This table provides metadata for the actual indicator available from Uganda statistics closest to the corresponding global SDG indicator. Please note that even when the global SDG indicator is fully available from Ugandan statistics, this table should be consulted for information on national methodology and other Ugandan-specific metadata information.
| Goal |
Goal 5: Achieve gender equality and empower all women and girls |
|---|---|
| Target |
Target 5.3: Eliminate all harmful practices, such as child, early and forced marriage and female genital mutilation |
| Indicator |
Indicator 5.3.2: Proportion of girls and women aged 15-49 years who have undergone female genital mutilation/ cutting, by age |
| Metadata update |
December 2021 |
| Related indicators |
The prevalence of female genital mutilation can be interpreted alongside other indicators about women’s well-being, including those on women’s health under Goal 3, those on the status of women under Goal 5, and those around violence against women under Goal 16. |
| Data reporter |
Uganda Bureau Of Statistics |
| Organisation |
Uganda Bureau Of Statistics |
| Contact person(s) |
Ms. Pamela Kakande |
| Contact organisation unit |
Demography & Social Statistics (DSS) |
| Contact person function |
Senior Statistician |
| Contact phone |
+256 772 303441 |
| Contact mail |
P.O. Box 7186Kampala |
| Contact email |
pamela.kakande@ubos.org |
| Definition and concepts |
Definition: The Proportion of girls and women aged 15-49 years who have undergone female genital mutilation/cutting is currently being measured by the proportion of women/girls aged 15-49 years who have undergone female genital mutilation/cutting. This indicator can be measured among smaller age groups, with the experience of younger women representing FGM/C that has occurred more recently and the experience of older women representing levels of the practice in the past. Concepts: Female genital mutilation (FGM) refers to “all procedures involving partial or total removal of the female external genitalia or other injury to the female genital organs for non-medical reasons” (World Health Organization, Eliminating Female Genital Mutilation: An interagency statement, WHO, UNFPA, UNICEF, UNIFEM, OHCHR, UNHCR, UNECA, UNESCO, UNDP, UNAIDS, WHO, Geneva, 2008, p.4) |
| Unit of measure |
Percent |
| Classifications |
Not Applicable |
| Data sources |
The Uganda Demographic and Health Survey (UDHS). |
| Data collection method |
Sample Design: The sample design for the 2016 UDHS used the sampling frame from the Uganda National Population and Housing Census (NPHC 2014). The census frame is a complete list of all census Enumeration Areas (EAs) created for the 2014 NPHC. In Uganda, an EA is a geographic area that covers an average of about 130 households. At the time of the NPHC, Uganda was divided administratively into 112 districts, which were grouped for this survey into 15 regions. The sample for the 2016 UDHS was designed to provide estimates of key indicators for the country as a whole, for urban and rural areas separately, and for each of the 15 sub regions. Estimates are also presented for three special areas: the Lake Victoria islands, the mountainous districts, and greater Kampala. The 2016 UDHS sample was stratified and selected in two stages. In the first stage, 697 EAs were selected from the 2014 NPHC, 162 EAs in urban areas and 535 in rural areas. Households constituted the second stage of sampling. A listing of households was compiled in each of the 696 accessible selected EAs from April to October 2016. To minimize the task of household listing, each large EA (that is to say more than 300 households) selected for the 2016 UDHS was segmented. Only one segment was selected for the survey with probability proportional to segment size, and the household listing was conducted only in the selected segment. Out of the 20,880 selected households (30 households per EA), 18,506 women aged 15-49 were successfully interviewed. All women age 15-49 who were either permanent residents of the selected households or visitors who stayed in the household the night before the survey were eligible to be interviewed. In one-third of the sampled households, all men age 15-54, including both usual residents and visitors who stayed in the household the night before the interview, were eligible for individual interviews. Recruitment and Training: UBOS recruited and trained field staff to serve as supervisors, CAPI managers, interviewers, health technicians, and reserve interviewers for the main fieldwork. Health technicians were trained separately from interviewers. A two day field practice was organized to provide trainees with additional hands on practice before the actual fieldwork. Prior to the main field work, a pre-test was conducted and best practices were adopted. Questionnaires: Four questionnaires were used for the 2016 UDHS: The Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. The questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect the population and health issues relevant to Uganda Input was solicited from all stakeholders such as; Government Ministries and Agencies, Non-governmental Organizations, and Development partners. After the finalization of the questionnaires in English, they were then translated into eight major local languages. The Household, Woman’s, and Man’s Questionnaires were programmed into a computer-assisted personal interviewing (CAPI) application for data collection purposes. Data collection: Data collection was conducted by 21 field teams, each consisting of one team leader, one field data Manager, three female interviewers, one male interviewer, one health technician, and a driver. The health technicians were responsible for anthropometric measurements, blood sample collection for Hemoglobin and malaria testing, and DBS specimen collection for vitamin A testing. The, interviewers used tablets to record all questionnaire responses during the interviews. The tablets were equipped with Bluetooth technology to enable remote electronic transfer of files, such as assignments from the team supervisor to the interviewers, individual questionnaires among survey team members, and completed questionnaires from interviewers to team supervisors. The field supervisors transferred data to the central data processing office via IFSS. Senior staff from the Makerere University School of Public Health, the Ministry of Health, and UBOS and a survey technical specialist from the DHS Program coordinated and supervised fieldwork activities. Data collection took place over a 6-month period from June 2016 through December 2016. The question used to collect data on this indicator is; Have you yourself been circumcised. Yes………….1 No…………. 2 |
| Data collection calendar |
Every five years |
| Data providers |
Uganda Bureau of statistics |
| Data compilers |
Department of Demographic and Social Statistics |
| Institutional mandate |
The UBOS Act 1998 provides for the development and maintenance of the National Statistical System (NSS) to ensure collection, analysis and publication of integrated, relevant, reliable and timely statistical information. It established the Bureau as the coordinating, monitoring and supervisory body for the National Statistical System. |
| Rationale |
FGM is a violation of girls’ and women’s human rights. There is a large body of literature documenting the adverse health consequences of FGM over both the short and long term. The practice of FGM is a direct manifestation of gender inequality FGM is condemned by a number of international treaties and conventions. Since FGM is regarded as a traditional practice prejudicial to the health of the girls. It violates the Convention on the Rights of the girl Child. |
| Comment and limitations |
Women are sometimes unwilling to disclose having undergone the procedure because of the sensitivity of the issue or the illegal status of the practice in Uganda. In addition, women may be un aware that they have been cut or of the extent of the cutting, particularly if FGM was performed at an early age. |
| Method of computation |
The number of girls and women aged 15-49 who have undergone FGM divided by the total number of girls and women aged 15-49 in the population multiplied by 100. |
| Validation |
Pretest, Training of field staff, field supervision, and data processing were conducted. Data Processing: It included checking for inconsistences, incompleteness and outliers. Data editing and cleaning included structure and consistency checks to ensure completeness of work in the field. |
| Methods and guidance available to countries for the compilation of the data at the national level |
Non |
| Quality management |
1. The survey implementation is overseen by a Technical Working Group which is constituted using a multi sectorial approach. 2. The survey report is reviewed by an experienced team at Management level who are in most cases Directors or Heads of departments and key stakeholders from Makerere School of Public Health, Molecular Laboratory of Makerere University School of Health Sciences, Ministry of Health and later reviewed by consultants |
| Quality assurance |
The UDHS goes through several stages before production and sharing of the final findings. During the Survey implementation.
|
| Quality assessment |
Before dissemination, the report is reviewed and quality assured by a professional team of the National Statistical System. Quality Control is addressed at all levels during Survey implementation |
| Data availability and disaggregation |
Data availability: Nationally representative prevalence data are currently available for women aged 15 to 49 years of age. Data series: UDHS 2011, UDHS 2016 Data disaggregation: Age (15-49 years at the national level, 15-19 years at the regional level) |
| Comparability/deviation from international standards |
The estimates compiled and presented at global level come directly from nationally produced data and are not adjusted or recalculated. |
| References and Documentation |
Uganda Demographic and Health Survey 2016 [FR333] (ubos.org) http://dhsprogram.com |
| Metadata last updated | Feb 12, 2026 |