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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*
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: egayawan@futa.edu.ng
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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.

Information

Type
Research Article
Copyright
© Cambridge University Press, 2018 
Figure 0

Figure 1 Maps of Nigeria showing (a) the prevalence of FGM and (b) support for continuation of FGM.

Figure 1

Table 1 Frequency distribution of study women (percentages in parentheses) based on their view on the continuation of FGM in Nigeria

Figure 2

Figure 2 Marginal effects of women’s educational level (with ‘no education’ as reference) on level of support for the continuation of FGM by Nigerian states: (a) primary; (b) secondary; and (c) higher level education. The bars indicate the lowest and highest values of marginal estimates.

Figure 3

Figure 3 Marginal effects of rural–urban residency (with ‘urban’ as reference) on level of support for continuation of FGM by Nigerian states. The bars indicate the lowest and highest values of marginal estimates.

Figure 4

Figure 4 Marginal effects of household wealth index (with ‘poorest’ as reference): (a) poorer; (b) middle; (c) richer; and (d) richest wealth index. The bars indicate the lowest and highest values of marginal estimates.

Figure 5

Figure 5 Marginal effects of access to mass media (with ‘no access’ as reference): (a) newspaper/magazine; (b) radio; and (c) television. The bars indicate the lowest and highest values of marginal estimates.

Figure 6

Figure 6 Marginal effects of religious affiliation (with ‘traditional/none’ as reference): (a) Christianity and (b) Islam. The bars indicate the lowest and highest values of marginal estimates.

Figure 7

Figure 7 Marginal effects of ever-married (with ‘never-married’ as reference). The bars indicate the lowest and highest values of marginal estimates.

Figure 8

Figure 8 Marginal effects of working status (with ‘not working’ as reference). The bars indicate the lowest and highest values of marginal estimates.

Figure 9

Figure 9 Marginal effects of model intercept. The bars indicate the lowest and highest values of marginal estimates.