Our results do not contradict those of Wang et al. and Dick et al. ; the results are mutually consistent. Instead, they reveal a novel age-specific risk factor undetectable by solely examining the condition of alcohol dependence rather than its age of onset. In view of the age differences between the sample studied in this paper, and the sample used in the studies of Wang et al. and Dick et al. it is not possible that they should contradict one another. In the Wang et al. study, about 5% of the alcohol dependent subjects had ages of onset of less than 16 years of age. This is too small a fraction to have an effect on the results. As we noted in our discussion of the trend tests, in our study the genotypic distributions of the alcohol dependent subjects change with age of onset. While we do not observe a significant SNP effect in the oldest age range with DTSA, the fraction of subjects with the minor allele in those who become alcohol dependent is greater than the fraction of subjects with the minor allele in those who do not become alcohol dependent . This trend acts to produce a similar genotypic distributions for alcohol dependent and non alcohol dependent subjects when considered regardless of age of onset. In terms of the methodology, DTSA requires that there be differences in genotypic distributions between alcohol dependent and non alcohol dependent subjects to give a statistically significant results for a SNP; this is not true for the family based method used by Wang et al. . Our interpretation is that family based studies are more powerful than the type of association study employed here; the absence of a distributional difference does not mean that there is no genetic effect. It is important to note that the objectives of the twin studies considered here and of this study are quite different. The twin studies investigate the presence of a “disease” condition, although exactly which condition varies considerably among studies. The objective of this study,vertical farming suppliers as a survival analysis, is to analyze the factors contributing to an event, the onset of a condition. Once the condition has come to pass, it is not of further interest in survival analysis.
The genetic effects which produce the condition are only significant at the onset of the condition, and their effects persist only if the subsequent onset of the condition in other subjects is attributable to them. In the twin studies post-onset presence of the condition is part of the outcome analyzed. That is, in the longitudinal studies using multistage models, the affected subjects are retained throughout the study subsequent to their becoming affected, while in the survival analysis method used in this study, the affected subjects are removed from consideration in the study once they have become affected, and no longer influence the results. Therefore, although the use of a longitudinal multi-stage model in van Beek et al. and Baker et al. enables genetic influences to have age-specific characteristics, these effects are modeled as persisting through time as a result of an effect at a single age range. If early onset alcohol use is associated with the more genetically determined form of alcoholism then it would be expected that genetic factors leading to early drinking and dependence would be manifest. Our results are consistent with this hypothesis. The pattern of genetic results obtained here, albeit from a single gene, is weighted towards the strongest effects manifesting themselves in the youngest age range. However, most twin studies find low genetic influences at younger ages and increases in genetic influences with age , although not all twin studies have this conclusion . These results can be understood after examination of the populations from which the twin samples are drawn and the outcomes which are modeled. The samples in the twin studies are drawn from the general population, not from the densely affected families which form the bulk of the sample used here. Thus genetic effects will be more difficult to find in the twin studies, particularly for the rarer, more genetically affected conditions. In a number of studies outcome definitions are broad, and are not subject to as strong genetic effect as more restricted outcomes such as alcohol dependence or externalizing disorders. The most dramatic example of this is the difference between the cross-sectional results from the Minnesota twin studies in which the outcomes are narrowly defined and the cross-sectional results from a Dutch twin study with the very broad outcome of having one or more alcohol abuse symptoms. The Minnesota twin studies have A > 0.6 for ages 11 and 17, while the Dutch twin study has A < 0.3 for ages 15–17 and 18–20, where A is the additive genetic effect.
Mid-adolescence is a vulnerable developmental period for cigarette smoking uptake, the onset of mental health conditions, and the emergence of comorbid tobacco use and mental health problems . The over-representation of smoking among adolescents with mental health problems generalizes across various conditions , remains robust after controlling for confounders, and is mediated by theoretically-relevant factors suggesting a causal relation . The rapid emergence and appeal of novel tobacco and nicotine products such as electronic cigarettes raises the question as to whether the same adolescent subgroup with mental health problems is at risk for using these products . This is important to address because this population may be particularly vulnerable to nicotine addiction, given that neural plasticity during adolescence and neuropathology in psychiatric conditions can enhance the brain’s sensitivity to nicotine . E-cigarettes—electronic devices that deliver inhaled nicotine emulate the sensorimotor properties of conventional cigarettes—are gaining popularity among adolescents. According to 2014 estimates, past 30 day use of e-cigarettes is more common than conventional cigarettes among U.S. 8th- and 10th- graders, and many adolescent e-cigarette users have never tried conventional cigarettes . E-cigarettes may be an attractive alternative to conventional cigarettes among youth because of beliefs that they are less harmful, addictive, malodorous, and costly than conventional cigarettes . Furthermore, e-cigarettes come in flavors appealing to youth and may be easier to obtain than conventional cigarettes because of inconsistent enforcement of restrictions against sales to minors . Such factors may facilitate e-cigarette initiation in adolescents who would not otherwise smoke conventional cigarettes and may perhaps have fewer risk factors for smoking —including mental health problems. Dual use of conventional and e-cigarettes is also common in adolescents , raising the possibility that some adolescents may use e-cigarettes to substitute for conventional cigarettes in situations where smoking is restricted. Indeed, school bathrooms and staircases are among the most common places adolescents report using e-cigarettes .
Given that adolescents with mental health symptoms are more prone to nicotine dependence , these populations could be more likely to initiate use of e-cigarettes to bridge situations when they are not able to smoke, which ultimately could perpetuate the over-representation of smoking among individuals with mental health problems. While research has yet to characterize the psychiatric comorbidity with patterns of conventional and e-cigarette use in adolescents, a recent study of Hawaiian adolescents found that alcohol/marijuana use and other psychosocial risk factors were highest in dual users, moderate in e-cigarette only users, and lowest in non-users . Most pairwise comparisons involving conventional cigarette only users were not significant in that study, perhaps limited by reduced statistical power due to the smaller size of this group . Given these findings, stratification of psychiatric comorbidity across dual use, single-product use, and non-use in adolescents is plausible. The current study characterized the mental health of adolescents who reported ever using ecigarettes, conventional cigarettes, both, or neither. To provide a wide-ranging picture of psychiatric comorbidity,vertical farming systems cost traditional syndrome-based indices of various depressive, manic, anxiety, and substance use disorders were administered. Consistent with NIMH’s Research Domain Criteria Initiative , we also assessed several transdiagnostic phenotypes implicated in multiple internalizing and externalizing psychopathologies and conventional cigarette use . Up to this point, data on the psychiatric comorbidity associated with ecigarette and dual use is virtually absent, leaving unclear as to how the mental health of these two groups compare to conventional cigarette users and non-users. Given that conventional cigarettes and e-cigarettes have both similarities and differences, whether the patterns of psychiatric comorbidity are similar or different between e-cigarette only users and conventional cigarette users is unclear. As the first study to comprehensively characterize psychiatric comorbidity in adolescent e-cigarette and dual use, this study may yield data that is important to tobacco policy by identifying adolescent populations that are psychiatrically vulnerable and potentially at risk for use of traditional and emerging tobacco products. Such data could highlight the need to protect psychiatrically vulnerable adolescents from tobacco product use take via targeted tobacco product regulation and behavioral health prevention programming for this populations.This report is based on a cross-sectional survey of substance use and mental health among 9 th grade students enrolled in ten public high schools surrounding Los Angeles, CA, USA.
The schools were recruited based on their adequate representation of diverse demographic characteristics. The percentage of students eligible for free lunch within each school on average across the ten schools was 31.1% . Students not in special education or English as a Second Language programs were eligible . Of the students who assented to participate , 3,383 provided active parental consent and enrolled in the study. In-classroom paper-and-pencil surveys were administered across two 60-minute data collections during the fall of 2013, conducted less than two weeks apart. Some students did not complete all questionnaires within the time allotted or were absent for data collections , leaving a final sample of 3310. The University of Southern California Institutional Review Board approved the protocol. Based on patterns of lifetime use, the sample was divided into: use of neither electronic nor conventional cigarettes ; use of conventional cigarettes only ; use of electronic cigarettes only ; use of electronic and conventional cigarettes . Primary analyses used generalized linear mixed models that accounted for clustering of data within school, in which the 4-level cigarette use group variable was a categorical regressor variable and a mental health indicator was the outcome variable, with separate models for each outcome. GLMM specified binary and continuous distributions for the lifetime substance use status and mental health quantitative outcomes, respectively. Because of skewed distributions on the three substance use problems measures, Poisson distributions were specified for these outcomes. For outcomes with omnibus groups differences, we conducted follow up pairwise contrasts using an adjusted p-value, correcting for study-wise false discovery rate of 0.05. GLMMs were adjusted for gender, age, ethnicity, and highest parental education; missing data on covariates were accounted for by dummy coding a ‘missingness’ variable to allow inclusion in analyses. Results are reported as standardized effect size estimates .As illustrated in Table 2, there were omnibus differences across the four groups for all outcomes. Pairwise contrasts indicated that adolescents who used conventional cigarettes only reported worse mental health than non-users and e-cigarette only users on multiple internalizing emotional syndromes and transdiagnostic phenotypes . On these internalizingemotional outcomes, the conventional cigarettes only and dual use groups did not significantly differ. For some internalizing outcomes , e-cigarette only users had higher elevations than non-users, but lower problem levels than conventional only or dual users. Relative to non-users, use of either product was related to the externalizing phenotypes of poorer inhibitory control and impulsivity. An ordered effect of dual use vs. e-cigarette use only vs. non-use was found for elevations in mania, positive urgency, and anhedonia. An ordered effect of dual use vs. either single product use vs. non-use was also found for lifetime use status and level of abuse/problems for all substances. Given the differences in patterns across internalizing and externalizing and positive-emotion seeking behaviors, syndromes, and traits, we plotted standardized T-scores of the outcomes by conventional/e-cigarette use status separately in the two domains. These figures respectively illustrate general trends of: differentiation of conventional and dual cigarette use from never and e-cigarette use on most internalizing outcomes , and tri-level ordered differentiation of never vs. single product vs. dual use on externalizing outcomes . Analyses of the substance problem outcomes utilizing the overall sample cannot distinguish between substance ever-users who report zero drug/alcohol-related problems and substance never-users.