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Estimating the incidence of abortion: a comparison of five approaches in Ghana
  1. Sarah C Keogh1,
  2. Easmon Otupiri2,
  3. Doris W Chiu1,
  4. Chelsea B Polis1,3,
  5. Rubina Hussain1,
  6. Suzanne O Bell4,
  7. Emmanuel K Nakua5,
  8. Roderick Larsen-Reindorf2
  1. 1Guttmacher Institute, New York, New York, USA
  2. 2Department of Population, Family and Reproductive Health, School of Public Health, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
  3. 3Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
  4. 4Department of Population, Family and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
  5. 5Department of Epidemiology and Biostatistics, Kwame Nkrumah University of Science and Technology, Kumasi, Ashanti, Ghana
  1. Correspondence to Dr Sarah C Keogh; skeogh{at}guttmacher.org

Abstract

Introduction Induced abortion estimates are critical for reproductive health programming. In countries like Ghana where abortion is somewhat legally restricted and highly stigmatised, official records are incomplete and different approaches are needed to measure abortion incidence. We conducted a study in Ghana to test five methodologies for estimating incidence: direct reporting, the list experiment, the confidante method, the Abortion Incidence Complications Method (AICM) and a modified AICM.

Methods The direct reporting, list experiment and confidante method were implemented through a nationally representative community-based survey (CBS) of 4722 women. The AICM used data from a nationally representative health facilities survey (HFS) and a knowledgeable informant survey. The modified AICM combined CBS and HFS data. For each approach, we calculated abortion incidence nationally and for Ghana’s three ecological zones and conducted checks to determine the most internally valid approaches.

Results National incidence estimates ranged from 27 per 1000 (AICM) to 61 (confidante method). The Northern zone displayed lower rates than the other two zones for all approaches. Validity and reliability checks found that the list experiment was invalid. The approaches that stood up to the internal validity checks and were most reliable were the direct reporting, confidante method and modified AICM. These approaches provide lower and upper bound estimates for the abortion rate, and the mean of the estimates from the three approaches yields a final abortion rate of 44 per 1000 and an unintended pregnancy rate of 103 per 1000.

Conclusions Comparing five approaches to estimating abortion enabled cross-validation of findings and highlighted strengths, pitfalls and requirements of each approach that can inform abortion estimation in other settings.

  • epidemiology
  • medical demography
  • public health
  • community-based survey
  • maternal health
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Footnotes

  • Handling editor Sanni Yaya

  • Twitter @cbpolis

  • Contributors Contributions to the AICM component of this study are detailed elsewhere. SCK, EO, CBP, SOB, EKN and RL-R: led the conceptualisation of the project. SCK, EO, DWC, RH, CBP and SOB: participated in developing aspects of the methodological approach used. SCK, DWC, RH and SOB: participated in programming and implementing computer code for the analysis. SCK, DWC and RH: verified the overall reproducibility of research outputs. SCK, DWC and RH: conducted the formal analysis. EO, EKN and RL-R: led the data collection efforts. SCK, EO, DWC, RH, CBP, SOB and EKN: provided resources in terms of study materials, contact with respondents, and computing resources. SCK, DWC, RH, SOB and EKN: performed data curation to manage and clean data. SCK wrote the original draft of the manuscript. SCK, EO, DWC, RH, CBP, SOB, EKN and RL-R: participated in reviewing and editing the draft. SCK, CBP, EO and SOB: had oversight and leadership responsibility for research activity planning and execution, including mentorship external to the core team. SCK, EO, DWC, RH, CBP, SOB and EKN: were responsible for managing and coordinating research activity planning and execution. SCK and CBP: were responsible for acquisition of the funding support for the project, leading to this publication.

  • Funding UK Aid from the UK Government, and Dutch Ministry of Foreign Affairs.

  • Disclaimer The views expressed are those of the authors and do not necessarily reflect the positions and policies of the donors.

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement Data are available upon request. De-identified versions of the raw Community-Based Survey, Health Facilities Survey and Knowledgeable Informants Survey datasets collected by the authors and used in this analysis are available from the Guttmacher Institute upon reasonable request to researchers who wish to use the data for scholarly analysis. To discuss obtaining copies of these datasets, please contact popcenter@guttmacher.org with the detailed protocol for your proposed study, and information about the funding and resources you have to carry out the study.