This investigation presents many intriguing findings. Despite the several technical shortcomings of this dataset it is fascinating for the details and tantalizing clues which have been revealed. Importantly most of its major findings have been confirmed previously in other locations particularly in Colorado, Hawaii, Canada, and USA and by professional bodies such as AHA, AAP and CDC lending support to the strength of its principal results [2, 3, 11, 13, 19, 20].
NNSW has higher prevalence rates of the cannabis related anomalies: neural tube defects; small intestinal atresia; body wall defects: exomphalos, gastroschisis, diaphragmatic hernia; the cardiovascular disorders: ASD, VSD, PDA, tetralogy of Fallot, and transposition of the great vessels (TxGrVess); and the genetic disorders: all chromosomal disorders, Downs syndrome, Turners syndrome and trisomy 18. Amongst the defect classes cardiovascular, respiratory, and chromosomal anomalies were elevated. Some of these associations have been previously reported [3, 4, 22] and were seen in our unpublished analyses of US data.
QLD Health data showed that the NNSW CI’s for CRD’s were mostly non-overlapping or were at the extreme end of the QLD CI’s. CRD’s had higher rate ratios than CNRD’s.
Rising rates of cardiovascular, gastrointestinal and respiratory defects, and their first principal component were associated with falling rates of tobacco and alcohol use but rising cannabis use, just as was found in Colorado and USA .
At geospatial and linear regression the cardiovascular defects ASD, VSD, PDA, ToF, TxGrVess; the chromosomal defects ACD, Downs, Turners, Trisomy 13; the body wall defects gastroschisis, exomphalos, diaphragmatic hernia; the GI disorders small intestinal atresia and anal stenosis were all linked with cannabis exposure and for most cannabis exposure was an independent risk factor.
Rising rates of cannabis exposure were more strongly associated with cardiovascular, chromosomal, gastrointestinal and body wall defects than were rising rates of tobacco or alcohol exposure.
Analysis of this dataset by the formal techniques of causal inference analysis including inverse probability weighting and E-Values demonstrated that the described relationships fulfil the criteria for causal relationships.
These results show a striking concordance with epidemiological series from elsewhere. ASD, VSD, ToF, obstructive urinary disorders, hydrocephalus, anal anomalies and Downs syndrome were linked with PCE in a large Hawaiian series . VSD has previously been linked with PCE . Neural tube defects were noted to be elevated in a cannabis-related manner in Canada and Hawaii [4, 11]. ASD, PDA ACD and Downs were seen to rise in close temporal association with increased cannabis use in Colorado . Exomphalos was implicated in animals [23, 24] and in some clinical series including in Queensland . Transposition of the great vessels has previously been linked with paternal PCE . Indeed in Canada total CA’s were linked with increased cannabis use after controlling for income and sociodemographic variables .
Many series implicate PCE in gastroschisis aetiology with a meta-analyzed bivariate O.R.=4.12 (95%C.I. 3.45-4.91) [4, 27-32]. Our findings PR=5.85 (3.54-9.67) contradict those of a 2011 NSW Health report on gastroschisis in this region  which erroneously applied an inflated Bonferroni correction to obviate a significant result. Indeed if the 9 cases reported in NSW  are added to the 16 cases reported in QLD the PR rises further to 9.13 (6.07-13.72).
Increasing reports from diverse sources indicate that the evidence is building that cannabis has significant teratological activities in humans in agreement with animal studies where many severe defects including oedema, exomphalos, phocomelia, spina bifida, myelocoele, exencephaly and foetal loss were documented [23, 24]. Concordant reports from Hawaii, Colorado and Canada suggest that the findings reported herein are indeed valid and are generalizable elsewhere. Given that likely half the NNSW congenital anomalies are reported internally within NSW  this suggests that the teratological situation in NNSW is indeed serious. Moreover some of the CA described here, especially chromosomal defects, are heavily therapeutically aborted antenatally again suggesting that the situation may well be much worse than our description suggests. Our analysis strongly implicates cannabis use as a likely underlying factor.
When one also considers the known epigenetic actions of cannabis [2, 12, 34-37] and its associations with developmental neurological dysfunction and autism [38-42] concerns relating to the intergenerational actions of cannabis are heightened.
From both the present data and from similar international analyses a number of important clinical implications arise. Notwithstanding its popular relatively benign image such analyses indicated not only that the potential teratological impacts of cannabis are significant but that they are likely causal in nature. Patients considering commencing a family should be encouraged to desist from all drugs prior to conception including cannabis. Patients who do fall pregnant and who are consuming cannabis should be encouraged to reduce and cease. Patients wishing to access treatment to assist with such withdrawal should be provided every encouragement and assistance to do so. Patients should be warned that the evidence base for the use of cannabis for most of its touted clinical indications is weak. Patients should be advised to avoid cannabis for morning sickness of pregnancy. Heavy cannabis smokers should be warned that cannabis hyperemesis can mimic hyperemesis gravidarum.
Moreover since the debate relating to cannabis is typically highly individualistic it seems prudent that medical professional organizations should partner with public health agencies and community groups to enlarge the focus of popular debate from the simply self-referential to a broader multigenerational perspective.
One major toxicological conclusion which follows directly from these studies is that access to cannabis should be highly restricted. Indeed such work calls into question the whole issue of the long term advisability of cannabis medicalization / legalization and the sustainability of such paradigms from a teratological perspective.
The present work has not considered neurological sequalae in the newborn and childhood as has previously been reported to overlap the autistic spectrum disorder and ADHD and thereby potentially play a major role in the modern widespread epidemic of these disorders [38-40, 43]. When such data is factored into consideration the imperatives for reconsideration and re-evaluation of cannabis legalization overall are largely increased.
Comparison with Alcohol
It is of interest to summarize and compare some of these results directly between cannabis and alcohol as the latter is a known human foetal teratogen and many learned bodies recommend strongly against tobacco exposure in pregnancy .
Figure 13 is a scatterplot of the frequency of the defect classes compared to the various substances. This Figure shows clearly that increasing cannabis use is associated much more strongly with several classes of congenital anomalies in this dataset than either tobacco or alcohol. The regression lines in this figure slope upwards much more strongly for cannabis for CNS defects, cardiovascular defects and chromosomal defects than for either of the other two substances.
Figures 14-16 perform a similar role for each individual defect by the three substances tobacco, alcohol and cannabis. On the tobacco and alcohol scatterplots most of the regression lines are flat or falling. In contradistinction on the cannabis scatterplot many of the first 32 defects appear to be rising with positive slope. This is quantified in Supplementary Tables 5-7 for cannabis, tobacco and alcohol respectively. The slopes of the first 8 CA’s are significant and seven slopes are positive for cannabis. This compared to tobacco and alcohol where only two and four slopes are significant respectively and all the slopes are negative.
Table 1 presents the remarkable result that of eight additive spatial models cannabis is independently predictive for all eight defects and indeed tobacco and alcohol do not appear in final models. Similarly in Table 3 cannabis is independently predictive for eight of nine defects in additive SARAR spatial models. Alcohol only features in the model for Downs syndrome and its regression coefficient is negative. These differences are compared directly in Table 5, where as noted cannabis is implicated in 46 terms compared to 15 for alcohol and 18 for tobacco. Cannabis is implicated independently in 27 terms compared to five each for tobacco and alcohol.
The overall conclusion then from this detailed comparison must be that cannabis is a relatively more powerful or more potent human teratogen than alcohol.
A classical criticism of correlative studies is that “correlation does not equal causation.” Judea Pearl, one of the leading causal statisticians in the world, has described this criticism as arising from what has been historically the “causalophobic” science of statistics [45, 46]. In relation to the present study the following points should be mentioned. Firstly to observe that an exposure and an outcome are associated not only statistically but also across space carries more weight than a simple statistical association. Secondly inverse probability weighting has been used in mixed effects and robust structural marginal models with very highly significant results. Inverse probability weighting is well established in the literature as transforming an observational study into a pseudo-randomized population from which casual inferences can properly be drawn. Thirdly we have used e-Values to quantify unmeasured confounding as a notorious source of extraneous confounding not controlled by the small number of covariates employed in the present analysis. E-Values provide a quantitative estimate of the degree of association required of any extraneous factor with both the exposure and the outcome to explain away the observed effect. Whilst in the literature e-Values above 1.25 have been stated to be noteworthy  our minimum e-Values ranged up to infinity in mixed effects models, and up to 5.2x10-13 in spatial models. This finding implies both the causal nature of the relationship, and also that the inclusion of further parameters in the model would not obviate the described effects.
Hence our study demonstrates a causal relationship of drug and particularly cannabis exposure to several congenital anomalies. The causal relationship in this case is greatly strengthened by the existence of similar results from other places in the world as described [2-4, 11, 19] and the existence of a plethora of biological and epigenetic processes to account for these effects as mentioned [3, 11-13, 34, 35, 37, 39, 47-51].
It is further noted that the present findings fulfill all of the qualitative and quantitative Hill criteria for causality .
Our study has several strengths and limitations. Its strengths include access to whole population data for Queensland and a significant portion of the NNSW data. The CA rates and confidence intervals were already provided by QLD Health. The NDSHS is a nationally representative survey conducted every three years and the authoritative source for most Australian drug use data. Our analytical strategy combined CA with drug exposure data which is unusual and useful. We have employed a variety of powerful statistical techniques in this investigation including geospatial analysis, inverse probability weighting, mixed models and E-Values. Study limitations relate mainly to the remote location of the NNSW area close to the Queensland border and the small numbers of some anomalies reported. Losses due to treatment within NSW and to stillbirths and prenatal therapeutic abortion occurring preferentially in CA babies implies that the present findings are conservative estimates. The very high CA rate reported in Queensland has not been explained despite formal enquiry. The origin of the NNSW denominator figure is unclear. NSW Mothers and Babies reports  indicate that during 2008-2015 22,084 babies were born in Northern NSW and 30,848 in the central coast region, totalling 52,932 births. These regions are shown together in our maps. Hence over 11 times the data is available as was used in this analysis if it can be properly collated between the two jurisdictions of NSW and Queensland. This would then facilitate geotemporospatial statistical modelling. This proper collation and assembly of data is a top research priority for future studies. The remote location of NNSW together with its somewhat trans-jurisdictional status has apparently made such a collation difficult in the past.