Social network-based measurement of abortion incidence: promising findings from population-based surveys in Nigeria, Cote d’Ivoire, and Rajasthan, India
Abstract Background Monitoring abortion rates is highly relevant for demographic and public health considerations, yet its reliable estimation is fraught with uncertainty due to lack of complete national health facility service statistics and bias in self-reported survey data. In this study, we aim...
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doaj-c8f1d4ac21cd48ff8f36ae23449ebeaa2020-11-25T03:52:06ZengBMCPopulation Health Metrics1478-79542020-10-0118111510.1186/s12963-020-00235-ySocial network-based measurement of abortion incidence: promising findings from population-based surveys in Nigeria, Cote d’Ivoire, and Rajasthan, IndiaSuzanne O. Bell0Mridula Shankar1Elizabeth Omoluabi2Anoop Khanna3Hyacinthe Kouakou Andoh4Funmilola OlaOlorun5Danish Ahmad6Georges Guiella7Saifuddin Ahmed8Caroline Moreau9Department of Population, Family and Reproductive Health, Johns Hopkins Bloomberg School of Public HealthDepartment of Population, Family and Reproductive Health, Johns Hopkins Bloomberg School of Public HealthDepartment of Statistics and Population Studies, University of the Western CapeIndian Institute of Health Management ResearchProgramme National de Santé de la Mère et de l’Enfant (PNSME)College of Medicine, University of IbadanIndian Institute of Health Management ResearchInstitut Supérieur des Sciences de la Population (ISSP), University of OuagadougouDepartment of Population, Family and Reproductive Health, Johns Hopkins Bloomberg School of Public HealthDepartment of Population, Family and Reproductive Health, Johns Hopkins Bloomberg School of Public HealthAbstract Background Monitoring abortion rates is highly relevant for demographic and public health considerations, yet its reliable estimation is fraught with uncertainty due to lack of complete national health facility service statistics and bias in self-reported survey data. In this study, we aim to test the confidante methodology for estimating abortion incidence rates in Nigeria, Cote d’Ivoire, and Rajasthan, India, and develop methods to adjust for violations of assumptions. Methods In population-based surveys in each setting, female respondents of reproductive age reported separately on their two closest confidantes’ experience with abortion, in addition to reporting about their own experiences. We used descriptive analyses and design-based F tests to test for violations of method assumptions. Using post hoc analytical techniques, we corrected for biases in the confidante sample to improve the validity and precision of the abortion incidence estimates produced from these data. Results Results indicate incomplete transmission of confidante abortion knowledge, a biased confidante sample, but reduced social desirability bias when reporting on confidantes' abortion incidences once adjust for assumption violations. The extent to which the assumptions were met differed across the three contexts. The respondent 1-year pregnancy removal rate was 18.7 (95% confidence interval (CI) 14.9–22.5) abortions per 1000 women of reproductive age in Nigeria, 18.8 (95% CI 11.8–25.8) in Cote d’Ivoire, and 7.0 (95% CI 4.6–9.5) in India. The 1-year adjusted abortion incidence rates for the first confidantes were 35.1 (95% CI 31.1–39.1) in Nigeria, 31.5 (95% CI 24.8–38.1) in Cote d’Ivoire, and 15.2 (95% CI 6.1–24.4) in Rajasthan, India. Confidante two’s rates were closer to confidante one incidences than respondent incidences. The adjusted confidante one and two incidence estimates were significantly higher than respondent incidences in all three countries. Conclusions Findings suggest that the confidante approach may present an opportunity to address some abortion-related data deficiencies but require modeling approaches to correct for biases due to violations of social network-based method assumptions. The performance of these methodologies varied based on geographical and social context, indicating that performance may be better in settings where abortion is legally and socially restricted.http://link.springer.com/article/10.1186/s12963-020-00235-yAbortionMeasurementSurvey |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Suzanne O. Bell Mridula Shankar Elizabeth Omoluabi Anoop Khanna Hyacinthe Kouakou Andoh Funmilola OlaOlorun Danish Ahmad Georges Guiella Saifuddin Ahmed Caroline Moreau |
spellingShingle |
Suzanne O. Bell Mridula Shankar Elizabeth Omoluabi Anoop Khanna Hyacinthe Kouakou Andoh Funmilola OlaOlorun Danish Ahmad Georges Guiella Saifuddin Ahmed Caroline Moreau Social network-based measurement of abortion incidence: promising findings from population-based surveys in Nigeria, Cote d’Ivoire, and Rajasthan, India Population Health Metrics Abortion Measurement Survey |
author_facet |
Suzanne O. Bell Mridula Shankar Elizabeth Omoluabi Anoop Khanna Hyacinthe Kouakou Andoh Funmilola OlaOlorun Danish Ahmad Georges Guiella Saifuddin Ahmed Caroline Moreau |
author_sort |
Suzanne O. Bell |
title |
Social network-based measurement of abortion incidence: promising findings from population-based surveys in Nigeria, Cote d’Ivoire, and Rajasthan, India |
title_short |
Social network-based measurement of abortion incidence: promising findings from population-based surveys in Nigeria, Cote d’Ivoire, and Rajasthan, India |
title_full |
Social network-based measurement of abortion incidence: promising findings from population-based surveys in Nigeria, Cote d’Ivoire, and Rajasthan, India |
title_fullStr |
Social network-based measurement of abortion incidence: promising findings from population-based surveys in Nigeria, Cote d’Ivoire, and Rajasthan, India |
title_full_unstemmed |
Social network-based measurement of abortion incidence: promising findings from population-based surveys in Nigeria, Cote d’Ivoire, and Rajasthan, India |
title_sort |
social network-based measurement of abortion incidence: promising findings from population-based surveys in nigeria, cote d’ivoire, and rajasthan, india |
publisher |
BMC |
series |
Population Health Metrics |
issn |
1478-7954 |
publishDate |
2020-10-01 |
description |
Abstract Background Monitoring abortion rates is highly relevant for demographic and public health considerations, yet its reliable estimation is fraught with uncertainty due to lack of complete national health facility service statistics and bias in self-reported survey data. In this study, we aim to test the confidante methodology for estimating abortion incidence rates in Nigeria, Cote d’Ivoire, and Rajasthan, India, and develop methods to adjust for violations of assumptions. Methods In population-based surveys in each setting, female respondents of reproductive age reported separately on their two closest confidantes’ experience with abortion, in addition to reporting about their own experiences. We used descriptive analyses and design-based F tests to test for violations of method assumptions. Using post hoc analytical techniques, we corrected for biases in the confidante sample to improve the validity and precision of the abortion incidence estimates produced from these data. Results Results indicate incomplete transmission of confidante abortion knowledge, a biased confidante sample, but reduced social desirability bias when reporting on confidantes' abortion incidences once adjust for assumption violations. The extent to which the assumptions were met differed across the three contexts. The respondent 1-year pregnancy removal rate was 18.7 (95% confidence interval (CI) 14.9–22.5) abortions per 1000 women of reproductive age in Nigeria, 18.8 (95% CI 11.8–25.8) in Cote d’Ivoire, and 7.0 (95% CI 4.6–9.5) in India. The 1-year adjusted abortion incidence rates for the first confidantes were 35.1 (95% CI 31.1–39.1) in Nigeria, 31.5 (95% CI 24.8–38.1) in Cote d’Ivoire, and 15.2 (95% CI 6.1–24.4) in Rajasthan, India. Confidante two’s rates were closer to confidante one incidences than respondent incidences. The adjusted confidante one and two incidence estimates were significantly higher than respondent incidences in all three countries. Conclusions Findings suggest that the confidante approach may present an opportunity to address some abortion-related data deficiencies but require modeling approaches to correct for biases due to violations of social network-based method assumptions. The performance of these methodologies varied based on geographical and social context, indicating that performance may be better in settings where abortion is legally and socially restricted. |
topic |
Abortion Measurement Survey |
url |
http://link.springer.com/article/10.1186/s12963-020-00235-y |
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