Perinatal depression (PND) is a severe complication of pregnancy, but there are no established risk factors predicting the disease. Evening chronotype has been associated with unhealthy lifestyle ...habits and adverse outcomes during pregnancy. In this study, we aimed to clarify whether chronotype can predict symptoms and/or occurrence of PND.
Two hundred ninety-nine women were followed-up from the first trimester of pregnancy until 6 months postpartum. Chronotype was assessed at baseline using the MEQ, while mood was repeatedly assessed by depression rating scales (EPDS, HDRS, MADRS). The influence of time and chronotype on EPDS, HDRS and MADRS, was estimated by constructing multilevel linear mixed regression models. A Cox proportional-hazard regression model was built to evaluate the association between chronotype and incidence of depression.
Chronotype modulated PND symptom severity depending on time of assessment, with evening chronotypes having a higher risk for developing PND symptoms, as assessed by EPDS, at postpartum visits V4 (5–12 days) and V5 (19–26 days). These also had less healthy lifestyle habits and were more likely to suffer from gestational diabetes mellitus and undergo cesarean delivery as compared to other chronotypes.
Only a minority of women were classified as evening chronotypes. The long follow-up phase of the study led to missing data.
Pregnant evening chronotypes show unhealthy lifestyle habits and sociodemographic characteristics commonly associated with a higher risk for PND. They also have a higher risk of developing PND symptoms in the first month after delivery. Chronotype should therefore be routinely assessed during pregnancy to identify women potentially at risk for developing PND.
•Prevention of perinatal depression (PND) is a priority for public mental health.•No established risk factors can predict which women are at risk to develop PND.•Evening chronotypes have more severe PND symptoms in the first month postpartum.•They also have less healthy lifestyle habits and more adverse pregnancy outcomes.•Chronotype should be routinely assessed during pregnancy to help PND prevention.
•Perinatal depression (PND) is a highly prevalent complication of pregnancy.•It is difficult to predict which women will experience depression during the peripartum.•Machine learning techniques may ...help identifying predictors of PND during early pregnancy.•We developed a data-driven ML model to quantify the risk of developing PND symptoms.•Besides psychosocial factors, sleep alterations were found to be a strong predictor of PND.
Perinatal depression (PND) is a common complication of pregnancy associated with serious health consequences for both mothers and their babies. Identifying risk factors for PND is key to early detect women at increased risk of developing this condition. We applied a machine learning (ML) approach to data from a multicenter cohort study on sleep and mood changes during the perinatal period (“Life-ON”) to derive models for PND risk prediction in a cross-validation setting. A wide range of sociodemographic variables, blood-based biomarkers, sleep, medical, and psychological data collected from 439 pregnant women, as well as polysomnographic parameters recorded from 353 women, were considered for model building. These covariates were correlated with the risk of future depression, as assessed by regularly administering the Edinburgh Postnatal Depression Scale across the perinatal period. The ML model indicated the mood status of pregnant women in the first trimester, previous depressive episodes and marital status, as the most important predictors of PND. Sleep quality, insomnia symptoms, age, previous miscarriages, and stressful life events also added to the model performance. Besides other predictors, sleep changes during early pregnancy should therefore assessed to identify women at higher risk of PND and support them with appropriate therapeutic strategies.
This study aimed to assess the concordance of various psychometric scales in detecting Perinatal Depression (PND) risk and diagnosis. A cohort of 432 women was assessed at 10-15th and 23-25th ...gestational weeks, 33-40 days and 180-195 days after delivery using the Edinburgh Postnatal Depression Scale (EPDS), Visual Analogue Scale (VAS), Hamilton Depression Rating Scale (HDRS), Montgomery-Åsberg Depression Rating Scale (MADRS), and Mini International Neuropsychiatric Interview (MINI). Spearman's rank correlation coefficient was used to assess agreement across instruments, and multivariable classification models were developed to predict the values of a binary scale using the other scales. Moderate agreement was shown between the EPDS and VAS and between the HDRS and MADRS throughout the perinatal period. However, agreement between the EPDS and HDRS decreased postpartum. A well-performing model for the estimation of current depression risk (EPDS > 9) was obtained with the VAS and MADRS, and a less robust one for the estimation of current major depressive episode (MDE) diagnosis (MINI) with the VAS and HDRS. When the EPDS is not feasible, the VAS may be used for rapid and comprehensive postpartum screening with reliability. However, a thorough structured interview or clinical examination remains necessary to diagnose a MDE.
to prospectively assess sleep and sleep disorders during pregnancy and postpartum in a large cohort of women.
multicenter prospective Life-ON study, recruiting consecutive pregnant women at a ...gestational age between 10 and 15 weeks, from the local gynecological departments. The study included home polysomnography performed between the 23rd and 25th week of pregnancy and sleep-related questionnaires at 9 points in time during pregnancy and 6 months postpartum.
439 pregnant women (mean age 33.7 ± 4.2 yrs) were enrolled. Poor quality of sleep was reported by 34% of women in the first trimester of pregnancy, by 46% of women in the third trimester, and by as many as 71% of women in the first month after delivery. A similar trend was seen for insomnia. Excessive daytime sleepiness peaked in the first trimester (30% of women), and decreased in the third trimester, to 22% of women. Prevalence of restless legs syndrome was 25%, with a peak in the third trimester of pregnancy. Polysomnographic data, available for 353 women, revealed that 24% of women slept less than 6 h, and 30.6% of women had a sleep efficiency below 80%. Sleep-disordered breathing (RDI≥5) had a prevalence of 4.2% and correlated positively with BMI.
The Life-ON study provides the largest polysomnographic dataset coupled with longitudinal subjective assessments of sleep quality in pregnant women to date. Sleep disorders are highly frequent and distributed differently during pregnancy and postpartum. Routine assessment of sleep disturbances in the perinatal period is necessary to improve early detection and clinical management.
•Sleep disorders are very frequent during pregnancy and puerperium.•Sleepiness peaks in the first trimester of pregnancy.•Insomnia and low sleep quality peak in the immediate post-partum period.•Multiparity is a risk factor for insomnia and low quality of sleep.•25% of women reported restless legs syndrome during pregnancy.
