Household structure, maternal characteristics and children’s stunting in sub-Saharan Africa: evidence from 35 countries
Bibliographic record
Abstract
BACKGROUND: Adequate nutrition in early childhood is a necessity to achieve healthy growth and development, as well as a strong immune system and good cognitive development. The period from conception to infancy is especially vital for optimal physical growth, health and development. In this study we examined the influence of household structure on stunting in children <5 yrs of age in sub-Saharan Africa (SSA) countries. METHODS: Demographic and Health Survey data from birth histories in 35 SSA countries were used in this study. The total sample of children born within the 5 yrs before the surveys (2008 and 2018) was 384 928. Children whose height-for-age z-score throughout was <-2 SDs from the median of the WHO reference population were considered stunted. Percentages and χ2 tests were used to explore prevalence and bivariate associations of stunting. In addition, a multivariable logistic regression model was fitted to stunted children. All statistical tests were conducted at a p<0.05 level of significance. RESULTS: More than one-third of children in SSA countries were reportedly stunted. The leading countries include Burundi (55.9%), Madagascar (50.1%), Niger (43.9%) and the Democratic Republic of the Congo (42.7%). The percentage of stunted children was higher among males than females and among rural children than their urban counterparts in SSA countries. Children from polygamous families and from mothers who had been in multiple unions had a 5% increase in stunting compared with children from monogamous families and mothers who had only one union (AOR 1.05 [95% CI 1.02 to 1.09]). Furthermore, rural children were 1.23 times as likely to be stunted compared with urban children (AOR 1.23 [95% CI 1.16 to 1.29]). Children having a <24-mo preceding birth interval were 1.32 times as likely to be stunted compared with first births (AOR 1.32 [95% CI 1.26 to 1.38]). In addition, there was a 2% increase in stunted children for every unit increase in the age (mo) of children (AOR 1.02 [95% CI 1.01 to 1.02]). Multiple-birth children were 2.09 times as likely to be stunted compared with a singleton (AOR 2.09 [95% CI 1.91 to 2.28]). CONCLUSIONS: The study revealed that more than one-third of children were stunted in SSA countries. Risk factors for childhood stunting were also identified. Effective interventions targeting factors associated with childhood stunting, such as maternal education, advanced maternal age, male sex, child's age, longer birth interval, multiple-birth polygamy, improved household wealth and history of mothers' involvement in multiple unions, are required to reduce childhood stunting in the region.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| 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) | 0.001 | 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".