Evaluating the association between household water, sanitation and hygiene (WASH) and selected placenta-related complications in The Gambia, Kenya and Mozambique
Bibliographic record
Abstract
Abstract Placenta-related complications such as pre-eclampsia, small-for-gestational-age (SGA) and stillbirth contribute significantly to maternal and perinatal mortality globally, with the highest burden in low– and middle-income countries (LMICs). The potential impact of inadequate access to household water, sanitation, and hygiene (WASH) on these outcomes has not been quantified. This study investigates the association between household WASH conditions and pre-eclampsia, stillbirth and SGA in The Gambia, Kenya, and Mozambique, where access to safe WASH services remains a challenge. This study is nested within the PRECISE (PREgnancy Care Integrating Translational Science, Everywhere) study, a prospective observational cohort including 5,745 unselected pregnant women. Multivariate logistic regression analysis was used to test the associations between household WASH and pre-eclampsia, SGA or stillbirth. Compared to women with piped water in their homes, those relying on other improved water sources had higher odds of experiencing selected placenta-related complications (adjusted odds ratio (aOR) 1.36 [95% confidence interval (CI) 1.18, 1.57], p < 0.001). Country-specific analyses revealed differences across settings. In both The Gambia (1.52 [1.03, 2.24], p = 0.034) and Kenya (1.29 [1.04, 1.59], p = 0.019), the use of other improved water sources was associated with increased odds of selected placenta-related complications. Unimproved sanitation, compared with improved sanitation, was associated with increased odds of selected placenta-related complications in Mozambique (1.35 [1.02, 1.80], p = 0.038). The findings highlight the role of household-level WASH conditions as potential risk factors for placenta-related complications. Even when water sources are improved, contamination can occur during collection, transport and storage, while unimproved sanitation can increase pathogen exposure. These results underline the need for targeted WASH interventions to reduce pregnancy-related risks. Addressing these gaps could significantly reduce the prevalence of placenta-related complications, contributing to improved maternal and neonatal health outcomes in LMICs. Future research should explore the mechanisms linking WASH to pre-eclampsia, SGA and stillbirth and other placenta-related complications, and assess the effect of comprehensive WASH interventions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".