https://doi.org/10.4081/gh.2025.1302
Geographic distribution and demographic factors associated with use of a long-acting reversible contraceptive (LARC) in Ethiopia
Submitted: 28 April 2024
Accepted: 4 December 2024
Published: 23 January 2025
Accepted: 4 December 2024
Abstract Views: 155
PDF: 28
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Authors
Background: Increasing access to and utilization of long-acting reversible contraceptives (LARC) can prevent unintended pregnancies and reduce unmet need for family planning in Ethiopia However, LARC uptake lags behind less effective contraceptive methods. This study aimed to analyze the geographical distribution and demographic factors associated to LARC uptake.
Methods: The 2019 Performance Monitoring For Action Ethiopia (PMA Ethiopia) survey data was used. Spatial autocorrelation was examined using Global Moran's I and Local Indicators of Spatial Association (LISA). Bivariate Moran's I and bivariate LISA (BiLISA), Spatial lag, and spatial error regression analyses were performed to assess the spatial correlation and association between LARC uptake and demographic factors.
Results: LARC uptake was 8% among the study population, with Afar and Somali regions having the lowest uptake. There was a statistically significant positive spatial autocorrelation for LARC uptake (Moran’s I= 0.308, p<0.001). Additionally, an inverse correlation was observed between LARC uptake and the percentage of Muslims, rural population, no formal education, and low wealth quantile. The spatial lag model indicated that zones with higher Muslim populations and those with higher percentages of population with no formal education had lower LARC uptake.
Conclusions: To expand access to LARC, the Ethiopian government, policymakers, and non-governmental organizations might implement programs targeting low-uptake areas (Afar and Somali regions). Muslim religious leaders could play an important role in promoting acceptance of LARC among their members. Tailored health education programs should be developed for Muslim populations and those with no formal education to enhance awareness and acceptance of LARC.
Anselin L, 2020. GeoDa An Introduction to Spatial Data Analysis: Global Spatial Autocorrelation. URL https://geodacenter.github.io/workbook/5a_global_auto/lab5a.html (accessed 12.2.24).
Azanaw MM, Fentie DT, Bukayaw YA, Lakew AM, Sisay MM, 2022. Spatial distribution and determinant factors of unmet need for family planning among all reproductive-age women in Ethiopia: a multi-level logistic regression modelling approach. Contracept Reprod Med 7, 13.
DOI: https://doi.org/10.1186/s40834-022-00178-9
Bolarinwa OA., Tessema ZT, Frimpong JB, Seidu A-A, Ahinkorah, BO, 2021. Spatial distribution and factors associated with modern contraceptive use among women of reproductive age in Nigeria: A multilevel analysis. PLoS One 16, e0258844.
DOI: https://doi.org/10.1371/journal.pone.0258844
Central Statistical Agency - CSA/Ethiopia, ICF, 2017. Ethiopia Demographic and Health Survey 2016. CSA and ICF, Addis Ababa, Ethiopia.
Chen Y, 2021. An analytical process of spatial autocorrelation functions based on Moran’s index. PLOS ONE 16, e0249589.
DOI: https://doi.org/10.1371/journal.pone.0249589
Cooper RA., Cooper, M.A., McGinley, E.L., Fan, X., Rosenthal, J.T., 2012. Poverty, Wealth, and Health Care Utilization: A Geographic Assessment. J Urban Health 89, 828–847.
DOI: https://doi.org/10.1007/s11524-012-9689-3
Curtis KM, Peipert JF, 2017. Long-Acting Reversible Contraception. N Engl J Med 376, 461–468.
DOI: https://doi.org/10.1056/NEJMcp1608736
Daie GF, 2012. Voluntary Villagization Scheme (VVS) For Transforming Semi-Pastoral Communities in Benishangul-Gumuz Region, Northwestern Ethiopia: Challenges And Local Development Indicators. J Sustainable Develop Afr 14, 162–196.
Ebrahim OA, Zeleke EG, Muluneh AG, 2021. Geographic variation and associated factors of long-acting contraceptive use among reproductive-age women in Ethiopia: a multi-level and spatial analysis of Ethiopian Demographic and Health Survey 2016 data. Reproductive Health 18, 122.
DOI: https://doi.org/10.1186/s12978-021-01171-2
Hubacher D, Mavranezouli I, McGinn E, 2008. Unintended pregnancy in sub-Saharan Africa: magnitude of the problem and potential role of contraceptive implants to alleviate it. Contraception 78, 73–78.
DOI: https://doi.org/10.1016/j.contraception.2008.03.002
Jacobstein R, Curtis C, Spieler J, Radloff S, 2013. Meeting the need for modern contraception: Effective solutions to a pressing global challenge. International Journal of Gynecology & Obstetrics 121, S9–S15.
DOI: https://doi.org/10.1016/j.ijgo.2013.02.005
Kowe P, Mutanga O, Odindi J, Dube T, 2019. Exploring the spatial patterns of vegetation fragmentation using local spatial autocorrelation indices. JARS 13, 024523.
DOI: https://doi.org/10.1117/1.JRS.13.024523
Lakew Y, Reda AA, Tamene H, Benedict S, Deribe K, 2013. Geographical variation and factors influencing modern contraceptive use among married women in Ethiopia: evidence from a national population based survey. Reproductive Health 10, 52.
DOI: https://doi.org/10.1186/1742-4755-10-52
Lee S-I, 2001. Developing a bivariate spatial association measure: An integration of Pearson’s r and Moran’s I. J Geograph Syst 3, 369–385.
DOI: https://doi.org/10.1007/s101090100064
Melka AS., Tekelab T, Wirtu D, 2015. Determinants of long acting and permanent contraceptive methods utilization among married women of reproductive age groups in western Ethiopia: a cross-sectional study. Pan Afr Med J 21, 246.
DOI: https://doi.org/10.11604/pamj.2015.21.246.5835
Nyarko SH, 2020. Spatial variations and socioeconomic determinants of modern contraceptive use in Ghana: A Bayesian multilevel analysis. PLOS ONE 15, e0230139.
DOI: https://doi.org/10.1371/journal.pone.0230139
Okunlola OA, Alobid M, Olubusoye OE, Ayinde K, Lukman AF, Szűcs, I, 2021. Spatial regression and geostatistics discourse with empirical application to precipitation data in Nigeria. Sci Rep 11, 16848.
DOI: https://doi.org/10.1038/s41598-021-96124-x
Olson DJ, and Piller A, 2013. Ethiopia: an emerging family planning success story. Stud Fam Plann 44:445–59.
DOI: https://doi.org/10.1111/j.1728-4465.2013.00369.x
Parks C, Peipert JF, 2016. Eliminating Health Disparities in Unintended Pregnancy with Long-Acting Reversible Contraception (LARC). Am J Obstet Gynecol 214, 681–688.
DOI: https://doi.org/10.1016/j.ajog.2016.02.017
Peipert JF, Madden T, Allsworth JE, Secura GM, 2012. Preventing Unintended Pregnancies by Providing No-Cost Contraception. Obstet Gynecol 120, 1291–1297.
DOI: https://doi.org/10.1097/AOG.0b013e318273eb56
Schenker J g, 2000. Women’s reproductive health: monotheistic religious perspectives. International Journal of Gynecology & Obstetrics 70, 77–86.
DOI: https://doi.org/10.1016/S0020-7292(00)00225-3
Shiferaw S, Spigt M, Seme A, Amogne A, Skrøvseth S, Desta S, Radloff S, Tsui A, GeertJan D, 2017. Does proximity of women to facilities with better choice of contraceptives affect their contraceptive utilization in rural Ethiopia? PLoS One 12, e0187311.
DOI: https://doi.org/10.1371/journal.pone.0187311
Stonehill A, Bishu SG, Taddese HB, 2020. Factors associated with long-acting and short-acting reversible contraceptive use in Ethiopia: an analysis of the 2016 Demographic and Health Survey. Eur J Contracept Reprod Health Care 25, 350–358.
DOI: https://doi.org/10.1080/13625187.2020.1795116
Suryowati K, Bekti RD, Faradila A, 2018. A Comparison of Weights Matrices on Computation of Dengue Spatial Autocorrelation. IOP Conf. Ser.: Mater. Sci. Eng. 335, 012052.
DOI: https://doi.org/10.1088/1757-899X/335/1/012052
Tegegne TK, Chojenta C, Forder PM, Getachew T, Smith R, Loxton D, 2020. Spatial variations and associated factors of modern contraceptive use in Ethiopia: a spatial and multilevel analysis. BMJ Open 10, e037532.
DOI: https://doi.org/10.1136/bmjopen-2020-037532
United States Department of State, 2019. 2019 Report on International Religious Freedom: Ethiopia.
Wado YD, Gurmu E, Tilahun T, Bangha M, 2019. Contextual influences on the choice of long-acting reversible and permanent contraception in Ethiopia: A multilevel analysis. PLoS One 14, e0209602.
DOI: https://doi.org/10.1371/journal.pone.0209602
Woldemichael A, Takian A, Akbari Sari A, Olyaeemanesh A, 2019. Availability and inequality in accessibility of health centre-based primary healthcare in Ethiopia. PLoS One 14, e0213896.
DOI: https://doi.org/10.1371/journal.pone.0213896
Yao J, Murray AT, Agadjanian V, Hayford SR, 2012. Geographic influences on sexual and reproductive health service utilization in rural Mozambique. Appl Geogr 32, 601–607.
DOI: https://doi.org/10.1016/j.apgeog.2011.07.009
Zenebe CB, Adefris M, Yenit MK, Gelaw YA, 2017. Factors associated with utilization of long-acting and permanent contraceptive methods among women who have decided not to have more children in Gondar city. BMC Womens Health 17, 75.
DOI: https://doi.org/10.1186/s12905-017-0432-9
Zhang C, Murayama Y, 2011. Testing Local Spatial Autocorrelation Using k-Order Neighbours, in: Murayama Y, Thapa RB (Eds.), Spatial Analysis and Modeling in Geographical Transformation Process: GIS-Based Applications. Springer Netherlands, Dordrecht, pp. 45–56.
DOI: https://doi.org/10.1007/978-94-007-0671-2_3
Zimmerman L, Desta S, Yihdego M, Rogers A, Amogne A, Karp C, Wood SN, Creanga A, Ahmed S, Seme A, Shiferaw S, 2020. Protocol for PMA-Ethiopia: A new data source for cross-sectional and longitudinal data of reproductive, maternal, and newborn health. Gates Open Res 4, 126.
DOI: https://doi.org/10.12688/gatesopenres.13161.1
How to Cite
Teni, M. T., Loux, T., Sandoval, N., & Sebert Kuhlmann, A. (2025). Geographic distribution and demographic factors associated with use of a long-acting reversible contraceptive (LARC) in Ethiopia. Geospatial Health, 20(1). https://doi.org/10.4081/gh.2025.1302
Copyright (c) 2025 the Author(s)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
PAGEPress has chosen to apply the Creative Commons Attribution NonCommercial 4.0 International License (CC BY-NC 4.0) to all manuscripts to be published.
Similar Articles
- Thandi Kapwata, Michael T. Gebreslasie, Random forest variable selection in spatial malaria transmission modelling in Mpumalanga Province, South Africa , Geospatial Health: Vol. 11 No. 3 (2016)
- Su Yun Kang, Susanna M. Cramb, Nicole M. White, Stephen J. Ball, Kerrie L. Mengersen, Making the most of spatial information in health: a tutorial in Bayesian disease mapping for areal data , Geospatial Health: Vol. 11 No. 2 (2016)
- Laura Grisotto, Dario Consonni, Lorenzo Cecconi, Dolores Catelan, Corrado Lagazio, Pier Alberto Bertazzi, Michela Baccini, Annibale Biggeri, Geostatistical integration and uncertainty in pollutant concentration surface under preferential sampling , Geospatial Health: Vol. 11 No. 1 (2016): Valencia Issue
- Omid Reza Abbasi, Yasser Ebrahimian Ghajari , Ali Asghar Alesheikh, A spatiotemporal analysis of the impact of the COVID-19 outbreak on noise pollution in Tehran, Iran , Geospatial Health: Vol. 17 No. 2 (2022)
- Jishuo Zhang, Meifang Li, Spatial access to public hospitals during COVID-19 in Nottinghamshire, UK , Geospatial Health: Vol. 17 No. 2 (2022)
- Seong-Yong Park, Jin-Mi Kwak, Eun-Won Seo, Kwang-Soo Lee, Spatial analysis of the regional variation of hypertensive disease mortality and its socio-economic correlates in South Korea , Geospatial Health: Vol. 11 No. 2 (2016)
- Yijia Liu, Wenzhong Shi, Anshu Zhang, Xiaosheng Zhu, The effectiveness of the restricted policy on specific venues in Hong Kong: A spatial point pattern view , Geospatial Health: Vol. 17 No. 2 (2022)
- Hassan M. Khormi, Lalit Kumar, Future malaria spatial pattern based on the potential global warming impact in South and Southeast Asia , Geospatial Health: Vol. 11 No. 3 (2016)
- Matthew Tuson, Matthew Yap, David Whyatt, Investigating local variation in disease rates within high-rate regions identified using smoothing , Geospatial Health: Vol. 18 No. 1 (2023)
- Anna-Sofie Stensgaard, Mark Booth, Grigory Nikulin, Nicky McCreesh, Combining process-based and correlative models improves predictions of climate change effects on Schistosoma mansoni transmission in eastern Africa , Geospatial Health: Vol. 11 No. s1 (2016): HEALTHY FUTURES
<< < 32 33 34 35 36 37 38 39 40 > >>
You may also start an advanced similarity search for this article.
