Relationship between Social Determinants of Health and Postpartum weight retention in Iran Based on the WHO Model: A Systematic Review
Bibliographic record
Abstract
Introduction: Postpartum weight retention has a significant effect on obesity, chronic disease, and adverse maternal, fetal, and neonatal outcomes. Nowadays, social factors are of the basic causes of health and disease. The present systematic review was conducted with aim to investigate the relationship between social determinants of health and postpartum weight retention in Iranian studies. Methods:In this systematic review, Persian and English observational articles (cohort, case-control, cross-sectional) were searched in databases of PubMed, Google Scholar, Scopus, Embase, Web of Science, SID, Magiran, Irandoc using the different combination of keywords related to “Social determinants of health” And “postpartum weight retention” obtained from Medical Subject Headings (MeSH) from 2000 to 2019. The articles were selected based on the inclusion and exclusion criteria. The quality of selected studies was evaluated using the Newcastle–Ottawa Scale. Results: From 485 reviewed articles, eight studies were selected. Social determinants of health were classified into structural and intermediate groups based on the WHO model. The structural determinants included education, occupation, income, and residence area. Intermediate determinants were classified into three domains of behavioral factors, biological factors, and psychosocial factors based on this model. According to the results of the reviewed studies, a statistically significant relationship was observed between postpartum weight retention with mother's education, exercise, postpartum functional status, exclusive breastfeeding, formula feeding, pre-pregnancy weight, gestational weight gain, parity, mode of delivery, age, depression, and anxiety. Conclusion: The results of the current systematic review illustrated the impact of structural and intermediate social determinants of health- including women's education and factors in behavioral, biological, and psychosocial domains- on postpartum weight retention. This result confirms the need for health authorities and staff to pay more attention to these influencing factors along with other medical factors to help prevent or reduce the extent of this problem and its complications.
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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 | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 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".