Postpartum Depression Among Rural Women From Developed and Developing Countries: A Systematic Review
Bibliographic record
Abstract
PURPOSE: Postpartum depression (PPD) is a significant public health problem, with significant consequences for the mother, infant, and family. Available research has not adequately examined the potential impact of sociodemographic characteristics, such as place of residence, on risk for PPD. Therefore, this systematic review and meta-analysis examines the prevalence of and risk factors for PPD in rural communities within developed and developing countries, and where possible, compares rates to those among urban women. METHODS: Five databases were searched, from start dates through early May 2010, using key words relevant to PPD and rural residence. Peer-reviewed articles were eligible if a standardized assessment of depression was administered to rural mothers within the first year postpartum. Data on PPD were extracted from 19 articles, of which 17 provided data for meta-analyses. FINDINGS: The overall prevalence of PPD among rural women was 27.0% (95% CI, 18.8%-37.2%). Prevalence was somewhat higher among women in developing countries (31.3%; 95% CI, 21.3%-43.5%) than among women in developed countries (21.5%; 95% CI, 10.9%-38.0%), although there was significant heterogeneity among both groups of studies. Comparisons between rural and urban women yielded conflicting results. Although established PPD risk factors were associated with depression in rural women, additional risk factors were reported for rural women from developing countries, such as having 2 or more young children. CONCLUSIONS: Longitudinal studies with clearly defined "rural" and "comparison" groups are needed to determine whether rural residence is associated with increased risk for PPD. The results can inform prevention and treatment programs tailored to serve rural women.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".