A cross-sectional study of the prevalence and factors associated with symptoms of perinatal depression and anxiety in Rwanda
Bibliographic record
Abstract
BACKGROUND: Perinatal depression and anxiety are increasingly recognized as important public health issues in low and middle-income countries such as Rwanda and may have negative consequences for both mothers and their infants. Maternal mental health may be particularly challenged in Rwanda because of the prevalence of risk factors such as poverty, low education levels, negative life events and marital problems. However, there are limited data about perinatal depression and anxiety symptoms in Rwanda. This study thus aimed to explore the prevalence of symptoms of perinatal depression and anxiety in Rwanda, and factors associated with them. METHODS: A sample of 165 women in the perinatal period (second and third trimester of pregnancy, up to 1 year postnatal) were interviewed individually over 1 month in October 2013. Women were interviewed at 5 of 14 health centres in the Eastern Province or the affiliated district hospital. Participants answered socio-demographic questions and scales measuring symptoms of perinatal depression (EPDS: Edinburgh Postnatal Depression Scale) and anxiety (SAS: Zung Self-rating Anxiety Scale). RESULTS: Among women in the antenatal period (N = 85), 37.6% had symptoms indicating possible depression (EPDS ≥10) and 28.2% had symptoms associated with clinical levels of anxiety (SAS > 45). Among women within the postnatal period (N = 77), 63.6% had symptoms of possible depression, whereas 48,1% had symptoms of probable anxiety. Logistic regression showed that symptoms of postnatal depression were higher for respondents who had four or more living children relative to those having their first child (Odds Ratio: 0.07, C.I. = 0.01-0.42), and for those with a poor relationship with their partner (Odds Ratio: .09, C.I. =0.03-0.25). Any lifetime exposure to stressful events was the only predictor of symptoms of postnatal anxiety (Odds Ratio = 0.20, C.I. = 0.09-0.44). CONCLUSIONS: Symptoms of postnatal depression and anxiety were prevalent in this Rwandan sample and most strongly predicted by interpersonal and social factors, suggesting that social interventions may be a successful strategy to protect against maternal mental health problems in the Rwandan context.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".