Improved Sanitation Facilities are Associated with Higher Body Mass Index and Higher Hemoglobin Concentration Among Rural Cambodian Women in the First Trimester of Pregnancy
Bibliographic record
Abstract
Multiple factors contribute to undernutrition in Cambodian women. Our aim was to determine if type of household sanitation facility was associated with body mass index (BMI) and hemoglobin (Hb) concentration among pregnant women. Women (N = 544) from 75 villages in Kampong Chhnang Province had their height, weight, and Hb measured (HemoCue Hb 201+) in the first trimester. Sociodemographic and household characteristics were collected. Multivariable linear and logistic regression models were used for analyses. Approximately 40% (N = 221) of women reported primarily using an ‘improved’ sanitation facility (closed pit latrine) and ∼60% (N = 323) used ‘non-improved’ facilities (open defecation). Mean ± standard deviation (SD) BMI was higher among women with improved versus non-improved facilities (19.9 ± 3.0 kg/m2 versus 19.4 ± 2.3 kg/m2; P = 0.01). Mean ± SD Hb concentration was also higher among women with improved versus non-improved facilities (118 ± 12 g/L versus 114 ± 14 g/L; P = 0.001). Anemia prevalence (Hb < 110 g/L) was higher among women with non-improved facilities (34% versus 25%; P = 0.04). An improved sanitation facility was a positive predictor of BMI (β = 0.57 kg/m2; 95% confidence interval [CI] = 0.10, 1.04) and Hb concentration (β = 2.94 g/L; 95% CI = 0.53, 5.35), adjusting for age, parity, household size, village, gestation week, source of drinking water, and iron folic acid supplementation. Poor sanitation was associated with lower BMI and Hb concentration among pregnant Cambodian women. This warrants multisectoral approaches involving the health, nutrition, water, and sanitation sectors to effectively improve maternal health in Cambodia.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.003 | 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".