Private health care market shaping and changes in inequities in childhood diarrhoea treatment coverage: evidence from the analysis of baseline and endline surveys of an ORS and zinc scale-up program in Nigeria
Bibliographic record
Abstract
BACKGROUND: Nearly 90,000 under-five children die from diarrhoea annually in Nigeria. Over 90% of the deaths can be prevented with oral rehydration salt (ORS) and zinc treatment but coverage nationally was less than 34% for ORS and 3% for zinc with wide inequities. A program was implemented in eight states to address critical barriers to the optimal functioning of the health care market to deliver these treatments. In this study, we examine changes in the inequities of coverage of ORS and zinc over the intervention period. METHODS: Baseline and endline household surveys were used to measure ORS and zinc coverage and household assets. Principal component analysis was used to construct wealth quintiles. We used multi-level logistic regression models to estimate predictive coverage of ORS and zinc by wealth and urbanicity at each survey period. Simple measures of disparity and concentration indices and curves were used to evaluate changes in ORS and zinc coverage inequities. RESULTS: At baseline, 28% (95% CI: 22-35%) of children with diarrhoea from the poorest wealth quintile received ORS compared to 50% (95% CI: 52-58%) from the richest. This inequality reduced at endline as ORS coverage increased by 21%-points (P < 0.001) for the poorest and 17%-points (P < 0.001) for the richest. Zinc coverage increased significantly for both quintiles at endline from an equally low baseline coverage level. Consistent with the findings of the pairwise comparison of the poorest and the richest, the summary measure of disparity across all wealth quintiles showed a narrowing of inequities from baseline to endline. Concentration curves shifted towards equality for both treatments, concentration indices declined from 0.1012 to 0.0480 for ORS and from 0.2640 to 0.0567 for zinc. Disparities in ORS and zinc coverage between rural and urban at both time points was insignificant except that the use of zinc in the rural at endline was significantly higher at 38% (95%CI: 35-41%) compared to 29% (95%CI, 25-33%) in the urban. CONCLUSION: The results show a pro-rural improvement in coverage and a reduction in coverage inequities across wealth quintiles from baseline to endline. This gives an indication that initiatives focused on shaping healthcare market systems may be effective in reducing health coverage gaps without detracting from equity as a health policy objective.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".