A Spatial Analysis of the Prevalence of Female Genital Mutilation/Cutting among 0-14-Year-Old Girls in Kenya

Abstract

Female genital mutilation/cutting (FGM/C), also known as female circumcision, is a global public health and human rights problem affecting women and girls. Several concerted efforts to eliminate the practice are underway in several sub-Saharan African countries where the practice is most prevalent. Studies have reported variations in the practice with some countries experiencing relatively slow decline in prevalence. This study investigates the roles of normative influences and related risk factors (e.g., geographic location) on the persistence of FGM/C among 0-14 years old girls in Kenya. The key objective is to identify and map hotspots (high risk regions). We fitted spatial and spatio-temporal models in a Bayesian hierarchical regression framework on two datasets extracted from successive Kenya Demographic and Health Surveys (KDHS) from 1998 to 2014. The models were implemented in R statistical software using Markov Chain Monte Carlo (MCMC) techniques for parameters estimation, while model fit and assessment employed deviance information criterion (DIC) and effective sample size (ESS). Results showed that daughters of cut women were highly likely to be cut. Also, the likelihood of a girl being cut increased with the proportion of women in the community (1) who were cut (2) who supported FGM/C continuation, and (3) who believed FGM/C was a religious obligation. Other key risk factors included living in the northeastern region; belonging to the Kisii or Somali ethnic groups and being of Muslim background. These findings offered a clearer picture of the dynamics of FGM/C in Kenya and will aid targeted interventions through bespoke policymaking and implementations.

Keywords: FGM/C; social norms; space-time interactions; spatial modelling and mapping.

Figure 1

Map of Kenya showing the eight administrative regions.

Figure 2

Evolution of FGM/C prevalence among 0–14 years old girls in Kenya from 1998 to 2014. Note that in 1998, there were no surveys in the North Eastern region hence the black-white stripes. Across the years, red regions had highest prevalence which decreased in magnitude as it fades through red to deep blue.

Figure 3

Non-linear effects of the proportions of women in a girl’s community who were cut (blue), who supported the continuation of FGM/C (orange), and who believed that FGM/C was a religious obligation for (a) Model A, (b) Model B and (c) Model C. Evidence from the 2014 KDHS.

Figure 4

Posterior risk maps [(a) and (c)] of Kenyan 0–14 years old girls’ FGM/C with the corresponding 95% (right) [(b) and (d)] posterior significance maps for Model B (left panel) and Model C (right panel). Deep blue to red corresponds to low risk to high risk. Black colour indicates significantly high-risk regions, white colour indicates significantly low risk regions and grey colour indicates nonsignificant regions.

Figure 5

Non-linear effects on a girl’s likelihood of experiencing FGM/C of mother’s age (a); girl’s age (b) and ethnic fractionalization index (EFI) (c). Evidence from the 2014 KDHS Model C.

Figure 6

Posterior risk maps ((a) and (c)) of Kenyan 0–14 years old girls’ FGM/C with the corresponding 95% (right (b) and (d)) posterior significance maps for Model II (left panel) and Model III (right panel). Deep blue to red corresponds to low risk to high risk. Black colour in (b) and (d) indicates significantly high-risk regions, white colour indicates significantly low risk regions and grey colour indicates nonsignificant regions. Evidence from the pooled 2003 to 2014 KDHS.

Figure 7

Predicted fully adjusted FGM/C prevalence among 0–14 years old girls in Kenya from 2003 to 2014 from the best fit model (Model III) of the pooled 2003 to 2014 data. Across the years, red regions had highest prevalence, while deep blue regions had lowest prevalence.

Figure 8

Time trend (left panel) and non-linear effect of mother’s age (right panel). Evidence from the KDHS 2003 to 2014 pooled data Model C*.