Geotemporospatial and causal inference epidemiological analysis of US survey and overview of cannabis, cannabidiol and cannabinoid genotoxicity in relation to congenital anomalies 2001–2015
verfasst von:
Albert Stuart Reece, Gary Kenneth Hulse
Cannabinoids including cannabidiol have recognized genotoxic activities but their significance has not been studied broadly epidemiologically across the teratological spectrum. We examined these issues including contextual space-time relationships and formal causal inferential analysis in USA.
Methods
State congenital anomaly (CA) rate (CAR) data was taken from the annual reports of the National Birth Defects Prevention Network 2001–2005 to 2011–2015. Substance abuse rates were from the National Survey of Drug Use and Health a nationally representative longitudinal survey of the non-institutionalized US population with 74.1% response rate. Drugs examined were cigarettes, monthly and binge alcohol, monthly cannabis and analgesic and cocaine abuse. Early termination of pregnancy for abortion (ETOPFA) rates were taken from the published literature. Cannabinoid concentrations were from Drug Enforcement Agency. Ethnicity and income data were from the US Census Bureau. Inverse probability weighted (IPW) regressions and geotemporospatial regressions conducted for selected CAs.
Results
Data on 18,328,529 births from an aggregated population of 2,377,483,589 for mid-year analyses 2005–2013 comprehending 12,611 CARs for 62 CAs was assembled and ETOPFA-corrected (ETOPFACAR) where appropriate. E-Values for ETOPFACARs by substance trends were elevated for THC (40 CAs), cannabis (35 CAs), tobacco (11 CAs), cannabidiol (8 CAs), monthly alcohol (5 CAs) and binge alcohol (2 CAs) with minimum E-Values descending from 16.55, 1.55x107, 555.10, 7.53x1019, 9.30 and 32.98. Cardiovascular, gastrointestinal, chromosomal, limb reductions, urinary, face and body wall CAs particularly affected. Highest v. lowest substance use quintile CAR prevalence ratios 2.84 (95%C.I. 2.44, 3.31), 4.85 (4.08, 5.77) and 1.92 (1.63, 2.27) and attributable fraction in exposed 0.28 (0.27, 0.28), 0.57 (0.51, 0.62) and 0.47 (0.38, 0.55) for tobacco, cannabis and cannabidiol. Small intestinal stenosis or atresia and obstructive genitourinary defect were studied in detail in lagged IPW pseudo-randomized causal regressions and spatiotemporal models confirmed the causal role of cannabinoids. Spatiotemporal predictive modelling demonstrated strongly sigmoidal non-linear cannabidiol dose-response power-function relationships (P = 2.83x10−60 and 1.61x10−71 respectively).
Conclusions
Data implicate cannabinoids including cannabidiol in a diverse spectrum of heritable CAs. Sigmoidal non-linear dose-response relationships are of grave concern.
These transgenerational genotoxic, epigenotoxic, chromosomal-toxic putatively causal teratogenic effects strongly indicate tight restrictions on community cannabinoid penetration.
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Abkürzungen
AFE
Attributable fraction in the exposed
BMP
Bone morphogenetic proteins
CA
Congenital anomaly
CBC
Cannabichromene
CBD
Cannabidiol
CBG
Cannabigerol
CBN
Cannabinol
CDC
Centers for disease control, Atlanta, Georgia
cGAS
Cyclic GMP-AMP Synthase
Dbx
Double homeobox
DEA
Drug enforcement agency
ETOPFA
Early termination of pregnancy for anomaly
ETOPFACAR
Early termination of pregnancy for anomaly -adjusted congenital anomaly rate
E-Value
Expected value
FVV
Fitted values
FGF
Fibroblast growth factor
Fox
Forkhead box
GAM
Generalized additive model
Gli1
Glioma-associated protein 1
IPW
Inverse probability weighting
NBDPN
National birth defects prevention network
Nkx
Homeobox protein Nkx
NSDUH
National survey of drug use and health
OGUD
Obstructive genitourinary defect
OLS
Ordinary least squares
PAR
Population attributable risk
Pax
Paired box
plm
Panel linear model
PR
Prevalence ratio
RDAS
Restricted-use data analysis system
re
Random effects
SAMHDA
Substance use and mental health data archive
SAMHSA
Substance abuse and mental health services administration
sem
Spatial error method
semsrre
Spatial error method, serial autocorrelation and random effects
sf
Simple features (Package in R)
SISA
Small intestinal stenosis and atresia
Shh
Sonic hedgehog
splm
Spatial panel linear model
spreml
Spatial panel random effects maximum likelihood
SPDSST
Spatial panel dataset in space-time
sr
Serial correlation
STING
Stimulator of interferon genes
THC
Δ9-Tetrahydrocannabinol
VEGFA
Vascular endothelial growth factor A
Background
Both “Epidiolex” (cannabidiol) registered in the USA by the Food and Drug Administration (FDA) and Sativex (Δ9-tetrahydrocannabinol (THC) - cannabidiol) registered by the Medicines and Healthcare Products Regulatory Authority (MHRA) of the United Kingdom carry strong warnings on their Product Information and Prescribers Information leaflets against their use in pregnancy and breast feeding which is the standard warning for genotoxic effects which routinely accompanies medicines including cytotoxic and cancer agents [1, 2]. Similar warnings occur on the labelling of “Hemp Oil” which is made freely accessible to the Australian public on supermarket shelves. Such overt warnings relating to acknowledged genotoxicity by the distributors and marketers of cannabinoids, and mandated warnings required by official drug regulators on both sides of the Atlantic directly imply that the genotoxicity of these agents is acknowledged in laboratory and preclinical studies and is in truth an established fact of science.
Paradoxically what might be termed the “standard” or “establishment” view of the risks posed by the use of cannabinoid products in pregnancy is relatively benign. Major authorities and several smaller convenience sample series claim that the use of cannabis in pregnancy is associated with increased prematurity, smaller head circumference, increased small for gestational age, low birth weight and relative infertility in male and female users [3‐5]. This view which enjoys widespread currency in the medical profession, is clearly at odds with the official governmental view endorsed in the requirements on registered product information for the medical profession and consumers, but is nevertheless typical of the community-wide confusion relating to much of the information on cannabis and cannabinoids.
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A broader and more concerning view on cannabinoid teratogenicity is expressed by other authorities including the Centres for Disease Control (CDC) Atlanta, Georgia, the American Heart Association (AHA) and the American Academy of Paediatrics (AAP) who have together warned of increased rates of six birth defects after prenatal cannabis exposure including ventricular septal defect, Epsteins anomaly, gastroschisis, diaphragmatic hernia, oesophageal atresia with or without tracheoesophageal fistula and anencephalus [6‐8]. The American College of Obstetricians and Gynaecologists (ACOG) strongly warn against the use of cannabis products in pregnancy [9]. Longitudinal studies of neurological and psychomotor development in prenatally exposed children conducted in Pittsburgh, Toronto and Netherlands uniformly indicate worrying levels of autism-like and ADHD-like features with altered neurological development and impairments of emotional development, motor tone and fine motor skills and cortical executive and visuospatial processing [10].
The most useful experimental animal models in which to study the effects of prenatal drug exposure are New Zealand white rabbits and hamsters. Classical studies from 1969 performed in rodents and hamsters showed a variety of defects including limb reduction, exencephaly, spina bifida, omphalocele, multiple malformations and myelocoele [11, 12]. As was noted at the time “this is a formidable list” [12]. However clinical confirmation of such a concerning and wide-ranging spectrum of congenital anomalies was mostly lacking. In 2007 a novel report from Hawaii listed 21 birth defects as being elevated after prenatal cannabis exposure, particularly affecting the cardiovascular, gastrointestinal, urinary and chromosomal systems and including arm defects, syndactyly and polydactyly however this study remained very much an exception and outlier for many years [13].
In an historical case series of illicit poly-drugs users from Washington DC 148 pregnancies amongst 140 women produced 12 embryos or infants with major congenital abnormalities, 43% had spontaneous first trimester abortions and four of eight serial pregnancies produced infants or embryos with major abnormalities [14]. The major congenital anomaly rate was a calculated by the authors at 96/1000 live births or 16 times the then control rate in USA in 1972 [14]. The usually quoted rate for spontaneous abortions at that time in USA was up to 20%. Of the eight infants whose major congenital anomaly was listed six had neural tube closure defects (meningomyelocele, myelocele, spina bifida or hydrocephalus), one had a cardiovascular defect (Tetralogy of Fallot), one had neuroblastoma and one had limb abnormalities (absent feet, absent finger and absent phalanges from fingers). All patients smoked cannabis [14, 15].
A report on atrial septal defect secundum type from the CDC database showing much higher rates and a steep acceleration of the rate of increase of atrial septal defect in high cannabis use states in the USA in recent years appeared which carried two major corollaries [16]. Firstly it implied that the list of cardiovascular anomalies jointly proposed by the AAP and AHA was incomplete. Secondly it implied that our knowledge of the subject of clinical cannabinoid teratogenesis including the list of cannabis-related congenital anomalies was similarly incomplete.
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The concerning Hawaiian study has since been supported by studies from other locations. Confirmation of the experimentally identified spina bifida and encephalocele findings recently came from an analysis of Canadian data [17]. Indeed total congenital anomalies, particularly including cardiovascular defects and chromosomal anomalies were recently noted to be three times higher in the northern Territories of Canada which traditionally smoke two to three times as much cannabis as Canadians living in the south [18]. An Australian report showed that 18 congenital defects were higher in high cannabis using parts of Northern New South Wales [19]. Colorado was noted to have a 29% jump in the expected rate of total birth defects across the period of cannabis legalization 2000–2013 and included particularly cardiovascular, central nervous system, genitourinary, musculoskeletal and chromosomal CAs [20].
Cannabinoids including cannabidiol have been implicated in direct damage by oxidation to DNA bases which is a major genotoxic and mutagenic lesion [21]. They have long been known to be toxic to chromosomes which are the natural way in which DNA is packaged inside the cell nucleus [22]. It was shown long ago that cannabinoids reduce the synthesis of the major molecules of biology DNA, RNA proteins and histones [23‐34]. Such gross level changes necessarily impact the genomic code. Translated into a twenty-first century understanding this would imply major interference in the epigenetic code where genome accessibility, controlled by histone modifications, the formation of euchromatin and the assembly of topologically organized transcriptionally active domains (the chromosomal “A compartment”) within the nucleus constitutes a major portion of normal gene regulation, cell function and indeed epigenetic cell specification and lineage determination [35]. And it has been well established that cannabinoids carry a heavy epigenetic footprint which is inheritable for several subsequent generations [35‐41].
As was recently observed chromosomal toxicity, genotoxic and epigenotoxic lesions can reasonably be expected to manifest in congenital anomaly profiles and patterns of cancerogenesis [42]. What is clearly lacking in the literature is a genotoxic survey of a national teratological database to study the issue of patterns of teratogenesis as they relate to substance exposure. The application of the formal techniques of geospatial analysis and causal inferential analysis to the whole database tracked by CDC of 62 birth defects is a massive task which can only be commenced in this forum. It is therefore our purpose in the present paper to present an overview and introduction to this topic with a few teratological case examples to illustrate the way in which such studies can be extended and the power of these analytical techniques. Formal treatment of the whole field must be left for another occasion. Since the required teratological and substance exposure and related data is available for USA that nation has been chosen for the present investigation.
As has been pointedly observed it is vitally important in any review of teratological epidemiology to consider the impact of early termination of pregnancy for anomalies (ETOPFA) [43, 44]. Our study provides estimates of these ETOPFA practices which are used to complete applicable datasets for affected congenital anomalies (CAs).
Given the rapid increase in the penetration of cannabis and cannabinoids into modern American society, all studies related to cannabinoid teratogenesis and cannabinoid genotoxicity must be regarded as urgent and of high priority in the national research agenda.
A related concern is the potential for cannabinoids to enter the food chain. Cases of babies born without limbs have been noted in France and Germany where cannabis has become widely available [45‐50] however this has not been seen in nearby Switzerland where its entry into the food chain is not permitted. Rapid introduction of cannabis into Colorado recently was associated with a 29% jump in total congenital anomalies [20] and Kentucky saw a massive and sharp spike in the incidence of atrial septal defect in recent years as cannabis has increasingly replaced tobacco as a major cash crop [16].
Not since Distillers unleashed thalidomide on the global market in 1957 has an agent which is known to be genotoxic been aggressively marketed for commercial reasons [51]. Of note the thalidomide debacle was avoided in the USA primarily because of genotoxic concerns [52, 53]. This international tragedy of recent history is also the foundational reason for the development of the modern drug regulatory scheme in many nations [53].
Aside from the fact of cannabis mutagenicity and genotoxicity itself one of the aspects of this subject which we find of most concern is the clear replication in many predictive geotemporospatial models of a sigmoidal relationship between cannabidiol and cannabinoid exposure and teratogenic outcomes for many congenital anomalies which is clearly highly reminiscent of the exponential dose-response relationships observed in numerous in vitro studies of cannabinoid genotoxicity and mitochondriopathy-epigenotoxicity [24, 26, 31, 54‐65]. It is the non-linear power function of dose-response between increased cannabinoid exposure and teratological outcomes which must be of particular concern to any community moving into a higher cannabinoid exposure zone. Equally of concern an exponential relationship was observed in both actual and predicted modelled trend studies of the relationship between cannabinoid exposure and US autism incidence [66]. Taken together such findings imply exponentiation both of major neurotoxic and major genotoxic developmental outcomes.
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It is self-evident that with the endocannabinoids playing critical roles in many body systems drugs modulating the endocannabinoid system will increasingly enter the international therapeutic marketplace in the coming years. We also feel that in order to assist cannabinoid therapeutics to find their appropriate niche in the global market that a proper understanding and appreciation of their long term neurotoxic and genotoxic activities is an absolute requirement both for regulators and for the public at large so that intergenerational community safety continues to be prioritized as a central and principal concern.
The overall purpose of the present analysis was to investigate substance and particularly cannabinoid exposure as a putative environmental risk factor for the observed spectrum of congenital anomalies. This was done directly using ecological USA data in bivariate analysis of continuous covariates. Key epidemiological parameters of public health interest such as the prevalence ratio, the aetiological fraction in the exposed and the population attributable risk were calculated from an analysis of categorized data. Detailed multivariable regression was undertaken using inverse probability weighted mixed effects, robust and panel regression for two selected CAs and spatiotemporal regression was also conducted for these CAs. Extensive use of the formal techniques of causal inference namely E-Values and inverse probability weighting was engaged to correct for the ecological fallacy and convert data into a pseudo-randomized quasi-experimental design. Finally predictive mathematical modelling was conducted to study overall trends of selected CAs as a function of cannabinoid exposure.
The minimum E-Value indicates the minimum strength of association required of some extraneous confounder covariate with both the outcome of interest and the exposure of concern to explain an observed assocation [67‐69]. It plays a central role in formal epidemiological assignment of causal relationships.
An overview and survey of a geospatial consideration of the field of genotoxicity manifested as cancerogenesis is the subject of a series of companion papers.
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Methods
Data
Rates of birth defects were taken from the annual reports of the National Birth Defects Prevention Network (NBDPN) 2001–2005 to 2011–2015 which is coordinated from the Centres for Disease Control (CDC), Atlanta, Georgia. For the purposes of conducting the analysis the nominal year of the report was taken as the temporal midpoint of the year of the report. Hence for the most recent report we used which was 2011–2015 [70] the nominal year for analysis was 2013. We analyzed all the major CAs collected long term by NBDPN across this period totally 62 CAs. This was joined with annual USA state based drug use cross-tabulation data from the National Survey of Drug Use and Health (NSDUH) Substance Use and Mental Health Data Archive (SAMHDA) Restricted-Use Data Analysis System (RDAS) maintained by the Substance Abuse and Mental Health Services Administration (SAMHSA) [71]. The drugs of interest were last month cigarette use, last month alcohol use, last year binge alcohol use, last year non-medical use of opioid analgesia (Analgesics), last month use of cannabis and last year use of cocaine. Substance exposure was also considered as a categorical variable. This was facilitated by establishing substance exposure quintiles for each year with the first quintile representing the lowest exposure and the fifth quintile the highest exposure. The cannabinoid concentration in Federal cannabis seizures was taken from published reports of the Drug Enforcement agency [72‐74]. Estimates of state level cannabinoid exposure was derived by multiplying the last month cannabis use rates by the Federal cannabinoid concentration. Quintiles for cannabinoid exposure were calculated across the whole period as a single group.
Some CAs and those particularly affecting chromosomal defects are heavily impacted by ETOPFA practice. The final ETOPFA rate by anomaly was arrived at as a composite synthesis of several published ETOPFA rates [75‐82]. Moreover, as defined in at least one longitudinal annual time series of ETOPFA rates it seems highly likely that the ETOPFA rate has been incrementally increasing over time [83]. In the longitudinal time series the ETOPFA rate for Downs syndrome rose from low levels in 1980 to 70% in 2014. This approximately linear rate of rise has been projected across all CAs according to the following formula:
where ETOPFA_Rate represents the adjusted CA rate, the Reported_Rate is the gazetted rate reported by NBDPN, the Composite rate is the composite rate derived from literature review shown in Table 1 and the FMaxTR is the Fraction of the Maximal Termination Rate in the year in question given in Supplementary Table 1 which is a tabular representation of graphical data taken from the only longitudinal series of ETOPFAs in the world we were able to identify [83].
Table 1
Regression Slopes for ETOPFA-Corrected Congenital Anomaly Rates by Cigarette Exposure
Parameters
Model
E-Values
Congenital Anomaly
Term
Estimate
Std.Error
t-Value
P_Value
Adj.R.Squared
S.D.
t-Statistic
P-Value
E-Value - Point
E-Value - Lower
Atrial septal defect
Cigarettes
461.4473
80.9277
5.7020
2.98E-08
0.0999
49.0262
32.5125
2.98E-08
10,490.78
555.10
Common truncus (truncus arteriosus)
Cigarettes
10.0328
1.8075
5.5506
6.33E-08
0.0912
1.0985
30.8095
6.33E-08
8137.59
434.55
Pyloric stenosis
Cigarettes
108.3707
29.4229
3.6832
0.0004
0.1025
9.7747
13.5660
0.0004
48,155.03
226.33
Tetralogy of Fallot
Cigarettes
8.6017
2.5730
3.3431
0.0009
0.0319
1.5895
11.1763
0.0009
274.78
14.91
Diaphragmatic hernia
Cigarettes
6.1187
1.9038
3.2139
0.0015
0.0306
1.1633
10.3291
0.0015
239.26
12.50
Double outlet right ventricle
Cigarettes
5.8943
2.1948
2.6856
0.0080
0.0369
1.0114
7.2122
0.0080
401.58
7.91
Rectal and large intestinal atresia/stenosis
Cigarettes
5.9460
2.2635
2.6269
0.0091
0.0198
1.3888
6.9008
0.0091
97.91
4.85
Dextro-transposition of great arteries (d-TGA)
Cigarettes
5.1147
2.1421
2.3877
0.0180
0.0260
1.0324
5.7011
0.0180
181.05
3.95
Transposition of great arteries
Cigarettes
5.8459
2.5671
2.2773
0.0235
0.0138
1.5155
5.1859
0.0235
66.41
2.67
Hypoplastic left heart syndrome
Cigarettes
4.7634
2.3941
1.9897
0.0475
0.0095
1.4718
3.9588
0.0475
37.52
1.28
Holoprosencephaly
Cigarettes
44.6731
22.6580
1.9716
0.0506
0.0195
10.1998
3.8873
0.0506
107.14
1.21
Cloacal exstrophy
Cigarettes
13.4134
7.0820
1.8940
0.0608
0.0220
2.7748
3.5873
0.0608
162.22
1.00
Ventricular septal defect
Cigarettes
64.3023
34.2374
1.8781
0.0614
0.0088
20.1650
3.5274
0.0614
35.91
1.00
Hydrocephalus without spina bifida
Cigarettes
21.5055
12.6853
1.6953
0.0926
0.0153
4.5872
2.8741
0.0926
142.01
1.00
Hypospadias
Cigarettes
58.5925
40.8897
1.4329
0.1530
0.0038
24.2028
2.0533
0.1530
17.59
1.00
Bladder exstrophy
Cigarettes
0.3683
0.2706
1.3607
0.1747
0.0031
0.1604
1.8515
0.1747
15.63
1.00
Biliary atresia
Cigarettes
0.8244
0.7004
1.1770
0.2402
0.0014
0.4223
1.3853
0.2402
11.30
1.00
Hirschsprung disease (congenital megacolon)
Cigarettes
5.2534
4.4871
1.1708
0.2441
0.0032
1.5328
1.3708
0.2441
44.74
1.00
Craniosynostosis
Cigarettes
13.2676
11.3680
1.1671
0.2462
0.0039
3.8587
1.3621
0.2462
45.19
1.00
Choanal atresia
Cigarettes
1.3216
1.1914
1.1093
0.2682
0.0008
0.7233
1.2307
0.2682
10.02
1.00
Amniotic Bands
Cigarettes
1.9776
1.8318
1.0796
0.2840
0.0023
0.5285
1.1656
0.2840
59.76
1.00
Cleft palate alone
Cigarettes
5.3064
4.9157
1.0795
0.2814
0.0007
2.7774
1.1653
0.2814
10.85
1.00
Ebstein anomaly
Cigarettes
0.7405
0.7584
0.9763
0.3297
−0.0002
0.4646
0.9532
0.3297
8.00
1.00
Reduction deformity, Lower limbs
Cigarettes
8.6524
9.1172
0.9490
0.3445
−0.0008
3.2313
0.9006
0.3445
22.36
1.00
Pulmonary valve atresia
Cigarettes
3.3612
3.8692
0.8687
0.3861
−0.0013
1.9006
0.7546
0.3861
9.47
1.00
Cleft lip with cleft palate
Cigarettes
3.2169
4.0414
0.7960
0.4271
−0.0020
1.8393
0.6336
0.4271
9.29
1.00
Gastroschisis
Cigarettes
2.1392
3.3067
0.6469
0.5182
−0.0021
1.9126
0.4185
0.5182
4.98
1.00
Clubfoot
Cigarettes
7.7021
14.8418
0.5189
0.6047
−0.0057
5.8097
0.2693
0.6047
6.14
1.00
Obstructive genitourinary defect
Cigarettes
19.2026
38.0533
0.5046
0.6148
−0.0066
12.9550
0.2546
0.6148
7.17
1.00
Coarctation of the aorta
Cigarettes
3.2398
6.6943
0.4840
0.6288
−0.0025
4.1228
0.2342
0.6288
3.51
1.00
Aniridia
Cigarettes
0.5344
1.4146
0.3778
0.7063
−0.0082
0.4681
0.1427
0.7063
5.10
1.00
Anophthalmia/microphthalmia
Cigarettes
1.5564
6.3984
0.2432
0.8080
−0.0034
3.8287
0.0592
0.8080
2.25
1.00
Epispadias
Cigarettes
0.2592
2.5368
0.1022
0.9189
−0.0121
0.7690
0.0104
0.9189
2.06
1.00
Interrupted aortic arch
Cigarettes
0.1509
2.0077
0.0751
0.9402
−0.0072
0.8982
0.0056
0.9402
1.60
1.00
Microcephalus
Cigarettes
0.3421
12.8915
0.0265
0.9789
−0.0084
4.5413
0.0007
0.9789
1.35
1.00
Encephalocele
Cigarettes
−0.0017
2.1734
−0.0008
0.9994
−0.0034
1.3370
0.0000
0.9994
1.04
NA
Congenital posterior urethral valves
Cigarettes
−0.5966
6.8233
−0.0874
0.9305
−0.0069
2.9831
0.0076
0.9305
1.69
NA
Single ventricle
Cigarettes
−0.3417
2.1972
−0.1555
0.8766
−0.0065
0.9898
0.0242
0.8766
2.08
NA
Congenital hip dislocation
Cigarettes
−6.9146
20.8003
−0.3324
0.7402
−0.0086
5.9638
0.1105
0.7402
5.19
NA
Renal agenesis/hypoplasia
Cigarettes
−2.2676
5.0062
−0.4530
0.6509
−0.0027
3.0895
0.2052
0.6509
3.31
NA
Esophageal atresia/tracheoesophageal fistula
Cigarettes
−0.6793
1.1994
−0.5664
0.5716
−0.0023
0.7428
0.3208
0.5716
4.03
NA
Small intestinal atresia/stenosis
Cigarettes
−1.8286
2.8694
−0.6373
0.5250
−0.0042
1.2732
0.4061
0.5250
6.85
NA
Pulmonary valve atresia and stenosis
Cigarettes
−42.7272
64.7992
−0.6594
0.5102
−0.0019
38.9612
0.4348
0.5102
4.87
NA
Spina bifida without anencephalus
Cigarettes
−4.8101
6.5013
−0.7399
0.4599
−0.0014
4.0680
0.5474
0.4599
5.31
NA
Atrioventricular septal defect
Cigarettes
−3.1546
4.0985
−0.7697
0.4422
−0.0015
2.4370
0.5924
0.4422
5.95
NA
Anencephalus
Cigarettes
−9.9229
12.0861
−0.8210
0.4123
−0.0010
7.5960
0.6741
0.4123
6.02
NA
Cleft lip with and without cleft palate
Cigarettes
−7.2523
8.1749
−0.8871
0.3767
−0.0016
3.0661
0.7870
0.3767
16.70
NA
Omphalocele
Cigarettes
−6.3434
6.2594
−1.0134
0.3118
0.0001
3.5702
1.0270
0.3118
9.55
NA
Patent ductus arteriosus
Cigarettes
−134.9204
93.6508
−1.4407
0.1527
0.0103
26.7177
2.0755
0.1527
197.55
NA
Cleft lip alone
Cigarettes
−7.6263
5.0141
−1.5210
0.1300
0.0072
2.3847
2.3134
0.1300
36.22
NA
Aortic valve stenosis
Cigarettes
−5.5657
3.5177
−1.5822
0.1147
0.0052
2.1283
2.5034
0.1147
21.09
NA
Limb deficiencies (reduction defects)
Cigarettes
−9.2468
5.6656
−1.6321
0.1044
0.0093
2.6416
2.6637
0.1044
47.85
NA
Congenital cataract
Cigarettes
−3.1133
1.7342
−1.7952
0.0737
0.0077
1.0449
3.2228
0.0737
29.59
NA
Reduction deformity, Upper limbs
Cigarettes
−9.9676
4.2945
−2.3210
0.0219
0.0342
1.5208
5.3870
0.0219
778.14
NA
Total anomalous pulmonary venous connection
Cigarettes
−2.9518
0.9933
−2.9718
0.0034
0.0421
0.4914
8.8318
0.0034
472.81
NA
Tricuspid valve atresia and stenosis
Cigarettes
−13.5992
4.5124
−3.0137
0.0028
0.0268
2.7617
9.0825
0.0028
176.14
NA
Deletion 22q11.2
Cigarettes
−4.0755
1.2068
−3.3771
0.0010
0.0817
0.5118
11.4051
0.0010
2803.97
NA
Turner syndrome
Cigarettes
−67.5119
15.2076
−4.4394
0.0000
0.1217
6.7057
19.7079
0.0000
19,050.01
NA
Trisomy 13
Cigarettes
−47.5542
8.4152
−5.6510
0.0000
0.0943
5.1389
31.9335
0.0000
9081.76
NA
Trisomy 18
Cigarettes
−102.6539
15.9192
−6.4485
0.0000
0.1174
9.7711
41.5825
0.0000
28,380.44
NA
Trisomy 21 (Down syndrome)
Cigarettes
−145.2252
19.7758
−7.3436
0.0000
0.1423
12.4068
53.9284
0.0000
84,541.57
NA
Anotia/microtia
Cigarettes
−47.4905
6.3089
−7.5275
0.0000
0.1587
3.8479
56.6635
0.0000
150,869.58
NA
Anzeige
Median household income and ethnicity data by state and year was sourced using tidycensus package [84] in R directly from the US Census bureau including linear interpolation for missing year data. The main ethnicities which were tracked included: Native Hawaiian / Pacific Islander (NHPI), American Indian / Alaska Native (AIAN), Asian-American, Hispanic-American, African-American and Caucasian-American. Cannabinoid concentration data in USA at the Federal level was taken from published reports of the US Drug Enforcement Agency (DEA) [72‐74]. The five cannabinoids of interest were Δ9-tetrahydrocannabinol (THC), cannabidiol (CBD), cannabigerol (CBG), cannabinol (CBN), and cannabichromene (CBC). Federal cannabinoid concentration was multiplied by state level cannabis use to compute an estimate of cannabinoid exposure in each state.
Further technical details relating to statistical methodology are provided in an online Statistical Appendix.
Data availability
Data, including R-code, spatial weights, ipw weights and main source datasets has been made freely available through the Mendeley Data repository online and can be accessed at https://doi.org/10.17632/w6ks529sxd.1 .
Ethics
The University of Western Australia Human Research Ethics Committee granted ethical approval for this study on 7th January 2020 RA/4/20/7724.
Results
This section is set out in three sections. First we examine bivariate continuous associations. We then calculate key epidemiological parameters of interest from categorization of key exposure variables. We then demonstrate how inverse probability weighting can be employed in multivariable regression models and also use spatiotemporal models to investigate causal relationships formally and in a space-time context as an analytical pathway proof of concept for subsequent detailed studies across all congenital anomalies.
18,328,529 births occurred in USA in the eight nominal years 2005–2013. 2008 was omitted as CA data was not available for that year. The cumulative aggregated population of the USA for these eight years year-on-year was 2,377,483,589. 12,611 birth defect rates relating to 62 birth defects in the 50 states of the USA were extracted from the published reports of the National Birth Defects Prevention Network which is coordinated by the CDC. The defects of interest are listed in Supplementary Table 1. The period of interest was 2005–2013 as that period could be related to drug and substance exposure data from the NSDUH from SAMHSA. Since NBDPN reports are issued for quinquennia this report comprehends the NBDPN reports from 2003–2007 to 2011–2015.
It is well known that several congenital anomalies are actively sought out by active antenatal screening programs. Some of these are subject to indications for early therapeutic termination of pregnancy for anomaly (ETOPFA). In considering the likely rate of congenital anomalies it is important to take this effect into consideration. Supplementary Table 1 also lists the ETOPFA rates from various published series [72‐74]. Series were selected for their breadth of coverage of multiple congenital anomalies. The right hand column lists the ETOPFA rates applied in the present work which were a composite of these series. This estimate of the ETOPFA-corrected rate was a dependent variable of interest in some of the present analyses. Supplementary Table 2 shows the time-dependent progression of the only longitudinal series of ETOPFA’s we were able to identify which was the Down Syndrome ETOPFA rate in Western Australia [83].
Continuous bivariate exposure survey
Figure 1 shows the time dependent trajectories of these various CAs corrected for estimates of ETOPFA.
Fig. 1
Time trends of selected congenital anomaly incidence rates
×
Figure 2 shows the substance exposure trends over this time period. Data was taken from the nationally representative annual SAMHSA NSDUH which reports a 74.1% response rate [85].
Fig. 2
Trends over time of various selected substances, data from National Survey of Drug Use and Health
×
Figure 3 shows the annual estimated cannabinoid exposure for state level data estimated from Federal data from the DEA relating to cannabinoid concentrations in drug seizures and the state level last month cannabis consumption. Rising trends are noted for all cannabinoids except cannabidiol which is declining.
Fig. 3
Trends over time of various selected estimates of cannabinoid exposure, data from National Survey of Drug Use and Health and Drug Enforcement Agency
×
Figure 4 shows the relationship of the various ETOPFA-corrected CA rates (ETOPFACAR) to tobacco exposure. As is expected many show a rising and positive relationship.
Fig. 4
Trends of various congenital anomaly incidence rates in relationship to tobacco exposure
×
Supplementary Fig. 1 shows the relationship of the ETOPFACAR estimates to binge alcohol exposure. Mostly weak or negative relationships are demonstrated.
Supplementary Fig. 2 shows the relationship of the ETOPFACARs to last month alcohol use. Similar appearances are seen.
Moving to Fig. 5 and considering the relationship of ETOPFACARs to cannabis exposure the pattern changes dramatically from weak associations to many clearly strongly positive and apparently highly significant associations.
Fig. 5
Trends of various congenital anomaly incidence rates in relationship to cannabis exposure
×
Figure 6 shows the relationship of the ETOPFACAR to THC exposure. Many of these relationships are clearly positive and highly significant.
Fig. 6
Trends of various congenital anomaly incidence rates in relationship to THC exposure
×
Figure 7 shows the relationship of the ETOPFACARs to state level estimated cannabidiol exposure. Some relationships appear to be positive, particularly in the top line of CAs.
Fig. 7
Trends of various congenital anomaly incidence rates in relationship to cannabidiol exposure
×
Supplementary Table 3 provides details of the slopes of the ETOPFACARs over time. The table was produced using the purrr-broom package combination in R using the nest-map-unnest workflow whereby multiple linear models can be processed simultaneously for each CA. The table lists the model β-estimates, the t-values and various model statistics. Lastly the table lists the point estimates of the E-Values for these regression lines together with the 95% lower bound of the E-Value.
Table 1 performs a similar function for tobacco exposure. One notes that in this Table 12 ETOPFACARs have minimum E-Values greater than 1.00.
Supplementary Table 4 performs the same function for binge alcohol exposure. Only two ETOPFACARs have elevated minimum E-Values in this table which are cleft lip alone and epispadias.
Supplementary Table 5 performs the same function for last month alcohol exposure. Here six ETOPFACARs have elevated minimum E-Values.
Contrariwise Table 2, which illustrates the relationship of the ETOPFACARs with cannabis exposure, contrasts sharply with Table 5. In Table 6 one notes that 35 ETOPFACARs are shown to have elevated minimum E-Values. These pertain particularly to cardiovascular system (9 anomalies), urinary tract (6 anomalies), gastrointestinal tract (five anomalies), all five chromosomal anomalies, four musculoskeletal or limb development anomalies (club foot, congenital hip dislocation, limb reduction deficiencies and leg reduction deficiencies), two anomalies each of face and body wall, and one anomaly of brain development.
Table 2
Regression Slopes for ETOPFA-Corrected Congenital Anomaly Rates by Cannabis Exposure
Parameters
Model
E-Values
Congenital Anomaly
Term
Estimate
Std.Error
t-Value
P_Value
Adj.R.Squared
S.D.
t-Statistic
P-Value
E-Value - Point
E-Value - Lower
Small intestinal atresia/stenosis
Cannabis
26.5037
3.7660
7.0377
7.66E-11
0.2534
1.0978
49.5291
7.66E-11
6.95E+09
1.55E+07
Trisomy 21 (Down syndrome)
Cannabis
221.1194
25.4625
8.6841
2.03E-16
0.1891
10.2305
75.4141
2.03E-16
6.97E+08
8.30E+06
Interrupted aortic arch
Cannabis
15.4036
3.1814
4.8418
3.40E-06
0.1390
0.8305
23.4430
3.40E-06
4.28E+07
4.68E+04
Clubfoot
Cannabis
94.0309
21.7820
4.3169
3.16E-05
0.1211
5.4311
18.6357
3.16E-05
1.39E+07
1.10E+04
Congenital hip dislocation
Cannabis
115.8679
32.7515
3.5378
6.07E-04
0.0997
5.6345
12.5159
6.07E-04
2.68E+08
8.60E+03
Trisomy 13
Cannabis
75.1394
14.1320
5.3170
2.08E-07
0.0841
5.1679
28.2701
2.08E-07
1.11E+06
8.58E+03
Obstructive genitourinary defect
Cannabis
241.0897
66.6741
3.6159
4.49E-04
0.0958
12.2786
13.0750
4.49E-04
1.15E+08
7.30E+03
Congenital posterior urethral valves
Cannabis
23.9399
6.0470
3.9590
1.18E-04
0.0925
1.6001
15.6734
1.18E-04
1.64E+06
1.96E+03
Trisomy 18
Cannabis
126.9696
26.3799
4.8131
2.34E-06
0.0678
10.0424
23.1662
2.34E-06
1.99E+05
1.85E+03
Esophageal atresia/tracheoesophageal fistula
Cannabis
8.8449
1.8993
4.6570
4.83E-06
0.0645
0.7176
21.6880
4.83E-06
1.49E+05
1.34E+03
Hypospadias
Cannabis
277.1790
62.0518
4.4669
1.16E-05
0.0640
23.4595
19.9532
1.16E-05
9.34E+04
842.36
Biliary atresia
Cannabis
4.4970
1.2418
3.6215
0.0003
0.0418
0.4136
13.1152
3.48E-04
3.96E+04
188.70
Deletion 22q11.2
Cannabis
6.6430
2.1356
3.1106
0.0024
0.0690
0.5153
9.6756
0.0024
2.49E+05
155.04
Turner syndrome
Cannabis
85.6995
27.3283
3.1359
0.0021
0.0614
6.9321
9.8340
0.0021
1.54E+05
137.32
Rectal and large intestinal atresia/stenosis
Cannabis
13.0849
3.6262
3.6085
0.0004
0.0395
1.3748
13.0210
3.62E-04
1.16E+04
105.07
Epispadias
Cannabis
12.5446
4.8274
2.5986
0.0111
0.0648
0.7392
6.7528
0.0111
1.02E+07
90.57
Renal agenesis/hypoplasia
Cannabis
27.3954
8.0283
3.4124
7.34E-04
0.0346
3.0315
11.6442
0.0007
7.45E+03
66.37
Anotia/microtia
Cannabis
37.2830
10.9541
3.4036
7.57E-04
0.0346
4.1220
11.5843
0.0008
7.51E+03
65.76
Diaphragmatic hernia
Cannabis
10.2830
3.0660
3.3539
9.01E-04
0.0335
1.1615
11.2486
0.0009
6.31E+03
56.94
Cleft palate alone
Cannabis
24.1946
7.4701
3.2389
0.0014
0.0366
2.7271
10.4902
0.0014
6.42E+03
48.45
Encephalocele
Cannabis
11.3770
3.4999
3.2507
0.0013
0.0311
1.3138
10.5670
0.0013
5.29E+03
45.63
Aortic valve stenosis
Cannabis
17.8815
5.6987
3.1378
0.0019
0.0296
2.1020
9.8461
0.0019
4.60E+03
36.41
Ventricular septal defect
Cannabis
166.2143
53.4999
3.1068
0.0021
0.0296
19.9528
9.6523
0.0021
3.92E+03
32.64
Pulmonary valve atresia
Cannabis
9.4232
3.2900
2.8642
0.0047
0.0369
1.0048
8.2037
0.0047
1.02E+04
29.43
Omphalocele
Cannabis
28.8975
9.4470
3.0589
0.0025
0.0311
3.5144
9.3568
0.0025
3.55E+03
29.18
Hypoplastic left heart syndrome
Cannabis
10.7890
3.7873
2.8487
0.0047
0.0224
1.4621
8.1152
0.0047
1.65E+03
15.88
Hirschsprung disease (congenital megacolon)
Cannabis
19.3922
8.4341
2.2993
0.0233
0.0356
1.5076
5.2866
0.0233
2.42E+05
10.95
Limb deficiencies (reduction defects)
Cannabis
21.4215
8.5782
2.4972
0.0134
0.0287
2.6156
6.2360
0.0134
3.45E+03
9.53
Bladder exstrophy
Cannabis
1.0618
0.4420
2.4021
0.0170
0.0173
0.1593
5.7701
0.0170
860.98
5.62
Tetralogy of Fallot
Cannabis
9.9067
4.1188
2.4052
0.0168
0.0152
1.6031
5.7852
0.0168
553.33
5.16
Total anomalous pulmonary venous connection
Cannabis
3.9176
1.7901
2.1885
0.0299
0.0208
0.4968
4.7896
0.0299
2.61E+03
3.71
Reduction deformity, Lower limbs
Cannabis
16.8233
8.1886
2.0545
0.0420
0.0251
1.5723
4.2209
0.0420
3.39E+04
2.57
Coarctation of the aorta
Cannabis
22.5596
10.7794
2.0928
0.0372
0.0111
4.0947
4.3800
0.0372
300.37
2.12
Atrial septal defect
Cannabis
285.3616
136.7781
2.0863
0.0378
0.0117
51.3723
4.3527
0.0378
313.06
2.08
Congenital cataract
Cannabis
5.9492
2.9939
1.9871
0.0479
0.0102
1.0436
3.9486
0.0479
357.58
1.39
Spina bifida without anencephalus
Cannabis
19.7183
10.1652
1.9398
0.0533
0.0086
4.0477
3.7628
0.0533
167.88
1.00
Cleft lip with cleft palate
Cannabis
11.1868
5.7863
1.9333
0.0548
0.0149
1.8237
3.7377
0.0548
530.72
1.00
Choanal atresia
Cannabis
3.9066
2.0476
1.9078
0.0574
0.0090
0.7204
3.6399
0.0574
277.66
1.00
Holoprosencephaly
Cannabis
72.7261
39.0245
1.8636
0.0644
0.0168
10.2141
3.4730
0.0644
1.30E+03
1.00
Cloacal exstrophy
Cannabis
20.4977
11.5158
1.7800
0.0777
0.0185
2.7798
3.1683
0.0777
1.64E+03
1.00
Anophthalmia/microphthalmia
Cannabis
9.2992
5.2676
1.7654
0.0786
0.0075
1.7798
3.1165
0.0786
231.75
1.00
Single ventricle
Cannabis
6.1305
3.7353
1.6412
0.1029
0.0112
0.9811
2.6936
0.1029
589.19
1.00
Pulmonary valve atresia and stenosis
Cannabis
19.6240
13.4446
1.4596
0.1455
0.0038
5.0335
2.1305
0.1455
68.97
1.00
Gastroschisis
Cannabis
5.8564
4.9756
1.1770
0.2402
0.0014
1.9092
1.3854
0.2402
32.10
1.00
Atrioventricular septal defect
Cannabis
6.8595
6.7893
1.0103
0.3132
7.69E-05
2.4351
1.0208
0.3132
25.45
1.00
Aniridia
Cannabis
2.4802
3.2029
0.7744
0.4405
−0.0038
0.4671
0.5996
0.4405
250.47
1.00
Cleft lip alone
Cannabis
5.3804
7.5548
0.7122
0.4773
−0.0027
2.3966
0.5072
0.4773
14.91
1.00
Microcephalus
Cannabis
12.6431
24.1277
0.5240
0.6012
−0.0061
4.5361
0.2746
0.6012
24.76
1.00
Patent ductus arteriosus
Cannabis
39.3210
155.2633
0.2533
0.8006
−0.0092
26.9797
0.0641
0.8006
7.00
1.00
Cleft lip with and without cleft palate
Cannabis
−0.2957
15.7796
−0.0187
0.9851
−0.0077
3.0755
0.0004
0.9851
1.41
–
Double outlet right ventricle
Cannabis
−0.1429
3.4924
−0.0409
0.9674
−0.0062
1.0338
0.0017
0.9674
1.52
–
Common truncus (truncus arteriosus)
Cannabis
−1.2255
3.0794
−0.3980
0.6909
−0.0028
1.1539
0.1584
0.6909
4.70
–
Ebstein anomaly
Cannabis
−0.5654
1.2641
−0.4473
0.6550
−0.0028
0.4652
0.2001
0.6550
5.49
–
Pyloric stenosis
Cannabis
−41.8439
60.3518
−0.6933
0.4896
−0.0047
10.3424
0.4807
0.4896
78.93
–
Tricuspid valve atresia and stenosis
Cannabis
−5.6602
7.5460
−0.7501
0.4538
−0.0015
2.8017
0.5626
0.4538
12.05
–
Amniotic Bands
Cannabis
−3.2223
4.0536
−0.7949
0.4293
−0.0052
0.5304
0.6319
0.4293
502.82
–
Hydrocephalus without spina bifida
Cannabis
−20.4351
24.5694
−0.8317
0.4072
−0.0026
4.6285
0.6918
0.4072
110.65
–
Dextro-transposition of great arteries (d-TGA)
Cannabis
−3.1308
3.5121
−0.8915
0.3739
−0.0012
1.0467
0.7947
0.3739
29.91
–
Anencephalus
Cannabis
−18.7394
19.5370
−0.9592
0.3382
−0.0003
7.5930
0.9200
0.3382
18.38
–
Transposition of great arteries
Cannabis
−4.6234
3.9852
−1.1601
0.2469
0.0012
1.5252
1.3459
0.2469
31.05
–
Craniosynostosis
Cannabis
−38.5041
18.9772
−2.0290
0.0454
0.0328
3.8024
4.1167
0.0454
2.01E+04
–
Reduction deformity, Upper limbs
Cannabis
−22.0440
7.9002
−2.7903
0.0061
0.0519
1.5068
7.7858
0.0061
1.21E+06
–
Supplementary Table 6 performs the same function for estimated THC exposure. In this Table 40 ETOPFACARs have minimum E-Values greater than 1.00. Chromosomal and cardiovascular defects are particularly featured but microtia, limb and leg reduction defects, club foot, gastroschisis, omphalocele, anencephalus, spina bifida, esophageal atresia, small and large intestinal stenosis or atresia and obstructive genitourinary defects and congenital posterior urethral valves also feature.
As shown in Table 3 the list of ETOPFACARs with minimum E-Values greater than 1.00 is shorter for cannabidiol. Eleven defects are featured which are in order: congenital dislocation of the hip, small intestinal stenosis or atresia, biliary atresia, obstructive genitourinary defect, large bowel atresia or stenosis, Hirschsprungs disease (congenital megacolon), esophageal atresia, diaphragmatic hernia cleft palate, reduction deformities of the legs and transposition of the great vessels.
Table 3
Regression Slopes for ETOPFA-Corrected Congenital Anomaly Rates by Cannabidiol Exposure
Parameters
Model
E-Values
Congenital Anomaly
Term
Estimate
Std.Error
t-Value
P_Value
Adj.R.Squared
S.D.
t-Statistic
P-Value
E-Value - Point
E-Value - Lower
Congenital hip dislocation
Cannabidiol
298.2937
55.1100
5.4127
6.32E-07
0.2589
3.8459
29.2973
6.32E-07
9.00E+30
7.53E+19
Small intestinal atresia/stenosis
Cannabidiol
61.6605
12.7480
4.8369
3.39E-06
0.1354
1.1814
23.3954
3.39E-06
8.48E+20
3.86E+12
Biliary atresia
Cannabidiol
10.9598
2.9445
3.7222
2.43E-04
0.0480
0.3922
13.8546
2.43E-04
2.22E+11
3.48E+05
Obstructive genitourinary defect
Cannabidiol
486.0939
176.6878
2.7511
0.0072
0.0680
13.0815
7.5688
0.0072
9.69E+14
3.51E+04
Hirschsprung disease (congenital megacolon)
Cannabidiol
38.1800
14.1676
2.6949
0.0084
0.0637
1.0029
7.2624
0.0084
2.22E+15
2.67E+04
Rectal and large intestinal atresia/stenosis
Cannabidiol
26.0458
8.9678
2.9044
0.0040
0.0274
1.3051
8.4354
0.0040
1.54E+08
751.61
Esophageal atresia/tracheoesophageal fistula
Cannabidiol
13.7132
4.8352
2.8361
0.0049
0.0253
0.7108
8.0437
0.0049
8.43E+07
464.16
Diaphragmatic hernia
Cannabidiol
21.8501
7.9675
2.7424
0.0065
0.0237
1.1678
7.5207
0.0065
4.96E+07
263.36
Cleft palate alone
Cannabidiol
46.0706
20.0476
2.2981
0.0224
0.0172
2.7752
5.2811
0.0224
7.27E+06
18.43
Reduction deformity, Lower limbs
Cannabidiol
42.6901
21.4422
1.9909
0.0492
0.0288
1.6564
3.9638
0.0492
3.07E+10
2.38
Transposition of great arteries
Cannabidiol
19.6282
9.8766
1.9873
0.0479
0.0106
1.4902
3.9496
0.0479
3.21E+05
1.71
Cloacal exstrophy
Cannabidiol
76.8088
39.8261
1.9286
0.0563
0.0231
2.7733
3.7195
0.0563
1.76E+11
1.00
Epispadias
Cannabidiol
19.8920
10.4475
1.9040
0.0604
0.0307
0.7526
3.6252
0.0604
5.58E+10
1.00
Clubfoot
Cannabidiol
123.4731
76.7503
1.6088
0.1102
0.0123
5.7575
2.5881
0.1102
5.98E+08
1.00
Deletion 22q11.2
Cannabidiol
11.7674
7.4174
1.5865
0.1154
0.0128
0.5307
2.5169
0.1154
1.16E+09
1.00
Pulmonary valve atresia
Cannabidiol
14.2898
9.1696
1.5584
0.1208
0.0075
1.0200
2.4285
0.1208
6.89E+05
1.00
Aniridia
Cannabidiol
11.4134
7.6646
1.4891
0.1403
0.0146
0.4236
2.2174
0.1403
8.91E+10
1.00
Cleft lip with and without cleft palate
Cannabidiol
47.9755
35.6346
1.3463
0.1812
0.0078
2.8627
1.8126
0.1812
8.40E+06
1.00
Hypospadias
Cannabidiol
215.6799
160.8491
1.3409
0.1811
0.0029
24.1209
1.7980
0.1811
6.84E+03
1.00
Interrupted aortic arch
Cannabidiol
12.3060
10.7579
1.1439
0.2546
0.0022
0.8940
1.3085
0.2546
5.51E+05
1.00
Cleft lip with cleft palate
Cannabidiol
18.8934
17.5531
1.0764
0.2832
8.75E-04
1.8366
1.1585
0.2832
2.33E+04
1.00
Bladder exstrophy
Cannabidiol
1.2975
1.2080
1.0741
0.2838
6.22E-04
0.1585
1.1537
0.2838
3.44E+03
1.00
Total anomalous pulmonary venous connection
Cannabidiol
4.1211
4.3730
0.9424
0.3473
−6.29E-04
0.5022
0.8881
0.3473
3.50E+03
1.00
Congenital cataract
Cannabidiol
4.4981
7.4397
0.6046
0.5460
−0.0024
1.0520
0.3655
0.5460
97.42
1.00
Dextro-transposition of great arteries (d-TGA)
Cannabidiol
5.4634
9.0926
0.6009
0.5487
−0.0036
1.0480
0.3610
0.5487
229.30
1.00
Aortic valve stenosis
Cannabidiol
9.0139
15.8331
0.5693
0.5696
−0.0025
2.1657
0.3241
0.5696
87.79
1.00
Microcephalus
Cannabidiol
25.8143
51.1470
0.5047
0.6150
−0.0082
3.7981
0.2547
0.6150
970.31
1.00
Cleft lip alone
Cannabidiol
10.5197
24.3612
0.4318
0.6664
−0.0045
2.3987
0.1865
0.6664
107.70
1.00
Tetralogy of Fallot
Cannabidiol
4.4464
10.6210
0.4186
0.6758
−0.0029
1.6091
0.1753
0.6758
24.21
1.00
Patent ductus arteriosus
Cannabidiol
104.0952
399.2821
0.2607
0.7950
−0.0114
28.5501
0.0680
0.7950
54.70
1.00
Congenital posterior urethral valves
Cannabidiol
2.4488
20.4918
0.1195
0.9050
−0.0069
1.6854
0.0143
0.9050
6.96
1.00
Ventricular septal defect
Cannabidiol
−23.7333
139.2946
−0.1704
0.8648
−0.0037
20.2028
0.0290
0.8648
5.27
NA
Choanal atresia
Cannabidiol
−1.0493
5.0746
−0.2068
0.8363
−0.0036
0.7189
0.0428
0.8363
7.01
NA
Limb deficiencies (reduction defects)
Cannabidiol
−9.2029
28.6458
−0.3213
0.7484
−0.0051
2.6608
0.1032
0.7484
46.05
NA
Single ventricle
Cannabidiol
−3.9066
11.5847
−0.3372
0.7364
−0.0059
0.9895
0.1137
0.7364
72.15
NA
Pulmonary valve atresia and stenosis
Cannabidiol
−22.4845
34.4394
−0.6529
0.5144
−0.0021
5.0837
0.4262
0.5144
111.44
NA
Gastroschisis
Cannabidiol
−9.7272
13.2026
−0.7368
0.4619
−0.0018
1.9055
0.5428
0.4619
207.72
NA
Coarctation of the aorta
Cannabidiol
−27.6410
27.9781
−0.9880
0.3240
−8.62E-05
4.2271
0.9760
0.3240
767.41
NA
Common truncus (truncus arteriosus)
Cannabidiol
−9.2806
8.3564
−1.1106
0.2677
8.54E-04
1.1939
1.2334
0.2677
2.36E+03
NA
Anophthalmia/microphthalmia
Cannabidiol
−14.7546
12.6122
−1.1699
0.2431
0.0014
1.7384
1.3686
0.2431
4.52E+03
NA
Encephalocele
Cannabidiol
−11.9747
9.2992
−1.2877
0.1989
0.0024
1.3294
1.6582
0.1989
7.26E+03
NA
Atrial septal defect
Cannabidiol
−610.8850
361.7188
−1.6888
0.0925
0.0071
52.7719
2.8522
0.0925
7.52E+04
NA
Atrioventricular septal defect
Cannabidiol
−31.8080
16.5300
−1.9243
0.0554
0.0099
2.4231
3.7028
0.0554
3.08E+05
NA
Hydrocephalus without spina bifida
Cannabidiol
−56.5887
54.7420
−1.0337
0.3040
7.37E-04
4.0806
1.0686
0.3040
6.05E+05
NA
Holoprosencephaly
Cannabidiol
−146.0616
130.5839
−1.1185
0.2652
0.0017
10.2919
1.2511
0.2652
8.12E+05
NA
Turner syndrome
Cannabidiol
−103.2404
93.9159
−1.0993
0.2736
0.0015
7.1498
1.2084
0.2736
1.02E+06
NA
Hypoplastic left heart syndrome
Cannabidiol
−21.8275
9.7759
−2.2328
0.0263
0.0137
1.4903
4.9854
0.0263
1.23E+06
NA
Amniotic Bands
Cannabidiol
−8.5621
9.9023
−0.8647
0.3909
−0.0044
0.5072
0.7476
0.3909
9.39E+06
NA
Double outlet right ventricle
Cannabidiol
−17.4959
10.8027
−1.6196
0.1073
0.0099
1.0255
2.6230
0.1073
1.11E+07
NA
Anotia/microtia
Cannabidiol
−75.4583
28.5853
−2.6398
0.0088
0.0215
4.1677
6.9683
0.0088
2.86E+07
NA
Renal agenesis/hypoplasia
Cannabidiol
−55.5432
21.1694
−2.6237
0.0092
0.0213
3.0263
6.8841
0.0092
3.59E+07
NA
Omphalocele
Cannabidiol
−72.7238
25.9206
−2.8056
0.0054
0.0273
3.5964
7.8716
0.0054
1.96E+08
NA
Tricuspid valve atresia and stenosis
Cannabidiol
−66.1395
18.6247
−3.5512
4.53E-04
0.0414
2.7738
12.6108
4.53E-04
5.30E+09
NA
Spina bifida without anencephalus
Cannabidiol
−100.5390
26.3548
−3.8148
1.67E-04
0.0446
4.0223
14.5529
1.67E-04
1.51E+10
NA
Trisomy 21 (Down syndrome)
Cannabidiol
−294.7787
68.5834
−4.2981
2.36E-05
0.0568
10.4764
18.4737
2.36E-05
2.64E+11
NA
Trisomy 13
Cannabidiol
−159.8606
36.7241
−4.3530
1.90E-05
0.0617
5.3524
18.9488
1.90E-05
1.27E+12
NA
Ebstein anomaly
Cannabidiol
−13.6797
3.1851
−4.2949
2.46E-05
0.0620
0.4446
18.4464
2.46E-05
2.90E+12
NA
Reduction deformity, Upper limbs
Cannabidiol
−50.5739
20.4153
−2.4773
0.0150
0.0493
1.5707
6.1368
0.0150
1.06E+13
NA
Craniosynostosis
Cannabidiol
−128.6709
60.4738
−2.1277
0.0361
0.0369
3.7943
4.5272
0.0361
5.05E+13
NA
Trisomy 18
Cannabidiol
−376.7155
67.6238
−5.5708
5.95E-08
0.0966
10.0334
31.0333
5.95E-08
1.38E+15
NA
Anencephalus
Cannabidiol
−405.9858
49.6283
−8.1805
9.98E-15
0.1900
7.0466
66.9210
9.98E-15
1.18E+23
NA
Hence from this series of data we note that the sequence of teratogens is THC (40 CAs) > cannabis (35 CAs) > tobacco (11 CAs) > cannabidiol (11 CAs) > monthly alcohol (5 CAs) > binge alcohol (2 CAs).
To aid with understanding and comparison these minimum E-Values are also presented graphically using a log scale. A horizontal line marks the literature described cut-off for causality at (log) 1.25 [67]. Supplementary Fig. 3 shows the minimum E-Values for ETOPFACARs over time.
Figure 8 lists the E-Values by CA for those ETOPFACARs which reported elevated finite minimum E-Values for tobacco.
Fig. 8
E-Values of regression lines of relationship of congenital anomaly incidence rates with tobacco exposure
×
Supplementary Fig. 4 and Figs. 9, 10, 11, 12 do this for binge alcohol, last month alcohol, cannabis, THC and cannabidiol exposure respectively. One notes that the graph for THC clearly has more defects listed.
Fig. 9
E-Values of regression lines of relationship of congenital anomaly incidence rates with last month exposure
Fig. 10
E-Values of regression lines of relationship of congenital anomaly incidence rates with cannabis exposure
Fig. 11
E-Values of regression lines of relationship of congenital anomaly incidence rates with THC exposure
Fig. 12
E-Values of regression lines of relationship of congenital anomaly incidence rates with cannabidiol exposure
×
×
×
×
Categorical exposure survey
Exposure data was categorized to allow the calculation of key parameters of public health interest such as the prevalence ratio, the aetiological fraction in the exposed and the population attributable risk.
In the following categorical analysis the data was taken from the raw unadjusted NBDPN rates themselves i.e. ETOPFACARs were not used in this series.
Figure 13 shows boxplots by CA and contrasts the highest and lowest quintiles of cigarette exposure by CA listing them in the order of the decreasing ratios between the highest and lowest quintiles.
Fig. 13
Categorical analysis of congenital anomaly incidence rates rates for extreme quintiles of tobacco exposure
×
Supplementary Figs. 5, 6, 7, 8 and Figs. 14 and 15 do this for binge alcohol, last month alcohol, analgesic, cocaine, last month cannabis and cannabidiol exposure. Cannabidiol quintiles in Fig. 15 are not grouped by year but calculated across the whole period.
Fig. 14
Categorical analysis of congenital anomaly incidence rates for extreme quintiles of last month cannabis exposure
Fig. 15
Categorical analysis of congenital anomaly incidence rates for extreme quintiles of canabidiol exposure
×
×
Supplementary Table 7 presents the numbers born with and without CAs in the highest and lowest quintiles of tobacco use states. The Prevalence Ratio (like the Odds Ratio for cohort studies), Attributable Fraction in the Exposed (AFE), the Population Attributable Risk (PAR), the Chi Squared value and the P-level of significance is also shown. The right most columns show the point estimate for the E-Value together with its 95% lower bound. In this Supplementary Table 7 defects are noted to have minimum E-Values elevated above 1.00.
Supplementary Tables 8, 9, 10 and Tables 4, 5 perform a similar function for binge alcohol, analgesics, cocaine, cannabis and cannabidiol respectively. As the CAs tracked by NBDPN / CDC changed over time as the cannabidiol exposure was falling 11 defects have no entries in Quintile 1 (see Fig. 15 for details). Numbers exposed in Quintile 2 were used for these CAs. In these five tables one notes respectively that 1, 21, 27, 10 and 11 CAs demonstrate elevated minimum E-Values. These data suggest that cannabis (21 defects) is the third most important teratogen behind analgesics (27 CAs) and tobacco (26 CAs). Teratogenesis from cannabidiol also appears to be significant (11 CAs).
Table 4
Numbers, Calculated Rates, Significance Levels and E-Values of Highest v. Lowest Cannabis Exposure Quintiles
Congenital Anomaly
Numbers
Calculated Rates
Significance
E-Values
Highest Defect Count
Highest Not Defect Count
Lowest Defect Count
Lowest Not Defect Count
Prevalence Ratio (C.I.)
Atrributable Fraction in the Exposed (C.I.)
Population Attributable Risk (C.I.)
Chi Squared
P-Value
E-Value - Point
E-Value - Lower
Cloacal exstrophy
444
1,141,378
177
2,207,096
4.8507 (4.075, 5.774)
0.7938 (0.7545, 0.8268)
0.5675 (0.5102, 0.6182)
386.73
2.13E-86
9.17
7.61
Congenital hip dislocation
773
722,717
973
2,078,182
2.2845 (2.0785, 2.5108)
0.562 (0.5186, 0.6014)
0.2488 (0.2167, 0.2796)
310.82
7.27E-70
3.99
3.57
Turner syndrome
1577
956,504
3159
2,999,000
1.5652 (1.4734, 1.6628)
0.3607 (0.3209, 0.3982)
0.1201 (0.1022, 0.1376)
214.37
7.69E-49
2.50
2.31
Coarctation of the aorta
3630
3,825,817
3787
5,516,098
1.382 (1.3205, 1.4464)
0.2762 (0.2425, 0.3084)
0.1352 (0.1157, 0.1542)
195.57
9.74E-45
2.11
1.97
Trisomy 18
7276
3,863,762
7853
5,454,321
1.3079 (1.2668, 1.3504)
0.2351 (0.2103, 0.2591)
0.1131 (0.0994, 0.1266)
273.35
1.06E-61
1.94
1.85
Hirschsprung disease (congenital megacolon)
230
943,071
372
2,220,573
1.4558 (1.2351, 1.716)
0.313 (0.1903, 0.4172)
0.1196 (0.0625, 0.1732)
20.28
6.69E-06
2.27
1.77
Trisomy 13
3310
3,809,527
3677
5,440,392
1.2856 (1.2266, 1.3474)
0.222 (0.1846, 0.2577)
0.1052 (0.085, 0.1248)
110.41
3.50E-06
1.89
1.75
Holoprosencephaly
2307
2,735,097
2013
2,952,020
1.2369 (1.1651, 1.3132)
0.1914 (0.1416, 0.2383)
0.1022 (0.0731, 0.1304)
48.76
2.90E-12
1.78
1.60
Diaphragmatic hernia
1210
3,785,854
1417
5,518,468
1.2447 (1.1528, 1.344)
0.1966 (0.1325, 0.2559)
0.0905 (0.0578, 0.1221)
31.39
2.11E-08
1.80
1.57
Congenital posterior urethral valves
272
1,222,110
516
3,083,046
1.3298 (1.1482, 1.5402)
0.248 (0.129, 0.3507)
0.0856 (0.038, 0.1308)
14.57
1.35E-04
1.99
1.56
Pulmonary valve atresia
622
3,217,047
573
3,778,215
1.2749 (1.1381, 1.4281)
0.2156 (0.1213, 0.2997)
0.1122 (0.0582, 0.1631)
17.67
2.62E-05
1.87
1.53
Small intestinal atresia/stenosis
1125
2,778,116
957
2,890,697
1.2232 (1.1222, 1.3333)
0.1824 (0.1088, 0.2499)
0.0986 (0.0556, 0.1396)
21.05
4.47E-06
1.75
1.49
Trisomy 21 (Down syndrome)
17,749
4,160,407
20,309
5,441,865
1.1431 (1.1203, 1.1664)
0.1247 (0.107, 0.1422)
0.0582 (0.0493, 0.067)
169.07
4.02E-26
1.55
1.49
Deletion 22q11.2
129
1,175,941
236
2,919,417
1.357 (1.0949, 1.6819)
0.2631 (0.0867, 0.4054)
0.093 (0.0215, 0.1592)
7.83
0.0051
2.05
1.42
Double outlet right ventricle
854
2,779,998
684
2,647,487
1.189 (1.0752, 1.3148)
0.1589 (0.07, 0.2394)
0.0883 (0.0359, 0.1378)
11.41
7.31E-04
1.66
1.36
Single ventricle
435
2,750,022
377
2,891,287
1.2131 (1.0568, 1.3925)
0.1757 (0.0538, 0.2818)
0.0941 (0.0246, 0.1586)
7.56
0.0060
1.72
1.30
Hypoplastic left heart syndrome
1608
3,991,321
2023
5,517,862
1.0989 (1.0292, 1.1732)
0.0899 (0.0284, 0.1476)
0.0398 (0.0116, 0.0673)
7.97
0.0048
1.43
1.20
Epispadias
93
733,098
214
2,211,891
1.3112 (1.0279, 1.6726)
0.2373 (0.0271, 0.4021)
0.0719 (9e-04, 0.1379)
4.79
0.0287
1.95
1.20
Biliary atresia
303
3,696,288
367
5,330,359
1.1906 (1.0226, 1.3862)
0.1601 (0.0221, 0.2786)
0.0724 (0.0063, 0.1341)
5.06
0.0244
1.67
1.17
Esophageal atresia/tracheoesophageal fistula
924
3,774,953
1207
5,460,967
1.1074 (1.0165, 1.2065)
0.097 (0.0162, 0.1711)
0.0421 (0.0058, 0.077)
5.45
0.0195
1.45
1.15
Clubfoot
1709
1,072,816
4038
2,722,058
1.0739 (1.0148, 1.1364)
0.0687 (0.0145, 0.1199)
0.0204 (0.0038, 0.0367)
6.09
0.0136
1.36
1.14
Spina bifida without anencephalus
4268
4,086,425
5488
5,514,397
1.0495 (1.0083, 1.0923)
0.0471 (0.0082, 0.0844)
0.0206 (0.0033, 0.0376)
5.59
0.0181
1.28
1.10
Atrioventricular septal defect
2405
3,784,659
3324
5,516,561
1.0546 (1.0007, 1.1114)
0.0518 (7e-04, 0.1002)
0.0217 (−1e-04, 0.043)
3.94
0.0470
1.29
1.03
Aniridia
32
866,880
55
2,154,589
1.4461 (0.9353, 2.2359)
0.3085 (−0.0692, 0.5527)
0.1135 (−0.0407, 0.2448)
2.78
0.0952
2.25
1.00
Total anomalous pulmonary venous connection
470
3,196,783
494
3,532,159
1.0512 (0.9265, 1.1928)
0.0487 (−0.0793, 0.1616)
0.0238 (−0.0382, 0.0821)
0.60
0.4381
1.28
1.00
Hydrocephalus without spina bifida
1057
954,941
2408
2,276,248
1.0463 (0.9733, 1.1248)
0.0442 (−0.0274, 0.1109)
0.0135 (−0.0085, 0.035)
1.50
0.2200
1.27
1.00
Interrupted aortic arch
184
2,761,460
180
2,801,964
1.0372 (0.8446, 1.2738)
0.0359 (−0.184, 0.2149)
0.0181 (−0.0893, 0.115)
0.12
0.7274
1.23
1.00
Bladder exstrophy
60
2,670,828
115
5,256,233
1.0268 (0.7515, 1.4029)
0.0261 (−0.3307, 0.2872)
0.0089 (−0.103, 0.1095)
0.03
0.8681
1.19
1.00
Transposition of great arteries
1049
2,418,662
2201
5,131,566
1.0112 (0.9395, 1.0884)
0.0111 (−0.0644, 0.0812)
0.0036 (−0.0204, 0.0269)
0.09
0.7669
1.12
1.00
Anotia/microtia
3396
3,783,668
4802
5,355,143
1.0009 (0.9579, 1.0459)
9e-04 (−0.0439, 0.0439)
4e-04 (−0.018, 0.0184)
0.00
0.9670
1.03
1.00
Cleft lip alone
1178
2,903,931
1366
3,261,461
0.9685 (0.8959, 1.0471)
−0.0325 (−0.1161, 0.0449)
−0.015 (−0.0523, 0.0209)
0.65
0.4216
1.22
NA
Tetralogy of Fallot
2063
3,991,594
2966
5,516,919
0.9613 (0.9088, 1.0169)
−0.0402 (−0.1003, 0.0166)
−0.0165 (−0.0402, 0.0067)
1.89
0.1692
1.24
NA
Cleft palate alone
2483
3,990,680
3402
5,227,758
0.9561 (0.9079, 1.0069)
−0.0459 (−0.1014, 0.0068)
−0.0194 (−0.0418, 0.0026)
2.89
0.0892
1.26
NA
Cleft lip with cleft palate
1907
3,032,425
2001
3,038,883
0.9551 (0.897, 1.0169)
−0.047 (−0.1148, 0.0166)
−0.0229 (−0.0547, 0.0079)
2.06
0.1508
1.27
NA
Congenital cataract
670
3,755,999
1016
5,381,175
0.9448 (0.857, 1.0416)
−0.0584 (−0.1669, 0.0399)
−0.0232 (−0.0637, 0.0157)
1.30
0.2537
1.31
NA
Encephalocele
932
3,791,070
1446
5,518,439
0.9382 (0.8641, 1.0187)
−0.0658 (−0.1573, 0.0184)
−0.0258 (−0.0594, 0.0068)
2.31
0.1289
1.33
NA
Cleft lip with and without cleft palate
969
1,026,247
2304
2,286,080
0.9369 (0.8691, 1.0099)
−0.0673 (−0.1504, 0.0098)
−0.0199 (−0.0428, 0.0025)
2.90
0.0887
1.34
NA
Gastroschisis
2165
4,016,001
3073
5,301,775
0.9301 (0.8803, 0.9827)
−0.0751 (−0.1359, −0.0176)
−0.0311 (−0.0548, −0.0079)
6.67
0.0098
1.36
NA
Anencephalus
4669
4,093,278
6782
5,513,103
0.9272 (0.8933, 0.9625)
−0.0784 (−0.1193, −0.0389)
−0.032 (−0.0477, −0.0164)
15.77
7.15E-05
1.37
NA
Omphalocele
1876
3,828,924
2621
4,919,500
0.9196 (0.8667, 0.9758)
−0.0874 (−0.1537, −0.0248)
−0.0364 (−0.0624, −0.0111)
7.68
0.0056
1.40
NA
Rectal and large intestinal atresia/stenosis
1581
3,785,483
2532
5,459,642
0.9006 (0.8457, 0.959)
−0.1104 (−0.1824, −0.0428)
−0.0424 (−0.0679, −0.0176)
10.68
0.0011
1.46
NA
Aortic valve stenosis
1391
3,730,418
2298
5,517,587
0.8953 (0.8376, 0.957)
−0.1169 (−0.1938, −0.045)
−0.0441 (−0.0706, −0.0182)
10.61
0.0011
1.48
NA
Pyloric stenosis
1264
709,529
4414
2,216,531
0.8946 (0.8403, 0.9524)
−0.1176 (−0.1897, −0.0499)
−0.0262 (−0.0406, −0.012)
12.19
4.82E-04
1.48
NA
Ebstein anomaly
360
3,742,751
592
5,439,310
0.8838 (0.7752, 1.0075)
−0.1315 (−0.2899, 0.0074)
−0.0497 (−0.103, 0.001)
3.42
0.0643
1.52
NA
Pulmonary valve atresia and stenosis
2810
2,731,571
6450
5,513,435
0.8793 (0.8412, 0.9192)
−0.1371 (−0.1885, −0.0878)
−0.0416 (−0.0557, −0.0277)
32.37
1.27E-08
1.53
NA
Obstructive genitourinary defect
2840
953,158
7681
2,213,264
0.8586 (0.8223, 0.8964)
−0.1642 (−0.2153, −0.1152)
−0.0443 (−0.0565, −0.0323)
48.16
3.92E-12
1.60
NA
Amniotic Bands
32
483,538
162
2,064,910
0.8435 (0.5773, 1.2325)
−0.1855 (−0.732, 0.1886)
−0.0306 (−0.0971, 0.0319)
0.78
0.3785
1.65
NA
Reduction deformity, Lower limbs
215
1,012,889
578
2,278,078
0.8366 (0.7153, 0.9784)
−0.1953 (−0.3978, −0.0221)
−0.0529 (−0.0986, −0.0092)
5.00
0.0253
1.68
NA
Choanal atresia
423
3,737,112
798
5,467,622
0.7755 (0.6893, 0.8726)
−0.2894 (−0.4507, −0.146)
−0.1003 (−0.1461, −0.0562)
17.96
2.26E-05
1.90
NA
Limb deficiencies (reduction defects)
1947
3,044,005
2616
3,159,025
0.7724 (0.7284, 0.8191)
−0.2944 (−0.3726, −0.2207)
−0.1256 (−0.1542, −0.0978)
74.81
2.33E-06
1.91
NA
Dextro-transposition of great arteries (d-TGA)
787
3,139,477
1263
3,768,524
0.748 (0.6843, 0.8176)
−0.3368 (−0.4613, −0.223)
−0.1293 (−0.1686, −0.0914)
41.16
1.40E-10
2.01
NA
Ventricular septal defect
10,038
2,237,688
33,128
5,486,757
0.743 (0.7265, 0.7598)
−0.3439 (−0.3742, −0.3143)
−0.08 (−0.0856, −0.0744)
681.68
0.0033
2.02
NA
Hypospadias
19,468
4,144,576
34,580
5,427,594
0.7373 (0.7244, 0.7504)
−0.3541 (−0.378, −0.3306)
−0.1275 (−0.1347, −0.1205)
1159.93
1.38E-05
2.05
NA
Common truncus (truncus arteriosus)
265
3,819,026
521
5,470,721
0.7286 (0.6285, 0.8447)
−0.3724 (−0.5911, −0.1838)
−0.1256 (−0.1831, −0.0708)
17.75
2.51E-05
2.09
NA
Atrial septal defect
17,822
3,769,242
36,035
5,426,139
0.712 (0.6993, 0.7249)
−0.4019 (−0.4272, −0.377)
−0.133 (−0.1397, −0.1263)
1381.73
1.09E-08
2.15
NA
Microcephalus
595
955,403
1996
2,276,660
0.7103 (0.6482, 0.7785)
−0.4074 (−0.5423, −0.2843)
−0.0936 (−0.1168, −0.0708)
54.10
1.90E-13
2.16
NA
Reduction deformity, Upper limbs
381
998,572
1239
2,277,417
0.7013 (0.6252, 0.7867)
−0.4256 (−0.5991, −0.271)
−0.1001 (−0.1302, −0.0708)
37.05
1.15E-09
2.20
NA
Anophthalmia/microphthalmia
1081
3,720,258
2643
5,328,083
0.5858 (0.5457, 0.6287)
−0.7068 (−0.8319, −0.5902)
−0.2052 (−0.2302, −0.1807)
224.65
1.48E-12
2.81
NA
Patent ductus arteriosus
3025
952,973
10,938
1,995,801
0.5792 (0.5563, 0.603)
−0.7226 (−0.7932, −0.6547)
−0.1565 (−0.1667, −0.1465)
721.65
5.95E-39
2.84
NA
Craniosynostosis
709
1,970,408
1706
2,570,932
0.5423 (0.4968, 0.5919)
−0.8436 (−1.0123, −0.689)
−0.2477 (−0.2802, −0.216)
193.44
7.18E-05
3.09
NA
Renal agenesis/hypoplasia
1705
3,788,008
4576
5,457,598
0.5368 (0.5078, 0.5675)
−0.8621 (−0.9686, −0.7614)
−0.234 (−0.2528, −0.2155)
496.12
0.0028
3.13
NA
Tricuspid valve atresia and stenosis
643
3,773,660
1767
5,518,118
0.5321 (0.4862, 0.5824)
−0.879 (−1.0565, −0.7169)
−0.2345 (−0.2646, −0.2052)
193.92
3.93E-04
3.16
NA
Table 5
Numbers, Calculated Rates, Significance Levels and E-Values of Highest v. Lowest Cannabidiol Exposure Quintiles
Congenital Anomaly
Numbers
Calculated Rates
Significance
E-Values
Highest Defect Count
Highest Not Defect Count
Lowest Defect Count
Lowest Not Defect Count
Prevalence Ratio (C.I.)
Atrributable Fraction in the Exposed (C.I.)
Population Attributable Risk (C.I.)
Chi Squared
P-Value
E-Value - Point
E-Value - Lower
Obstructive genitourinary defect
7247
2,484,854
145
95,592
1.9227 (1.631, 2.2665)
0.4792 (0.3862, 0.5581)
0.4698 (0.3771, 0.5486)
62.8480
2.22E-15
3.25
2.64
Pulmonary valve atresia
396
2,552,400
462
4,024,227
1.3514 (1.1817, 1.5455)
0.26 (0.1537, 0.3529)
0.12 (0.0638, 0.1729)
19.4818
1.02E-05
2.04
1.64
Small intestinal atresia/stenosis
566
1,402,095
1224
3,815,218
1.2583 (1.1389, 1.3901)
0.2052 (0.122, 0.2806)
0.0649 (0.035, 0.0939)
20.5107
5.93E-06
1.83
1.54
Cloacal exstrophy
238
834,373
661
3,007,409
1.2978 (1.1191, 1.5051)
0.2294 (0.1064, 0.3355)
0.0607 (0.0232, 0.0969)
11.9548
5.45E-04
1.92
1.48
Cleft lip with and without cleft palate
3437
3,791,717
33
55,337
1.52 (1.0787, 2.1418)
0.3419 (0.0729, 0.5329)
0.3387 (0.0713, 0.529)
5.8113
0.0159
2.41
1.37
Clubfoot
1057
721,190
5114
3,838,593
1.1001 (1.0296, 1.1755)
0.0909 (0.0287, 0.1491)
0.0156 (0.0043, 0.0267)
7.9686
0.0048
1.43
1.20
Biliary atresia
385
5,083,733
265
4,192,774
1.1982 (1.0247, 1.4011)
0.1654 (0.0241, 0.2863)
0.098 (0.0104, 0.1778)
5.1462
0.0233
1.69
1.18
Trisomy 21 (Down syndrome)
7317
5,291,885
5706
4,357,620
1.0559 (1.02, 1.0932)
0.0529 (0.0196, 0.0851)
0.0297 (0.0107, 0.0484)
9.4889
0.0021
1.30
1.16
Double outlet right ventricle
282
1,402,379
745
4,282,993
1.156 (1.008, 1.3258)
0.135 (0.0079, 0.2457)
0.0371 (1e-04, 0.0726)
4.3080
0.0379
1.58
1.10
Diaphragmatic hernia
1433
5,035,560
1143
4,362,183
1.0861 (1.0048, 1.1739)
0.0792 (0.0048, 0.1481)
0.0441 (0.0018, 0.0845)
4.3354
0.0373
1.39
1.07
Trisomy 13
597
5,167,619
443
4,353,779
1.1354 (1.0041, 1.2839)
0.1192 (0.0041, 0.2211)
0.0684 (4e-04, 0.1319)
4.1053
0.0427
1.53
1.07
Single ventricle
136
1,397,584
315
3,963,023
1.2243 (1.0012, 1.497)
0.1832 (0.0012, 0.332)
0.0552 (−0.0038, 0.1108)
3.9021
0.0482
1.75
1.04
Spina bifida without anencephalus
1838
5,297,364
1509
4,361,817
1.0029 (0.9369, 1.0736)
0.0029 (−0.0673, 0.0685)
0.0016 (−0.0364, 0.0382)
0.0070
0.9332
1.06
1.00
Rectal and large intestinal atresia/stenosis
1883
4,468,696
1830
4,361,496
1.0043 (0.9417, 1.071)
0.0043 (−0.0619, 0.0663)
0.0022 (−0.0309, 0.0342)
0.0169
0.8966
1.07
1.00
Anotia/microtia
1049
5,138,925
856
4,221,402
1.0067 (0.9198, 1.1018)
0.0066 (−0.0872, 0.0924)
0.0036 (−0.0471, 0.052)
0.0208
0.8853
1.09
1.00
Transposition of great arteries
1324
4,204,444
1356
4,361,970
1.013 (0.9391, 1.0927)
0.0128 (−0.0648, 0.0848)
0.0063 (−0.0315, 0.0428)
0.1114
0.7385
1.13
1.00
Aortic valve stenosis
961
5,083,758
806
4,362,520
1.0232 (0.9317, 1.1236)
0.0226 (−0.0733, 0.11)
0.0123 (−0.0393, 0.0613)
0.2296
0.6318
1.18
1.00
Hypoplastic left heart syndrome
1308
5,297,894
1048
4,362,278
1.0277 (0.9475, 1.1147)
0.0269 (−0.0554, 0.1029)
0.0149 (−0.0305, 0.0584)
0.4336
0.5102
1.20
1.00
Cleft lip alone
478
1,444,653
1378
4,282,360
1.0282 (0.9266, 1.141)
0.0275 (−0.0792, 0.1235)
0.0071 (−0.0199, 0.0333)
0.2753
0.5998
1.20
1.00
Trisomy 18
1219
5,196,590
983
4,362,343
1.041 (0.9571, 1.1323)
0.0394 (−0.0448, 0.1168)
0.0218 (−0.0248, 0.0663)
0.8786
0.3486
1.25
1.00
Atrioventricular septal defect
2286
5,034,707
1877
4,361,449
1.055 (0.9925, 1.1215)
0.0521 (−0.0075, 0.1083)
0.0286 (−0.0045, 0.0607)
2.9581
0.0854
1.30
1.00
Patent ductus arteriosus
7335
2,484,766
111
40,496
1.077 (0.8927, 1.2993)
0.0713 (−0.1199, 0.2298)
0.0702 (−0.1181, 0.2268)
0.5999
0.4386
1.36
1.00
Total anomalous pulmonary venous connection
389
3,073,253
459
4,095,548
1.1294 (0.9867, 1.2928)
0.1146 (−0.0135, 0.2264)
0.0526 (−0.008, 0.1095)
3.1216
0.0773
1.51
1.00
Deletion 22q11.2
53
718,890
216
3,557,414
1.2142 (0.8991, 1.6398)
0.1764 (−0.1122, 0.3901)
0.0348 (−0.0241, 0.0902)
1.6082
0.2047
1.72
1.00
Congenital hip dislocation
1807
2,126,749
27
40,580
1.277 (0.8732, 1.8676)
0.2168 (−0.1452, 0.4643)
0.2136 (−0.1434, 0.4591)
1.5973
0.2063
1.87
1.00
Hirschsprung disease (congenital megacolon)
591
2,581,794
17
95,720
1.2889 (0.7958, 2.0875)
0.2241 (−0.2565, 0.5209)
0.2178 (−0.2497, 0.5105)
1.0699
0.3010
1.90
1.00
Gastroschisis
2169
4,985,466
1842
4,215,660
0.9957 (0.9357, 1.0595)
−0.0043 (−0.0686, 0.0561)
−0.0023 (−0.0366, 0.0308)
0.0185
0.8919
1.07
NA
Cleft lip with cleft palate
1220
2,126,674
2452
4,225,916
0.9887 (0.9231, 1.059)
−0.0114 (−0.0833, 0.0557)
−0.0038 (−0.027, 0.0188)
0.1054
0.7455
1.12
NA
Coarctation of the aorta
2728
5,193,099
2332
4,360,994
0.9824 (0.9295, 1.0382)
−0.0179 (−0.0758, 0.0368)
−0.0097 (−0.0402, 0.02)
0.3976
0.5283
1.15
NA
Anencephalus
920
5,240,706
775
4,279,449
0.9694 (0.881, 1.0666)
−0.0316 (−0.135, 0.0624)
−0.0172 (−0.0713, 0.0343)
0.4074
0.5233
1.21
NA
Esophageal atresia/tracheoesophageal fistula
1127
5,138,847
988
4,362,338
0.9683 (0.889, 1.0547)
−0.0327 (−0.1248, 0.0518)
−0.0174 (−0.0648, 0.0278)
0.5454
0.4602
1.22
NA
Tetralogy of Fallot
2121
5,286,622
1815
4,361,511
0.9641 (0.9055, 1.0265)
−0.0372 (−0.1043, 0.0258)
−0.0201 (−0.0551, 0.0138)
1.3068
0.2530
1.23
NA
Encephalocele
411
4,911,620
370
4,241,015
0.9591 (0.8335, 1.1038)
−0.0426 (−0.1998, 0.094)
−0.0224 (−0.1008, 0.0504)
0.3388
0.5605
1.25
NA
Congenital posterior urethral valves
138
857,092
685
4,036,200
0.9487 (0.7901, 1.1391)
−0.0541 (−0.2655, 0.1221)
−0.0091 (−0.0405, 0.0214)
0.3184
0.5725
1.29
NA
Interrupted aortic arch
86
1,397,634
247
3,744,641
0.9329 (0.7299, 1.1923)
−0.072 (−0.3701, 0.1613)
−0.0186 (−0.0852, 0.044)
0.3082
0.5788
1.35
NA
Dextro-transposition of great arteries (d-TGA)
710
3,124,610
928
3,803,093
0.9312 (0.8445, 1.0268)
−0.0738 (−0.1841, 0.0261)
−0.032 (−0.0767, 0.0108)
2.0431
0.1529
1.36
NA
Congenital cataract
718
5,120,845
664
4,243,840
0.8961 (0.8064, 0.9959)
−0.1159 (−0.2401, −0.0041)
−0.0602 (−0.1199, −0.0036)
4.1522
0.0416
1.48
NA
Bladder exstrophy
105
5,028,475
92
3,896,531
0.8844 (0.6685, 1.17)
−0.1307 (−0.4959, 0.1453)
−0.0697 (−0.2418, 0.0786)
0.7411
0.3893
1.52
NA
Cleft palate alone
2399
4,579,165
2605
4,360,721
0.877 (0.8297, 0.927)
−0.1402 (−0.2052, −0.0787)
−0.0672 (−0.096, −0.0392)
21.5360
3.47E-06
1.54
NA
Pyloric stenosis
3934
2,242,962
192
95,545
0.8728 (0.755, 1.009)
−0.1454 (−0.3238, 0.0089)
−0.1387 (−0.3071, 0.0081)
3.3864
0.0657
1.55
NA
Pulmonary valve atresia and stenosis
3896
5,109,183
3880
4,359,446
0.8568 (0.8195, 0.8957)
−0.167 (−0.22, −0.1163)
−0.0837 (−0.1081, −0.0598)
46.5051
9.14E-12
1.61
NA
Limb deficiencies (reduction defects)
558
1,485,079
1830
4,142,972
0.8506 (0.7737, 0.9352)
−0.1755 (−0.2924, −0.0692)
−0.041 (−0.0643, −0.0182)
11.2100
8.14E-04
1.63
NA
Hydrocephalus without spina bifida
2149
3,618,806
68
95,669
0.8355 (0.6562, 1.0637)
−0.1968 (−0.5234, 0.0598)
−0.1907 (−0.5046, 0.0576)
2.1340
0.1441
1.68
NA
Amniotic Bands
270
2,585,899
12
95,725
0.8329 (0.4672, 1.485)
−0.2006 (−1.1404, 0.3266)
−0.1921 (−1.0736, 0.3147)
0.3851
0.5349
1.69
NA
Ebstein anomaly
334
5,107,133
323
4,105,245
0.8312 (0.7133, 0.9686)
−0.2031 (−0.4019, −0.0324)
−0.1032 (−0.1924, −0.0207)
5.6284
0.0177
1.70
NA
Choanal atresia
521
5,096,396
542
4,311,319
0.8132 (0.721, 0.9171)
−0.2297 (−0.3868, −0.0904)
−0.1126 (−0.1801, −0.0489)
11.4006
7.34E-04
1.76
NA
Omphalocele
759
4,673,203
785
3,901,285
0.8072 (0.7305, 0.8919)
−0.2388 (−0.3688, −0.1212)
−0.1174 (−0.1736, −0.0639)
17.7733
2.49E-05
1.78
NA
Common truncus (truncus arteriosus)
278
4,620,690
336
4,240,246
0.7593 (0.6477, 0.89)
−0.317 (−0.5439, −0.1235)
−0.1435 (−0.2289, −0.0642)
11.6117
6.55E-04
1.96
NA
Reduction deformity, Lower limbs
537
3,780,505
18
95,719
0.7554 (0.4722, 1.2082)
−0.3238 (−1.1173, 0.1723)
−0.3133 (−1.0687, 0.1662)
1.3798
0.2401
1.98
NA
Ventricular septal defect
14,557
3,929,002
21,430
4,341,896
0.7507 (0.735, 0.7667)
−0.3305 (−0.3588, −0.3029)
−0.1337 (−0.1434, −0.1241)
714.8336
2.2e-320
1.99
NA
Craniosynostosis
470
1,120,061
1679
2,992,172
0.7478 (0.6751, 0.8284)
−0.337 (−0.481, −0.2071)
−0.0737 (−0.098, −0.05)
31.2156
2.31E-08
2.01
NA
Hypospadias
24,587
5,157,522
27,515
4,196,875
0.7271 (0.7147, 0.7398)
−0.3728 (−0.3965, −0.3495)
−0.1759 (−0.1855, −0.1664)
1321.8209
1.02E-289
2.09
NA
Anophthalmia/microphthalmia
561
5,108,305
636
4,192,403
0.7239 (0.6462, 0.811)
−0.3813 (−0.5474, −0.2331)
−0.1787 (−0.2431, −0.1176)
31.3790
2.12E-08
2.11
NA
Turner syndrome
125
845,663
838
4,079,070
0.7195 (0.5962, 0.8683)
−0.3898 (−0.6771, −0.1517)
−0.0506 (−0.0765, −0.0253)
11.8932
5.63E-04
2.13
NA
Microcephalus
1436
2,490,665
81
95,656
0.6809 (0.5443, 0.8518)
−0.4683 (−0.8365, −0.1739)
−0.4433 (−0.7838, −0.1678)
11.4591
7.11E-04
2.30
NA
Holoprosencephaly
198
1,372,610
882
3,954,496
0.6468 (0.5544, 0.7545)
−0.5461 (−0.8037, −0.3252)
−0.1001 (−0.1316, −0.0695)
31.1923
2.34E-08
2.46
NA
Epispadias
230
2,250,082
41
257,008
0.6408 (0.4596, 0.8933)
−0.5606 (−1.1756, −0.1194)
−0.4758 (−0.9565, −0.1132)
7.0075
0.0081
2.50
NA
Renal agenesis/hypoplasia
1586
5,011,917
2240
4,361,086
0.6161 (0.5777, 0.657)
−0.6228 (−0.7306, −0.5217)
−0.2582 (−0.2922, −0.2251)
222.0395
1.63E-50
2.63
NA
Atrial septal defect
20,411
5,016,582
33,798
4,329,528
0.5212 (0.5122, 0.5304)
−0.9115 (−0.9449, −0.8787)
−0.3432 (−0.352, −0.3345)
5563.5773
2.2e-320
3.23
NA
Reduction deformity, Upper limbs
1001
3,765,890
50
95,687
0.5087 (0.3829, 0.6758)
−0.9653 (−1.6107, −0.4795)
−0.9194 (−1.5155, −0.4646)
22.5864
2.01E-06
3.34
NA
Tricuspid valve atresia and stenosis
510
5,059,825
973
4,362,353
0.4519 (0.406, 0.503)
−1.2126 (−1.4628, −0.9878)
−0.417 (−0.4702, −0.3658)
222.4058
1.36E-50
3.85
NA
As shown in Table 4 six cardiovascular anomalies, five chromosomal, five gastrointestinal, two urinary, two limb, and one each facial (Holoprosencephaly), body wall (Diaphragmatic hernia) and CNS (spina bifida without anencephalus) anomaly are accompanied by higher E-Values in the high cannabis use quintiles. Interestingly both congenital posterior urethral vales and diaphragmatic hernia and several gastrointestinal anomalies appear both on this list and on the list of elevated E-Values shown in Table 2 where cannabis exposure is treated as a continuous covariate.
As indicated in Table 5 12 anomalies including three cardiovascular (pulmonary valve atresia, double outlet right ventricle, single ventricle), three gastrointestinal (small intestinal atresia /stenosis, biliary atresia, cloacal extrophy), two chromosomal (Trisomies 14 and 21) and one each limb (clubfoot), body wall (diaphragmatic hernia), face (cleft lip with and without cleft palate) and genitourinary (obstructive genitourinary defect) anomaly were noted to have elevated minimum E-Values in highest cannabidiol exposure quintiles.
For ease of comparison these Prevalence Ratios are presented together by substance in Table 6. The prevalence ratios for cannabidiol appear in the right hand column and are listed in descending order.
Table 6
Prevalence Ratios by Substance
Congenital Anomaly
Cigarettes Prevalence Ratio
Binge Alcohol Prevalence Ratio
Analgesics Prevalence Ratio
Ccoaine Prevalence Ratio
Cannabis Prevalence Ratio
Cannabidiol Prevalence Ratio
Obstructive genitourinary defect
0.92 (0.87, 0.97)
1.02 (0.97, 1.07)
0.9 (0.85, 0.94)
1.17 (1.11, 1.23)
0.86 (0.82, 0.9)
1.92 (1.63, 2.27)
Cleft lip with and without cleft palate
1.06 (0.98, 1.13)
0.95 (0.88, 1.02)
1.3 (1.2, 1.41)
1.02 (0.94, 1.11)
0.94 (0.87, 1.01)
1.52 (1.08, 2.14)
Pulmonary valve atresia
1.06 (0.91, 1.22)
0.45 (0.38, 0.54)
1.64 (1.46, 1.85)
0.97 (0.86, 1.1)
1.27 (1.14, 1.43)
1.35 (1.18, 1.55)
Cloacal exstrophy
2.84 (2.44, 3.31)
0.85 (0.73, 0.98)
1.61 (1.41, 1.83)
0.63 (0.54, 0.72)
4.85 (4.08, 5.77)
1.3 (1.12, 1.51)
Hirschsprung disease (congenital megacolon)
1.12 (0.95, 1.33)
0.57 (0.47, 0.7)
1.06 (0.89, 1.27)
1.01 (0.84, 1.21)
1.46 (1.24, 1.72)
1.29 (0.8, 2.09)
Congenital hip dislocation
0.93 (0.84, 1.04)
1.09 (0.97, 1.24)
0.95 (0.85, 1.06)
1.85 (1.65, 2.07)
2.28 (2.08, 2.51)
1.28 (0.87, 1.87)
Small intestinal atresia/stenosis
0.86 (0.77, 0.97)
0.87 (0.77, 0.97)
1.09 (0.99, 1.2)
1.1 (1, 1.21)
1.22 (1.12, 1.33)
1.26 (1.14, 1.39)
Single ventricle
0.84 (0.66, 1.05)
0.46 (0.36, 0.59)
1.07 (0.93, 1.23)
0.81 (0.7, 0.93)
1.21 (1.06, 1.39)
1.22 (1, 1.5)
Deletion 22q11.2
0.59 (0.45, 0.77)
1.26 (0.98, 1.6)
2.93 (2.39, 3.58)
1.81 (1.46, 2.25)
1.36 (1.09, 1.68)
1.21 (0.9, 1.64)
Biliary atresia
1.02 (0.87, 1.2)
0.63 (0.51, 0.77)
0.88 (0.74, 1.05)
1.12 (0.94, 1.32)
1.19 (1.02, 1.39)
1.2 (1.02, 1.4)
Double outlet right ventricle
1.04 (0.92, 1.17)
0.69 (0.6, 0.79)
1.12 (1.01, 1.23)
0.91 (0.82, 1.01)
1.19 (1.08, 1.31)
1.16 (1.01, 1.33)
Trisomy 13
0.62 (0.53, 0.71)
0.97 (0.85, 1.1)
0.86 (0.82, 0.9)
1.76 (1.67, 1.85)
1.29 (1.23, 1.35)
1.14 (1, 1.28)
Total anomalous pulmonary venous connection
0.62 (0.52, 0.74)
0.62 (0.5, 0.75)
1.44 (1.24, 1.66)
1.31 (1.13, 1.52)
1.05 (0.93, 1.19)
1.13 (0.99, 1.29)
Clubfoot
1.02 (0.97, 1.08)
0.88 (0.83, 0.93)
1.03 (0.97, 1.1)
0.99 (0.94, 1.05)
1.07 (1.01, 1.14)
1.1 (1.03, 1.18)
Diaphragmatic hernia
1.22 (1.13, 1.33)
0.83 (0.76, 0.91)
1.15 (1.06, 1.26)
0.87 (0.79, 0.95)
1.24 (1.15, 1.34)
1.09 (1, 1.17)
Patent ductus arteriosus
0.96 (0.92, 1)
0.72 (0.69, 0.75)
1.13 (1.08, 1.18)
0.79 (0.75, 0.82)
0.58 (0.56, 0.6)
1.08 (0.89, 1.3)
Trisomy 21 (Down syndrome)
0.83 (0.8, 0.87)
1.03 (0.99, 1.07)
1.02 (0.99, 1.04)
1.13 (1.11, 1.16)
1.14 (1.12, 1.17)
1.06 (1.02, 1.09)
Atrioventricular septal defect
0.95 (0.89, 1.01)
0.79 (0.74, 0.84)
1.07 (1.01, 1.13)
0.92 (0.87, 0.98)
1.05 (1, 1.11)
1.06 (0.99, 1.12)
Trisomy 18
0.66 (0.6, 0.73)
0.89 (0.82, 0.98)
1.06 (1.02, 1.1)
1.34 (1.29, 1.39)
1.31 (1.27, 1.35)
1.04 (0.96, 1.13)
Cleft lip alone
1.06 (0.96, 1.17)
1.04 (0.94, 1.15)
1.18 (1.08, 1.28)
0.82 (0.75, 0.89)
0.97 (0.9, 1.05)
1.03 (0.93, 1.14)
Hypoplastic left heart syndrome
1.2 (1.1, 1.3)
0.69 (0.62, 0.75)
1.12 (1.04, 1.19)
0.91 (0.85, 0.98)
1.1 (1.03, 1.17)
1.03 (0.95, 1.11)
Aortic valve stenosis
0.96 (0.87, 1.06)
0.71 (0.64, 0.8)
1.59 (1.48, 1.71)
1.03 (0.96, 1.11)
0.9 (0.84, 0.96)
1.02 (0.93, 1.12)
Transposition of great arteries
1.25 (1.16, 1.36)
0.8 (0.73, 0.87)
1.23 (1.14, 1.32)
0.85 (0.79, 0.91)
1.01 (0.94, 1.09)
1.01 (0.94, 1.09)
Anotia/microtia
0.37 (0.32, 0.42)
0.87 (0.77, 0.97)
1.38 (1.3, 1.46)
1.62 (1.53, 1.71)
1 (0.96, 1.05)
1.01 (0.92, 1.1)
Rectal and large intestinal atresia/stenosis
1.2 (1.12, 1.28)
0.84 (0.78, 0.9)
1.08 (1, 1.16)
0.87 (0.81, 0.94)
0.9 (0.85, 0.96)
1 (0.94, 1.07)
Spina bifida without anencephalus
1.04 (0.97, 1.11)
0.83 (0.77, 0.9)
1.36 (1.3, 1.42)
1 (0.96, 1.05)
1.05 (1.01, 1.09)
1 (0.94, 1.07)
Gastroschisis
1 (0.94, 1.07)
0.89 (0.83, 0.96)
1.47 (1.39, 1.56)
0.97 (0.91, 1.03)
0.93 (0.88, 0.98)
1 (0.94, 1.06)
Cleft lip with cleft palate
1.14 (1.06, 1.22)
0.86 (0.79, 0.93)
1.37 (1.28, 1.46)
0.93 (0.87, 0.99)
0.96 (0.9, 1.02)
0.99 (0.92, 1.06)
Coarctation of the aorta
1.16 (1.09, 1.23)
0.7 (0.66, 0.75)
1.16 (1.1, 1.22)
0.87 (0.82, 0.92)
1.38 (1.32, 1.45)
0.98 (0.93, 1.04)
Anencephalus
0.89 (0.81, 0.99)
0.7 (0.63, 0.78)
1.36 (1.29, 1.42)
1.03 (0.99, 1.08)
0.93 (0.89, 0.96)
0.97 (0.88, 1.07)
Esophageal atresia/tracheoesophageal fistula
1.08 (0.99, 1.18)
1.06 (0.97, 1.16)
1.04 (0.95, 1.14)
1.01 (0.92, 1.1)
1.11 (1.02, 1.21)
0.97 (0.89, 1.05)
Tetralogy of Fallot
1.1 (1.03, 1.17)
0.78 (0.73, 0.84)
1.03 (0.97, 1.1)
0.99 (0.93, 1.05)
0.96 (0.91, 1.02)
0.96 (0.91, 1.03)
Encephalocele
1.21 (1.05, 1.39)
0.68 (0.58, 0.81)
1.08 (0.98, 1.18)
0.91 (0.83, 1)
0.94 (0.86, 1.02)
0.96 (0.83, 1.1)
Congenital posterior urethral valves
1.11 (0.95, 1.29)
0.61 (0.52, 0.71)
1.06 (0.92, 1.23)
0.84 (0.73, 0.97)
1.33 (1.15, 1.54)
0.95 (0.79, 1.14)
Interrupted aortic arch
1.27 (0.99, 1.62)
0.85 (0.65, 1.11)
1.38 (1.12, 1.69)
0.81 (0.65, 1)
1.04 (0.84, 1.27)
0.93 (0.73, 1.19)
Dextro-transposition of great arteries (d-TGA)
1.19 (1.08, 1.33)
0.89 (0.79, 1)
0.96 (0.87, 1.07)
0.89 (0.8, 0.98)
0.75 (0.68, 0.82)
0.93 (0.84, 1.03)
Congenital cataract
0.93 (0.83, 1.04)
0.91 (0.81, 1.02)
1.09 (0.97, 1.22)
0.97 (0.87, 1.08)
0.94 (0.86, 1.04)
0.9 (0.81, 1)
Bladder exstrophy
1.57 (1.19, 2.05)
0.92 (0.69, 1.24)
1.16 (0.86, 1.57)
0.86 (0.62, 1.18)
1.03 (0.75, 1.4)
0.88 (0.67, 1.17)
Cleft palate alone
1.23 (1.16, 1.31)
1.01 (0.95, 1.08)
1.16 (1.09, 1.22)
0.97 (0.91, 1.02)
0.96 (0.91, 1.01)
0.88 (0.83, 0.93)
Pyloric stenosis
1.72 (1.63, 1.82)
0.35 (0.32, 0.38)
1.9 (1.8, 2.01)
0.66 (0.62, 0.71)
0.89 (0.84, 0.95)
0.87 (0.75, 1.01)
Pulmonary valve atresia and stenosis
1 (0.95, 1.05)
0.71 (0.67, 0.75)
1.02 (0.97, 1.07)
0.87 (0.83, 0.92)
0.88 (0.84, 0.92)
0.86 (0.82, 0.9)
Limb deficiencies (reduction defects)
1.09 (1, 1.19)
0.87 (0.79, 0.95)
1.07 (1, 1.15)
0.85 (0.79, 0.91)
0.77 (0.73, 0.82)
0.85 (0.77, 0.94)
Hydrocephalus without spina bifida
1.34 (1.22, 1.47)
1.03 (0.94, 1.14)
0.87 (0.8, 0.95)
0.97 (0.89, 1.06)
1.05 (0.97, 1.12)
0.84 (0.66, 1.06)
Amniotic Bands
0.95 (0.67, 1.33)
0.65 (0.49, 0.86)
1.49 (1.04, 2.13)
0.67 (0.44, 1.03)
0.84 (0.58, 1.23)
0.83 (0.47, 1.49)
Ebstein anomaly
1.13 (0.97, 1.33)
0.71 (0.59, 0.85)
1.33 (1.16, 1.53)
0.92 (0.8, 1.05)
0.88 (0.78, 1.01)
0.83 (0.71, 0.97)
Choanal atresia
1.4 (1.23, 1.58)
1.02 (0.9, 1.17)
0.83 (0.74, 0.93)
0.88 (0.78, 0.99)
0.78 (0.69, 0.87)
0.81 (0.72, 0.92)
Omphalocele
1.19 (1.07, 1.31)
0.79 (0.71, 0.87)
1.07 (1.01, 1.15)
0.85 (0.79, 0.91)
0.92 (0.87, 0.98)
0.81 (0.73, 0.89)
Common truncus (truncus arteriosus)
2.1 (1.8, 2.46)
0.58 (0.48, 0.7)
1.02 (0.87, 1.2)
0.72 (0.61, 0.85)
0.73 (0.63, 0.84)
0.76 (0.65, 0.89)
Reduction deformity, Lower limbs
1.22 (1.03, 1.45)
0.94 (0.78, 1.13)
1.04 (0.88, 1.24)
0.82 (0.69, 0.98)
0.84 (0.72, 0.98)
0.76 (0.47, 1.21)
Ventricular septal defect
1.19 (1.17, 1.22)
0.84 (0.82, 0.86)
0.85 (0.83, 0.87)
0.79 (0.77, 0.81)
0.74 (0.73, 0.76)
0.75 (0.73, 0.77)
Craniosynostosis
1.27 (1.14, 1.42)
0.61 (0.54, 0.69)
1.12 (1.01, 1.24)
0.98 (0.89, 1.08)
0.54 (0.5, 0.59)
0.75 (0.68, 0.83)
Hypospadias
1.59 (1.56, 1.62)
0.87 (0.85, 0.89)
0.98 (0.96, 1)
1 (0.98, 1.02)
0.74 (0.72, 0.75)
0.73 (0.71, 0.74)
Anophthalmia/microphthalmia
0.79 (0.69, 0.91)
1.03 (0.9, 1.18)
1.18 (1.08, 1.27)
1.17 (1.07, 1.27)
0.59 (0.55, 0.63)
0.72 (0.65, 0.81)
Turner syndrome
0.61 (0.53, 0.71)
1.14 (1.01, 1.3)
1.01 (0.95, 1.08)
1.11 (1.04, 1.19)
1.57 (1.47, 1.66)
0.72 (0.6, 0.87)
Microcephalus
1.32 (1.18, 1.46)
0.78 (0.7, 0.87)
1.1 (0.98, 1.23)
0.91 (0.82, 1.02)
0.71 (0.65, 0.78)
0.68 (0.54, 0.85)
Holoprosencephaly
1.92 (1.71, 2.16)
0.56 (0.49, 0.65)
0.85 (0.8, 0.9)
0.39 (0.36, 0.41)
1.24 (1.17, 1.31)
0.65 (0.55, 0.75)
Epispadias
0.8 (0.62, 1.04)
1.22 (0.92, 1.62)
0.69 (0.53, 0.91)
1.37 (1.04, 1.8)
1.31 (1.03, 1.67)
0.64 (0.46, 0.89)
Renal agenesis/hypoplasia
1.25 (1.17, 1.34)
0.92 (0.86, 0.99)
0.95 (0.9, 1)
0.84 (0.8, 0.89)
0.54 (0.51, 0.57)
0.62 (0.58, 0.66)
Atrial septal defect
2.53 (2.49, 2.57)
0.56 (0.54, 0.57)
1.31 (1.29, 1.34)
0.71 (0.7, 0.73)
0.71 (0.7, 0.72)
0.52 (0.51, 0.53)
Reduction deformity, Upper limbs
0.9 (0.79, 1.03)
0.95 (0.83, 1.09)
1.02 (0.9, 1.16)
0.83 (0.73, 0.94)
0.7 (0.63, 0.79)
0.51 (0.38, 0.68)
Tricuspid valve atresia and stenosis
0.67 (0.59, 0.76)
0.91 (0.81, 1.03)
0.61 (0.56, 0.68)
1.17 (1.07, 1.29)
0.53 (0.49, 0.58)
0.45 (0.41, 0.5)
Aniridia
1.24 (0.65, 2.38)
0.34 (0.15, 0.78)
1.84 (1.29, 2.63)
1.72 (1.14, 2.6)
1.45 (0.94, 2.24)
–
Table 7 presents the Attributable Fractions in the Exposed (AFEs) in a similar manner. One notes that they descend from a strikingly high rate of 79.38% for cloacal extrophy after cannabis exposure.
Table 7
Attributable Fraction in the Exposed by Substance
Congenital Anomaly
Cigarettes AFE
Binge Alcohol AFE
Analgesics AFE
Cocaine AFE
Cannabis AFE
Cannabidiol AFE
Obstructive genitourinary defect
−0.09 (−0.15, −0.03)
0.02 (−0.03, 0.07)
−0.11 (−0.17, −0.06)
0.15 (0.1, 0.19)
−0.16 (−0.22, −0.12)
0.48 (0.39, 0.56)
Cleft lip with and without cleft palate
0.05 (−0.02, 0.12)
−0.06 (−0.14, 0.02)
0.23 (0.17, 0.29)
0.02 (−0.06, 0.1)
−0.07 (−0.15, 0.01)
0.34 (0.07, 0.53)
Pulmonary valve atresia
0.05 (−0.09, 0.18)
−1.21 (−1.63, −0.86)
0.39 (0.32, 0.46)
−0.03 (−0.16, 0.09)
0.22 (0.12, 0.3)
0.26 (0.15, 0.35)
Cloacal exstrophy
0.65 (0.59, 0.7)
−0.18 (−0.36, −0.02)
0.38 (0.29, 0.45)
−0.6 (−0.84, −0.39)
0.79 (0.75, 0.83)
0.23 (0.11, 0.34)
Hirschsprung disease (congenital megacolon)
0.11 (−0.06, 0.25)
−0.75 (−1.12, −0.44)
0.06 (−0.12, 0.21)
0.01 (−0.2, 0.17)
0.31 (0.19, 0.42)
0.22 (−0.26, 0.52)
Congenital hip dislocation
−0.07 (−0.19, 0.04)
0.09 (−0.03, 0.19)
−0.05 (−0.18, 0.06)
0.46 (0.4, 0.52)
0.56 (0.52, 0.6)
0.22 (−0.15, 0.46)
Small intestinal atresia/stenosis
−0.16 (−0.29, −0.03)
−0.15 (−0.29, −0.03)
0.08 (−0.01, 0.16)
0.09 (0, 0.17)
0.18 (0.11, 0.25)
0.21 (0.12, 0.28)
Single ventricle
−0.2 (−0.51, 0.05)
−1.17 (−1.77, −0.7)
0.06 (−0.08, 0.19)
−0.24 (−0.43, −0.07)
0.18 (0.05, 0.28)
0.18 (0, 0.33)
Deletion 22q11.2
−0.69 (−1.2, −0.3)
0.2 (−0.02, 0.38)
0.66 (0.58, 0.72)
0.45 (0.31, 0.56)
0.26 (0.09, 0.41)
0.18 (−0.11, 0.39)
Biliary atresia
0.02 (−0.15, 0.17)
−0.6 (−0.96, −0.31)
−0.13 (−0.34, 0.05)
0.1 (−0.06, 0.24)
0.16 (0.02, 0.28)
0.17 (0.02, 0.29)
Double outlet right ventricle
0.03 (−0.09, 0.15)
−0.46 (−0.67, −0.27)
0.1 (0.01, 0.19)
−0.1 (−0.21, 0.01)
0.16 (0.07, 0.24)
0.13 (0.01, 0.25)
Trisomy 13
−0.62 (−0.87, −0.41)
−0.04 (−0.18, 0.09)
−0.16 (−0.23, −0.11)
0.43 (0.4, 0.46)
0.22 (0.18, 0.26)
0.12 (0, 0.22)
Total anomalous pulmonary venous connection
−0.6 (−0.91, −0.34)
−0.62 (−0.98, −0.33)
0.3 (0.19, 0.4)
0.24 (0.11, 0.34)
0.05 (−0.08, 0.16)
0.11 (−0.01, 0.23)
Clubfoot
0.02 (−0.04, 0.07)
−0.14 (−0.2, −0.08)
0.03 (−0.03, 0.09)
−0.01 (−0.07, 0.05)
0.07 (0.01, 0.12)
0.09 (0.03, 0.15)
Diaphragmatic hernia
0.18 (0.12, 0.25)
−0.21 (−0.32, −0.1)
0.13 (0.05, 0.2)
−0.15 (−0.26, −0.06)
0.2 (0.13, 0.26)
0.08 (0, 0.15)
Patent ductus arteriosus
−0.05 (−0.09, 0)
−0.39 (−0.45, −0.33)
0.11 (0.07, 0.15)
−0.27 (−0.33, −0.21)
−0.72 (−0.79, −0.65)
0.07 (−0.12, 0.23)
Trisomy 21 (Down syndrome)
−0.2 (−0.25, −0.15)
0.03 (−0.01, 0.07)
0.02 (−0.01, 0.04)
0.12 (0.1, 0.14)
0.12 (0.11, 0.14)
0.05 (0.02, 0.09)
Atrioventricular septal defect
−0.06 (−0.13, 0.01)
−0.27 (−0.36, −0.18)
0.06 (0.01, 0.12)
−0.08 (−0.15, −0.02)
0.05 (0, 0.1)
0.05 (−0.01, 0.11)
Trisomy 18
−0.52 (−0.67, −0.38)
−0.12 (−0.22, −0.02)
0.05 (0.02, 0.09)
0.25 (0.23, 0.28)
0.24 (0.21, 0.26)
0.04 (−0.04, 0.12)
Cleft lip alone
0.06 (−0.04, 0.15)
0.04 (−0.07, 0.13)
0.15 (0.07, 0.22)
−0.23 (−0.33, −0.13)
−0.03 (−0.12, 0.04)
0.03 (−0.08, 0.12)
Hypoplastic left heart syndrome
0.17 (0.09, 0.23)
−0.46 (−0.61, −0.32)
0.1 (0.04, 0.16)
−0.1 (−0.18, −0.03)
0.09 (0.03, 0.15)
0.03 (−0.06, 0.1)
Aortic valve stenosis
−0.04 (−0.16, 0.06)
−0.4 (−0.57, −0.25)
0.37 (0.32, 0.42)
0.03 (−0.04, 0.1)
−0.12 (−0.19, −0.04)
0.02 (−0.07, 0.11)
Transposition of great arteries
0.2 (0.14, 0.26)
−0.25 (−0.36, −0.14)
0.18 (0.12, 0.24)
−0.18 (−0.27, −0.09)
0.01 (−0.06, 0.08)
0.01 (−0.06, 0.08)
Anotia/microtia
−1.73 (−2.1, −1.4)
−0.15 (−0.29, −0.03)
0.28 (0.23, 0.32)
0.38 (0.35, 0.42)
0 (−0.04, 0.04)
0.01 (−0.09, 0.09)
Rectal and large intestinal atresia/stenosis
0.17 (0.11, 0.22)
−0.19 (−0.28, −0.11)
0.07 (0, 0.14)
−0.15 (−0.24, −0.07)
−0.11 (−0.18, −0.04)
0 (−0.06, 0.07)
Spina bifida without anencephalus
0.04 (−0.03, 0.1)
−0.2 (−0.3, −0.11)
0.27 (0.23, 0.3)
0 (−0.05, 0.04)
0.05 (0.01, 0.08)
0 (−0.07, 0.07)
Gastroschisis
0 (−0.07, 0.06)
−0.13 (−0.21, −0.05)
0.32 (0.28, 0.36)
−0.03 (−0.1, 0.03)
−0.08 (−0.14, −0.02)
0 (−0.07, 0.06)
Cleft lip with cleft palate
0.12 (0.06, 0.18)
−0.16 (−0.26, −0.07)
0.27 (0.22, 0.32)
−0.08 (−0.15, −0.01)
−0.05 (−0.11, 0.02)
−0.01 (−0.08, 0.06)
Coarctation of the aorta
0.14 (0.09, 0.19)
−0.42 (−0.52, −0.33)
0.14 (0.09, 0.18)
−0.15 (−0.21, −0.09)
0.28 (0.24, 0.31)
−0.02 (−0.08, 0.04)
Anencephalus
−0.12 (−0.24, −0.01)
−0.43 (−0.59, −0.28)
0.26 (0.23, 0.3)
0.03 (−0.01, 0.08)
−0.08 (−0.12, −0.04)
−0.03 (−0.14, 0.06)
Esophageal atresia/tracheoesophageal fistula
0.07 (−0.01, 0.15)
0.06 (−0.03, 0.14)
0.04 (−0.05, 0.12)
0.01 (−0.09, 0.09)
0.1 (0.02, 0.17)
−0.03 (−0.12, 0.05)
Tetralogy of Fallot
0.09 (0.03, 0.15)
−0.28 (−0.38, −0.19)
0.03 (−0.03, 0.09)
−0.01 (−0.08, 0.05)
−0.04 (−0.1, 0.02)
−0.04 (−0.1, 0.03)
Encephalocele
0.17 (0.05, 0.28)
−0.46 (−0.72, −0.24)
0.07 (−0.02, 0.15)
−0.1 (−0.2, 0)
−0.07 (−0.16, 0.02)
−0.04 (−0.2, 0.09)
Congenital posterior urethral valves
0.1 (−0.06, 0.23)
−0.65 (−0.93, −0.42)
0.06 (−0.08, 0.18)
−0.19 (−0.38, −0.03)
0.25 (0.13, 0.35)
−0.05 (−0.27, 0.12)
Interrupted aortic arch
0.21 (−0.01, 0.38)
−0.17 (−0.54, 0.1)
0.27 (0.11, 0.41)
−0.24 (−0.53, 0)
0.04 (−0.18, 0.21)
−0.07 (−0.37, 0.16)
Dextro-transposition of great arteries (d-TGA)
0.16 (0.07, 0.25)
−0.13 (−0.27, 0)
−0.04 (−0.15, 0.06)
−0.13 (−0.25, −0.02)
−0.34 (−0.46, −0.22)
−0.07 (−0.18, 0.03)
Congenital cataract
−0.07 (−0.2, 0.04)
−0.1 (−0.24, 0.02)
0.08 (−0.03, 0.18)
−0.03 (−0.15, 0.08)
−0.06 (−0.17, 0.04)
−0.12 (−0.24, 0)
Bladder exstrophy
0.36 (0.16, 0.51)
−0.08 (−0.45, 0.19)
0.14 (−0.16, 0.36)
−0.17 (−0.61, 0.15)
0.03 (−0.33, 0.29)
−0.13 (−0.5, 0.15)
Cleft palate alone
0.19 (0.14, 0.23)
0.01 (−0.05, 0.07)
0.13 (0.08, 0.18)
−0.04 (−0.1, 0.02)
−0.05 (−0.1, 0.01)
−0.14 (−0.21, −0.08)
Pyloric stenosis
0.42 (0.39, 0.45)
−1.85 (−2.08, −1.63)
0.47 (0.44, 0.5)
−0.5 (−0.61, −0.4)
−0.12 (−0.19, −0.05)
−0.15 (−0.32, 0.01)
Pulmonary valve atresia and stenosis
0 (−0.05, 0.05)
−0.4 (−0.48, −0.33)
0.02 (−0.03, 0.06)
−0.14 (−0.2, −0.09)
−0.14 (−0.19, −0.09)
−0.17 (−0.22, −0.12)
Limb deficiencies (reduction defects)
0.09 (0, 0.16)
−0.15 (−0.26, −0.05)
0.07 (0, 0.13)
−0.18 (−0.26, −0.1)
−0.29 (−0.37, −0.22)
−0.18 (−0.29, −0.07)
Hydrocephalus without spina bifida
0.25 (0.18, 0.32)
0.03 (−0.06, 0.12)
−0.15 (−0.25, −0.06)
−0.03 (−0.12, 0.05)
0.04 (−0.03, 0.11)
−0.2 (−0.52, 0.06)
Amniotic Bands
−0.06 (−0.49, 0.25)
−0.53 (−1.03, −0.16)
0.33 (0.04, 0.53)
−0.49 (−1.28, 0.03)
−0.19 (−0.73, 0.19)
−0.2 (−1.14, 0.33)
Ebstein anomaly
0.12 (−0.03, 0.25)
−0.41 (−0.69, −0.18)
0.25 (0.14, 0.35)
−0.09 (−0.25, 0.05)
−0.13 (−0.29, 0.01)
−0.2 (−0.4, −0.03)
Choanal atresia
0.28 (0.19, 0.37)
0.02 (−0.11, 0.15)
−0.2 (−0.35, −0.07)
−0.14 (−0.28, −0.01)
−0.29 (−0.45, −0.15)
−0.23 (−0.39, −0.09)
Omphalocele
0.16 (0.07, 0.24)
−0.27 (−0.41, −0.14)
0.07 (0.01, 0.13)
−0.18 (−0.26, −0.1)
−0.09 (−0.15, −0.02)
−0.24 (−0.37, −0.12)
Common truncus (truncus arteriosus)
0.52 (0.44, 0.59)
−0.73 (−1.1, −0.43)
0.02 (−0.15, 0.16)
−0.39 (−0.64, −0.18)
−0.37 (−0.59, −0.18)
−0.32 (−0.54, −0.12)
Reduction deformity, Lower limbs
0.18 (0.03, 0.31)
−0.07 (−0.28, 0.12)
0.04 (−0.14, 0.19)
−0.22 (−0.46, −0.02)
−0.2 (−0.4, −0.02)
−0.32 (−1.12, 0.17)
Ventricular septal defect
0.16 (0.14, 0.18)
−0.19 (−0.22, −0.16)
−0.18 (−0.2, −0.15)
−0.26 (−0.29, −0.23)
−0.34 (−0.37, −0.31)
−0.33 (−0.36, −0.3)
Craniosynostosis
0.21 (0.12, 0.29)
−0.64 (−0.84, −0.46)
0.11 (0.01, 0.19)
−0.02 (−0.13, 0.08)
−0.84 (−1.01, −0.69)
−0.34 (−0.48, −0.21)
Hypospadias
0.37 (0.36, 0.38)
−0.15 (−0.17, −0.13)
−0.02 (−0.04, 0)
0 (−0.02, 0.02)
−0.35 (−0.38, −0.33)
−0.37 (−0.4, −0.35)
Anophthalmia/microphthalmia
−0.26 (−0.44, −0.1)
0.03 (−0.11, 0.15)
0.15 (0.08, 0.22)
0.14 (0.07, 0.21)
−0.71 (−0.83, −0.59)
−0.38 (−0.55, −0.23)
Turner syndrome
−0.63 (−0.89, −0.41)
0.13 (0.01, 0.23)
0.01 (−0.05, 0.07)
0.1 (0.04, 0.16)
0.36 (0.32, 0.4)
−0.39 (−0.68, −0.15)
Microcephalus
0.24 (0.16, 0.32)
−0.28 (−0.42, −0.15)
0.09 (−0.02, 0.18)
−0.09 (−0.22, 0.02)
−0.41 (−0.54, −0.28)
−0.47 (−0.84, −0.17)
Holoprosencephaly
0.48 (0.41, 0.54)
−0.78 (−1.05, −0.54)
−0.18 (−0.25, −0.11)
−1.58 (−1.74, −1.43)
0.19 (0.14, 0.24)
−0.55 (−0.8, −0.33)
Epispadias
−0.24 (−0.6, 0.03)
0.18 (−0.08, 0.38)
−0.44 (−0.9, −0.1)
0.27 (0.04, 0.44)
0.24 (0.03, 0.4)
−0.56 (−1.18, −0.12)
Renal agenesis/hypoplasia
0.2 (0.15, 0.25)
−0.08 (−0.16, −0.01)
−0.05 (−0.11, 0)
−0.18 (−0.25, −0.12)
−0.86 (−0.97, −0.76)
−0.62 (−0.73, −0.52)
Atrial septal defect
0.6 (0.6, 0.61)
−0.79 (−0.83, −0.76)
0.24 (0.22, 0.25)
−0.4 (−0.43, −0.37)
−0.4 (−0.43, −0.38)
−0.91 (−0.94, −0.88)
Reduction deformity, Upper limbs
−0.11 (−0.27, 0.03)
−0.05 (−0.21, 0.08)
0.02 (−0.11, 0.14)
−0.2 (−0.36, −0.06)
−0.43 (−0.6, −0.27)
−0.97 (−1.61, −0.48)
Tricuspid valve atresia and stenosis
−0.49 (−0.7, −0.31)
−0.1 (−0.24, 0.03)
−0.63 (−0.8, −0.48)
0.15 (0.07, 0.22)
−0.88 (−1.06, −0.72)
−1.21 (−1.46, −0.99)
Aniridia
0.2 (−0.53, 0.58)
−1.92 (−5.62, −0.28)
0.46 (0.23, 0.62)
0.42 (0.12, 0.61)
0.31 (−0.07, 0.55)
–
Table 8 performs a similar function for Population Attributable Risk (PAR). Cloacal extrophy again heads the list from a PAR of 56.75% after cannabis exposure.
Table 8
Population Attributable Risk by Substance
Congenital Anomaly
Cigarettes PAR
Binge Alcohol PAR
Analgesics PAR
Cocaine PAR
Cannabis PAR
Cannabidiol PAR
Obstructive genitourinary defect
−0.03 (−0.05, −0.01)
0.01 (−0.02, 0.03)
−0.03 (−0.05, −0.02)
0.07 (0.05, 0.09)
−0.04 (−0.06, −0.03)
0.47 (0.38, 0.55)
Cleft lip with and without cleft palate
0.02 (−0.01, 0.04)
−0.02 (−0.05, 0.01)
0.09 (0.06, 0.12)
0.01 (−0.03, 0.05)
−0.02 (−0.04, 0)
0.34 (0.07, 0.53)
Hirschsprung disease (congenital megacolon)
0.05 (−0.02, 0.11)
−0.24 (−0.32, −0.16)
0.02 (−0.04, 0.08)
0 (−0.09, 0.09)
0.12 (0.06, 0.17)
0.22 (−0.25, 0.51)
Congenital hip dislocation
−0.03 (−0.08, 0.02)
0.05 (−0.02, 0.11)
−0.02 (−0.05, 0.02)
0.28 (0.23, 0.33)
0.25 (0.22, 0.28)
0.21 (−0.14, 0.46)
Pulmonary valve atresia
0.01 (−0.02, 0.05)
−0.27 (−0.32, −0.22)
0.18 (0.14, 0.23)
−0.02 (−0.09, 0.05)
0.11 (0.06, 0.16)
0.12 (0.06, 0.17)
Biliary atresia
0.01 (−0.04, 0.05)
−0.16 (−0.22, −0.1)
−0.04 (−0.1, 0.01)
0.06 (−0.04, 0.14)
0.07 (0.01, 0.13)
0.1 (0.01, 0.18)
Patent ductus arteriosus
−0.02 (−0.04, 0)
−0.16 (−0.18, −0.13)
0.04 (0.02, 0.05)
−0.12 (−0.14, −0.09)
−0.16 (−0.17, −0.15)
0.07 (−0.12, 0.23)
Trisomy 13
−0.11 (−0.13, −0.08)
−0.01 (−0.06, 0.03)
−0.06 (−0.08, −0.04)
0.3 (0.27, 0.32)
0.11 (0.09, 0.12)
0.07 (0, 0.13)
Small intestinal atresia/stenosis
−0.02 (−0.04, −0.01)
−0.05 (−0.08, −0.01)
0.03 (0, 0.06)
0.06 (0, 0.11)
0.1 (0.06, 0.14)
0.06 (0.03, 0.09)
Cloacal exstrophy
0.27 (0.22, 0.31)
−0.05 (−0.09, −0.01)
0.1 (0.07, 0.14)
−0.23 (−0.29, −0.16)
0.57 (0.51, 0.62)
0.06 (0.02, 0.1)
Single ventricle
−0.03 (−0.06, 0.01)
−0.25 (−0.31, −0.18)
0.02 (−0.03, 0.07)
−0.13 (−0.22, −0.04)
0.09 (0.02, 0.16)
0.06 (0, 0.11)
Total anomalous pulmonary venous connection
−0.08 (−0.1, −0.05)
−0.17 (−0.23, −0.11)
0.13 (0.08, 0.19)
0.15 (0.07, 0.23)
0.02 (−0.04, 0.08)
0.05 (−0.01, 0.11)
Diaphragmatic hernia
0.05 (0.03, 0.08)
−0.06 (−0.1, −0.03)
0.05 (0.02, 0.08)
−0.08 (−0.13, −0.03)
0.09 (0.06, 0.12)
0.04 (0, 0.08)
Double outlet right ventricle
0.01 (−0.02, 0.04)
−0.15 (−0.2, −0.1)
0.04 (0, 0.07)
−0.05 (−0.11, 0)
0.09 (0.04, 0.14)
0.04 (0, 0.07)
Deletion 22q11.2
−0.11 (−0.16, −0.06)
0.09 (−0.01, 0.19)
0.4 (0.33, 0.47)
0.31 (0.2, 0.4)
0.09 (0.02, 0.16)
0.03 (−0.02, 0.09)
Trisomy 21 (Down syndrome)
−0.04 (−0.05, −0.03)
0.01 (0, 0.03)
0.01 (0, 0.01)
0.07 (0.06, 0.08)
0.06 (0.05, 0.07)
0.03 (0.01, 0.05)
Atrioventricular septal defect
−0.01 (−0.03, 0)
−0.08 (−0.11, −0.06)
0.02 (0, 0.04)
−0.04 (−0.07, −0.01)
0.02 (0, 0.04)
0.03 (0, 0.06)
Trisomy 18
−0.09 (−0.11, −0.07)
−0.04 (−0.07, −0.01)
0.02 (0.01, 0.04)
0.16 (0.14, 0.18)
0.11 (0.1, 0.13)
0.02 (−0.02, 0.07)
Clubfoot
0.01 (−0.01, 0.02)
−0.05 (−0.06, −0.03)
0.01 (−0.01, 0.02)
0 (−0.03, 0.02)
0.02 (0, 0.04)
0.02 (0, 0.03)
Hypoplastic left heart syndrome
0.05 (0.02, 0.07)
−0.13 (−0.16, −0.1)
0.04 (0.02, 0.07)
−0.05 (−0.09, −0.01)
0.04 (0.01, 0.07)
0.01 (−0.03, 0.06)
Aortic valve stenosis
−0.01 (−0.04, 0.01)
−0.12 (−0.15, −0.08)
0.18 (0.15, 0.2)
0.02 (−0.02, 0.06)
−0.04 (−0.07, −0.02)
0.01 (−0.04, 0.06)
Cleft lip alone
0.01 (−0.01, 0.03)
0.01 (−0.02, 0.05)
0.06 (0.03, 0.1)
−0.12 (−0.17, −0.07)
−0.02 (−0.05, 0.02)
0.01 (−0.02, 0.03)
Transposition of great arteries
0.08 (0.05, 0.11)
−0.08 (−0.11, −0.05)
0.07 (0.05, 0.1)
−0.08 (−0.12, −0.05)
0 (−0.02, 0.03)
0.01 (−0.03, 0.04)
Anotia/microtia
−0.19 (−0.2, −0.17)
−0.05 (−0.09, −0.01)
0.12 (0.1, 0.14)
0.25 (0.22, 0.28)
0 (−0.02, 0.02)
0 (−0.05, 0.05)
Rectal and large intestinal atresia/stenosis
0.05 (0.03, 0.07)
−0.06 (−0.09, −0.04)
0.02 (0, 0.05)
−0.07 (−0.11, −0.04)
−0.04 (−0.07, −0.02)
0 (−0.03, 0.03)
Spina bifida without anencephalus
0.01 (−0.01, 0.03)
−0.06 (−0.09, −0.04)
0.12 (0.1, 0.14)
0 (−0.02, 0.02)
0.02 (0, 0.04)
0 (−0.04, 0.04)
Gastroschisis
0 (−0.02, 0.02)
−0.04 (−0.06, −0.02)
0.15 (0.12, 0.17)
−0.02 (−0.05, 0.02)
−0.03 (−0.05, −0.01)
0 (−0.04, 0.03)
Cleft lip with cleft palate
0.03 (0.01, 0.04)
−0.06 (−0.09, −0.03)
0.12 (0.1, 0.15)
−0.04 (−0.08, 0)
−0.02 (−0.05, 0.01)
0 (−0.03, 0.02)
Congenital posterior urethral valves
0.03 (−0.02, 0.07)
−0.17 (−0.21, −0.12)
0.02 (−0.03, 0.06)
−0.09 (−0.17, −0.02)
0.09 (0.04, 0.13)
−0.01 (−0.04, 0.02)
Coarctation of the aorta
0.04 (0.02, 0.05)
−0.12 (−0.14, −0.1)
0.05 (0.03, 0.07)
−0.08 (−0.11, −0.05)
0.14 (0.12, 0.15)
−0.01 (−0.04, 0.02)
Anencephalus
−0.03 (−0.05, 0)
−0.12 (−0.16, −0.09)
0.12 (0.1, 0.14)
0.02 (−0.01, 0.04)
−0.03 (−0.05, −0.02)
−0.02 (−0.07, 0.03)
Esophageal atresia/tracheoesophageal fistula
0.02 (0, 0.04)
0.02 (−0.01, 0.06)
0.01 (−0.02, 0.05)
0 (−0.05, 0.05)
0.04 (0.01, 0.08)
−0.02 (−0.06, 0.03)
Interrupted aortic arch
0.04 (−0.01, 0.09)
−0.05 (−0.13, 0.03)
0.12 (0.04, 0.19)
−0.13 (−0.28, −0.01)
0.02 (−0.09, 0.11)
−0.02 (−0.09, 0.04)
Tetralogy of Fallot
0.02 (0.01, 0.04)
−0.09 (−0.11, −0.06)
0.01 (−0.01, 0.04)
−0.01 (−0.04, 0.03)
−0.02 (−0.04, 0.01)
−0.02 (−0.06, 0.01)
Encephalocele
0.05 (0.01, 0.09)
−0.13 (−0.18, −0.08)
0.03 (−0.01, 0.06)
−0.05 (−0.1, 0)
−0.03 (−0.06, 0.01)
−0.02 (−0.1, 0.05)
Dextro-transposition of great arteries (d-TGA)
0.04 (0.02, 0.07)
−0.04 (−0.08, 0)
−0.01 (−0.05, 0.02)
−0.07 (−0.14, −0.01)
−0.13 (−0.17, −0.09)
−0.03 (−0.08, 0.01)
Limb deficiencies (reduction defects)
0.02 (0, 0.04)
−0.05 (−0.08, −0.02)
0.03 (0, 0.05)
−0.1 (−0.14, −0.06)
−0.13 (−0.15, −0.1)
−0.04 (−0.06, −0.02)
Turner syndrome
−0.12 (−0.15, −0.09)
0.05 (0, 0.09)
0 (−0.02, 0.02)
0.06 (0.02, 0.1)
0.12 (0.1, 0.14)
−0.05 (−0.08, −0.03)
Congenital cataract
−0.02 (−0.04, 0.01)
−0.03 (−0.08, 0.01)
0.03 (−0.01, 0.07)
−0.02 (−0.08, 0.04)
−0.02 (−0.06, 0.02)
−0.06 (−0.12, 0)
Cleft palate alone
0.05 (0.03, 0.06)
0.01 (−0.02, 0.03)
0.05 (0.03, 0.08)
−0.02 (−0.05, 0.01)
−0.02 (−0.04, 0)
−0.07 (−0.1, −0.04)
Bladder exstrophy
0.13 (0.04, 0.21)
−0.03 (−0.13, 0.07)
0.05 (−0.05, 0.14)
−0.07 (−0.23, 0.06)
0.01 (−0.1, 0.11)
−0.07 (−0.24, 0.08)
Craniosynostosis
0.03 (0.01, 0.04)
−0.15 (−0.18, −0.12)
0.04 (0, 0.07)
−0.01 (−0.08, 0.05)
−0.25 (−0.28, −0.22)
−0.07 (−0.1, −0.05)
Pulmonary valve atresia and stenosis
0 (−0.01, 0.01)
−0.11 (−0.13, −0.1)
0.01 (−0.01, 0.02)
−0.06 (−0.09, −0.04)
−0.04 (−0.06, −0.03)
−0.08 (−0.11, −0.06)
Holoprosencephaly
0.15 (0.12, 0.18)
−0.18 (−0.22, −0.14)
−0.06 (−0.08, −0.04)
−0.61 (−0.65, −0.57)
0.1 (0.07, 0.13)
−0.1 (−0.13, −0.07)
Ebstein anomaly
0.03 (−0.01, 0.07)
−0.12 (−0.17, −0.06)
0.11 (0.05, 0.16)
−0.05 (−0.12, 0.03)
−0.05 (−0.1, 0)
−0.1 (−0.19, −0.02)
Choanal atresia
0.09 (0.05, 0.13)
0.01 (−0.04, 0.06)
−0.07 (−0.11, −0.03)
−0.07 (−0.14, −0.01)
−0.1 (−0.15, −0.06)
−0.11 (−0.18, −0.05)
Omphalocele
0.04 (0.02, 0.07)
−0.08 (−0.12, −0.05)
0.03 (0, 0.05)
−0.09 (−0.13, −0.06)
−0.04 (−0.06, −0.01)
−0.12 (−0.17, −0.06)
Ventricular septal defect
0.06 (0.05, 0.06)
−0.06 (−0.07, −0.06)
−0.05 (−0.06, −0.04)
−0.11 (−0.12, −0.1)
−0.08 (−0.09, −0.07)
−0.13 (−0.14, −0.12)
Pyloric stenosis
0.24 (0.21, 0.26)
−0.39 (−0.41, −0.36)
0.2 (0.19, 0.22)
−0.16 (−0.19, −0.14)
−0.03 (−0.04, −0.01)
−0.14 (−0.31, 0.01)
Common truncus (truncus arteriosus)
0.22 (0.17, 0.27)
−0.18 (−0.24, −0.13)
0.01 (−0.05, 0.06)
−0.18 (−0.28, −0.1)
−0.13 (−0.18, −0.07)
−0.14 (−0.23, −0.06)
Hypospadias
0.12 (0.11, 0.12)
−0.05 (−0.05, −0.04)
−0.01 (−0.01, 0)
0 (−0.01, 0.01)
−0.13 (−0.13, −0.12)
−0.18 (−0.19, −0.17)
Anophthalmia/microphthalmia
−0.05 (−0.09, −0.02)
0.01 (−0.04, 0.06)
0.06 (0.03, 0.09)
0.08 (0.04, 0.13)
−0.21 (−0.23, −0.18)
−0.18 (−0.24, −0.12)
Hydrocephalus without spina bifida
0.09 (0.06, 0.12)
0.01 (−0.02, 0.05)
−0.04 (−0.06, −0.02)
−0.01 (−0.05, 0.02)
0.01 (−0.01, 0.04)
−0.19 (−0.5, 0.06)
Amniotic Bands
−0.01 (−0.05, 0.04)
−0.14 (−0.22, −0.06)
0.1 (0, 0.2)
−0.11 (−0.22, −0.01)
−0.03 (−0.1, 0.03)
−0.19 (−1.07, 0.31)
Renal agenesis/hypoplasia
0.06 (0.04, 0.08)
−0.03 (−0.05, 0)
−0.02 (−0.03, 0)
−0.09 (−0.12, −0.06)
−0.23 (−0.25, −0.22)
−0.26 (−0.29, −0.23)
Reduction deformity, Lower limbs
0.06 (0, 0.11)
−0.02 (−0.09, 0.04)
0.01 (−0.05, 0.07)
−0.1 (−0.19, −0.01)
−0.05 (−0.1, −0.01)
−0.31 (−1.07, 0.17)
Atrial septal defect
0.28 (0.27, 0.28)
−0.2 (−0.21, −0.2)
0.09 (0.09, 0.1)
−0.17 (−0.18, −0.16)
−0.13 (−0.14, −0.13)
−0.34 (−0.35, −0.33)
Tricuspid valve atresia and stenosis
−0.09 (−0.12, −0.07)
−0.03 (−0.08, 0.01)
−0.16 (−0.18, −0.13)
0.09 (0.04, 0.13)
−0.23 (−0.26, −0.21)
−0.42 (−0.47, −0.37)
Microcephalus
0.11 (0.07, 0.16)
−0.11 (−0.16, −0.06)
0.03 (−0.01, 0.06)
−0.04 (−0.09, 0.01)
−0.09 (−0.12, −0.07)
−0.44 (−0.78, −0.17)
Epispadias
−0.09 (−0.2, 0.01)
0.09 (−0.04, 0.2)
−0.1 (−0.17, −0.03)
0.13 (0.01, 0.24)
0.07 (0, 0.14)
−0.48 (−0.96, −0.11)
Reduction deformity, Upper limbs
−0.03 (−0.07, 0.01)
−0.02 (−0.07, 0.03)
0.01 (−0.04, 0.05)
−0.09 (−0.15, −0.03)
−0.1 (−0.13, −0.07)
−0.92 (−1.52, −0.46)
Aniridia
0.09 (−0.22, 0.32)
−0.35 (−0.57, −0.16)
0.21 (0.07, 0.33)
0.25 (0.04, 0.42)
0.11 (−0.04, 0.24)
–
Applicable P-values are listed together by substance in Table 9. In reading this table it should be noted that P values in R are only computed down to 2.2x10−320. Such values in the table may be better understood as zeroes.
Table 9
Significance Levels by Substance
Congenital Anomaly
Cigarettes P-Value
Binge Alcohol P-Value
Analgesics P-Value
Cocaine P-Value
Cannabis P-Value
Cannabidiol P-Value
Atrial septal defect
2.2e-320
0.0215
9.26E-39
0.00536446
1.09E-08
2.2e-320
Ventricular septal defect
7.36E-08
0.1490
1.24E-20
1.93E-04
0.0033
2.2e-320
Hypospadias
2.2e-320
0.4362
0.0317
0.7536
1.38E-05
1.02E-289
Tricuspid valve atresia and stenosis
7.29E-10
0.1377
4.01E-159
6.31E-04
3.93E-04
1.36E-50
Renal agenesis/hypoplasia
5.30E-11
0.0215
0.0606
2.82E-09
0.0028
1.63E-50
Obstructive genitourinary defect
0.0012
0.4876
4.12E-05
2.37E-09
3.92E-12
2.22E-15
Pulmonary valve atresia and stenosis
0.9716
0.0408
0.4950
3.64E-08
1.27E-08
9.14E-12
Anophthalmia/microphthalmia
8.86E-04
0.6781
7.92E-05
3.62E-04
1.48E-12
2.12E-08
Craniosynostosis
1.80E-05
1.0000
0.0266
0.7020
7.18E-05
2.31E-08
Holoprosencephaly
1.66E-28
2.00E-15
5.89E-08
2.02E-04
2.90E-12
2.34E-08
Reduction deformity, Upper limbs
0.1301
0.4407
0.7110
0.0042
1.15E-09
2.01E-06
Cleft palate alone
2.29E-11
0.6532
3.78E-07
0.2282
0.0892
3.47E-06
Small intestinal atresia/stenosis
0.0106
0.0125
0.0775
0.0531
4.47E-06
5.93E-06
Pulmonary valve atresia
0.4522
0.0978
2.23E-17
0.6602
2.62E-05
1.02E-05
Omphalocele
8.62E-04
6.56E-06
0.0288
7.27E-07
0.0056
2.49E-05
Cloacal exstrophy
1.36E-45
0.0284
1.91E-12
6.90E-11
2.13E-86
5.45E-04
Turner syndrome
9.14E-11
0.0367
0.7522
0.0014
7.69E-49
5.63E-04
Common truncus (truncus arteriosus)
7.03E-22
1.02E-08
0.8321
7.90E-05
2.51E-05
6.55E-04
Microcephalus
3.39E-07
7.86E-06
0.1067
0.1136
1.90E-13
7.11E-04
Choanal atresia
1.42E-07
0.7186
0.0014
0.0290
2.26E-05
7.34E-04
Limb deficiencies (reduction defects)
0.0428
0.0034
0.0405
1.72E-06
2.33E-06
8.14E-04
Trisomy 21 (Down syndrome)
1.75E-07
0.0895
0.1491
1.49E-55
4.02E-26
0.0021
Clubfoot
0.4663
3.66E-06
0.2788
0.7378
0.0136
0.0048
Epispadias
0.0915
0.1591
0.0084
0.0242
0.0287
0.0081
Cleft lip with and without cleft palate
0.1248
0.1441
3.43E-11
0.5715
0.0887
0.0159
Ebstein anomaly
0.1232
1.57E-04
3.81E-05
0.2279
0.0643
0.0177
Biliary atresia
0.7657
4.48E-06
0.1548
0.2026
0.0244
0.0233
Diaphragmatic hernia
5.26E-07
5.72E-05
0.0011
0.0013
2.11E-08
0.0373
Double outlet right ventricle
0.5739
4.13E-08
0.0314
0.0743
7.31E-04
0.0379
Congenital cataract
0.2114
0.1134
0.1381
0.5892
0.2537
0.0416
Trisomy 13
1.77E-11
0.5945
4.20E-09
3.06E-106
3.50E-06
0.0427
Single ventricle
0.1289
2.42E-10
0.3626
0.0037
0.0060
0.0482
Pyloric stenosis
1.38E-84
0.1051
1.78E-122
9.40E-29
4.82E-04
0.0657
Total anomalous pulmonary venous connection
1.05E-07
1.64E-06
9.84E-07
3.78E-04
0.4381
0.0773
Atrioventricular septal defect
0.0937
6.48E-12
0.0269
0.0073
0.0470
0.0854
Hydrocephalus without spina bifida
1.84E-09
0.4705
0.0011
0.5085
0.2200
0.1441
Dextro-transposition of great arteries (d-TGA)
8.25E-04
0.0513
0.4822
0.0198
1.40E-10
0.1529
Deletion 22q11.2
6.98E-05
0.0672
3.67E-28
4.72E-08
0.0051
0.2047
Congenital hip dislocation
0.1991
0.1493
0.3536
1.13E-27
7.27E-70
0.2063
Reduction deformity, Lower limbs
0.0231
0.5017
0.6312
0.0277
0.0253
0.2401
Tetralogy of Fallot
0.0047
7.04E-11
0.2681
0.6597
0.1692
0.2530
Hirschsprung disease (congenital megacolon)
0.1818
1.55E-08
0.4987
0.9565
6.69E-06
0.3010
Trisomy 18
6.05E-04
0.0140
0.0034
2.43E-08
1.06E-61
0.3486
Bladder exstrophy
0.0011
0.5975
0.3200
0.3343
0.8681
0.3893
Patent ductus arteriosus
0.0375
0.8028
2.36E-07
1.22E-09
5.95E-39
0.4386
Esophageal atresia/tracheoesophageal fistula
0.0977
0.2148
0.3880
0.8914
0.0195
0.4602
Hypoplastic left heart syndrome
1.91E-05
1.35E-14
0.0014
0.0080
0.0048
0.5102
Anencephalus
0.0269
1.45E-10
4.05E-44
0.1442
7.15E-05
0.5233
Coarctation of the aorta
5.48E-07
0.8820
3.82E-08
1.56E-07
9.74E-45
0.5283
Amniotic Bands
0.7468
0.0026
0.0271
0.0681
0.3785
0.5349
Encephalocele
0.0079
4.74E-06
0.1125
0.0397
0.1289
0.5605
Congenital posterior urethral valves
0.2039
8.57E-11
0.4012
0.0184
1.35E-04
0.5725
Interrupted aortic arch
0.0582
0.2411
0.0022
0.0472
0.7274
0.5788
Cleft lip alone
0.2215
0.4773
1.95E-04
1.40E-06
0.4216
0.5998
Aortic valve stenosis
0.4160
6.46E-09
9.78E-36
0.4210
0.0011
0.6318
Transposition of great arteries
1.49E-08
5.27E-07
4.54E-08
1.54E-05
0.7669
0.7385
Cleft lip with cleft palate
1.92E-04
2.58E-04
3.32E-04
0.0304
0.1508
0.7455
Anotia/microtia
9.45E-10
0.0148
4.05E-37
2.02E-64
0.9670
0.8853
Gastroschisis
0.9978
0.0014
9.74E-13
0.3662
0.0098
0.8919
Rectal and large intestinal atresia/stenosis
4.34E-08
2.94E-06
0.0493
1.69E-04
0.0011
0.8966
Spina bifida without anencephalus
0.2806
5.86E-06
2.14E-29
0.9854
0.0181
0.9332
Aniridia
0.5068
0.0073
6.17E-04
0.0096
0.0952
–
Minimum E-Values for these comparisons are shown in Table 10 by substance.
Table 10
E-Values by Substance
Congenital Anomaly
Cigarettes E-Value
Binge Alcohol E-Value
Analgesics E-Value
Cocaine E-Value
Cannabis E-Value
Cannabidiol E-Value
Obstructive genitourinary defect
1.00
1.46
2.64
Pulmonary valve atresia
1.00
2.28
1.53
1.64
Small intestinal atresia/stenosis
1.00
1.00
1.49
1.54
Cloacal exstrophy
4.32
2.16
7.61
1.48
Cleft lip with and without cleft palate
1.00
1.70
1.00
1.37
Clubfoot
1.00
1.00
1.14
1.20
Biliary atresia
1.00
1.00
1.17
1.18
Trisomy 21 (Down syndrome)
1.00
1.00
1.46
1.49
1.16
Double outlet right ventricle
1.00
1.11
1.36
1.10
Diaphragmatic hernia
1.52
1.31
1.57
1.07
Trisomy 13
2.73
1.75
1.07
Single ventricle
1.00
1.30
1.04
Transposition of great arteries
1.59
1.54
1.00
1.00
Rectal and large intestinal atresia/stenosis
1.50
1.01
1.00
Hypoplastic left heart syndrome
1.44
1.26
1.20
1.00
Cleft lip alone
1.00
1.00
1.38
1.00
Hirschsprung disease (congenital megacolon)
1.00
1.00
1.00
1.77
1.00
Spina bifida without anencephalus
1.00
1.93
1.00
1.10
1.00
Anotia/microtia
1.93
2.43
1.00
1.00
Aortic valve stenosis
2.32
1.00
1.00
Atrioventricular septal defect
1.10
1.03
1.00
Congenital hip dislocation
1.00
2.69
3.57
1.00
Deletion 22q11.2
1.00
4.22
2.28
1.42
1.00
Patent ductus arteriosus
1.37
1.00
Total anomalous pulmonary venous connection
1.79
1.51
1.00
1.00
Trisomy 18
1.16
1.91
1.85
1.00
Atrial septal defect
4.38
1.89
Common truncus (truncus arteriosus)
2.99
1.00
Holoprosencephaly
2.80
1.60
Pyloric stenosis
2.64
3.00
Hypospadias
2.48
Choanal atresia
1.77
1.00
Hydrocephalus without spina bifida
1.73
1.00
1.00
Bladder exstrophy
1.67
1.00
1.00
Microcephalus
1.65
1.00
Renal agenesis/hypoplasia
1.62
Ventricular septal defect
1.61
Cleft palate alone
1.58
1.00
1.41
Craniosynostosis
1.53
1.13
Coarctation of the aorta
1.42
1.43
1.97
Dextro-transposition of great arteries (d-TGA)
1.36
Omphalocele
1.35
1.09
Cleft lip with cleft palate
1.33
1.88
Encephalocele
1.28
1.00
Tetralogy of Fallot
1.20
1.00
Reduction deformity, Lower limbs
1.20
1.00
Limb deficiencies (reduction defects)
1.06
1.06
Aniridia
1.00
1.90
1.53
1.00
Congenital posterior urethral valves
1.00
1.00
1.56
Ebstein anomaly
1.00
1.60
Esophageal atresia/tracheoesophageal fistula
1.00
1.00
1.00
1.00
1.15
Interrupted aortic arch
1.00
1.49
1.00
Amniotic Bands
1.26
Anencephalus
1.91
1.00
Anophthalmia/microphthalmia
1.00
1.39
1.35
Congenital cataract
1.00
Epispadias
1.00
1.25
1.20
Gastroschisis
2.12
Pulmonary valve atresia and stenosis
1.00
Reduction deformity, Upper limbs
1.00
Tricuspid valve atresia and stenosis
1.35
Turner syndrome
1.10
1.00
1.25
2.31
Summary of bivariate analyses
Given that the above tables present a lot of information it is of interest to distil this information down into more intellectually digestible components.
Supplementary Table 11 extracts the 85 ETOPFACARs which have significant E-Values for the 35 cannabis related CAs, the 40 THC related CAs and the 11 cannabidiol CAs considered as continuous variables. The table is arranged in descending order of the lower bound of the E-Values. 37/85 E-Values are greater than 9.0 which is the E-Value for the tobacco-lung cancer relationship and 84/85 are greater than 1.25 which is the quoted cut-off for causality [68].
Table 11 re-lists the 41 CAs listed in Table 20 and retains only the ETOPFACAR with the highest minimum E-Value. In this Table 28/41 are greater than 9.0 and 40/41 are greater than 1.25. On this list 28 CAs are related to cannabis, 5 to THC and 8 to cannabidiol.
Table 11
Summary Single CAs with Significant Cannabinoid E-Values Continuous Variables
Defect
No.
System
Term
Estimate
Std.Error
Students T
P_Value
S.D.
E-Value-Point Estimate
E-Value-Lower Limit
Congenital hip dislocation
1
Limb
CBD
298.2937
55.1100
5.4127
0.0000
3.8459
9.00E+30
7.53E+19
Small intestinal atresia/stenosis
2
GIT
CBD
61.6605
12.7480
4.8369
0.0000
1.1814
8.48E+20
3.86E+12
Trisomy 21 (Down syndrome)
3
Chromosomes
Cannabis
221.1194
25.4625
8.6841
0.0000
10.2305
6.97E+08
8.30E+06
Biliary atresia
4
GIT
CBD
10.9598
2.9445
3.7222
0.0002
0.3922
2.22E+11
3.48E+05
Interrupted aortic arch
5
CVS
Cannabis
15.4036
3.1814
4.8418
0.0000
0.8305
4.28E+07
4.68E+04
Obstructive genitourinary defect
6
GUT
CBD
486.0939
176.6878
2.7511
0.0072
13.0815
9.69E+14
3.51E+04
Hirschsprung disease (congenital megacolon)
7
GIT
CBD
38.1800
14.1676
2.6949
0.0084
1.0029
2.22E+15
2.67E+04
Clubfoot
8
Limb
Cannabis
94.0309
21.7820
4.3169
0.0000
5.4311
1.39E+07
1.10E+04
Trisomy 13
9
Chromosomes
Cannabis
75.1394
14.1320
5.3170
0.0000
5.1679
1.11E+06
8.58E+03
Congenital posterior urethral valves
10
GUT
Cannabis
23.9399
6.0470
3.9590
0.0001
1.6001
1.64E+06
1.96E+03
Trisomy 18
11
Chromosomes
Cannabis
126.9696
26.3799
4.8131
0.0000
10.0424
1.99E+05
1.85E+03
Esophageal atresia/tracheoesophageal fistula
12
GIT
Cannabis
8.8449
1.8993
4.6570
0.0000
0.7176
1.49E+05
1.34E+03
Hypospadias
13
GUT
Cannabis
277.1790
62.0518
4.4669
0.0000
23.4595
9.34E+04
842.36
Rectal and large intestinal atresia/stenosis
14
GIT
CBD
26.0458
8.9678
2.9044
0.0040
1.3051
1.54E+08
751.61
Diaphragmatic hernia
15
Body Wall
CBD
21.8501
7.9675
2.7424
0.0065
1.1678
4.96E+07
263.36
Deletion 22q11.2
16
Chromosomes
Cannabis
6.6430
2.1356
3.1106
0.0024
0.5153
2.49E+05
155.04
Turner syndrome
17
Chromosomes
Cannabis
85.6995
27.3283
3.1359
0.0021
6.9321
1.54E+05
137.32
Epispadias
18
GUT
Cannabis
12.5446
4.8274
2.5986
0.0111
0.7392
1.02E+07
90.57
Renal agenesis/hypoplasia
19
GUT
Cannabis
27.3954
8.0283
3.4124
0.0007
3.0315
7.45E+03
66.37
Anotia/microtia
20
Face
Cannabis
37.2830
10.9541
3.4036
0.0008
4.1220
7.51E+03
65.76
Cleft palate alone
21
Face
Cannabis
24.1946
7.4701
3.2389
0.0014
2.7271
6.42E+03
48.45
Encephalocele
22
CNS
Cannabis
11.3770
3.4999
3.2507
0.0013
1.3138
5.29E+03
45.63
Aortic valve stenosis
23
CVS
Cannabis
17.8815
5.6987
3.1378
0.0019
2.1020
4.60E+03
36.41
Ventricular septal defect
24
CVS
Cannabis
166.2143
53.4999
3.1068
0.0021
19.9528
3.92E+03
32.64
Pulmonary valve atresia
25
CVS
Cannabis
9.4232
3.2900
2.8642
0.0047
1.0048
1.02E+04
29.43
Omphalocele
26
Body Wall
Cannabis
28.8975
9.4470
3.0589
0.0025
3.5144
3.55E+03
29.18
Hypoplastic left heart syndrome
27
CVS
Cannabis
10.7890
3.7873
2.8487
0.0047
1.4621
1.65E+03
15.88
Limb deficiencies (reduction defects)
28
Limb
Cannabis
21.4215
8.5782
2.4972
0.0134
2.6156
3.45E+03
9.53
Bladder exstrophy
29
GUT
Cannabis
1.0618
0.4420
2.4021
0.0170
0.1593
8.61E+02
5.62
Tetralogy of Fallot
30
CVS
Cannabis
9.9067
4.1188
2.4052
0.0168
1.6031
5.53E+02
5.16
Total anomalous pulmonary venous connection
31
CVS
Cannabis
3.9176
1.7901
2.1885
0.0299
0.4968
2.61E+03
3.71
Reduction deformity, Lower limbs
32
Limb
Cannabis
16.8233
8.1886
2.0545
0.0420
1.5723
3.39E+04
2.57
Coarctation of the aorta
33
CVS
Cannabis
22.5596
10.7794
2.0928
0.0372
4.0947
300.37
2.12
Atrial septal defect
34
CVS
Cannabis
285.3616
136.7781
2.0863
0.0378
51.3723
313.06
2.08
Spina bifida without anencephalus
35
CNS
THC
2.8769
0.8458
3.4015
0.0008
4.0422
3.23
1.96
Choanal atresia
36
Face
THC
0.4877
0.1646
2.9621
0.0033
0.7074
3.15
1.78
Anophthalmia/microphthalmia
37
CNS
THC
1.1940
0.4167
2.8651
0.0045
1.7156
3.17
1.74
Transposition of great arteries
38
CVS
CBD
19.6282
9.8766
1.9873
0.0479
1.4902
3.21E+05
1.71
Holoprosencephaly
39
Face
THC
8.0303
3.0912
2.5978
0.0104
10.1025
3.54
1.68
Congenital cataract
40
Face
Cannabis
5.9492
2.9939
1.9871
0.0479
1.0436
357.58
1.39
Single ventricle
41
CVS
THC
0.6263
0.3014
2.0780
0.0394
0.9759
2.99
1.22
To further condense this material Table 12 lists the organ systems of the various CAs listed in descending order of the percentages of the listed CAs for that organ system. It is noted immediately that the list is headed by chromosomal disorders, but that genitourinary, gastrointestinal, limb defects, body wall defects, cardiovascular anomalies and facial anomalies all have more than 50% of their listed CAs positively and potentially causally associated with one of the various cannabinoids.
Table 12
Summary Continuous Variables by System
System
No. Anomalies
Total No. Anomalies
% of Total Anomalies
Chromosomes
5
5
100.0%
GUT
6
7
85.7%
GIT
5
6
83.3%
Limb
4
5
80.0%
Body Wall
2
3
66.7%
CVS
11
19
57.9%
Face
5
9
55.6%
CNS
3
7
42.9%
Total
41
61
67.2%
A similar exercise can be performed on the CARs (not corrected for ETOPFAs) treated as categorical variables comparing the highest Quintile (Quintile 5) with the lowest quintile (Quintile 1, or the absence of data, Quintile 2).
Supplementary Table 12 shows selected parameters from this comparison extracted for those 31 CARs with elevated minimum E-Values listed in descending order of E-Values. 21 of these CARs are related to cannabis and 12 are related to cannabidiol.
Table 13 removes the duplicates from these CARs and retains the most significant results leaving 23 CARs, 17 related to cannabis and 6 to cannabidiol.
Table 13
Summary CAs with Significant Cannabinoid E-Values Categorical Variables
Defect
No.
System
Term
PR_C.I.
AFE_C.I.
ChiSqu
P-Value
E-Value-Point Estimate
E-Value-Lower Limit
Cloacal exstrophy
1
GIT
Cannabis
4.85 (4.08, 5.77)
0.79 (0.75, 0.83)
386.7336
2.13E-86
9.17
7.61
Congenital hip dislocation
2
Limb
Cannabis
2.28 (2.08, 2.51)
0.56 (0.52, 0.60)
310.8170
7.27E-70
3.99
3.57
Coarctation of the aorta
3
CVS
Cannabis
1.38 (1.31, 1.45)
0.28 (0.24, 0.31)
152.3739
2.64E-35
2.10
1.95
Obstructive genitourinary defect
4
GUT
CBD
1.92 (1.63, 2.27)
0.48 (0.39, 0.56)
62.8480
2.22E-15
3.25
2.64
Turner syndrome
5
Chromosomes
Cannabis
1.54 (1.36, 1.75)
0.35 (0.26, 0.43)
46.5388
4.58E-12
2.45
2.06
Trisomy 21 (Down syndrome)
6
Chromosomes
Cannabis
1.12 (1.08, 1.16)
0.11 (0.08, 0.14)
45.1282
9.42E-12
1.49
1.39
Diaphragmatic hernia
7
Body Wall
Cannabis
1.24 (1.15, 1.34)
0.20 (0.13, 0.26)
31.3922
1.09E-08
1.80
1.57
Trisomy 18
8
Chromosomes
Cannabis
1.22 (1.13, 1.32)
0.18 (0.11, 0.24)
25.4031
2.41E-07
1.73
1.51
Small intestinal atresia/stenosis
9
GIT
Cannabis
1.22 (1.12, 1.33)
0.18 (0.11, 0.25)
21.0508
2.33E-06
1.75
1.49
Small intestinal atresia/stenosis
9
GIT
CBD
1.26 (1.14, 1.39)
0.21 (0.12, 0.28)
20.5107
5.93E-06
1.83
1.54
Hirschsprung disease (congenital megacolon)
10
GIT
Cannabis
1.46 (1.24, 1.72)
0.31 (0.19, 0.42)
20.2790
3.50E-06
2.27
1.77
Pulmonary valve atresia
11
CVS
CBD
1.35 (1.18, 1.55)
0.26 (0.15, 0.35)
19.4818
1.02E-05
2.04
1.64
Holoprosencephaly
12
Face
Cannabis
1.27 (1.12, 1.43)
0.21 (0.11, 0.30)
14.9227
5.94E-05
1.86
1.50
Pulmonary valve atresia
13
CVS
Cannabis
1.28 (1.13, 1.45)
0.22 (0.11, 0.31)
14.7343
6.56E-05
1.87
1.50
Congenital posterior urethral valves
14
GUT
Cannabis
1.33 (1.15, 1.54)
0.25 (0.13, 0.35)
14.5658
7.18E-05
1.99
1.56
Cloacal exstrophy
15
GIT
CBD
1.30 (1.12, 1.51)
0.23 (0.11, 0.34)
11.9548
5.45E-04
1.92
1.48
Trisomy 13
16
Chromosomes
Cannabis
1.22 (1.09, 1.38)
0.18 (0.08, 0.27)
11.7980
3.18E-04
1.75
1.41
Trisomy 21 (Down syndrome)
17
Chromosomes
CBD
1.06 (1.02, 1.09)
0.05 (0.02, 0.09)
9.4889
0.0021
1.30
1.16
Double outlet right ventricle
18
CVS
Cannabis
1.21 (1.07, 1.36)
0.17 (0.06, 0.27)
9.2314
0.0013
1.70
1.34
Clubfoot
19
Limb
CBD
1.10 (1.03, 1.18)
0.09 (0.03, 0.15)
7.9686
0.0048
1.43
1.20
Deletion 22q11.2
20
Chromosomes
Cannabis
1.36 (1.09, 1.68)
0.26 (0.09, 0.41)
7.8339
0.0028
2.05
1.42
Clubfoot
21
Limb
Cannabis
1.07 (1.01, 1.14)
0.07 (0.01, 0.12)
6.0907
0.0077
1.36
1.14
Cleft lip with and without cleft palate
22
Face
CBD
1.52 (1.08, 2.14)
0.34 (0.07, 0.53)
5.8113
0.0159
2.41
1.37
Esophageal atresia/tracheoesophageal fistula
23
GIT
Cannabis
1.11 (1.02, 1.21)
0.10 (0.02, 0.17)
5.4545
0.0112
1.45
1.15
Single ventricle
24
CVS
Cannabis
1.23 (1.03, 1.46)
0.19 (0.03, 0.32)
5.4301
0.0113
1.76
1.22
Biliary atresia
25
GIT
CBD
1.20 (1.02, 1.40)
0.17 (0.02, 0.29)
5.1462
0.0233
1.69
1.18
Biliary atresia
25
GIT
Cannabis
1.19 (1.02, 1.39)
0.16 (0.02, 0.28)
5.0640
0.0141
1.67
1.17
Hypoplastic left heart syndrome
26
CVS
Cannabis
1.10 (1.01, 1.19)
0.09 (0.01, 0.16)
4.8102
0.0164
1.42
1.11
Epispadias
27
GUT
Cannabis
1.31 (1.03, 1.67)
0.24 (0.03, 0.40)
4.7877
0.0166
1.95
1.20
Diaphragmatic hernia
28
Body Wall
CBD
1.09 (1.00, 1.17)
0.08 (0.00, 0.15)
4.3354
0.0373
1.39
1.07
Double outlet right ventricle
29
CVS
CBD
1.16 (1.01, 1.33)
0.14 (0.01, 0.25)
4.3080
0.0379
1.58
1.10
Trisomy 13
30
Chromosomes
CBD
1.14 (1.00, 1.28)
0.12 (0.00, 0.22)
4.1053
0.0427
1.53
1.07
Single ventricle
31
CVS
CBD
1.22 (1.00, 1.50)
0.18 (0.00, 0.33)
3.9021
0.0482
1.75
1.04
Table 14 lists these various CARs by body system. The results are qualitatively similar to those presented in Table 12 but less dramatic.
Table 14
Summary Categorical Variables by System
System
No. Anomalies
Total No. Anomalies
% of Total Anomalies
Chromosomes
5
5
100.0%
GIT
5
6
83.3%
GUT
3
7
42.9%
Limb
2
5
40.0%
Body Wall
1
3
33.3%
CVS
5
19
26.3%
Face
2
9
22.2%
CNS
0
7
0.0%
Total
22
61
36.1%
Detailed analyses of specific congenital anomalies
It is of interest to consider two of these defects in detail by way of example of the kinds of space-time analyses which might be performed to investigate these data in greater detail. This brief analytical discussion is intended to be exemplary rather than exhaustive as a thorough spatiotemporal treatment of all of this material would require a very large undertaking indeed beyond the bounds of the space which is presently available.
Small intestinal stenosis and atresia (SISA)
We look first at small intestinal stenosis and atresia (SISA). Figure 16 presents map-graphically the states which provided data for this analysis. SISA is not diagnosed prenatally and is not impacted by ETOPFA practices.
Fig. 16
Map-graph of the incidence of small intestinal atresia or stenosis across USA over time
×
Supplementary Table 13 presents the results of final inverse probability weighted mixed effects models. Interestingly one notes that in these models cannabis and / or cannabinoids are significantly related to SISA incidence. Importantly cannabidiol is independently significantly related and has a positive coefficient in all models in which it appears.
Supplementary Table 14 presents final inverse probability weighted robust generalized linear regression models. Cannabis is significant alone. When all the substances are included in an additive model, only cannabis remains as shown in the second model on this page. In an interactive model with drugs cannabis is again independently significant. In comprehensive additive and interactive models including income and all ethnicities, significant terms including cannabidiol appear in both final models.
Supplementary Table 15 presents the results of inverse probability weighted panel regression models lagging cannabinoids. In both additive and interactive models terms including cannabidiol are significant and have positive coefficients.
States contributing data to the SISA dataset are shown in Supplementary Fig. 9 along with their edited geospatial linkages.
Table 15 presents the results of final geospatial models. Terms including cannabis are positive and significant in all cases.
Table 15
Small Intestinal Stenosis or Atresia - Introductory Space – Time Regression Models
Table 16 shows the results of final geospatial models looking at substances using the cannabinoids as covariates. In all cases terms including the cannabinoids are significant. In models lagged at one, two and three years terms including cannabidiol are significant and the coefficients positive.
Table 16
Small Intestinal Stenosis or Atresia - Cannabinoid Space – Time Regression Models
Table 17 presents a similar analysis this time including all income and ethnicity covariates. In each model terms for the cannabinoids are positive and significant. In each model terms including cannabidiol are also positive and significant.
Table 17
Small Intestinal Stenosis or Atresia - Comprehensive Cannabinoid Space – Time Regression Models
Table 18 collects some of the regression terms from earlier tables and presents their applicable computed E-Values for the inverse probability weighted mixed effects and panel models.
Table 18
Small Intestinal Stenosis or Atresia - E-Values from Mixed Effects and Panel Regression Models
Parameter
Estimate (C.I.)
R.R. (C.I.)
E-Values
MIXED EFFECTS
Cannabis Only
Cannabis
2.83 (2.03, 3.63)
5.66 (3.48, 3.19)
10.80, 6.43
Additive Model – Drugs
Cannabis
1.46 (0.69, 2.22)
3.91 (1.93, 7.92)
7.28, 3.27
Interactive Model – Drugs
Cigarettes: Cannabis: Binge.Alcohol
5638.66 (3549.85, 7727.46)
Infinity (Infinity, Infinity)
Infinity, Infinity
Cigarettes: Cannabis: Binge.Alcohol: Analgesics
1797.36 (1122.19, 2472.54)
Infinity (Infinity, Infinity)
Infinity, Infinity
Cannabis: Binge.Alcohol
8008.91 (4682.06, 11,335.77)
Infinity (Infinity, Infinity)
Infinity, Infinity
Cannabis: Binge.Alcohol: Analgesics
2546 (1467.93, 3624.06)
Infinity (Infinity, Infinity)
Infinity, Infinity
Additive Model – Cannabinoids
THC
0.94 (0.41, 1.48)
2.41 (1.47, 3.93)
4.24, 2.31
CBD
0.84 (0.25, 1.43)
2.18 (1.27, 3.74)
3.78, 1.85
Interactive Model – Cannabinoids
CBG: CBD
10.47 (7.47, 13.47)
4.59E+06 (6.01E+04, 3.51E+08)
3.18E+06, 1.20E+05
CBD
34.98 (24.72, 45.24)
1.85E+22 (6.74E+15, 5.11E+28)
3.71E+22, 1.34E+16
THC: CBG: CBD
0.57 (0.37, 0.76)
2.29 (1.73, 3.04)
4.03, 2.87
CBG
32.45 (19.49, 45.41)
2.45E+20 (3.32E+12, 6.15E+28)
3.05E+20, 6.65E+12
Cigarettes: THC: CBD
13.79 (6.1, 21.48)
6.03E+08 (8.99E+06, 4.03E+13)
1.21E+09, 1.80E+04
Additive Model - Including Sociodemographics
THC
1.45 (0.79, 2.12)
3.97 (2.12, 7.41)
7.41, 3.67
CBD
0.81 (0.21, 1.4)
2.145 (1.24, 3.77)
3.74, 1.77
Interactive Model - Including Sociodemographics
CBG
77.88 (58.11, 97.66)
3.15E+38 (7.30E+28, 1.36E+48)
6.30E+38, 1.46E+29
CBD
63.63 (47.13, 80.13)
2.82E+31 (2.57E+23, 3.09E+39)
5.64E+31, 5.15E+23
CBG: CBD
18.44 (13.62, 23.25)
1.29E+09 (5.85E+06, 2.87E+11)
2.59E+09, 1.17E+07
Cigarettes: THC
2351.21 (1186.17, 3516.25)
Infinity (Infinity, Infinity)
Infinity, Infinity
Cigarettes: THC: CBD
548.39 (275.16, 821.63)
2.07E+284 (4.31E+141, Infinity)
Infinity, 8.61E+141
Cigarettes: THC: CBG: CBD
135.08 (66.39, 203.77)
5.92E+66 (2.01E+33, 1.74E+100)
1.18E+67, 4.03E+33
Cigarettes: THC: CBG
575.97 (282.33, 869.61)
1.19E+271 (8.89E+137, Infinity)
Infinity, 1.77E+138
PANEL MODELS
Additive Model - Including Sociodemographics
CBG
1.07 (0.51, 1.63)
3.31 (1.77, 3.17)
6.06, 2.94
CBD
0.61 (0.23, 0.99)
1.97 (1.298, 3.02)
3.36, 1.91
Interactive Model - Including Sociodemographics
Cigarettes: THC
20.18 (10.52, 29.83)
4.31E+28 (9.13E+14, 2.04E+42)
8.63E+28, 1.82E+15
CBG: CBD
0.92 (0.4, 1.44)
20.014 (3.65, 109.74)
39.53, 6.76
CBD
3.68 (1.19, 6.16)
1.65E+05 (49.84, 5.46E+08)
3.30E+05, 99.18
1 Years Lag
Cigarettes: THC
6.68 (3.64, 9.72)
2.42E+06 (70.07, 8.34E+03)
4.83E+03, 139.63
Table 19 performs a similar role for regression terms derived from geospatial models.
Table 19
Small Intestinal Stenosis or Atresia - E-Values from Space – Time Regression Models
Parameter
Estimate (C.I.)
R.R. (C.I.)
E-Values
SPACE-TIME MODELS
Additive Model - Drugs
Cannabis
1.15 (0.46, 1.84)
9.60 (2.48, 37.17)
18.70, 4.40
Interactive Model - Drugs
Cigarettes: Cannabis: Binge.Alcohol
57.95 (30.14, 85.75)
2.40E+28 (6.17E+14, 9.36E+41)
4.81E+28, 1.23E+15
Cannabis: Binge.Alcohol
30.95 (15.37, 46.53)
1.44E+15 (3.48E+07, 5.96E+22)
2.88E+15, 6.96E+07
Cigarettes: Cannabis: Binge.Alcohol: Analgesics
11.55 (3.04, 20.06)
4.54E+05 (31.57, 6.55E+09)
9.09E+05, 62.64
2 Years Lag
Interactive Model - Drugs
Cannabis: Analgesics
68.51 (39.94, 97.07)
6.69E+62 (4.80E+36, 9.34E+88)
1.33E+63, 9.61E+36
4 Years Lag
Interactive Model - Drugs
Cannabis: Analgesics
1284.76 (677.88, 1891.64)
Infinity (Infinity, Infinity)
Infinity, Infinity
Cannabis
4106.59 (2160.15, 6053.02)
Infinity (Infinity, Infinity)
Infinity, Infinity
Additive Model - Cannabinoids
CBG
0.96221 (0.28, 1.64)
16.09 (2.45, 105.29)
31.67, 4.35
Interactive Model - Cannabinoids
Cigarettes: THC: Binge.Alcohol
5169.433 (3191.79, 7147.08)
Infinity (Infinity, Infinity)
Infinity, Infinity
THC
172.247 (93.57, 250.92)
4.79E+103 (2.62E+56, 8.74E+150)
9.58E+103, 5.25E+56
Cigarettes: THC: CBG: Binge.Alcohol
480.252 (250.09, 710.41)
1.19E+289 (6.58E+150, Infinity)
Infinity, 1.31E+151
Cigarettes: CBG
339.558 (175.8, 503.32)
2.45E+204 (1.04E+106, 5.80E+302)
Infinity, 2.08E+106
CBG: Binge.Alcohol
276.267 (124.22, 428.31)
1.96E+166 (9.07E+74, 4.26E+257)
Infinity, 1.81E+75
1 Years Lag
Interactive Model - Cannabinoids
Cigarettes: CBD
510 (212.08, 807.92)
Infinity (2.65E+187, Infinity)
Infinity, Infinity
Cigarettes: THC: CBD
563 (229.8, 896.2)
Infinity (1.78E+204, Infinity)
Infinity, Infinity
Cigarettes: THC: CBG
1770 (513.64, 3026.36)
Infinity (Infinity, Infinity)
Infinity, Infinity
THC
5.51 (0.37, 10.65)
7.74E+04 (2.18, 2.74E+09)
1.55E+05, 3.79
2 Years Lag
Interactive Model - Cannabinoids
Cigarettes: CBG
2040.99 (821.21, 3260.77)
Infinity (Infinity, Infinity)
Infinity, Infinity
CBG: CBD
6381.11 (2226.34, 10,535.89)
Infinity (Infinity, Infinity)
Infinity, Infinity
THC
10.36 (1.06, 19.65)
7.65E+09 (10.81, 5.41E+18)
1.53E+10, 21.11
3 Years Lag
Interactive Model - Cannabinoids
CBD
3.38 (0.51, 6.26)
183.44 (2.20, 1.52E+04)
366.39, 3.83
Interactive Model - Including Sociodemographics
CBG
1.15 (0.45, 1.85)
11.34 (2.58, 49.90)
22.17, 4.59
Cigarettes: CBD
1.33 (0.36, 2.3)
16.55 (2.15, 127.21)
32.59, 3.72
1 Years Lag
Interactive Model - Including Sociodemographics
Cigarettes: THC
109.89 (22.86, 196.92)
4.32E+91 (1.62E+19, 1.15E+164)
8.68E+91, 3.25E+19
Cigarettes: THC: CBD
24.48 (3.55, 45.41)
2.57E+20 (985.96, 6.70E+37)
5.14E+20, 1.97E+03
2 Years Lag
Interactive Model - Including Sociodemographics
CBD
1.00 (0.41, 1.60)
6.70 (2.18, 20.54)
12.89, 3.80
CBG
1.74 (0.53, 2.94)
26.83 (2.76, 260.21)
53.17, 4.98
THC: CBD
1.75 (0.48, 3.03)
274.86 (2.47, 313.56)
55.22, 4.38
THC
5.80 (0.80, 10.8)
2.96E+04 (4.60, 7.71E+08)
1.19E+05, 6.68
Supplementary Table 16 lists all 57 of these minimum E-Values in descending order. All 57 are noted to be above the threshold of 1.25, 34 are noted to be greater than 100 and 13 are infinite.
It is of interest to consider predicted values from geospatiotemporal models. For this purpose the comprehensive interactive model shown in Table 17 lagged to two years was chosen.
The 101 predicted percentile values from matrix multiplication and scale adjustment are shown graphically in Fig. 17 with least squares regression lines, cubic polynomial and GAM curves are fitted. Percentiles refer to percentiles of cannabidiol exposure. Supplementary Table 17 presents the comparison of the ninetieth and tenth percentiles, the 95th and fifth percentiles and the first and 99th percentiles. An increasing ratio is noted in the right hand column consistent with an increasing effect at higher doses, and the obvious upwards inflection point on the fitted curve.
Fig. 17
Modelled rates of small intestinal stenosis or atresia rates with rising cannabidiol exposure in a geospatial model lagged to two years
×
Supplementary Table 18 presents concisely the results of the various linear, polynomial and GAM regressions. At Anova testing the cubic curve is noted to have a superior fit to the least squares regression line (Anova: F = 365.64, df = 2, 97, P = 7.86x10−47) and the GAM is also noted to have a superior fit to the least squares line (Anova: F = 265.91, df = 7.89, 91.11, P = 2.83x10−60). The GAM model was superior to the cubic model (Anova: F = 23.096, df = 5.85, 93.15, P = 3.37x10−16).
Supplementary Table 19 presents the E-Values which are applicable to these linear regression results. The minimum E-Values are noted to range up to 1.73x1036.
As mentioned the abscissa of this regression study was percentiles of cannabidiol exposure. When percentiles of the three cannabinoids THC, cannabigerol and cannabidiol were used instead similar results were obtained particularly with relation to strongly sigmoidal modelled trends (results not shown).
Obstructive genitourinary defects
Figure 18 illustrates states contributing data to the obstructive genitourinary disorder (OGUD) dataset. This disorder is diagnosed prenatally but is not subject to ETOPFA practices.
Fig. 18
Map-graph of the incidence of obstructive genitourinary defects across USA over time
×
Supplementary Table 20 presents final inverse probability weighted mixed effects models. Interestingly cannabis is again shown to be the only remaining term in the final additive model for drugs. In the last two models on the comprehensive dataset, the effect of cannabinoids is strongly positive. In the final comprehensive interactive model two significant terms include cannabidiol and have positive β-coefficients.
Final inverse probability weighted robust generalized linear regression models are presented in Supplementary Table 21. In the final comprehensive interactive model shown in this Table two terms for cannabidiol are strongly positive at high levels of statistical significance.
Final comprehensive inverse probability weighted panel regression models for cannabinoids are shown in Supplementary Table 22. Many positive terms for cannabinoids are noted.
Supplementary Fig. 10 illustrates the geospatial linkages which were derived and edited for the OGUD dataset.
Table 20 presents the results of final geospatiotemporal models for OGUD incidence. One notes that cannabis alone is highly signifcant. In an additive model limited to substance covariates, cannabis was the only remaining significant term in the final model. At two years of lag cannabis was again the most significant term. The overall effect of cannabis in this model was positive. The effects of THC, cannabigerol and cannabidiol considered separately were positive in each case.
Table 20
Obstructive Genitourinary Defects - Introductory Space – Time Regression Models
Table 22 lists final comprehensive interactive and interactive temporally lagged models. All models include positive significant terms for cannabinoids.
Table 22
Obstructive Genitourinary Defects - Comprehensive Cannabinoid Space – Time Regression Models
Table 23 lists the E-Values derived from mixed effects and panel regression models and Table 24 shows those derived from spatiotemporal models.
Table 23
Obstructive Genitourinary Defects - E-Values from Mixed Effects and Panel Regression Models
Parameter
Estimate (C.I.)
R.R. (C.I.)
E-Values
MIXED EFFECTS MODELS
Cannabis Only
Cannabis
14.35 (8.44, 20.27)
94.85 (15.13, 594.66)
189.20, 29.75
Additive Model - Drugs
Cannabis
14.35 (8.44, 20.27)
94.85 (15.13, 594.66)
189.20, 29.75
Interactive Model - Drugs
Cigarettes: Cannabis: Analgesics
333.48 (176.14, 490.83)
1.62E+51 (4.54E+27, 5.81E+74)
3.25E+51, 9.09E+27
Cannabis: Bng.Alcohol: Analgesics
700.3 (368.06, 1032.54)
3.47E+107 (6.41E+57, 1.88E+157)
6.94E+107, 1.29E+58
Cannabis: Bng.Alcohol
921.93 (370.26, 1473.6)
3.75E+1241 (9.87E+58, 1.43E_224)
7.51E+141, 1.97E+59
Additive Model - Cannabinoids
THC
43.47 (8.06, 78.89)
1.72E+06 (18.61, 1.59E+11)
3.43E+06, 36.72
Interactive Model - Cannabinoids
Cigarettes: THC
1945.4 (832.31, 3058.5)
2.73E+296 (5.73E+130, Infinity)
Infinity, 1.14E+131
Cigarettes: THC: CBG
482.22 (204.16, 760.28)
3.02E+73 (1.23E+32, 7.37E+114)
6.04E+73, 2.46E+32
Additive Model - Including Sociodemographics
THC
11.62 (7.82, 15.42)
58.96 (16.01, 217.10)
117.42, 31.52
Interactive Model - Including Sociodemographics
THC: CBG
918.55 (286.58, 1550.52)
2.27E+138 (4.07E+45, 1.27E+231)
4.55E+138, 8.15E+45
THC: CBG: CBD
248.54 (72.69, 424.4)
2.73E+37 (4.24E+11, 1.76E+63)
5.46E+37, 8.49E+11
THC
3517.29 (910.69, 6123.89)
Infinity (1.78E+147, Infinity)
Infinity, 3.57E+147
THC: CBD
946.55 (214.43, 1678.68)
3.75E+142 (1.34E+35, 1.05E+250)
7.51E+142, 2.69E+35
PANEL MODELS
Interactive Model - Including Sociodemographics
THC
7726.08 (3068.06, 12,384.1)
Infinity (9.29E+186, Infinity)
Infinity, Infinity
THC: CBD
2899.61 (1040.91, 4758.31)
1.47E+176 (2.93E+63, 7.39E+288)
Infinity, 5.86E+63
THC: CBG: CBD
202.14 (44.72, 359.56)
1.91E+12 (545.0179, 6.69E+21)
3.82E+12, 1.09E+03
Sociodemographic Interactive Model - 1 Lag
Cigarettes: THC: CBD
163.56 (80.31, 246.82)
4.75E+08 (1.85E+04, 1.21E+13)
9.50E+08, 3.71E+04
Cigarettes: THC
719.66 (347.71, 1091.61)
1.50E+38 (3.05E+18, 7.39E+57)
3.01E+38, 6.11E+18
Additive Model - Drugs
Cannabis
10.61 (4.7, 16.52)
5.66E+19 (8.37E+08, 3.82E+30)
1.13E+20, 1.67E+09
Interactive Model - Drugs
Cannabis
10.61 (4.7, 16.52)
44.75 (5.40, 370.45)
89.06, 10.29
Interactive Model - Drugs, 2 Lags
Cannabis
241.68 (65.24, 418.12)
3.25E+08 (204.43, 5.18E+14)
6.51E+08, 408.35
THC
THC
8.14 (4.27, 12)
19.67 (4.78, 80.93)
38.84, 9.03
Cannabigerol
Cannabigerol
7.54 (3.14, 11.94)
14.30 (3.04, 67.26)
28.10, 5.53
Additive Model - Drugs & Cannabinoids
THC
8.14 (4.27, 12)
18.91 (4.68, 76.34)
37.31, 8.84
Interactive Model - Drugs & Cannabinoids
THC
8.14 (4.27, 12)
19.67 (47.78, 80.94)
38.84, 9.04
1 Spatial Lag - Interactive Model, THC * CBD
Cigarettes: CBD
792.04 (292.87, 1291.2)
2.15E+125 (3.19E+46, 1.45E+204)
4.31E+125, 6.39E+46
Cigarettes: THC: CBD
912.27 (282.87, 1541.68)
2.29E+144 (9.107E+44, 5.77E+243)
4.58E+144, 1.83E+45
Cigarettes: THC
3167.74 (941.61, 5393.88)
Infinity (5.16E+149, Infinity)
Infinity, 1.03E+150
1 Spatial Lag - Interactive Model, THC * CBG
Cigarettes: THC: CBG
855.74 (286.28, 1425.2)
8.09E+135 (4.45E+45, 1.47E+226)
1.61E+136, 8.91E+45
Cigarettes: THC
2980.74 (841.4, 5120.08)
Infinity (2.06E+134, Infinity)
Infinity, 4.14E+134
Cigarettes: CBG
755.71 (171.07, 1340.34)
1.05E+120 (2.27E+27, 4.83E+212)
2.09E+120, 4.54E+27
1 Spatial, 1 Temporal Lag Cannabinoids
Cigarettes: THC: CBD
1394.48 (386.59, 2402.38)
4.17E+192 (4.79E+53, Infinity)
Infinity, 9.59E+53
Cigarettes: THC: THC.Spatial: CBD
1384.11 (374.49, 2393.72)
1.53E+1981 (1.02E+52, Infinity)
Infinity, 2.05E+52
Cigarettes: THC
5000.58 (1323.37, 8677.78)
Infinity (6.65E+183, Infinity)
Infinity, Infinity
Cigarettes: THC: THC.Spatial
4975.93 (1182.67, 8769.19)
Infinity (2.62E+164, Infinity)
Infinity, Infinity
Cigarettes: CBD
522.98 (44.27, 1001.7)
1.74E+72 (1.77E+06, 1.70E+138)
3.47E+72, 3.54E+06
1 Spatial, 2 Temporal Lags Cannabinoids
Cigarettes: CBD
48,350.5 (20,095.92, 76,605.08)
Infinity (Infinity, Infinity)
Infinity, Infinity
Cigarettes: THC
217,699.3 (89,605.46, 345,793.14)
Infinity (Infinity, Infinity)
Infinity, Infinity
Cigarettes: THC: CBD
76,973.5 (31,232.59, 122,714.41)
Infinity (Infinity, Infinity)
Infinity, Infinity
THC
11,707.8 (4631.81, 18,783.79)
Infinity (1.01E+190, Infinity)
Infinity, Infinity
THC: THC.Spatial
19,063 (7395.32, 30,730.68)
Infinity (2.51E+303, Infinity)
Infinity, Infinity
Interactive Model - Including Sociodemographics
THC
37.58 (9.36, 65.79)
1.86E+06 (37.31, 9.29E+10)
3.72E+06, 74.13
THC: CBG
6.95 (0.33, 13.56)
14.44 (1.14, 1852.37)
28.36, 1.54
Sociodemographic Interactive, 1 Lag
Cigarettes: THC
46.25 (16.84, 75.67)
3.85E+05 (109.80, 1.35E+09)
7.71E+05, 219.10
Sociodemographic Interactive, 2 Lags
Cigarettes: THC: CBD
6151.83 (2693.75, 9609.91)
1.63E+301 (1.72E+132, Infinity)
Infinity, 3.45E+132
Cigarettes: THC
22,951.53 (9883.29, 36,019.77)
Infinity (Infinity, Infinity)
Infinity, Infinity
Cigarettes: CBD
4078.6 (1248.29, 6908.9)
5.02E+199 (2.51E+61, Infinity)
Infinity, 5.02E+61
Table 24
Obstructive Genitourinary Defects - E-Values from Space-Time Regression Models
Parameter
Estimate (C.I.)
R.R. (C.I.)
E-Values
Additive Model – Drugs
Cannabis
10.61 (4.7, 16.52)
5.66E+19 (8.37E+08, 3.82E+30)
1.13E+20, 1.67E+09
Interactive Model – Drugs
Cannabis
10.61 (4.7, 16.52)
44.75 (5.40, 370.45)
89.06, 10.29
Interactive Model - Drugs, 2 Lags
Cannabis
241.68 (65.24, 418.12)
3.25E+08 (204.43, 5.18E+14)
6.51E+08, 408.35
THC
THC
8.14 (4.27, 12)
19.67 (4.78, 80.93)
38.84, 9.03
Cannabigerol
Cannabigerol
7.54 (3.14, 11.94)
14.30 (3.04, 67.26)
28.10, 5.53
Additive Model - Drugs & Cannabinoids
THC
8.14 (4.27, 12)
18.91 (4.68, 76.34)
37.31, 8.84
Interactive Model - Drugs & Cannabinoids
THC
8.14 (4.27, 12)
19.67 (47.78, 80.94)
38.84, 9.04
1 Spatial Lag - Interactive Model, THC * CBD
Cigarettes: CBD
792.04 (292.87, 1291.2)
2.15E+125 (3.19E+46, 1.45E+204)
4.31E+125, 6.39E+46
Cigarettes: THC: CBD
912.27 (282.87, 1541.68)
2.29E+144 (9.107E+44, 5.77E+243)
4.58E+144, 1.83E+45
Cigarettes: THC
3167.74 (941.61, 5393.88)
Infinity (5.16E+149, Infinity)
Infinity, 1.03E+150
1 Spatial Lag - Interactive Model, THC * CBG
Cigarettes: THC: CBG
855.74 (286.28, 1425.2)
8.09E+135 (4.45E+45, 1.47E+226)
1.61E+136, 8.91E+45
Cigarettes: THC
2980.74 (841.4, 5120.08)
Infinity (2.06E+134, Infinity)
Infinity, 4.14E+134
Cigarettes: CBG
755.71 (171.07, 1340.34)
1.05E+120 (2.27E+27, 4.83E+212)
2.09E+120, 4.54E+27
1 Spatial, 1 Temporal Lag Cannabinoids
Cigarettes: THC: CBD
1394.48 (386.59, 2402.38)
4.17E+192 (4.79E+53, Infinity)
Infinity, 9.59E+53
Cigarettes: THC: THC.Spatial: CBD
1384.11 (374.49, 2393.72)
1.53E+1981 (1.02E+52, Infinity)
Infinity, 2.05E+52
Cigarettes: THC
5000.58 (1323.37, 8677.78)
Infinity (6.65E+183, Infinity)
Infinity, Infinity
Cigarettes: THC: THC.Spatial
4975.93 (1182.67, 8769.19)
Infinity (2.62E+164, Infinity)
Infinity, Infinity
Cigarettes: CBD
522.98 (44.27, 1001.7)
1.74E+72 (1.77E+06, 1.70E+138)
3.47E+72, 3.54E+06
1 Spatial, 2 Temporal Lags Cannabinoids
Cigarettes: CBD
48,350.5 (20,095.92, 76,605.08)
Infinity (Infinity, Infinity)
Infinity, Infinity
Cigarettes: THC
217,699.3 (89,605.46, 345,793.14)
Infinity (Infinity, Infinity)
Infinity, Infinity
Cigarettes: THC: CBD
76,973.5 (31,232.59, 122,714.41)
Infinity (Infinity, Infinity)
Infinity, Infinity
THC
11,707.8 (4631.81, 18,783.79)
Infinity (1.01E+190, Infinity)
Infinity, Infinity
THC: THC.Spatial
19,063 (7395.32, 30,730.68)
Infinity (2.51E+303, Infinity)
Infinity, Infinity
Interactive Model - Including Sociodemographics
THC
37.58 (9.36, 65.79)
1.86E+06 (37.31, 9.29E+10)
3.72E+06, 74.13
THC: CBG
6.95 (0.33, 13.56)
14.44 (1.14, 1852.37)
28.36, 1.54
Sociodemographic Interactive, 1 Lag
Cigarettes: THC
46.25 (16.84, 75.67)
3.85E+05 (109.80, 1.35E+09)
7.71E+05, 219.10
Sociodemographic Interactive, 2 Lags
Cigarettes: THC: CBD
6151.83 (2693.75, 9609.91)
1.63E+301 (1.72E+132, Infinity)
Infinity, 3.45E+132
Cigarettes: THC
22,951.53 (9883.29, 36,019.77)
Infinity (Infinity, Infinity)
Infinity, Infinity
Cigarettes: CBD
4078.6 (1248.29, 6908.9)
5.02E+199 (2.51E+61, Infinity)
Infinity, 5.02E+61
These 47 E-Values are listed in descending order in Supplementary Table 23. All 47 are noted to be above 1.25, 36 are noted to be above 100 and nine are noted to be infinite.
It is of interest to consider the way in which rising levels of cannabidiol might impact these results. The model chosen was the first comprehensive interactive model shown in Table 21 lagged to two years. Percentiles refer to percentiles of cannabidiol exposure.
The results of matrix multiplication and scale revision are shown in Fig. 19 with least squares regression lines, cubic polynomial and GAM curves fitted. Percentiles are compared in Supplementary Table 24 and one again notes an increasing ratio reflecting the obvious inflection points in the fitted curves. Regression summaries for these three smoothers are shown in Supplementary Table 25. At Anova testing both the cubic polynomial (Anova: F = 499.86, df = 2, 97, P = 5.82x10−51) and the GAM curve (Anova: F = 172.08, df = 7.7934, 91.207, P = 1.61x10−71) are noted to be superior to the least squares regression line confirming the significance of the inflection points in the curves.
Fig. 19
Modelled rates of obstructive genitourinary defect with rising cannabidiol exposure in a geospatial model lagged to two years
×
The E-Values from the two linear regression models are shown in Supplementary Table 26 and their minima are noted to range up to 8.36x1041 in the case of the cubic polynomial curve.
When this exercise was repeated for this congenital anomaly including percentiles of THC and cannabigerol in addition to cannabidiol exposure, again the sigmoidal non-linear shape of the fitted curve was strongly confirmed (results not shown).
Discussion
Main results
The overall picture to emerge from this national state level survey of cannabinoid teratogenesis confirms and extends the Hawaiian study of 2007 [13] in preference to the “standard model” of cannabinoid and cannabidiol teratogenesis widely canvassed in the medical profession. These findings support the genotoxic warnings placed by national regulatory agencies on approved cannabinoid products including cannabidiol.
The main outcome from this USA teratological survey and overview is that cannabis, THC, cannabidiol and cannabigerol have highly significant associations with congenital anomaly rates whether considered as continuous variables by regression line slope or categorical variables by comparing extreme quintiles and are accompanied by highly significant prevalence ratios, attributable fractions in the exposed, population attributable risks, significance levels and E-values. For the continuous variable analysis 28 of the 41 CAs listed in Table 11 have minimum E-Values greater than 9.0 which is the very high value found in the tobacco-lung cancer relationship [86]. As judged by the number of ETOPFACARs impacted this putative teratogenic effect is greater for THC (40 CAs) than for cannabis (35 CAs) than for tobacco (11 CAs). For cannabidiol (11 CAs) this effect is greater than either last month alcohol consumption (5 CAs) or binge alcohol consumption (2 CAs). For two CAs considered in detail by spatiotemporal analysis and the formal techniques of causal inference, namely small intestinal stenosis or atresia and obstructive genitourinary defects, there is clear epidemiological evidence of both close association across time and space which persists after full model adjustment, and of a causal relationship with cannabinoid including cannabidiol exposure. Moreover predictive modelling from selected spatiotemporal models demonstrates that the relationship between rising cannabidiol exposure and CA incidence is strongly sigmoidal in that both fitted curves show obvious strong positive inflections in their upper ranges which is closely and strongly reminiscent of the exponential dose-response curves observed in the laboratory in numerous genotoxic and mitochondriopathic assays [21, 24, 26, 31, 42, 54‐65, 87]. P-values for this non-linearity are 2.83x10−60 and 1.61x10 −71 respectively. For these CAs minimum polynomial E-Values for the predictive percentile models range up to 1.73x1036 and 8.36x1041.
The slope of the bivariate relationship between estimates of the ETOPFA-corrected CA incidence rate and the rate of substance exposure for many anomalies is significantly elevated for cannabis, THC and cannabidiol. As shown in Table 2 35 ETOPFA-corrected congenital anomalies have elevated minimum E-values by cannabis exposure regression slope which comprise nine cardiovascular anomalies, six anomalies of the urinary tract, five anomalies of the gastrointestinal tract, all five chromosomal anomalies, four limb musculoskeletal anomalies, two each of face and body wall anomalies and one brain anomaly. For 28 of these 35 anomalies the minimum E-Value is greater than 9.0. The forty CAs with elevated E-values after THC exposure may be grouped as ten cardiovascular CAs, six gastrointestinal CAs, six CAs of the urinary tract, all five chromosomal CAs, five CAs of the facial structures, four CAs of limb development including limb deficiencies and leg reductions, two central nervous system CAs including encephalocele and spina bifida without anencephalus, and two CAs of the body wall development diaphragmatic hernia and omphalocele (Supplementary Table 6).
The twelve ETOPFACARs with elevated E-Values from regression slopes after cannabidiol exposure include small and large intestinal esophageal and biliary atresias and stenoses, hip dislocation, obstructive genitourinary anomalies, and diaphragmatic herniae, cleft palate, reduction deformity of legs and transposition of the great arteries. Obstructive genitourinary defect, esophageal, small and large intestinal and biliary atresias and stenoses, diaphragmatic hernia, Hirschsprungs disease and hip dislocation have elevated E-Values when cannabidiol is considered as both continuous and categorical variables (Tables 3 and 5). For nine of these 12 CAs the minimum E-Value is greater than 18 (Table 3).
Tables 2 and 4 list the CAs with elevated E-Values when cannabis is treated as a continuous and as a categorical variable respectively. The defects which appear on both lists are the chromosomal anomalies Trisomies 13, 18 and 21 (Downs syndrome) and Deletion 22q11.2; the gastrointestinal anomalies esophageal atresia, small intestinal atresia or stenosis, biliary atresia and Hirschsprung disease; the cardiovascular defects hypoplastic left heart syndrome, coarctation of the aorta and pulmonary valve atresia or stenosis; the limb defects congenital hip dislocation and clubfoot, the body wall defect diaphragmatic hernia, and the urological disorder congenital posterior urethral valve.
Interpretation
Hence these data show not only close association between cannabinoid exposure and various CAs but clearly indicate the existence of a threshold effect above which the teratogenic impact dramatically increases, closely mirroring in patterns of human disease the amply documented threshold effects seen in cellular, molecular, genotoxic and epigenotoxic laboratory studies [21, 24, 26, 31, 42, 54‐65, 87].
The present study is intended to be introductory and pathfinding in the sense that its methods are not widely deployed across the published literature of the clinical teratological disciplines and we are keen to see advanced statistical methods more widely utilized to study the important questions raised by this study. However it is also true that sufficient evidence has been presented in the above material to enable several conclusions to be made definitively. Cannabinoid genotoxicity as tracked across multiple congenital anomalies is clinically significant and of public health importance and concern. Cannabis and cannabidiol test strongly positive on the bivariate results presented and are each implicated in more congenital anomalies than either tobacco or alcohol respectively both legal drugs which are widely acknowledged to be toxic to the developing foetus. Based on the very elevated minimum E-Values ofound cannabidiol is also a clinically significant teratogen and presumptive genotoxin and is more potent than either binge alcohol consumption or last month alcohol use. For selected congenital anomalies cannabinoid teratogenicity persists after multivariable adjustment in inverse probability weighted models of causal inference, and after consideration in their inherently space-time context. For both congenital anomalies studied in detail spatiotemporal modelling shows strong evidence of a threshold effect above which the impacts of cannabidiol and cannabinoid teratogenicity are supra-linear, sigmoidal and greatly amplified.
These findings lead to the sobering conclusion that cannabinoid genotoxicity is of great public health importance to maternal-foetal and reproductive medicine in contrast to the fact that it appears to be largely missing from public health discourse to date where it is essentially overlooked.
Moreover given that the prevalence of cannabis use and cannabinoid exposure in the global community is clearly rising increasing cannabinoid exposure will not be related in simple linear fashion to increased congenital anomalies across a wide spectrum of developmental disorders, but the non-linearity of the relationship and the existence of clear thresholds for genotoxicity both in the laboratory and across diverse human communities (in USA as a whole and in Hawaii, Colorado, Canada and Australia [13, 17‐20]) implies that a much greater incidence of clinical teratogenesis might reasonably be expected to accompany this increased use, as was indeed recently demonstrated nationwide in USA for atrial septal defect secundum type [16] and for autism [66, 88] and has also recently been demonstrated in Canada and Australia [17‐19]. This was also recently confirmed for all five chromsomal disorders reported across USA [89].
The present report is preliminary in the sense that a wider detailed geotemporospatial and causal inference study of many other congenital anomalies is clearly indicated. At the time of writing this more comprehensive and detailed manuscript is in preparation. Our unpublished findings are that such upper range predicted curve positive inflections and sigmoidality are typical and normative amongst geospatial models for almost all positively impacted congenital anomalies studied to date. Also strongly indicated are geotemporospatial studies at finer geospatial resolution such as was recently published from CDC for gastroschisis at county level and which employed similar prevalence ratio methodology to the present study [90].
One notes also that the USA is moving relatively rapidly into an era when cannabinoids are more widely available than previously as the legislative regimes relating to cannabis are progressively relaxed. The replacement of tobacco crops in many places with hemp crops implies that cannabinoids of various forms will increasingly enter the food chain both explicitly as lollies, candies, chocolates, sauces, health foods and oils, and implicitly as stock feed, bird feed and in dairy and egg products. It therefore seems inevitable in such a paradigm that population level cannabinoid exposure will necessarily increase. In this context the traditional way of doing teratological studies by simply asking a binary question as to maternal antenatal exposure to cannabis becomes increasingly inaccurate and passé. Calls for a quantitative biomarker of cannabinoid exposure have been issued derived potentially from epigenomic and / or glycomic metrics [91]. As we enter an era of more widespread known and unknown cannabinoid exposure in the community, higher level cannabinoid potency, higher intensity cannabis use and the widespread availability of highly concentrated cannabinoid oils, dabs, waxes, shatters, extracts and products it seems that the urgency of deriving such a quantitative biomarker necessarily proportionately increases. An important corollary of the deployment of such an objective biomarker is that much smaller numbers of maternal-foetal pairs can be used to measure effect sizes and the chance of mis-attribution is potentially greatly reduced with the added advantage for analysis and for statistical power that cannabinoid exposure can be treated more properly as a continuous variable.
Mechanistic considerations
Role of morphogen gradients in body pattern formation
The gradients of various key morphogens control of the formation of the body in many respects [92]. This is well illustrated in the case of the neural tube which goes to form the spinal cord and central nervous system. Bone morphogenetic proteins and Wnts are released from the dorsal roof plate region in high concentration. Sonic hedgehog (shh) is released form the notochord and induces shh release form the ventral floorplate of the neural tube in high concentration [92]. Hence between the dorsal roof plate and the ventral floor plate there exist opposing and antagonistic gradients from BMPs and Wnts dorsally as against shh ventrally. Shh suppresses class I factors (Pax-3/7, Dbx-1, Dbx-2, Irx3 and Pax-6) and stimulates class II factors (Foxa-2, Nkx-6.2, Nkx-6.1, Olig-2, Nkx-2.2 and Nkx-2.9). These opposing gradients specify in detail the nature of the neurons which will develop in the various loci of the developing neural tube. At the same time lateral gradients of retinoic acid emanate from the lateral edges of the neural tube descending to very low concentrations along the lumen of the neural tube. Rostral-causal axial differentiation is controlled by opposing gradients of retinoic acid rostrally competing with FGF and Gli1 from the caudal end of the neural tube [92].
Hence in a very real way one could say that the structures of the neural tube are actually woven together by opposing and antagonistic but balanced morphogen gradients. Similar principles often operate in numerous other tissues at the level of the overall body pattern, at the organ level, for body rotation where it is not symmetrical, and at the cellular and subcellular levels.
In considering the impacts of cannabinoids on the forming embryo it is of interest to consider the effects cannabinoids might have on one of the main morphogen systems in the body which is sonic hedgehog. A brief consideration of their impacts on other fundamental morphogen systems follows.
Sonic Hedgehog
Sonic Hedgehog (shh) is one of the most important of all the body morphogens. Indeed one contemporary textbook includes 174 references to this key morphogen [92].
Shh has been shown to be critically involved in the development of the following structures [92]:
Gastrula / Early Embryo
Primitive node of the late gastrula
Notochord
shh gradient along ventral surface of embryo
Gradient antagonizes its opposing morphogens, particularly FGFs, from posterior embryo
Brain
Early Forebrain specifier and organizer
Controls ventral midbrain formation including the ventral tegmental area and Nucleus Accumbens
Cerebellum organizer – The large Purkinje cell secrete shh which stimulates granule cell proliferation [92]
Induces motor neuron development in the ventral neural tube [92]
Splits the single eye field into two halves, right and left [92]
Induces the outgrowth of the optic cup from the forebrain which becomes the optic nerve and then the optic vesicle and later neural retina
The bulging frontal lobe of the forebrain secretes shh to induce an ectodermal organizing centre in the overlying skin called the frontonasal ectodermal zone which controls the development of the cheeks and nose again by the secretion of shh
Induction of the ventral and nasal retinae of the eye
Acts as a repulsive signal guiding axonal growth of retinal ganglion cells
Controls formation and remodelling of branchial arch blood vessels [101]
Together with BMP and notch signalling shh is critically involved with induction of the first dedicated haemopoietic cells which arise in the fusing dorsal aortae
Arterial differentiation is induced in a molecular cascade which commences with shh signaling to VEGFA and notch from a general endothelial background of angioblasts [92, 102, 103]
Genitourinary
Contributes to bladder growth and sufficiency [92]
Contributes as a trophic factor to development and outgrowth of the genital tubercle under the influence of shh derived from the urethral endoderm [92]
Limbs
Zone of polarizing activity in limb formation [92]
Key organizer of the patterning of the digits [92]
Hair buds development
Therefore the recent demonstration therefore that cannabidiol and THC inhibit shh signalling necessarily carries major implications for cannabinoid-related teratogenesis [42]. These cannabinoids were noted to both depress shh and Gli1 mRNA and induce the formation of a CB1R-smoothened (“smoothened” is the effector molecule of the shh “patched” receptor) heteromer which reverses the polarity of downstream signalling of smoothened. These authors noted that the critical period for foetal development in this regard is the third to fourth week of gestation in the embryonal period of development when many women are unaware that they are pregnant.
Interference with shh-dependent processes at key stages of development will likely result in the following anomalies which have been described in various studies as being cannabis-related:
Gastrointestinal stenoses and atresias (USA- present study)
Anorectal agenesis
It has been reported by many investigators that cannabinoids reduce cell growth and reduce synthesis of the macromolecules of life such as DNA, RNA and proteins including histones [12, 23, 24, 26‐32, 119‐122].
The inhibition of cell growth and division would explain many features of cannabis teratogenesis including:
i)
Failure of the anterior and posterior neuropores to close, resulting in encephalocele, exencephaly and spina bifida respectively;
ii)
Cleft lip and palate due to failure of the facial and palatal processes to properly fuse
iii)
Several cardiovascular defects including:
a.
Atrial septal defect secundum, where the atrial septal folds fail to grow across the defect
b.
Ventricular septal defects where the various components of the ventricular wall fail to join across the defect
c.
Stenoses and atresias of the heart valves
d.
Defective development of the great vessels, which have a very complex developmental course
iv)
Body wall defects
v)
Limb defects, where failure or interruption of cell division at key period of limb bud outgrowth interrupts the normal sequence of events required for normal limb development affecting:
Small intestinal stenosis and atresia (USA- present study)
c.
Large intestinal stenosis and atresia (USA- present study)
d.
Biliary stenosis and atresia (USA- present study)
e.
Anorectal stenosis and atresias (USA- present study)
vii)
Arterial vascular catastrophes
a.
Limb development
b.
Body wall – omphalocele, gastroschisis, diaphragmatic hernia
As shown above shh is known to be a key morphogen directing the differentiation of the arterial tree and its inhibition can be expected to disrupt normal vasculogenic and arterial supply of key tissues. Cannabinoids are also vasoactive [123]. Both type 1 and 2 cannabinoid receptors (CB1Rs and CB2Rs) along with other receptor subtypes have been described on the vasculature [123]. Cannabinoids acting at CB1Rs are often proinflammatory and vasoconstrictive [123‐127]. Such vascular defects could be involved with the genesis of various congenital anomalies including:
i)
Body wall defects (gastroschisis and omphalocele) – cocaine and various vasoconstrictive antihistaminic drugs are known to be associated with gastroschisis [128‐133] and cannabinoids may act similarly at least in the foetal period of development
ii)
Gastrointestinal stenoses and atresias
iii)
Limb development as the developing limb anlage is highly vascular dependent any interruption of its blood supply will necessarily truncate development.
Hence it could be said that the full spectrum of cannabinoid-induced embryopathy follows to a close approximation a picture of shh mutation or deficit. The point has previously been made that embryonic shh deficiency causes a wide variety of congenital defects including effects on vertebra, anal atresia, cardiovascular anomalies, tracheoesophageal fistula, renal defects and limb defects (VACTERL syndrome) [134]. These defects also have similarities both to fetal alcohol syndrome [42] and Di George / Velocardiofacial (palatocardiofacial) syndrome which may also include kidney and intellectual problems [135].
Other genotoxic mechanisms
In addition to direct and indirect interactions with specific morphogen pathways cannabinoids have also been shown to interact deleteriously with chromosomes, DNA, the epigenome and mitochondrial-metabolic-epigenomic pathways. These are reviewed in a companion manuscript and have been considered elsewhere [18‐20, 24, 28, 31, 37, 38, 41, 91, 113, 136‐142].
Specific organ systems
Heart
In Hawaii five cardiovascular defects were related to elevated cannabis use, atrial and ventricular septal defects, pulmonary valve atresia and stenosis, tetralogy of Fallot and hypoplastic left heart syndrome [13]. In Colorado four cardiovascular defects rose across time with increasing community cannabinoid penetration, namely atrial septal defect, ventricular septal defect, patent ductus arteriosus and anomalies of the pulmonary artery [20]. In Canada total cardiovascular defects were related to increased cannabis use [18]. In Australia total cardiovascular defects, atrial and ventricular septal defects, transposition of the great arteries, tetralogy of Fallot and patent ductus arteriosus occurred with higher incidence in high cannabis using areas [19]. They also featured prominently in the present US overview.
It is important to appreciate that heart development occurs by including cells from many loci in the embryo including the primary and secondary heart fields, proepicardium, Juxtacardiac field [143], cardiac neural crest and neural crest [92].
Major morphogens acting are retinoic acid, FGFs and shh. Neuregulin is involved in the induction of both the heart valves and also the subendocardial electrical conducting system of the heart [92].
It therefore follows that heart and great vessels form as a result of a carefully orchestrated sequential complementation of progenitor cells from many areas, some quit remote from the cardiogenic field itself [92]. It is also apparent that numerous genes and transcription factors are involved in this process [92].
Given the wide diversity of cannabinoid actions in a wide variety of cell types it seems particularly unlikely that cannabinoids would not impact this delicate and intricate process at many points.
The numerous interactions of shh with both heart and great vessel formation were enumerated above.
Respiratory defects
Respiratory defects were noted to be elevated in the high cannabis using areas of Colorado and Canada [18, 20]. Shh is noted to be centrally involved in the budding and development of the respiratory tree [92].
Face
In the Hawaiian series incidence rates of cleft lip and palate together with anotia / microtia were elevated by prenatal cannabis exposure [13]. Microphthalmia was non-significantly elevated. In Canada facial clefts were non-significantly elevated [18]. In Australia facial and ear anomalies were non-significantly elevated [19].
As was noted above shh plays a large role in face development through the frontal facial organizer, at the tip of the frontonasal processes which form the sides of the cleft lip, at the tips of the palatal shelves, in the tongue, teeth, taste buds and filiform papillae [92].
Alcohol and steroidal alkaloids are known to disrupt shh signalling in the face [144].
Gastrointestinal tract
The Hawaiian series noted that several gastrointestinal anomalies were elevated following prenatal cannabis exposure including esophageal atresia, pyloric stenosis, and large bowel stenoses and atresias including anorectal atresia [13]. In Australia small intestinal stenosis was identified positively [19]. Gastrointestinal anomalies featured prominently in the present analysis including particularly small intestinal stenosis and atresia which was linked with cannabidiol use both causally and in a space-time context.
The prominent involvement of shh and major morphogens in the growth and development of all parts of the gastrointestinal tract was described above [92].
Urinary tract
Given the above notes on the location of shh in the genitourinary system it is of interest that obstructive genitourinary defects were identified both in Hawaii and in the present US survey series [13]. Hypospadias was identified positively in Australia [19].
Body wall anomalies
Gastroschisis and diaphragmatic hernia have previously been noted to be linked with prenatal cannabis exposure by CDC and NBDPN researchers [7] although gastroschisis was not positively identified in the present investigation [7]. In Colorado gastroschisis and diaphragmatic hernia were positively identified [20].
Limbs
Limb reductions were noted as significant correlates in the continuous bivariate analysis of THC and cannabis with minimal E-Values of 1.89 and 9.53. Leg reductions were noted as significant correlates of cannabidiol, THC and cannabis with minimal E-Values of 2.38, 1.32, and 2.57 (Tables 6, 7, 8). They were not seen in association with tobacco, alcohol or cocaine exposure. This finding is consistent with the arm reduction anomalies reported from Hawaii following prenatal cannabis exposure [13], the elevation of total congenital anomalies seen in Canada which also may have included limb reductions [18] and preclinical studies [11, 12, 104]. Cannabis of course is well known to interfere with both cellular division including macromolecular synthesis and blood vessel sprouting. Blood vessels are known to have high density cannabinoid receptors which are known to be frequently pro-inflammatory and vasoactive [123‐127]. Moreover limb outgrowth occurs in a tight time window during embryogenesis [145]. It is therefore possible that cannabinoid exposure during this critical window of development interferes with cellar division in the limb bud and vascular budding and outgrowth thereby compromising limb development.
It is of interest that arm reduction anomalies along with polydactyly and syndactyly were noted to have occurred with increased incidence rates following prenatal cannabis exposure in the Hawaiian series, and leg anomalies rates rose in the present US series [13]. Polydactyly and syndactyly and total musculoskeletal anomalies rose in Colorado with cannabis legalization [20]. It is difficult to comment on the major limb anomalies as it is a congenital anomaly for which ETOPFA may be practised at high rates. In the Australian series there was a non-significant trend to higher rates of major arm and leg anomalies in the high cannabis using areas [19]. Similarly outbreaks of major limb anomalies were noted in both France and Germany [45, 47, 48, 50] in recent years where cannabinoids have been allowed to enter the food chain, but not in nearby Switzerland where this is not permitted.
Major morphogens involved in early limb development are opposing gradients of the Fibroblast Growth Factors (FGF) and Wnt on the one hand and retinoic acid on the other. Limb length is controlled by Hox genes D-9 to D-13. Specification and formation of the fingers and toes is controlled by alternating interactions and gradients between sonic hedgehog, gremlin and FGF4 and by manipulating these gradients and gene dosages experimentally one is able to control various malformations in a predictable manner [145].
It is of interest therefore that there are at least three major pathways by which cannabinoids can interfere with limb bud development and outgrowth:
i)
Direct inhibition of cell division and cell growth
ii)
Direct and indirect blockades of shh gradients from the zone of polarizing activity in the inferior axillary region and along the posterior edge of the limb and in the digital rays
iii)
Vasculopathic mechanisms whereby interference with the ingrowing blood supply compromises limb development.
It is important to note that limb development is strictly sequential so that a block at critical developmental time periods will inevitably block subsequent steps. It is easy to appreciate in such a paradigm that significant cannabinoid intake in such critical windows of gestation may have potentially catastrophic implications for limb growth and development.
It is also noteworthy that cannabis shares many of the mechanisms of action of thalidomide [146‐152] an agent which is notorious for interfering with limb outgrowth and bony skeletal development, albeit at higher potency [53, 146, 151, 153‐156].
Chromosomal defects
Downs syndrome was identified positively in Hawaii, Colorado, Australia and Canada as well as in the present analysis of both categorical and continuous ETOPFA-corrected data [13, 18‐20]. Chromosomal defects were found to be elevated in Canada and Australia [18, 19] as well as in the present US survey.
Several mechanisms of indirect chromosomal clastogenicity and DNA breakage have been described [24, 26, 28, 33, 138].
Interactions of cannabinoids with other major morphogen systems
Interaction between FGF (Fibroblast Growth Factor) and endocannabinoid systems have also been described [157, 158] including transactivation of the FGF1R by CB1R [159].
Interactions between cannabinoids and bone morphogenetic proteins have also been described [160‐162].
Interactions between cannabinoids and retinoic acid signalling have been described [163‐165].
Interactions between cannabinoids and notch signalling have also been reported [166‐172].
Interactions between cannabinoids and Wnt signalling have also been reported [173‐179].
Interactions between cannabinoids and hippo have been reported [140].
Cannabinoids also interact with the neurexin-neuroligin system [180‐182] which is key to the architecture and development of neural synapses.
Cannabinoids also interact with the slit-robo system [168, 169, 183] which control arterial pathfinding and also axonal growth cone steering mechanisms [92, 171, 184, 185]. Slit-robo signalling is also one of the major morphogens directing and controlling the exuberant outgrowth of the massive human neocortex [183, 186].
Commonality
Given this plethora of actions of actions between cannabinoids and the major morphogens of human and mammalian development one might well wonder why such anomalies are not becoming much more common. There are several parts to this answer. One factor is that the birth defect data from states where cannabis is legal such as Washington state and Oregon are almost non-existent. Data from Colorado shows a dramatic rise in congenital anomalies across the period of legalization as has been mentioned elsewhere [20]. Also since cannabinoids are involved in virtually every aspect of reproduction including gamete formation and meiotic divisions, the function of supporting granulosa and Sertoli cells in ovary and testis, cells placentation, implantation, sperm fertility and hyperactivation, ovarian signals to the sperm and cell division at the early zygote, morula and embryonic stages a high rate of foetal loss is expected from severe anomalies which does not necessarily appear on lists of birth defects, but is chronicled in case series such as that described above from Washington D.C [14, 15]. Moreover the actual state level ETOPFA rate likely varies from place to place and this is a major determinant of the rates of many serious CAs.
Causal assignment
Two of the commonest criticisms made of observational studies are that the exposure of interest is not distributed randomly across all experimental subjects, and that there may be some uncontrolled confounding operating from some unmeasured variables which account for the observed effect and for which the observed variables are acting merely as surrogates or substitute markers.
The first criticism is answered in the present study by the use of inverse probability weighting of the exposed groups. It is well established that the use of this procedure across observations transforms a merely observational dataset into a pseudo-randomized one from which causal conclusions can properly be drawn by comparing exposure groups. This technique is particularly suitable for those comparisons which would not generally be ethical to apply in randomized controlled studies, such as antenatal exposures.
The second criticism is addressed herein by the use of E-Values. E-Values, or expected values, calculate the degree of correlation required of some unknown confounding variable with both the exposure and the outcome to explain away the observed effect. The literature mentions that values above 1.25 are generally considered to indicate causal effects [67]. The E-value for the lung cancer – tobacco relationship is 9 which is considered high [67, 68, 86]. It is clear from the present study that many of the E-Values quoted are much higher than this gold standard metric.
Moreover it is entirely proper to use E-Values freely in relation both to specific models (which have model standard deviations) and to final predictive models as has been done in the present report [69].
One also notes that for two congenital anomalies we have conducted multiple regression by several techniques which have very similar conclusions. Moreover for these defects we have shown in their intrinsic natural space-time context that these relationships are conserved and indeed amplified.
Furthermore our results are also consistent with a long, robust and highly consistent tradition of laboratory and preclinical evidence as noted above.
As judged by the criteria of causation proposed by Hill [187] the present results fulfil the criteria of strength of association, consistency across studies in the manner described, specificity amongst substance exposures, temporality of sequence, coherence with known data, biological plausibility as described in the above mechanistic discussion, biological dose-response curve, analogy with similar situations in other places and experimental confirmation.
Generalizability
The present study has several advantages. Its study subject is a sizeable base population comprising a national census birth population in excess of 18 million births, from a notional year-on-year aggregated annualized total population of over 2 billion persons. Drug use data is taken from a well verified nationally representative survey which has been faithfully repeated annually for several decades now with very little important change which greatly facilitates comparison between periods. Advanced statistical methods are employed on both the aggregate dataset of all defects and two congenital anomalies in particular. The techniques both of formal space-time analysis and of causal inference have been utilized. For these reasons internal to the study we are confident that the present work is widely applicable across the globe. Results reported herein strongly indicate that in those third world nations where cannabis is known to be much more widely used the results are expected to be much more severe than those reported for this nation where historically cannabis use was relatively restricted until recent years.
The demonstration that many of these effects give the appearance on bivariate analysis of being truly causal also necessarily implies that the results are truly biological and widely generalizable.
The present work is also entirely consistent with a large and growing external body of evidence from particular states within USA, namely Colorado and Hawaii [13, 20] and also from Australia and Canada which attest to the concordance with the findings reported herein [17‐19].
Another important body of work which supports the present results is the preclinical literature which the present results closely replicate. As was noted above in fact virtually all of the mentioned congenital anomalies have been positively identified in the present study.
Hence for this variety of both internal and external reasons we feel that the findings in the present study are widely generalizable with the primary caveat that in nations where cannabis is more widely available we believe that the findings would be of even greater concern in those cases where reliable datasets exist for its accurate assessment.
Strengths and limitations
In considering the strengths and limitations of the present study it is important to clarify exactly what this study is and what it is not. The present study sets out to present a broad overview of the apparent relationship of the US teratological experience to substance exposure in the population during the notional period 2005–2013 when both major datasets are available. It goes on to explore two particular anomalies in detail from both a causal inference and geotemporospatial perspective as examples of the manner in which such analyses can be carried forward using more versatile analytical techniques on extent data series. For these reasons we feel it is premature to propose a list of cannabinoid related congenital anomalies and limit ourselves merely to noting that the issue is of considerable concern and well warrants further advanced statistical, epidemiological and basic science investigation. Thus our study is not the last word on US substance-related teratology, but in that it applies a series of advanced sequential linear and predictive modelling and sophisticated analytical space-time and causal inferential techniques our study is more like the first word opening an important discussion which has not been well addressed in recent years.
This study has several strengths including using a nationwide census database for congenital anomalies, using a large well validated nationally representative sample of the non-institutionalized US population, using the major techniques of quantitative causal inference namely inverse probability weighting and E-values, and geospatial regression across space and time simultaneously to assess these roles, and continues by studying the predicted values from space-time models to examine the way in which increasing cannabidiol exposure can be related spatiotemporally to increasing dose-effect relationships. The analytical techniques featuring linear models in tidy format conducted serially on 62 congenital anomalies in purrr allow direct comparison of models within the same statistical run. The use of multi-facetted plots allow the direct visual comparison of the effect on multiple congenital anomalies to be visually inspected at a glance, and similarly between plot comparisons allows the effects of various environmental teratogens to be directly compared. Graphical presentations of E-Values also allow the quantitative and causal significance of findings between substances to be directly compared.
The limitations of this study relate to the limitations of its design. In common with most epidemiological studies individual patient level exposure data was not available to it. Obvious ways in which the present work might be extended such as by increasing the geospatial resolution of the work and by increasing the numbers of congenital anomalies for which detailed regression results are presented are outside the ambit of the present study, and represent a fertile area for future workers. NBDPN may be able to further extend the dataset by completing missing data fields. Moreover perhaps the most definitive technique by which to study these data would include the use of inverse probability weighting in spatiotemporal models. It may become possible with time to employ a weighting term which is actually a product of two lists of weights, one being a sparse geospatial matrix and one being IPW, similar to a current implementation in the R “survey” package. Since such techniques have not been developed at the time of writing it has not been possible to deploy them on these topics. In their stead multiple IPW causal models have been used to address pseudo-randomization and complete these gaps. This also represents an important area for future statistical methodological development. As the USA moves increasingly towards population wide exposure to cannabinoids the importance of quantifiable continuous measures of exposure to various cannabinoids, for example by epigenomic and or glycomic criteria proportionately increases as has previously been noted [91]. State level anomaly-specific ETOPFA rates were not available to this work and ETOPFA rates had to be estimated from the published literature. Their addition to the present dataset would improve the quality and accuracy of the various estimates used.
Conclusion
In summary we note that bivariate analysis of ETOPFA-corrected CA incidence against state-based substance exposure rates indicates that cannabis and estimated THC are more important environmental teratogens than tobacco, and cannabidiol is likely more important in these metrics than either binge or regularly consumed alcohol. Elevated E-values for many defects indicates that a causal relationship is likely. Small intestinal stenosis and atresia and obstructive genitourinary defects were studied in detail by inverse probability weighted mixed effects, robust and panel regression and by space-time regression and by predictive modelling in spatiotemporal models where these findings were all strongly confirmed and again were shown to be epidemiologically causal in nature. Results are consistent and concordant with several decades of preclinical and laboratory work implicating cellular pathways at chromosomal, genomic, epigenomic and mitochondriopathic levels and with interruption of major embryonal-foetal morphogen gradients particularly sonic hedgehog and with patterns of fetotoxicity and embryotoxicity observed in preclinical models and fulfil the Hill criteria of causality. The present work is part of an on-going project to further investigate these themes in greater depth and finer detail. Further work by interested groups in related areas is strongly indicated.
The present situation where cannabidiol is widely available across USA and popularly perceived as harmless is unusually uninformed and particularly ill-advised. Our analyses implicate THC, cannabigerol and cannabidiol, and analyses could be presented similarly implicating also cannabinol and cannabichromene. From a public health point of view the present de facto policy of official negligence is at once unjustified and unjustifiable.
Data indicate that cannabinoid teratogenicity including cannabidiol teratogenicity and presumptive genotoxicity are clinically significant and carry far-reaching and multi-generational public health impacts in foetal-maternal and reproductive medicine. We feel that it is important that the transgenerational impacts of general register-wide overviews and surveys such as this be given wide canvas and discussion in the community and assume substantial prominence in the public debate on the proper and proven role of cannabinoids in the global community. Moreover the assignment of proper weight to inheritable considerations is essential to optimally formulate policy which balances the risk-benefit equation relating to the general widespread distribution of known genotoxins such as numerous cannabinoids – including cannabidiol - as indeed genotoxicity and fetotoxicity has always been a foundational cornerstone and was always the conceptual origin of modern drug regulation by national Government agencies.
Acknowledgements
We wish to acknowledge with grateful thanks the work of Professor Mark Stevenson in upgrading epiR to version 2.0.11 to enable the analysis of the large integers encountered on this project. We also wish to acknowledge the invaluable support of Professor Giovanni Millo with numerous occasions of technical advice and assistance in relation to the use of the splm software package and geospatial model specification and the spreml function in particular.
Declarations
Ethics approval and consent to participate
The Human Research Ethics Committee of the University of Western Australia provided ethical approval for the study to be undertaken 7th January 2020 (No. RA/4/20/4724). Consent to participate was not required as the data utilized was derived from publicly available anonymous datasets and no individual identifiable data was utilized.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
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Geotemporospatial and causal inference epidemiological analysis of US survey and overview of cannabis, cannabidiol and cannabinoid genotoxicity in relation to congenital anomalies 2001–2015
In einer Leseranfrage in der Zeitschrift Journal of the American Academy of Dermatology möchte ein anonymer Dermatologe bzw. eine anonyme Dermatologin wissen, ob er oder sie einen Patienten behandeln muss, der eine rassistische Tätowierung trägt.
Extreme Arbeitsverdichtung und kaum Supervision: Dr. Andrea Martini, Sprecherin des Bündnisses Junge Ärztinnen und Ärzte (BJÄ) über den Frust des ärztlichen Nachwuchses und die Vorteile des Rucksack-Modells.
Akute Brustschmerzen sind ein Alarmsymptom par exellence, schließlich sind manche Auslöser lebensbedrohlich. Auch Kinder klagen oft über Schmerzen in der Brust. Ein Studienteam ist den Ursachen nachgegangen.
Darauf haben viele Praxen gewartet: Das Zi hat eine Liste von Praxisverwaltungssystemen veröffentlicht, die von Nutzern positiv bewertet werden. Eine gute Grundlage für wechselwillige Ärztinnen und Psychotherapeuten.
Update Pädiatrie
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