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State Trends of Cannabis Liberalization as a Causal Driver of Increasing Testicular Cancer Rates across the USA

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  • Albert Stuart Reece

    (Division of Psychiatry, University of Western Australia, Crawley, WA 6009, Australia
    School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA 6027, Australia)

  • Gary Kenneth Hulse

    (Division of Psychiatry, University of Western Australia, Crawley, WA 6009, Australia
    School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA 6027, Australia)

Abstract

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 Δ9-tetrahydrocannabinol (THC), cannabinol, cannabigerol, and cannabichromene (6.75 × 10 −9 < p < 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 < 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 > 1.25 ranged up to 1.4 × 10 63 and 10 > 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.

Suggested Citation

  • Albert Stuart Reece & Gary Kenneth Hulse, 2022. "State Trends of Cannabis Liberalization as a Causal Driver of Increasing Testicular Cancer Rates across the USA," IJERPH, MDPI, vol. 19(19), pages 1-37, October.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:19:p:12759-:d:934336
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    References listed on IDEAS

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    1. Etienne Hebert-Chatelain & Tifany Desprez & Román Serrat & Luigi Bellocchio & Edgar Soria-Gomez & Arnau Busquets-Garcia & Antonio Christian Pagano Zottola & Anna Delamarre & Astrid Cannich & Peggy Vin, 2016. "A cannabinoid link between mitochondria and memory," Nature, Nature, vol. 539(7630), pages 555-559, November.
    2. Millo, Giovanni, 2014. "Maximum likelihood estimation of spatially and serially correlated panels with random effects," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 914-933.
    3. Millo, Giovanni & Piras, Gianfranco, 2012. "splm: Spatial Panel Data Models in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 47(i01).
    4. Marco Koch & Luis Varela & Jae Geun Kim & Jung Dae Kim & Francisco Hernández-Nuño & Stephanie E. Simonds & Carlos M. Castorena & Claudia R. Vianna & Joel K. Elmquist & Yury M. Morozov & Pasko Rakic & , 2015. "Hypothalamic POMC neurons promote cannabinoid-induced feeding," Nature, Nature, vol. 519(7541), pages 45-50, March.
    5. van der Wal, Willem M. & Geskus, Ronald B., 2011. "ipw: An R Package for Inverse Probability Weighting," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 43(i13).
    6. Kapoor, Mudit & Kelejian, Harry H. & Prucha, Ingmar R., 2007. "Panel data models with spatially correlated error components," Journal of Econometrics, Elsevier, vol. 140(1), pages 97-130, September.
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    1. Albert Stuart Reece & Gary Kenneth Hulse, 2022. "Epidemiological Patterns of Cannabis- and Substance- Related Congenital Uronephrological Anomalies in Europe: Geospatiotemporal and Causal Inferential Study," IJERPH, MDPI, vol. 19(21), pages 1-61, October.
    2. Albert Stuart Reece & Gary Kenneth Hulse, 2023. "Clinical Epigenomic Explanation of the Epidemiology of Cannabinoid Genotoxicity Manifesting as Transgenerational Teratogenesis, Cancerogenesis and Aging Acceleration," IJERPH, MDPI, vol. 20(4), pages 1-24, February.

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