Childhood Malnutrition is Associated with Maternal Care during Pregnancy and Childbirth: A Cross-Sectional Study in Bauchi and Cross River States, Nigeria
Bibliographic record
Abstract
BACKGROUND: Malnutrition remains an important cause of childhood morbidity and mortality; the levels of childhood malnutrition in Nigeria are among the highest in the world. The literature supports many direct and indirect causes of malnutrition, but few studies have examined the link between maternal care during pregnancy and childbirth and childhood malnutrition. This study examines this potential link in Bauchi and Cross River states in Nigeria. DESIGN AND METHODS: In 2011, a household survey collected information about children under four years old and their mothers' last pregnancy. Trained fieldworkers measured mid-upper arm circumference (MUAC) of children aged 6-47 months. We examined associations with childhood malnutrition in bivariate and multivariate analysis. RESULTS: Some 4.4% of 3643 children in Cross River, and 14.7% of 2706 in Bauchi were malnourished (MUAC z-score). In both states, a child whose mother had fewer than four government antenatal care visits was more likely to be malnourished (Cross River: OR 1.85, 95%CIca 1.33-2.55; Bauchi: OR 1.29, 95%CIca 1.02-1.63). In Bauchi, a child whose mother who rarely or never discussed pregnancy and childbirth with her husband (OR 1.34, 95%CIca 1.07-1.68), and who did not have her last delivery attended by a skilled health worker was more likely to be malnourished (OR 1.50, 95%CIca 1.09-2.07). CONCLUSIONS: These findings, if confirmed in other studies, suggest that poor care of women in pregnancy and childbirth could pose a longer term risk to the health of the child, as well as increasing immediate risks for both mother and child. Significance for public healthChildhood malnutrition is a public health priority, accounting for almost 1/5 of global disease burden among children under five years old. Many studies have examined risk factors for childhood malnutrition, but few have examined the link between maternal care during pregnancy and childbirth and childhood malnutrition. This study, albeit a cross-sectional design, provides evidence of a link between poor care during pregnancy and childbirth and childhood malnutrition in two states of Nigeria. This is important for public health because it suggests another benefit of caring for women during pregnancy and childbirth. This could not only reduce maternal and child perinatal mortality, but also have benefits for the longer-term health and development of children. This finding could be useful for paternal advocacy; it may motivate men to support their wives during pregnancy and childbirth since through this support, fathers can also protect the future development of their children.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".