ArticleScientific reports2025
Trend and multivariate decomposition analysis of modern contraceptive utilization among women in Ethiopia.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Unmet need for family planning among reproductive-age women living with HIV in Africa: a systematic review and meta-analysis.BMC women's health · 2026Pooled it
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Analyzing the trend and identifying the factors influencing the utilization of modern contraceptives is essential for designing effective measures to improve reproductive health and economic development to ensure universal access to family planning services. This study aimed to investigate the trends in modern contraceptive use among women of reproductive age in Ethiopia and the factors influencing these trends. Data from the 2014 to 2019 Performance Monitoring and Accountability/Action Survey datasets were analyzed, with 4422 women in 2014, 5113 in 2015, 5071 in 2016, 4927 in 2017, 4981 in 2018, and 6117 in 2019 included. Data analysis was conducted using Stata version 16.0 statistical software. Given the sample disproportionality, survey design considerations were taken into account by applying probability weights. The sample weight was utilized with weighting factors provided in the PMA data to address the complex survey design. The 'svy' Stata command was applied to consider the clustering effect before descriptive statistical analysis. The trend was examined based on selected characteristics, with the primary statistical parameter being the trend of modern contraceptive utilization. The trends of modern contraceptive utilization for each year from 2014 to 2019 were calculated. Then, logit-based decomposition analysis was used to identify the factors driving changes in modern contraceptive utilization. Statistical significance was determined at a P value of less than 0.05, and results were presented as decomposition coefficients and percentages. Additionally, we conducted data smoothing to predict the future trend of modern contraceptive utilization and did not visually observe a distinct trend. We explored different time-series models such as linear, quadratic, exponential, and exponential smoothing. The results showed that the exponential smoothing trend model provided the most accurate fit, with the lowest standard error of estimate, sum square error, and highest adjusted R
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