reliable factors related to health care policy making that shaped the decisions of MENA governments to issue a SAHO or not in response to COVID-19. The results identify specific political, social, and medical factors that played important roles and provide a look at early government responses to a global health crisis in a heterogeneous region of the world.

Deterring Drunk Driving: Why Some States Go Further Than Others in Policy Innovation

Policy innovation and diffusion studies have, since 1990, generally focused on a specific policy over time. Yet, few studies have considered if and why states adopt related multiple policies-a package of reforms-in a policy area. Are more innovative states in DUI policy likely to adopt a comprehensive set of policies or use them as substitutes for each other? In this study, we assess how overall state innovativeness relates to the adoption of sixteen DUI (Driving Under the Influence) laws. We find that state innovativeness in traffic safety policies (but not overall policy innovativeness), organizational size, and professionalism of a state highway department increase the likelihood that a state will adopt a more comprehensive bundle of DUI laws. Furthermore, we also test whether institutional or competitive bandwagon effects are found across this policy area and demonstrate that national institutional bandwagon effects are an important factor related to the increased comprehensiveness of state adoption of DUI policies.

What factors predict the passage of state-level e-cigarette regulations?

E-cigarettes are controversial products. They may help addicted smokers to consume nicotine in a less harmful manner or to quit tobacco cigarettes entirely, but these products may also entice youth into smoking. This controversy complicates e-cigarette regulation as any regulation may lead to health improvements for some populations, and health declines for other populations. Using data from 2007 to 2016, we examine factors that are plausibly linked with U.S. state e-cigarette regulations. We find that less conservative states are more likely to regulate e-cigarettes and that states with stronger tobacco lobbies are less likely to regulate e-cigarettes. This information can help policymakers as they determine how best to promote public health through regulation.

Are political views related to smoking and support for tobacco control policies? A survey across 28 European countries

BACKGROUND

General political views are rarely considered when discussing public support for tobacco control policies and tobacco use. The aim of this study was to explore potential associations between political views, smoking and support for tobacco control policies.

METHODS

We analysed responses from 22,313 individuals aged ≥15 years from 28 European Union (EU) member states, who self-reported their political views (far-left [1-2 on a scale 1-10]; centre-left (3-4); centre (5-6); centre-right (7-8); and far-right (9-10) in wave 82.4 of the Eurobarometer survey in 2014. We ran multi-level logistic regression models to explore associations between political views and smoking, as well as support for tobacco control policies, adjusting for socio-demographic factors.

RESULTS

Compared to those placing themselves at the political centre, people with far-left political views were more likely to be current smokers (Odds Ratio [OR] = 1.13; 95% Confidence Interval [CI]: 1.01-1.26), while those in the centre-right were the least likely to smoke (OR = 0.84; 95% CI: 0.76-0.93). Similar associations were found for having ever been a smoker. Respondents on the left side of the political spectrum were more likely to support tobacco control policies and those on the centre-right were less likely to support them, as compared to those at the political centre, after controlling for smoking status.

CONCLUSIONS

General political views may be associated not only with support for tobacco control policies, but even with smoking behaviours, which should be taken into account when discussing these issues at a population level. Further research is needed to explore the implications of these findings.

State political ideology, policies and health behaviors: The case of tobacco

Anti-smoking campaigns are widely viewed as a success case in public health policy. However, smoking rates continue to vary widely across U.S. states and the success of anti-smoking campaigns is contingent upon states' adoption of anti-smoking policies. Though state anti-smoking policy is a product of a political process, studies of the effect of policies on smoking prevalence have largely ignored how politics shapes policy adoption, which, in turn, impact state health outcomes. Policies may also have different effects in different political contexts. This study tests how state politics affects smoking prevalence both through the policies that states adopt (with policies playing a mediating role on health outcomes) or as an effect modifier of behavior (tobacco control policies may work differently in states in which the public is more or less receptive to them). The study uses publicly available data to construct a time-series cross-section dataset of state smoking prevalence, state political context, cigarette excise taxes, indoor smoking policies, and demographic characteristics from 1995 to 2013. Political ideology is measured using a validated indicator of the ideology of state legislatures and of the citizens of a state. We assess the relationship between state political context and state smoking prevalence rates adjusting for demographic characteristics and accounting for the mediating/moderating role of state policies with time and state fixed effects. We find that more liberal state ideology predicts lower adult smoking rates, but that the relationship between state ideology and adult smoking prevalence is only partly explained by state anti-smoking policies.

Detecting causality in policy diffusion processes

A universal question in network science entails learning about the topology of interaction from collective dynamics. Here, we address this question by examining diffusion of laws across US states. We propose two complementary techniques to unravel determinants of this diffusion process: information-theoretic union transfer entropy and event synchronization. In order to systematically investigate their performance on law activity data, we establish a new stochastic model to generate synthetic law activity data based on plausible networks of interactions. Through extensive parametric studies, we demonstrate the ability of these methods to reconstruct networks, varying in size, link density, and degree heterogeneity. Our results suggest that union transfer entropy should be preferred for slowly varying processes, which may be associated with policies attending to specific local problems that occur only rarely or with policies facing high levels of opposition. In contrast, event synchronization is effective for faster enactment rates, which may be related to policies involving Federal mandates or incentives. This study puts forward a data-driven toolbox to explain the determinants of legal activity applicable to political science, across dynamical systems, information theory, and complex networks.

Impact of State Ignition Interlock Laws on Alcohol-Involved Crash Deaths in the United States

OBJECTIVES

To investigate the impact on alcohol-involved crash deaths of universal ignition interlock requirements, which aim to prevent people convicted of driving under the influence of alcohol from driving while intoxicated.

METHODS

We used data from the National Highway Traffic Safety Administration for 1999 to 2013. From 2004 to 2013, 18 states made interlocks mandatory for all drunk-driving convictions. We compared alcohol-involved crash deaths between 18 states with and 32 states without universal interlock requirements, accounting for state and year effects, and for clustering within states.

RESULTS

Policy impact was apparent 3 years after implementation. The adjusted rate of alcohol-involved crash deaths was 4.7 (95% confidence interval [CI] = 4.0, 5.4) per 100,000 in states with the universal interlock requirement, compared with 5.5 (95% CI = 5.48, 5.53) in states without, an absolute reduction of 0.8 (95% CI = 0.1, 1.5) deaths per 100,000 per year.

CONCLUSIONS

Requiring ignition interlocks for all drunk-driving convictions was associated with 15% fewer alcohol-involved crash deaths, compared with states with less-stringent requirements. Interlocks are a life-saving technology that merit wider use.