Unintended Pregnancy and Contraceptive Use Among Residents of Slum and Non-Slum Areas in Kinshasa, DRC: A Comparative Analysis Using PMA Survey Data (2014-2020)

Author:

Kabasubabo Francis K.1,Faye Cheikh2,Wado Yohannes D.2,Akilimali Pierre Z.3

Affiliation:

1. Patrick Kayembe Research Center

2. African Population and Health Research Center

3. University of Kinshasa

Abstract

Abstract

Urbanization is rapidly increasing worldwide, with slum settlements emerging as a significant concern, particularly in low- and middle-income countries like the Democratic Republic of Congo. This study examines contraceptive use and unintended pregnancies among women residing in slum and non-slum areas of Kinshasa between 2014 and 2020. We analyzed data from the Performance Monitoring for Action survey conducted between 2014 and 2020, encompassing 19,568 women. Logistic regression, adjusted for socio-demographic factors, was used to assess the association between residence type (slum vs. non-slum) and contraceptive use as well as unintended pregnancies. Results indicate a rise in contraceptive prevalence in Kinshasa from 2014 to 2020, with slum areas consistently exhibiting higher prevalence rates compared to non-slum areas. Long-term contraceptive method prevalence increased from 4% to 8% in slum areas, contrasting with the stable rate of approximately 3% in non-slum areas over the same period. Although there was a decline in unintended pregnancy prevalence in slum areas in recent years, rates remain elevated compared to non-slum areas. In bivariate analysis, women residing in slum areas were twice as likely to report unintended pregnancies compared to those in non-slum areas (OR: 2.33; 95% CI; 2.008 – 2.698). However, after adjusting for socio-demographic characteristics, residence type (slum vs. non-slum) did not significantly influence the occurrence of unintended pregnancies. These findings underscore the persistent challenges faced by women in slum areas regarding unintended pregnancies, despite improvements in contraceptive prevalence. Addressing these disparities requires targeted interventions tailored to the specific needs of urban populations, particularly those residing in slum settlements.

Publisher

Springer Science and Business Media LLC

Reference27 articles.

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3. UN-Habitat urban data site. 2018. https://data.unhabitat.org/datasets/cd4e1deb72ea49bd8f3403f8a9edfe6d/explore.

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