Reducing micronutrient deficiencies in Pakistani children: are subsidies on fortified complementary foods cost-effective?
Bibliographic record
Abstract
OBJECTIVE: To estimate the cost-effectiveness of price subsidies on fortified packaged complementary foods (FPCF) in reducing iodine deficiency, iron-deficiency anaemia and vitamin A deficiency in Pakistani children. DESIGN: The study proceeded in three steps: (i) we determined the current lifetime costs of the three micronutrient deficiencies with a health economic model; (ii) we assessed the price sensitivity of demand for FPCF with a market survey in two Pakistani districts; (iii) we combined the findings of the first two steps with the results of a systematic review on the effectiveness of FPCF in reducing micronutrient deficiencies. The cost-effectiveness was estimated by comparing the net social cost of price subsidies with the disability-adjusted life years (DALY) averted. SETTING: Districts of Faisalabad and Hyderabad in Pakistan. SUBJECTS: Households with 6-23-month-old children stratified by socio-economic strata. RESULTS: The lifetime social costs of iodine deficiency, iron-deficiency anaemia and vitamin A deficiency in 6-23-month-old children amounted to production losses of $US 209 million and 175 000 DALY. Poor households incurred the highest costs, yet even wealthier households suffered substantial losses. Wealthier households were more likely to buy FPCF. The net cost per DALY of the interventions ranged from a return per DALY averted of $US 783 to $US 65. Interventions targeted at poorer households were most cost-effective. CONCLUSIONS: Price subsidies on FPCF might be a cost-effective way to reduce the societal costs of micronutrient deficiencies in 6-23-month-old children in Pakistan. Interventions targeting poorer households are especially cost-effective.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".