Prevalence and determinants of menstrual regulation among ever-married women in Bangladesh: evidence from a national survey
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Despite the remarkable reduction of maternal mortality, unsafe and untimely menstrual regulation (MR) remains a major maternal health problem in Bangladesh. This study aimed to determine the prevalence and identify determinants of MR among ever-married women in Bangladesh. METHODS: Data for this study have been extracted from Bangladesh Demographic and Health Survey (BDHS) 2014. The survey followed a two-stage stratified sampling procedure and the study used a sub-sample of 8084 ever-married women aged 15 to 49 years extracted from survey sample of 17,863. Univariate and multivariate mixed-effect logistic regression analyses were used to identify risk factors for MR accounting for potential between-clusters variations. RESULTS: The weighted prevalence of MR was 12.3% (95% CI: 11.1-13.4%) among (991/8084) ever-married women. Women were less likely to have MR if they were from Chittagong (AOR 0.74, 95% CI: 0.57-0.96; p = 0.026) and Sylhet (AOR 0.53, 95% CI: 0.36-0.77; p = 0.001) divisions. Women were more likely to have MR if they were from high (AOR 1.47, 95% CI: 1.18-1.83; p = 0.001) and the highest (AOR 1.62, 95% CI: 1.27-2.05; p < 0.001) socioeconomic status (SES) group; being employed (AOR 1.35, 95% CI: 1.16-1.56; p < 0.001), having one or two children (AOR 1.73, 95% CI: 1.24-2.40: p = 0.001) and ≥ 3 children (AOR 2.56, 95% CI: 1.82-3.58; p < 0.001), and having membership of non-government organization (NGO) (AOR 1.18, 95% CI: 1.02-1.38; p = 0.030). CONCLUSION: MR is prevalent among Bangladeshi women and independently associated with geographic location, SES, parity, employment and NGO membership status. Health policy should prioritize in reducing spatial and socioeconomic inequalities in relation to MR services by ensuring accessibility and availability of MR services, especially in suburban divisions. Furthermore, abortion should be legalized in Bangladesh that will ultimately reduce the morbidity and mortality associated with unsafe abortion.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it