Preconception sleep, pregnancy loss, and adverse pregnancy outcomes among women with a history of pregnancy loss.

study questionAre preconception sleep characteristics associated with pregnancy loss and adverse pregnancy outcomes? SUMMARY ANSWER: Preconception sleep characteristics were not associated with pregnancy loss, but earlier sleep midpoints were associated with lower risk of adverse pregnancy outcomes, while social jetlag >1 h was associated with greater risk of a composite of adverse pregnancy outcomes. WHAT IS KNOWN ALREADY: Short sleep duration in mid-pregnancy has been associated with risk of second-trimester pregnancy loss, preterm birth (PTB), and hypertensive disorders of pregnancy (HDP). The relationships between preconception sleep and pregnancy loss, and adverse pregnancy outcomes have not been well characterized, despite plausible links. STUDY DESIGN, SIZE, DURATION: This was a secondary analysis of a randomized controlled trial conducted between 2006 and 2012 that prospectively followed 1228 women who were attempting to become pregnant after a history of pregnancy loss. Women were followed for ≤6 cycles while attempting pregnancy, and throughout pregnancy if they conceived. Over the follow-up, 140 women withdrew from the study. PARTICIPANTS/MATERIALS, SETTING,

methodsThis study evaluated baseline, self-reported preconception sleep duration, sleep latency, sleep midpoint, and social jetlag with risk of pregnancy loss and adverse pregnancy outcomes (e.g. PTB, HDP, and gestational diabetes (GDM)) among 1228 women with a history of pregnancy loss in the EAGeR trial. Pregnancy was documented by hCG tests; 797 women became pregnant over the follow-up. Pregnancy losses were defined as any loss after a positive hCG test; there were 188 pregnancy losses. PTB, HDP, and GDM cases were ascertained via medical record abstraction. PTB (n = 53), HDP (n = 62), and GDM (n = 22) were examined as a composite outcome (n = 118) and PTB and HDP were examined individually in exploratory analyses. GDM was not examined individually due to insufficient numbers. Log-Poisson models were used to estimate relative risks (RR) and 95% CIs for associations between preconception sleep characteristics, and pregnancy loss or adverse pregnancy outcomes with adjustment for age, BMI, lifestyle, and sociodemographic factors. Stabilized inverse probability weights were applied to address potential selection bias from loss to follow-up and from restricting to pregnancy. MAIN RESULTS AND THE ROLE OF CHANCE: Preconception sleep characteristics were not associated with risk of pregnancy loss. Preconception sleep duration and sleep latency were not associated with risk of the composite adverse pregnancy outcome. Early preconception sleep midpoints were associated with a lower risk of the composite adverse pregnancy outcome (first vs second tertile RR; 0.63, 95% CI: 0.40, 0.98) and preconception social jetlag was associated with a higher risk of the composite adverse pregnancy outcome (>1 vs ≤1 h RR; 1.65, 95% CI: 1.11, 2.44). LIMITATIONS, REASONS FOR CAUTION: Preconception sleep was restricted to baseline self-report, which may be non-differentially misclassified and may underestimate these associations. The EAGeR study did not measure sleep during pregnancy. There were few adverse pregnancy outcomes and thus limited power to evaluate individual outcomes; the findings could be due to chance. WIDER IMPLICATIONS OF THE

findingsThese findings suggest that preconception sleep is not associated with pregnancy loss, but preconception sleep timing may be relevant for risk of adverse pregnancy outcomes. Additional studies on preconception sleep and adverse pregnancy outcomes are needed given the potential impact of poor sleep on pregnancy outcomes. STUDY FUNDING/COMPETING INTEREST(S): Joshua R. Freeman and this work were supported by the Intramural Research Program Cancer Research Training Award, National Cancer Institute, National Institutes of Health (ZIA CP010197), and the Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland (Contract numbers: HHSN267200603423, HHSN267200603424, HHSN267200603426, HHSN275201300023I). Dr Silver received NIH funding through the listed contracts as site-PI for the original EAGeR trial at the University of Utah. Dr O'Brien reports receiving funding from the Star Legacy Foundation (paid to institution); an advisory board role at the Star Legacy Foundation; and receiving travel support from the Star Legacy Foundation. Dr Dunietz reports a role as Associate Editor at Human Reproduction and a role on the Journal Editorial Board of SLEEP. Dr Purdue-Smithe is an employee of Merck & Co. and has received stock compensation as an employee of Merck & Co. in the past 36 months. The work in this manuscript was completed before Dr Purdue-Smithe's employment at Merck & Co. and is unrelated to Dr Purdue-Smithe's work at the company. Dr Silver reports royalties or licenses from BJOG and UpToDate, Inc. in the past 36 months, receiving payment or honoraria for Grand Rounds in the past 36 months, and participating on a Data Safety Monitoring Board or Advisory Board for a National Institutes of Health-funded Apple Trial in the past 36 months. The other authors report there are no competing interests to declare. TRIAL REGISTRATION NUMBER: Clinicaltrials.gov NCT00467363.