The Global Health Observatory
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The Global Health Observatory
Explore a world of health data
Contraceptive prevalence is the percentage of women who are currently using, or whose partner is currently using, at least one method of contraception, regardless of the method used.
For analytical purposes, contraceptive methods are often classified as either modern or traditional. Modern methods of contraception include female and male sterilization, the intra-uterine device (IUD), the implant, injectables, oral contraceptive pills, male and female condoms, vaginal barrier methods (including the diaphragm, cervical cap and spermicidal foam, jelly, cream and sponge), lactational amenorrhea method (LAM), emergency contraception and other modern methods not reported separately (e.g., the contraceptive patch or vaginal ring). Traditional methods of contraception include rhythm (e.g., fertility awareness-based methods, periodic abstinence), withdrawal and other traditional methods not reported separately.
For analytical and comparative purposes, country-level model-based estimates and projections are generated using a Bayesian hierarchical model (see references below).
At regional and global levels
In order to generate regional and global estimates for any given reference year, the Population Division/DESA uses a Bayesian hierarchical model, described in detail in:
Alkema et al. (2013) (Alkema, L., Kantorova, V., Menozzi, C., & Biddlecom, A. (2013). National, regional, and global rates and trends in contraceptive prevalence and unmet need for family planning between 1990 and 2015: a systematic and comprehensive analysis. The Lancet. 2013; 381(9878), 1642-1652. ) and Kantorová et al. (2020). (Kantorová V., M. C. Wheldon, P. Ueffing., A. N. Z. Dasgupta (2020). Estimating progress towards meeting women’s contraceptive needs in 185 countries: A Bayesian hierarchical modelling study. PLoS Medicine. 2020; 17(2):e1003026.)
Country-level, model-based estimates are only used for computing regional and global averages and are not used for global SDG reporting of trends at the country level. However, the model-based estimates are recommended to be used for analytical and comparative purposes. Since the model takes into account the relationship of family planning indicators - contraceptive use of any, modern and traditional methods, unmet need for family planning – the information from surveys that only provide data on contraceptive use (and have no information on unmet need for family planning) is considered as well. The model is providing estimates of the indicator for countries and years without direct survey data by extrapolating underlying trends determined using data across all countries. The model implicitly weights observations from other countries such that higher weights are given to observations from more similar countries. The fewer the number of observations for the country of interest, the more its estimates are driven by the experience of other countries, whereas for countries with many observations the results are determined to a greater extent by those empirical observations.
The Bayesian hierarchical model is used to generate regional and global estimates and projections of the indicator. Aggregate estimates and projections are weighted averages of the model-based country estimates, using the number of women aged 15-49 for the reference year in each country. The number of women aged 15-49 are taken from United Nations, Department of Economic and Social Affairs, Population Division (2024). World Population Prospects 2024. Numbers of women who are married or in a union are taken from United Nations, Department of Economic and Social Affairs, Population Division (2024). Estimates and Projections of Women of Reproductive Age Who Are Married or in a Union: 2022 Revision. New York: United Nations, which are estimates and projections based on data from United Nations, Department of Economic and Social Affairs, Population Division (2019). World Marriage Data 2019.
Details of the methodology are described in Kantorová et al (2020) and United Nations, Department of Economic and Social Affairs, Population Division (2024).