The relationship between depression, stress, anxiety, and postpartum weight retention: A systematic review
Bibliographic record
Abstract
Postpartum weight retention (PPWR) is a factor that causes permanent obesity and subsequent chronic and noncommunicable diseases. The relationship between depression/stress/anxiety and PPWR has been studied in some articles, but there is no definitive conclusion in this regard. The present systematic review was conducted to investigate the relationship between depression/stress/anxiety and PPWR. An extensive search was performed in the PubMed, Scopus, Embase, Web of Science, Google Scholar, SID, and Magiran, Irandoc databases using Medical Subject Headings terms (or their Persian synonyms) from 2000 to 2020. Inclusion and exclusion criteria were used for articles selection. The quality of the selected articles was assessed using the Newcastle-Ottawa Scale. Out of 371 reviewed articles, 24 articles were selected. The total sample size was 51,613 (range: 49-37,127). The mean of PPWR ranged from 0.5 kg (standard deviation [SD] = 6.49) to 6.4 kg (SD = 8.5). There was a statistically significant relationship between depression/stress/anxiety and PPWR in 12 of 23, 4 of 6, and 3 of 8 studies. This review demonstrates the relationship between depression/stress/anxiety and PPWR. Time of depression/stress/anxiety assessment is an important issue, as well as different measurement tools. Prevention of the mothers' psychological problems through educational and supportive programs may help to limit PPWR.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".