MODEL-BASED ESTIMATES OF FAMILY PLANNING INDICATORS

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National, regional and global estimates are based on a Bayesian hierarchical model of contraceptive prevalence and unmet need for family planning. For each country, the expected transition is modelled from low to higher levels of contraceptive prevalence with a logistic growth curve, where the pace of contraceptive prevalence is expected to increase initially, up to a maximum pace, after which it decreases when prevalence approaches higher levels. To allow for deviations from a smooth path of growth in prevalence, as indicated by the data, the logistic growth curve is combined with a time series model. The trend in the use of modern contraceptive methods as a proportion of total contraceptive prevalence is modelled in a similar manner, using a country-specific logistic growth curve combined with a time series model.

A Bayesian hierarchical model is used to estimate the parameters of the logistic growth curves for each country: the asymptote or expected final level, the pace of adoption and the time-point of inflection in the curve (or the year when the pace of adoption is at its peak). The estimates are based on the observations for the country of interest as well as on the subregional, regional and global experience. This approach implies that 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 observations.

Levels of total contraceptive prevalence are used to estimate the percentage of women with an unmet need for family planning based on an expected (and empirically observed) statistical relationship between total contraceptive prevalence and unmet need. Country-specific estimates of unmet need were obtained by modelling the general relation between contraceptive prevalence and unmet need using a hierarchical approach and a time series model to capture country-specific changes in trends of unmet need. For countries without data on unmet need, estimates of unmet need were based on each country’s estimates of total contraceptive prevalence, the relation between contraceptive prevalence and unmet need and the distribution of country-specific levels of unmet need in the respective subregion.

Estimates of contraceptive prevalence and unmet need for family planning are based on all available data in a country. Additional parameters are included in the model to account for the potential misclassification of women in a subset of surveys and to account for potential differences in prevalence outcomes associated with surveys where the sampled population was not representative of married or in-union women aged 15-49but consisted instead of women in different age groups, all sexually-active women regardless of marital status, or where the sample was not nationally-representative.

Regional and global estimates are weighted averages of the model-based country estimates, using the number of married or in-union women aged 15-49 for the reference year in each country. The estimated weights were derived from data on the proportion of women who were married or in a union in each country as presented in World Marriage Data 2008 (United Nations publication, POP/DB/Mar/Rev2008), estimates of the proportion of women living in cohabitation for European countries (OECD, Table SF3.3.A Partnership and prevalence of cohabitation, OECD Family Database, 2011. Available from http://www.oecd.org/ social/family/database) and from estimates of the number of women by age group obtained from World Population Prospects: The 2010 Revision (United Nations publication, Extended Dataset, Sales No. 11.XIII.7).

A Markov Chain Monte Carlo algorithm was used to generate samples of the posterior distributions of the parameters. This approach produced a set of trajectories of contraceptive prevalence and unmet need for family planning for each country. Functions of these outcomes were also produced to measure other indicators, such as the percentage of demand for family planning that is satisfied (the ratio of contraceptive prevalence over the sum of contraceptive prevalence and the unmet need for family planning). Uncertainty intervals (80 and 95 per cent) were also computed for all indicators of interest.

The model-based estimates of modern and traditional prevalence for a country or aggregate group (e.g., region) do not always sum to the estimated total contraceptive prevalence for the country or aggregate group because the trajectory that gives the median for modern method prevalence does not have to correspond to the same posterior draw as the trajectory that gives the median for traditional method prevalence. However, the majority of differences are small (less than two percentage points for the period 1990-2015 for 92 per cent of countries or areas and one percentage point or less for aggregate groups for the period 1990-2015). The same issue applies to comparisons of model-based estimates of total demand for family planning compared with the sum of model-based estimates of contraceptive prevalence and unmet need for family planning.

Additional details of the methodology are available in the technical paper: Alkema, Leontine, Vladimira Kantorova, Clare Menozzi and Ann Biddlecom (forthcoming). 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. (accepted for publication in The Lancet).

 

Country and area classification

The designations employed in this publication do not imply the expression of any opinion whatsoever on the part of the Secretariat of the United Nations concerning the legal status of any country, territory or area or of its authorities, or concerning the delimitation of its frontiers or boundaries.

The designations “more developed regions” and “less developed regions” are used for statistical convenience and do not necessarily express a judgment about the stage reached by a particular country or area in the development process. The term “country” as used in this publication also refers, as appropriate, to territories or areas. The more developed regions comprise all regions of Europe plus Northern America, Australia/New Zealand and Japan. The less developed regions comprise all regions of Africa, Asia (excluding Japan) and Latin America and the Caribbean, as well as Melanesia, Micronesia and Polynesia.

The lists of least developed countries (LDCs), land-locked developing countries (LLDC) and small island developing States are available from the UN Office of the High Representative for the Least Developed Countries, Landlocked Developing Countries and Small Island Developing States (of UN-OHRLLS). The group of least developed countries comprises 48 countries. Pending the official status, it was decided also to include South Sudan in the least developed countries for statistical purposes. Other less developed countries comprise the less developed regions excluding the least developed countries. The group of land-locked developing countries comprises 31 countries and the group of small island developing States comprises 52 countries. Lists of countries for each group are available from www.unohrlls.org.

The designation sub-Saharan Africa is commonly used to indicate all of Africa except northern Africa, with the Sudan included in sub-Saharan Africa.

Country names and the composition of geographical areas follow those presented in Standard Country or Area Codes for Statistical Use, Revision 4, available from: http://unstats.un.org/unsd/methods/m49/m49.htm

Suggested citation: United Nations, Department of Economic and Social Affairs, Population Division (2012). World Contraceptive Use 2012 (POP/DB/CP/Rev2012).