Epidemiology of postnatal depression and its associated factors in Africa: A systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Postnatal depression (PND) is a major cause of negative health-related behaviors and outcomes during infancy, childhood and adolescent period. In Africa, the burden of postnatal depression is high. However, it is under-investigated hence under-treated. To fill this information gap and to advise further interventions, we aimed at analyzing its epidemiology in Africa. METHODS: We searched observational studies conducted in Africa and published in between 01/01/2007 and 30/06/2018 in CINHAL, MEDLINE, PsycINFO, Psychiatry online, PubMed, SCOPES, and Emcare databases. We assessed the quality of the studies using the Newcastle Ottawa Scale (NOS) and included studies with good quality. We evaluated the heterogeneity using the Higgins I2 statistics. We used a random-effects model to pool estimates. We assessed publication bias using the funnel plot and Egger's test statistics and adjusted using Tweedie's and Duval Trim and Fill analysis. The protocol has been registered in the PROSPERO (Protocol No. CRD42018100461). RESULTS: Nineteen studies involving 40,953 postnatal mothers were part of this systematic review and meta-analysis. The overall pooled prevalence of PND was 16.84% (95% CI: 14.49% -19.19%). The odds of having PND was higher among women with a poor obstetric condition (POR = 2.11; 95% CI: 1.11-4.01) and history of adverse birth and infant health outcomes (POR = 2.85; 95% CI: 1.29-6.25). Having a history of common mental health disorders (POR = 2.47; 95% CI: 1.51-4.04), poor social support (POR = 2.06; 95% CI: 1.05-4.05), lower economic status (POR = 2.38; 95% CI: 1.75-3.23), and those who had exposure to a different form of intimate partner violence (POR = 2.87; 95% CI: 1.60-5.16) had higher odds of PND. CONCLUSION: While robust prevalence studies are scarce, our review indicated a high prevalence rate of postnatal depression. The analysis also identified postpartum women at increased risk of PND. Therefore, there is a need to design and escalate comprehensive strategies to decrease its burden, focusing on those women at risk of PND.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.036 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".