The influence of birth outcomes and pregnancy complications on interpregnancy interval: A quantile regression analysis

Elsevier

Available online 18 May 2023

Annals of EpidemiologyAuthor links open overlay panel, , , , , ABSTRACTPurpose

To ascertain whether adverse pregnancy outcomes at first pregnancy influence subsequent interpregnancy intervals (IPIs) and whether the size of this effect varies with IPI distribution

Methods

We included 251,892 mothers who gave birth to their first two singletons in Western Australia, from 1980–2015. Using quantile regression, we investigated whether gestational diabetes, hypertension, or preeclampsia in the first pregnancy influenced IPI to subsequent pregnancy and whether effects were consistent across the IPI distribution. We considered intervals at the 25th centile of the distribution as ‘short’ and the 75th centile as ‘long’.

Results

The average IPI was 26.6 months. It was 0.56 months (95% CI: 0.25-0.88 months) and 1.12 months (95% CI: 0.56 – 1.68 months) longer after preeclampsia, and gestational hypertension respectively. There was insufficient evidence to suggest that the association between previous pregnancy complications and IPI differed by the extent of the interval. However, associations with marital status, race/ethnicity and stillbirth contributed to either shortening or prolonging IPIs differently across the distribution of IPI.

Conclusion

Mothers with preeclampsia and gestational hypertension had slightly longer subsequent interpregnancy intervals than mothers whose pregnancies were not complicated by these conditions. However, the extent of the delay was small (<2 months).

Section snippetsINTRODUCTION

Interpregnancy interval (IPI), the period between the end of one pregnancy and conception of the next, has been associated with adverse pregnancy complications. [1], [2] Both short and long IPIs are associated with a greater risk of gestational diabetes and hypertensive complications of pregnancy (preeclampsia, gestational hypertension) in subsequent pregnancies.

It is well established that pregnancy complications have a higher tendency to recur. [3], [4] A recent meta-analysis reported that

Design, participants, and data sources

We conducted a longitudinal study of mothers who gave birth to their first two singletons (parity 0 and 1) at 20-44 weeks of gestation in Western Australia (WA) between 1980 - 2015. We obtained birth records from the Midwives Notification System (MNS), and maternal hospitalization records from Hospital Morbidity Data Collection. [6], [7] Data sources have been described in detail in our protocol. 8

Cohort characteristics

Of the eligible 258,037 women with their first two consecutive pregnancies between 1980 and 2015, 6,145 were excluded due to missing information on key covariates (gestational length, SES, maternal age, IPI, and infant weight), leaving 251,892 women eligible for analyses (Supplementary Figure 1). The mean (+ SD) age at study entry (first delivery) was 25.29 (5.2) and peaked between 25-29 years. The majority of mothers were married and Caucasian (Table 1). The prevalence of gestational diabetes,

Discussion

Using data from a large population cohort of mothers with their first two births, we used quantile regression to ascertain whether pregnancy complications at first pregnancy influence subsequent IPI and verify whether changes occur along the IPI distribution. To our knowledge, no studies have investigated the influence of pregnancy complications on IPI or whether this effect is consistent across the IPI distribution. We observed that mothers with hypertensive complications had slightly longer

CRediT authorship contribution statement

Amanuel Gebremedhin: Conceptualization, Methodology, Software, Formal analysis and Investigation, Writing – original draft, Visualization. Annette K REGAN: Methodology, Validation, Writing – Review & Editing, Supervision. Siri E HÅBERG: Validation, Writing – Review & Editing. M Luke MARINOVICH: Validation, Writing – Review & Editing, Supervision. Gizachew A Tessema: Validation, Writing – Review & Editing, Resources, Supervision. Gavin Pereira: Methodology, Validation, Writing – Review &

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

The authors would like to thank the Data Linkage Branch (Department of Health WA) as well as the Data Custodians for the MNS and HMDC for providing data for this project.

Disclosure of conflicts of interest

The authors have no potential conflicts of interest to disclose.

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