Women’s Empowerment and HIV Testing Uptake: A Meta-analysis of Demographic and Health Surveys from 33 Sub-Saharan African Countries
Bibliographic record
Abstract
Background: There is a growing body of evidence suggesting that women’s empowerment can help achieve better health behaviours and outcomes. However, few have looked at the impact of women’s empowerment on HIV testing in Sub-Saharan Africa (SSA). This study investigated the association between women’s empowerment and HIV testing among women in 33 countries across SSA. Methods: Cross-sectional data from the most recent Demographic and Health Surveys (2005-2018) of 33 countries in SSA were used. Confounder adjusted logistic regression analysis was completed separately for each of the 33 DHS datasets to produce the adjusted Odds Ratio (OR) for the association between women empowerment and HIV testing. The regression analysis strictly accounted for the three design elements (weight, cluster and strata) to produce an estimate representative of the respective countries. Finally, an Individual Participant Data (IPD) meta-analysis approach was used to statistically pool the effect of women empowerment on HIV testing. Results: There was a wide variation in the percentage of women who were empowered among the countries studied, with only a few countries such as South Africa, Angola and Ghana having a high prevalence of negative attitudes toward wife beating. HIV testing was higher in Angola, Lesotho, Uganda and South Africa. While participation in one or two of the three decisions had been marginally associated with lower odds of HIV testing across the SSA regions (0.89; 95%CI: 0.83, 0.97); the corresponding prediction interval crossed the null. Being involved in the three decisions (0.92; 95%CI: 0.84, 1.00) and disagreement to wife-beating (0.99; 95%CI: 0.94, 1.05) had no statistical relationship with HIV testing uptake. Conclusion and Global Health Implications: The two indirect indicators of women empowerment could not predict HIV testing uptake. Further studies are recommended to establish the nature of the relationship between HIV testing and women’s empowerment that is measured through standard tools. Key words: • HIV/AIDS prevention • Women • Empowerment • Gender equality • Global health • Sub-Saharan Africa Copyright © 2020 Yaya et al. Published by Global Health and Education Projects, Inc. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in this journal, is properly cited.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".