Socio-economic and cultural factors associated with the utilization of maternal healthcare services in Togo: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Proper utilization of maternal healthcare services plays a major role on pregnancy and birth outcomes. In sub-Saharan Africa, maternal and child mortality remains a major public health concern, especially in least developed countries such as Togo. In this study, we aimed to analyze factors associated with use of maternal health services among Togolese women aged 15-49 years. METHODS: This study used data from third round of nationally representative Demographic and Health Survey conducted in Togo in 2013. Analysis included 4,631 women aged 15-49 years. Outcome variables were timely first antenatal care (ANC) visits, adequate ANC4 + visits, and health facility delivery. Data were analyzed using Stata version 16. RESULTS: Overall, proportion of maternal healthcare utilization was 27.53% for timely first ANC visits, 59.99% for adequate ANC visits, and 75.66% for health facility delivery. Our multivariable analysis showed significant differences among women in highest wealth quintile, especially in rural areas with increasing odds of timely first ANC visits (Odds ratio (OR) = 3.46, 95% CI = 2.32,5.16), attending adequate ANC visits (OR = 2.19, 95% CI = 1.48,3.24), and delivering in health facilities (OR = 8.53, 95% CI = 4.06, 17.92) compared to those in the poorest quintile. Also, women with higher education had increased odds of timely first ANC visits (OR = 1.37, 95% CI = 1.11,1.69), and attending adequate ANC visits (OR = 1.73, 95% CI = 1.42,2.12) compared to those with no formal education. However, having higher parity and indigenous beliefs especially in rural areas decreased odds of using healthcare services. CONCLUSIONS: Findings from this study showed that socio-economic inequality and socio-cultural barriers influenced the use of maternal healthcare services in Togo. There is therefore a need to improve accessibility and the utilization of maternal healthcare services through women's economic empowerment and education to reduce the barriers.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".