Sleep quality and associated factors among pregnant women attending antenatal care at Jimma Medical Center, Jimma, Southwest Ethiopia, 2020: cross-sectional study.
Volume: 21
Issue: 1
Year of Publication: 2021
Abstract summary
Sleep is a natural physiological process vital for the physical and mental wellbeing of pregnant women and their fetuses. Even though poor sleep quality is a common problem among pregnant women, it is not studied in developing countries including Ethiopia. Therefore, this study was aimed to assess the poor sleep quality and associated factors among pregnant women attending antenatal care at Jimma medical center, Jimma, Southwest Ethiopia, 2020.A cross-sectional study design was conducted among 415 pregnant women at Jimma Medical Center (JMC). The study subjects were selected using a systematic random sampling technique. Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality using face-to-face interviews. SPSS version 25 was used to analyze data. Bivariate and multivariable logistic regressions were done to identify factors related to sleep quality. In multivariable logistic regression variables with a p-value less than 0.05 was considered significant and, adjusted OR (AOR) with 95% CI was used to present the strength of the association.The prevalence of poor sleep quality among pregnant women was found to be 30.8% (95% CI (26.5, 35.2). In multivariable analysis, age ≥ 30 years old (AOR = 1.94;95%CI:1.03,3.66), Multigravida (AOR = 1.90;95%CI:1.90,3.32),depression (AOR = 4.26;95%CI:2.54,7.14),stress (AOR = 1.85;95%CI:1.20,3.02) were variables significantly associated with poor sleep quality.This study found a high prevalence of poor sleep quality among pregnant women. Older age, gravidity, depression, and stress were associated with poor sleep quality. It is better to have routine sleep pattern screening and teach sleep hygiene practice for pregnant women.Study Outcome
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Statistics
Citations : Benjamins JS, Migliorati F, Dekker K, Wassing R, Moens S, Blanken TF, te Lindert BHW, Sjauw Mook J, van Someren EJW. Insomnia heterogeneity: characteristics to consider for data-driven multivariate subtyping. Sleep Med Rev. 2017;36:71–81. doi: 10.1016/j.smrv.2016.10.005.Authors : 5
Identifiers
Doi : 469SSN : 1471-244X