Literature DB >> 33478450

Hotspots of female genital mutilation/cutting and associated factors among girls in Ethiopia: a spatial and multilevel analysis.

Tesfahun Taddege Geremew1, Muluken Azage2, Endalkachew Worku Mengesha2.   

Abstract

BACKGROUND: Female genital mutilation/cutting (FGM/C) is a harmful traditional practice that violates the human rights of girls and women. It is widely practiced mainly in Africa including Ethiopia. There are a number of studies on the prevalence of FGM/C in Ethiopia. However, little has been devoted to its spatial epidemiology and associated factors. Hence, this study aimed to explore the spatial pattern and factors affecting FGM/C among girls in Ethiopia.
METHODS: A further analysis of the 2016 Ethiopia Demographic and Health Survey data was conducted, and a total of 6985 girls nested in 603 enumeration areas were included in this analysis. Global Moran's I statistic was employed to test the spatial autocorrelation, and Getis-Ord Gi* as well as Kulldorff's spatial scan statistics were used to detect spatial clusters of FGM/C. Multilevel logistic regression models were fitted to identify individual and community level factors affecting FGM/C.
RESULTS: Spatial clustering of FGM/C was observed (Moran's I = 0.31, p-value < 0.01), and eight significant clusters of FGM/C (hotspots) were detected. The most likely primary SaTScan cluster was detected in the neighborhood areas of Amhara, Afar, Tigray and Oromia regions (LLR = 279.0, p < 0.01), the secondary cluster in Tigray region (LLR = 67.3, p < 0.01), and the third cluster in Somali region (LLR = 55.5, P < 0.01). In the final best fit model, about 83% variation in the odds of FGM/C was attributed to both individual and community level factors. At individual level, older maternal age, higher number of living children, maternal circumcision, perceived beliefs as FGM/C are required by religion, and supporting the continuation of FGM/C practice were factors to increase the odds of FGM/C, whereas, secondary or higher maternal education, better household wealth, and regular media exposure were factors decreasing the odds of FGM/C. Place of residency, Region and Ethnicity were also among the community level factors associated with FGM/C.
CONCLUSIONS: In this study, spatial clustering of FGM/C among girls was observed in Ethiopia, and FGM/C hotspots were detected in Afar, Amhara, Tigray, Benishangul Gumuz, Oromia, SNNPR and Somali regions including Dire Dawa Town. Both individual and community level factors play a significant role in the practice of FGM/C. Hence, FGM/C hotspots require priority interventions, and it is also better if the targeted interventions consider both individual and community level factors.

Entities:  

Keywords:  Circumcision; Genital mutilation/cutting; Multilevel; Spatial

Mesh:

Year:  2021        PMID: 33478450      PMCID: PMC7818563          DOI: 10.1186/s12889-021-10235-8

Source DB:  PubMed          Journal:  BMC Public Health        ISSN: 1471-2458            Impact factor:   3.295


  16 in total

1.  Conformity and change: community effects on female genital cutting in Kenya.

Authors:  Sarah R Hayford
Journal:  J Health Soc Behav       Date:  2005-06

2.  Female genital mutilation among mothers and daughters in Harar, eastern Ethiopia.

Authors:  Teshome Oljira; Nega Assefa; Yadeta Dessie
Journal:  Int J Gynaecol Obstet       Date:  2016-08-22       Impact factor: 3.561

3.  Factors determining whether Ethiopian women support continuation of female genital mutilation.

Authors:  Saba W Masho; Lindsey Matthews
Journal:  Int J Gynaecol Obstet       Date:  2009-08-27       Impact factor: 3.561

4.  Gender differences in support for the discontinuation of female genital cutting in Sierra Leone.

Authors:  Marguerite L Sagna
Journal:  Cult Health Sex       Date:  2014-04-16

5.  Health complications of female genital mutilation in Sierra Leone.

Authors:  Owolabi Bjälkander; Laurel Bangura; Bailah Leigh; Vanja Berggren; Staffan Bergström; Lars Almroth
Journal:  Int J Womens Health       Date:  2012-07-06

6.  Female genital mutilation: prevalence, perceptions and effect on women's health in Kersa district of Ethiopia.

Authors:  Wondimu Shanko Yirga; Nega Assefa Kassa; Mengistu Welday Gebremichael; Arja R Aro
Journal:  Int J Womens Health       Date:  2012-02-13

7.  Prevalence of female genital mutilation and its effect on women's health in Bale zone, Ethiopia: a cross-sectional study.

Authors:  Daniel Bogale; Desalegn Markos; Muhammedawel Kaso
Journal:  BMC Public Health       Date:  2014-10-16       Impact factor: 3.295

8.  Power evaluation of disease clustering tests.

Authors:  Changhong Song; Martin Kulldorff
Journal:  Int J Health Geogr       Date:  2003-12-19       Impact factor: 3.918

9.  Measures of clustering and heterogeneity in multilevel Poisson regression analyses of rates/count data.

Authors:  Peter C Austin; Henrik Stryhn; George Leckie; Juan Merlo
Journal:  Stat Med       Date:  2017-11-08       Impact factor: 2.373

10.  Secular trends in the prevalence of female genital mutilation/cutting among girls: a systematic analysis.

Authors:  Ngianga-Bakwin Kandala; Martinsixtus C Ezejimofor; Olalekan A Uthman; Paul Komba
Journal:  BMJ Glob Health       Date:  2018-11-06
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  3 in total

1.  Predictors of uncircumcised primary school girls' intention to genital cutting in South Ethiopia: Application of theory of planned behavior.

Authors:  Solomon Haile; Dawit Sullamo; Tekle Ejajo; Firanbon Teshome; Yohannes Kebede
Journal:  PLoS One       Date:  2022-06-30       Impact factor: 3.752

2.  Behavioral Barriers to Stop Female Genital Mutilation/Cutting in South Ethiopia: An Exploratory Qualitative Study of the Perspective of Women.

Authors:  Ephrem Lejore Sibamo; Shimelash Bitew Workie
Journal:  Int J Womens Health       Date:  2022-08-10

3.  Socio-economic disparities in female genital circumcision: finding from a case-control study in Mahabad, Iran.

Authors:  Shahla Shafaati Laleh; Ghodratollah Roshanaei; Farzaneh Soltani; Fatemeh Ghamari Mehran
Journal:  BMC Public Health       Date:  2022-10-07       Impact factor: 4.135

  3 in total

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