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Analysing Normative Influences on the Prevalence of Female Genital Mutilation/Cutting among 0–14 Years Old Girls in Senegal: A Spatial Bayesian Hierarchical Regression Approach

Author

Listed:
  • Ngianga-Bakwin Kandala

    (Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry CV4 7AL, UK
    Division of Epidemiology and Biostatistics, School of Public Health, University of the Witwatersrand, Johannesburg 2193, South Africa)

  • Chibuzor Christopher Nnanatu

    (Department of Mathematics, Physics & Electrical Engineering (MPEE), Northumbria University, Newcastle NE1 8ST, UK)

  • Glory Atilola

    (Department of Mathematics, Physics & Electrical Engineering (MPEE), Northumbria University, Newcastle NE1 8ST, UK)

  • Paul Komba

    (Department of Mathematics, Physics & Electrical Engineering (MPEE), Northumbria University, Newcastle NE1 8ST, UK)

  • Lubanzadio Mavatikua

    (Department of Mathematics, Physics & Electrical Engineering (MPEE), Northumbria University, Newcastle NE1 8ST, UK)

  • Zhuzhi Moore

    (Independent Consultant, Vienna, VA 22182, USA)

  • Dennis Matanda

    (Population Council, Avenue 5, 3rd Floor, Rose Avenue, Nairobi, Kenya)

Abstract

Background: Female genital mutilation/cutting (FGM/C) is a harmful traditional practice affecting the health and rights of women and girls. This has raised global attention on the implementation of strategies to eliminate the practice in conformity with the Sustainable Development Goals (SDGs). A recent study on the trends of FGM/C among Senegalese women (aged 15–49) which examined how individual- and community-level factors affected the practice, found significant regional variations in the practice. However, the dynamics of the practice among girls (0–14 years old) is not fully understood. This paper attempts to fill this knowledge gap by investigating normative influences in the persistence of the practice among Senegalese girls, identify and map ‘hotspots’. Methods: We do so by using a class of Bayesian hierarchical geospatial modelling approach implemented in R statistical software (R Foundation for Statistical Computing, Vienna, Austria) using R2BayesX package. We employed Markov Chain Monte Carlo (MCMC) techniques for full Bayesian inference, while model fit and complexity assessment utilised deviance information criterion (DIC). Results: We found that a girl’s probability of cutting was higher if her mother was cut, supported FGM/C continuation or believed that the practice was a religious obligation. In addition, living in rural areas and being born to a mother from Diola, Mandingue, Soninke or Poular ethnic group increased a girl’s likelihood of being cut. The hotspots identified included Matam, Tambacounda and Kolda regions. Conclusions: Our findings offer a clearer picture of the dynamics of FGM/C practice among Senegalese girls and prove useful in informing evidence-based intervention policies designed to achieve the abandonment of the practice in Senegal.

Suggested Citation

  • Ngianga-Bakwin Kandala & Chibuzor Christopher Nnanatu & Glory Atilola & Paul Komba & Lubanzadio Mavatikua & Zhuzhi Moore & Dennis Matanda, 2021. "Analysing Normative Influences on the Prevalence of Female Genital Mutilation/Cutting among 0–14 Years Old Girls in Senegal: A Spatial Bayesian Hierarchical Regression Approach," IJERPH, MDPI, vol. 18(7), pages 1-26, April.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:7:p:3822-:d:530857
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    References listed on IDEAS

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