Is Distribution a Problem in Iron-Folic Acid Consumption in India? An Exploration of District Level Household Survey
Bibliographic record
Abstract
Aims: Anemia accounts for 40% of maternal deaths in India. In order to address this problem, the Government of India implemented the largest programme with the greatest potential to reduce maternal mortality by free distribution of Iron-Folic Acid (IFA) supplementations especially during Antenatal Care (ANC) visits. But the major concern among the policymakers and researchers has been poor adherence to the supplement among pregnant women. However, we tend to think that given the severity of the problem, there is no investigation on the adherence issue. Hence, the aim of the paper is to understand whether IFA consumption by pregnant women in India is largely a distribution problem of IFA supplements through ANC. Background: The distribution of Iron-Folic Acid (IFA) supplementation is not working especially through Antenatal Care (ANC) attendance. The program implementers believe that it is because of lack of adherence to IFA supplements by pregnant women. It is important to investigate the problem before any policy changes are made without proper evidence. Objectives: The purpose of this study is to examine whether the problem of IFA consumption by pregnant women is due to the problem of public distribution of IFA supplements through ANC attendance. Methods: This study had used the fourth round of District Level Household Survey data, which collects information on IFA supplements, their distribution and consumption. Bivariate and tri-variate analyses were used to understand the relationship between IFA distribution to pregnant women and their consumption patterns in 19 Indian states and two Union Territories (UTs) of pregnant women (88,487) and between the age of 15-49 years. Results: In almost all the states except Chhattisgarh, more than 75% of the pregnant women consumed 100 or more IFA supplements when they received 100 or more IFA supplements from providers. Similar is the case even among those women who received 100 or more IFA supplements through 1 or 2 ANC attendance except Arunachal Pradesh (60%), Meghalaya (67%), Pondicherry (57%) and Andaman and Nicobar (0%). The consumption of IFA supplements among pregnant women gets better than 75% if they receive 100 or more supplements only after attending three or more ANCs. Conclusion: It seems that distribution is a problem in the consumption of IFA supplements by pregnant women in India. Full antenatal attendance by the women could be part of the problem but not supplying at least 100 IFA supplementations to even those who attend ANC due to stock-outs and ineffective management is a serious concern. Hence, Governments should distribute at least the recommended 100 IFA supplements to the women in their 1st ANC attendance to address anaemia.
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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 | 0.001 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, 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".