Link between insomnia and perinatal depressive symptoms: A meta-analysis.
Farnoosh EmamianHabibolah KhazaieMichele L OkunMasoud TahmasianAmir Ali SepehryPublished in: Journal of sleep research (2019)
Evidence shows the possible link between insomnia and perinatal depressive symptoms. In order to find a convergent quantitative answer, we collected data via the search of Medline, EMBASE and reference tracking, which included nine studies (a total sample of 1,922 women). An aggregate effect size estimate (correlation coefficient) was generated using the comprehensive meta-analysis software. For the meta-analytic procedure, a random effects model was set a priori. Moderating factors, including study design, method of assessment of depression, geographical origin of data, publication year, mean age, % married, breastfeeding rate, quality and type of data, % primiparous and history of depression, were examined via categorical or univariate mixed-effects (method of moments) meta-regression methods. Heterogeneity and publication bias were examined using standard meta-analytic approaches. We found a significant, medium-size relationship between insomnia and perinatal depressive symptoms (point estimate, 0.366; 95% confidence interval [CI], 0.205-0.508; p < 0.001; n = 9) and this was significantly heterogeneous (Q, 118.77; df, 8; p < 0.001; I2 , 93.26%). The effect size estimate was significant for studies reporting no history of depression (point estimate, 0.364; 95% CI, 0.035-0.622; p < 0.05; n = 5) and for study design. With meta-regression, no moderating factor (age, marriage rate, breastfeeding rate, pregnancy history or publication year) significantly mediated the effect size estimate. The depression assessment scale used, but not other categorical variables, explained the magnitude of heterogeneity. We found that insomnia during the perinatal period is associated with depressive symptoms, which warrants screening pregnant mothers for insomnia and depression.
Keyphrases
- depressive symptoms
- sleep quality
- social support
- pregnant women
- systematic review
- preterm infants
- big data
- case control
- single cell
- data analysis
- magnetic resonance imaging
- type diabetes
- mass spectrometry
- polycystic ovary syndrome
- preterm birth
- quality improvement
- adverse drug
- deep learning
- diffusion weighted imaging
- clinical evaluation
- drug induced