Household Poverty and Contraceptive Non-Intention Among Women of Childbearing Age in Union in Burundi: Validity of the Theory of Intergenerational Flows of Wealth
Main Article Content
Abstract
The Republic of Burundi wants to control population growth by increasing the prevalence of contraception by 1.5% per year. However, the intention to use modern contraception is declining among women of childbearing age. The proportion of women wishing to use contraception has dropped from 66% in 2010 to 53% in 2016–2017. This research aims to verify whether household poverty is at the root of this contraceptive non-intention of women whose couples hope for better wealth from a large group of offspring. Data from the 2010 and 2016–2017 Demographic and Health Surveys of Burundi were analyzed using multilevel logistic regression. There is no significant difference in contraceptive non-intention found between women from poor households and those with medium standards of living (p = .587 ˃ .05) or rich (p = .098 ˃ .05) in 2010 or between women from wealthy households and those from poor (p = .101 ˃ .05) or medium (p = .689 ˃ .05) standards of living in 2016–2017. Standard of living does not count among the principal factors of contraceptive non-intention in Burundi. Instead, attention should be paid to sociocultural factors.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
References
• Ahuja, M., Frimpong, E., Okoro, J., Wani, R., & Armel, S. (2020). Risk and protective factors for intention of contraception use among women in Ghana. Health Psychology Open, 7(2). https://doi.org/10.1177/2055102920975975
• Babalola, S., John, N., Ajao, B., & Speizer, I. (2015). Ideation and intention to use contraceptives in Kenya and Nigeria. Demographic Research, 33, 211–238. https://doi.org/10.4054/DemRes.2015.33.8
• Becker, G. S. (1960). An economic analysis of fertility. In National Bureau of Economic Research (Ed.), Demographic and economic change in developed countries (pp. 209–240). Columbia University Press. http://www.nber.org/books/univ60-2
• Bringé, A., & Golaz, V. (2017). Manuel pratique d’analyse multiniveau [A practical handbook of multilevel analysis]. Ined Éditions. https://doi.org/10.4000/books.ined.12777
• Caldwell, J. C. (1976). Toward a restatement of demographic transition theory. Population and Development Review, 2(3/4), 321–366. https://doi.org/10.2307/1971615
• Callahan, R., & Becker, S. (2013). Contraceptive intentions and use in rural Bangladesh. Population Association of America. https://paa2013.princeton.edu/papers/130056
• De Bourmont, M. (2012). La résolution d’un problème de multi-colinéarité au sein des études portant sur les déterminants d’une publication volontaire d’informations: Proposition d’un algorithme de décisions implifié basé sur les indicateurs de Belsley, Kuh et Welsch (1980) [Resolving a multi-collinearity problem within studies of the determinants of voluntary news release: Proposition of an implicit decision algorithm based on Belsley, Kuh, and Welsch indicators (1980)]. Comptabilités et innovation, Article hal-00691156. https://hal.archives-ouvertes.fr/hal-00691156
• Dibaba, Y. (2009). Factors influencing women’s intention to limit child bearing in Oromia, Ethiopia. Ethiopian Journal of Health Development, 23(1), 28–33. https://doi.org/10.4314/ejhd.v23i1.44834
• Doliger, C. (2008). La fécondité et ses déterminants économiques: Becker vs Easterlin [Fertility and its economic determinants: Becker vs Easterlin]. Revue économique, 59(5), 955–971. https://doi.org/10.3917/reco.595.0955
• Easterlin, R. A. (1975). An economic framework for fertility analysis. Studies in Family Planning, 6(3), 54–63. https://doi.org/10.2307/1964934
• Gendreau, F. (1993). La population de l’Afrique: Manuel de démographie [The population of Africa: A handbook of demography]. Karthala; CEPED. https://horizon.documentation.ird.fr/exl-doc/pleins_textes/pleins_textes_7/carton07/35169.pdf
• ISTEEBU, Government of Burundi (BDI), & ICF International. (2012). Deuxième Enquête Démographique et de Santé Burundi 2010 [Second Demographic and Health Survey of Burundi 2010]. Archive Nationale des Données du Burundi. https://www.isteebu.bi/nada/index.php/catalog/4
• Kamuragiye, A., & Buzingo, D. (2019). Maitriser la croissance de la population pour profiter du dividende demographique en Afrique subsaharienne: La cas du Burundi [Contain the Population Growth to Benefit from the Demographic Dividend in Sub-Saharan Africa: The Case of Burundi]. Les Editions l’Empreinte du Passant.
• Lemessa, R., & Wencheko, E. (2014). Factors affecting the intention of women to limit childbearing in rural Ethiopia. Ethiopian Journal of Health Development, 28(2), 75–80. https://ejhd.org/index.php/ejhd/article/view/32
• Leridon, H. (2015). Théories de la fécondité: Des démographes sous influence [The development of fertility theories: A multidisciplinary endeavor]. Population, 70(2), 309–348. https://doi.org/10.3917/popu.1502.0331
• Machiyama, K., & Cleland, J. C. (2013, February). Insights into unmet need in Ghana (STEP UP Research Report). London School of Hygiene and Tropical Medicine. https://doi.org/10.31899/rh4.1062
• Manirakiza, R. (2008). Population et développement au Burundi [Population and development in Burundi]. Harmattan.
• Masuy, A. J. (2013). L’exploration: Évaluer, préparer et décrire [Exploration: Assessing, preparing and describing]. In G. Masuy-Stroobant & R. Costa (Eds.), Analyser les données en Sciences sociales: De la préparation des données à l’analyse multivariée [Analyzing Data in the Social Sciences: From Data Preparation to Multivariate Analysis] (pp. 49–74). P.I.E. Peter Lang.
• Ministry to the Presidency Responsible for Good Governance and Planning [Burundi] (MPBGP), Ministry of Public Health and the Fight against AIDS [Burundi] (MSPLS), Institute of Statistics and Economic Studies in Burundi (ISTEEBU), & ICF International. (2017). Troisième Enquête Démographique et de Santé 2016–2017 [Third demographic and health survey 2016–2017]. https://www.isteebu.bi/wp-content/uploads/2020/10/EDS-III.pdf
• Nganawara, D. (2016). Famille et scolarisation des enfants en âge scolaire obligatoire au Cameroun: Une analyse à partir du recensement de 2005 [Family and schooling of children of compulsory school age in Cameroon: An analysis based on the 2005 census]. Observatoire démographique et statistique de l’espace francophone (ODSEF). https://www.odsef.fss.ulaval.ca/sites/odsef.fss.ulaval.ca/files/rr_odsef_scolarisation_cameroun_final.pdf
• Nganawara, D. (2017). Analyse de fécondité [Fertility analysis] (Les documents pédagogiques de l’IFORD [IFORD educational documents]). http://www.iford-cm.org/index.php/formation/30-formation/200-espace-etudiants-3
• Programme Alimentaire Mondial (PAM). (2017, March). République du Burundi: Analyse de la sécurité alimentaire en situation d’urgence au Burundi [Republic of Burundi: Emergency food security in Burundi]. United Nations. https://fscluster.org/sites/default/files/documents/efsa_2017_version_finale.pdf
• Republic of Burundi. (2018, June). Plan National de Développement du Burundi (PND Burundi 2018–2027) [National Development Plan of Burundi (PND Burundi 2018–2027)]. http://www.presidence.gov.bi/wp-content/uploads/2018/08/PND-Burundi-2018-2027-Version-Finale.pdf
• Schaalma, H., Aarø, L. E., Flisher, A. J., Mathews, C., Kaaya, S., Onya, H., Ragnarson, A., & Klepp, K. I. (2009). Correlates of intention to use condoms among Sub-Saharan African youth: The applicability of the theory of planned behaviour. Scandinavian Journal of Public Health, 37(2_suppl), 87–91. https://doi.org/10.1177/1403494808090632
• Schoumaker, B. (2013). La régression linéaire multiple [Multiple linear regression]. In G. Masuy-Stroobant & R. Costa (Eds.), Analyser les données en Sciences sociales: De la préparation des données à l’analyse multivariée [Analyzing Data in the Social Sciences: From Data Preparation to Multivariate Analysis] (pp. 227–252). P.I.E. Peter Lang.
• Sindayihebura, J. F. R., Nganawara, D., Bouba Djourdebbe, F., & Manirakiza, R. (2022). Family planning services supply and non-intention to use the modern contraception among women of childbearing age in union in Burundi. International Journal of Mathematical Analysis, 16(2), 81–88. https://doi.org/10.12988/ijma.2022.912423
• Sindayihebura, J. F. R., & Nkunzimana, A. (2020). Changement climatique et anémie chez les femmes en âge de procréer au Burundi: Approche par la région de residence [Climate change and anemia among women of childbearing age in Burundi: Approach by the region of residence]. Revue de l’Université du Burundi: Séries Sciences Humaines et Sociales, 18(1), 160–173. http://revue.ub.edu.bi/JUB/article/view/84
• Smuseneto, A. (2019). Determinants of childbearing among Thai-Muslim Generation Y in Thailand. Journal of Population and Social Studies, 27(4), 321–333. https://doi.org/10.25133/JPSSv27n4.021
• Tabutin, D., & Schoumaker, B. (2020). La démographie de l’Afrique subsaharienne au XXIe siècle: Bilan des changements de 2000 à 2020, perspectives et défis d’ici 2050 [The demography of Sub-Saharan Africa in the 21st Century: Transformations from 2000 to 2020, Prospects and Challenges to 2050]. Population, 75(2-3), 165–286. https://doi.org/10.3917/popu.2002.0169
• Tiruneh, F. N., Chuang, K. Y., Ntenda, P. A. M., & Chuang, Y. C. (2016). Factors associated with contraceptive use and intention to use contraceptives among married women in Ethiopia. Women & Health, 56(1), 1–22. https://doi.org/10.1080/03630242.2015.1074640
• United Nations Development Programme (UNDP). (2020, December). République du Burundi: Rapport National sur le Développement Humain – Edition 2019: Cohésion sociale, dividende démographique et développement humain durable [Republic of Burundi: National Human Development Report – Edition 2019: Social cohesion, demographic dividend and sustainable human development]. https://www.bi.undp.org/content/burundi/fr/home/library/mdg/RNDH.html