Birth outcomes associated with prenatal participation in a government support programme for mothers with low incomes
Bibliographic record
Abstract
BACKGROUND: Women with low incomes are at higher risk to have low-birthweight (LBW) babies and less likely to participate in prenatal support programmes than women with higher incomes. This study examined birth outcomes among participants in the Newfoundland and Labrador Mother-Baby Nutrition Supplement (MBNS), a prenatal programme for women with low incomes that provides a monthly financial supplement and printed information on infant health and development, along with a referral to public health nursing services. METHODS: Application data (e.g. mother's age, education) for those who applied between August 2002 and December 2004 were obtained from the Provincial Government. Birth outcomes (e.g. birthweight, weeks of gestation) were available for 1599 women. Of these, 862 were parity zero and subsequently delivered full-term infants. Comparisons were made on demographics, timeliness of enrolment and rates of full-term LBW. RESULTS: Participants were more often single, younger and less educated than the average woman who gave birth in the Province or Canada in 2004. Women enrolled early were less likely to have a full-term LBW baby than those enrolled late (chi(2)((1)) = 4.03, P = 0.045). Mothers enrolled late had a higher rate of full-term LBW than was the case in the Province [risk ratio (RR) = 2.76, 95% confidence interval (CI) = 1.61-4.74] and Canada (RR = 2.53, 95% CI = 1.55-4.21) whereas those enrolled earlier, despite increased risk due to low income, age and education, single status and zero parity, had rates of full-term LBW on par with the Province (RR = 1.29, 95% CI = 0.71-2.32) and Canada (RR = 1.19, 95% CI = 0.68-2.08). CONCLUSION: The MBNS is an effective intervention for improving birth outcomes in women considered at risk. The challenge is to enrol pregnant women as early as possible. Future research will examine what programme component or combination of components (e.g. financial, information, referral) affects birth outcomes.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".