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. 2021 Sep 6;18(17):9400.
doi: 10.3390/ijerph18179400.

Heterogeneity of Modern Contraceptive Use among Urban Slum and Nonslum Women in Kinshasa, DR Congo: Cross-Sectional Analysis

Pierre Z Akilimali  1 , Nguyen-Toan Tran  2   3 , Anastasia J Gage  4
Affiliations

Heterogeneity of Modern Contraceptive Use among Urban Slum and Nonslum Women in Kinshasa, DR Congo: Cross-Sectional Analysis

Pierre Z Akilimali et al. Int J Environ Res Public Health. .

Abstract

Urban populations have been increasing at an alarming rate, with faster growth in urban slums than that in nonslums over the past few decades. We examine the association between slum residence and the prevalence of contraceptive use among women of reproductive age, and assess if the effect was modified by household wealth. We conducted cross-sectional analysis comprising 1932 women in slums and 632 women in nonslums. We analyzed the moderating effect through an interaction between household wealth and neighborhood type, and then conducted stratified multivariable logistic-regression analysis by the type of neighborhood. Fewer women living in nonslum neighborhoods used modern methods compared to those living in slum neighborhoods. Within slum neighborhoods, the odds of using modern contraceptive methods were higher among women visited by community health workers than among those who had not been visited. Parity was one of the strong predictors of modern contraceptive use. Within nonslum neighborhoods, women from the wealthiest households were more likely to use modern contraceptives than those from the poorest households. Household wealth moderated the association between the type of neighborhood and modern contraceptive use. The study findings suggested heterogeneity in modern contraceptive use in Kinshasa, with a surprisingly higher contraceptive prevalence in slums.

Keywords: Kinshasa; community health worker; family planning; heterogeneity; urban slum.

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Conflict of interest statement

The authors declare no conflict of interest. The organizations cited above supported the study financially but did not have a role in the design of the study, analysis of the data, or final interpretation of findings.

Figures

Figure 1
Figure 1
Map of Kinshasa and the 58 selected enumeration areas.
Figure 2
Figure 2
Contraceptive prevalence rate by wealth index and type of neighborhoods.
Figure 3
Figure 3
Unmet need and total demand by type of neighborhood.
Figure 4
Figure 4
Bivariate association between neighborhoods and contraceptive-method choice.
See this image and copyright information in PMC

References

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