Health and nutrition knowledge, attitudes and practices of pregnant women attending and not-attending ANC clinics in Western Kenya: a cross-sectional analysis
Bibliographic record
Abstract
BACKGROUND: Antenatal care (ANC) is a key strategy to decreasing maternal mortality in low-resource settings. ANC clinics provide resources to improve nutrition and health knowledge and promote preventive health practices. We sought to compare the knowledge, attitude and practices (KAP) among women seeking and not-seeking ANC in rural Kenya. METHODS: Data from a community-based cross-sectional survey conducted in Western Province, Kenya were used. Nutrition knowledge (NKS), health knowledge (HKS), attitude score (AS), and dietary diversity score (DDS) were constructed indices. χ2 test and Student's t-test were used to compare proportions and means, respectively, to assess the difference in KAP among pregnant women attending and not-attending ANC clinics. Multiple regression analyses were used to assess the impact of the number of ANC visits (none, <4, ≥4) on knowledge and practice scores, adjusting for maternal socio-demographic confounders, such as age, gestational age, education level and household wealth index. RESULTS: Among the 979 pregnant women in the survey, 59% had attended ANC clinics while 39% had not. The mean (±SD) NKS was 4.6 (1.9) out of 11, HKS was 6.2 (1.7) out of 12, DDS was 4.9 (1.4) out of 12, and AS was 7.4 (2.2) out of 10. Nutrition knowledge, attitudes, and DDS were not significantly different between ANC clinic attending and non-attending women. Among women who attended ANC clinics, 82.6% received malaria and/or antihelmintic treatment, compared to 29.6% of ANC clinic non-attendees. Higher number of ANC clinic visits and higher maternal education level were significantly positively associated with maternal health knowledge. CONCLUSIONS: Substantial opportunities exist for antenatal KAP improvement among women in Western Kenya, some of which could occur with greater ANC attendance. Further research is needed to understand multi-level factors that may affect maternal knowledge and practices.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".