Sociodemographic characteristics associated with the utilization of maternal health services in Cambodia
Bibliographic record
Abstract
BACKGROUND: Cambodia is a Southeast Asian country and has one the highest rates of maternal and child mortality with inadequate use of maternal healthcare services in the region. The present study aimed to analyse the progress made in terms of using maternal healthcare services since 2000. METHODS: Two rounds of Demographic and Health Surveys (DHS 2000 and DHS 2014) were used in the study. Sample population consisted 11,961 women aged between 15 and 49 years. The outcome measures were: Timing of first antenatal care (ANC) attendance, adequacy of ANC attendance, place of delivery and postnatal checkup. WHO guidelines were used to set the cut-off/define these measures. Data were analyzed in Stata version 14 using descriptive and multivariate regression analyses. RESULTS: Findings indicated that the overall prevalence of making the first ANC visit in the first trimester was 64.19% [95%CI = 62.22,66.11], and that of having at least four ANC visits was 43.80% [95%CI = 41.89,45.73]. Prevalence of health facility delivery was 48.76% [46.62,50.90] and that of postnatal checkup was 71.14% [95%CI = 69.21,73.01]. Between 2000 and 2014, the percentage of timely and adequate use of ANC increased by respectively 61.8 and 65.3%, while that of health facility delivery and postnatal care increased by respectively 74.5 and 43.9%. Important demographic, socioeconomic and geographic disparities were observed in the utilization of ANC, health facility delivery and postnatal care services. Urban residency, having better educational status, white collar job, access to electronic media showed positive association, whereas higher parity (having > 2 children) and unwanted pregnancy showed negative association with the use of maternal healthcare services. Having at least four ANC visits was associated with significantly increased higher odds of using health facility delivery and postnatal care. CONCLUSION: There has a been a remarkable increase in the prevalence of women who are using the maternal healthcare services since 2000. The current findings provide important insights regarding the sociodemographic factors associated with the utilization of maternal health services in Cambodia that could contribute to evidence-based health policy making and designing intervention programs.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".