Perinatal Impacts of Cannabis and Nicotine: An Analysis of the Cannabis Use During Development and Early Life Study
Trammel, C. J.; Agrawal, A.; Bogdan, R.; Lawlor, M.; Raghuraman, N.; Kelly, J. C.; Smyser, C. D.; Rogers, C.; Carter, E. B.
Show abstract
OBJECTIVEEvaluate associations between prenatal cannabis use (PCU) and perinatal outcomes. METHODSWe performed an interval analysis of a prospective cohort study of pregnant individuals with pre-pregnancy cannabis use and negative self-report of nicotine use, comparing those who continued cannabis through pregnancy with those who stopped. Patients underwent interviews and urine drug screening for cannabis and cotinine, a nicotine metabolite, in each trimester. The primary outcome was small for gestational age (SGA) at delivery. Secondary outcomes included antenatal and postpartum complications, mode of delivery, and neonatal outcomes. Secondary analyses included stratification by intensity of cannabis use and urinary cotinine positivity. RESULTSBirthing persons with PCU differed in age (25.5 vs 27.8 years, p=0.001), body mass index (BMI; 27.4 vs 30.9, p=0.001), area deprivation index percentiles (92% PCU vs 88%, p=0.013), cotinine positivity (42.8% vs 10.8%, p<0.001), Hispanic ethnicity (2% vs 7.2%, p=0.009), and education attainment beyond high school (29.4% vs 50%, p<0.001) compared to controls. Birthing person outcomes did not differ. Risks of SGA and other neonatal outcomes did not differ when adjusted for confounders on initial analysis, or with stratification by intensity of cannabis use. Despite negative self-report for nicotine, 42.8% of PCU patients tested positive for cotinine (PCU+c). PCU+c was associated with increased risk of SGA and birthweight less than the 5th percentile, compared to PCU cases without nicotine exposure (17.4% vs 8.3%, aRR 2.7 [1.21-5.38], 35.8% vs 18.6%, aRR 2.4 [1.51-3.48]), and controls (35.8% vs 12.9%, aRR 2.75 [1.64-4.13]). Cotinine-negative PCU patients and controls did not differ. CONCLUSIONPCU was not independently associated with adverse birthing person outcomes. Many patients demonstrated nicotine exposure, either via inadvertent exposure or undisclosed use. While neonates exposed to cannabis alone did not differ from unexposed neonates, those exposed to both cannabis and nicotine were at increased risk of SGA.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Tobacco, nicotine, and cannabis use and exposure in an Australian Indigenous population during pregnancy: A protocol to measure parental and foetal exposure and outcomes 94%
- Characterization of Neonatal Abstinence Syndrome in Arizona from 2010-2017 93%
- Urinary prostaglandin metabolites as biomarkers for human labour: Insights into future predictors 92%
Similar papers in this journal
- Rare but elevated incidence of hematological malignancy after clozapine use in schizophrenia: a population cohort study 91%
- Adverse childhood experiences: associations with educational attainment and adolescent health, and the role of family and socioeconomic factors. Analysis of a prospective cohort study. 90%
- Association of genetic liability to smoking initiation with e-cigarette use in young adults. 90%
Similar papers in this journal
- Neurodevelopmental outcomes at one year in offspring of mothers who test positive for SARS-CoV-2 during pregnancy 93%
- Child Developmental Patterns across Subtypes of Hypertensive Disorders of Pregnancy: TMM BirThree Cohort Study 92%
- Regional Variation in Antenatal Late Preterm Steroid Use following the ALPS Trial 92%
Similar papers in this journal
Similar papers in this journal
- Reduction in Spontaneous and Iatrogenic Preterm Births in Twin Pregnancies During COVID-19 Lockdown in Melbourne, Australia: A Multicenter Cohort Study 93%
- Smoking during pregnancy and its effect on placental weight: A Mendelian randomization study 92%
- Social inequalities in pregnancy metabolic profile: findings from the multi-ethnic Born in Bradford cohort study 90%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.