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Evaluating changes in the prevalence of female genital mutilation/cutting among 0-14 years old girls in Nigeria using data from multiple surveys: A novel Bayesian hierarchical spatio-temporal model

Female genital mutilation/cutting (FGM/C) is considered a public health and human rights concern, mainly concentrated in Africa, and has been targeted for elimination under the sustainable development goals. Interventions aimed at ending the practice often rely on data from household surveys which e...

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Autores principales: Nnanatu, Chibuzor Christopher, Atilola, Glory, Komba, Paul, Mavatikua, Lubanzadio, Moore, Zhuzhi, Matanda, Dennis, Obianwu, Otibho, Kandala, Ngianga-Bakwin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7880428/
https://www.ncbi.nlm.nih.gov/pubmed/33577614
http://dx.doi.org/10.1371/journal.pone.0246661
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author Nnanatu, Chibuzor Christopher
Atilola, Glory
Komba, Paul
Mavatikua, Lubanzadio
Moore, Zhuzhi
Matanda, Dennis
Obianwu, Otibho
Kandala, Ngianga-Bakwin
author_facet Nnanatu, Chibuzor Christopher
Atilola, Glory
Komba, Paul
Mavatikua, Lubanzadio
Moore, Zhuzhi
Matanda, Dennis
Obianwu, Otibho
Kandala, Ngianga-Bakwin
author_sort Nnanatu, Chibuzor Christopher
collection PubMed
description Female genital mutilation/cutting (FGM/C) is considered a public health and human rights concern, mainly concentrated in Africa, and has been targeted for elimination under the sustainable development goals. Interventions aimed at ending the practice often rely on data from household surveys which employ complex designs leading to outcomes that are not totally independent, thus requiring advanced statistical techniques. Combining data from multiple surveys within robust statistical framework holds promise to provide more precise estimates due to increased sample size, and accurately identify ‘hotspots’ and allow for assessment of changes over time. In this study, rich datasets from six (6) successive waves of the Nigeria Demographic and Health Surveys and Multiple Indicator Cluster Surveys undertaken between 2003 and 2016/17, were combined and analyzed in order to better assess changes in the likelihood and prevalence of FGM/C among 0-14-year old girls in Nigeria. We used Bayesian hierarchical regression models which explicitly accounted for the inherent spatial and temporal autocorrelations within the data while simultaneously adjusting for variations due to different survey methods and the effects of linear and non-linear covariates. Parameters were estimated using Markov chain Mote Carlo techniques and model fit assessments were based on Deviance Information Criterion. Results show that prevalence of FGM/C among 0–14 years old girls in Nigeria varied over time and across geographical locations and peaked in 2008 with a shift from South to North. A girl was more likely to be cut if her mother was cut, supported FGM/C continuation, or had no higher education. The effects of mother’s age, wealth and type of residence (urban-rural) were no longer significant in 2016. These results reflect the gains of interventions over the years, but also echo the belief that FGM/C is a social norm thus requiring tailored all-inclusive interventions for the total abandonment of FGM/C in Nigeria.
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spelling pubmed-78804282021-02-19 Evaluating changes in the prevalence of female genital mutilation/cutting among 0-14 years old girls in Nigeria using data from multiple surveys: A novel Bayesian hierarchical spatio-temporal model Nnanatu, Chibuzor Christopher Atilola, Glory Komba, Paul Mavatikua, Lubanzadio Moore, Zhuzhi Matanda, Dennis Obianwu, Otibho Kandala, Ngianga-Bakwin PLoS One Research Article Female genital mutilation/cutting (FGM/C) is considered a public health and human rights concern, mainly concentrated in Africa, and has been targeted for elimination under the sustainable development goals. Interventions aimed at ending the practice often rely on data from household surveys which employ complex designs leading to outcomes that are not totally independent, thus requiring advanced statistical techniques. Combining data from multiple surveys within robust statistical framework holds promise to provide more precise estimates due to increased sample size, and accurately identify ‘hotspots’ and allow for assessment of changes over time. In this study, rich datasets from six (6) successive waves of the Nigeria Demographic and Health Surveys and Multiple Indicator Cluster Surveys undertaken between 2003 and 2016/17, were combined and analyzed in order to better assess changes in the likelihood and prevalence of FGM/C among 0-14-year old girls in Nigeria. We used Bayesian hierarchical regression models which explicitly accounted for the inherent spatial and temporal autocorrelations within the data while simultaneously adjusting for variations due to different survey methods and the effects of linear and non-linear covariates. Parameters were estimated using Markov chain Mote Carlo techniques and model fit assessments were based on Deviance Information Criterion. Results show that prevalence of FGM/C among 0–14 years old girls in Nigeria varied over time and across geographical locations and peaked in 2008 with a shift from South to North. A girl was more likely to be cut if her mother was cut, supported FGM/C continuation, or had no higher education. The effects of mother’s age, wealth and type of residence (urban-rural) were no longer significant in 2016. These results reflect the gains of interventions over the years, but also echo the belief that FGM/C is a social norm thus requiring tailored all-inclusive interventions for the total abandonment of FGM/C in Nigeria. Public Library of Science 2021-02-12 /pmc/articles/PMC7880428/ /pubmed/33577614 http://dx.doi.org/10.1371/journal.pone.0246661 Text en © 2021 Nnanatu et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Nnanatu, Chibuzor Christopher
Atilola, Glory
Komba, Paul
Mavatikua, Lubanzadio
Moore, Zhuzhi
Matanda, Dennis
Obianwu, Otibho
Kandala, Ngianga-Bakwin
Evaluating changes in the prevalence of female genital mutilation/cutting among 0-14 years old girls in Nigeria using data from multiple surveys: A novel Bayesian hierarchical spatio-temporal model
title Evaluating changes in the prevalence of female genital mutilation/cutting among 0-14 years old girls in Nigeria using data from multiple surveys: A novel Bayesian hierarchical spatio-temporal model
title_full Evaluating changes in the prevalence of female genital mutilation/cutting among 0-14 years old girls in Nigeria using data from multiple surveys: A novel Bayesian hierarchical spatio-temporal model
title_fullStr Evaluating changes in the prevalence of female genital mutilation/cutting among 0-14 years old girls in Nigeria using data from multiple surveys: A novel Bayesian hierarchical spatio-temporal model
title_full_unstemmed Evaluating changes in the prevalence of female genital mutilation/cutting among 0-14 years old girls in Nigeria using data from multiple surveys: A novel Bayesian hierarchical spatio-temporal model
title_short Evaluating changes in the prevalence of female genital mutilation/cutting among 0-14 years old girls in Nigeria using data from multiple surveys: A novel Bayesian hierarchical spatio-temporal model
title_sort evaluating changes in the prevalence of female genital mutilation/cutting among 0-14 years old girls in nigeria using data from multiple surveys: a novel bayesian hierarchical spatio-temporal model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7880428/
https://www.ncbi.nlm.nih.gov/pubmed/33577614
http://dx.doi.org/10.1371/journal.pone.0246661
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