Aboriginal and Immigrant Women’s Food Choices and Practices in Pregnancy: A Scoping Review
Bibliographic record
Abstract
Dietary patterns of pregnant women are closely related to cultural values, beliefs, and various social and economic factors. Knowledge of the food choices and practices among pregnant Aboriginal and immigrant women, who both are vulnerable to poor pregnancy and birth outcomes, is essential for midwives and other maternity care providers to provide culturally appropriate care during pregnancy. A “scoping review,” guided by Arksey and O’Malley’s framework, was performed to examine and outline the extent, range, and nature of empirical evidence on immigrant and Aboriginal women’s food practices during pregnancy. Assisted by an information scientist, a systematic search strategy without language or date restrictions was implemented in several electronic databases to identify primary research articles on the subject. Two reviewers independently screened, selected, and charted the data, and team consensus was used for discrepancies. A descriptive analytical framework was followed to depict the existing narrative account of the included studies. Seventeen articles describing seven qualitative and ten quantitative research studies were selected for review, and nine themes were identified. This review will help midwives and other maternity care providers gain an understanding of the importance of culture for Aboriginal and immigrant women’s diets and of existing barriers so that prenatal care can be individually tailored to include nutritional advice and to optimize culturally appropriate care. More individual studies that focus on the cultural aspects of immigrants and Aboriginal pregnant women are needed to improve prenatal care. This article has been peer reviewed.
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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 | 0.012 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.010 | 0.013 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".