Co-occurrence across time and space of drug- and cannabinoid- exposure and adverse mental health outcomes in the National Survey of Drug Use and Health: combined geotemporospatial and causal inference analysis

Background: Whilst many studies have linked increased drug and cannabis exposure to adverse mental health (MH) outcomes their effects on whole populations and geotemporospatial relationships are not well understood. Methods Ecological cohort study of National Survey of Drug Use and Health (NSDUH) geographically-linked substate-shapefiles 2010–2012 and 2014–2016 supplemented by five-year US American Community Survey. Drugs: cigarettes, alcohol abuse, last-month cannabis use and last-year cocaine use. MH: any mental illness, major depressive illness, serious mental illness and suicidal thinking. Data analysis: two-stage, geotemporospatial, robust generalized linear regression and causal inference methods in R. Results 410,138 NSDUH respondents. Average response rate 76.7%. When drug and sociodemographic variables were combined in geospatial models significant terms including tobacco, alcohol, cannabis exposure and various ethnicities remained in final models for all four major mental health outcomes. Interactive terms including cannabis were related to any mental illness (β-estimate = 1.97 (95%C.I. 1.56–2.37), P \u3c  2.2 × 10− 16), major depressive episode (β-estimate = 2.03 (1.54–2.52), P = 3.6 × 10− 16), serious mental illness (SMI, β-estimate = 2.04 (1.48–2.60), P = 1.0 × 10− 12), suicidal ideation (β-estimate = 1.99 (1.52–2.47), P \u3c  2.2 × 10− 16) and in each case cannabis alone was significantly associated (from β-estimate = − 3.43 (− 4.46 − −2.42), P = 3.4 × 10− 11) with adverse MH outcomes on complex interactive regression surfaces. Geospatial modelling showed a monotonic upward trajectory of SMI which doubled (3.62 to 7.06%) as cannabis use increased. Extrapolated to whole populations cannabis decriminalization (4.26%, (4.18, 4.34%)), Prevalence Ratio (PR) = 1.035(1.034–1.036), attributable fraction in the exposed (AFE) = 3.28%(3.18–3.37%), P \u3c 10− 300) and legalization (4.75% (4.65, 4.84%), PR = 1.155 (1.153–1.158), AFE = 12.91% (12.72–13.10%), P \u3c 10− 300) were associated with increased SMI vs. illegal status (4.26, (4.18–4.33%)). Conclusions Data show all four indices of mental ill-health track cannabis exposure across space and time and are robust to multivariable adjustment for ethnicity, socioeconomics and other drug use. MH deteriorated with cannabis legalization. Cannabis use-MH data are consistent with causal relationships in the forward direction and include dose-response and temporal-sequential relationships. Together with similar international reports and numerous mechanistic studies preventative action to reduce cannabis use is indicated

What are the characteristics of vitamin D metabolism in opioid dependence? An exploratory longitudinal study in Australian primary care

OBJECTIVE: Compare vitamin D levels in opioid dependence and control population and adjust for relevant confounding effects. Nuclear hormone receptors (including the vitamin D receptor) have been shown to be key transducers and regulators of intracellular metabolism and comprise an important site of pathophysiological immune and metabolic dysregulation potentially contributing towards pro-ageing changes observed in opioid-dependent patients (ODPs). DESIGN: Longitudinal prospective comparing ODPs with general medical controls (GMCs). SETTING: Primary care. PARTICIPANTS: Prospective review comparing 1168 ODP (72.5% men) and 415 GMC (51.6% men, p INTERVENTIONS: Nil. Observational study only. PRIMARY AND SECONDARY OUTCOMES: Serum vitamin D levels and relevant biochemical parameters. RESULTS: Vitamin D levels were higher in the ODP (70.35±1.16 and 57.06±1.81 nmol/L, p CONCLUSION: Vitamin D was higher in ODP in both sexes in bivariate, cross-sectional, cas

Socioeconomic, ethnocultural, substance- and cannabinoid-related epidemiology of down syndrome USA 1986–2016: Combined geotemporospatial and causal inference investigation

Background: Down syndrome (DS) is the commonest of the congenital genetic defects whose incidence has been rising in recent years for unknown reasons. This study aims to assess the impact of substance and cannabinoid use on the DS Rate (DSR) and assess their possible causal involvement. Methods: An observational population-based epidemiological study 1986–2016 was performed utilizing geotemporospatial and causal inferential analysis. Participants included all patients diagnosed with DS and reported to state based registries with data obtained from National Birth Defects Prevention Network of Centers for Disease Control. Drug exposure data was from the National Survey of Drug Use and Health (NSDUH) a nationally representative sample interviewing 67,000 participants annually. Drug exposures assessed were: cigarette consumption, alcohol abuse, analgesic/opioid abuse, cocaine use and last month cannabis use. Covariates included ethnicity and median household income from US Census Bureau; maternal age of childbearing from CDC births registries; and cannabinoid concentrations from Drug Enforcement Agency. Results: NSDUH reports 74.1 % response rate. Other data was population-wide. DSR was noted to rise over time and with cannabis use and cannabis-use quintile. In the optimal geospatial model lagged to four years terms including Δ9-tetrahydrocannabinol and cannabigerol were significant (from β-est. = 4189.96 (95 % C.I. 1924.74, 6455.17), p = 2.9 × 10 − 4). Ethnicity, income, and maternal age covariates were not significant. DSR in states where cannabis was not illegal was higher than elsewhere (β-est. = 2.160 (1.5, 2.82), R.R. = 1.81 (1.51, 2.16), p = 4.7 × 10 − 10). In inverse probability-weighted mixed models terms including cannabinoids were significant (from β-estimate = 18.82 (16.82, 20.82), p \u3c 0.0001). 62 E-value estimates ranged to infinity with median values of 303.98 (IQR 2.50, 2.75 × 107) and 95 % lower bounds ranged to 1.1 × 1071 with median values of 10.92 (IQR 1.82, 7990). Conclusions: Data show that the association between DSR and substance- and cannabinoid- exposure is robust to multivariable geotemporospatial adjustment, implicate particularly cannabigerol and Δ9-tetrahydrocannabinol, and fulfil quantitative epidemiological criteria for causality. Nevertheless, detailed experimental studies would be required to formally demonstrate causality. Cannabis legalization was associated with elevated DSR’s at both bivariate and multivariable analysis. Findings are consistent with those from Hawaii, Colorado, Canada, Australia and Europe and concordant with several cellular mechanisms. Given that the cannabis industry is presently in a rapid growth-commercialization phase the present findings linking cannabis use with megabase scale genotoxicity suggest unrecognized DS risk factors, are of public health importance and suggest that re-focussing the cannabis debate on multigenerational health concerns is prudent

European epidemiological patterns of cannabis- and substance-related congenital neurological anomalies: Geospatiotemporal and causal inferential study

Introduction: Of the many congenital anomalies (CAs) recently linked with community cannabis exposure, arguably the most concerning are neurological CAs (NCAs). We therefore conducted a detailed study of this in fourteen European nations. Methods. Congenital anomaly data were from Eurocat. Drug exposure data were from European Monitoring Centre for Drugs and Drug Addiction. Income from World bank. Results: The Netherlands, Spain, France and Bulgaria reported increasing rates of many NCAs. The NCA rate (NCAR) was: severe microcephaly 2.14 x 1013 higher in nations with increasing daily cannabis use when compared to those without (p = 0.0204, minimum E-value (mEV) = 1.35). At bivariate analysis, the mEVs of the following NCAs were significantly cannabis related, craniosynostosis 5.27 x 1011, nervous system 4.87 x 1011, eye 2.73 x 107, microphthalmos 4.07 x 106, anencephalus 710.37, hydrocephalus 245.64, spina bifida 14.86 and neural tube defects 13.15. At inverse probability, weighted panel regression terms including cannabis were significantly related to the following series of anomalies: nervous system, anencephalus, severe microcephalus, microphthalmos, neural tube defect and spina bifida from p = 5.09 x 10−8, \u3c 2.2 x 10−16, \u3c 2.2 x 10−16, 4.84 x 10−11, \u3c 2.2 x 10−16 and 9.69 x 10−7. At geospatial regression, this same series of anomalies had terms including cannabis significant from p = 0.0027, 1.53 x 10−7, 3.65 x 10−6, 2.13 x 10−8, 0.0002 and 9.76 x 10−12. 88.0% of 50 E-value estimates and 72.0% of mEVs \u3e 9. This analysis therefore demonstrates both close association of cannabis exposure with multiple NCAs across space-time and also fulfills the quantitative criteria of causal inferential analysis. Conclusions: Nine NCARs on bivariate and six NCARs on multivariable regression were cannabis related and fulfilled quantitative epidemiological criteria for causality and are consistent with other series. Particular concerns relate to exponential dose–response effects demonstrated in the laboratory and epidemiological studies. Great caution with community cannabinoid penetration is warranted. Data indicate that cannabis is a significant environmental teratogen and thus imply that cannabinoids should be regulated similarly to the manner in which all other important genotoxins are carefully controlled by communities for their self-sustaining longevity and the protection of generations yet to com

Causal inference multiple imputation investigation of the impact of cannabinoids and other substances on ethnic differentials in US testicular cancer incidence

Background: Ethnic differences in testicular cancer rates (TCRs) are recognized internationally. Cannabis is a known risk factor for testicular cancer (TC) in multiple studies with dose-response effects demonstrated, however the interaction between ancestral and environmental mutagenic effects has not been characterized. We examined the effects of this presumed gene-environment interaction across US states. Methods: State based TCR was downloaded from the Surveillance Epidemiology and End Results (SEER) website via SEERStat. Drug use data for cigarettes, alcohol use disorder, analgesics, cannabis and cocaine was taken from the National Survey of Drug Use and Health a nationally representative study conducted annually by the Substance Abuse and Mental Health Services Administration (SAMHSA) with a 74.1% response rate. Cannabinoid concentrations derived from Drug Enforcement Agency publications. Median household income and ethnicity data (Caucasian-American, African-American, Hispanic-American, Asian-American, American-Indian-Alaska-Native-American, Native-Hawaiian-Pacific-Islander-American) was from the US Census Bureau. Data were processed in R using instrumental regression, causal inference and multiple imputation. Results: 1975–2017 TCR rose 41% in African-Americans and 78.1% in Caucasian-Americans; 2003–2017 TCR rose 36.1% in Hispanic-Americans and 102.9% in Asian-Pacific-Islander-Americans. Ethnicity-based scatterplot-time and boxplots for cannabis use and TCR closely mirrored each other. At inverse probability-weighted interactive robust regression including drugs, income and ethnicity, ethnic THC exposure was the most significant factor and was independently significant (β-estimate = 4.72 (2.04, 7.41), P = 0.0018). In a similar model THC, and cannabigerol were also significant (both β-estimate = 13.87 (6.33, 21.41), P = 0.0017). In additive instrumental models the interaction of ethnic THC exposure with Asian-American, Hispanic-American, and Native-Hawaiian-Pacific-Islander-American ethnicities was significant (β-estimate = − 0.63 (− 0.74, − 0.52), P = 3.6 × 10− 29, β-estimate = − 0.25 (− 0.32, − 0.18), P = 4.2 × 10− 13, β-estimate = − 0.19 (− 0.25, − 0.13), P = 3.4 × 10− 9). After multiple imputation, ethnic THC exposure became more significant (β-estimate = 0.68 (0.62, 0.74), P = 1.80 × 10− 92). 25/33 e-Values \u3e 1.25 ranging up to 1.07 × 105. Liberalization of cannabis laws was linked with higher TCR’s in Caucasian-Americans (β-estimate = 0.09 (0.06, 0.12), P = 6.5 × 10− 10) and African-Americans (β-estimate = 0.22 (0.12, 0.32), P = 4.4 × 10− 5) and when dichotomized to illegal v. others (t = 6.195, P = 1.18 × 10− 9 and t = 4.50, P = 3.33 × 10− 5). Conclusion: Cannabis is shown to be a TC risk factor for all ethnicities including Caucasian-American and African-American ancestries, albeit at different rates. For both ancestries cannabis legalization elevated TCR. Dose-response and causal relationships are demonstrated

State trends of cannabis liberalization as a causal driver of increasing testicular cancer rates across the USA

Background: The cause of the worldwide doubling-tripling of testicular cancer rates (TCRs) in recent decades is unknown. Previous cohort studies associated cannabis use with TCR including dose–response relationships but the contribution of cannabis to TCRs at the population level is unknown. This relationship was tested by analyzing annual trends across US states and formally assessed causality. Four US datasets were linked at state level: age-adjusted TCRs from Centers for Disease Control Surveillance Epidemiology and End Results database; drug use data from annual National Survey of Drug Use and Health including 74.1 % response rate; ethnicity and median household income data from the US Census Bureau; and cannabinoid concentration data from Drug Enforcement Agency reports. Data was processed in R in spatiotemporal and causal inference protocols. Results: Cannabis-use quintile scatterplot-time and boxplots closely paralleled those for TCRs. The highest cannabis-use quintile had a higher TCR than others (3.44 ± 0.05 vs. 2.91 ± 0.2, mean ± S.E.M., t = 10.68, p = 1.29 × 10 − 22). A dose–response relationship was seen between TCR and Δ 9-tetrahydrocannabinol (THC), cannabinol, cannabigerol, and cannabichromene (6.75 × 10 − 9 \u3c p \u3c 1.83 × 10 − 142). In a multivariate inverse probability-weighted interactive regression including race and ethnic cannabis exposure (ECE), ECE was significantly related to TCR (β-estimate = 0.89 (95 % C.I. 0.36, 2.67), p \u3c 2.2 × 10 − 16). In an additive geospatiotemporal model controlling for other drugs, cannabis alone was significant (β-estimate = 0.19 (0.10, 0.28), p = 3.4 × 10 − 5). In a full geospatial model including drugs, income and ethnicity cannabinoid exposure was significant (cannabigerol: β-estimate = 1.39 (0.024, 2.53), p = 0.0017); a pattern repeated at two spatial and two temporal lags (cannabigerol: β-estimate = 0.71 (0.05, 1.37), p = 0.0.0350; THC: β-estimate = 23.60 (11.92, 35.29), p = 7.5 × 10 – 5). 40/41 e-Values \u3e 1.25 ranged up to 1.4 × 1063 and 10 \u3e 1000 fitting causal relationship criteria. Cannabis liberalization was associated with higher TCRs (ChiSqu. = 312.2, p = 2.64 × 10 − 11). Rates of TC in cannabis-legal states were elevated (3.36 ± 0.09 vs. 3.01 ± 0.03, t = 4.69, p = 4.86 × 10 − 5). Conclusions: Cannabis use is closely and causally associated with TCRs across both time and space and higher in States with liberal cannabis legislation. Strong dose–response effects were demonstrated for THC, cannabigerol, cannabinol, cannabichromene and cannabidiol. Cannabinoid genotoxicity replicates all major steps to testicular carcinogenesis including whole-genome doubling, chromosomal arm excision, generalized DNA demethylation and chromosomal translocations thereby accelerating the pathway to testicular carcinogenesis by several decades

Geotemporospatial and causal inferential epidemiological overview and survey of USA cannabis, cannabidiol and cannabinoid genotoxicity expressed in cancer incidence 2003–2017: part 2 – categorical bivariate analysis and attributable fractions

Background: As the cannabis-cancer relationship remains an important open question epidemiological investigation is warranted to calculate key metrics including Rate Ratios (RR), Attributable Fractions in the Exposed (AFE) and Population Attributable Risks (PAR) to directly compare the implicated case burden between emerging cannabinoids and the established carcinogen tobacco. Methods: SEER*Stat software from Centres for Disease Control was used to access age-standardized state census incidence of 28 cancer types (including “All (non-skin) Cancer”) from National Cancer Institute in US states 2001–2017. Drug exposures taken from the National Survey of Drug Use and Health 2003–2017, response rate 74.1%. Federal seizure data provided cannabinoid exposure. US Census Bureau furnished income and ethnicity. Exposure dichotomized as highest v. lowest exposure quintiles. Data processed in R. Results: Nineteen thousand eight hundred seventy-seven age-standardized cancer rates were returned. Based on these rates and state populations this equated to 51,623,922 cancer cases over an aggregated population 2003–2017 of 124,896,418,350. Fifteen cancers displayed elevated E-Values in the highest compared to the lowest quintiles of cannabidiol exposure, namely (in order): prostate, melanoma, Kaposi sarcoma, ovarian, bladder, colorectal, stomach, Hodgkins, esophagus, Non-Hodgkins lymphoma, All cancer, brain, lung, CLL and breast. Eleven cancers were elevated in the highest THC exposure quintile: melanoma, thyroid, liver, AML, ALL, pancreas, myeloma, CML, breast, oropharynx and stomach. Twelve cancers were elevated in the highest tobacco quintile confirming extant knowledge and study methodology. For cannabidiol RR declined from 1.397 (95%C.I. 1.392, 1.402), AFE declined from 28.40% (28.14, 28.66%), PAR declined from 15.3% (15.1, 15.5%) and minimum E-Values declined from 2.13. For THC RR declined from 2.166 (95%C.I. 2.153, 2.180), AFE declined from 53.8% (53.5, 54.1%); PAR declined from 36.1% (35.9, 36.4%) and minimum E-Values declined from 3.72. For tobacco, THC and cannabidiol based on AFE this implies an excess of 93,860, 91,677 and 48,510 cases; based on PAR data imply an excess of 36,450, 55,780 and 14,819 cases. Conclusion: Data implicate 23/28 cancers as being linked with THC or cannabidiol exposure with epidemiologically-causal relationships comparable to those for tobacco. AFE-attributable cases for cannabinoids (91,677 and 48,510) compare with PAR-attributable cases for tobacco (36,450). Cannabinoids constitute an important multivalent community carcinogen

Epigenomic and other evidence for cannabis-induced aging contextualized in a synthetic epidemiologic overview of cannabinoid-related teratogenesis and cannabinoid-related carcinogenesis

Background: Twelve separate streams of empirical data make a strong case for cannabis-induced accelerated aging including hormonal, mitochondriopathic, cardiovascular, hepatotoxic, immunological, genotoxic, epigenotoxic, disruption of chromosomal physiology, congenital anomalies, cancers including inheritable tumorigenesis, telomerase inhibition and elevated mortality. Methods: Results from a recently published longitudinal epigenomic screen were analyzed with regard to the results of recent large epidemiological studies of the causal impacts of cannabis. We also integrate theoretical syntheses with prior studies into these combined epigenomic and epidemiological results. Results: Cannabis dependence not only recapitulates many of the key features of aging, but is characterized by both age-defining and age-generating illnesses including immunomodulation, hepatic inflammation, many psychiatric syndromes with a neuroinflammatory basis, genotoxicity and epigenotoxicity. DNA breaks, chromosomal breakage-fusion-bridge morphologies and likely cycles, and altered intergenerational DNA methylation and disruption of both the histone and tubulin codes in the context of increased clinical congenital anomalies, cancers and heritable tumors imply widespread disruption of the genome and epigenome. Modern epigenomic clocks indicate that, in cannabis-dependent patients, cannabis advances cellular DNA methylation age by 25 – 30 % at age 30 years. Data have implications not only for somatic but also stem cell and germ line tissues including post-fertilization zygotes. This effect is likely increases with the square of chronological age. Conclusion: Recent epigenomic studies of cannabis exposure provide many explanations for the broad spectrum of cannabis-related teratogenicity and carcinogenicity and appear to account for many epidemiologically observed findings. Further research is indicated on the role of cannabinoids in the aging process both developmentally and longitudinally, from stem cell to germ cell to blastocystoids to embryoid bodies and beyond

Contemporary epidemiology of rising atrial septal defect trends across USA 1991–2016: A combined ecological geospatiotemporal and causal inferential study

© 2020, The Author(s). Background: Cardiovascular anomalies are the largest group of congenital anomalies and the major cause of death in young children, with various data linking rising atrial septal defect incidence (ASDI) with prenatal cannabis exposure. Objectives / Hypotheses. Is cannabis associated with ASDI in USA? Is this relationship causal? Methods: Geospatiotemporal cohort study, 1991–2016. Census populations of adults, babies, congenital anomalies, income and ethnicity. Drug exposure data on cigarettes, alcohol abuse, past month cannabis use, analgesia abuse and cocaine taken from National Survey of Drug Use and Health (78.9% response rate). Cannabinoid concentrations from Drug Enforcement Agency. Inverse probability weighted (ipw) regressions. Analysis conducted in R. Results: ASDI rose nationally three-fold from 27.4 to 82.8 / 10,000 births 1991–2014 during a period when tobacco and alcohol abuse were falling but cannabis was rising. States including Nevada, Kentucky, Mississippi and Tennessee had steeply rising epidemics (Time: Status β-estimate = 10.72 (95%C.I. 8.39–13.05), P \u3c 2.0 × 10 − 16). ASDI was positively related to exposure to cannabis and most cannabinoids. Drug exposure data was near-complete from 2006 thus restricting spatial modelling from 2006 to 2014, N = 282. In geospatial regression models cannabis: alcohol abuse term was significant (β-estimate = 19.44 (9.11, 29.77), P = 2.2 × 10 − 4); no ethnic or income factors survived model reduction. Cannabis legalization was associated with a higher ASDI (Time: Status β-estimate = 0.03 (0.01, 0.05), P = 1.1 × 10 -3). Weighted panel regression interactive terms including cannabis significant (from β-estimate = 1418, (1080.6, 1755.4), P = 7.3 × 10 -15). Robust generalized linear models utilizing inverse probability weighting interactive terms including cannabis appear (from β-estimate = 78.88, (64.38, 93.38), P = 1.1 × 10 -8). Marginal structural models with machine-aided SuperLearning association of ASDI with high v. low cannabis exposure R.R. = 1.32 (1.28, 1.36). Model e-values mostly \u3e 1.5. Conclusions: ASDI is associated with cannabis use, frequency, intensity and legalization in a spatiotemporally significant manner, robust to socioeconomicodemographic adjustment and fulfilled causal criteria, consistent with multiple biological mechanisms and similar reports from Hawaii, Colorado, Canada and Australia. Not only are these results of concern in themselves, but they further imply that our list of the congenital teratology of cannabis is as yet incomplete, and highlight in particular cardiovascular toxicology of prenatal cannabinoid and drug exposure

Epidemiological association of cannabinoid- and drug- exposures and sociodemographic factors with limb reduction defects across USA 1989–2016: A geotemporospatial study

Background: Reports of major limb defects after prenatal cannabis exposure (PCE) in animals and of human populations in Hawaii, Europe and Australia raise the question of whether the increasing use of cannabis in USA might be spatiotemporally associated with limb reduction rates (LRR) across USA. Methods: Congenital anomaly data was from the National Birth Defects Prevention Network, drug use data was taken from the National Survey of Drug Use and Health (NSDUH), cannabinoid concentration was estimated from Federal seizure data and ethnicity and income data were from the US Census bureau. Geotemporospatial analysis was conducted in R. Results: 436 LRR datapoints were obtained. LRR was significantly associated with cannabis use and tetrahydrocannabinol (THC) exposure and demonstrated prominent cannabis-use quintile effects. A sharp increase in LRR occurred from the fourth to fifth quintiles of cannabis exposure (mean ± S.E.M 3.78 ± 0.38 to 6.66 ± 0.56/10,000 live births, P = 5.22 × 10−9). In final lagged geospatial models adjusted for ethnicity and income interactive terms including cannabinoids were highly significant and robust to adjustment. States in which cannabis was not legalized had a lower LRR (4.28 v 5.01/10,000 live births, relative risk reduction = −0.15, (95%C.I. −0.25, −0.02), P = 0.021). Internationally 37–63% of cases are estimated to not be born alive. Their inclusion in these analyzes uniformly intensified the identified effects and the significance of the effect of the cannabis legalization paradigm rose from P = 0.0256 to P = 0.0146 to P = 0.0048 with silent factors of 0%, 36% and 63%, respectively. Conclusion: Therefore a spatiotemporal and dose-dependent association between several cannabinoids including THC and cannabigerol and LRR is reported, is robust to adjustment, is consistent with pathophysiological and preclinical studies, accords with findings elsewhere, is markedly exacerbated in higher exposure quintiles, is exacerbated by cannabis legalization and evidences dose-related intergenerational sequaelae