Global, regional, and subregional classification of abortions by safety, 2010-14: estimates from a Bayesian hierarchical model

Lancet. 2017 Nov 25;390(10110):2372-2381. doi: 10.1016/S0140-6736(17)31794-4. Epub 2017 Sep 27.


Background: Global estimates of unsafe abortions have been produced for 1995, 2003, and 2008. However, reconceptualisation of the framework and methods for estimating abortion safety is needed owing to the increased availability of simple methods for safe abortion (eg, medical abortion), the increasingly widespread use of misoprostol outside formal health systems in contexts where abortion is legally restricted, and the need to account for the multiple factors that affect abortion safety.

Methods: We used all available empirical data on abortion methods, providers, and settings, and factors affecting safety as covariates within a Bayesian hierarchical model to estimate the global, regional, and subregional distributions of abortion by safety categories. We used a three-tiered categorisation based on the WHO definition of unsafe abortion and WHO guidelines on safe abortion to categorise abortions as safe or unsafe and to further divide unsafe abortions into two categories of less safe and least safe.

Findings: Of the 55· 7 million abortions that occurred worldwide each year between 2010-14, we estimated that 30·6 million (54·9%, 90% uncertainty interval 49·9-59·4) were safe, 17·1 million (30·7%, 25·5-35·6) were less safe, and 8·0 million (14·4%, 11·5-18·1) were least safe. Thus, 25·1 million (45·1%, 40·6-50·1) abortions each year between 2010 and 2014 were unsafe, with 24·3 million (97%) of these in developing countries. The proportion of unsafe abortions was significantly higher in developing countries than developed countries (49·5% vs 12·5%). When grouped by the legal status of abortion, the proportion of unsafe abortions was significantly higher in countries with highly restrictive abortion laws than in those with less restrictive laws.

Interpretation: Increased efforts are needed, especially in developing countries, to ensure access to safe abortion. The paucity of empirical data is a limitation of these findings. Improved in-country data for health services and innovative research to address these gaps are needed to improve future estimates.

Funding: UNDP/UNFPA/UNICEF/WHO/World Bank Special Programme of Research, Development and Research Training in Human Reproduction; David and Lucile Packard Foundation; UK Aid from the UK Government; Dutch Ministry of Foreign Affairs; Norwegian Agency for Development Cooperation.

Publication types

  • Comparative Study

MeSH terms

  • Abortion, Induced / statistics & numerical data*
  • Abortion, Legal / statistics & numerical data*
  • Abortion, Therapeutic / statistics & numerical data*
  • Bayes Theorem
  • Cohort Studies
  • Databases, Factual
  • Developed Countries / statistics & numerical data
  • Developing Countries / statistics & numerical data
  • Female
  • Global Health*
  • Humans
  • Internationality
  • Patient Safety*
  • Pregnancy
  • Prevalence
  • Risk Assessment
  • United Nations