Factors influencing the use of modern contraceptive in Nigeria: a multilevel logistic analysis using linked data from performance monitoring and accountability 2020
Bibliographic record
Abstract
BACKGROUND: The population of Nigeria is estimated at over 190 million and it is projected to increase by 44% between 2015 and 2030. However, less than one-quarter of women within reproductive age in Nigeria uses modern contraceptive methods despite its importance. Hence, this study aims at examining the influence of individual and community level factors on the use of modern contraceptive method. METHODS: The study is a secondary analysis of linked household and Service Delivery Point datasets from a 2018 survey conducted by Performance, Monitoring and Accountability in Nigeria. Data was abstracted for a total of 9126 sexually active women within the ages of 15-49 years across 295 enumeration areas in seven States. A 2-level binary logistic regression was used to examine the association between study variables and the use of modern contraceptives while adjusting for the clustering effect. RESULTS: There was significant influence of educational level, marital status, parity, socio-economic status, fertility intention, and awareness of family planning methods on the use of modern contraceptives. Also, women who perceived support from someone in the community on family planning were more likely to use modern contraceptive unlike those without such support. Those who believed that contraceptive methods are used by almost all and some of their friends or relatives were more likely to use modern contraceptive compared to those who think otherwise. CONCLUSIONS: The study shows the need to reduce inequalities between FP utilization across women with different socio-economic status as well as increasing the awareness for modern contraceptive methods.
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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 | 0.000 | 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 | 0.000 |
| 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".