Components of antenatal care received by women in fishing communities on Lake Victoria, Uganda; a cross sectional survey
Bibliographic record
Abstract
Abstract Background: Uganda has one of the highest maternal deaths at a ratio of 336 per 100,000 live births. As Uganda strives to achieve sustainable development goals, components of antenatal care are key to reduction of maternal mortality. We explored women’s receipt of seven of the Uganda guidelines components of antenatal care, and associated factors in hard to reach Lake Victoria island fishing communities of Kalangala district.Methods: A cross sectional survey among 486 consenting women aged 15-49 years, who were pregnant or had a birth or abortion in the past 6 months was conducted in 6 island fishing communities of Kalangala district, Uganda, during January-May 2018. Interviewer administered questionnaires, in Open Data Kit software were used to collect data on socio-demographics and receipt of seven of the Uganda guidelines components of antenatal care. Regression modeling was used to determine factors associated with receipt of all seven components. Analyses were done using STATA version 15.1.Results: Women’s median (range) age was 26 (15-45) years, majority were married [87.0%, (423/486)], their main occupation was housewives (stay home mums) [45.1%, (219/486)] and never studied beyond seven years of education [69.1%, (336/486)]. Over three quarters of women who attended the nationally recommended four focused ANC visits did not receive all seven components of care at least once during the visits [76.4%, (107/140), P<0.05]. Women who reported being attended to by a doctor were thrice as likely to have received all seven components as those seen by a midwife/nurse (aOR=3.2; 95% CI:1.1-9.1).Conclusions: There is need to improve components of antenatal care received by women in these communities. Implementation programs need to evaluate receipt of antenatal care components among attendees in these hard to reach communities.Trial Registration: PACTR201903906459874 (Retrospectively registered).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".