These effects could result in temporally distinct yet still related changes between PCC and changes in alcohol-related morbidities. There are many reasons why the precision of PCC estimates matters. First, the Tax Cuts and Jobs Act of 2017 reduced excise taxes on all alcoholic beverages. A large body of evidence shows that decreases in alcohol taxes can result in increases in alcohol consumption , which can give rise to alcohol-related morbidity and mortality . If there is a further and continued increase in alcohol consumption by the U.S. population over age 15, then further increases in alcohol-related problems may be forthcoming, such as traffic accidents and suicides . Second, the recent legalization of recreational cannabis in many states is of concern in an environment of increasing alcohol use because of the negative impact of simultaneous cannabis and alcohol use, such as drunk driving, social consequences, and harms to self . Third, recent national surveys report a decline in both any alcohol use and binge drinking among youth , suggesting that the noted increase in PCC is due to more alcohol use and binge drinking among middle-aged and older adults. Indeed, recent surveys have observed an increase in self-reported past-month binge drinking and AUD among adults aged 50 and older , and an increase in alcohol-related emergency department visits . This is cause for concern because older adults are more likely to have various co-morbidities and to use medication that contraindicates the use of alcohol . Finally, the national surveys and meta-analysis that showed an increase in binge drinking generally may be particularly concerning if the alcohol content of the beverages being consumed is higher than previously assumed as this may increase the likelihood of negative alcohol-related consequences.
This work has limitations that should be considered when interpreting our results. The estimate for PCC from wine may have been underestimated from 2012 to 2016 since we carried forward the %ABV value for 30% of total sales volume from 2011 to 2016 instead of calculating from actual wine %ABV values. This change in methodology was due to changes in the availability of data,indoor grow shelves which also highlights the challenge of this methodology to identify adequate and reliable sources of information. Relatedly, how we calculated the mean %ABV of wine by identifying the leading brands of wine based on sales in Pennsylvania only is a limitation because it does not represent sales nationally. Since only general brands and not individual brands are reported nationally it is not possible to determine if using leading individual brand sales of wine in Pennsylvania would result in an over or underestimate of the mean %ABV of wine and thus its impact on PCC wine estimates. Regarding the %ABV of all alcoholic beverages, the %ABV value taken from producer reports or websites may not accurately reflect the actual amount of alcohol. This is less likely for spirits which are taxed based on alcohol content at the federal level, but may still be relevant for beer and wine which are not routinely tested by independent authorities, except in regard to labelling where considerable error is allowed. Regarding other components of the calculation of PCC estimates, population estimates may also represent another source of error as certain under counted groups, often rural and/or racial/ethnic minorities, and those not included in the population such as foreign tourists and undocumented immigrants, may comprise a greater proportion of the population in recent years . The alcohol sales data may also have error due to unaccounted for changes in reporting practices over time, variation by state, and the time delay between actual consumption and the publication of state tax records .
Moreover, alcohol sales data will not include unrecorded consumption from illicit production, importation, and sales. Fortunately, unrecorded consumption is likely minimal due to substantial decreases in illicit alcohol production in the U.S. since the 1970s . Similarly, cross-state sales are also present but not likely to have a significant impact on consumption estimates . However, these factors are a reality and may introduce inaccuracies into our PCC estimates . Finally, the likely errors in each component of the PCC calculation, that is, the alcohol sales figures, the %ABV values, and population estimates, would result in errors in the PCC estimates. Since these error values are unknown, however, statistical tests of differences between ABV-variant and ABV-invariant PCC estimates are not feasible. It is noteworthy that the population estimates and alcohol sales data are also components of the AEDS methodology such that the same errors are included in our PCC estimates. Further, the errors in the estimates of components of the PCC calculation beyond the %ABV values represent other possibilities for improving the precision of PCC estimates, such that refinements in alcohol sales figures and population estimates could improve PCC calculations. These refinements, however, would necessitate changes in the reporting and collection of these data, which would likely be more cumbersome than including data on annual changes in %ABV values of beer, wine, and spirits. The inclusion of time-varying %ABV in the calculation of PCC estimates showed increasing % ABVs for all beverage types, preferences for beverages with higher and increasing %ABV, and a greater increase in PCC estimates compared to those using time invariant %ABV values. PCC measures are used to explain changes in alcohol-related mortality and morbidity , for comparison of alcohol use across geographic regions , the study of alcohol policies , the examination of alcohol use over time, the calculation of global alcohol-attributable fractions, and to inform news articles about alcohol use in the U.S. .
It is therefore critical that PCC measures are as precise as possible to ensure that conclusions drawn from the applications of these measures are accurate and valid. Through the presentation of estimates based on ABV variation and comparisons to estimates from ABV-invariant methods we suggest that the inclusion of annual estimates of the %ABV of alcoholic beverages sold in the U.S. is necessary to ensure the precision of PCC measures and the accurate detection of changes in alcohol consumption over time and place. Drugs that activate cannabinoid receptors, the molecular target of Δ 9 -tetrahydrocannabinol in marijuana,indoor garden table reduce nausea and emesis produced by chemotherapy , alleviate pain symptoms associated with central and peripheral neuropathies , decrease pain and spasticity in multiple sclerosis , and improve psychomotor deficits in Tourette’s syndrome . Despite such broad therapeutic potential, the clinical usefulness of these agents is limited by their psychotropic and reinforcing effects, which account for the remarkable prevalence of marijuana as an abused drug.Mechanistically, they have been linked to the ability of these substances to activate CB1-type cannabinoid receptors in the central nervous system, enhance activity of midbrain dopaminergic neurons, and elicit dopamine release in the reward-controlling shell region of the nucleus accumbens . By contrast, the contribution of endocannabinoid signals to the regulation of normative reward-based behaviors is still unclear, despite indications that pharmacological or genetic interruption of CB1 receptor activity strongly affects such behaviors . One important set of questions that remains unanswered relates to the chemical neuroanatomy of endocannabinoid-mediated reward and, in particular, to the functions served by individual endocannabinoid substances in reward modulation. Two such substances have been characterized: anandamide and 2-arachidonoylglycerol .Both compounds are produced in and released from neuronal and glial cells upon demand, and are eliminated by uptake into cells followed by intracellular hydrolysis. In the brain, anandamide is primarily hydrolyzed by the postsynaptic membrane-associated amidase, fatty acid amide hydrolase,which also cleaves other non-cannabinoid fatty-acid ethanolamides such as oleoylethanolamide .
On the other hand, 2-AG is predominantly hydrolyzed by the presynaptic cytosolic lipase, monoacylglycerol lipase and, to a lesser extent, by two additional membrane-associated lipases, ABHD6 and ABHD12 . The existence of distinct biochemical pathways mediating the deactivation of anandamide and 2-AG suggests that selective pharmacological interruption of each of these pathways might help define the contribution of individual endocannabinoid signals to the modulation of reward. The compound URB597 is a potent and selective inhibitor of intracellular FAAH activity . In rodents, URB597 increases brain anandamide levels without changing the levels of 2-AG . Moreover, the drug elicits antinociceptive, anxiolytic-like, and antidepressant-like effects , which are likely mediated by enhanced anandamide activity at CB1 receptors, because they are attenuated by the CB1 antagonists rimonabant and AM251 . Importantly, URB597 does not cause place preference or substitute for THC in rat drug-discrimination tests, an indication that it may lack hedonic properties . In the present study, we investigated the rewarding properties of URB597 in squirrel monkeys, a primate species that has been extensively used to model human reward-based behavior and has provided precious insights into the reinforcing effects of cannabinoids . We first determined the effects of URB597 on endocannabinoid levels in areas of the brainassociated with reward, memory and emotional responses to stress. Next, we tested whether URB597 would either be self-administered by monkeys or would alter their self-administration of THC and cocaine. Finally, to assess the potential of URB597 to precipitate relapse to abuse in abstinent individuals, we examined its ability to reinstate extinguished drug-seeking behavior. Twenty three adult male squirrel monkeys weighing 0.9 to 1.1 kg were housed in individual cages in a temperature- and humidity-controlled room with unrestricted access to water. Monkeys were fed a daily ration consisting of five biscuits of high protein monkey diet and two pieces of Banana Softies that maintained their body weights at a constant level throughout the study. Fresh fruits, vegetables and environmental enrichment were provided daily. One group of five monkeys was used for experiments with the anandamide self-administration baseline: all monkeys had a history of anandamide self-administration . Another group of four monkeys was used for experiments with the THC self administration baseline: three monkeys had a history of THC self-administration and one monkey had history of anandamide self-administration . Another group of four monkeys was used for experiments with the cocaine self-administration baseline; all monkeys had a history of cocaine self-administration . A group of ten monkeys with no prior exposure to cannabinoids was used for neurochemical analyses . Adult male Wistar rats , n = 6–12 per group, were used for evaluation of brain lipid levels in rats. The animals were housed at constant room temperature and humidity under a 12-h light/dark cycle. Food and water were available ad libitum. Monkeys and rats were maintained in facilities fully accredited by AALAC and experiments were conducted in accordance with guidelines of the Institutional Animal Care and Use Committee of the Intramural Research Program, NIDA, NIH, and followed the Guidelines for the Care and Use of Mammals in Neuroscience and Behavioral Research . Experimental chambers and other apparatus used in this study were the same as previously described . Monkeys were surgically prepared with chronic indwelling venous catheters . The catheters were connected to polyethylene tubing, which passed out of the isolation chamber where it was attached to a motor-driven syringe pump. Before the start of each session, monkeys were placed into Plexiglas chairs and restrained in the seated position by waist locks. Before each session, catheters were flushed with 1 ml of saline and one priming injection was delivered . At the start of the session, the white house light was turned off and green stimulus lights were turned on. In the presence of the green lights, monkeys were required to make 10 responses on a lever to produce an injection of anandamide, THC or cocaine. Completion of 10 responses on the lever turned off the green lights and produced an intravenous injection of 40 µg/kg of anandamide, 4 µg/kg of THC or 30 µg/kg of cocaine paired with a 2-s illumination of amber stimulus lights . Duration of each injection was 0.2 s and injection volume was 0.2 ml. Each injection was followed by a 60-s timeout period, during which the chamber was dark and lever presses had no programmed consequences. One-hour sessions were conducted five days per week . All monkeys had learned to respond under the FR10 schedule for the particular training drug prior to beginning this study. After completing the previous experiments, monkeys self administered the training dose of each drug for at least five sessions until responding was stable .