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Age differences in adult past-year marijuana use and risk perceptions in the U.S., 2002–2013
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Abstracts / Drug and Alcohol Dependence 171 (2017) e2–e226
200,000–600,000 similar to those from animals receiving only the ALF-cV2 vaccine. The combination vaccine group sera inhibited the binding of cV2 to ␣47 integrin by 65%. Conclusions: The heroin-HIV vaccine induced protection against heroin challenge and very high titer cV2 antibodies, that blocked ␣47 integrin receptor binding, a proposed mechanism of efficacy of the V2 antibodies in RV144. The findings suggest that an effective heroin-HIV vaccine is feasible. Financial support: Support provided by a Cooperative Agreement (W81XWH-07-2-067) between the HJF and the US Army MRMC; NIDA Avant Garde award (1DP1DA034787-01); and the Intramural Research Programs of NIDA and NIAAA. http://dx.doi.org/10.1016/j.drugalcdep.2016.08.370 Does perceived availability of marijuana explain changes in marijuana use after medical marijuana law implementation among U.S. adults? Christine Mauro 1,∗ , Julian Santaella 2 , June H. Kim 2 , Melanie M. Wall 1 , Silvia S. Martins 2 1 Biostatistics, Columbia University, NY, NY, United States 2 Epidemiology, Columbia University, NY, NY, United States
Aims: Previous work showed an increase in marijuana use (MU) after passage of medical marijuana laws (MML) in those aged 26 and older, but not among those 12–17 and 18–25. Further, perceived availability (PA) of marijuana was found to be a partial mediator of this relationship. The current aim is to further characterize the associations between MU, MML, and PA by stratifying those 26 and older into three groups: 26–39, 40–64, or 65+. Methods: Data were from the National Survey of Drug Use and Health (NSDUH) restricted use data portal 2004–2013. The primary exposure was a time-varying indicator of state-level MML (0 = Before vs. 1 = After), the outcome was past-month MU, and the potential mediator was PA (easy vs. difficult). A multilevel logistic regression model of individual level data tested the state-level MML effect on MU and PA by age (26–39, 40–64, 65+). The model included a random intercept by state and controlled for secular trends and individual- and state-level covariates. Results: Among all age groups of interest (26–39, 40–64, 65+), prevalence of marijuana increased after MML passage. In those 26–39, prevalence increased from 8.9% to 10.2% (AOR = 1.2 [1.1, 1.3]); among those 40–64, from 4.5% to 6.0% (AOR: 1.4 [1.2, 1.5]); and among those 65+ from 0.3% to 0.8% (AOR: 2.6 [1.5, 4.6]). Controlling for MML, PA was significantly associated with MU in each age group. Further, in these age categories, passing an MML significantly increased PA of marijuana. After accounting for PA, the association between MML and MU decreased by 14.7%, 14.5%, and 13.0%, respectively, indicating that PA is a partial mediator. Conclusions: MU increased after passage of MML among adults ages 26–39, 40–64, and 65+. These increases were partially mediated by PA of marijuana. Further exploration of other factors related to availability of marijuana in states with MML are warranted. Financial support: Supported by NIH grant 1R01DA037866 (Martins). http://dx.doi.org/10.1016/j.drugalcdep.2016.08.371
Age differences in adult past-year marijuana use and risk perceptions in the U.S., 2002–2013 Pia M. Mauro ∗ , Dvora Shmulewitz, Deborah Hasin, Aaron L. Sarvet, Reanne Rahim-Juwel, Qiana Brown, Hannah Carliner, Melanie Wall, Silvia S. Martins Columbia University, New York, NY, United States Aims: Recent increases in marijuana use (MU) among U.S. adults call for a nuanced assessment of trends by age. We estimated agespecific trends in MU and perception of great risk of regular MU, and estimated the public health burden of adult MU in 2002–2013. Methods: Adults 18+ from the 2002–2013 National Surveys on Drug Use and Health were included (N = 451,160). Logistic regressions estimated temporal trends by age (18–25, 26–34, 35–49, 50–64, 65+) for past-year MU prevalence and perception of great risk of regular MU, adjusting for complex sampling, sex, race/ethnicity, income, education, and marital status. Age-year interactions tested differences in rate of change; changes in the number of adults reporting past-year MU from 2002 to 2013 were estimated. Results: In 2002, 30.1% of adults ages 18–25, 14.8% of 26–34, 9.1% of 35–49, 3.4% of 50–64, and 0.6% of 65+ reported past-year MU. By 2013, MU increased significantly for all ages except 3549. Rate of increase differed by age (interaction p < .001), and was greatest in magnitude for ages 50 and older. By age, the estimated additional adult past-year users in 2013 compared to 2002 were 2.2 million ages 18–25, 2.5 million ages 26–34, 3.2 million ages 50–64, and 0.5 million ages 65 and older. In 2002, 35.3% of adults ages 18–25, 45.9% of 26–34, 49.4% of 35–49, 57.1% of 50–64, and 66.1% of 65+ perceived great risk of regular MU; this decreased significantly for all ages by 2013. Rate of decrease differed by age (interaction p < .001), and was greatest in magnitude for ages 26–34 and 50–64, and smallest for ages 35–49. Conclusions: In a changing marijuana policy landscape, public health consequences and implications of the growing number of younger (18–34) and older (50+) adults reporting MU (and perceiving its use to be less risky) requires attention, particularly as baby boomers (50+) enter older adulthood. In the 35–49 age group, potential age-specific buffering factors affecting MU (e.g., number of young children) should be explored. Financial support: T32DA031099, R01DA037866, R01DA034244, New York State Psychiatric Institute. http://dx.doi.org/10.1016/j.drugalcdep.2016.08.372 Methamphetamine dependence linked to interoceptive processing deficits during aversive breathing load April Chelsea May 1,∗ , Jennifer Lorraine Stewart 4 , Paul Davenport 2 , Susan Tapert 1 , Martin P. Paulus 3 1
UC San Diego, San Diego, CA, United States Physiological Sciences, University of Florida, Gainesville, FL, United States 3 Laureate Institute for Brain Research, Tulsa, OK, United States 4 Queens College, City University of New York, Flushing, NY, United States 2
Aims: Inspiratory breathing load is an experimental tool to induce a negative interoceptive state and investigate the processes that contribute to drug-taking behavior as a consequence of negative reinforcement mechanisms. Previous studies have shown
Abstracts / Drug and Alcohol Dependence 171 (2017) e2–e226
200,000–600,000 similar to those from animals receiving only the ALF-cV2 vaccine. The combination vaccine group sera inhibited the binding of cV2 to ␣47 integrin by 65%. Conclusions: The heroin-HIV vaccine induced protection against heroin challenge and very high titer cV2 antibodies, that blocked ␣47 integrin receptor binding, a proposed mechanism of efficacy of the V2 antibodies in RV144. The findings suggest that an effective heroin-HIV vaccine is feasible. Financial support: Support provided by a Cooperative Agreement (W81XWH-07-2-067) between the HJF and the US Army MRMC; NIDA Avant Garde award (1DP1DA034787-01); and the Intramural Research Programs of NIDA and NIAAA. http://dx.doi.org/10.1016/j.drugalcdep.2016.08.370 Does perceived availability of marijuana explain changes in marijuana use after medical marijuana law implementation among U.S. adults? Christine Mauro 1,∗ , Julian Santaella 2 , June H. Kim 2 , Melanie M. Wall 1 , Silvia S. Martins 2 1 Biostatistics, Columbia University, NY, NY, United States 2 Epidemiology, Columbia University, NY, NY, United States
Aims: Previous work showed an increase in marijuana use (MU) after passage of medical marijuana laws (MML) in those aged 26 and older, but not among those 12–17 and 18–25. Further, perceived availability (PA) of marijuana was found to be a partial mediator of this relationship. The current aim is to further characterize the associations between MU, MML, and PA by stratifying those 26 and older into three groups: 26–39, 40–64, or 65+. Methods: Data were from the National Survey of Drug Use and Health (NSDUH) restricted use data portal 2004–2013. The primary exposure was a time-varying indicator of state-level MML (0 = Before vs. 1 = After), the outcome was past-month MU, and the potential mediator was PA (easy vs. difficult). A multilevel logistic regression model of individual level data tested the state-level MML effect on MU and PA by age (26–39, 40–64, 65+). The model included a random intercept by state and controlled for secular trends and individual- and state-level covariates. Results: Among all age groups of interest (26–39, 40–64, 65+), prevalence of marijuana increased after MML passage. In those 26–39, prevalence increased from 8.9% to 10.2% (AOR = 1.2 [1.1, 1.3]); among those 40–64, from 4.5% to 6.0% (AOR: 1.4 [1.2, 1.5]); and among those 65+ from 0.3% to 0.8% (AOR: 2.6 [1.5, 4.6]). Controlling for MML, PA was significantly associated with MU in each age group. Further, in these age categories, passing an MML significantly increased PA of marijuana. After accounting for PA, the association between MML and MU decreased by 14.7%, 14.5%, and 13.0%, respectively, indicating that PA is a partial mediator. Conclusions: MU increased after passage of MML among adults ages 26–39, 40–64, and 65+. These increases were partially mediated by PA of marijuana. Further exploration of other factors related to availability of marijuana in states with MML are warranted. Financial support: Supported by NIH grant 1R01DA037866 (Martins). http://dx.doi.org/10.1016/j.drugalcdep.2016.08.371
Age differences in adult past-year marijuana use and risk perceptions in the U.S., 2002–2013 Pia M. Mauro ∗ , Dvora Shmulewitz, Deborah Hasin, Aaron L. Sarvet, Reanne Rahim-Juwel, Qiana Brown, Hannah Carliner, Melanie Wall, Silvia S. Martins Columbia University, New York, NY, United States Aims: Recent increases in marijuana use (MU) among U.S. adults call for a nuanced assessment of trends by age. We estimated agespecific trends in MU and perception of great risk of regular MU, and estimated the public health burden of adult MU in 2002–2013. Methods: Adults 18+ from the 2002–2013 National Surveys on Drug Use and Health were included (N = 451,160). Logistic regressions estimated temporal trends by age (18–25, 26–34, 35–49, 50–64, 65+) for past-year MU prevalence and perception of great risk of regular MU, adjusting for complex sampling, sex, race/ethnicity, income, education, and marital status. Age-year interactions tested differences in rate of change; changes in the number of adults reporting past-year MU from 2002 to 2013 were estimated. Results: In 2002, 30.1% of adults ages 18–25, 14.8% of 26–34, 9.1% of 35–49, 3.4% of 50–64, and 0.6% of 65+ reported past-year MU. By 2013, MU increased significantly for all ages except 3549. Rate of increase differed by age (interaction p < .001), and was greatest in magnitude for ages 50 and older. By age, the estimated additional adult past-year users in 2013 compared to 2002 were 2.2 million ages 18–25, 2.5 million ages 26–34, 3.2 million ages 50–64, and 0.5 million ages 65 and older. In 2002, 35.3% of adults ages 18–25, 45.9% of 26–34, 49.4% of 35–49, 57.1% of 50–64, and 66.1% of 65+ perceived great risk of regular MU; this decreased significantly for all ages by 2013. Rate of decrease differed by age (interaction p < .001), and was greatest in magnitude for ages 26–34 and 50–64, and smallest for ages 35–49. Conclusions: In a changing marijuana policy landscape, public health consequences and implications of the growing number of younger (18–34) and older (50+) adults reporting MU (and perceiving its use to be less risky) requires attention, particularly as baby boomers (50+) enter older adulthood. In the 35–49 age group, potential age-specific buffering factors affecting MU (e.g., number of young children) should be explored. Financial support: T32DA031099, R01DA037866, R01DA034244, New York State Psychiatric Institute. http://dx.doi.org/10.1016/j.drugalcdep.2016.08.372 Methamphetamine dependence linked to interoceptive processing deficits during aversive breathing load April Chelsea May 1,∗ , Jennifer Lorraine Stewart 4 , Paul Davenport 2 , Susan Tapert 1 , Martin P. Paulus 3 1
UC San Diego, San Diego, CA, United States Physiological Sciences, University of Florida, Gainesville, FL, United States 3 Laureate Institute for Brain Research, Tulsa, OK, United States 4 Queens College, City University of New York, Flushing, NY, United States 2
Aims: Inspiratory breathing load is an experimental tool to induce a negative interoceptive state and investigate the processes that contribute to drug-taking behavior as a consequence of negative reinforcement mechanisms. Previous studies have shown