Use of micronutrient supplements among pregnant women in <scp>A</scp>lberta: results from the <scp>A</scp>lberta <scp>P</scp>regnancy <scp>O</scp>utcomes and <scp>N</scp>utrition (<scp>APrON</scp>) cohort
Bibliographic record
Abstract
Maternal nutrient intake in the prenatal period is an important determinant of fetal growth and development and supports maternal health. Many women, however, fail to meet their prenatal nutrient requirements through diet alone and are therefore advised to consume nutrient supplements. The purpose of this study was to describe the use of natural health products (NHP) by pregnant women in each trimester of pregnancy. Women (n = 599) participating in the first cohort of the Alberta Pregnancy Outcomes and Nutrition (APrON) study completed an interviewer-administered supplement intake questionnaire during each trimester of pregnancy. NHP use was high, with >90% taking multivitamin/mineral supplements, and nearly half taking at least one additional single-nutrient supplement. Compliance with supplementation guidelines was high for folic acid (>90%), vitamin D (∼70%) and calcium (∼80%), but low for iron (<30%) and for all four nutrients together (≤11%). On average, women met or exceeded the recommended dietary allowance for folic acid, vitamin D and iron from NHPs alone, with median daily intakes of 1000 μg, 400 IU and 27 mg, respectively. The median calcium intake was 250 mg d(-1) . Up to 26% of women exceeded the tolerable upper intake level for folic acid and up to 19% did so for iron at some point of their pregnancy. Findings highlight the need to consider both dietary and supplemental sources of micronutrients when assessing the nutrient intakes of pregnant 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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".