Delayed Lactogenesis II is Associated With Lower Sleep Efficiency and Greater Variation in Nightly Sleep Duration in the Third Trimester

Abstract

Background. Metabolic and hormonal disturbances are associated with sleep disturbances and delayed onset of lactogenesis II. Research Aims. The aim of this study was to measure sleep using wrist actigraphy during gestation weeks 22 and 32 to determine if sleep characteristics were associated with blood glucose, body mass index, gestational related disease, delayed onset of lactogenesis II, or work schedule. Methods. Demographic data were collected at study intake from primiparous women who wore a wrist actigraph during gestation weeks 22 (n = SO) and 32 (n = 44). Start and end sleep time, total nighttime sleep, sleep efficiency, wake after sleep onset, and sleep fragmentation were measured. Night to night variability was assessed with the root mean square of successive difference. Blood glucose levels, body mass index, and gestational disease data were abstracted from medical charts. Timing of lactogenesis II was determined by survey. Results. Between gestation week 22 and 32, sleep efficiency decreased and fragmentation increased (p < .05). During gestation week 32, blood glucose was negatively correlated with sleep duration, and positively related to fragmentation (p < .OS). Women who experienced delayed lactogenesis II had lower sleep efficiency and greater fragmentation (p < .05), and greater night-to-night variability in sleep start and end time, efficiency, and duration during gestation week 32 (p < .OS). Conclusion. Women with better sleep efficiency and more stable nightly sleep time are less likely to experience delayed onset of lactogenesis II. Interventions to improve sleep may improve maternal health and breastfeeding adequacy.

Pregnancy rest-activity patterns are related to salivary cortisol rhythms and maternal-fetal health indicators in women from a disadvantaged population

“…Previous studies reported overall activity levels of pregnant women were decreased and onset of activity shifted to an earlier time relative to non-pregnant states [31]. We found no difference in time of waking or start of sleep time between gestational weeks 22 and 32 in this population of women [18], but there was a shift in time of peak of activity to nearly an hour earlier in the third trimester relative to second trimester. Mean activity (mesor) of women in our population also decreased as pregnancy progressed from gestational weeks 22 to 32.…”

“…The remaining were withdrawn by research staff due to lack of compliance to study protocol. There was no difference in demographic variables between recruited, retained and withdrawn populations [18,19].…”

“…Actigraphic data were collected in 30-sec epochs and Actiware software (Version 5.04; Respironics, Inc.) was used to export activity counts into excel files (https:// purr.purdue.edu/publications/3376) for calculation of the autocorrelation coefficient at 24 hr (r24) and cosinor analysis. Actigraphic sleep variables: (1) sleep onset time, (2) end sleep time, (3) total sleep time, (4) sleep efficiency, (5) time in minutes of wakefulness after sleep onset during the night (WASO) and fragmentation index (FragI) were calculated as previously described [18].…”

“…Wilcoxon signed-rank test was used to compare activity and cortisol cosinor analysis variables across the three study timepoints. Because of the limited sample size we were not able to determine the relationship of variables in groups of participants with and without diagnosis of preeclampsia, hypertension, or gestational diabetes (GDM) alone, so despite being etiologically distinct diseases, women were categorized as diagnosed with gestational related disease or not [approximately 1/3 of participants; please see [18] and [19]]. The Mann-Whitney U test was used to determine effect of categorical BMI (r < 25 or >25) or diagnosis of gestational related disease (yes or no for diagnosis of hypertension, preeclampsia and, or GDM during pregnancy) on r24 of activity or rest-activity and saliva cortisol cosine fit calculated variables.…”

“…The mean age of study participants was 23 ± 3.8 years old, with 64% indicating they were Black or African American and of low socioeconomic status. Detailed descriptions of the sample of the population that completed actigraphy [18] and Pittsburgh Sleep Quality Index (PSQI) and Edinburgh Postnatal Depression Scale (EPDS) surveys [19] are available in our previous publications. The demographics of the population that completed the saliva collection arm was similar to the population that completed actigraphy and PSQI survey components of the study (Table 1).…”