No Female Disadvantage in Anthropometric Status among Children in India
Bibliographic record
Abstract
Female disadvantage in child mortality, intra-household allocation of food and coverage of health interventions has been shown to exist in India. At the same time, there has been limited examination of female disadvantage in nutritional status. Using measures of anthropometry and anthropometric failure, we study female disadvantage in child nutritional status from the data collected from the Indian National Family Health Survey (NFHS) undertaken in 1992–1993 and 2005–2006. Height and/or weight measurements were available on 70,148 children aged 0–47 months in both survey periods. Child anthropometry (height/length-for-age [HAZ], weight-for-age [WAZ], weight-for-height/length [WHZ]) and anthropometric failure (defined according to the 2006 WHO growth standards as stunting, wasting and underweight) were analysed using linear and logistic regression models. In pooled regression models, boys were more likely to have lower anthropometric scores and higher rates of anthropometric failure. Across survey periods, the change in anthropometric status was greater for boys compared to girls for WAZ/underweight and WHZ/wasting, but was similar for HAZ/stunting. Boy–girl differences in anthropometry (with boys doing worse) were greater at less than 24 months of age and narrowed over time particularly in the 0–5 and 6–11 month age groups, resulting in no gender differences in anthropometric status. Declines in anthropometric status in HAZ/stunting and WAZ/underweight were found among third or higher birth order boys and girls, especially within families with two preceding children of the same sex but also in households with preceding children of mixed genders, suggesting a birth order effect as opposed to a birth order and gender effect. In 1992–1993 and 2005–2006, levels of anthropometric failure were higher among boys compared to girls in a majority of states. Although girls had lower levels of anthropometric failure, the magnitude of the between survey period decline was higher in girls in fewer states compared to boys (5/20, 7/25 and 10/20 states for stunting, underweight and wasting, respectively). In summary, in the most recently available data, using measures of anthropometric status, we did not find consistent evidence for female disadvantage in nutritional status among girls in India.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".