Associations Between Iron Deficiency Anemia and Wages in India: A Secondary Data Analysis (P22-016-19)
Bibliographic record
Abstract
Economic analyses add value beyond evidence to the implementation of any policy. The study explored the association between iron deficiency anemia (IDA) and the wages of adult men and women between 15- 49 years in India so that the possible monetary benefits of iron fortification policies could be evaluated. National sample survey organization (NSSO) Employment- Unemployment data was statistically matched with the NSSO Consumer Expenditure data at an individual level for the year 2011–12. The anemia levels (assuming 50% of anemia was due to iron deficiency) was mathematically modelled in response to a wide range of nutrient intakes, including iron intake from heme and non-heme sources along with inhibitors and enhancers in the diet, adjusting for bioavailability, sanitation and menstrual losses in women. A two-stage Heckman selection model was used to establish the association between wages and IDA. In the first stage, a probit model was used to determine labour force participation and in the second stage, an ordinary least square model, corrected for sample selection bias, was used to determine the impact of IDA on wages. The presence of IDA resulted in a decline of 15.3 percentage points in wages of regular salaried employed men as compared to those without IDA. Similar patterns was observed for women but the impact of anemia on wages was lower in comparison to men. Among women, a decline of 8.0 percentage points was observed in the wages of regular salaried employed women compared to those without IDA. However, the presence of IDA had no significant impact on the wages of casual labourers. This indicated that there were other random factors that affected the wages of this segment of population. There is an association between IDA and wages for a segment of working population. Addressing anemia through iron fortification programs such as the usage of double fortified salt could possibly change living standards of the population through improvement in earnings. International Development Research Centre, Canada; Tata Trusts, India.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".