Focus on Abortion: Article

An Application of the List Experiment to Estimate Abortion Prevalence in Karachi, Pakistan

Sarah Huber-Krum, Harvard T.H. Chan School of Public Health Kristy Hackett, Harvard T.H. Chan School of Public Health Navdep Kaur, Harvard T.H. Chan School of Public Health Sidrah Nausheen, Aga Khan University Sajid Soofi, Aga Khan University David Canning, Harvard T.H. Chan School of Public Health Iqbal Shah, Harvard T.H. Chan School of Public Health

First published online:

| DOI: https://doi.org/10.1363/46e0520
Abstract / Summary

Abortion is particularly difficult to measure, especially in legally restrictive settings such as Pakistan. The List Experiment—a technique for measuring sensitive health behaviors indirectly—may minimize respondents’ underreporting of abortion due to stigma or legal restrictions, but has not been previously applied to estimate abortion prevalence in Pakistan.


A sample of 4,159 married women of reproductive age were recruited from two communities of Karachi in 2018. Participants completed a survey that included a double list experiment to measure lifetime abortion prevalence, as well as direct questions about abortion and other background characteristics. Data were used to calculate direct and indirect estimates of abortion prevalence for the overall sample and by sociodemographic characteristics, as well as to test for a design effect. Regression analyses were conducted to examine associations between characteristics and abortion reporting from direct questioning and the list experiment.


The estimate of abortion prevalence from the list experiment was 16%; the estimate from the direct question was 8%. No evidence of a design effect was found. Abortion reporting was associated with most selected characteristics in the regression model for direct questioning, but with few in the list experiment models.


That the estimate of abortion prevalence in Karachi generated from the list experiment was twice that generated from direct questioning suggests that the indirect method reduced underreporting, and may have utility to estimate abortion in similar settings and to improve the accuracy of data collecting for other sensitive health topics.

Author's Affiliations

Sarah Huber-Krum and Kristy Hackett are research associates, Navdep Kaur is data manager, David Canning is professor and Iqbal Shah is principal research scientist—all with Harvard T.H. Chan School of Public Health, Cambridge, MA, USA. Sidrah Nausheen and Sajid Soofi are assistant professors—both with Aga Khan University, Karachi, Pakistan.


The views expressed in this publication do not necessarily reflect those of the Guttmacher Institute.