Socioeconomic, Ethnocultural, Substance- and Cannabinoid- Related Epidemiology of Down Syndrome USA 1986-2016 Dataset: An Ecological Geotemporospatial and Causal Inference Investigation

Published: 04-07-2020| Version 1 | DOI: 10.17632/tn46tdhc4c.1
Albert Reece


Background. Downs syndrome (DS) is the commonest of the congenital genetic defects. Its incidence has been rising in recent years for unknown reasons. Objective. Investigate the relationship of DS to substance- and cannabinoid- exposure; and causality. Methods. Observational ecological population-based epidemiological study 1986-2016. Analysis performed January 2020. Geotemporospatial and causal inference analysis. Participants: Patients were diagnosed with DS and reported to state based registries; collated nationally. Data source: annual reports of National Birth Defects Prevention Network of Centres for Disease Control. Exposures: Drug exposure was taken from the National Survey of Drug Use and Health (NSDUH) conducted annually by Substance Abuse and Mental Health Services Administration. Nationally representative sample 67,000 participants annually. Drug exposures: cigarette consumption, alcohol abuse, analgesic/opioid abuse, cocaine use and last month cannabis use. Ethnicity and median household income: US Census Bureau. Maternal age of childbearing: CDC births registries. Cannabinoid concentrations: Drug Enforcement Agency seizures. Results. NSDUH report 74.1% mean annual response rate. All other data was population-wide. DS rate (DSR) was noted to be rising over time, 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=2.9x10-4). 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=4.7x10-10). In inverse probability-weighted mixed models terms including cannabinoids were significant (from β-estimate=18.82 (16.82, 20.82), P<0.0001). EValues in geospatial models ranged up to infinity. Conclusions. Our 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 causal crietria. Cannabis legalization was associated with elevated DSR’s. These findings are consistent with those from Hawaii, Colorado, Canada and Australia 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 and intergenerational health concerns is prudent.