The association of water carriage, water supply and sanitation usage with maternal and child health. A combined analysis of 49 Multiple Indicator Cluster Surveys from 41 countries
Bibliographic record
Abstract
BACKGROUND: Millions of people carry water home from off-plot sources each day and lack improved sanitation. Research on the health outcomes associated with water fetching is limited, and with usage of improved sanitation is inconclusive. OBJECTIVES: To analyse the association of water fetching, unimproved water supplies, and usage of improved sanitation facilities with indicators of women's and children's health. METHODS: 49 Multiple Indicator Cluster Surveys from 41 countries were merged, creating a data set of 2,740,855 people from 539,915 households. Multilevel, multivariable analyses were conducted, using logistic regression for binary outcomes, negative binomial regression for count data and ordinary linear regression for linear data. We adjusted for confounding factors and accounted for clustering at survey, cluster and household level. RESULTS: Compared to households in which no-one collects water, water fetching by any household member is associated with reduced odds of a woman giving birth in a health care facility (OR 0.88 to 0.90). Adults collecting water is associated with increased relative risk of childhood death (RR 1.04 to 1.05), children collecting water is associated with increased odds of diarrheal disease (OR 1.10 to 1.13) and women or girls collecting water is associated with reduced uptake of antenatal care (β-0.04 to -0.06) and increased odds of leaving a child under five alone for one or more hours, one or more days per week (OR 1.07 to 1.16). Unimproved water supply is associated with childhood diarhhoea (OR 1.05), but not child deaths, or growth scores. When the percentage of people using improved sanitation is more than 80% an association with reduced childhood death and stunting was observed, and when more than 60%, usage of improved sanitation was associated with reduction of diarhhoea and acute undernutrition. CONCLUSION: Fetching water is associated with poorer maternal and child health outcomes, depending on who collects water. The percentage of people using improved sanitation seems to be more important than type of toilet facility, and must be high to observe an association with reduced child deaths and diarhhoea. Water access on premises, and near universal usage of improved sanitation, is associated with improvements to maternal and child health.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".