Gender inequity as a barrier to women’s access to skilled pregnancy care in rural Nigeria: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Maternal mortality has been an issue of global importance, with continued efforts by the international development community towards its reduction. The provision of high quality maternal healthcare has been identified as a key strategy in preventing maternal mortality. Gendered intrahousehold power structures, gendered dynamics of resource allocation and women's limited ability in decision-making can have a huge impact on maternal health-seeking behaviour and overall health status. Using a gender lens, this study explores the root causes of women's limited access to and utilisation of maternal healthcare services in rural areas of Edo State, Nigeria. METHODS: This qualitative study involved the analysis of data collected from gender- and age-desegregated focus group discussions (FDGs) in 20 communities in Etsako East and Esan South East local government areas of Edo State, Nigeria. Focus group participants comprised women between the ages of 15-45 y who have been pregnant within the last 5 y and their male spouses and partners of varying ages. A total of 20 FGDs were conducted. Coded transcripts were reviewed and analysed using the gender framework as an analytical guide. RESULTS: Most responses indicated that women did not entirely have the power to make decisions regarding when to seek care during pregnancy. Women's experiences of access to quality care showed intersecting areas of gender and social economic status (SES) and how they impact on access to health. Many of the responses suggested high levels of economic marginalisation among women with women being financially dependent on their spouses and partners for pregnancy healthcare-related costs. Furthermore, a man's financial status determined the type of care his spouse or partner sought. Women identified a high workload as an issue during pregnancy and a barrier to accessing maternal healthcare services. The role of men within households was generally perceived as that of financial providers, therefore a husband's support was commonly constructed to solely mean financial support. CONCLUSION: This paper brings attention to the role of gender and SES in producing and sustaining limitations to women's access to quality care. Interventions geared towards supporting women's financial independence is an important step towards improving their access to skilled healthcare, more so are interventions that improve women's decision-making capacities.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".