Figures
Abstract
Objective
To describe prescription medicine dispensing before and during pregnancy in New Zealand, 2005–2015.
Methods
Members of the New Zealand Pregnancy Cohort were linked with their dispensing records in a national database of prescription products dispensed from community pharmacies. We identified the proportion of pregnancies during which at least one prescription medicine was dispensed, the number of different medicines used and the most commonly dispensed medicine groups both during pregnancy and in the 270 days before conception. Dispensing during pregnancy was assessed by several maternal characteristics.
Results
874,884 pregnancies were included. Over the study timeframe, the proportion of pregnancies exposed to a non-supplement prescription medicine increased from 38.5% to 67.2%. The mean number of different non-supplement medicines dispensed during pregnancy increased from 2.5 to 3.2. Dispensing during pregnancy was weakly associated with body mass index, smoking status and ethnicity. Pregnancy exposure was highest for Antibacterials (26.0%), Analgesics (16.7%) and Antinausea & Vertigo Agents (11.0%).
Citation: Donald S, Sharples K, Barson D, Horsburgh S, Parkin L (2020) Patterns of prescription medicine dispensing before and during pregnancy in New Zealand, 2005–2015. PLoS ONE 15(6): e0234153. https://doi.org/10.1371/journal.pone.0234153
Editor: Angela Lupattelli, University of Oslo, NORWAY
Received: February 23, 2020; Accepted: May 19, 2020; Published: June 2, 2020
Copyright: © 2020 Donald et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The data underlying the results presented in the study cannot be shared publicly because they contain potentially identifiable and sensitive patient information. Restrictions on data sharing have been imposed by the New Zealand Ministry of Health. The data are available for researchers who meet the criteria for access to confidential data, from the New Zealand Ministry of Health (data-enquiries@health.govt.nz). The authors had no special access to the underlying data. Anonymised data would be sufficient to replicate study results.
Funding: This research was supported by a Clinical Research Training Fellowship (SD) from the Health Research Council of New Zealand (grant number 16/072) (https://www.hrc.govt.nz/). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Although many medicines lack evidence on their risk in pregnancy [1, 2] there is still substantial use of prescription medicines during pregnancy [3], with exposure increasing over recent decades [4–6]. Some recent estimates from Western countries show the proportions of pregnancies exposed to at least one medication ranged from 46%–93% [4, 5, 7–13]. Many pregnant women take multiple different medicines [10, 13–15]. Although patterns of use vary by country, systemic antibacterials, anti-emetics, gynaecological anti-infectives and antihistamines are commonly among the most dispensed medications during pregnancy [5, 8–10, 13–23].
Despite a deficit of safety information, the management of chronic or acute conditions during pregnancy may require continuation of an already prescribed medicine and/or the initiation of new therapies. A high proportion of pregnancies are unplanned [24], so that fetal exposure to medicines may occur in the early stages of organogenesis before the pregnancy is recognised. Awareness of medicine utilisation patterns allows the appropriateness of prescribing during pregnancy to be assessed and any concerning trends to be addressed. It may also highlight priority research areas.
There have been no comprehensive investigations of prescription medicine use during pregnancy in New Zealand. New Zealand has a publicly funded health care system, with free hospital and maternity care, as well as subsidised prescription medicines. Information on the use of these health services is held in national databases; these data have been used to construct a pregnancy cohort which can now be linked with dispensing records to investigate medicine use during pregnancy.
The aims of this study were to i) describe trends in prescription medicine dispensing before and during pregnancy in New Zealand from 2005–2015, and ii) examine prescription medicine dispensing during pregnancy by maternal characteristics.
Methods
Study cohort
This study was undertaken using the New Zealand Pregnancy Cohort, a national cohort containing 941,468 pregnancies over the period 2005–2015. The generation of this cohort has been described [25]. Briefly, records of pregnancies were identified in four New Zealand national health databases (covering hospital discharges, maternity care, laboratory tests (antenatal blood tests) and mortality records). Pregnancies with records in more than one database were matched using a unique patient identifier (an encrypted National Health Index (NHI)) and the pregnancy dates extracted or estimated from each database. Cohort members whose records lacked a last menstrual period (LMP) date or gestational age data (15%) had their LMP date estimated from an ICD-10-AM ‘duration of pregnancy’ code (O09) [26], which provided a range of earliest and latest possible gestational ages at the time of pregnancy end.
The pregnancy cohort includes all identified pregnancies of women who were 15–49 years of age at the start of pregnancy and had an LMP date between 1 January 2005 and 15 March 2015. In addition to virtually all deliveries of live and/or stillborn infants, the cohort also contains most other recognised pregnancies–those during which antenatal blood testing was undertaken and/or the woman received hospital care for a miscarriage, termination, or other early pregnancy loss. Not all cohort pregnancies have a known outcome; most of these pregnancies were identified by an early antenatal blood test only, and were presumed to be pregnancies that did not progress past the early stages. Maternal characteristics available for cohort members included maternal age, prioritised ethnicity, deprivation (New Zealand Index of Deprivation—NZDep) quintile, body mass index (BMI), smoking status and parity (primiparous vs. non-primiparous). Further description of these variables is available in S1 File.
For this study, only pregnancies with an LMP date from 15 September 2005 were included to ensure that 270 days of pre-conception dispensing data were available.
Dispensing data
Dispensings of publicly funded medications from community pharmacies in New Zealand are recorded in the national Pharmaceutical Collection (PHARMS) [27]. PHARMS does not use the Anatomical Therapeutic Chemical (ATC) classification system but instead products are organised into therapeutic groups. In general, Level 1 therapeutic groups are organised by body system (e.g. Nervous System), with Level 2 therapeutic groups organised by functional group (e.g. Antidepressants) and Level 3 by drug class (e.g. Selective Serotonin Reuptake Inhibitors). Individual drugs (e.g. citalopram) have a unique chemical id number.
Using the NHI, records of dispensings occurring from 270 days prior to conception through to the end of pregnancy were linked with each pregnancy. Dispensings of medical devices, vaccines, food products and non-medicinal dermatological or compounding products were excluded (S1 Table). Dispensings of vitamins, minerals and folic acid were retained and categorised as supplements (S2 Table).
Exposure was defined as the dispensing of ≥1 prescription medicine (i.e. a filled prescription) during the time period of interest. Dispensings in eight time periods were considered: three consecutive 90-day pre-pregnancy periods (1–90, 91–180, and 181–270 days pre-conception), the entire 9-month pre-pregnancy period, each of the three pregnancy trimesters, and the entire pregnancy (S1 Fig). Conception was assumed to have occurred 14 days after the LMP date.
Analyses
Changes in the proportion of pregnancies with ≥1 non-supplement dispensing by year of LMP, for each of the pre-pregnancy and pregnancy periods, were assessed. The denominator for Trimesters 2 and 3 was the number of pregnancies that had persisted to the start of the trimester. For any given pregnancy, we did not left censor the pre-pregnancy period for a previous pregnancy occurring within the previous 270 days. Sensitivity analyses were carried out to assess the impact of 1) using the earliest or latest estimated LMP dates for the 15% of the cohort with a range of LMP dates, and 2) left censoring those with a previous pregnancy in the pre-pregnancy period. The proportions of pregnancies in which ≥1 non-supplement medicine was dispensed were compared by pregnancy outcome (for Trimester 1), and by maternal characteristics. For pregnancies with at least one non-supplement dispensing, changes in the number of different medicines dispensed over time (year of LMP) were assessed, as well as differences by maternal characteristics and by pregnancy outcome (for Trimester 1).
Dispensings were examined to determine which medicine groups (Therapeutic Group Level 2) were associated with ≥1% of the pregnancies, in either the 270-day pre-pregnancy period or during pregnancy. Those therapeutic groups dispensed during ≥1% of pregnancies were examined for changes in proportions over time (in 3 time periods: 2005–2008, 2009–2011, 2012–2015).
Multiple imputation using chained equations (m = 40 imputations) was used to estimate missing maternal characteristic data. The imputation model included the year of LMP, all six maternal characteristics, three outcome variables and several auxiliary variables derived from the cohort members’ past dispensings and hospitalisations. Full details of the imputation model are available in S2 File.
A generalised estimating equation framework was used for analyses of proportions with ≥1 dispensing, to allow for clustering of more than one pregnancy within a mother. Proportions were compared using relative risk regression [28] with Poisson errors, robust standard errors and clustered by mother. Analyses of the number of medicines dispensed in those with ≥1 dispensing were modelled using negative binomial regression (adjusted for clustering by mother) to estimate the relative change in the mean number of different medicines used. Analyses were done by trimester to account for duration of pregnancy. All analyses were carried out using STATA v14.2.
Results
The analyses were based on 874,884 pregnancies to 468,480 women (see S3 Table for the number of pregnancies per cohort member). For each pregnancy, maternal characteristics at the time of the pregnancy and the pregnancy outcome are shown in Table 1. The relative proportions of pregnancy outcomes did not change substantially over the study period (S4 Table). All findings reported in this paper are based on the analyses undertaken using the earliest LMP dates, which did not vary substantially from those found using the latest LMP dates.
Overall, a prescription medicine or supplement was dispensed at least once during 69.4% of pregnancies. However, the proportion of exposed pregnancies increased over time, rising from 43.9% in 2005 to 82.3% in 2015. This increase was accompanied by a corresponding, though less pronounced, increase in exposure in the 270-day pre-pregnancy period, from 47.8% to 71.8%.
After excluding supplements, ≥1 dispensing occurred during 57.8% of all pregnancies, and in 64.6% of pregnancies ending in the delivery of a live and/or stillborn infant. An increase in the exposed proportion over time was evident in all pre-pregnancy and pregnancy periods (Fig 1). For the whole cohort, exposure during pregnancy increased from 38.5% in 2005 to 67.2% in 2015 (RR 1.75 [1.72–1.78]). Although the exposed proportions in the 90-days prior to pregnancy and in Trimester 1 were very similar overall (35.3% and 35.5% respectively), exposure was slightly higher in Pre-pregnancy 1 until 2010, after which time exposure in Trimester 1 became slightly higher. For pregnancies ending in delivery, the exposed proportions for the individual pre-pregnancy and pregnancy periods were very similar to those of the whole cohort (S5 Table). Results for the sensitivity analyses of the exposed proportions using the earliest and latest LMP dates are shown in S6 Table. Proportions with pre-pregnancy exposure to ≥1 non-supplement medicine did not change substantially when pregnancies with a previous pregnancy in the 270-day pre-pregnancy period were excluded from the analyses (S7 Table).
Pre-pregnancy 3 = 181–270 days pre-conception, Pre-pregnancy 2 = 91–180 days pre-conception, Pre-pregnancy 1 = 1–90 days pre-conception. The denominators for Trimesters 2 and 3 include only those pregnancies that persisted to the start of the respective trimester.
The proportion of pregnancies in which multiple non-supplement medicines were dispensed rose over the study period, from 14.6% to 25.3% for 2–3 different medicines, from 6.9% to 19.1% for 4–7 medicines, and from 1.2% to 4.3% for ≥8 medicines. Considering only the pregnancies with ≥1 non-supplement dispensing, the mean number of different medicines dispensed for the cohort overall was 2.9, increasing from 2.5 in 2005 to 3.2 in 2015 (RR 1.49 [1.44–1.53]). The mean number of medicines dispensed during pregnancies that ended in delivery was 3.1. Over the study timeframe, the mean number of different medicines dispensed increased in all pre-pregnancy and pregnancy periods (Fig 2). The mean number of different medicines dispensed in the 270 days pre-pregnancy also increased over the study timeframe, from 2.8 to 3.9 (RR 1.57 [1.52–1.61]).
Pre-pregnancy 3 = 181–270 days pre-conception, Pre-pregnancy 2 = 91–180 days pre-conception, Pre-pregnancy 1 = 1–90 days pre-conception.
During Trimester 1, exposure to ≥1 non-supplement was slightly higher in pregnancies that ended early compared to those ending in a delivery (38.8% vs 34.6%), with a similar mean number of medicines dispensed in both groups (2.3 vs 2.1) (Table 2).
After adjusting for the other maternal characteristics, year of LMP and clustering by mother, the likelihood of being dispensed a non-supplement medicine at least once during a pregnancy trimester was not strongly associated with the maternal characteristics investigated (Table 3). In all trimesters, a dispensing was less likely for Asian women versus European women, whereas Māori women were marginally less likely to have had ≥1 dispensing in Trimester 1 (aRR 0.92 [0.92–0.93]), and Trimester 3 exposure was slightly lower in Pacific women (aRR 0.93 [0.92–0.94]. A dispensing was slightly more likely in all trimesters if a woman was obese versus a healthy weight, or was more deprived. Exposure was higher in smokers in Trimester 1 (aRR 1.09 [1.08–1.09]) and Trimester 3 (aRR1.08 [1.07–1.09]), and in non-primiparous women in Trimester 3 (aRR1.11 [1.10–1.12]).
The mean number of different non-supplement medicines dispensed during the pregnancy trimesters did not vary substantially by the different maternal characteristics; obesity, smoking, and the oldest age group were weakly associated with the dispensing of more medicines (Table 4). The relative risks for associations with maternal characteristics found in the complete case analyses were broadly similar to those reported above (S8 Table).
Therapeutic groups dispensed during at least 1% of pregnancies are shown in Table 5 (relative risks and 95% confidence intervals for trends during pregnancy and for trends over time are available in S9 and S10 Tables respectively). All therapeutic groups dispensed to at least one cohort member before or during pregnancy are listed in S11 Table. Overall, Minerals (36.9%) and Antianaemics (27.8%) were dispensed in the highest proportion of pregnancies. Practically all of the pre-pregnancy and pregnancy Antianaemics dispensings were folic acid. Antibacterials (26.0%), Analgesics (16.7%) and Antinausea & Vertigo Agents (11.0%) were the most commonly dispensed non-supplements during pregnancy. Dispensing of therapeutic groups during Trimester 1 by pregnancy outcome are shown in S12 Table.
Non-supplement therapeutic groups in Table 5 that were dispensed more commonly during Trimester 1 than in the 30 days prior to pregnancy included the Antinausea & Vertigo Agents, Gynaecological Anti-infectives, Laxatives, Urinary Tract Infections, Antacids & Antiflatulants, Treatments for Substance Dependence, and Antithrombotic Agents.
Antibacterial dispensings were fairly stable throughout pre-pregnancy and pregnancy. Rising use throughout pregnancy was seen for Gynaecological Anti-infectives, Antiulcerants, Antacids & Antiflatulants, Topical Antifungals, and Diabetes. Conversely, dispensings of Antianaemics, Antinausea & Vertigo Agents, Antidepressants, Non-steroidal Anti-inflammatory Drugs, and Hormonal Contraceptives dropped throughout pregnancy.
For all therapeutic groups in Table 5 except Inhaled Corticosteroids, the proportion exposed during pregnancy increased over time. Compared to the earliest years of the study, the non-supplement groups with the highest absolute increase in the proportion of pregnancies with ≥1 dispensing by the end of the study were the Analgesics (+10.8%), Antinausea and Vertigo Agents (+8.9%) and Antibacterials (+7.5%). In terms of relative increase, the top non-supplement groups were the Antithrombotic Agents (RR 5.40 [5.12–5.70]), Treatments for Substance Dependence (RR 4.22 [4.00–4.45]), and Laxatives (RR 2.76 [2.69–2.84]).
Discussion
We found that the proportion of pregnancies in which at least one non-supplement prescription medicine was dispensed increased substantially between 2005 and 2015, and the number of different medicines dispensed also rose. Exposure in early pregnancy was similar in all pregnancies regardless of outcome, but was higher during the whole pregnancy for those that progressed to a delivery. This discrepancy is likely attributable to the longer duration of such pregnancies. During pregnancy, dispensing did not vary substantially by the maternal characteristics; the strongest positive associations with higher exposure was in obese women.
This study is the first to describe prescription medicine dispensing patterns in pregnant women in New Zealand. A key strength is the inclusion of over 878,000 pregnancies–representing almost all of the live and stillbirths nationally between 2005 and 2015, as well as many of the pregnancies which did not progress past early pregnancy. Linkage of these pregnancies with national dispensing data from community pharmacies has provided a national picture of prescription medicine dispensing in pregnancy.
There were some limitations to this study which require further consideration. In New Zealand the use of folic acid, iodine and iron are recommended during pregnancy [29, 30] and these products are available both on prescription and over-the-counter. Despite evidence from this study showing that the proportion of pregnancies in which Minerals, Vitamins and Antianaemics (mostly folic acid) were dispensed increased considerably, the lack of information on patterns of over-the-counter purchases of these supplements limited our ability to draw meaningful conclusions regarding overall exposure patterns. However, our key focus was the use of non-supplement prescription medicines.
Our study used dispensing data, which does not necessarily equate to consumption, so could have overestimated medicines actually used in pregnancy. Pregnant women often overestimate the teratogenic risk of prescription medicines, which can reduce adherence during pregnancy [31–34]. However, several studies have shown high levels of concordance between self-reported medicine use and medical records for medicines used to treat chronic conditions during pregnancy, with somewhat lower concordance for medicines used intermittently or for short durations [35–39]. It is important to note that concordance may be affected not only by non-consumption but also by incorrect self-report (e.g. poor recall for short-term medicines [35, 36], or non-disclosure of socially stigmatised medicines [35] and medicines viewed as innocuous [40]). Dispensing claims databases are regarded as a valid data source for pregnancy pharmacoepidemiology studies [41, 42].
Although the exposure definition used in this study (≥1 dispensing) was fairly simple, it was appropriate for the study aims, which were to provide a general overview of prescription medicine dispensing in pregnancy and to describe changes over time. In future studies which aim to explore potential relationships between the use of specific medicines in pregnancy and health outcomes, it will be possible to employ more sophisticated exposure definitions which take dose and duration of use into account. We did not censor the pre-pregnancy period if there was a previous pregnancy within the 270 days examined, however our sensitivity analyses demonstrated that it would have made very little difference to our findings had we done so.
PHARMS does not include information about medicines dispensed in hospital, so exposure may have been underestimated if women were admitted to hospital during pregnancy. PHARMS records are compiled from reimbursement claims from community pharmacies, and the data quality is dependent upon the information submitted in the claims. The proportion of dispensing records (for all patients of all ages) without an NHI was 13.4% in 2005, 7.8% in 2006, and <5% by 2008. While a small part of the increase in dispensing seen in this study could be attributable to the improved NHI recording over time, the increases in dispensing were much higher than the improvement in NHI recording and most of the increase seen is probably due to real changes in dispensing patterns. Additionally, because exposure was simply defined as ≥1 dispensing, it is possible that while some dispensings to a particular woman were lacking an NHI, others did include an NHI, minimising exposure misclassification.
An appreciable proportion of records were missing data for BMI, smoking status and parity. We used multiple imputation to fill in the missing data, which should produce estimates with reduced bias compared with complete case analyses [43], however, some residual bias could remain due to the nature of some of the missing data. The associations between maternal characteristics and dispensing patterns in our cohort were weak. Some studies have found stronger associations between the use of at least one medicine during pregnancy and BMI [5], smoking [44], ethnicity [45], and household income [14], although observed relationships with parity [5, 18, 44] and maternal age [5, 44] vary. However, different settings and health systems from the New Zealand context make direct comparisons with international studies difficult.
The weak association with maternal characteristics in this study could be due to residual confounding or a true reflection that dispensing in pregnancy in New Zealand is not strongly dependent on these factors. Antenatal care is free, with midwives able to prescribe within their scope of practice, partially reducing the impact of recognised financial barriers associated with accessing primary care [46]. We were unable to adjust for factors such as education level, household income, alcohol use, marital status, and whether a pregnancy was planned, which have been shown to be associated with medicine use in pregnancy in other studies [14, 44, 45]. Other studies have found an association between a summary measure of chronic health conditions and being dispensed a prescription medicine during pregnancy [5, 45]. We were not able to explore this association because we did not have access to primary care data and we did not think the use of hospitalisation records would provide a reliable measure of chronic disease in women of child-bearing age. Moreover, we felt that using dispensings of medicines to generate a chronic condition variable to then analyse dispensing patterns would be circular.
The proportion of pregnancies ending in a delivery during which a non-supplement medicine was dispensed in New Zealand (64.6%) occurred in the middle of the range of international comparisons over a similar time period, and was roughly comparable to exposure in British Columbia, Canada (2002–2011: 62%) [5] and Denmark (1999–2009: 56.0%) [4]. Substantially higher exposure was found for women in the US Medicaid Program (2000–2007: 82.5%) [9] and in France (2004–2005: 93%) [13]. Women with pregnancies ending in a delivery in New Zealand were exposed to a similar mean number of different medicines during pregnancy (3.1) as those in British Columbia (2.7) [15], Denmark (2.6) [14] and Norway (3.3) [10], but much lower than French women (11.3) [13]. Medicines requiring a prescription may vary between countries, which could contribute to the variation in these estimates across studies.
Our most commonly dispensed non-supplement group during pregnancy was Antibacterials (26.0% during pregnancy; 11.0%–14.4% per trimester), which was also the most dispensed group during pregnancy in Western Australia (10.4%) [18] and a number of European (11.6%–27.0% during pregnancy [19, 21]; 9.4%–12.5% per trimester [8, 10]) and North American (26.1%–39.8%) [15–17] locations. Antibacterials were also highly dispensed during pregnancy in the Netherlands (20.6%) [23] and France (50.9%) [47]. Pregnancy exposure to Analgesics (including opioids and non-opioids) in New Zealand (16.7%; 6.7%–9.6% per trimester) was similar to that found in a study of eight Health Maintenance Organizations (14.2%) in the United States [17], although that study’s timeframe (1996–2000) was prior to the opioid epidemic [48]. Except for in France (72.0%) [47] analgesic exposure was much lower in most other regions (3.7% [18], 4.3% [23]; 1–1.5% per trimester [49]) than in New Zealand. Our use of Antinausea & Vertigo Agents (11.0%) was similar to that in Quebec (13.7%) [16] but direct comparisons were more difficult as some locations [8, 10, 15, 23] had lower antiemetic use but higher use of antihistamines, some of which (e.g. doxylamine) may be used for alleviating nausea in pregnancy.
Conclusion
This high-level overview of dispensing patterns has demonstrated increasingly medicated pregnancies in New Zealand in recent years, which is consistent with international trends in medicine use both within [4–6] and outside of [50, 51] pregnancy. Like their non-pregnant counterparts, pregnant women deserve to have their health issues treated effectively, so while this increase in medicine use isn’t necessarily cause for concern, the lack of pregnancy safety information for most medicines does mean that this increase shouldn’t be ignored. This study further highlights the urgent need for researchers to better quantify potential fetal impacts of exposure to medications commonly used during pregnancy.
This study provides directions for future research. For example, Antibacterials were dispensed in more than a quarter of New Zealand pregnancies, and it would be informative to investigate the specific antibiotics dispensed as some (tetracyclines, aminoglycosides) are not recommended in pregnancy. The high prevalence of anti-emetic exposure in the first trimester (8%) could also warrant further investigation, considering recent questions about the fetal safety of ondansetron in early pregnancy [52–54].
Supporting information
S1 File. Assignment of maternal characteristics.
https://doi.org/10.1371/journal.pone.0234153.s001
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S2 File. Details of the multiple imputation model to estimate missing maternal characteristics.
https://doi.org/10.1371/journal.pone.0234153.s002
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S1 Fig. Pre-pregnancy and pregnancy time periods examined in this study.
https://doi.org/10.1371/journal.pone.0234153.s003
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S1 Table. Products in the Pharmaceutical Collection excluded from this study.
https://doi.org/10.1371/journal.pone.0234153.s004
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S2 Table. Products in the Pharmaceutical Collection categorised as supplements.
https://doi.org/10.1371/journal.pone.0234153.s005
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S3 Table. Number of pregnancies per cohort member.
https://doi.org/10.1371/journal.pone.0234153.s006
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S5 Table. Proportion with ≥1 dispensing of a non-supplement medicine, for the whole cohort and for pregnancies ending in a delivery.
https://doi.org/10.1371/journal.pone.0234153.s008
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S6 Table. Comparison of the proportion of exposed pregnancies using the earliest vs latest LMP dates.
https://doi.org/10.1371/journal.pone.0234153.s009
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S7 Table. Comparison of the proportions with ≥1 non-supplement dispensing in pre-pregnancy using the whole cohort vs left-censoring for those with a previous pregnancy within 270 days.
https://doi.org/10.1371/journal.pone.0234153.s010
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S8 Table. Proportions with ≥1 dispensing of a non-supplement medication by maternal characteristics: complete case analyses vs analyses using imputed data, by trimester.
https://doi.org/10.1371/journal.pone.0234153.s011
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S9 Table. Proportions with ≥1 dispensing from Level 2 therapeutic groups; trends before and during pregnancy (with relative risks and 95% confidence intervals).
https://doi.org/10.1371/journal.pone.0234153.s012
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S10 Table. Proportions with ≥1 dispensing from Level 2 therapeutic groups; trends over study years (with relative risks and 95% confidence intervals).
https://doi.org/10.1371/journal.pone.0234153.s013
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S11 Table. Proportions with ≥1 dispensing from the Level 2 therapeutic groups before and during pregnancy.
Table includes all therapeutic groups dispensed to at least one cohort member.
https://doi.org/10.1371/journal.pone.0234153.s014
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S12 Table. Proportions with ≥1 dispensing from Level 2 therapeutic groups during Trimester 1, by grouped pregnancy outcome.
https://doi.org/10.1371/journal.pone.0234153.s015
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Acknowledgments
We would like to thank the team at Analytical Services, Ministry of Health for extracting the data from the National Collections. This research was supported by a contract from the Health Research Council of New Zealand.
References
- 1. Lo WY, Friedman JM. Teratogenicity of recently introduced medications in human pregnancy. Obstetrics & Gynecology. 2002;100(3):465–73.
- 2. Adam MP, Polifka JE, Friedman JM. Evolving knowledge of the teratogenicity of medications in human pregnancy. American Journal of Medical Genetics Part C: Seminars in Medical Genetics. 2011;157(3):175–82. pmid:21766440
- 3. Daw JR, Hanley GE, Greyson DL, Morgan SG. Prescription drug use during pregnancy in developed countries: a systematic review. Pharmacoepidemiology and Drug Safety. 2011;20(9):895–902. pmid:21774029
- 4. Bjørn A-MB, Nørgaard M, Hundborg HH, Nohr EA, Ehrenstein V. Use of prescribed drugs among primiparous women: an 11-year population-based study in Denmark. Clinical Epidemiology. 2011;3(1):149–56. pmid:21607016
- 5. Smolina K, Hanley GE, Mintzes B, Oberlander TF, Morgan S. Trends and determinants of prescription drug use during pregnancy and postpartum in British Columbia, 2002–2011: A population-based cohort study. PLoS One. 2015;10(5):e0128312. pmid:26011706
- 6. Mitchell AA, Gilboa SM, Werler MM, Kelley KE, Louik C, Hernández-Díaz S. Medication use during pregnancy, with particular focus on prescription drugs: 1976–2008. American Journal of Obstetrics and Gynecology. 2011;205(1):51.e1–.e8. pmid:21514558
- 7. Dillon P, O'Brien KK, McDonnell R, Donnelly-Swift E, Galvin R, Roche A, et al. Prevalence of prescribing in pregnancy using the Irish primary care research network: a pilot study. BMC Pregnancy & Childbirth. 2015;15:67. pmid:25884886
- 8. Stephansson O, Granath F, Svensson T, Haglund B, Ekbom A, Kieler H. Drug use during pregnancy in Sweden–assessed by the Prescribed Drug Register and the Medical Birth Register. Clinical Epidemiology. 2011;3:43–50. pmid:21386973
- 9. Palmsten K, Hernandez-Diaz S, Chambers CD, Mogun H, Lai S, Gilmer TP, et al. The most commonly dispensed prescription medications among pregnant women enrolled in the U.S. Medicaid program. Obstetrics & Gynecology. 2015;126(3):465–73. pmid:26244530
- 10. Engeland A, Bramness JG, Daltveit AK, Rønning M, Skurtveit S, Furu K. Prescription drug use among fathers and mothers before and during pregnancy. A population‐based cohort study of 106 000 pregnancies in Norway 2004–2006. British Journal of Clinical Pharmacology. 2008;65(5):653–60. pmid:18294334
- 11. Gagne JJ, Maio V, Berghella V, Louis DZ, Gonnella JS. Prescription drug use during pregnancy: a population-based study in Regione Emilia-Romagna, Italy. European Journal of Clinical Pharmacology. 2008;64(11):1125–32. pmid:18685836
- 12. Irvine L, Flynn RWV, Libby G, Crombie IK, Evans JMM. Drugs dispensed in primary care during pregnancy: a record-linkage analysis in Tayside, Scotland. Drug Safety. 2010;33(7):593–604. pmid:20553060
- 13. Lacroix I, Hurault C, Sarramon MF, Guitard C, Berrebi A, Grau M, et al. Prescription of drugs during pregnancy: a study using EFEMERIS, the new French database. European Journal of Clinical Pharmacology. 2009;65(8):839–46. pmid:19365629
- 14. Olesen C, Thrane N, Henriksen TB, Ehrenstein V, Olsen J. Associations between socio-economic factors and the use of prescription medication during pregnancy. European Journal of Clinical Pharmacology. 2006;62(7):547–53. pmid:16673101
- 15. Daw JR, Mintzes B, Law MR, Hanley GE, Morgan SG. Prescription drug use in pregnancy: a retrospective, population-based study in British Columbia, Canada (2001–2006). Clinical Therapeutics. 2012;34(1):239–49.e2. pmid:22169049
- 16. Berard A, Sheehy O. The Quebec Pregnancy Cohort—Prevalence of medication use during gestation and pregnancy outcomes. PLoS ONE 2014;9. pmid:24705674
- 17. Andrade SE, Gurwitz JH, Davis RL, Chan KA, Finkelstein JA, Fortman K, et al. Prescription drug use in pregnancy. American Journal of Obstetrics and Gynecology. 2004;191(2):398–407. pmid:15343213
- 18. Colvin L, Slack-Smith L, Stanley FJ, Bower C. Pharmacovigilance in pregnancy using population-based linked datasets. Pharmacoepidemiology and Drug Safety. 2009;18(3):211–25. pmid:19173342
- 19. Artama M, Gissler M, Malm H, Ritvanen A. Nationwide register-based surveillance system on drugs and pregnancy in Finland 1996–2006. Pharmacoepidemiology and Drug Safety. 2011;20(7):729–38. pmid:21626607
- 20. de Jonge L, de Walle HE, de Jong-van den Berg LT, van Langen IM, Bakker MK. Actual use of medications prescribed during pregnancy: a cross-sectional study using data from a population-based congenital anomaly registry. Drug Safety. 2015;38(8):737–47. pmid:26041497
- 21. Hardy JR, Leaderer BP, Holford TR, Hall GC, Bracken MB. Safety of medications prescribed before and during early pregnancy in a cohort of 81 975 mothers from the UK General Practice Research Database. Pharmacoepidemiology and Drug Safety. 2006;15(8):555–64. pmid:16767799
- 22. Malm H, Martikainen J, Klaukka T, Neuvonen PJ. Prescription drugs during pregnancy and lactation—a Finnish register-based study. European Journal of Clinical Pharmacology. 2003;59(2):127–33. pmid:12700878
- 23. Schirm E, Meijer WM, Tobi H, de Jong-van den Berg LTW. Drug use by pregnant women and comparable non-pregnant women in The Netherlands with reference to the Australian classification system. European Journal of Obstetrics & Gynecology and Reproductive Biology. 2004;114(2):182–8. pmid:15140513
- 24. Singh S, Sedgh G, Hussain R. Unintended pregnancy: worldwide levels, trends, and outcomes. Studies in Family Planning. 2010;41(4):241–50. pmid:21465725
- 25. Donald S, Barson D, Horsburgh S, Sharples K, Parkin L. Generation of a pregnancy cohort for medicine utilisation and medicine safety studies in New Zealand. Pharmacoepidemiology and Drug Safety. 2018;27(12):1335–43. pmid:30394649
- 26.
National Centre for Classification in Health. International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification (ICD-10-AM-III). 3rd ed. Sydney: NCCH, Faculty of Health Sciences, The University of Sydney; 2002.
- 27.
Ministry of Health. Pharmaceutical Collection Wellington: Ministry of Health; 2018 [Available from: https://www.health.govt.nz/nz-health-statistics/national-collections-and-surveys/collections/pharmaceutical-collection.
- 28. Lumley T, Kronmal R, Ma S. Relative Risk Regression in Medical Research: Models, Contrasts, Estimators, and Algorithms. UW Biostatistics Working Paper Series. 2006;Working Paper 293.
- 29.
Ministry of Health. Helpful advice during pregnancy: folic acid, iodine and vitamin D 2018 [Available from: https://www.health.govt.nz/your-health/pregnancy-and-kids/pregnancy/helpful-advice-during-pregnancy/folic-acid-iodine-and-vitamin-d.
- 30. Houghton LA. Nutrition and supplements during pregnancy. Best Practice Journal. 2008(18):42–9.
- 31. Sanz E, Gómez-López T, Martínez-Quintas MJ. Perception of teratogenic risk of common medicines. European Journal of Obstetrics & Gynecology and Reproductive Biology. 2001;95(1):127–31.
- 32. Nordeng H, Ystrøm E, Einarson A. Perception of risk regarding the use of medications and other exposures during pregnancy. European Journal of Clinical Pharmacology. 2010;66(2):207–14. pmid:19841915
- 33. Widnes SF, Schjøtt J, Eide GE, Granas AG. Teratogenic risk perception and confidence in use of medicines in pairs of pregnant women and general practitioners based on patient information leaflets. Drug Safety. 2013;36(6):481–9. pmid:23539202
- 34. Lupattelli A, Picinardi M, Einarson A, Nordeng H. Health literacy and its association with perception of teratogenic risks and health behavior during pregnancy. Patient Education and Counseling. 2014;96(2):171–8. pmid:24862909
- 35. Sarangarm P, Young B, Rayburn W, Jaiswal P, Dodd M, Phelan S, et al. Agreement between self-report and prescription data in medical records for pregnant women. Birth Defects Research Part A: Clinical and Molecular Teratology. 2012;94(3):153–61. pmid:22253196
- 36. Cheung K, El Marroun H, Elfrink ME, Jaddoe VWV, Visser LE, Stricker BHC. The concordance between self‐reported medication use and pharmacy records in pregnant women. Pharmacoepidemiology and Drug Safety. 2017;26(9):1119–25. pmid:28744981
- 37. Pisa FE, Casetta A, Clagnan E, Michelesio E, Vecchi Brumatti L, Barbone F. Medication use during pregnancy, gestational age and date of delivery: agreement between maternal self-reports and health database information in a cohort. BMC Pregnancy and Childbirth. 2015;15(1):310. pmid:26608022
- 38. Olesen C, Sondergaard C, Thrane N, Nielsen GL, de Jong-van den Berg L, Olsen J. Do pregnant women report use of dispensed medications? Epidemiology. 2001;12(5):497–501. pmid:11505166
- 39. Skurtveit S, Selmer R, Odsbu I, Handal M. Self-reported data on medicine use in the Norwegian mother and child cohort study compared to data from the Norwegian prescription database. Norsk Epidemiologi. 2014;24(1–2):209–16.
- 40. Mitchell AA, Cottler LB, Shapiro S. Effect of questionnaire design on recall of drug exposure in pregnancy. American Journal of Epidemiology. 1986;123(4):670–6. pmid:3953545
- 41. Charlton RA, Neville AJ, Jordan S, Pierini A, Damase-Michel C, Klungsøyr K, et al. Healthcare databases in Europe for studying medicine use and safety during pregnancy. Pharmacoepidemiology and Drug Safety. 2014;23(6):586–94. pmid:24664855
- 42. Huybrechts KF, Bateman BT, Hernández-Díaz S. Use of real-world evidence from healthcare utilization data to evaluate drug safety during pregnancy. Pharmacoepidemiology and Drug Safety. 2019;28(7):906–22. pmid:31074570
- 43. White IR, Carlin JB. Bias and efficiency of multiple imputation compared with complete-case analysis for missing covariate values. Statistics in Medicine. 2010;29(28):2920–31. pmid:20842622
- 44. Cleary BJ, Butt H, Strawbridge JD, Gallagher PJ, Fahey T, Murphy DJ. Medication use in early pregnancy-prevalence and determinants of use in a prospective cohort of women. Pharmacoepidemiology and Drug Safety. 2010;19(4):408–17. pmid:20099251
- 45. Riley EH, Fuentes-Afflick E, Jackson RA, Escobar GJ, Brawarsky P, Schreiber M, et al. Correlates of prescription drug use during pregnancy. Journal of Women's Health. 2005;14(5):401–9. pmid:15989412
- 46.
Ministry of Health. Barriers to accessing health care Wellington: Ministry of Health; 2018 [Available from: https://minhealthnz.shinyapps.io/nz-health-survey-2017-18-annual-data-explorer/_w_a04772ad/_w_d2f526cb/#!/explore-topics.
- 47. Demailly R, Escolano S, Quantin C, Tubert‐Bitter P, Ahmed I. Prescription drug use during pregnancy in France: A study from the national health insurance permanent sample. Pharmacoepidemiology & Drug Safety. 2017;26(9):1126–34. pmid:28758270
- 48. Jones MR, Viswanath O, Peck J, Kaye AD, Gill JS, Simopoulos TT. A brief history of the opioid epidemic and strategies for pain medicine. Pain Ther. 2018;7(1):13–21. pmid:29691801
- 49. Bakker MK, Jentink J, Vroom F, Van Den Berg PB, De Walle HE, Jong‐Van Den Berg D. Drug prescription patterns before, during and after pregnancy for chronic, occasional and pregnancy‐related drugs in the Netherlands. BJOG: An International Journal of Obstetrics & Gynaecology. 2006;113(5):559–68. pmid:16637899
- 50. Kantor ED, Rehm CD, Haas JS, Chan AT, Giovannucci EL. Trends in prescription drug use among adults in the United States from 1999–2012. JAMA. 2015;314(17):1818–30. pmid:26529160
- 51. Zhang F, Mamtani R, Scott FI, Goldberg DS, Haynes K, Lewis JD. Increasing use of prescription drugs in the United Kingdom. Pharmacoepidemiology and Drug Safety. 2016;25(6):628–36. pmid:26710965
- 52. Kaplan YC, Richardson JL, Keskin-Arslan E, Erol-Coskun H, Kennedy D. Use of ondansetron during pregnancy and the risk of major congenital malformations: A systematic review and meta-analysis. Reproductive Toxicology. 2019;86:1–13. pmid:30849498
- 53. Huybrechts KF, Hernández-Díaz S, Straub L, Gray KJ, Zhu Y, Patorno E, et al. Association of maternal first-trimester ondansetron use with cardiac malformations and oral clefts in offspring JAMA. 2018;320(23):2429–37. pmid:30561479
- 54. Zambelli-Weiner A, Via C, Yuen M, Weiner DJ, Kirby RS. First trimester ondansetron exposure and risk of structural birth defects. Reproductive Toxicology. 2019;83:14–20. pmid:30385129