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Estimating geographic variations in the determinants of attitude towards the practice of female genital mutilation in Nigeria

Published online by Cambridge University Press:  27 December 2018

Ezra Gayawan Open the ORCID record for Ezra Gayawan [Opens in a new window]  and
Rukayat Salewa Lateef
Ezra Gayawan*
Affiliation:
Biostatistics and Spatial Statistics Laboratory, Department of Statistics, Federal University of Technology, Akure, Nigeria
Rukayat Salewa Lateef
Affiliation:
Biostatistics and Spatial Statistics Laboratory, Department of Statistics, Federal University of Technology, Akure, Nigeria
*
*Corresponding author. Email: [email protected]
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Abstract

Female genital mutilation (FGM) has persisted in Nigeria despite the very harmful effects on its victims. Massive inequality in the demographic and socioeconomic status of the Nigerian populace, coupled with marked differences in cultural values, have led to lopsided patterns of most health indicators based on the geographical location. The risk factors of health indicators are equally expected to vary according to location. This study aimed to explain the spatial variations in the risk factors for female cutting in Nigeria. Data were from the geo-referenced 2013 Nigeria Demographic and Health Survey. The objective was to estimate the spatially varying relationships of the factors influencing women’s attitude towards female cutting in Nigeria and to identify how the variables exact influence across the states using geographically weighted logistic regression analysis – a technique that allows for spatially varying relationships among variables to be established. The results showed that women’s higher educational level and higher household wealth lowered the desire for continuation of FGM everywhere in the country, but the effects of most other variables varied in direction, strength and magnitude. The findings suggest the use of local approaches to address the factors that encourage the continuation of female cutting in Nigeria.

Keywords

NigeriaFemale Genital MutilationGeographically Weighted Regression
Type
Research Article
Information
Journal of Biosocial Science , Volume 51 , Issue 5 , September 2019 , pp. 645 - 657
Copyright
© Cambridge University Press, 2018 

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