Probiotics in pregnancy: Inequities in knowledge exchange, attitudes, and use of probiotics in a socio-demographically diverse, cross-sectional survey sample of pregnant Canadians
Bibliographic record
Abstract
Pregnancy interventions, potentially including consumption of nutraceuticals like probiotics, represent possible avenues for preventing non-communicable diseases. However, evidence syntheses indicate that probiotic interventions, while effective in managing some pregnancy complications (e.g., gestational diabetes), do not confer health benefits to uncomplicated pregnancies. Messaging around probiotics in pregnancy is mixed, such that people with low-risk pregnancies may nevertheless feel pressure to spend limited resources on (costly) probiotics. To tailor knowledge exchange and support safe, equitable access to pregnancy probiotics when their prescription may be warranted, we need to understand who takes probiotics during pregnancy and under what conditions. We used chi-square and logistic regression analyses of anonymous, cross-sectional survey data from 341 pregnant Canadians of diverse socio-demographic backgrounds to assess which respondents, by socio-demographic characteristics and pre-pregnancy/pregnancy health indicators, were relatively likely to: perceive probiotics as beneficial to pregnancy health and/or report taking probiotics during pregnancy. Forty-seven percent of respondents perceived probiotics as beneficial to pregnancy health; 51 % reported consuming them. Probiotic attitudes and consumption were socio-demographically-patterned: higher-income, post-secondary-educated respondents disproportionately perceived probiotics as healthy and consumed them. There was no evidence of variation in probiotics attitudes or use by pregnancy health indicators. Socio-economic factors may be more important determinants of pregnancy probiotic use in this sample than indications for pregnancy complications. Clear guidelines on pregnancy probiotics that reflect current evidence are needed. Equitable access to probiotics should be facilitated for pregnant people likely to benefit from interventions (i.e., those with certain complications), supporting long-term health equity.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 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".