Characteristics of vulnerable women and their association with participation in a Canada Prenatal Nutrition Program site in Toronto, Canada
Bibliographic record
Abstract
INTRODUCTION: The Canada Prenatal Nutrition Program (CPNP) supports community organizations to provide maternal-infant health services for socially/economically vulnerable women. As part of our research program exploring opportunities to provide postnatal breastfeeding support through the CPNP, we investigated the sociodemographic and psychosocial characteristics of clients enrolled in a Toronto CPNP site and explored associations with participation. METHODS: Data were collected retrospectively from the charts of 339 women registered in one southwest Toronto CPNP site from 2013 to 2016. Multivariable regression analyses were used to assess associations between 10 maternal characteristics and three dimensions of prenatal program participation: initiation (gestational age at enrolment in weeks), intensity (number of times one-on-one supports were received) and duration (number of visits). RESULTS: The mean (SD) age of clients was 31 (5.7) years; 80% were born outside of Canada; 29% were single; and 65% had household incomes below the Statistics Canada family size-adjusted low-income cut-offs. Income was the only characteristic associated with all dimensions of participation. Compared to clients living above the low-income cut-off, those living below the low-income cut-off enrolled in the program 2.85 weeks earlier (95% CI: -5.55 to -0.16), had 1.29 times higher number of one-on-one supports (95% CI: 1.03 to 1.61) and had 1.29 times higher number of program visits (95% CI: 1.02 to 1.63). CONCLUSION: Our findings show that this CPNP site serves vulnerable women, with few differences in participation based on maternal characteristics. This evidence can guide service provision and monitoring decisions at this program site. Further research is needed to explore new program delivery models to enhance perinatal services for vulnerable women.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".