Objective This study aimed to describe the overall quantity and type of supplements and medications used during pregnancy in a low-risk cohort and to examine any racial/ethnic differences in intake. Study Design We used data from 2,164 racially/ethnically diverse, nonobese, and low-risk pregnant women participating without pre-pregnancy chronic conditions in a prospective cohort study at 12 sites across the United States. Medication data were self-reported as free text in enrollment, follow-up visit questionnaires, and abstracted from medical records at delivery. Supplements and medications data were mapped to their active ingredients and categorized into corresponding classes using the Slone Drug Dictionary. The total number and classes of supplements and medications consumed during pregnancy were calculated. Modified Poisson regression models were used to estimate the racial/ethnic differences in supplements and medications intake. All models were adjusted for maternal sociodemographic factors and study site. Results 98% of women took at least one supplement during pregnancy, with prenatal vitamins/multivitamins being most common. While only 31% reported taking no medications during pregnancy, 23% took one, 18% took two, and 28% took three or more. The percentage of women taking at least one medication during pregnancy was highest among non-Hispanic white women and lowest among Asians (84 vs. 55%, p < 0.001). All racial/ethnic groups reported taking the same top four medication classes including central nervous system agents, gastrointestinal drugs, anti-infective agents, and antihistamines. Compared with non-Hispanic white women, Hispanic (adjusted relative risk [aRR]: 0.84, 95% confidence interval [CI]: 0.71–0.98), and Asian women (aRR: 0.83, 95% CI: 0.70–0.98) were less likely to take central nervous system agents, as well as gastrointestinal drugs (Hispanics aRR: 0.79, 95% CI: 0.66–0.94; Asians aRR = 0.75, 95% CI: 0.63–0.90), and antihistamines (Hispanics aRR: 0.65, 95% CI: 0.47–0.92). Conclusion Supplement intake was nearly universal. Medication use was also common among this low-risk pregnancy cohort and differed by race/ethnicity. ClinicalTrials.gov Identifier NCT00912132. Key Points
A UK programme, led by the National Institute for Health Research (NIHR) ( https://www.nihr.ac.uk ) and coordinated by Applied Research Collaborations (ARC), ( https://www.nihr.ac.uk/explore-nihr/support/collaborating-in-applied-health-research.htm ) aimed to identify and select evidence-based, implementation-ready service innovations for evaluation. The programme focused on seven areas of health provision. We report on a prioritisation process designed to identify and assess innovations in one of these areas: child and maternal health (CH&M).We developed a three-stage, online, stakeholder driven process to 1) identify, 2) assess and prioritise and 3) select evidence-based interventions or service models, using crowdsourcing to identify projects and the APEASE criteria to assess and select projects. A brief evidence review was conducted for all initial suggestions to identify those with the largest evidence-base to take forward for ranking by stakeholders. Stakeholder workshops considered and ranked these suggestions using the APEASE criteria. We then conducted in-depth evidence reviews for the highest ranked suggestions. The Project Management Group and Advisory Board used these reviews and the APEASE criteria to select the final projects.We received 32 initial suggestions from a range of clinicians, practitioners and researchers. Fourteen of the most evidence-based suggestions were considered and ranked at four themed stakeholder workshops. Nine suggestions were ranked for further in-depth evidence review and a final four projects were selected for implementation evaluation using the APEASE criteria. These were: 1. Maternal Mental Health Services Multidisciplinary Teams 2. Early years tooth brushing programme 3. Trauma-focused CBT for young people in care and 4. Independent Domestic Violence Advisors in maternity settings. Feedback from participants suggested that having public representatives participating in all stakeholder meetings, rather than being consulted separately, focused discussions clearly on patient benefit rather than research aims.The stakeholder-driven process achieved its aim of identifying, prioritising and assessing and selecting, evidence-based projects for wider implementation and evaluation. The concurrent process could be adapted by other researchers or policy makers.
Higher caffeine consumption during pregnancy has been associated with lower birth weight. However, associations of caffeine consumption, based on both plasma concentrations of caffeine and its metabolites, and self-reported caffeinated beverage intake, with multiple measures of neonatal anthropometry, have yet to be examined.
Objective
To evaluate the association between maternal caffeine intake and neonatal anthropometry, testing effect modification by fast or slow caffeine metabolism genotype.
Design, Setting, and Participants
A longitudinal cohort study, the National Institute of Child Health and Human Development Fetal Growth Studies–Singletons, enrolled 2055 nonsmoking women at low risk for fetal growth abnormalities with complete information on caffeine consumption from 12 US clinical sites between 2009 and 2013. Secondary analysis was completed in 2020.
Exposures
Caffeine was evaluated by both plasma concentrations of caffeine and paraxanthine and self-reported caffeinated beverage consumption measured/reported at 10-13 weeks gestation. Caffeine metabolism defined as fast or slow using genotype information from the single nucleotide variant rs762551 (CYP1A2*1F).
Main Outcomes and Measures
Neonatal anthropometric measures, including birth weight, length, and head, abdominal, arm, and thigh circumferences, skin fold and fat mass measures. The β coefficients represent the change in neonatal anthropometric measure per SD change in exposure.
Results
A total of 2055 participants had a mean (SD) age of 28.3 (5.5) years, mean (SD) body mass index of 23.6 (3.0), and 580 (28.2%) were Hispanic, 562 (27.4%) were White, 518 (25.2%) were Black, and 395 (19.2%) were Asian/Pacific Islander. Delivery occurred at a mean (SD) of 39.2 (1.7) gestational weeks. Compared with the first quartile of plasma caffeine level (≤28 ng/mL), neonates of women in the fourth quartile (>659 ng/mL) had lower birth weight (β = −84.3 g; 95% CI, −145.9 to −22.6 g;P = .04 for trend), length (β = −0.44 cm; 95% CI, −0.78 to −0.12 cm;P = .04 for trend), and head (β = −0.28 cm; 95% CI, −0.47 to −0.09 cm;P < .001 for trend), arm (β = −0.25 cm; 95% CI, −0.41 to −0.09 cm:P = .02 for trend), and thigh (β = −0.29 cm; 95% CI, −0.58 to −0.04 cm;P = .07 for trend) circumference. Similar reductions were observed for paraxanthine quartiles, and for continuous measures of caffeine and paraxanthine concentrations. Compared with women who reported drinking no caffeinated beverages, women who consumed approximately 50 mg per day (~ 1/2 cup of coffee) had neonates with lower birth weight (β = −66 g; 95% CI, −121 to −10 g), smaller arm (β = −0.17 cm; 95% CI, −0.31 to −0.02 cm) and thigh (β = −0.32 cm; 95% CI, −0.55 to −0.09 cm) circumference, and smaller anterior flank skin fold (β = −0.24 mm; 95% CI, −0.47 to −0.01 mm). Results did not differ by fast or slow caffeine metabolism genotype.
Conclusions and Relevance
In this cohort study, small reductions in neonatal anthropometric measurements with increasing caffeine consumption were observed. Findings suggest that caffeine consumption during pregnancy, even at levels much lower than the recommended 200 mg per day of caffeine, are associated with decreased fetal growth.
OBJECTIVES: To identify homogenous depressive symptom trajectories over the postpartum period and the demographic and perinatal factors linked to different trajectories. METHODS: Mothers (N = 4866) were recruited for Upstate KIDS, a population-based birth cohort study, and provided assessments of depressive symptoms at 4, 12, 24, and 36 months postpartum. Maternal demographic and perinatal conditions were obtained from vital records and/or maternal report. RESULTS: Four depression trajectories were identified: low-stable (74.7%), characterized by low symptoms at all waves; low-increasing (8.2%), characterized by initially low but increasing symptoms; medium-decreasing (12.6%), characterized by initially moderate but remitting symptoms; and high-persistent (4.5%), characterized by high symptoms at all waves. Compared with the high-persistent group, older mothers (maximum odds ratio [OR] of the 3 comparisons: 1.10; 95% confidence interval [CI]: 1.05 to 1.15) or those with college education (maximum OR: 2.52; 95% CI: 1.36 to 4.68) were more likely to be in all other symptom groups, and mothers who had a history of mood disorder (minimum OR: 0.07; 95% CI: 0.04 to 0.10) or gestational diabetes mellitus diagnosis (minimum OR: 0.23; 95% CI: 0.08 to 0.68) were less likely to be in other symptom groups. Infertility treatment, multiple births, prepregnancy BMI, gestational hypertension, and infant sex were not differentially associated with depressive symptom trajectories. CONCLUSIONS: One-quarter of mothers in a population-based birth cohort had elevated depressive symptoms in 3 years postpartum. Screening for maternal depression beyond the postpartum period may be warranted, particularly after mood and diabetic disorders.
Many women who experience gestational diabetes (GDM), gestational hypertension (GHT), pre-eclampsia (PE), have a spontaneous preterm birth (sPTB) or have an offspring born small/large for gestational age (SGA/LGA) do not meet the criteria for high-risk pregnancies based upon certain maternal risk factors. Tools that better predict these outcomes are needed to tailor antenatal care to risk. Recent studies have suggested that metabolomics may improve the prediction of these pregnancy-related disorders. These have largely been based on targeted platforms or focused on a single pregnancy outcome. The aim of this study was to assess the predictive ability of an untargeted platform of over 700 metabolites to predict the above pregnancy-related disorders in two cohorts. We used data collected from women in the Born in Bradford study (BiB; two sub-samples, n = 2000 and n = 1000) and the Pregnancy Outcome Prediction study (POPs; n = 827) to train, test and validate prediction models for GDM, PE, GHT, SGA, LGA and sPTB. We compared the predictive performance of three models: (1) risk factors (maternal age, pregnancy smoking, BMI, ethnicity and parity) (2) mass spectrometry (MS)-derived metabolites (n = 718 quantified metabolites, collected at 26–28 weeks’ gestation) and (3) combined risk factors and metabolites. We used BiB for the training and testing of the models and POPs for independent validation. In both cohorts, discrimination for GDM, PE, LGA and SGA improved with the addition of metabolites to the risk factor model. The models’ area under the curve (AUC) were similar for both cohorts, with good discrimination for GDM (AUC (95% CI) BiB 0.76 (0.71, 0.81) and POPs 0.76 (0.72, 0.81)) and LGA (BiB 0.86 (0.80, 0.91) and POPs 0.76 (0.60, 0.92)). Discrimination was improved for the combined models (compared to the risk factors models) for PE and SGA, with modest discrimination in both studies (PE-BiB 0.68 (0.58, 0.78) and POPs 0.66 (0.60, 0.71); SGA-BiB 0.68 (0.63, 0.74) and POPs 0.64 (0.59, 0.69)). Prediction for sPTB was poor in BiB and POPs for all models. In BiB, calibration for the combined models was good for GDM, LGA and SGA. Retained predictors include 4-hydroxyglutamate for GDM, LGA and PE and glycerol for GDM and PE. MS-derived metabolomics combined with maternal risk factors improves the prediction of GDM, PE, LGA and SGA, with good discrimination for GDM and LGA. Validation across two very different cohorts supports further investigation on whether the metabolites reflect novel causal paths to GDM and LGA.
Background The association between obesity (body mass index (BMI) ≥ 30 kg/m2) and pattern of medication use during pregnancy in the United States is not well-studied. Higher pre-pregnancy BMI may be associated with increases or decreases in medication use across pregnancy as symptoms (e.g. reflux) or comorbidities (e.g. gestational diabetes) requiring treatment that may be associated with higher BMI could also change with advancing gestation.Objectives To determine whether prenatal medication use, by the number and types of medications, varies by pre-pregnancy obesity status.Methods In a secondary data analysis of a racially/ethnically diverse prospective cohort of pregnant women with low risk for fetal abnormalities enrolled in the first trimester of pregnancy and followed to delivery (singleton, 12 United States clinical sites), free text medication data were obtained at enrollment and up to five follow-up visits and abstracted from medical records at delivery.Results In 436 women with obesity and 1750 women without obesity (pre-pregnancy BMI, 19–29.9 kg/m2), more than 70% of pregnant women (77% of women with and 73% of women without obesity) reported taking at least one medication during pregnancy, respectively (adjusted risk ratio (aRR)=1.10, 95% confidence interval (CI)=1.01, 1.20), with 81% reporting two and 69% reporting three or more. A total of 17 classes of medications were identified. Among medication classes consumed by at least 5% of all women, the only class that differed between women with and without obesity was hormones and synthetic substitutes (including steroids, progesterone, diabetes, and thyroid medications) in which women with obesity took more medications (11 vs. 5%, aRR = 1.9, 95% CI = 1.38, 2.61) compared to women without obesity. Within this class, a higher percentage of women with obesity took diabetes medications (2.3 vs. 0.7%) and progesterone (3.4 vs. 1.3%) than their non-obese counterparts. Similar percentages of women with and without obesity reported consuming medications in the remaining medication classes including central nervous system agents (50 and 46%), gastrointestinal drugs (43 and 40%), anti-infective agents (23 and 21%), antihistamines (20 and 17%), autonomic drugs (10 and 9%), and respiratory tract agents (7 and 6%), respectively (p > 0.05 for all adjusted comparisons). There were no differences in medication use by obesity status across gestation. Since the study exclusion criteria limited the non-obese group to women without thyroid disease, in a sensitivity analysis we excluded all women who reported thyroid medication intake and still a higher proportion of women with obesity took the hormones and synthetic substitutes class compared to women without obesity.Conclusion Our findings suggest that pre-pregnancy obesity in otherwise healthy women is associated with a higher use of only selected medications (such as diabetes medications and progesterone) during pregnancy, while the intake of other more common medication types such as analgesics, antibiotics, and antacids does not vary by pre-pregnancy obesity status. As medication safety information for prenatal consumption is insufficient for many medications, these findings highlight the need for a more in-depth examination of factors associated with prenatal medication use.
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