Association between Maternal and Child Nutritional Status in Hula, Rural Southern Ethiopia: A Cross Sectional Study
Bibliographic record
Abstract
BACKGROUND: Maternal and child under nutrition is highly prevalent in low-income and middle-income countries, resulting in substantial increases in mortality and overall disease burden. The aim of this baseline survey was to determine the association between selected maternal characteristics, maternal nutritional status and children's nutritional status. METHODS AND FINDINGS: A survey with a cross sectional design was conducted between September and October 2012 in Hula, Ethiopia. The study subjects were 197 mothers of children between the ages of 6 and 23 months. Weight and height (mothers) or recumbent length (children) were measured using calibrated, standardized techniques. Seven percent of children were below -2 weight for height Z score (WHZ), 11.5% were below -2 height for age Z score (HAZ) and 9.9% were below -2 weight for age Z score (WAZ). Maternal anthropometrics were associated with child nutritional status in the bivariate analysis. Maternal BMI (r = 0.16 P = 0.02) and educational status (r = 0.25 P = 0.001) were correlated with WHZ of children while maternal height (r = 0.2 P = 0.007) was correlated with HAZ of children. After multivariate analysis, children whose mothers had salary from employment had a better WHZ score (P = 0.001) and WAZ score (P<0.001). Both maternal BMI and maternal height were associated with WHZ (P = 0.04) and HAZ (P = 0.01) score of children. CONCLUSION: Having a mother with better nutritional status and salaried employment is a benefit for the nutritional status of the child. The interrelationship between maternal and child nutritional status stresses the value of improving maternal nutritional status as this should improve both maternal and child health outcomes. Therefore strategies to improve nutritional status of children should also include improving the nutritional status of the mother and empowering her financially.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".