Knowledge of Female Circumcision

 

Percentage of women and men who have heard of female circumcision

 

Definition

 

Percentage of women (or men) age 15-49 who have heard of female circumcision.

 

Coverage:

Population base: Women (or men) age 15-49 (IR file, MR file)

Time period: Current status at time of survey

 

Numerator: Number of women (or men) age 15-49 who have heard of female circumcision (women: g100 = 1 or g101 = 1; men: mg100 = 1 or mg101 = 1)

Denominator: Number of women (or men) age 15-49

 

Variables: IR file, MR file.

g100

Ever heard of female circumcision (women)

g101

Ever heard of genital cutting (probed) (women)

v005

Women's sample weight

mg100

Ever heard of female circumcision (men)

mg101

Ever heard of genital cutting (probed) (men)

mv005

Men's sample weight

 

Calculation

 

Numerator divided by the denominator, multiplied by 100.

 

Handling of Missing Values

 

Missing values are not included in the numerator but kept in the denominator.

 

Notes and Considerations

 

A respondent is asked whether they have heard of female circumcision. If they responded that they have not heard of female circumcision, they are asked a further probing question asking whether they have heard of a practice where a female’s genitals are cut. This is why both questions (variables g100 and g101) must be taken into account when estimating the prevalence of respondents who have ever heard of FGC.

 

Changes over Time

 

In DHS-6 on, the FGC variables have become standardized, and the variable series often starts with g100 – “Ever heard of female circumcision”. In previous surveys and with some exceptions in more recent surveys, other variable names have been used. See below for a summary of the name of the variable equivalent to g100. The variable prefix (i.e., ‘fg’ for variable fg100) of the variables shown in the table below be the prefix for the following FGC variables in any survey.

 

First variable in variable series

Individual data files from past surveys

(please see the section on Recode File Names in Chapter 1 to understand the naming of data files)

fg100

BJIR41, BFIR43, EGIR4A, EGIR42, ETIR41, ETIR51, GNIR52, MLIR41, NGIR4B, SNIR4H, TZIR4I

s901

BFIR31

s801

EGIR33, EGIR51

v901

GNIR41

s1001

CMIR44, KEIR3A, TZIR3A

s551

MLIR32, NIIR31

g121_01

SNIR6D

s227

SDIR02

s1101

SZIR51

s730f

UGIR7B

 

References

 

Hayford, S. R. 2005. “Conformity and Change: Community Effects on Female Genital Cutting in Kenya”. Journal of Health and Social Behavior. 46(2): 121–140. https://asu.pure.elsevier.com/en/publications/conformity-and-change-community-effects-on-female-genital-cutting

 

Resources

 

DHS-8 Tabulation plan: Table FGC.1

 

API Indicator IDs:

Women:

FG_KFCC_W_HFC

 

Men:

FG_KFCC_M_HFC

(API link, STATcompiler link)