Availability and Intake of Foods with Naturally Occurring or Added Vitamin D in a Setting of High Vitamin D Deficiency
Bibliographic record
Abstract
Vitamin D deficiency is common during pregnancy in Bangladesh. We aimed to examine availability and intake of foods with naturally occurring or added vitamin D in pregnant women in an urban, low income setting. We examined baseline data from an ongoing, 5‐arm, randomized controlled trial of vitamin D supplementation enrolling pregnant women at 17 to 24 weeks gestation in in Dhaka, Bangladesh (n=319; “MDIG” Trial goal n=1300, ClinicalTrials.gov: NCT01924013). A focused, semi‐quantitative food frequency questionnaire was used to estimate dietary intake of foods containing vitamin D and potentially fortified with vitamin D in the past month. Further, local food markets were visited to document the availability of vitamin D fortified foods. Median (IQR) fish intake was 2.6 (1.3, 4.6) times per week, with only 5% of women reporting no fish intake (Table 1). Fresh milk was commonly consumed (21% drank once per day) but powdered milk was not (80% never consumed). In market analysis, the only locally available, packaged foods labeled as vitamin D fortified were powdered milk and ice cream. Fresh milk, cheese, yogurt, breakfast cereals, and crackers were not vitamin D fortified. Powdered milk was widely available; we identified 13 different powdered milk products (Table 2). All were vitamin D fortified, yet only 3 products indicated 100 IU or more per serving (approximate amount in one serving of milk in the US). Promoting use of powdered milk and fortifying fresh milk should be explored as practical ways to improve vitamin D intake in pregnant women in Bangladesh Support Gates Foundation (OPP1066764) and NIH BIRCWH award (K12HD055882). Table 1. Prevalence of food intake in pregnant women for foods with naturally occurring or added vitamin D, Dhaka, Bangladesh, 2014 (n=319). No. of pregnant women self‐reporting intake over past month Never < once per week Once per week 2‐6 times per week Once per day > once per day Food n (%) Milk, fresh 1 60 (18.8) 83 (26.0) 19 (6.0) 88 (27.6) 68 (21.3) 1 (0.3) Powdered milk 1 254 (79.6) 19 (6.0) 10 (3.1) 15 (4.7) 17 (5.3) 4 (1.3) Yogurt 1 159 (49.8) 138 (43.3) 16 (5.0) 6 (1.9) 0 (0) 0 (0) Ice cream 104 (32.6) 144 (45.1) 27 (8.5) 39 (12.2) 4 (1.3) 1 (0.3) Cheese 293 (91.9) 23 (7.2) 2 (0.6) 1 (0.3) 0 (0) 0 (0) Egg 29 (9.0) 61 (19.1) 36 (11.3) 128 (40.1) 62 (19.4) 3 (0.9) Poultry 51 (16.0) 121 (37.9) 62 (19.4) 82 (25.7) 2 (0.6) 1 (0.3) Beef/Mutton/Pork 56 (17.6) 122 (38.2) 57 (17.9) 81 (25.4) 3 (0.9) 0 (0) Organ meats 183 (57.4) 114 (35.7) 13 (4.1) 7 (2.2) 2 (0.6) 0 (0) Fish (fresh or dried) 17 (5.3) 45 (14.1) 76 (23.8) 133 (41.7) 25 (7.8) 23 (7.2) 1 Trace amount of vitamin D naturally occurring per the Food Composition Table for Bangladesh, 1 st Edition, University of Dhaka, June 2013. Table 2. Vitamin D content and cost of powdered milk products in Dhaka, Bangladesh, 2014. 1
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".