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The literature varies in its characterization of the risk preference variable, even with the same discrete choice questions. My results are similar whether including the full 4-category variable or the linear adjusted risk tolerance measure. Mis-classification of contraceptive consistency as well as contraceptive method could be a concern. There were some discrepancies between women’s reported percent of contraceptive usage and their method type. For example, there were 13 people who reported 0% use of birth control methods and also reported IUD use. This may result from misinterpretation of the question specifically for women using long acting methods. Or those women may have recently switch to IUDs, or use IUDs for other medical issues. It is challenging to determine if this is an error or an accurate response. There may be similar but less outwardly apparent misclassification across all contraceptive groups. The characterization of sexual behavior is limited in NLSY. Notably, respondents were not asked about sexual activity with a same sex partner in the last year. While the results of number of sexual partners are suggestive, future research on risk preference and sexual risk behavior should include a more comprehensive battery of questions. Potential intention-behavior incongruence may lead to the outcome of unintended pregnancy. Novel epidemiologic studies that include models of decision-making could identify antecedents of unintended pregnancy and develop interventions that may be targeted by individual risk preferences. This work provides an initial examination of the relationship between risk preferences and sexual risk behavior and contraceptive use. The findings merit future research with longitudinal samples to explore measure stability over time and in response to life circumstances. If a relationship between risk preferences and reproductive risk behavior, including number of partners and contraceptive use is reinforced,cannabis growing equipment it should inform our models of etiology of unintended pregnancy and also target behavioral interventions.

The goal of this research was to demonstrate the potential contribution of behavioral economics to our understanding of reproductive choices and behavior. Examining people’s decision-making can tell us not only about their likelihood of experiencing outcomes of interest, but also give information about their overall orientation. Preferences and biases may explain behavior and could be integrated into work on psychosocial predictors of health. The link between measured risk aversion and sexual and reproductive outcomes signal the importance of these measures beyond explaining financial behavior. They may, it appears, have implications for our understanding mechanisms underlying choices that drive reproductive health. This is an important step towards predicting who will be at highest risk of adverse outcomes and potentially develop models for intervention. The economic recession in the U.S. prompted increased interest in economic drivers of fertility. Variation in economic conditions may influence pregnancy intentions as well as contraceptive and sexual behavior, thereby altering risk of pregnancy. Additionally, the economic environment may impact individual decision-making on whether to continue a pregnancy. Understanding how economic uncertainty affects fertility intention and decision-making offers insight into the determinants of unintended pregnancy, spontaneous and induced abortion. Unintended pregnancy reduction is a stated national and international public health priority. Nearly half of pregnancies to women aged 15-44 in the United States are unintended, and 40% of those pregnancies end in abortion. Literature links unintended pregnancy to negative health outcomes for mothers and children, making it a significant public health concern and the target of prevention efforts as part of Healthy People 2020. Unintended pregnancy and pregnancy decision-making result from a multidimensional set of economic, cultural, social, psychological and demographic determinants. While risk of unintended pregnancy extends to the majority of women through their reproductive years, age, income, race/ethnicity, and psychosocial factors are associated with occurrence.

There is an educational gradient in unintended pregnancy, with higher incidence among women with lower levels of education. Women who experience unintended pregnancies are more likely have riskier psychosocial profiles prior to pregnancy, including depression, perceived stress, and low social support . Consequences of unintended pregnancy are substantial. There is some evidence of increased maternal risk behavior during pregnancy among those pregnancies that are unintended, including smoking and drinking. Consequences of unintended births include depression, preterm birth and delays in child development. It is estimated that unintended pregnancies cost the US more than $20 billion per year in expenses for births, abortions and miscarriages. Traditional measures of pregnancy intention measure the degree to which a pregnancy was planned or correctly timed. Unintended pregnancies are defined as pregnancies that are mistimed or unwanted at the time of conception. Intended pregnancies include pregnancies that are wanted at the time of conception or happen later than desired. Literature has critiqued this measure as one-dimensional, while asserting that people may feel a complex and multidimensional set of emotions surrounding pregnancy. In addition pregnancy intentions are dynamic and can change prior to and over the course of a pregnancy. Pregnancy intentions are often retrospectively recalled at the time of conception. This can be problematic as participant’s responses of intentions and desires can change depending on when they are assessed. Despite critiques that standard unintended pregnancy measures may not capture there this nuance, they are useful to identify time trends and risk factors. Researchers have long examined the relationship of the economy to fertility. Most studies find evidence for pro-cyclical effects , meaning slowing fertility in an economic downturn. The literature posits several mechanisms through which a worsening economy could affect fertility. First, an income effect from individual economic hardship causes individuals to rationally postpone or revise fertility plans.Becker , for example, suggests that the income effect leads to a quantity-quality trade off in childbearing decisions. Temporary income decreases may cause delays in childbearing whereas more persistent periods of unemployment may reduce the underlying desire to have children.

The economic environment can affect perception of risk in a population, not only among those directly affected by the experience of, for example, unemployment. Uncertainties in the labor market may affect fertility through anticipation of hardship, making fertility planning more challenging. These mechanisms would also yield a pro-cyclical association between the performance of the economy and fertility. Few studies show evidence of counter-cyclical effects, which assume that as employment opportunities decrease, the opportunity costs of time spent raising children decrease as well. This would promote substitution effects of fertility for employment. The recent economic recession in the United States provides opportunity for understanding mechanisms relating the economy and fertility. The Great Recession in the Unites States officially began in December 2007 and ended in June 2009. Unemployment and foreclosures rapidly increased as consumer confidence declined nationwide. During the Great Recession, the fertility rate decreased from 69.6 births per thousand women in 2007 to 66.4 births per thousand women in 2009, and has continued to decline. Several studies have documented a fertility decline in the United States and Europe from 2007-2011. During that time, state level economic indicators were linked to general fertility declines, as well as heterogeneity within subgroups. Schneider found strongest fertility effects of the economic downturn among women aged 20-24, who experienced lower rates of live birth than expected. Decreases in fertility were attributed to increased economic hardship and economic uncertainty which may have affected changes in contraceptive use, increases in abortion, miscarriage, or shifts in pregnancy intentions. Cherlin attributed a greater decline in fertility for young women to postponement rather than elimination of childbearing. Ananat et al. found birthrate declines among black but not white teens following country level job losses. They inferred that changes could be attributed to abortion or pregnancy avoidance based on the timing in gestation at which point the job losses occur. They hypothesized that black teens may be more vulnerable to job loss or uncertainty than white youth and found that the reductions in black teen births may be due to increased pregnancy terminations, reductions in sexual activity and increased contraceptive use. Much of the above work theorizes that fertility decline is due to rational choice to postpone or abstain from childbearing,cannabis plant growing however the ratio of intended and to unintended births during the Great Recession has rarely been examined. There is limited research on how the economic environment may serve as a determinant of unintended pregnancy and pregnancy outcome. Economic uncertainty or income effects may influence decision making prior to pregnancy, including pregnancy planning, sexual behavior and contraceptive use, and decision-making once a pregnancy has occurred, including the decision to abort. A study of institutional and individual economic measures found perception of job and income insecurity as well as aggregate unemployment rates to be associated with decreases short term childbearing intentions. A recent study by Percheski and Kimbo used the National Survey of Family Growth to investigate the risk of unintended pregnancy among women in the great recession. They exploited statewide indicators of unemployment, foreclosure and consumer sentiment and find reductions in both intended and unintended pregnancy among non-college educated women. They investigated the determinants of the decline, but found little evidence that economic indicators reduced sexual activity or increased contraceptive use . Reductions in births observed during the economic downturn may also have resulted from changes in pregnancy outcomes. While challenging to observe given high rates of fetal loss prior to pregnancy recognition, changes in the proportion of pregnancies that are not carried to term can alter fertility rates. A related body of literature establishes the increase of spontaneous abortion, following economic shocks.

Additionally, work demonstrating the shared correlation of spontaneous abortion and induced abortion suggests a positive relationship in response to economic events. Ananat et al.’s finding that teen fertility decreases following job loss that occurs during the first trimester could be explained by either mechanism. Research on abortion patients finds that economic insecurity is often cited as a reason for the decision. In the current investigation, I focus on two primary research questions: i.) Is national economic uncertainty associated with ratio of pregnancies reported as mistimed or unwanted relative to intended pregnancies; and ii) Is national economic uncertainty associated with the ratio of pregnancies ending in abortions or miscarriages relative to live births? Economic uncertainty, measured by changes in national monthly measures of the economy, captures contextual effects beyond effects among individuals who have experienced job loss or economic change. To investigate the relationship of economic uncertainty and reproductive health outcomes, I use data from the National Survey of Family Growth , combined with and monthly national unemployment data from the National Bureau of Labor statistics and the national consumer sentiment index from the Conference Board. The National Survey of Family Growth is a cross sectional, nationally representative survey administered by the National Center for Health Statistics. The Survey, initiated in 1973, collects data on fertility in the United States and contains detailed questions about sexual behavior, contraceptive use, relationship status and pregnancy.The survey collects data on each pregnancy, retrospectively recalled by participants. It is one of the only national surveys to include questions about pregnancy intention and contraception use at the time that the pregnancy occurred, as well as report of pregnancy resolution. This allows for examination of multiple pregnancies. NSFG includes inverse probability selection weighting based on of PSU, segment, housing unit, and person within selected household sampling procedures My analysis uses the 2006-2010 wave, which includes a national sample of 12,279 women and 10,403 men age 15-44 years living in households in the United States. In person interviews were conducted for a total sample size of 22,682. The interviews averaged 80 minutes in length for women. The response rate was 77% overall—78% for women, 75% for men]. To investigate women’s reproductive health outcomes, I use the pregnancy data file from the 2006-2010 survey of women across the US. The pregnancy file contains information on all of the participants’ past and current pregnancies, including date of conception, ‘wantedness’ at the time of conception, and pregnancy outcome. Therefore pregnancy is the unit of analysis. Economic uncertainty, as measured by the unemployment rate, Index of Consumer Sentiment, and timing of recession was associated with increased ratio of unintended compared to intended pregnancy, and abortion and miscarriage compared to live birth. Among unintended pregnancies, the ratio of mistimed pregnancies appeared more strongly and consistently associated with economic indicators than unwanted pregnancies.

Time preferences are related to health investment and health status and self-reported health. Several studies characterize addictive behaviors, including cigarette smoking, alcohol consumption and illicit drug use, as a special case of discounting. A review of gambling and substance use studies found consistent evidence that high rates of discounting are associated with a range of addictive behaviors with adverse health consequences.Discount rates have also been linked to alcohol dependence, alcohol abuse disorder, and moderate levels of alcohol use, including heavy social drinking. These effects are seen early in life, as discounting is positively correlated with age of first alcohol use and number of passed out episodes among adolescents. Illicit drug use also shows a consistent relationship, with higher discount rates among heroin and opioid-dependent individuals compared to non-drug users. Discount rates have also been studied in relationship to eating behavior and obesity, and may be closely related to food rewards among children. There are mixed results of monetary discounting and BMI in adults.The trade offs between longer-term goals and immediate rewards of unprotected sex fit a discounting framework. A qualitative study exploring determinants of inconsistent contraceptive use found that eroticism of unprotected sex and misunderstanding the risk of conception was a powerful explanatory factor. In one of the only articles to propose the connection between contraceptive use and behavioral economic interventions, Stevens and Berland note the connection of present-biased preferences to long acting reversible contraceptive use. They suggest that present bias in use of LARC could be leveraged by reducing the actual or perceived costs of obtaining LARC methods, such as higher cost if insurance is unavailable and discomfort of the procedure, in favor of long term benefits . While these types of changes to clinical encounters make intuitive sense based on behavioral economics,indoor cannabis grow system no research directly links delay discounting to contraceptive method choice. However, literature about other reproductive and sexual decisions may offer insight into the connection with contraceptive use. Individual decision-making is also shaped by perception of risk. Prospect theory describes decision-making in the context of risk.

The theory posits that people take greater risks to avoid loss than to realize gain even if the loss and gain are equal. It has gained credibility in the arena of health decision-making in comparison to the standard economic model, which assumes people are rational agents who make choices to maximize utility. Risk preferences are frequently studied in social science and are established as strong determinants of financial decision-making, including investment and savings. Risk preferences are generally measured as willingness to take gambles with income.People willing to take fewer gambles are generally deemed risk averse and those more willing to take gambles risk tolerant. Prospect theory also described lossaverse behavior in the context of risk, where individuals are more sensitive to potential losses than gains. A few studies have examined risk preferences and health behaviors. Anderson found that an experimental measure of risk aversion was negatively associated with several health behaviors, including smoking, heavy drinking, obesity, and non-use of a seat belt. A seminal study in the Health and Retirement Study found that an economic measure of risk tolerance predicted risk behavior including smoking and drinking. Loss aversion has also been linked to reduced cancer screening behavior among those with chronic disease who would be most sensitive to health losses. Willingness to accept risk has intuitive connection to sexual and reproductive health behaviors. The consequences of sexual and reproductive behavior, including unintended pregnancy to STI transmission, are probabilistic rather than certain. Thus an individual’s tolerance for risk may affect their willingness to engage in unprotected sex. Although it is clear that individual decision-making affects sexual and reproductive health behaviors, including contraceptive method choice, consistency of condom use, number of sexual partners, and use of substances while engaging in sex, literature exploring the connection of discounting and risk tolerance has emerged only recently. This systematic scoping review examines the literature suggesting how two decisional preferences from behavioral economics, temporal discounting and risk tolerance, may influence sexual and reproductive behavior. The review seeks to contribute to the literature on sexual and reproductive health by assessing the state of the evidence available and offering suggestions for future work.

Descriptions from the 20 included articles are displayed in Table 1. Sixteen studies utilized cross-sectional designs, three were longitudinal, and one embedded within a randomized trial. Four of the studies tested correlations between the preference measure of interest and one or more health behaviors and did not control for confounding variables, making causal assessment of findings difficult. Participants were recruited from university courses or psychology labs, general populations or subgroups of the general population clinical samples, Facebook, or MTurk. Overall 10 studies focused on adolescents or young adults. These studies noted that adolescents are a particularly important subgroup to study in the context of sexual risk behavior, as they have heightened risk of STI and also unintended pregnancy. Five papers focused on college students above 18. Three studies included general samples of young people including 16-24 year old Swiss young adults, 18-24 year olds from urban centers, and 14-30 year olds from and medical and STI clinics. Two studies included even younger samples of Appalachian youth aged 10-17 at recruitment, and 10-12 year olds in Philadelphia. Three studies focused on sexual risk behavior among men who have sex with men. One study included only male heterosexual college students, 21-32, and another only heterosexual women from the PSID. Four studies required hazardous alcohol or substance use dependence for eligibility.The dependent and independent variables of interest as well as the results are summarized in Table 2. The majority of the articles examined delay or probability discounting while only three assessed a measure of risk tolerance. Earlier studies of discounting and sexual behavior used survey measures of monetary discounting: a trade off between present and future monetary rewards. More recently,cannabis grow equipment in recognition of domain specific preferences, discounting measures have been developed for discounting relating to sexual rewards. There is a further distinction between delay discounting and probability discounting, of both money and sex. Probability discounting tasks entail choices between smaller sooner rewards and delayed uncertain rewards. The reviewed articles can be divided into those that use measures of monetary discounting, sexual discounting, or both. Studies that assessed monetary discounting most often used the Monetary Choice Questionnaire , a 27-item measure involving choices between smaller immediate rewards and larger delayed rewards developed by Kirby.

One study used the MCQ but added a time perspective measure to assess future uncertainty. Chesson used a three-item hypothetical payoff measure. One study included probability discounting of money in addition to delay discounting.Sexual delay discounting tasks were used in several studies. Participants were asked to consider 60 photographs of people and to rank who they most want to have sex with, least want to have sex with, who is most likely to have an STI and least likely to have an STI. The chosen photos were then shown to participants to assess willingness to wait for condom-protected sex with a higher ranked partner versus immediate unprotected sex as a form of sexual delay discounting. Both studies found that sexual discounting differed as a function of the stated partner characteristics. Darioitis found that youth discounted significantly more with partners they ‘most want to have sex with’ and partners whom they thought were ‘least likely to have an STI.’ The sexual probability discounting tasks extend this same logic as the delay tasks, but instead of a delay they use varying chances of engaging in sex with the preferred partner. One study modified the SDDT for use with MSM. Two studies included both measures of monetary and sexual discounting. Johnson and Bruner were the first to find evidence of sexual domain specificity, as they not find evidence of monetary discounting with HBRS measure. Lawyer proposed another specification of the sexual discounting task. This task did not use hypothetical partner images, but instead asked participants about a trade off between more minutes of the sexual activity with some delay or fewer minutes immediately. The study used several scales that are validated in sexuality research and correlated with behavior. Sexual delay and probability discounting were associated with the measure of sexual excitability, but not with other non-sexual measures. Additionally monetary discounting was not associated with sexual outcomes, lending support to the domain specificity of sexual discounting. In the three articles focusing on risk tolerance, each used a different measure. Brobdeck used a risk preference and hedonism scale from the Trier Integrated Personality Inventory developed by Becker. Schmidt used a measure of hypothetical gambles over lifetime income that is modeled after the Health and Retirement Study in the PSID. Szrek et al employed four risk-taking propensity measures, including the a general measure of risk-taking propensity derived from a one-item survey question , a risk aversion index calculated from a set of incentivized monetary gambles , a measure of risk taking derived from an incentive compatible behavioral task—the Balloon Analog Risk Task , and a composite score of risk-taking likelihood in the health domain from the Domain-Specific Risk Taking scale.

Seventeen of the 20 articles evaluated the effect of discounting or risk tolerance on sexual behavior and outcomes. Of these, seven examine these relationships in the context of substance use. The sexual discounting task was repeatedly associated with sexual behavior. All studies assessed self-report of sexual risk behavior, and Chesson also included laboratory measures of STIs. Daugherty and Base, included a measure of sociosexual orientation , a measure of degree to which individual is more comfortable engaging in sexual behaviors without mental or emotional commitment. Lawyer examined sexual excitability rather than self reported behavior. Johnson and Bruner examined HIV risk behaviors, finding a significant relationship between greater discounting and history of high-risk sex. Dariotis and Johnson extended these findings from older high-risk sample to a sample of youth, finding that the four components of the SDT were negatively correlated with several reported sexual behaviors, including number of lifetime risky sexual partners. In addition, they found that less favorable attitudes towards risk were correlated with lower discounting, or preference for postponed protected sex under the ‘most want to have sex with’ and ‘least likely to have an STI’ components. Jarmolowizc applied the SDT task to promiscuity, finding that number of sexual partners selected on discounting task was related to higher rates of delay discounting, which was predictive of sexual behavior. Collado et al. examined sexual delay discounting and self-reported STI risk sex behaviors, HIV knowledge and STI risk perception among college students. They found that higher values of each of the four SDT measures were associated with self-reported risk behaviors. Hermann et al. extended the SDT to men who have sex with men and found discounting of condom protected anal intercourse to be hyperbolic, meaning that participants discounted using condoms as delays to CPAI increased. Steeper discounting of CPAI was associated with unprotected anal intercourse, substance use, not having been tested for HIV, sex under the influence of substances. One study examined risk tolerance, and argued that risk taking is domain specific, comparing four risk propensity measures with health risk behavior including sexual risk behavior. The found the Dohmen measure of general risk propensity was positively correlated with sexual risk behavior along with problem drinking and seat belt use. A risk aversion index calculated from a set of incentivized monetary gambles and the BART, and the DOSPERT scale were each uncorrelated with sexual risk behavior. Adolescence is a critical period for sexual behavior, as risk behavior emerges and peaks during the period . In one of the few studies to have self-reported data along with laboratory measures of STIs, higher discount rates were associated with ever having sexual intercourse, sexual intercourse before age 16, and ever having gonorrhea or chlamydia, controlling for demographics among a sample of adolescents and young adults.They did not find significant association of discount rates with unprotected sex or HSV-2 testing or infection. Khurana enrolled 10-12 year olds and examined the role working memory on adolescent early sexual initiation two years later and potential meditational pathways of impulsivity.

We then use two approaches for computing the semantic similarity between them: cosine similarity computed between average token embeddings, and BERTSCORE , which involves computation over BERT token embeddings of the tweet and misconception to obtain an F1-score-like measurement that we use as a similarity score. For the cosine similarity approach, we experiment with both non-contextualized and contextualized word embeddings. For non-contexualized word embeddings we use 300D GloVe trained on 2014- Wikipedia and Gigaword embeddings . For contexualized embeddings we use a pretrained BERT-LARGE model. However, Since BERT is not trained on COVID-19-related text we also use COVID-Twitter-BERT1 which uses domain-adaptive pretraining on 160M tweets about COVID-19. For sake of brevity, we will append the suffix to models that use COVID-Twitter-BERT instead of spelling out the full model name.We present the performance of similarity models in Table 4.1. Average embedding, both with GloVe and BERT embeddings, perform the worst . Although information retrieval based approaches, TF-IDF and BM25, considerably outperform the average embedding techniques, BERTSCORE captures the similarity as accurately as well. Domain adaptation, however, further improves the embedding-based similarity techniques, improving average BERT embeddings to be as good as others, while making BERTSCORE much more accurate than all other techniques. Thus we see that using domain adaptation and BERTSCORE are both important for performing accurate misconception retrieval.We illustrate the differences in the similarity models using example predictions in Table 4.2. The first example provides a challenging case of retrieval that requires taking both COVID-19 knowledge and contextual information into account, and thus only the BERTSCORE model is able to retrieve the correct misconception. The second example primarily requires domain knowledge that ‘coronavirus’ and ‘Sars-cov-2’ are very similar,vertical cannabis and only domain-adapted models are able to score the correct misconception highest.

The last example shows when contextual embeddings outperform non-contextual embedding . Due to the lack of adequately large datasets for stance detection with pairs of sentences , we cannot use existing datasets to train models for our setup. However, since classes in misinformation detection correspond to those in natural language inference and fact verification, tasks with much larger training datasets, we instead experiment with zero-shot learning on these tasks. The COVID-19 Health Risk Assessment task released after the pandemic started, also allowed us to experiment with few-shot learning by combining it with COVID-19 tweet-misonception pairs annotated for stance by researchers at the UCI School of medicine. Standard evaluation metrics like we have used above can overestimate the real world performance of NLP models, and do not reveal enough information about situations where the models are failing or how to fix them. To evaluate our stance detection models more rigorously we use the matrix of linguistic capabilities and test types provided by Check List for behaviour testing of NLP models. We evaluate our best zero- and few-shot models: BERTSCORE + SBERT trained on MNLI and CH+PA respectively. We test the following linguistic capabilities: Robustness , Negation, Vocabulary, NER , Temporal , and SRL . We perform three types of types: Minimum Functionality Tests , which are simple ’sanity checks’ of targetted capabilities; Invariance Tests consisting of perturbations which should not change model output; and Directional Expectation Tests For all tests, we use the COVID-19 misconceptions from COVIDLIES. For MFTs we construct simple tweets based on perturbations of the misconceptions, eg. introducing a simple typo: Salt water → wtaer protects from coronavirus. From the results of the tests in 4.5 we see that that there are linguistic capabilities that the zero-shot model is more competent at than the few-shot model and vice versa. Notably, the few-shot model is more robust to typos and positive paraphrases possibly because it is trained on informally written content . However, an alarming incompetency of the few-shot model is when the constructed tweet is identical to the misconception— the output should obviously be Agree, which the zero-shot model is able to correctly predict 100% of the time, while the the few-shot model only 91.9% of the time .

A possible explanation for why this happens is that the tweets in COVID-Hera tend to repeat the headlines or claims they are paired with verbatim, even in the refute/rebutscategory. Both models failed spectacularly at NER tests when perturbing country names and numbers in misconceptions to construct tweets, i.e., they always fail to predict No Stance in these cases. For INV and DIR tests we randomly sample 45 misconception-tweet pairs per class from COVIDLIES that both models are able to correct the label for. For INV tests we perturbed tweets in ways that should not lead to output changes, and for DIR tests perturbations were to induce a specific label switch. INV tests were more successful than DIR tests for both models . In the social sciences, there have been recent efforts to quantify COVID-19 misin formation on social media , as well experimental efforts to prevent propagation of misinformation . At the same time, members of the NLP community have been working on developing tools for the automatic detection of COVID-19-related misinformation online. Serrano et al. detect YouTube videos spreading conspiracy theories using features of user comments, and Dharawat et al. classify tweets by the severity of health risks associated with them. McQuillan et al. study the behaviour of COVID-19 misinformation networks on Twitter using mapping, topic modeling, bridging centrality, and divergence. Penn Medicine launched a chat bot to provide patients with accurate information about the virus , and a crowd sourced chat bot, Jennifer, is also available to answer questions about the pandemic . We are the first to frame COVID-19 misinformation detection as a two-stage task of misconception retrieval and pairwise classification of stance, and add to this body of work by providing a dataset and benchmark models for automated identification of misinformation.There are several datasets for misinformation detection with binary veracity labels , for example, Fake NewsNet consisting of news articles, Some Like It Hoax consisting of Facebook posts, and PHEME containing twitter threads. Misinformation detection is also closely related to fact-checking since both tasks aim to assess the veracity of claims. FEVER is a dataset of claims and evidence pairs with Supported, Refuted or Not Enough Info labels to facilitate research in automated fact checking.

This is similar to Emergent , a stance classification dataset consisting of rumored claims and associated news articles with labels of For, Against, or Observing the claim. Stance detection is also the focus of the Fake News Challenge 1 consisting of pairs of news article headlines and body texts with Agrees, Disagrees, Discusses, and Unrelated labels. Our proposed models for detecting misinformation by using classififiers fall within the framework of detecting misinformation using content features . Other approaches include using crowd behaviour , reliability of the source , knowledge graphs , or a combination of these approaches . Adapting these techniques to COVID-19 misinformation is a promising direction for future work. The ongoing COVID-19 pandemic has been accompanied by a corresponding ‘infodemic’ of misin formation about the virus. It is important to develop tools to automatically detect misinformation online, especially on social media sites where the volume and speed of the spread are high. However, rapidly evolving information and novel language make existing misinformation detection datasets and models ineffective for detecting COVID-19 misinformation. In this work, to initiate research on this important and timely topic, we introduced COVIDLIES, a benchmark dataset containing known COVID-19 misconceptions accompanied with tweets that Agree, Disagree, or express No Stance for each misconception, annotated by experts.We evaluate a number of approaches for this task, including common semantic similarity models for retrieval,cannabis hydroponic set up accurate models trained on a variety of NLI datasets, and domain adaptation by pretraining language models on a corpus of COVID-19 tweets. We demonstrate domain adaptation significantly improves results for both sub-tasks of misinformation detection. We also show that it is feasible to detect the stance of tweets towards misconceptions using both zero-shot and few-shot settings. We showed that few-shot learning slightly improves stance detection when evaluating using standard aggregate performance metrics. However, further behaviour testing using CheckList leaves an unclear picture of which setting is better. Both settings have considerable scope for improvement. Future work will involve exploring improved performance on stance detection, preferably without reliance of methods that require a large amount of data collection since they are not quickly available in an emerging crisis. We plan to continually expand our annotated dataset by including posts from other domains such as news articles and Reddit, and misconceptions from sources beyond Wikipedia, such as Poynter . We invite researchers to build COVID-19 misinformation detection systems and evaluate their performance using the presented dataset.Chemotherapy-induced nausea and vomiting can be classified into three categories: acute onset, occurring within 24 h of the initial chemotherapy administration; delayed onset, occurring 24 h to several days after the initial treatment; and anticipatory nausea and vomiting . Anticipatory nausea develops in response to chemotherapy treatments, in which cytotoxic drugs are delivered in the presence of a novel context . Developing in approximately 30% of patients by their fourth treatment , AN has traditionally been understood in terms of classical conditioning. After one or more treatment sessions, a conditional association develops between the distinctive contextual cues of the treatment environment and the unconditioned stimulus of chemotherapy treatment that results in the unconditioned response of post-treatment illness experienced by the patient. Subsequent exposure to the treatment environment results in the patient experiencing a conditioned response of nausea and/ or vomiting before initiation of chemotherapy treatment. Once it develops, AN has been reported to be especially refractive to anti-emetic treatment . The evaluation of potential treatments for AN would be accelerated by the establishment of a reliable rodent model of nausea.

Although rats are incapable of vomiting, they display characteristic gaping reactions when exposed to a flavoured solution previously paired with lithium induced nausea. In fact, this gaping reaction in the rat requires the same orofacial musculature as that required for vomiting in other species . Only drugs that produce emesis in species capable of vomiting produce conditioned gaping in rats, although many non emetic drugs produce conditioned taste avoidance . Furthermore, anti-emetic drugs interfere with the establishment of conditioned gaping reactions elicited by a nausea-paired flavor, presumably by interfering with the nausea . Conditioned gaping in rats appears to be a selective index of conditioned nausea. Not only are flavor cues capable of eliciting conditioned gaping reactions when paired with lithium chloride – induced nausea in rats, but recently Limebeer et al. have demonstrated that re-exposure to LiCl-paired contextual cues also elicit conditioned gaping reactions in rats. This paradigm more closely resembles that reported to produce AN in chemotherapy patients. Rats were injected with LiCl or saline before placement in a vanilla-odor laced chamber with lights and texture different than their home cage on each of four trials, separated by 72 h. To equate both groups for experience with illness, the rats in group unpaired were injected with LiCl and those in group paired were injected with saline 24 h after each conditioning trial but were then simply returned to their home cage. When the rats were returned to the conditioning context, 72 h after the final conditioning trial, rats in group paired showed the conditioned gaping reaction, as a measure of AN. Although classical anti-emetic treatments such as the 5- hydroxytryptamine-3 antagonist, Ondansetron , effectively reduce unconditioned nausea and vomiting, they are ineffective in the alleviation of conditioned nausea once it develops in humans . Indeed, OND also did not suppress the conditioned gaping reactions displayed during re-exposure to the LiCl-paired context . Further more, using the emetic species, Suncus murinus as an animal model for AN, pre-treatment with a dose of OND that was shown to alleviate acute vomiting , did not reduce the display of conditioned retching reactions during re-exposure to a nausea-paired context . Thus, although OND has proven effective in the reduction of acute post-treatment nausea and vomiting, it does not appear to relieve conditioned nausea when it does develop.The psychoactive component in marijuana— delta-9-tetrahydrocannabinol —has been shown to interfere with the expression of vomiting in shrews and ferrets and conditioned gaping reactions elicited by a lithium-paired flavor in rats .

In the present review, I outline recent progress made in these directions, specifically focusing on endocannabinoid deactivation, and discuss some of the challenges lying ahead.Anandamide was the first endocannabinoid sub stance to be isolated and structurally characterized . Its formationinneural cells is thought to require two enzymatic steps, which are illu strated in Fig. 1. This reaction, which is mediated by a unique D-type phospholipase , produces anandamide and phosphatidic acid, which is recycled to produce other glycerol-containing phospholipids. The cellular stores of NAPE are small, but canbe refilled by an N-acyltransferase activity, which catalyzes the intermolecular passage of anarachidonic acid group from the sn-1 positionof phosphatidylcholine to the head group of phos phatidylethanolamine . Incultures of rat cortical neurons, NAT activity is controlled by two intracellular second messengers: Ca2+, which is required to activate the enzyme, and cyclic 30 , 50 -adeno sine monophosphate , which stimulates protein kinase A-dependent protein phosphorylation and, via an unknown mechanism, enhances NAT activity . Although separate enzymes cata lyze the syntheses of anandamide and NAPE, the two events are likely to occur simultaneously because Ca2+- stimulated anandamide production is often accompanied by denovo formationof NAPE . Anandamide synthesis can be elicited in vitro by a variety of agents that elevate intracellular Ca2+ levels. For example, the Ca2+ ionophore ionomycin stimulates [ 3 H]anandamide formation in cultures of ratstriatal and cortical neurons labeled by incubation with [ 3 H]ethanolamine . In the same neurons, Ca2+-dependent [3 H]ana ndamide production may be elicited by the glutamate receptor agonist, kainate, by the K+ channel blocker 4- aminopyridine, and by membrane-depolarizing con centrations of K+ ions .

Depolarizationof neural cells was also shown to evoke Ca2+-dependent anandamide release in vivo . Along with Ca2+ entry,vertical grow shelf activation of certain G pro tein-coupled receptors can also initiate anandamide generation. Administration of the dopamine D2-recep tor agonist quinpirole causes a profound stimulation of anandamide synthesis in the rat basal ganglia, which is prevented by the D2 antagonist raclopride . Importantly, cocaine elicits a similar response , suggesting a role for anandamide in the actions of these psychostimulant drugs. The ability of the anandamide transport inhibitor AM404 to reduce D2 agonist induced hyperactivity, discussed below, further sup ports this possibility .The biological elimination of anandamide proceeds through two successive steps of high-affinity transport into cells, followed by intracellular degradation . Brain neurons and astrocytes in culture internalize anandamide through a process that fulfills all key requirements of a carrier-mediated transport. Plots of the initial rates of [3 H]anandamide internalization in rat brain neurons and astrocytes in culture yield apparent Michaelis constants that are consistent with a saturable process and are comparable to the KM values of brain amine or amino-acid transporters . Moreover, neurons and astrocytes in culture internalize [3 H]anandamide, along with a select group of structurally related compounds, in a stereoselective manner . Evenfurther, [3 H]ana ndamide internalization can be inhibited by drugs that have no effect on the uptake of non-cannabinoid lipid mediators such as fatty acids and eicosanoids . Nevertheless, anandamide is internalized in a Na+- and energy-inde pendent manner , a feature that differentiates this lipid mediator from most conven tional neurotransmitters.The prototype of this class of drugs, the arachidonate derivative AM404 , has provided important information on the properties of anandamide transport, not only aiding the in vitro characterization of this process, but also helping to reveal its possible functions in animals. Importantly, the partial cannabimetic profile exhibited by this agent in vivo suggests that anandamide transport might provide a useful tar get in disease conditions in which the endocannabinoid system is hypofunctional . Evidence indicates that one such condition could be opiate withdrawal, which is markedly reduced in rodents by administering AM404 . These theories have been hindered by the fact that the putative transport system responsible for anandamide internalization is still uncharacterized at the mol ecular level.

In fact, the presence of such a system has been recently questioned, based on the observation that [ 3 H]anandamide uptake in certain cell lines is saturable at longer , but not at shorter incubationtimes . This finding has been interpreted to suggest that fatty-acid amide hydrolase —a key enzyme of intracellular anandamide degradation, described in a subsequent section—may be responsible for the saturation of uptake noted at longer incubation times . However, the result may also be explained on purely technical grounds, as the high concentration of serum albumin used in the experiments of Glaser and collaborators was previously shown to prevent [3 H]anandamide internalization . Consistent with this interpretation, recent stu dies have provided additional evidence for the existence of an anandamide transport system independent of FAAH . In particular, one of these studies has shown that cultures of cortical neurons isolated from the brain of FAAH null mice internalize anandamide as efficiently as do neurons that express normal levels of the enzyme. The same study also demonstrated that the transport inhibitor AM404 is equally effective at reducing anandamide internalization in neurons of FAAH-null and wild-type mice. These results indicate that FAAH does not pro vide the driving force for anandamide uptake or serve as a target for AM404. Invivo experiments further support this conclusion, showing that AM404 not only enhances the actions of exogenous anandamide in FAAH-null mice, but acts more effectively in this mutant strain than it does in control animals. This implies that AM404 is not in fact a FAAH inhibitor, as it has been proposed , but a FAAH substrate. In support of this idea, it was found that membranes prepared from the brains of normal mice rapidly hydrolyze AM404, whereas those prepared from mice that lack FAAH are unable to carry out this reaction.The fact that FAAH is not directly involved in anandamide internalization raises the question of what mechanism provides the driving force for this process. One possibility is that an intracellular protein may sequester anandamide at the membrane, driving its internalization and facilitating its movement to the mitochondria and the endoplasmic reticulum, where FAAH is primarily localized . If selective for anandamide, such a protein might participate in the transport process as well as serve as a target for transport inhibitors. This hypothetical model is consistent with fatty acid transport into cells, which is also thought to require the cooperation of membrane transporters and intracellular fatty-acid binding proteins .AM404 increases endogenous anandamide levels in brain tissue and peripheral blood of rats and mice . This effect is accompanied by a series of behavioral responses that, though blocked by the CB1 antagonist rimonabant , are clearly distinguishable from those of direct cannabinoid agonists.

For example, administra tion of AM404 into the cerebral ventricles of rats decreases exploratory activity without producing cata lepsy and analgesia, two hallmarks of direct CB1 receptor activation. Inaddition, AM404 reduces two characteristic effects caused by activationof D2 family receptors: the yawning response elicited in mice by low doses of the D1/D2-receptor agonist apomorphine; and the stimu lationof locomotor activity evoked inrats by the D2- receptor agonist quinpirole . These effects are observed at doses of AM404 that selectively target anandamide transport and produce only mild hypokinesia when the drug is administered alone . The results of this study,cannabis grow indoor which have been  confirmed in several subsequent reports , demarcate the pharmacological profifile of AM404 from those of direct-acting cannabinoid drugs. This distinction may result from the ability of AM404 to enhance ananda mide signaling in an activity-dependent manner, caus ing anandamide to accumulate in discrete regions of the brain and only when appropriate stimuli initiate its release. Pharmacological activationof D2 receptors may represent one such stimulus, suggesting that blockade of anandamide transport might offffer an inno vative strategy to correct abnormalities associated with dysfunction in dopaminergic transmission. Initial tests of this hypothesis have shownthat systemic adminis tration of AM404 normalizes movement in sponta neously hypertensive rats , an inbred line in which hyperactivity and attention defificits have been linked to a defective regulation of mesocorticolimbic dopamine pathways .FAAH was first identifified as an amide hydrolase activity present in rat liver tissue, which catalyzes the hydrolysis of the fatty-acid ethanolamides palmitoy lethanolamide and oleoylethanolamide . That anandamide serves as a substrate for this activity was first suggested onthe basis of biochemical evidence and later demonstrated by molecular clon ing, heterologous expression and generation of FAAH null mice by homologous recombination . FAAH belongs to a group of enzymes known as ‘amidase signature family’ and catalyzes the hydrolysis not only of anandamide and other fatty-acid ethanola mides, but also of primary amides such as oleamide and even of fatty-acid esters such as 2-AG . Elegant site-directed mutagenesis and X-ray diffffraction studies have demonstrated that this unusually broad substrate preference is due to a novel catalytic mech anism involving the amino-acid residue lysine 142. This residue may act as a general acid catalyst, favoring the protonation and consequent detachment of reaction products from the enzyme’s active site . Three serine resi dues that are conserved in all amidase signature enzymes also may be essential for enzymatic activity: serine 241 may serve as the enzyme’s catalytic nucleophile, while serine 217 and 218 may modulate catalysis through an as-yet-unidenti- fified mechanism .

Electron microscopy experiments in the rat and mouse brain have shown that FAAH is predominantly, if not exclusively localized to intracellular membrane com partments, particularly to the endoplasmic reticulum and the mitochondria . Although FAAH appears to be the predominant route of anandamide hydrolysis in the brain, other enzymes are likely to participate in the breakdown of this endocannabinoid in peripheral tissues. An acid amide hydrolase activity catalytically distinct from FAAH has beencharacterized inhumanmega karyoblastic cells and shown to be highly expressed in the rat thymus, lungs and intestine .The search for small-molecule inhibitors of intra cellular FAAH activity has led to the emergence of sev eral potent and selective agents, which include substituted sulfonyl flfluorides , alpha-keto-oxazolopyridines an d carbamic acid esters . The latter were identifified during structure– activity relationship studies aimed at determining whether esters of carbamic acid such as the insecticide carbaryl inhibit FAAH activity. It was found that, although carbaryl is ineffective in this regard, variations in its template result in significant inhibitory potencies. Fur ther structural optimizations yielded a group of highly potent inhibitors, a representative example of which is provided by the compound URB597 . Kinetic and dialysis experiments indicate that URB597 interacts non-competitively with FAAH, which is suggestive of anirreversible or slowly revers ible associationwith the enzyme. Importantly, URB597 has no notable effect on CB1 or CB2 binding, ananda mide transport, or rat brain monoglyceride lipase , a cytosolic serine hydrolase that catalyzes the hydrolysis of the second endocannabinoid, 2-arachido noylglycerol  . Following administration to rats in vivo, URB597 produces profound, dose-dependent inhibition of brain FAAH activity. After injection of a maximal dose of compound , FAAH inhi bitionis rapid , persistent and asso ciated with a 3-fold increase in brain anandamide levels. Furthermore, the inhibitor intensififies and pro longs the effects produced by exogenous anandamide, yet it elicits no overt cannabinoid-like actions when administered alone; for example, it does not cause hypothermia, hot-plate analgesia, or hyperphagia .Although URB597 does not display a typical canna binoid profifile in live animals, it exerts several pharma cological effects that might be therapeutically relevant. One such effect, the ability to reduce anxiety-like beha viors inrats, was demonstrated intwo distinct experi mental models: the elevated ‘zero maze’ test, and the isolation-induced ultrasonic emission test . The ‘zero maze’ consists of an elevated annular platform with two open and two closed quad rants and is based on the conflflict between an animal’s instinct to explore its environment and its fear of open spaces where it may be attacked by predators . Benzodiazepines and other clinically used anxiolytic drugs increase the proportion of time spent in, and the number of entries made into, the open com partments. In a similar fashion, URB597 elicits anxio lytic-like responses at a dose that corresponds to those required to inhibit brain FAAH activity. Moreover, these effects are prevented by the CB1-selective antagonist rimona bant. Analogous results were obtained in the ultrasonic vocalizationemissiontest, which measures the number of stress-induced vocalizations emitted by rat pups removed from their nest .

It is possible that participants in our study were obtaining care in safety‐net primary care settings with CCMs. Alternatively, the reduced odds of unmet need amongst those who had regular care providers could reflect other factors that we did not measure. For example, having a regular care provider may be a marker for increased system engagement and reduced barriers to any type of care. Those who seek primary care may be more organized, knowledgeable about safety‐net service availability, and have more access to transportation and other enabling resources. . Having a case manager was associated with less mental health and substance use treatment need. In the case management brokerage model, case managers help people navigate care systems and provide a linkage to services. In the clinical case management model, case managers serve as care providers and may provide both mental health and substance use services directly . In some models, such as intensive case management, case managers provide both brokerage and direct services . It is possible that the association between having a case manager and decreased odds of unmet need for both mental health and substance use services is a result of reverse causality; treatment programs may assign a case manager. We found that participants who first became homeless at age 50 or older had a higher odds of unmet substance use treatment need. Those with late onset homelessness had led more “typical” lives, with a higher likelihood of having been continuously employed and having been married or partnered . They were less likely to have had early onset of substance use problems, thus, they may have developed substance use problems more recently. These individuals may have been less aware of safety‐ net resources in general or resources for substance use treatment in particular. Spending time in jail/prison in the past 6 months was associated with reduced unmet substance use treatment need. It is possible that participants initiated substance use treatment while incarcerated. However, most incarceration settings do not provide adequate treatment services. 

Alternatively, as a condition of release,hydroponic racks participants may have been required to engage in substance use treatment.By giving medication‐assisted treatments, such as buprenorphine for opioid use disorder and naltrexone for alcohol use disorder in primary care settings, primary care providers can begin to address this unmet need . However, there is a need for greatly expanded substance use services. Our study has several limitations. We did not use a full psychiatric diagnostic interview. However, screening measures are important empirical tools for the referral of individuals to mental health treatment, especially when integrated care is available . We did not ask participants where they received mental health services, thus we cannot determine whether they received care colocated with primary care, or treatment in mental health specific settings.Historical descriptions of the stimulatory effects of Cannabis sativa on feeding are now explained by the ability of its psycho active constituent 9 -tetrahydrocannabinol to interact with CB1 cannabinoid receptors . Both THC and the endogenous cannabinoid anan damide  promote overeating in partially satiated rats . Moreover, THC increases fat intake in laboratory animals and stimulates appetite in humans . The selective CB1 receptor antagonist SR141716A counteracts these effects and, when administered alone, decreases standard chow intake and caloric consumption , presumably by antagonizing the actions of endogenously released endocan nabinoids such as anandamide and 2-arachidonoylglycerol . These results suggest that endocannabinoid substances may play a role in the promotion of food intake, possibly by delaying satiety. It is generally thought that the hyperphagic actions of cannabinoids are mediated by CB1 receptors located in brain circuits involved in the regulation of motivated behaviors . Thus, infusions of anandamide in the ventromedial hypothalamus were shown to promote hyperphagia , whereas the anorectic effects of leptin were found to be associated with a decrease in hypothalamic anandamide levels . Nevertheless, evidence suggests that cannabinoids also may promote feeding by acting at periph eral sites. Indeed, CB1 receptors are found on nerve terminals innervating the gastrointestinal tract , which are known to be involved in mediating satiety signals that originated in the gut .

To test this hypothesis, in the present study we have examined the impact of feeding on intestinal anandamide accumulation, the effects of central versus peripheral systemic administration of cannabinoid receptor agonists on feeding behavior, and the effects of sensory deafferentation on cannabinoid-induced hyperphagia.Animals. Male Wistar rats were housed individually with food and water available ad libitum, except when restriction was required. All animal procedures met the National Institutes of Health guidelinesfor the care and use of laboratory animals and the European Commu nities directive 86/609/EEC regulating animal research. Surgery. For intracerebroventricular injections, stainless steel guide cannulas aimed at the lateral ventricle were implanted in the rats. The animals were anesthetized with equithesin and placed in a David Kopf Instruments stereotaxic instrument with the incisor bar set at 5 mm above the interaural line. A guide cannula was secured to the skull by using two stainless steel screws and dental cement and was closed with 30 gauge obturators . The implantation coordinates were 0.6 mm posterior to bregma,2.0 mm lateral, and 3.2 mm below the surface of the skull. These coordinates placed the cannula 1 mm above the ventricle. Aftera7d post surgical recovery period, cannula patency was confirmed by gravity flow of isotonic saline through an 8-mm-long, 30 gauge injector inserted within the guide to 1 mm beyond its tip. This procedure allowed the animals to become familiar with the injection technique. Chemicals. Capsaicin was purchased from Sigma , and cholecystokinin octapeptide sulfated , R–methyl]pyrol[1,2,3-de]-1,4-benzoxazin-6-yl) methanone monomethanesulfonate , and 1,4-dihydro-3–5H-pyrrolo[3,2-b]pyridin-5- one were obtained from Tocris Cookson . N-pip eridino-5–1–4-methylpyrazole-3- carboxamide was a gift from Sanofi Recherche . Anandamide and oleoylethanolamide were synthesized in the laboratory . Capsaicin was dissolved in 5% Tween 80, 5% propyleneglycol, and 90% saline. All other drugs were dissolved in dimethylsulfoxide and administered in 70% DMSO in sterile saline. HPLC/mass spectrometry analyses. Anandamide was solvent-extracted from tissues, fractionated by column chromatography, and quantified by HPLC/mass spectrometry with an isotope dilution method, as described previously . Drug treatments. Capsaicin was administered subcutaneously  in rats anesthetized with ethyl ether.

The total dose of capsaicin was divided into three injections . Control rats received vehicle injections. Experiments were performed 10 d after capsaicin treatment in rats that had lost the corneal chemosensory reflex , and showed enhanced water intake 10 d after capsaicin treatment.For intracerebroventricular administration, the obturator was removed from the guide cannula and an 8 mm injector that was connected to 70 cm of calibrated polyethylene-10 tubing was lowered into the ventricle. The tubing was then raised until flow began, and 5l of drug solution was infused over a 30–60 sec period. The injector was left in the guide cannula for an additional 30 sec and then removed. The stylet was immediately replaced. Animals were tested 5 min after injections. The intracerebroventricular cannula placements were evaluated after each experiment by dye injection. Only rats with proper intracerebroventricular placements were included in the data analysis. Food intake studies. The effects of drugs on feeding behavior were analyzed in animals deprived of food for 24 hr and habituated to handling or in partially satiated animals . To this end, 48 hr before testing,indoor garden table the bedding material was removed from the cage and a small can containing food pellets was placed inside the cage for 4 hr. The animals were then food-deprived for 24 hr, with access to water ad libitum. The animals were returned to their home cage 15 min after drug administration; there, a can with a measured amount of food and a bottle containing 250 ml of fresh water were placed. Food pellets and food spillage were weighed at 60, 120, and 240 min after starting the test, and the amount of food eaten was recorded. At the end of the test, the amount of water consumed was also measured. For partial satiation of animals, 24 hr food-deprived rats were allowed to eat from the can for 1 hr. The can was replaced and intake was recorded. Fifteen minutes after drug injections, the food was again presented, and the amount consumed was recorded hourly for the next 4 hr. Open-field test. Motor behaviors in the open field were studied in an opaque open field as described previously . The field was illuminated using a ceiling halogen lamp regulated to yield 350 lux at the center of the field. Rats were habituated to the field for 10 min the day before testing. On the experimental day, the animals were treated and placed in the center of the field, and locomotor activity and rearing and grooming behavior were scored for 5 min at 5, 30, 60, and 120 min after drug injection. Behavior was scored by trained observers who were unaware of the experimental conditions. Statistics. Statistical significance was assessed by one-way or multi-factorial ANOVA, as required. After a significant F value, post hoc analysis was performed. Calculations were done using the BMDP statistical package .We first investigated whether starvation and refeeding affect anandamide content in intestinal tissue, where various intrinsic signals modulating food intake, such as CCK and OEA , are generated. As shown in Figure 1, food deprivation was accompanied by a seven fold increase in anandamide content in the small intestine, an effect that was reversed on refeeding. In contrast, no such increase was observed in brain or stomach tissues . The change in intestinal anandamide did not result from the inhibition of anandamide degradation. Indeed, fatty acid amidohydrolase activity, which catalyzes the deactivating hydro lysis of anandamide, was not affected by the feeding status .The small intestine produces both anandamide, which stimulates food intake , and OEA, which inhibits food intake by acting on peripheral sensory fibers . However, the intestinal levels of the two compounds appear to be reciprocally regulated. Thus, the OEA content decreases , whereas the anandamide content increases during starvation. To examine the possible interaction of these fatty acid ethanolamides on feeding, we studied whether OEA blocks AEA-induced hyperphagia and whether blockade of CB1 receptors with a low, sub-threshold dose of SR141716A potentiates the inhibitory actions of OEA on food intake.

The results, illustrated in Figure 4A, indicate that pretreatment with OEA inhibits AEA-induced hyperphagia in partially satiated rats, whereas SR141716A and OEA act synergistically to decrease eating in food-deprived animals . The effects were ob served during the 240 min period of testing. The inhibitory actions of combined SR141716A and OEA lasted for at least 24 hr , a prolonged effect that these drugs do not elicit separately.The present results suggest, first, that systemically administered cannabinoid agents affect food intake predominantly by engaging peripheral CB1 receptors localized to capsaicin-sensitive sensory terminals and, second, that intestinal anandamide is a relevant signal for the regulation of feeding. Two observations support the idea that cannabinoid agents modulate feeding through a peripheral mechanism. First, the lack of effect of central administration of cannabinoid antagonists such as SR14116A and 6-iodo-2-methyl-1-[2-ethyl]-[1H]-indol-3-yl methanone on food intake in food-deprived animals and, second, the ability of capsaicin-induced deafferentation to prevent changes in feeding elicited by the peripheral administration of cannabinoid drugs. Moreover, the similar pattern of expression of the early gene c-fos on hypothalamic and brainstem areas regulating food intake after both the peripheral administration of either CB1 agonists and antagonists and the acute administration of peripherally acting satiety modulators such as gastrointestinal hormones or feeding inhibitors such as OEA further support the peripheral actions of cannabinoids on food intake. Finally, the fact that the CB1 receptor antagonist SR141716A was active only after intraperitoneal or oral administration but not after subcutaneous injection further supports this hypothesis. These results do exclude the possibility that peripheral anandamide also modulates feeding by acting on specific hypothalamic areas involved in caloric homeostasis . However, they do suggest that the predominant effects of systemically administered SR141716A are mediated by peripheral CB1 receptors, which may thus represent a potential target for anorexic agents. The concentration of anandamide in intestinal tissue increases during food deprivation, reaching levels that are threefold greater than those needed to half maximally activate CB1 receptors . This surge in anandamide levels, the mechanism of which is unknown, may serve as a short-range hunger signal to promote feeding. This idea is supported by the ability of SR141716A to reduce food intake after systemic but not central administration.

DSM-IV diagnoses for all disorders were made algorithmically from SSAGA information. However for these analyses we also generated a DSM-5 diagnosis for AUD in the following way. Individual alcohol symptoms were queried, starting with symptoms of DSM-IV alcohol dependence and alcohol abuse, adding craving and subtracting legal problems related to alcohol. Onset and offset of each symptom was recorded, making it possible to cluster symptoms that occurred by age. Thus the analyses presented here use DSM-5 AUD as an outcome variable while all other disorders are diagnosed by DSM-IV.Diagnoses of externalizing and internalizing disorders at the baseline interview were also made algorithmically from the SSAGA using DSM-IV. Externalizing disorders included any of the following: ADHD, conduct disorder/antisocial personality disorder, oppositional defiant disorder, drug use disorder . Internalizing disorders included major depression, panic disorder, obsessive-compulsive disorder, social phobia, and agoraphobia.Subjects were divided into groups based on whether they had an externalizing disorder or an internalizing disorder at the time of the baseline interview. The groups were: Externalizing, Internalizing, Both, or Neither. Alcohol use disorder diagnosis was then assessed at each interview period, using the DSM 5 distinctions for Mild AUD , Moderate AUD , and Severe AUD . Subjects with age of onset of AUD prior to age of onset of internalizing/externalizing disorders were excluded from analysis. We also performed a sensitivity analysis in which all subjects with externalizing were compared with all subjects without externalizing; likewise subjects with internalizing were compared with all subjects without internalizing . An externalizing-internalizing interaction term was included in this analysis. Overall, 43.0% of the sample met criteria for a diagnosis of either Mild, Moderate, or Severe AUD by the end of the observation period .

At the time of the baseline interview, 982/3286 subjects had an externalizing diagnosis ; 140/3286 subjects had an internalizing diagnosis , 286 had both and 1878 had neither . All covariates had significant relationships to age of onset in subjects with either mild, moderate, or severe AUD . The association of any comorbid disorder and presence of Alcohol Use Disorder was significant overall ,plant growing stand and there was a significant effect of comorbidity on age of onset as well . Among subjects with an externalizing disorder only at baseline, 515/982 had some type of AUD during the follow-up period. Among subjects with an internalizing disorder only at baseline 66/140 had an AUD. Among subjects with both externalizing and internalizing, 182/286 had an AUD. In comparison, subjects with neither type of disorder had an AUD rate of 34.7% . Figure 1 shows onset of alcohol use disorders in subjects stratified by initial diagnoses of Externalizing disorder, Internalizing disorder, Both, or Neither. Figures 1a–c show onset of mild, moderate, and severe AUDs respectively. For each type of AUD, the relationship with comorbid disorders is significant by Log-rank test and Cox Proportional Hazards . Age of onset comparisons are shown in Kaplan-Meier Plots . Each of these shows significant effects of comorbidity by Log-rank Test . The plots do not include a covariate effect but we have also achieved similar results by the Cox model adjusting for covariate effects . The statistical effect of comorbidity is generally greatest in the development of Severe AUD and least in Mild AUD based on the hazard ratios in the different comorbidity types . The three groups are significantly different from each other in the strength of the comorbidity effect . The sensitivity analysis showed a clear effect of externalizing on age of onset in mild AUD, moderate AUD, and severe AUD . For internalizing, there was an effect in moderate AUD and severe AUD . No statistical interaction was seen between the effect of externalizing and the effect of internalizing. Age of onset distributions are presented for Mild AUD , Moderate AUD , and Severe AUD . The distributions include drinking milestones as well as onset ages for the diagnoses of Mild AUD , Moderate AUD and Severe AUD . As noted above, the study samples are independent of each other for analytic purposes, and are classified according to the most severe disorder that the subject met criteria for during the observation period.

Figure 2 shows drinking milestones in subjects who developed an alcohol use disorder. Figure 2a–c show mean, median, interquartile range, and outliers for subjects with mild , moderate and severe alcohol use disorder. Subjects are classified in a cohort according to the most severe form of disorder they manifested during the observation period. In Figure 2b milestones for the moderate group include the age when they would have been first classified as showing a mild AUD. In Figure 2c milestones for the severe group include the ages when they would have been first classified as showing a mild or moderate AUD. We used ANOVA and i-test to detect the correlation between the onset of drinking milestones in the four diagnostic groups. The mean age of first drink progresses from 16.2 inUnaffected to 14.9 in Mild to 14.4 in Moderate to 12.8 in Severe . The mean age of first regular drinking progresses from 18.8 in Unaffected to 17.5 in Mild to 16.9 in Moderate to 15.7 in Severe . The mean age for meeting criteria for Mild AUD progresses from 18.6 in Mild to 17.4 in Moderate to 16.1 in Severe . The mean age for meeting criteria for Moderate AUD progresses from 19.1 in Moderate to 17.3 in Severe . The age of onset for Severe AUD is 18.5. This age relationship is detailed in Figure 3. Figure 3 represents the onset of alcohol use and alcohol problems in 3286 adolescents observed over a ten year period. It includes 1870 who remained unaffected, 684 who developed mild alcohol use disorder, 415 who developed moderate alcohol use disorder, and 317 who developed severe alcohol use disorder. The ANOVA for onset of first drink among the unaffected, mild, moderate, and severe cohorts shows p < 0.001. The ANOVA for onset of regular drinking among the unaffected, mild, moderate, and severe cohorts shows p < 0.001. The ANOVA for onset age of mild AUD among the mild, moderate, and severe cohorts shows p < 0.001. The t-test for onset age of moderate AUD between the moderate and severe cohorts shows p < 0.001. These data suggest a strong effect of externalizing and internalizing disorders on prevalence and age of onset of Alcohol Use Disorder among adolescents/young adults at risk for the development of AUD on the basis of family history.

Externalizing disorders were clearly associated with an increased risk for AUD and for earlier development of AUD. Internalizing disorders by themselves did not show a significant effect, but in combination with externalizing disorders they were associated with an earlier onset for severe AUD . When we considered all internalizing disorders together a clear effect on onset of moderate AUD was seen as well. By the end of the follow-up period,plant grow table more than 60% of young people with both externalizing and internalizing disorders at baseline had developed alcohol dependence in comparison with about 30% of young people with neither type of comorbid disorder. The effect of comorbidity was stronger in more severe forms of AUD, with a 6-fold increase in risk for Severe AUD among subjects with both externalizing and internalizing disorders compared to subjects with neither form of comorbid disorder. There was also evidence for an earlier developmental course in more severe forms of AUD compared to less severe. Persons with Severe AUD were likely to have their first full drink prior to the age of 13 and be drinking regularly prior to age 16 and experiencing 1–2 alcohol problems by that same age. In contrast young people who did not demonstrate any AUD were likely to have their first drink at 16 and start regular drinking just prior to age 19. Median and mean ages of onset for each type of AUD were 18–19, though the range extended through the follow-up period. Those at greatest risk for an AUD were males of European descent from an alcohol dependent proband family with one or more childhood onset psychiatric diagnoses. Those at least risk were females of African-American ancestry from a non-case family with no childhood onset diagnosis. Limitations of the study include the fact that all analyses are based on self-report and there is no independent corroboration of diagnoses or symptoms. Subjects interviewed in their late 20s may have had more difficulty with accurate reporting of events in early teenage years in comparison to subjects in their mid-teens. Retention rate from baseline interview to two-year interview was 85%, the majority of subjects completed at least four interviews . Families in the COGA study tend to be densely affected and results may not be generalizable to persons with alcohol use disorder in the general population. The subjects were ascertained at 7 University-based clinical sites and the populations studied reflect those sites. The magnitude of these effects was substantial, and this information may be helpful in targeting efforts at education and prevention. In this sample most of the AUD-affected subjects had a comorbid psychiatric disorder at baseline. Many such subjects may come to clinical attention for their childhood-onset disorders and it may be worth educational efforts targeting AUD, especially for those at increased familial risk. It has been argued, though, that more intensive interventions are not likely to be cost- effective at this time . It seems to be of value to continue to try to quantify risk in various clinically and biologically identifiable groups. Polygenic risk scores, especially as they increase in power with data from expanding clinical samples, will likely be of use . It would also be of value to attempt to separate AUD effects from other forms of SUD, since we know that they are highly comorbid in many samples, including the sample studied here. The internet has profoundly altered how individuals obtain information regarding their health, and men’s health is no exception. Although men are less likely than women to pursue preventative health care and more likely to develop chronic cardiovascular and metabolic disease, the rise of online social media platforms may play a role in challenging this disproportion. Men contending with infertility increasingly turn to social media platforms for information, guidance, and discussion with peers. A male factor contributes to nearly 60% of all cases of infertility, yet cultural and societal constructs of masculinity create psycho social barriers to consultation with a physician. Social media platforms enfranchise men to take an active role in understanding causes and treatments for infertility by providing anonymity absent from face-to-face encounters. Although health information online is becoming more readily accessible, it escapes the scrutiny of scientific publication guidelines, allowing for the propagation of non-evidenced-based material. Social media tends to amplify the most sensational content and headlines. Literature assessing the quality of male infertility content available online remains scarce, although a recent review has shown that urological conditions as a whole suffer from a spread of misinformation on social media. Social media analytics tools have emerged that provide detailed, quantitative metrics, but these tools have not yet been applied to content in the male infertility space. Given the proliferation of sensationalism on social media, we hypothesized that content about male infertility shared on social media platforms may be largely inaccurate or misleading. Using a combination of ananalytics tool and a quality rating system, we per formed a quantitative and qualitative analysis of male infertility content shared on social media. These data may inform how men’s health specialists should aproach patient education about male infertility, as well as ways in which they engage with social media in the future.We used the social media analytics tool BuzzSumo to identify the most shared male infertility content from September 2018 through August 2019. BuzzSumo gathers data across the social media platforms Facebook, Pinterest, Reddit, and Twitter to generate a list of article links with the highest online engagement. Engagement is defined as the total number of interactions that users have with a particular article link, including actions, such as “liking,” “commenting,” and “sharing” on social media. Two urologists with advanced fellowship training in male reproductive medicine initially screened a total of 20 search terms related to male infertility using BuzzSumo.

Since 2014, overall life expectancy in the US has fallen for three years in a row, reversing a century-long trend of steadily declining mortality rates. This decrease in life expectancy reflects a dramatic increase in deaths from so-called “deaths of despair” – alcohol, drugs and suicide – among Americans without a college degree . Case and Deaton suggest that the increase in deaths from alcohol, drugs and suicide is largely attributable to stagnant living standards and long-term declines in economic opportunity among working class non-Hispanic whites. Other scholars have questioned the explanatory focus on distress and despair , especially for drug-related deaths. These researchers point instead to the role of new highly addictive and risky drugs. Case agrees with this revision. We contribute to this discussion by examining how two economic policies that increase after tax incomes of low-income Americans – the minimum wage and the earned income tax credit – causally affect deaths of despair. To do so, we use the CDC’s geocoded causes of death mortality data and leverage plausibly exogenous variation across states and time in these two policies. We employ the standard approach in the minimum wage – employment and EITC literatures to estimate panel models of cause-specific mortality over time, controlling for state and year fixed effects, testing the crucial parallel trends assumption and implementing a series of falsification and robustness tests. First, we estimate a set of placebo regressions, testing for effects in a sample of adults with a bachelor’s degree or higher. As this group is unlikely to work minimum wage jobs or to be eligible for the EITC, any effects on this group then are likely spurious, indicating a problem with the research design. Moreover, we implement event study models estimating changes in mortality around the time that states increase the minimum wage or implement state EITCs. Our models do not find a significant effect of either policy on drug mortality. However,vertical rack both higher minimum wages and EITCs significantly reduce non-drug suicides among lesseducated adults.

We find no significant effects in the more educated placebo sample, which is reassuring for our study design. We also find heterogeneous effects by gender: effects are larger and more statistically significant for women; for men, effects of the minimum wage are only marginally significant. Our estimated event study models establish parallel pre-trends — states that increase their minimum wages do not experience differential mortality trends in the years leading up to the implementation of the new higher wage. Moreover, the event study models show a discontinuous drop in suicide mortality at the time of minimum wage increases and implementation of state EITCs. Using auxiliary data from the Current Population Survey, we show that estimated effects significantly correlate with exposure to policies: sub-samples with larger exposure to minimum wages tend to have larger associated effects of minimum wages on suicides, while estimated effects of the EITC on average are larger for groups that have high rates of estimated EITC receipt. The findings of this paper contribute to the debate on the causes of deaths of despair. This discussion has taken place against a backdrop of a large body of literature that identifies socioeconomic status as a primary social determinant of health . However, the identification of causality remains a key issue within this literature: lower income may prevent individuals from engaging in health-enhancing behaviors or to access medical care, leading to poorer health outcomes. At the same time, sicker individuals may have more difficulty maintaining employment, leading to a negative association between health and income. To address this issue of causality, a number of recent papers have used quasi-experimental methods to isolate the effects of labor market shocks on mental health, all-cause mortality and deaths of despair . Carpenter, McLellan and Rees find that economic downturns lead to increased intensity of prescription pain reliever use and to increases in substance use disorders involving opioids. Moreover, they find that such effects are concentrated among working-age white males with low educational attainment. Autor, Dorn and Hanson find that labor demand shocks lead to premature mortality among young males.

These studies indicate that negative income shocks worsen health. More generally, a growing literature finds effects of economic policies on related health behaviors and outcomes. For example, using data from the Behavioral Risk Factor Surveillance System, Horn, MacLean and Strain find that minimum wage increases lead to reduced self-reported depression among women, but not among men. Sabia, Pitts and Argys find that minimum wages do not have harmful effects on teen alcoholism or drunk driving fatalities.While their findings are suggestive, the analysis stops short of credibly establishing a causal link . This partly results from limitations inherent to publicly available data: the authors are not able to explore heterogeneous effects by education and therefore cannot conduct placebo tests. Moreover, suppression of cells with few underlying observations complicate their analysis of effects by race and gender. Finally, their models make no attempt to analyze the credibility of the parallel trends assumption by examining time paths of effects around minimum wage increases. More generally, our methods improve in important respects upon the existing literature on minimum wages and health. Previous work on the employment effects of minimum wages highlighted some weak methods that characterize many of the studies that find negative employment effects . In our view, many of Leigh, Leigh and Du’s 15 “high quality” papers also use questionable methods that cast doubt on their validity as credible causal analyses of minimum wage effects on health outcomes. 2 The rest of the paper is organized as follows: Section 2 presents the data, while section 3 presents our empirical models in some detail. Results are presented in section 4, and section 5 concludes.In this paper, we study effects of two policies intended to raise incomes for low wage workers: the minimum wage and the EITC. During the sample period, many states implemented minimum wage policies exceeding the federal. Moreover, the sample period covers a significant federal minimum wage increase in 2007-2009; this increase was nonbinding for several high minimum wage states.

As a result, there is substantial variation in minimum wages within and between states in our sample. Eligibility for the EITC varies with household income and family characteristics: To qualify, households must have earned income; the credit phases in gradually up to a plateau, before phasing out at higher incomes. The phase-in and phase-out rates and maximum credit vary with family characteristics. The bulk of EITC credits go to low income families with children: Adults with no qualifying children are only eligible for relatively small benefits – in 2015, the maximum credit for people with no dependents was $503, compared to $5548 for a family with 2 dependents. This variation in eligibility and credit size has allowed researchers to study effects of the policy by comparing changes in outcomes for different family types around the time of federal EITC expansions. However, the mortality data do not include detailed family information to implement this kind of analysis. Instead, our empirical approach will exploit variation in state EITCs. These policies typically take the form of a proportional increase to the federal credit. 25 states plus DC had state EITCs at some time during the sample period. The policies vary significantly in magnitude,microgreen flood table with top-up rates ranging from 3.5% to 40%. We hypothesize that these two policies may affect deaths of despair by raising earnings at the low end of the income distribution. However, the model does not allow us to test this hypothesis directly. Rather, our estimates may reflect a combination of income and employment effects. Traditional economic theory predicts that higher minimum wages may induce job loss, as employers respond to higher labor costs by cutting back on employment. If this were the case, we might expect higher minimum wages to have negative effects on health in general, and on deaths of despair in particular. However, the large literature examining the effects of minimum wages on employment suggests that the disemployment effects have been small at most . Moreover, recent studies find that higher minimum wages raises earnings at the low end of the household earnings distribution, leading to significant reductions in poverty . Several studies have found that EITC expansions have positive employment effects for single mothers . To assess whether employment effects are quantitatively important in our sample, we have estimated simple panel models using the Current Population Survey. Results, shown in Appendix table 1, indicate that neither policy has any statistically significant effects on employment in either a pooled sample of workers with high school or less, or when separating samples by gender.3 However, these estimates could mask heterogeneous employment impacts across individuals. To the extent that employment in itself affects health, our estimates will then in part reflect these effects, together with any impacts of higher income. Note that we do not consider the impact of the Supplemental Nutrition Assistance Program . While this program is arguably a key safety net and antipoverty program, the lack of state level variation makes it difficult to estimate meaningful effects of this program on short term mortality.Sample Our primary data source consists of the restricted access geocoded CDC Multiple Causes of Death data for the years 1999 to 2015. The data is collapsed by state of residence, year and demographic cells, defined by age , education and gender. The analysis focuses on non-elderly adult mortality, excluding deaths at ages younger than 18 or older than 64. Observations with missing data are excluded from the sample.

We exclude four states – Georgia, Nevada, Rhode Island and South Dakota –from the sample because of missing and incomplete education data. In theremaining 46 states plus Washington, DC, 2.48 percent of the death records for the causes we study have missing data during the sample period. The term “deaths of despair” typically includes deaths from drug overdoses, suicides, and deaths from alcohol abuse . Some of these causes, such as deaths from alcoholic liver disease, reflect medical conditions that develop over time. As a consequence, alcohol-related mortality may be less responsive to minimum wage in the short run. We focus therefore on drug overdoses and suicides, which are more likely to be responsive to recent policy changes. For each cell, we calculate the number of deaths that are due to intentional and unintentional drug overdoses as well as the number of non-drug suicides.To take zeroes into account, we use the inverse hyperbolic sine transformation of the death count as our primary measure of mortality We obtained cell-level demographic characteristics and population counts using data from the Current Population Survey’s Annual Social and Economic Supplement . For each cell, we use the CPS survey responses to estimate the distribution of race and ethnicity , the share rural, the share uninsured, and the average age.5 We obtained the following state-level economic covariates from the University of Kentucky Center on Poverty Research : state GDP, population share receiving SSI, state population, the state unemployment rate and the state Earned Income Tax Credit. We obtained data on minimum wages from Vaghul and Zipperer . Since a number of studies have linked marijuana legalization to reductions in prescription opioid use , and the role of cannabis in helping treat opioid use disorder , we also include indicators for whether a state has legalized marijuana for medical or recreational use. Finally, we also include indicators for whether a state has implemented a Prescription Drug Monitoring Program ; based on evidence that such programs may reduce opioid misuse . We obtained state-level marijuana legalization and PDMP variables from the Prescription Drug Abuse Policy System.6 Table 1 shows summary statistics of the sample. The first three rows, which display average mortality rates, confirm a well-known socioeconomic gradient. All cause-specific mortality rates are noticeably higher among the lower-educated group than among the higher-educated group . The most striking differences are for drug non-suicide and non-drug suicide mortality rates. Within each education stratum, rates due to drug non-suicide and non-drug suicide are substantially higher among men than women, particularly among those with a high school diploma or less.

We uniquely examined how GM status is related to risk for SUDs. This is an important contribution as studies assessing SUDs by gender identity are limited and typically focused on substance use instead of abuse . In contrast to findings related to sexual orientation, we did not find consistent evidence of greater prevalence of SUDs among GMs after accounting for sexual orientation in statistical models. The only exception is that GMs assigned male evidenced elevated odds for alcohol dependence. This lack of evidence, however, should be interpreted with caution considering small numbers of GM participants in GUTS and previous evidence indicating their disproportionate substance use . Additional studies quantifying associations between gender identity and SUDs are needed.Among the general population, more people assigned male at birth report probable SUDs than do people assigned female at birth . In contrast, we found SMs assigned female generally had similar or higher levels of SUDs compared to SMs assigned male, and sexual-orientation differences were larger in assigned females than assigned males. One reason is that comparisons between SM and CH women will yield relatively large effect sizes because CH women have the lowest levels of SUDs of all groups defined by sexual orientation and birth sex. Beyond this explanation, there is little insight into why SM women are at especially elevated risk, though some have proposed that SM women are at greater risk for minority-specific stressors and mood disorders, resulting in greater risk for SUDs .Among participants with a drug use disorder, we found that some subgroups of SGMs had elevated odds of reporting use of certain drugs compared with CHs and cisgender participants. Studies examining sexual orientation or gender identity differences in drug use among individuals with drug use disorders are rare; however, cross-sectional studies with participants of the NSDUH found that SM adults were significantly more likely than heterosexuals to report past-year marijuana and other drug use . This indicates that SGMs may be more likely to use different substances than non-SGMs,grow rack which has implications for screening, intervention, and treatment .

The DSM-IV defined separate criteria for substance abuse and dependence, whereas in the updated DSM-5, abuse and dependence are combined into a single SUD diagnosis . Studies comparing DSM-IV and DSM-5 SUD diagnostic criteria have shown increases , no differences , and decreases in prevalence. Increases in SUD prevalences under DSM-5 may relate to the inclusion of ³GLDJQRVWLF RUSKDQV´ in diagnoses those who meet one or two DSM-IV criteria for dependence, but none for abuse . Nonetheless, concordance of DSM-IV and DSM-5 diagnoses are acceptable, with concordance increasing with severity , suggesting that our findings are likely similar to those resulting had we used DSM-5 criteria. Further research is needed to clarify this issue. GUTS participants are not representative of the U.S. population as they are children of registered nurses and predominantly non-Hispanic White. The prevalence of SUDs in GUTS, however, is comparable to same-aged participants of the NSDUH , as is the distribution of SGMs enrolled in GUTS compared to population-based studies . Additionally, GUTS participants were not enrolled based on their sexual orientation or gender identity. GUTS assessed sexual orientation with a single item tapping both identity and attraction. This limits direct comparisons between our findings and other studies assessing dimensions of sexual orientation separately because research indicates these dimensions have different associations with substance involvement . Further, despite the large sample size, we were limited in our ability to detect within group differences among SGMs. Despite these limitations, our study is strengthened by including multiple SGM subgroups, enabling examination of heterogeneous outcomes that may otherwise be obscured when combining SGM categories. Future research should include more diverse, nationally representative samples to enable examination of interactions between sexual orientation, gender identity, and other sociodemographic factors to further identify higher-risk SGM subgroups.Among the general population, young adults with SUDs experience disproportionate economic and public health burdens and have low utilization of SUD treatment . For SGM young adults, these issues may be even more persistent, with one study finding that less than 4% of the 14-20% of SMs needing treatment actually accessing treatment .

Specific barriers to treatment among SGMs include a lack of targeted interventions, differences in coping strategies and psychiatric comorbidities, discrimination within healthcare settings, lack of provider knowledge about SGM health needs, and lack of insurance . Consequently, increasing access to treatment alone may be insufficient to address SGM SUD disparities. Efforts should also focus on bolstering the provision of culturally tailored, SGM affirming treatment which promotes resilience, coping, and wellness. Further, given high co-morbidity with other mental disorders, interventions are needed which integrate psychological and SUD treatment .Alcohol dependence , characterized by excessive drinking and diagnosed using features such as loss of control over drinking and excessive consumption despite negative consequences, is one of the most common and costly public health problems worldwide.1 In the United States, 12.5% of the population meets criteria for DSM-IV AD.1,2 AD is a complex disease with both genetic and environmental underpinnings and an estimated heritability around 50%.3 Identification of loci associated with AD liability could provide new insights into the biological mechanisms underlying this serious disorder and lead to new therapeutic pathways. Individual genome-wide association studies of AD have been relatively modest in size and have failed to identify consistently replicable loci,5 with the exception of variants within the alcohol metabolizing genes, notably ADH1B, and to a lesser degree, ADH1C. A recent large GWAS meta-analysis of 14 904 AD cases and 37 944 controls, which includes some of the samples used in this study, also only detected genome-wide significant association with rs1229984 and rs2066702 ; both single nucleotide polymorphism are in ADH1B.However, when examining a broader definition of alcohol use disorders from medical records, loci in additional genes have recently been identified.4 We have previously conducted GWAS of AD-related phenotypes in smaller subsets of the data used in the present study, but results have eluded replication and power to detect rs1229984 has been low . One possible challenge to identification of novel loci contributing to AD susceptibility may be the heterogeneity underlying the diagnosis of AD. Meeting criteria for DSM-IV AD requires that an individual endorse any three of the seven DSM-IV criteria during the same 12-month period.

In epidemiological studies and in COGA , this criterion is endorsed quite frequently by individuals with AD, and also by those who do not meet criteria for DSM-IV AD and thus, might index lower severity. Indeed, in item response theory analyses, this criterion had the lowest difficulty as indicated by the item characteristic curves in Figure S7. In contrast, the finding on chromosomes 2 and 15, while GWS for Time spent drinking were also associated with Giving up activities , both highly correlated criteria indicative of high difficulty, and thus, risk for DSM-IV AD.In addition to Withdrawal, we previously found these criteria to distinguish a highly heritable high-risk group of individuals at risk for AD from those in both low- and moderate-risk groups. Thus, as shown in Figure S7, while the chromosome 8 finding potential maps to lower AD severity, the chromosome 2 and 15 findings potentially indicate greater severity. However,greenhouse grow tables none of these loci were GWS for our AD criterion count measure, which is commonly used as an index of severity. These results are consistent with the argument that the validity of an individual criterion, and its impact on impairment may rely heavily on the other criteria that are endorsed alongside it.Importantly, these results underscore that novel information can be gained from studying individual criteria that index differing levels of AD severity that may operate discontinuously. Gene-based analysis identified two GWS genes for two different phenotypes. OTOP1 was associated with DSM-IV criterion count. This gene is related to maintaining metabolic homeostasis but it is not well-studied. BRINP1 showed association with Drinking despite problems. This gene is mostly expressed in brain regions and has been linked to schizophrenia; cognition disorders and Parkinson’s disease.Further studies are needed to test its role in AD. Previous studies indicate that AD may be related to variations in the brain’s reward system,including decreased reward-network volume and differential neural activity in reward circuitry.In the COGA Prospective Sample, minor allele carriers of rs1912461 showed greater differentiation in frontal evoked theta power between loss and gain feedback trials in an EEG-based Monetary Gambling Task.

Prior studies have found lower reward-related theta power in alcoholics and in high-risk offspring of alcoholics than controls performing the same task.Moreover, it has recently been proposed that frontal theta reflects a promising mechanism through which cognitive control may be enacted by invoking a shift from habitual-based striatum responses to deliberative prefrontal-based control of behavior.Furthermore, the frontal central theta power difference between loss and gain conditions may reflect the need for cognitive control to process goal-relevant information, such as decision making and action selection, based on choice-relevant information for optimal functioning in the environment.In this study, the COGA Prospective Sample participants were included in the COGA discovery GWAS. We, therefore, examined the sensitivity of our discovery findings to exclusion of these overlapping individuals from the prospective sample. The resulting GWAS found that while statistical significance decreased in some instances due to the decrease in sample size, the overall results remained highly consistent , indicating that the overlapping subjects were not solely responsible for the GWS findings from the discovery GWAS. In the DNS, rs61826952 minor allele carriers had decreased VS activity to positive vs negative feedback in a number-guessing fMRI task. Increased VS activity and dopamine release to non-alcohol reward have been associated with substance use initiation and problematic drinking.In contrast, studies of AD reported relatively reduced VS activity to non-alcohol reward85,86 and heightened activity to alcohol cues.87 These apparently disparate findings can be integrated with stage-based theories of addiction, which hypothesize that initial problematic use is associated with the positive reinforcing aspects of a substance, while later compulsive use is driven by negative reinforcement and diminished cognitive control, resulting from changes in neural plasticity induced by chronic alcohol use. Thus, results from the college based DNS suggested that the minor allele of rs61826952 may protect from AD by reducing VS-related reward drive, thereby diminishing the likelihood of initiating problematic drinking behavior. Replication of individual variants/genes other than those involved in alcohol metabolism can be challenging and notably influenced by heterogeneity across samples, ascertainment approach, definitions of affected and unaffected, and even nuanced differences in interview instruments.For instance, although families ascertained for AD were included in the replication samples, OZALC had samples ascertained for heavy smoking and drinking , and SAGE included two sub-samples recruited for nicotine and cocaine dependence. In addition, unlike the prior large AD GWAS by Gelernter et al,we excluded individuals with ≥2 abuse or dependence criteria for alcohol or any illicit drug from our unaffected group. This may have led to a greater degree of genetic separation between affected and unaffected in the current analysis and contributed to the lack of replication. Despite these potential differences, for 2 of the 5 loci , meta-analyses across samples yielded more significant associations. In addition, the PRS analyses found that the aggregated effect of variants in regions other than the ADH cluster and the ALDH2 locus significantly contributed to AD liability in these diversely ascertained samples. While the proportion of explained variance is modest, it is consistent with other PRS analyses and supports the generalizability of our findings at a polygenic level. We also examined whether our analyses supported recent findings of Kranzler et al, who conducted a GWAS of alcohol use disorders defined using ICD codes derived from the electronic health records of individuals participating in the Million Veterans Project.4 In this multiancestral sample of 274 424 predominantly male veterans, Kranzler et al identified 18 genome-wide significant loci for AUD as well as for the consumption sub-scale of the Alcohol Use Disorders Identification Testkit . Their signal for rs1229984 was also noted in our COGA GWAS. In addition, modest evidence for directional and statistical support was also noted for rs12639940 on chromosome 4 , and rs2961816 on chromosome 5. Our findings should be considered within the context of a few key limitations. First, despite being large, it is evident that our sample is under powered to detect loci of modest effect.

Like other phospholipid metabolites, N-acyl PEs and NAEs accumulate rapidly in the CNS after the inception of an ischemic injury . This response, likely caused by postischemic rises in the concentration of free Ca21 , may confuse quantitative analysis unless appropriate precautions are taken to prevent it. In our experiments, we have immersed the heads of the animals in liquid nitrogen within 2 sec of decapitation, a procedure that has been used extensively to determine basal levels of free fatty acids and diacylglycerols in brain tissue . Then, by using an analytical approach that combines HPLC purification and GC/MS identification, we have shown that both anandamide and N-arachidonoyl PE are present in brain under these conditions. On average, we measured 11 6 7 pmol of anandamide/gm of wet brain tissue, a value very similar to those obtained very recently by Schmid et al. in pig brain and cow brain , by Sugiura et al. in rat brain , and by Felder et al. in various regions of rat and human brain . Such anandamide levels should be well within the detection limit of the GC/MS isotope dilution method developed by Kempe et al. . These authors did not detect anandamide in their analyses of rat brain tissue, however; differences in the extraction and purification of lipids may account for this discrepancy.The low amounts measured in our study accord better with those obtained with lipid mediators and neuropeptides , than with those obtained with neurotransmitters . Thus, our results reinforce the notion that anandamide may act in the CNS more as a modulatory substance than as a classical neurotransmitter, a possibility that finds further support in its nonvesicular mechanism of release . A comparison of the brain levels of anandamide with those of N-arachidonoyl PE may help clarify the metabolic relationship between these lipid products. The content of N-arachidonoyl PE , twice as large that of anandamide,grow rack systems supports its proposed role as anandamide precursor. Yet, the relatively small proportions of this precursor pool may indicate the existence of an active biochemical mechanism for the resynthesis of N-arachidonoyl PE depleted during neural activity.

In support of this possibility, we have shown previously that biosynthesis of N-acyl PEs in cortical mixed cultures is stimulated by physiologically relevant rises in intracellular Ca21 , elicited by membranedepolarizing agents or by Ca21 ionophore .How may intracellular Ca21 levels regulate N-arachidonoyl PE biosynthesis? Extensive investigations by the laboratory of Schmid and colleagues have shown that formation of other N-acyl PEs is mediated by a Ca21 -dependent N-acyltransferase activity, which transfers a saturated or monounsaturated fatty acyl group from the sn-1 position of phospholipids to the primary amino group of PE . Our results support this general mechanism, and extend it to N-arachidonoyl PE . We have identified and partially characterized a Ca21 – dependent enzyme activity that catalyzes the biosynthesis of N-[14C]arachidonoyl PE, when a phospholipid containing [14C]arachidonate at the sn-1 position is provided as fatty acyl donor. We have also demonstrated that sn-1 arachidonoyl phospholipids are normal, albeit quantitatively minor, components of brain phospholipids. Thus, our results indicate that brain tissue contains the complement of enzymatic activity and lipid substrates necessary for the biosynthesis of N-arachidonoyl PE. While the present study was being drafted, Sugiura et al. reported on the occurrence of a similar enzyme activity and phospholipid substrate in rat brain. Further experiments are necessary to determine whether the N-arachidonoyltransferase activity described in these studies resides in the same enzyme responsible for the biosynthesis of saturated and monounsaturated N-acyl PEs. The discrete tissue localization of N-acyltransferase activity, concentrated in brain and testis, and its relative enrichment in select areas of the CNS, highlight its potential importance in neural signaling. This distribution only partially parallels that of CB1 cannabinoid receptors. In fact, whereas these receptors are densely expressed in cortex, hippocampus, cerebellum, and striatum , they are only sparsely present in the brainstem . A possible explanation for this difference is that anandamide may have additional effects that are not mediated by the activation of any of the known cannabinoid receptor sub-types .

Stimulation of N-acyltransferase activity may account for the Ca21 -dependent increase in N-arachidonoyl PE biosynthesis observed when cortical mixed cultures are exposed to membrane depolarizing agents or Ca21 ionophore . In agreement with this conclusion, we observed that BTNP, a drug that we found to inhibit N-acyltransferase activity in vitro, also prevents ionomycin-induced N-arachidonoyl PE biosynthesis in these cultures.The preceding discussion has focused on the N-acyltransferase pathway as a possible biochemical mechanism for the formation of N-arachidonoyl PE and anandamide, but it is important to note that these lipids represent only a small fraction of the N-acyl PEs and NAEs found in brain. What, if any, are the physiological roles of saturated and monounsaturated N-acyl PEs and NAEs? Although it is not yet possible to provide an adequate answer to this question, several findings indicate that these lipids may be biologically active. For example, N-palmitoylethanolamine was shown to protect cerebellar granule neurons from excitotoxic death and to prevent antigen-induced mast cell activation, possibly by binding to CB2-like cannabinoid receptors . Moreover, N-oleoylethanolamine and N-linoleoylethanolamine were found to inhibit anandamide degradation in vitro, as well as in intact astrocytes in culture , and pharmacological effects of these and other NAEs on cell membrane properties have been reported . These different lines of evidence suggest that the NAEs may constitute a family of lipid signaling molecules, which may serve multiple physiopathological functions in the CNS.Alcohol consumption, particularly heavy use, is prevalent among PWH with rising rates of consumption in older PWH . To date, most studies in older PWH have focused on the combined presence of heavy alcohol use and HIV disease as risk factors for mortality and the development of age-related, multi-system comorbidities . With respect to neurobehavioral health, there is evidence that heavy alcohol use compounds HIV-related neurotoxicity , thereby impairing higher-order neurocognitive abilities critical for daily functioning .

Despite the known adverse neurocognitive effects of heavy alcohol use among older PWH, it is poorly understood whether lower levels of alcohol use similarly increase risk for neurocognitive impairment or, conversely, confer a degree of neuroprotection as has been proposed in prior studies of HIV-seronegative adults . [Note: Definitions of light, moderate and heavy drinking have been arbitrarily characterized across the literature; therefore, we are using “low-risk” henceforth to represent less than heavy alcohol consumption] . The evidence supporting protective effects of alcohol,rolling flood tables suggests an inverted J-shaped association between levels of alcohol consumed and risk for a multitude of diseases , such that there is a higher risk among heavy drinkers and abstainers compared to those with low-risk alcohol consumption . The existing literature examining the association between alcohol consumption and neurocognition among HIV- adults also suggests an inverted Jshaped association, such that low-risk alcohol consumption is associated with better neurocognition than alcohol abstinence, and heavy consumption is associated with the worst neurocognition compared to both no consumption and low-risk consumption . A longitudinal study using the UK Biobank found, among middle and older aged adults, a significant curvilinear association between alcohol consumption and neurocognition. Specifically, neurocognitive performance improved with increased alcohol use, up to one standard drink per day, at which point performance worsened . Results of studies examining this curvilinear association, however, have been inconsistent. Conflicting evidence suggests a positive linear association between neurocognition and alcohol consumption, rather than a curvilinear association . Previous literature suggests that neurocognitive deficits increase with heavier alcohol consumption among older adults . Furthermore, Parsons and Nixon suggest a potential threshold-effect, such that the deleterious effects of alcohol only occur after a specific threshold of consumption ; with heightened effects occurring at heavier levels of alcohol consumption . These inconsistent findings between a curvilinear, linear, and threshold association between alcohol consumption and neurocognition could result from confounding effects of other medical comorbidities, socioeconomic factors, and past alcohol use among current alcohol abstainers, that could contribute more strongly to neurocognitive deficits . The putative multi-system benefits of low-risk alcohol consumption in HIV- individuals have not been systematically investigated among PWH.

Results of earlier studies suggest elevated rates of alcohol use among PWH while more recent reports show similar rates compared to the general population . The majority of alcohol-focused research among PWH has focused on the detrimental effects of heavy drinking or alcohol use disorders . For example, research has consistently shown combined detrimental effects of heavy drinking and HIV disease on neurocognitive function as well as gray and white matter integrity, with the worst outcomes among the heaviest drinkers . Considering that majority of PWH do not report heavier drinking compared to the general population , there is a need for a more comprehensive understanding of the impact of low-risk alcohol consumption among PWH. Examination of whether low-risk drinking exerts differential neurocognitive effects based on HIV serostatus is particularly salient given the increasingly popular recommendations for older adults to follow certain nutritional guidelines . Given that HIV disease can enhance vulnerability to physiological damage from environmental stressors , there may be no level of alcohol associated with better neurocognitive functioning among PWH. Advancing age is independently associated with a higher risk of neurocognitive and neurodegenerative diseases including Alzheimer’s Disease and its precursor mild cognitive impairment . Despite use of combination antiretroviral therapy, older PWH remain particularly vulnerable to HIV-associated neurocognitive impairment and neurodegenerative diseases associated with aging . Considering alcohol consumption is common among PWH, and with advancing age these persons are at a heightened risk for neurocognitive impairment, the present study examined associations between the non-linear effect of recent low-risk alcohol consumption and HIV status on global and domain-specific neurocognitive outcomes. Within the range of low-risk drinking, we hypothesize a curvilinear association between recent alcohol consumption and neurocognition among HIV- individuals, such that intermediate levels of low-risk drinking will be associated with better neurocognitive function compared to non-drinkers and heavier levels; however, we do not expect this curvilinear association among PWH. Participants included 310 PWH and 89 HIV- older adults enrolled in NIH funded research studies at the University of California, San Diego HIV Neurobehavioral Research Program from 2003-2016. Participants were recruited from the greater San Diego area by the HNRP. Regulatory approval was obtained from the University of California San Diego Institutional Review Board prior to the start of protocol implementation. We have previously published several papers using other aspects of these data including medication adherence, age of first alcohol use, and neurocognitive function . The current study represents a secondary analysis of baseline alcohol use and neurobehavioral data from the HNRP. Exclusion criteria for the current analysis included 1) self-reported current or past diagnosis of a psychotic or mood disorder with psychotic features; 2) presence of a neurological condition that could impair neurocognitive function ; 3) positive urine toxicology for illicit drugs or evidence of alcohol intoxication by Breathalyzer test on the day of testing; 4) current diagnosis of AUD; 5) current diagnosis of non-alcohol substance use disorders ; 6) recent “at risk” alcohol consumption as defined per the National Institute on Alcohol Abuse and Alcoholism criteria for “at risk” drinking ; and 7) aged 49 years and younger. The UCSD Institutional Review Board approved this study, and all participants provided written informed consent to participate. Neuromedical Evaluation All participants completed comprehensive medical evaluations and were tested for HIV by enzyme-linked immunosorbent assay . A Western Blot confirmed positive results. Reverse transcriptase-polymerase chain reaction tested levels of HIV viral load in plasma . Psychiatric, Alcohol, and Substance Use Evaluation Current and lifetime mood and substance use disorders were assessed via The Composite International Diagnostic Interview , a fully-structured, computer-based interview . Diagnoses were made in accordance with DSM-IV criteria, as the parent grants from which baseline data were collected were funded before the DSM 5 was published. DSM-IV criteria for alcohol abuse are met when participants report continued alcohol use despite recurring problems . DSM-IV criteria for alcohol dependence are met when participants endorse symptoms of tolerance, withdrawal, and impaired control over drinking . AUD was assigned when DSM-IV criteria for alcohol abuse or dependence was met in order to maintain consistency with DSM 5 criteria and nomenclature.

Caretakers provided informed consent and adolescents provided assent until age 17 and consent thereafter. We restricted analysis to adolescents at ages, as substance use by year was rare at younger ages: 93.9% and 84.5% did not use marijuana or alcohol, respectively, on any occasion between the ages of 7-12. Study procedures were approved by the Institutional Review Boards of the University of Pittsburgh School of Medicine and the Columbia University Mailman School of Public Health. Alcohol and marijuana use were assessed semi-annually by a 16-item Substance Use Scale adapted from the National Youth Survey. Adolescents were queried about timing, quantity, and frequency of alcohol and marijuana use. We defined “marijuana frequency” as the number of occasions of marijuana use in the past year. We defined “alcohol frequency” as the number of occasions of drinking in the past year. We defined “alcohol quantity” as the average number of drinks per occasion in the past year. For phases separated by only 6 months, past-year values were constructed by taking the average of the two semi-annual interviews. Affective, anxiety, and conduct problems were measured with items from the Child Behavior Checklist , Teacher Report Form , Youth Self-Report , and Young Adult Self Report from the Achenbach system of assessment.DSM-oriented problem domains were measured with items rated as very consistent with DSM-IV symptoms of affective disorders, anxiety disorders, and conduct disorder by a group of mental health professionals.The scales were administered to caregivers and teachers from age 7 to 16, and youth from age 10 to 19 .Items were scored as 0 = not true, 1 = somewhat or sometimes true, and 2 = very true or often true .In order to facilitate comparison across informants, total scores for each scale were converted to t-scores based on age- and gender-specific national norms .An average T-score was then calculated for years when multiple informants completed the scales. The average internal consistency coefficients for the caregiver, teacher, and youth depression scales were 0.82, 0.76, and 0.81, respectively. For the anxiety scales,rolling bench the internal consistency coefficients for caregiver, teacher and youth scales were 0.72, 0.73, and 0.67, respectively.

For the conduct disorder scale, the internal consistency coefficients were 0.91, 0.9, and 0.83 for caregiver, teacher, and youth scales, respectively.These scales have been shown to discriminate between clinic referred adolescents with depressive, anxiety, and conduct disorders and non-referred adolescents. All the scales used have previously shown acceptable concurrent and predictive validity in ROC analyses comparing the scales with official records of offense and delinquency or by assessing discrimination between adolescents referred to psychiatric clinics and non-referred adolescents.Several potential time-varying confounding factors were included in the current study to parse out the effect of psychiatric problems from the constellation of time-varying risk factors that could increase both psychiatric problems and substance use. The selection of confounders was based on theory and a review of the literature, as detailed below. “Family factors” included changes in socioeconomic status , assessed yearly by applying the Hollings head Index of Social Status to data provided by the primary caretaker or youth no longer living with family beginning at age 16; changes in parental supervision/involvement, a 43-question scale concerning caretakers’ knowledge of the youths’ whereabouts, the frequency of joint discussions, planning, and activities, and the amount of time that the youth is unsupervised; positive parenting, a scale measuring perception of frequency of positive responses to youth behavior; parental stress, a 14-item scale measuring perceived stress levels and caretakers’ abilities to cope with stress in the previous month 18; and parental use of physical punishment, drawn from a scale that measures parental discipline strategies. “Peer Variables” consisted of changes in youth peer delinquency and peer substance use, a 15-item scale that corresponds to a self-reported delinquency scale.Analyses were conducted in R version 3.0.2 and 3.0.3. Missing data in the covariates were imputed using R package ‘mice’ for “multivariate imputation by chained equations,” an implementation of fully conditional specified models for imputation. The fully conditional approach differs from the more traditional joint modeling approach by specifying a multivariate imputation model on a variable-by-variable basis. This fully conditional approach is used as an alternative to traditional joint modeling when no suitable multivariate distribution can be found. We imputed 20 datasets, and in subsequent analyses used the R package ‘mitools to pool the results of functions run on the 20 data sets using Rubin’s Rules.

We employed quasi-Poisson regression techniques to assess the fixed effects that one-yearlagged changes in psychiatric problems had on subsequent changes in alcohol use frequency/quantity and marijuana use frequency from ages 13 to 19. Quasi-Poisson models are an approach to dealing with over-dispersion, which was apparent in initial Poisson models. They use the mean regression function and the variance function from Poisson generalized linear models but leave the dispersion parameter unrestricted and estimate it from the data. Unlike negative binomial models, the variance is assumed to be a linear function of the mean.This strategy leads to the same coefficient estimates as a standard Poisson model but standard errors are adjusted for over dispersion. Following the “dummy variable method” for fixed effects in Poisson models 41 we included k – 1 dummy variables to represent the sample participants in each model. A series of models were fit sequentially to test the association of each one-year-lagged psychiatric problem domain with each substance use outcome. First, we regressed separately each one year-lagged shift in the average psychiatric problem T-scores on each substance use outcome. Within these models, age-related changes in substance use were controlled for using natural cubic splines. Natural cubic splines are a flexible smoothing approach for non-linear relationships, and are composed of piece wise polynomial functions that split the continuous age variable into separate line segments, each free to have its own shape. Segments are joined by “knots,” which we specified a priori to result in line segments for ages 13-14, 15-16, and 17-19. Slopes are constrained to converge at each knot. Second, we sequentially tested groups of potential confounders. All covariates were back-lagged two years, so that they would be modeled prior to the measurement of the exposure. This ensured that the estimated total effect of change in psychiatric problems on change in substance use included effects mediated through the covariates that occurred contemporaneous to changes in psychiatric problems. In our second set of models, we adjusted for age, SES, substance use variables that were not modeled as the outcome , and measures of psychiatric problems that were not the exposure of interest . In our third and fourth sets of models, we adjusted for age and parenting variables and age and peer variables, respectively.

In our fifth set of models,dry rack cannabis we adjusted for covariates that were significant in models. Third, we tested whether age modified the effect of our exposures by including a product term between exposure and each age spline. Significant effect measure modification was then probed to clarify how the association between psychiatric problems and substance use changed across the age splines. We conducted a sensitivity analysis to establish the directionality of the association between psychiatric problems and substance use. We thus estimated, with linear fixed effects models, the effect that changes in one-year-lagged substance use had on change in psychiatric problem domains in the following year. We followed the same modeling strategy for these models as we did with our primary models. We adjusted for groups of confounders as described above, first adjusting for SES, psychiatric problem domains that were not modeled as the outcome , and measures of substance use that were not the exposure of interest . Next we adjusted for parenting variables and peer variables, respectively. Finally, we adjusted for covariates that were significant in any of the previous groups of confounder models. Covariates were lagged one year prior to the exposure measure , to avoid blocking the causal Table 1 shows mean substance use and psychiatric problem counts over time, as well as demographic characteristics at baseline. The reports of particular informants in our psychiatric problem measures did not influence the associations between psychiatric problems and substance use . Table 2 displays the exponentiated coefficients and confidence intervals of quasiPoisson models, which can be interpreted as rate ratios. Table 2 shows the rate of substance use associated with a one-unit within-subject change in lagged psychiatric problems. Changes in lagged conduct problems were positively associated with changes in marijuana frequency. During years in which adolescents experienced a one-unit increase in conduct problems, the rate at which they smoked marijuana the following year increased 1.03 times : 1.01, 1.05. For a standard deviation change in conduct problems, this is equivalent to a 1.15 times higher rate of marijuana use frequency . The magnitude of this association did not change appreciably after adjusting for potential confounders, including alcohol quantity and frequency, SES, affective and anxiety problems, parenting, and peer deviance. Changes in lagged conduct problems were also associated with changes in alcohol quantity, only after adjusting for peer deviance. During years in which adolescents experienced a one-unit increase in conduct problems, the rate of their average alcohol consumption per occasion the following year increased by 1.01 . For a standard deviation change in conduct problems, this is equivalent to a 1.05 times higher rate of alcohol use . Associations of all covariates with substance use are presented in Appendix C, Table C1. Table 3 presents results for tests of effect measure modification of the association between conduct problems and marijuana frequency and alcohol quantity by age. Because splines are polynomial functions, there is no simple quantitative interpretation of individual effect modification terms; however, the significance of the coefficients implies that the associations between lagged conduct problems and marijuana frequency, and lagged conduct problems and alcohol quantity, differed by age. For ease of interpretation we present these results in Figure 1, which shows the predicted values of substance use outcomes associated with minimum, mean, and third-quartile levels of lagged conduct disorder T-scores, over time. Compared to minimal changes in lagged conduct problems, adolescents with mean or third-quartile levels of change in lagged conduct problems show markedly different marijuana frequency trajectories, which become the most disparate at ages 17-19. Compared to minimal changes in lagged conduct problems, adolescents with mean or third-quartile levels of change in lagged conduct problems show higher alcohol quantity in early adolescence but lower alcohol quantity in later adolescence. The results of our sensitivity analysis are presented in Table 4 and 5, and Figure 2. Table 4 displays the change in psychiatric problems associated with a one-unit change in lagged substance use in the prior year. There was one reverse association: while changes in lagged anxiety problems were not associated with changes in substance use, the opposite did occur: changes in lagged alcohol quantity in the past year were positively associated with changes in anxiety problems. During years in which adolescents experienced a one-unit increase in the average quantity of alcohol consumed when drinking, their anxiety problems T-score increased the following year by 0.12 . For a standard deviation change in average alcohol quantity, this is equivalent to an anxiety T-score increase of 0.3 .Associations of all lagged covariates with psychiatric problems are presented in Appendix C, Table C2. Table 5 presents results for tests of effect measure modification of the association between lagged alcohol quantity and anxiety problems by age, and Figure 2 shows the predicted values of anxiety problem T-scores associated with minimum, mean, and third-quartile levels of lagged alcohol quantity, over time. Adolescents show a decline in anxiety problems throughout adolescence, and little difference by the magnitude of fluctuations in lagged alcohol quantity. However, deviations arose at ages 13-14 and 17-19, where those who exhibited a mean or third-quartile level of increase in lagged alcohol quantity showed slower declines in anxiety problems compared to those who did not increase alcohol intake over time. This study focused on the longitudinal relationship between changes in psychiatric problems and changes in substance use one year later. However, the temporal resolution of this relationship may occur on a much shorter time frame – that is, changes in psychiatric problems may have immediate effects on substance use .