Associations between endometriosis and adverse pregnancy and perinatal outcomes: a population-based cohort study.

PURPOSE: To examine the association between endometriosis and adverse pregnancy and perinatal outcomes (preeclampsia, placenta previa, and preterm birth). METHODS: A population-based retrospective cohort study was conducted among 468,778 eligible women who contributed 912,747 singleton livebirths between 1980 and 2015 in Western Australia (WA). We used probabilistically linked perinatal and hospital separation data from the WA data linkage system's Midwives Notification System and Hospital Morbidity Data Collection databases. We used a doubly robust estimator by combining the inverse probability weighting with the outcome regression model to estimate adjusted risk ratios (RR) and 95% confidence intervals (CIs). RESULTS: There were 19,476 singleton livebirths among 8874 women diagnosed with endometriosis. Using a doubly robust estimator, we found pregnancies in women with endometriosis to be associated with an increased risk of preeclampsia with RR of 1.18, 95% CI 1.11-1.26, placenta previa (RR 1.59, 95% CI 1.42-1.79) and preterm birth (RR 1.45, 95% CI 1.37-1.54). The observed association persisted after stratified by the use of Medically Assisted Reproduction, with a slightly elevated risk among pregnancies conceived spontaneously. CONCLUSIONS: In this large population-based cohort, endometriosis is associated with an increased risk of preeclampsia, placenta previa, and preterm birth, independent of the use of Medically Assisted Reproduction. This may help to enhance future obstetric care among this population.

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

PURPOSE: 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 to 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 mo. It was 0.56 mo (95% CI: 0.25-0.88 mo) and 1.12 mo (95% CI: 0.56 - 1.68 mo) 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 IPIs than mothers whose pregnancies were not complicated by these conditions. However, the extent of the delay was small (<2 mo).

Bias in the association between advanced maternal age and stillbirth using left truncated data.

Restriction to analysis of births that survive past a specified gestational age (typically 20 weeks gestation) leads to biased exposure-outcome associations. This bias occurs when the cause of restriction (early pregnancy loss) is influenced by both the exposure and unmeasured factors that also affect the outcome. The aim of this study is to estimate the magnitude of bias resulting from left truncated data in the association between advanced maternal age and stillbirth. We simulated data for the causal pathway under a collider-stratification mechanism. Simulation parameters were based on an observed birth cohort from Western Australia and a range of plausible values for the prevalence of early pregnancy loss, unmeasured factor U and the odds ratios for the selection effects. Selection effects included the effects of maternal age on early pregnancy loss, U on early pregnancy loss, and U on stillbirth. We compared the simulation scenarios to the observed birth cohort that was truncated to pregnancies that survived beyond 20 gestational weeks. We found evidence of marginal downward bias, which was most prominent for women aged 40 + years. Overall, we conclude that the magnitude of bias due to left truncation is minimal in the association between advanced maternal age and stillbirth.

Interpregnancy intervals and adverse birth outcomes in high-income countries: An international cohort study.

BACKGROUND: Most evidence for interpregnancy interval (IPI) and adverse birth outcomes come from studies that are prone to incomplete control for confounders that vary between women. Comparing pregnancies to the same women can address this issue. METHODS: We conducted an international longitudinal cohort study of 5,521,211 births to 3,849,193 women from Australia (1980-2016), Finland (1987-2017), Norway (1980-2016) and the United States (California) (1991-2012). IPI was calculated based on the time difference between two dates-the date of birth of the first pregnancy and the date of conception of the next (index) pregnancy. We estimated associations between IPI and preterm birth (PTB), spontaneous PTB, and small-for-gestational age births (SGA) using logistic regression (between-women analyses). We also used conditional logistic regression comparing IPIs and birth outcomes in the same women (within-women analyses). Random effects meta-analysis was used to calculate pooled adjusted odds ratios (aOR). RESULTS: Compared to an IPI of 18-23 months, there was insufficient evidence for an association between IPI <6 months and overall PTB (aOR 1.08, 95% CI 0.99-1.18) and SGA (aOR 0.99, 95% CI 0.81-1.19), but increased odds of spontaneous PTB (aOR 1.38, 95% CI 1.21-1.57) in the within-women analysis. We observed elevated odds of all birth outcomes associated with IPI ≥60 months. In comparison, between-women analyses showed elevated odds of adverse birth outcomes for <12 month and >24 month IPIs. CONCLUSIONS: We found consistently elevated odds of adverse birth outcomes following long IPIs. IPI shorter than 6 months were associated with elevated risk of spontaneous PTB, but there was insufficient evidence for increased risk of other adverse birth outcomes. Current recommendations of waiting at least 24 months to conceive after a previous pregnancy, may be unnecessarily long in high-income countries.

Association between interpregnancy interval and hypertensive disorders of pregnancy: Effect modification by maternal age.

BACKGROUND: Short and long interpregnancy intervals (IPI) are associated with increased risk of hypertensive disorders of pregnancy, yet whether this association is modified by maternal age remains unclear. OBJECTIVES: To examine if the association between IPI and hypertensive disorders of pregnancy varies by maternal age at birth prior to IPI. METHODS: We conducted a population-based cohort study of all mothers who had their first two (n = 169 896) consecutive births in Western Australia (WA) between 1980 and 2015. We estimated the risk of preeclampsia and gestational hypertension for 6 to 60 months of IPI according to maternal age at birth prior to IPI (<20 years, 20-24, 25-29, 30-34 and ≥35 years). We modelled IPI using restricted cubic splines and reported adjusted relative risk (RRs) with 95% CI at 6, 12, 24, 36, 48 and 60 months, with 18 months as reference. RESULTS: The risk of preeclampsia was increased at longer IPIs (60 months) compared to 18 months for mothers 35 years or older (RR 2.19, 95% confidence interval (CI) 1.14, 4.18) and to a lesser extent for mothers 30- to 34 years old (RR 1.43, 95% CI 1.10, 1.84). Compared to 18 months, the risk of preeclampsia was lower at 12 months of IPI for mothers younger than 20 years (RR 0.74, 95% CI 0.57, 0.96), but not for mothers 35 years or older (RR 0.62, 95% CI 0.36, 1.07). There was insufficient evidence for increased risk of hypertensive disorders of pregnancy at shorter IPIs of <18 months for mothers of all ages. CONCLUSIONS: Our findings challenge the "one size fits all" recommendation for an optimal IPI, and a more tailored approach to family planning counselling may be required to improve health.

Interpregnancy interval and hypertensive disorders of pregnancy: A population-based cohort study.

BACKGROUND: Despite extensive research on risk factors and mechanisms, the extent to which interpregnancy interval (IPI) affects hypertensive disorders of pregnancy in high-income countries remains unclear. OBJECTIVES: To examine the association between IPI and hypertensive disorders of pregnancy in a high-income country setting using both within-mother and between-mother comparisons. METHODS: A retrospective population-based cohort study was conducted among 103 909 women who delivered three or more consecutive singleton births (n = 358 046) between 1980 and 2015 in Western Australia. We used conditional Poisson regression with robust variance, matching intervals of the same mother and adjusted for factors that vary within-mother across pregnancies, to investigate the association between IPI categories (reference 18-23 months), and the risk of hypertensive disorders of pregnancy. For comparison with previous studies, we also applied unmatched Poisson regression (between-mother analysis). RESULTS: The incidence of preeclampsia and gestational hypertension during the study period was 4%, and 2%, respectively. For the between-mother comparison, mothers with intervals of 6-11 months had lower risk of preeclampsia with adjusted relative risk (RR) 0.92 (95% confidence interval [CI] 0.85, 0.98) compared to reference category of 18-23 months. With the within-mother matched design, we estimated a larger effect of long IPI on risk of preeclampsia (RR 1.29, 95% CI 1.18, 1.42 for 60-119 months; and RR 1.30, 95% CI 1.10, 1.53 for intervals ≥120 months) compared to 18-23 months. Short IPIs were not associated with hypertensive disorders of pregnancy. CONCLUSIONS: In our cohort, longer IPIs were associated with increased risk of preeclampsia. However, there was insufficient evidence to suggest that short IPIs (<6 months) increase the risks of hypertensive disorders of pregnancy.

Stillbirth risk prediction using machine learning for a large cohort of births from Western Australia, 1980-2015.

Quantification of stillbirth risk has potential to support clinical decision-making. Studies that have attempted to quantify stillbirth risk have been hampered by small event rates, a limited range of predictors that typically exclude obstetric history, lack of validation, and restriction to a single classifier (logistic regression). Consequently, predictive performance remains low, and risk quantification has not been adopted into antenatal practice. The study population consisted of all births to women in Western Australia from 1980 to 2015, excluding terminations. After all exclusions there were 947,025 livebirths and 5,788 stillbirths. Predictive models for stillbirth were developed using multiple machine learning classifiers: regularised logistic regression, decision trees based on classification and regression trees, random forest, extreme gradient boosting (XGBoost), and a multilayer perceptron neural network. We applied 10-fold cross-validation using independent data not used to develop the models. Predictors included maternal socio-demographic characteristics, chronic medical conditions, obstetric complications and family history in both the current and previous pregnancy. In this cohort, 66% of stillbirths were observed for multiparous women. The best performing classifier (XGBoost) predicted 45% (95% CI: 43%, 46%) of stillbirths for all women and 45% (95% CI: 43%, 47%) of stillbirths after the inclusion of previous pregnancy history. Almost half of stillbirths could be potentially identified antenatally based on a combination of current pregnancy complications, congenital anomalies, maternal characteristics, and medical history. Greatest sensitivity is achieved with addition of current pregnancy complications. Ensemble classifiers offered marginal improvement for prediction compared to logistic regression.

Effect of interpregnancy interval on gestational diabetes: a retrospective matched cohort study.

PURPOSE: To examine the association between interpregnancy interval (IPI) and gestational diabetes using both within-mother and between-mother comparisons. METHODS: A retrospective cohort study of 103,909 women who delivered three or more consecutive singleton births (n = 358,046) between 1 January 1980 and 31 December 2015 in Western Australia. The association between IPI and gestational diabetes was estimated using conditional logistic regression, matching pregnancies to the same mother and adjusted for factors that vary within-mother across pregnancies. For comparison with previous studies, we also applied unmatched logistic regression (between-mother analysis). RESULTS: The conventional between-mother analysis resulted in adjusted odds ratios (aOR) of 1.13 (95% CI, 1.06-1.21) for intervals of 24-59 months and 1.51 (95% CI, 1.33-1.70) for intervals of 120 or more months, compared with IPI of 18-23 months. In addition, short IPIs were associated with lower odds of gestational diabetes with (aOR: 0.89; 95% CI, 0.82-0.97) for 6-11 months and (aOR: 0.92; 95% CI, 0.85-0.99) for 12-17-month. In comparison, the adjusted within-mother matched analyses showed no statistically significant association between IPIs and gestational diabetes. All effect estimates were attenuated using the within-mother matched model. CONCLUSION: Our findings do not support the hypothesis that short IPI (<6 months) increases the risk of gestational diabetes and suggest that observed associations in previous research might be attributable to confounders that vary between mothers.

Developing evidence-based recommendations for optimal interpregnancy intervals in high-income countries: protocol for an international cohort study.

INTRODUCTION: Short interpregnancy interval (IPI) has been linked to adverse pregnancy outcomes. WHO recommends waiting at least 2 years after a live birth and 6 months after miscarriage or induced termination before conception of another pregnancy. The evidence underpinning these recommendations largely relies on data from low/middle-income countries. Furthermore, recent epidemiological investigations have suggested that these studies may overestimate the effects of IPI due to residual confounding. Future investigations of IPI effects in high-income countries drawing from large, population-based data sources are needed to inform IPI recommendations. We aim to assess the impact of IPIs on maternal and child health outcomes in high-income countries. METHODS AND ANALYSIS: This international longitudinal retrospective cohort study will include more than 18 million pregnancies, making it the largest study to investigate IPI in high-income countries. Population-based data from Australia, Finland, Norway and USA will be used. Birth records in each country will be used to identify consecutive pregnancies. Exact dates of birth and clinical best estimates of gestational length will be used to estimate IPI. Administrative birth and health data sources with >99% coverage in each country will be used to identify maternal sociodemographics, pregnancy complications, details of labour and delivery, birth and child health information. We will use matched and unmatched regression models to investigate the impact of IPI on maternal and infant outcomes, and conduct meta-analysis to pool results across countries. ETHICS AND DISSEMINATION: Ethics boards at participating sites approved this research (approval was not required in Finland). Findings will be published in peer-reviewed journals and presented at international conferences, and will inform recommendations for optimal IPI in high-income countries. Findings will provide important information for women and families planning future pregnancies and for clinicians providing prenatal care and giving guidance on family planning.