Planning of births and childhood undernutrition in Nepal: evidence from a 2016 national survey
Bibliographic record
Abstract
BACKGROUND: Childhood undernutrition is a significant public health issue in low-and middle-income countries, including Nepal. However, there is limited evidence showing the association between the planning of birth (PoB) and childhood undernutrition (stunting and underweight). We aimed to investigate the relationship between PoB and childhood undernutrition in the current study. METHODS: We used the Nepal Demographic and Health Survey (NDHS) 2016 data, a nationally representative cross-sectional household survey. We used two anthropometric indicators of childhood undernutrition as the outcome of this study. PoB is the main predictor. We used binary logistic regression with sampling weights to estimate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) to examine the association between the PoB and childhood undernutrition. Unless stated, the significant association between the variables is calculated with p < 0.001. RESULTS: The overall prevalence of stunting was 35.8%, and underweight was 27.1% in children under 5 years of age in Nepal. We found a higher rate of stunting (52.7%) and underweight (41.1%) in children with birth order > 3 and < 2 years of the interval between birth and subsequent birth (IBBSB). The association between the children's birth order and the prevalence of undernutrition had strong statistical significance. Mother's age at marriage (p = 0.001), underweight mother, mother's education, father's education, wealth quintile, no exposure to mass media, children's age, and place of residence(p = 0.001) were significantly associated with childhood undernutrition. The result of the multiple logistic regression showed that children with birth order one and 12-24 months of the interval between marriage and first birth (IBMFB) had significantly decreased odds of stunting than those children with birth order one and < 12 months of IBMFB (OR 0.6, 95% CI 0.4-0.9). CONCLUSION: The findings of the study demonstrate that PoB has a protective effect on childhood undernutrition. Delaying of childbirth until 12-24 months after marriage was found to be associated with reduced childhood stunting odds. To mitigate childhood undernutrition, Nepal's government needs to promote delayed childbearing after marriage while focusing on uplifting the household economics status and wide coverage of and utilization of mass media.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".