Predictors of skilled birth attendance among married women in Cameroon: further analysis of 2018 Cameroon Demographic and Health Survey
Bibliographic record
Abstract
BACKGROUND: In Cameroon, maternal deaths remain high. The high maternal deaths in the country have been attributed to the low utilization of maternal healthcare services, including skilled birth attendance. This study examined the predictors of skilled birth services utilization among married women in Cameroon. METHODS: Data from the 2018 Cameroon Demographic and Health Survey was analyzed on 7881 married women of reproductive age (15-49 years). Both bivariate and multivariable logistic regression analyses were carried out to determine the predictors of skilled childbirth services. The results were presented with crude odds ratio (cOR) and adjusted odds ratio (aOR) and 95% confidence interval (CI). RESULTS: The coverage of skilled birth attendance among married women of reproductive age in Cameroon was 66.2%. After adjusting for potential confounders, media exposure (aOR = 1.46, 95% CI: 1.11-1.91), higher decision making (aOR = 1.88, 95% CI: 1.36-2.59), maternal education (aOR = 2.38, 95% CI; 1.65-3.42), place of residence (aOR = 0.50, 95% CI; 0.33-0.74), religion (aOR = 0.55, 95% CI; 0.35-0.87), economic status (aOR = 5.16, 95% CI; 2.58-10.30), wife beating attitude (aOR = 1.32, 95% CI; 1.05-1.65), parity (aOR = 0.62, 95% CI; 0.41-0.93) and skilled antenatal care (aOR = 14.46, 95% CI; 10.01-20.89) were found to be significant predictors of skilled birth attendance. CONCLUSIONS: This study demonstrates that social, economic, regional, and cultural factors can act as barriers to skilled childbirth services utilization in Cameroon. Interventions that target women empowerment, antenatal care awareness and strengthening are needed, especially among the rural poor, to reduce barriers to care seeking. Maternal healthcare services utilization interventions and policies in Cameroon need to focus on specific equity gaps that relate to socio-economic status, maternal education, and the economic empowerment of women. Such policies and interventions should also aim at reducing geographical barriers to access to maternal healthcare services, including skilled birth attendance. Due to the presence of inequities in the use of skilled birth attendance services, programs aimed at social protection and empowerment of economically disadvantaged women are necessary for the achievement of the post-2015 targets and the Sustainable Development Goals. Globally, Cameroon is one of the countries with high maternal deaths. Low utilization of maternal healthcare services, including skilled birth attendance have been found to account for the high maternal deaths in the country. This study sought to examine the factors associated with skilled childbirth services utilization among married women in Cameroon. Using data from the 2018 Cameroon Demographic and Health Survey, we found that the coverage of skilled birth attendance among married women of reproductive age in Cameroon is high. Factors such as higher decision-making power, higher maternal education, place of residence, religion, higher economic status, wife beating attitude, parity and skilled antenatal care were found to be the significant predictors of skilled birth attendance. This study has shown that socio-economic, regional and cultural factors account for the utilization of skilled childbirth services utilization in Cameroon. Interventions aimed at enhancing the utilization of skilled childbirth services in Cameroon should target women empowerment, antenatal care awareness creation and sensitization, especially among the rural poor, to reduce barriers to care seeking. Maternal healthcare services utilization interventions and policies in Cameroon need to focus on specific equity gaps that relate to socio-economic status, maternal education, and the economic empowerment of women.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".