BACKGROUND: The relationship between economic conditions and substance abuse is unclear, with few studies reporting drug-specific substance abuse. The present study examined the association between economic conditions and drug-specific substance abuse admissions. METHODS: State annual administrative data were drawn from the 1993-2016 Treatment Episode Data Set. The outcome variable was state-level aggregate number of treatment admissions for six categories of primary substance abuse (alcohol, marijuana/hashish, opiates, cocaine, stimulants, and other drugs). Additionally, we used a broader outcome for the number of treatment admissions, including primary, secondary, and tertiary diagnoses. We used a quasi-experimental approach -difference-in-difference model- to estimate the association between changes in economic conditions and substance abuse treatment admissions, adjusting for state characteristics. In addition, we performed two additional analyses to investigate (1) whether economic conditions have an asymmetric effect on the number of substance use admissions during economic downturns and upturns, and (2) the moderation effects of economic recessions (2001, 2008-09) on the relationship between economic conditions and substance use treatment. RESULTS: The baseline model showed that unemployment rate was significantly associated with substance abuse treatment admissions. A unit increase in state unemployment rate was associated with a 9% increase in treatment admissions for opiates (β = 0.087, p < .001). Similar results were found for other substance abuse treatment admissions (cocaine (β = 0.081, p < .001), alcohol (β = 0.050, p < .001), marijuana (β = 0.036, p < .01), and other drugs (β = 0.095, p < .001). Unemployment rate was negatively associated with treatment admissions for stimulants (β = - 0.081, p < .001). The relationship between unemployment rate and opioids treatment admissions was not statistically significant in models that adjusted for state fixed effects and allowed for a state- unique time trend. We found that the association between state unemployment rates and annual substance abuse admissions has the same direction during economic downturns and upturns. During the economic recession, the negative association between unemployment rate and treatment admissions for stimulants was weakened. CONCLUSION: These findings suggest that economic hardship may have increased substance abuse. Treatment for substance use of certain drugs and alcohol should remain a priority even during economic downturns.

The moral hazard theory asserts that having health insurance may increase individual risk-taking behaviors. We examined the association between state health insurance coverage and excessive alcohol use among U.S. adults. We used 2001-2017 Behavioral Risk Factor Surveillance System data to estimate annual binge and heavy drinking rates for each state. In a multivariable regression analysis, we used difference-in-difference (DID) models to assess the association between state-level insurance coverage and binge and heavy drinking. Additionally, we assess the potential asymmetric effect and whether economic recessions (2001, 2008-09) had a moderation effect. In the multivariable DID analysis, aggregate state insurance coverage was not significantly associated with binge drinking rates in baseline analysis with state-fixed effects (Model 1), and in the analysis that extends the baseline model to include state unique time trend (Model 2). A similar result was found for heavy drinking in Model 1. In contrast, the result showed a significant association between health insurance coverage and heavy drinking rates in Model 2. However, we found no significant association for binge and heavy drinking rates in both models in the analyses restricting data to periods before the methodological change in the BRFSS sampling frame. The results did not show asymmetric effects, and the association between health insurance and excessive alcohol use did not differ during economic recessions. These findings largely do not support assertions that health insurance may lead to moral hazards (risk-taking behaviors), especially binge drinking.

Prescription-opioid misus e continues to be a significant health concern in the United States. The relationship between marijuana use and prescription-opioid misuse is not clear from the extant literature. This study examined national trends in prescription-opioid misuse among marijuana users and non-users using the 2007-2017 National Survey on Drug Use and Health. Cochran-Armitage tests were used to assess the statistical significance of changes in the yearly prevalence of prescription-opioid misuse and marijuana use. Multivariable logistic regression was used to examine the association between prescription-opioid and marijuana use adjusting for sociodemographic characteristics. From 2007 to 2017, marijuana use increased, while prescription-opioid misuse declined. Larger declines in prescription-opioid misuse were found among marijuana users than non-users. Marijuana ever-use was significantly associated with prescription-opioid misuse. Specifically, marijuana ever-users had higher odds of prescription-opioid misuse (ever-misuse [OR: 3.04; 95% CI, 2.68-3.43]; past-year misuse [OR: 3.44; 95% CI, 3.00-3.94]; and past-month misuse [OR: 4.50; 95% CI, 3.35-6.05]) compared to marijuana never-users. Similar results were found for the association of past-year and past-month marijuana use with prescription-opioid misuse. This study provides data on trends and associations about opioid misuse among marijuana users and non-users in a changing social environment of drug use in the United States. Future research should consider whether there is a causal relationship between marijuana use and prescription opioid misuse.

BACKGROUND: Many states in the U.S. still have Alcohol Exclusion Laws (AELs), which allow insurance companies to deny health claims resulting from alcohol impairment. There are concerns that this form of structural stigmatization affects alcohol treatment-seeking behaviors. We examined the effects of AEL repeal on treatment admissions for alcohol use disorder (AUD). METHODS: Data on alcohol treatment admissions from 1992 to 2017 were obtained from the Treatment Episode Data Set. The state-level aggregate number of treatment admissions was derived, including healthcare professional referrals only, self-referrals only, and both self-referral and healthcare professional referrals. The number of treatment admissions by health insurance status (private, public, and uninsured) was also calculated. The study used a difference-in-differences (DID) quasi-experimental design. RESULTS: The DID analysis showed that the number of admissions for alcohol treatment from healthcare professional referrals increased 16% in the AEL repeal states compared to states with AELs or that never had AELs (IRR=1.16, 95% CI=1.07, 1.25). These results were consistent for analysis by payment sources. In particular, treatment admissions from healthcare professional referrals for patients covered by private insurance increased about 38% in states with AEL repeal (IRR=1.38, 95% CI=1.17, 1.64) compared to states without AEL repeal. However, the findings were no longer significant when the state-specific time trends were taken into account. CONCLUSIONS: This study documented that AEL repeal may have had a significant impact on the number of treatment admissions for AUD. These findings suggest that AELs function as a barrier to treatment-seeking behavior.

BACKGROUND: Individuals with alcohol-related disorders often encounter barriers to accessing treatment. One potential barrier is the state alcohol exclusion laws (AELs) that allow insurers to deny coverage for injuries or illnesses caused by alcohol intoxication. Several states have repealed AELs by prohibiting them completely, including banning exclusions in health and accident insurance policies, limiting their scope, or creating exemptions. OBJECTIVES: To examine whether prohibiting alcohol exclusions in health and accident insurance policies is associated with alcohol-related treatment admissions. DESIGN: We used the 2002 to 2017 Treatment Episode Data Set and obtained data from several sources to control for state-level factors. We employed a heterogeneous difference-in-differences method and an event study to compare the treatment admissions in Colorado and Illinois, two states that uniquely repealed AELs, with control states that allowed or had no AELs. MAIN MEASURES: We used aggregated alcohol treatment admission for adults by healthcare referral: (i) with alcohol as the primary substance and (ii) with alcohol as the primary, secondary, or tertiary substance. KEY RESULTS: We found a significant relationship between AEL repeal and increased referrals. AEL repeal in Colorado and Illinois was associated with higher treatment admissions from 2008 to 2011 (average treatment effect on the treated: 2008 = 653, 2009 = 1161, 2010 = 1388, and 2011 = 2020). We also found that a longer duration of exposure to AEL repeal was associated with higher treatment admissions, but this effect faded after the fourth year post-treatment. CONCLUSIONS: Our study reveals a potential positive association between the repeal and prohibition of AELs and increased alcohol-related treatment admissions. These findings suggest that states could enhance treatment opportunities for alcohol-related disorders by reconsidering their stance on AELs. While our study highlights the possible public health benefits of repealing AELs, it also paves the way for additional studies in this domain.

BACKGROUND: For decades, alcohol exclusion laws (AELs) have allowed insurance companies to reject claims for physical injuries caused by alcohol consumption, including injuries from impaired driving. A central premise of AELs is that they function as a deterrent to risk-taking behaviors, such as excessive drinking. If this assumption is correct, state repeal of these laws should result in increased drinking. This study examines whether the repeal of AELs by some states affects drinking behaviors. METHODS: Data were obtained from the 1993 to 2017 Behavioral Risk Factor Surveillance System nationwide survey. Exploiting the natural experiment presented by state repeal of AELs, we assessed the impact on current drinking and binge drinking. We used a rigorous quasi-experimental difference-in-differences analysis and conducted a battery of sensitivity analyses to assure robust findings. RESULTS: Overall, the study found no discernable impact of state repeal of AELs on alcohol consumption. While the repeal of AELs significantly decreased the odds of reporting drinking in the past 30 days compared to those living in states with AELs or that never had AELs, the effects were small (aOR = 0.98, 95% CI = 0.96, 0.99). Likewise, there were higher odds of binge drinking among individuals living in states that repealed AELs compared to those living in states without AELs, yet with small effects (aOR = 1.03, 95% CI = 1.01, 1.05). After additionally adjusting for state-varying characteristics and state-specific time trends, no significant effects were identified regarding current and binge drinking. Findings from the sensitivity analyses were largely consistent with the main analysis. CONCLUSION: This study found no evidence supporting the idea that repealing AELs increased alcohol consumption or binge drinking. Future studies should consider other state-specific dimensions within the Uniform Accident and Sickness Policy Provision Law.

BACKGROUND: This study examines how the North Carolina state prevention system responded to a policy shift from individual-level prevention strategies to environmental strategies from the perspective of the organizations implementing the policy shift. METHODS: We use two data sources. First, we conducted interviews to collect qualitative data from key informants. Second, we used prevention provider agency expenditure data from the year the shift was announced and the following year. RESULTS: The interviews allowed us to identify effective features of policy change implementation in complex systems, such as the need for clear communication and guidance about the policy changes. Our interview and expenditure analyses also underscore variation in the level of guidance and oversight provided by implementing agencies to prevention providers. CONCLUSIONS: Our analyses suggest that more active monitoring and oversight may have facilitated more consistent implementation of the policy shift toward greater use of environmental prevention strategies.