Insurance coverage may alter the volume of hospital visits for other conditions, during which additional drug-related diagnoses may also be identified and captured as secondary diagnoses. We aggregated visits by month, gender-age, and race/ethnicity. Rate denominators came from the American Community Survey’s five-year 2015 population estimates broken down by age group, gender, and race/ethnicity . To evaluate whether changes in SUD-related hospital visits were attributable to Prop 47, we assessed whether county-level changes in drug arrest rates were associated with county-level changes in SUDrelated hospital visit rates. The measure of change for both variables was defined as the difference in the observed and expected rates during the ten months post-policy period, for each county and gender-age group. To estimate expected rates, we modeled monthly county rates with cluster robust standard errors using a Poisson specification and county fixed effects, stratifying models by gender-age group. Calendar month dummies controlled for seasonal trends, and a continuous linear term for months controlled for secular trends. A binary variable indicated whether the period was pre- or post-policy. To project post-policy rates based on pre-policy trends, we created duplicate observations but set the post-policy binary variable to zero, such that model predictions were based on how trends were expected to proceed in the absence of the policy. We then calculated the model-predicted rate for the 10-month post-policy period,vertical farm cannabis and subtracted it from the observed rate. Linear regression was used to model the effect of a reduction of 100 drug arrests per 100,000 on the SUD-related hospital visit rate in each county or county grouping during the 10-month post-policy period.
All analyses were conducted in Stata version 15. Counties with small populations were grouped by region, replicating the groupings created by the Office of Statewide Health Planning and Development . Groups included North Central , Foothills , Central Coast , North Coast , North , North East , and East Central . Changes in statewide SUD-related hospital visits could be attributable to a variety of factors unrelated to Prop 47. Since the immediate effect of Prop 47 was to reduce drug arrest rates, if changes in hospital visits were related to Prop 47, counties with greater reductions in drug arrests would be expected to experience greater changes in hospital visits. Table 4.2 displays the median observed vs. expected county drug arrest and SUD-related hospital visit rates per 100,000 in the 10 months post-policy, by gender-age group. We find that median county drug arrest rates declined in every group, with the greatest declines among males ages 15-24 . Median increases in SUD-related hospital visit rates were also greatest in this population , which reflects findings from the statewide analysis. However, results from the linear regression of county changes in SUD-related hospital visits on county changes in drug arrest rates indicates associations were non-significant for every age and gender group, including males ages 15-24 . Though the confidence interval included zero, the direction of the effect was the reverse of what was expected: among males ages 15-24, a decline of 100 per 100,000 drug arrests was associated with a decline of 8 per 100,000 SUD-related hospital visits . This study of the effects of Prop 47 on SUD-related hospital visits in California suggests that a reduction in drug arrests was not associated with an increase in hospital visits. Evidence shows that increasing the severity of sanctions for drug offenses historically did not affect use , though research on the health effects of easing drug laws has been generally limited to marijuana. This body of literature suggests that medical marijuana legalization had no effect on marijuana initiation or DSM-IV dependence/abuse among users , and reduced opioid-related hospital admissions with no impact on marijuana related hospitalizations .
Studies of the impacts of legalizing marijuana for recreational use show greater divergence and potentially negative health effects, with increases in emergency department visits, hospitalizations, and regional poison control center calls linked to marijuana exposure , and mixed findings regarding effects on adolescent use and perceived harmfulness across states . Legalization, however, is distinct from reducing criminal penalties, with different mechanisms through which use could be altered. For example, though legalization may have a similar effect as reducing criminal penalties on minimizing arrests and incarceration associated with the drug, it also increases access to the drug. Legalization may garner media attention that increases public awareness of the reform, in turn potentially reducing perceptions of risks associated with the drug or generating drug use tourism . Reclassifying drug offenses, in contrast, may go relatively under the public radar, which could correspond with a lesser effect on public perceptions or use patterns. Regardless of public awareness of the reform, there is clear evidence that arrests and incarceration dropped as a result of Prop 47 . This study indicates reducing drug arrests did not alter SUD-related hospital visits on a population level. Findings would be bolstered by further research that examines the effect of shorter sentences in addition to reduced arrest rates, and that investigates changes in individual trajectories through the criminal justice system, access to treatment, and outcomes. While individual-level studies would offer a stronger assessment of the association between the exposure and outcome of interest, causal inference in such studies would be challenged by the likelihood that police and prosecutors shifted focus to individuals with more severe criminal histories post-policy. Such a shift would itself be worth exploring; if the individuals no longer getting arrested are those with a lower risk of hospital visits, then it may help to explain why the drop in arrests had little effect on hospital visit rates.
In any case, it is imperative to gain insight into whether and how individuals at greatest risk of negative health outcomes from substance use are being engaged in services within the new policy environment, including best practices for counties’ use of Prop 47 savings to increase treatment access. That genetic factors have an age-specific influence on the onset of alcohol dependence is suggested by the findings that there are strong genetic effects contributing to risk for alcohol dependence particularly connected with early onset of drinking activity . Correspondingly,vertical farm growing racks the rate of adult alcohol dependence is significantly greater among those who start drinking at a relatively early age than among those who start drinking after the age of 19 ; Hussong et al. ; Chen et al.. Studies of adolescent brain development point to neurophysiological factors that could enhance the likelihood of substance use/abuse in those between 14 years of age and 17 years of age . Significant changes in the dopaminergic system occur during adolescence, as well as growth and refinement of prefrontal and limbic circuitry . As a result of the early enhanced activity of the mesolimbic system in contrast to the more slowly maturing prefrontal control systems and their connections to other brain regions, changes in the adolescent brain may lead to enhanced risk taking compared to earlier and later stages of maturation. Specifically, these changes may lead to a reduced cognitive control of the reward system in the brain in early to middle adolescence, leading to increased risk for alcohol and other substance abuse disorders . Alcohol dependence and risk for alcoholism in both adults and adolescents is associated with reduced power in event related oscillations in a number of different experiments which elicit a P3 or P300 response . ERO power in a task that elicits a P3 response is also associated with a number of SNPs in the CHRM2 gene . Alcohol dependence in adults was found to be associated with a number of SNPs in the cholinergic M2 receptor gene in two studies . A refinement of the study of Wang et al. showed that the association was present only in those subjects who had comorbid illicit drug dependence . This group of subjects and their family members form a genetically vulnerable group, that is, a group whose alcohol dependent members have a more heritable form of the disorder. The alcohol dependent members of this group had a significantly earlier age of onset of drinking compared to the alcohol dependent subjects without comorbid drug dependence. A generalized measure of externalizing psychopathology including alcohol dependence and illicit drug dependence is associated with the same group of SNPs in the CHRM2 gene . Additionally, there is variation in the genetic factors associated with alcohol dependence; multiple genetic factors were found to contribute to a DSM-IV diagnosis of alcohol dependence in adults . Some differences were found between genetic factors involved in alcohol consumption in adolescents and in young adults in twin study models. In order to investigate the age specificity of the genetic and endophenotypic factors noted above on the early onset of alcohol use and dependence, we studied adolescents and young adults drawn from the Collaborative Studies on the Genetics of Alcoholism sample .
Because we wanted to understand the processes which lead from non-drinking to regular drinking to alcohol dependence we used both the onset of regular alcohol use and of alcohol dependence as dependent variables. As we noted above, more severe cases of alcohol dependence in adults were found associated with earlier ages of onset of drinking and are more likely to be the result of genetic factors, thus we hypothesized that specific genetic and related neurophysiological endophenotypes would have a greater predictive power in those with the earliest ages of onset. Discrete time survival analysis was used to investigate the contribution of genetic variants in CHRM2, ERO power, and environmental factors to the onset of regular alcohol use and of alcohol dependence in adolescents and young adults, to deal with the first two items of investigation. Additional statistical tests, including both genetic and endophenotypic independent variables, were used to link the onset of regular alcohol use to the onset of alcohol dependence, to deal with the third item of investigation. To deal with the fourth item, the same DTSA methodology as was used for the entire sample was applied to a behaviorally defined sub-sample, the definition of which is discussed subsequently . The results of the DTSA calculations suggested further investigation of age related changes in the genotypic distributions of those who became alcohol dependent. A further test was made to determine whether there was an effect of alcohol use on our endophentypic covariates. Data were analyzed in a cross sectional sample of subjects who were assessed at least once when they were between the ages of 12 and 25 years. They were drawn from multiplex alcoholic families and a set of community families in the Collaborative Studies on Genetics of Alcoholism . Written informed consent was obtained from all subjects, and the Institutional Review Boards of each collaborative site approved all procedures. The procedures used by COGA for diagnostic interviews and recording and analyzing EEG data have been described previously . A detailed description of population characteristics of alcohol use and dependence are given in section 2.6.Diagnostic measures for outcomes were taken from direct interviews using the Semi Structured Assessment of Alcoholism instrument . Data were obtained from child and adult versions of the SSAGA. DSM-IV criteria were used for alcohol dependence and DSM-III-R criteria were used for other substance-use related diagnoses. Once the criteria for a diagnosis were met, the diagnosis was recorded as present, regardless of any subsequent change in status as determined by succeeding interviews. The age of onset was determined from data obtained at the first interview that recorded the diagnosis as present. Illicit drug use was defined as the use of any of heroin, cocaine, barbiturates, or amphetamines without regard to frequency or age of onset.A substantial literature indicates that alcohol dependence and risk for alcoholism are associated with reduced levels of brain activity when subjects respond to infrequent target stimuli within a sequence of non-target stimuli . Representation of this response in terms of brain rhythms or event related oscillations has proved fruitful . The ERO amplitudes used in this study were obtained from responses to rare target stimuli that elicited a P3 component in a visual oddball experiment at three midline leads . Three leads were chosen because of topographical variation in the significance of results in previous studies .