The role of gender inequality and health expenditure on the coverage of demand for family planning satisfied by modern contraceptives: a multilevel analysis of cross-sectional studies in 14 LAC countries
Bibliographic record
Abstract
Background: Despite international efforts to improve reproductive health indicators, little attention is paid to the contributions of contextual factors to modern contraceptive coverage, especially in the Latin America and the Caribbean (LAC) region. This study aimed to identify the association between country-level Gender Inequality and Health Expenditure with demand for family planning satisfied by modern contraceptive methods (DFPSm) in Latin American sexually active women. Methods: Our analyses included data from the most recent (post-2010) Demographic and Health Survey or Multiple Indicator Cluster Survey from 14 LAC countries. Descriptive analyses and multilevel logistic regressions were performed. Six individual-level factors were included. The effect of the country-level factors Gender Inequality Index (GII) and Current Health Expenditure on DFPSm was investigated. Findings: DFPSm ranged from 41.8% (95% CI: 40.2-43.5) in Haiti to 85.6% (95% CI: 84.9-86.3) in Colombia, with an overall median coverage of 77.8%. A direct association between the odds of DFPSm and woman's education, wealth index, and the number of children was identified. Women from countries in the highest GII tertile were less likely (OR: 0.32, 95% CI: 0.13-0.76) to have DFPSm than those living in countries in the lowest tertile. Interpretation: Understanding the contribution of country-level factors to modern contraception may allow macro-level actions focused on the population's reproductive needs. In this sense, country-level gender inequalities play an important role, as well as individual factors such as wealth and education. Funding: Bill and Melinda Gates Foundation and Associação Brasileira de Saúde Coletiva (ABRASCO).
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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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".