IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0053346.html
   My bibliography  Save this article

Measuring Unsafe Abortion-Related Mortality: A Systematic Review of the Existing Methods

Author

Listed:
  • Caitlin Gerdts
  • Divya Vohra
  • Jennifer Ahern

Abstract

Background: The WHO estimates that 13% of maternal mortality is due to unsafe abortion, but challenges with measurement and data quality persist. To our knowledge, no systematic assessment of the validity of studies reporting estimates of abortion-related mortality exists. Study Design: To be included in this study, articles had to meet the following criteria: (1) published between September 1st, 2000-December 1st, 2011; (2) utilized data from a country where abortion is “considered unsafe”; (3) specified and enumerated causes of maternal death including “abortion”; (4) enumerated ≥100 maternal deaths; (5) a quantitative research study; (6) published in a peer-reviewed journal. Results: 7,438 articles were initially identified. Thirty-six studies were ultimately included. Overall, studies rated “Very Good” found the highest estimates of abortion related mortality (median 16%, range 1–27.4%). Studies rated “Very Poor” found the lowest overall proportion of abortion related deaths (median: 2%, range 1.3–9.4%). Conclusions: Improvements in the quality of data collection would facilitate better understanding global abortion-related mortality. Until improved data exist, better reporting of study procedures and standardization of the definition of abortion and abortion-related mortality should be encouraged.

Suggested Citation

  • Caitlin Gerdts & Divya Vohra & Jennifer Ahern, 2013. "Measuring Unsafe Abortion-Related Mortality: A Systematic Review of the Existing Methods," PLOS ONE, Public Library of Science, vol. 8(1), pages 1-14, January.
  • Handle: RePEc:plo:pone00:0053346
    DOI: 10.1371/journal.pone.0053346
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0053346
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0053346&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0053346?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Sander Greenland, 2001. "Sensitivity Analysis, Monte Carlo Risk Analysis, and Bayesian Uncertainty Assessment," Risk Analysis, John Wiley & Sons, vol. 21(4), pages 579-584, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sander Greenland, 2005. "Multiple‐bias modelling for analysis of observational data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(2), pages 267-306, March.
    2. Richard R. Lester & Laura C. Green & Igor Linkov, 2007. "Site‐Specific Applications of Probabilistic Health Risk Assessment: Review of the Literature Since 2000," Risk Analysis, John Wiley & Sons, vol. 27(3), pages 635-658, June.
    3. Sander Greenland, 2004. "Bounding Analysis as an Inadequately Specified Methodology," Risk Analysis, John Wiley & Sons, vol. 24(5), pages 1085-1092, October.
    4. Sander Greenland, 2005. "Discussion on "Statistical Issues Arising in the Women's Health Initiative"," Biometrics, The International Biometric Society, vol. 61(4), pages 920-921, December.
    5. Olivier Catelinois & Dominique Laurier & Pierre Verger & Agnès Rogel & Marc Colonna & Marianne Ignasiak & Denis Hémon & Margot Tirmarche, 2005. "Uncertainty and Sensitivity Analysis in Assessment of the Thyroid Cancer Risk Related to Chernobyl Fallout in Eastern France," Risk Analysis, John Wiley & Sons, vol. 25(2), pages 243-252, April.
    6. Paul Gustafson, 2006. "Sample size implications when biases are modelled rather than ignored," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(4), pages 865-881, October.
    7. Sander Greenland, 2023. "Connecting simple and precise P‐values to complex and ambiguous realities (includes rejoinder to comments on “Divergence vs. decision P‐values”)," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 50(3), pages 899-914, September.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0053346. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.