Magnitude and level of association between poor sleep quality and common mental disorders among reproductive age women in Ethiopia: systematic review and meta-analysis
Bibliographic record
Abstract
Sleep disturbances are prevalent throughout a woman’s life and significantly affect overall well-being. Research worldwide has established a strong link between poor sleep quality and mental health disorders. However, studies examining this relationship within the Ethiopian context remain scarce. This study aimed to assess the prevalence of sleep quality and its association with common mental health disorders among Ethiopian women of reproductive age. Systematic searches were conducted in PubMed, Google Scholar, CINAHL and African Journals Online and included articles published from inception to February 2025. The quality of eligible studies was assessed using Newcastle-Ottawa Scale (NOS). A DerSimonian-Laird random-effects meta-analysis was used to estimate the pooled effect size of the outcome measures with their 95% CI. Stata version 14.0(StataCorp, College Station, Texas, USA) was used for statistical analysis. A total of 10 studies reported the prevalence of poor sleep quality among women in reproductive age, and the pooled prevalence of poor sleep quality was 54% (95% CI: 0.46–0.63, I2 = 97.14%, p < 0.001). The finding suggests a strong positive association between poor sleep quality and CMDs. The pooled adjusted odds ratio of poor sleep quality and depression is AOR = 2.78 (95% CI: 1.66–3.90, I2 = 37.9%), anxiety AOR = 2.65 (95% CI: 1.84–3.46, I2 = 0.00%), stress AOR = 1.69 (95% CI: 0.83–2.5, I2 = 56.7%). The prevalence of poor sleep quality among women of reproductive age is notably high in Ethiopia. This finding underscores the widespread nature of sleep disturbances in this population, highlighting a critical public health concern. Also the findings highlight a significant association between poor sleep quality and common mental disorders (CMDs). Addressing CMDs as a key factor in poor sleep quality interventions and underscores the need for tailored strategies to improve both sleep and psychological well-being in this vulnerable group. CRD42025643365.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".