Factors Associated with Pregnancy Intentions Amongst Postpartum Women Living with HIV in Rural Southwestern Uganda
Bibliographic record
Abstract
Comprehensive HIV treatment and care makes it safer for women living with HIV (WLWH) to have the children they desire, partly through provision and appropriate use of effective contraception. However, nearly one third of WLWH in-care in a large Ugandan cohort became pregnant within 3 years of initiating ART and half of these incident pregnancies (45%) were unplanned. We therefore describe future pregnancy plans and associated factors among postpartum WLWH in rural southwestern Uganda in order to inform interventions promoting postpartum contraceptive uptake. This analysis includes baseline data collected from adult WLWH enrolled into a randomized controlled trial to evaluate the effect of family planning support versus standard of care at 12 months postpartum in southwestern Uganda. Enrolled postpartum WLWH completed an interviewer-administered questionnaire at enrolment. Among 320 enrolled women, mean age, CD4 count, and duration on ART was 28.9 (standard deviation [SD] 5.8) years, 395 cells/mm 3 (SD = 62) and 4.6 years (SD = 3.9), respectively. One-hundred and eighty nine (59%) of women reported either personal (175, 55%) or partner (186, 58%) desire for more children in the next 2 years. Intentions to have more children was strongly associated with partner’s desire for more children (AOR = 31.36; P < 0.000), referent pregnancy planned (AOR = 2.69; P = 0.050) and higher household income > 150,000 Shs per month (AOR = 1.37; P = 0.010). Previous use of modern contraception (AOR = 0.07; P = 0.001), increasing age (AOR = 0.34; P = 0.012), having > 2 own children living in a household (AOR = 0.42; P = 0.021) and parity > 2 (AOR = 0.59; P = 0.015) were associated with reduced odds of pregnancy intention. Our findings highlight the role male partners play in influencing pregnancy intentions postpartum and the importance of engaging men in sexual and reproductive health counselling about child spacing for the health of women, children, and families. This should be addressed alongside key individual-level social, demographic, economic and structural factors within which couples can understand risks of unplanned pregnancies and access effective contraceptive methods when they need or want them.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".