Academy of Breastfeeding Medicine Clinical Protocol #21: Breastfeeding in the Setting of Substance Use and Substance Use Disorder (Revised 2023)

Background: The Academy of Breastfeeding Medicine (ABM) revised the 2015 version of the substance use disorder (SUD) clinical protocol to review the evidence and provide updated literature-based recommendations related to breastfeeding in the setting of substance use and SUD treatments. Key Information: Decisions around breastfeeding are an important aspect of care during the peripartum period, and there are specific benefits and risks for substance-exposed mother-infant dyads. Recommendations: This protocol provides breastfeeding recommendations in the setting of nonprescribed opioid, stimulant, sedative-hypnotic, alcohol, nicotine, and cannabis use, and SUD treatments. Additionally, we offer guidance on the utility of toxicology testing in breastfeeding recommendations. Individual programs and institutions should establish consistent breastfeeding approaches that mitigate bias, facilitate consistency, and empower mothers with SUD. For specific breastfeeding recommendations, given the complexity of breastfeeding in mothers with SUD, individualized care plans should be created in partnership with the patient and multidisciplinary team with appropriate clinical support and follow-up. In general, breastfeeding is recommended among mothers who stop nonprescribed substance use by the time of delivery, and they should continue to receive ongoing postpartum care, such as lactation support and SUD treatment. Overall, enhancing breastfeeding education regarding substance use in pregnancy and lactation is essential to allow for patient-centered guidance.

Generic Workflow to Predict Medicine Concentrations in Human Milk Using Physiologically-Based Pharmacokinetic (PBPK) Modelling-A Contribution from the ConcePTION Project

Women commonly take medication during lactation. Currently, there is little information about the exposure-related safety of maternal medicines for breastfed infants. The aim was to explore the performance of a generic physiologically-based pharmacokinetic (PBPK) model to predict concentrations in human milk for ten physiochemically diverse medicines. First, PBPK models were developed for "non-lactating" adult individuals in PK-Sim/MoBi v9.1 (Open Systems Pharmacology). The PBPK models predicted the area-under-the-curve (AUC) and maximum concentrations (C_max) in plasma within a two-fold error. Next, the PBPK models were extended to include lactation physiology. Plasma and human milk concentrations were simulated for a three-months postpartum population, and the corresponding AUC-based milk-to-plasma (M/P) ratios and relative infant doses were calculated. The lactation PBPK models resulted in reasonable predictions for eight medicines, while an overprediction of human milk concentrations and M/P ratios (>2-fold) was observed for two medicines. From a safety perspective, none of the models resulted in underpredictions of observed human milk concentrations. The present effort resulted in a generic workflow to predict medicine concentrations in human milk. This generic PBPK model represents an important step towards an evidence-based safety assessment of maternal medication during lactation, applicable in an early drug development stage.

Technical Report: Breastfeeding and the Use of Human Milk

Breastfeeding and human milk are the normative standards for infant feeding and nutrition. The short- and long-term medical and neurodevelopmental advantages of breastfeeding make breastfeeding or the provision of human milk a public health imperative. The American Academy of Pediatrics (AAP) recommends exclusive breastfeeding for approximately 6 months after birth. Furthermore, the AAP supports continued breastfeeding, along with appropriate complementary foods introduced at about 6 months, as long as mutually desired by mother and child for 2 years or beyond. These recommendations are consistent with those of the World Health Organization (WHO). Medical contraindications to breastfeeding are rare. The AAP recommends that birth hospitals or centers implement maternity care practices shown to improve breastfeeding initiation, duration, and exclusivity. The Centers for Disease Control and Prevention and The Joint Commission monitor breastfeeding practices in United States hospitals. Pediatricians play a critical role in hospitals, their practices, and communities as advocates of breastfeeding and, thus, need to be trained about the benefits of breastfeeding for mothers and children and in managing breastfeeding. Efforts to improve breastfeeding rates must acknowledge existing disparities and the impact of racism in promoting equity in breastfeeding education, support, and services.

Caffeine, Paraxanthine, Theophylline, and Theobromine Content in Human Milk

This study aimed to assess the content of caffeine and its metabolites—paraxanthine, theophylline, and theobromine—in breast milk according to selected factors. Samples of human milk were collected from 100 women living in the east–northeast region of Poland. Information on the consumption of beverages and foods containing caffeine was collected using a 3 day food record. The determination of caffeine and its metabolite content was performed using liquid chromatography–mass spectrometry (LC–MS/MS). This study research showed that more caffeine was found in the milk of women living in cities, with secondary education, aged 34–43, and also in milk from the 3rd and 4th lactation periods (p ≤ 0.05). Factors such as place of residence, level of education, age, and stage of lactation influenced the nutritional choices of breastfeeding women, which had an impact on the level of caffeine and its metabolites in breast milk. A positive correlation was found between the consumption of caffeine with food and drinks and its level in human milk.

Vertical Transfer of Metabolites Detectable from Newborn's Dried Blood Spot Samples Using UPLC-MS: A Chemometric Study

The pregnancy period and first days of a newborn's life is an important time window to ensure a healthy development of the baby. This is also the time when the mother and her baby are exposed to the same environmental conditions and intake of nutrients, which can be determined by assessing the blood metabolome. For this purpose, dried blood spots (DBS) of newborns are a valuable sampling technique to characterize what happens during this important mother-child time window. We used metabolomics profiles from DBS of newborns (age 2-3 days) and maternal plasma samples at gestation week 24 and postpartum week 1 from n=664 mother-child pairs of the Copenhagen Prospective Studies on Asthma in Childhood 2010 (COPSAC2010) cohort, to study the vertical mother-child transfer of metabolites. Further, we investigated how persistent the metabolites are from the newborn and up to 6 months, 18 months, and 6 years of age. Two hundred seventy two metabolites from UPLC-MS (Ultra Performance Liquid Chromatography-Mass Spectrometry) analysis of DBS and maternal plasma were analyzed using correlation analysis. A total of 11 metabolites exhibited evidence of transfer (R>0.3), including tryptophan betaine, ergothioneine, cotinine, theobromine, paraxanthine, and N6-methyllysine. Of these, 7 were also found to show persistence in their levels in the child from birth to age 6 years. In conclusion, this study documents vertical transfer of environmental and food-derived metabolites from mother to child and tracking of those metabolites through childhood, which may be of importance for the child's later health and disease.

Tobacco cigarette and cannabis use among new mothers

BACKGROUND AND AIMS

In the United States, the prevalence of cannabis use during pregnancy has increased whereas tobacco smoking has decreased. This study aimed to estimate the prevalence of tobacco cigarette smoking and cannabis use among new mothers, stratified by breastfeeding status. Additionally, trend analysis was used to examine changes in tobacco and cannabis use over time.

DESIGN

Cross-sectional study based on the National Health and Nutrition Examination Survey (NHANES, 2001-18).

SETTING

United States.

PARTICIPANTS

Population-based sample of new mothers (within 2 years of childbirth) aged 20-44 years (n = 1332).

MEASUREMENTS

For each NHANES data cycle, the prevalence of tobacco smoking measured by self-report or serum cotinine was estimated. Additionally, we estimated the prevalence of cannabis use measured by self-report. Using Joinpoint Regression, we tested for significant changes in trends and produced the average 'data-cycle' percentage change (APC).

FINDINGS

From 2001 to 2018, more than one in five new mothers were tobacco cigarette smokers. New mothers who were breastfeeding were less likely to smoke cigarettes [7.4%, 95% confidence interval (CI) = 4.9%, 10.9% compared with mothers who were not breastfeeding (25.7%, 95% CI = 22.3%, 29.3%]. Results from Joinpoint regression indicated no robust temporal trends for self-reported tobacco smoking (APC = -1.3, 95% CI = -8.6, 6.7; P = 0.7) or for cotinine levels ≥ 4.47 ng/ml (APC = 0.3, 95% CI = -5.0, 5.9; P = 0.9), whereas cannabis use had increased among new mothers (APC = 23.7, 95% CI = 4.8, 46.0; P = 0.02).

CONCLUSIONS

Consistent with the increase seen among other subgroups, cannabis use has approximately doubled among US new mothers since 2005. There is no significant evidence of a change in tobacco smoking among US new mothers since 2001.

Prediction of drug concentrations in milk during breastfeeding, integrating predictive algorithms within a physiologically-based pharmacokinetic model

There is a risk of exposure to drugs in neonates during the lactation period due to maternal drug intake. The ability to predict drugs of potential hazards to the neonates would be useful in a clinical setting. This work aimed to evaluate the possibility of integrating milk-to-plasma (M/P) ratio predictive algorithms within the physiologically-based pharmacokinetic (PBPK) approach and to predict milk exposure for compounds with different physicochemical properties. Drug and physiological milk properties were integrated to develop a lactation PBPK model that takes into account the drug ionization, partitioning between the maternal plasma and milk matrices, and drug partitioning between the milk constituents. Infant dose calculations that take into account maternal and milk physiological variability were incorporated in the model. Predicted M/P ratio for acetaminophen, alprazolam, caffeine, and digoxin were 0.83 ± 0.01, 0.45 ± 0.05, 0.70 ± 0.04, and 0.76 ± 0.02, respectively. These ratios were within 1.26-fold of the observed ratios. Assuming a daily milk intake of 150 ml, the predicted relative infant dose (%) for these compounds were 4.0, 6.7, 9.9, and 86, respectively, which correspond to a daily ingestion of 2.0 ± 0.5 mg, 3.7 ± 1.2 µg, 2.1 ± 1.0 mg, and 32 ± 4.0 µg by an infant of 5 kg bodyweight. Integration of the lactation model within the PBPK approach will facilitate and extend the application of PBPK models during drug development in high-throughput screening and in different clinical settings. The model can also be used in designing lactation trials and in the risk assessment of both environmental chemicals and maternally administered drugs.

Determinants of the introduction of early complementary feeding before and after the third month of life: a multinomial analysis

The introduction of early complementary feeding (ECF) is determined by different factors depending on when it occurs. The objective of this study was to analyze factors associated with the introduction of ECF in two different moments of the infant's life: from zero to three and from four to five months of age. A cohort with 3,306 dyads studied in the BRISA survey in São Luis/MA in 2010 was used. Questionnaires were applied at birth and at follow-up when the infants were 15 to 36 months of age of women with more than 20 weeks of gestational age, residing in this municipality. A multivariate model of multinomial logistic regression was used to verify associations between independent variables and ECF at 0 to 3 months and at 4 to 5 months of age. A hierarchical analysis model was used to select variables for confounding adjustment. Variables with a P-value <0.05 were considered significant. For ECF introduced between 0-3 months, the variables "use of pacifier", "maternal paid activity", "smoking", and "postpartum pregnancy" were identified as risk factors. The variables "use of pacifier" and "maternal paid activity" remained associated as a risk for ECF introduced from 4-5 months. The variable 'mother without partner' (RR=1.26 and P=0.04) represented a risk factor for ECF only for the 4-5 months period. Although each period presented specific risk factors, the use of pacifier and maternal professional activity were associated in the two periods studied, indicating their importance for the introduction of ECF.

Monitoring of Chemical Risk Factors for Sudden Infant Death Syndrome (SIDS) by Hydroxyapatite-Graphene-MWCNT Composite-Based Sensors

Sensing properties of chemical sensors based on ternary hydroxyapatite-graphene-multiwalled carbon nanotube (HA-GN-MWCNT) nanocomposite in the detection of chemical substances representing risk factors for sudden infant death syndrome (SIDS), have been evaluated. Characterization data of the synthesized composite have shown that the graphene-MWCNT network serves as a matrix to uniformly disperse the hydroxyapatite nanoparticles and provide suitable electrical properties required for developing novel electrochemical and conductometric sensors. A HA-GN-MWCNT composite-modified glassy carbon electrode (HA-GN-MWCNT/GCE) has been fabricated and tested for the simultaneous monitoring of nicotine and caffeine by cyclic voltammetry (CV) and square wave voltammetry (SWV), whereas a HA-GN-MWCNT conductive gas sensor has been tested for the detection of CO2 in ambient air. Reported results suggest that the synergic combination of the chemical properties of HA and electrical/electrochemical characteristics of the mixed graphene-MWCNT network play a prominent role in enhancing the electrochemical and gas sensing behavior of the ternary HA-GN-MWCNT hybrid nanostructure. The high performances of the developed sensors make them suitable for monitoring unhealthy actions (e. g. smoking, drinking coffee) in breastfeeding women and environmental factors (bad air quality), which are associated with an enhanced risk for SIDS.

Maternal E-Cigarette Exposure Results in Cognitive and Epigenetic Alterations in Offspring in a Mouse Model

Electronic cigarette (e-cigarette) use is on the rise worldwide and is particularly attractive to young people and as a smoking substitute by pregnant woman. There is a perception in pregnant women and women of child-bearing age that the use of e-cigarettes (vaping) is safer than smoking tobacco cigarettes during pregnancy. However, there is little evidence to support this perception. Here, we examined the offspring from mouse dams that had been exposed during and after pregnancy to ambient air (sham) ( n = 8), e-cigarette aerosols with nicotine ( n = 8), or e-cigarette aerosols without nicotine ( n = 8). Offspring underwent cognitive testing at 12 weeks of age and epigenetic testing of brain tissues at 1 day, 20 days, and 13 weeks after birth. The findings showed deficits in short-term memory, reduced anxiety, and hyperactivity in offspring following maternal e-cigarette exposure using the novel object recognition and elevated plus maze tests. In addition, global DNA methylation was increased in the brains of offspring soon after birth. Using a quantitative-PCR array specific to chromatin modification enzymes on genomic DNA and histones,13 key genes were identified to be significantly altered in the offspring brains from the e-cigarette groups compared to the nonexposed groups. The changes to genes Aurka, Aurkb, Aurkc, Kdm5c, Kdm6b, Dnmt3a, Dnmt3b, and Atf2, all associated with modulating neurological activity, were validated using RT-qPCR. In conclusion, in a mouse model, maternal exposure to e-cigarette aerosols resulted in both cognitive and epigenetic changes in offspring. This suggests that the use of e-cigarettes during pregnancy may have hitherto undetected neurological consequences on newborns.