Objectively measured short sleep duration and later sleep midpoint in pregnancy are associated with a higher risk of gestational diabetes Francesca L.

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Objectively measured short sleep duration and later sleep midpoint in pregnancy are associated with a higher risk of gestational diabetes Francesca L. Facco MD., MSCI.1, William A. Grobman, MD, MBA.2, Kathryn J. Reid, PhD.3, Corette B. Parker, DrPH.4, Shannon M. Hunter, MS.4, Robert M. Silver, MD.5, Robert C. Basner, MD.6 , George R. Saade, MD.7, Grace W. Pien, MD, MSCE.8 , Shalini Manchanda, MD.9, Judette M. Louis, MD., PhD.10, Chia-Ling, Nhan-Chang, MD.11 , Judith H. Chung, MD, PhD.12 , Deborah A. Wing, MD, MBA.12,13, Hyagriv N. Simhan, MD.1, David M. Haas, MD, MS.14, Jay Iams, MD.15, Samuel Parry, MD.16, Phyllis C. Zee, MD., PhD.3 1. Department of Obstetrics and Gynecology, Magee-Womens Research Institute & Foundation, University of Pittsburgh School of Medicine, Pittsburgh, PA 2. Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Northwestern University Feinberg School of Medicine, Chicago, IL 3. Department of Neurology and Center for Circadian and Sleep Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 4. RTI International, Research Triangle Park, NC 5. Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Utah Health Sciences Center, Salt Lake City, UT 6. Department of Clinical Medicine, College of Physicians and Surgeons, Columbia University, New York, NY 7. Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Texas Medical Branch, Galveston, TX 8. Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 9. Department of Medicine, Section of Pulmonary, Critical Care, Sleep and Occupational Medicine, Indiana University School of Medicine, Indianapolis, IN 10. Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Case Western Reserve University School of Medicine, Cleveland, OH 11. Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, College of Physicians and Surgeons, Columbia University, New York, NY 12. Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of California, Irvine, School of Medicine, Irvine, CA 13. Miller Childrens Hospital/Long Beach Memorial Center, Long Beach, CA 14. Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Indiana University School of Medicine, Indianapolis, IN 15. Department of Obstetrics and Gynecology, Ohio State University, Columbus, OH 16. Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Pennsylvania School of Medicine, Philadelphia, PA Facco FL, Grobman WA, Reid KJ et al. AJOG 2017

Background Experimental and epidemiologic data suggest that among non-pregnant adults, sleep duration may be an important risk factor for chronic disease Although pregnant women commonly complain of poor sleep, few studies have objectively evaluated the quality of sleep in pregnancy or have explored the relationship between sleep disturbances and maternal and perinatal outcomes Facco FL, Grobman WA, Reid KJ et al. AJOG 2017

Objective To examine the relationship between objectively assessed sleep duration, timing and continuity (measured via wrist actigraphy) and maternal cardiovascular and metabolic morbidity specific to pregnancy Facco FL, Grobman WA, Reid KJ et al. AJOG 2017

Methods The Sleep Duration and Continuity Study was conducted as a sub-study of the Nulliparous Pregnancy Outcome Study: Monitoring Mothers-to-be (nuMoM2b) NuMoM2b was an observational cohort study, conducted at 8 clinical sites and managed by a central data coordinating and analysis center The parent study protocol included nulliparous women of at least 13 years of age, although for this sub-study, those under the age of 18 were excluded given significant differences in adolescent versus adult sleep Women with chronic hypertension and pre-existing diabetes were also excluded Facco FL, Grobman WA, Reid KJ et al. AJOG 2017

Methods Subjects were recruited at the 2nd study visit (16- 21 weeks’) to wear an actigraph to record objective sleep activity for 7 consecutive days An actigraphy recording was considered successful if there was a minimum of 5 days recorded and if within the five days there was less than 4 hours of off-wrist time per 24-hour period and no off-wrist signal during the time the subject indicated she was in bed Central sleep reading center Facco FL, Grobman WA, Reid KJ et al. AJOG 2017

Actigraphy provides an objective measure of rest-activity patterns from which various measures of sleep duration, quality and timing can be determined daily Actiwatch (Philips Respironics) Facco FL, Grobman WA, Reid KJ et al. AJOG 2017

Sleep variable description/definitions Variable name Sleep variable description/definitions Sleep duration (hours)   Sleep duration was defined as the total amount of time scored as sleep during the main designated rest period each day. The sleep duration for each available day (5-7 days) were then averaged. The cut off of an average sleep duration of < 7 hours was chosen based on prior data in pregnant women from the authors and on recommendations for adequate sleep duration recently published by the American Academy of Sleep Medicine. Sleep midpoint (hh:mm) Sleep midpoint is the clock time that represents the midpoint between the clock time of sleep onset and the clock time of sleep offset. The sleep midpoint was calculated for each valid day then averaged for each available day (5-7 days). The cut off of an average sleep midpoint later than 5am was chosen a priori based on large samples of population based self-reported data. Wake after sleep onset (minutes) Wake after sleep onset (WASO) is the total amount of minutes spent awake between sleep onset and the end of the rest interval. The minutes of WASO were calculated for each valid day then averaged for each available day (5-7 days). Given that there are no well-established actigraphy based cutoffs for WASO, the data were divided into quartiles and those with an average WASO ≥ 75th percentile were considered to have poor sleep. Sleep fragmentation (%) The sleep fragmentation index (FI) is calculated as the proportion of all epochs from sleep onset to sleep offset with an activity count of 2 or greater plus the proportion of all bouts of immobility (activity count less than 2 in every epoch) that were 1 minute or less in duration. The FI was determined for each valid day then averaged for each available day (5-7 days). Given that there are no well-established actigraphy based cutoffs for FI, the data were divided into quartiles and those with an average FI ≥ 75th percentile were considered to have poor sleep. Facco FL, Grobman WA, Reid KJ et al. AJOG 2017

Primary outcomes Composite of hypertensive disorders of pregnancy mild, severe, or superimposed preeclampsia eclampsia antepartum gestational hypertension Gestational diabetes (GDM) Facco FL, Grobman WA, Reid KJ et al. AJOG 2017

Statistical Considerations Chi-square tests were used to assess associations between sleep variables and categorical baseline characteristics Crude odds ratios and 95% confidence intervals were estimated from univariate logistic regression models to characterize the magnitude of the relationship between sleep characteristics and hypertensive disorders of pregnancy and GDM For associations that were significant in univariate analysis, multiple logistic regression was used to explore further the association of sleep characteristics with pregnancy outcomes Facco FL, Grobman WA, Reid KJ et al. AJOG 2017

RESULTS Facco FL, Grobman WA, Reid KJ et al. AJOG 2017

Results 901 eligible women consented to participate. 782 submitted valid actigraphy studies The median gestational age at recruitment was 19 1/7 weeks range 15 6/7 – 22 5/7 weeks of gestation The rate of hypertensive disorders was 11.6% preeclampsia 4.9% (38/782) antepartum gestational hypertension 6.8% (53/782) The rate of gestational diabetes was 4.2%. majority of women (n= 699, 94.3%) completed their GTT more than 1 week after the actigraphy study Facco FL, Grobman WA, Reid KJ et al. AJOG 2017

Results Sleep duration of < 7 hours was present in 27.9% of the participants Only 3.5% and 2.6% of women had sleep durations of < 6 hours or ≥ 9 hours, respectively 18.9% of women had a sleep midpoint later than 5 AM Facco FL, Grobman WA, Reid KJ et al. AJOG 2017

Results A detailed table of participant characteristics stratified by different sleep metrics is presented in the paper Of note, we found that women who worked regular day shifts had significantly earlier sleep midpoints compared to women who reported working some form of shift work or who were unemployed

Results Short sleep duration (< 7 hours) and a later sleep midpoint (≥ 5 AM) were associated with an increased risk of GDM Short sleep (< 7 HR): OR 2.24, 95% CI 1.11, 4.53 Late Midpoint (≥ 5 AM): OR 2.58, 95% CI 1.24, 5.36 Short sleep and sleep midpoint were not associated with hypertensive disorders Facco FL, Grobman WA, Reid KJ et al. AJOG 2017

Facco FL, Grobman WA, Reid KJ et al. AJOG 2017

Facco FL, Grobman WA, Reid KJ et al. AJOG 2017 On this slide are data from this same cohort we presented last year at SMFM and are preparing for publication We found that women with SD < 7 hours had twice the rate of GDM compared to those who sleep on average >= 7 hours. This association remained significant even after adjusting for age and BMI. This finding is congruous with GWG data presented today where short sleepers from this cohort were also those who were more likely to have greater weigh gains, thus putting them at higher risk for GDM. Facco FL, Grobman WA, Reid KJ et al. AJOG 2017

Results A model with both sleep duration and sleep midpoint as well as their interaction term revealed that while there was no significant interaction between these exposures, the main effects of both short sleep duration and later sleep midpoint with GDM remained significant (aOR 2.06, 95% CI 1.01, 4.19; aOR 2.37, 95% CI 1.13, 4.97, respectively) Additionally, after adjusting separately for age, BMI and race/ethnicity and work schedule , both short sleep duration and later sleep midpoint remained associated with GDM Facco FL, Grobman WA, Reid KJ et al. AJOG 2017

Results No associations were demonstrated between the sleep quality measures (WASO, sleep fragmentation) and hypertensive disorders or GDM Facco FL, Grobman WA, Reid KJ et al. AJOG 2017

Summary Our data demonstrate that, among nulliparous women, both sleep duration and timing of sleep in the second trimester are associated with the development of GDM We did not detect any relationship between measures of sleep duration, timing or sleep quality and hypertensive disorders of pregnancy Facco FL, Grobman WA, Reid KJ et al. AJOG 2017

Strengths Use of actigraphy to obtain a weeklong objective recording of rest/activity Central and blinded actigraphy reading center Facco FL, Grobman WA, Reid KJ et al. AJOG 2017

Limitations Onetime assessment of sleep in pregnancy Given the observational design, there is always the possibility of residual confounding from unmeasured variables or a limit in the extent to which even measured confounders can be assessed Facco FL, Grobman WA, Reid KJ et al. AJOG 2017

Conclusion We found a relationship between short sleep duration and later sleep timing with GDM in nulliparous women Although this is an observational study, it is biologically plausible that the relationship may be causal The mechanisms by which sleep duration and timing may impact metabolism in pregnancy are likely multifactorial and further research is needed to better understand the biology of sleep in pregnancy and whether interventions in early pregnancy to address sleep duration and schedule can modify the risk of GDM Facco FL, Grobman WA, Reid KJ et al. AJOG 2017

SPECIAL THANKS TO OUR RESEARCH COORDINATORS Acknowledgements Case Western Reserve University / Ohio State University - Jay Iams, MD, Wendy Dalton, RN, Cheryl Latimer, RN, LuAnn Polito, RN, JD,; Columbia University / Christiana Care - Ronald Wapner, MD, Matthew K. Hoffman, MD, MPH, , Karin Fuchs, MD, Caroline Torres, MD, Stephanie Lynch, RN, BSN, CCRC, Ameneh Onativia, MD, Michelle DiVito, MSN, CCRC ; Indiana University - Tatiana Foroud, PhD, Emily Perkins, BS, MA, CCRP, Shannon Barnes, RN, MSN, Alicia Winters, BS, Catherine L. McCormick, RN, F ; University of Pittsburgh - H Steve N. Caritis, MD, Melissa Bickus, R.N., B.S., Paul D. Speer, MD, Stephen P. Emery, MD, Ashi R. Daftary, MD,; Northwestern University - Alan M. Peaceman, MD, Peggy Campbell, RN, BSN, CCRC, Jessica S. Shepard, MPH , Crystal N. Williams, BA; University of California at Irvine - Pathikd D. Wadhwa, MD, PhD, Michael P. Nageotte, MD, Pamela J. Rumney, RNC, CCRC, Manuel Porto, MD, Valerie Pham, RDMS; University of Pennsylvania - Jack Ludmir, MD, Michal Elovitz, MD, Mary Peters, BA, MPH, Brittany Araujo,BS,; University of Utah - M. Sean Esplin, MD, Kelly Vorwaller, RN, Julie Postma, RN, Valerie Morby, RN, Melanie Williams, RN, Linda Meadows, RN; RTI International - Deborah W. McFadden, MBA, Barbara V. Alexander, MSPH, Venkat Yetukuri, MS, Tommy E. Holder, Jr, BS, Holly L. Franklin, MPH, Martha J. DeCain, BS, Christopher Griggs, BS; Harvard University, Brigham and Women’s Hospital- Susan Surovec, BA, Julianne Ulanski, BS; National Heart Lung and Blood Institute-Aaron Laposky, PhD; Eunice Kennedy Shriver National Institute of Child Health and Human Development - Marian Willinger, PhD, Maurice Davis, DHA, MPA, MHSA SPECIAL THANKS TO OUR RESEARCH COORDINATORS Facco FL, Grobman WA, Reid KJ et al. AJOG 2017

Funding NIH/NHLBI-R01HL105549 This study is supported by grant funding from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) and the National Heart Lung and Blood Institute: U10 HD063036, Research Triangle Institute; U10 HD063072, Case Western Reserve University; U10 HD063047, Columbia University; U10 HD063037, Indiana University; U10 HD063041, Magee-Women's Hospital; U10 HD063020, Northwestern University; U10 HD063046, University of California Irvine; U10 HD063048, University of Pennsylvania; and U10 HD063053, University of Utah Facco FL, Grobman WA, Reid KJ et al. AJOG 2017