Socio-Spatial Determinants of Accessibility and Utilization of Pediatric Services in Kinshasa, Democratic Republic of the Congo

Jean Pierre Kambondji Bukaya; Patrick Ngoie Mululu; Jean Claude Kamanda wa Kamanda; Kabamba Kabata; Aketi Loukia

Jean Pierre Kambondji Bukaya
Patrick Ngoie Mululu
Jean Claude Kamanda wa Kamanda
Kabamba Kabata
Aketi Loukia

Keywords: pediatric services, accessibility, healthcare utilization, self-medication, socio-spatial inequalities, Kinshasa, logistic regression

Abstract

This study examines the socio-spatial determinants of accessibility to and utilization of pediatric services in Kinshasa. Using survey data from 1,164 parents and guardians and a series of binary logistic regression models, the analysis explores how geographic position, household socio-demographic profile, transport conditions, perceived barriers, and prior care experiences shape the choice between formal pediatric consultation and self-medication or other non-medicalized practices. The results show pronounced territorial inequalities in the distribution of respondents and in the spatial pattern of pediatric consultation and self-medication across the city. Among the respondents, 67.27% reported resorting to pediatric consultation while 32.71% relied on self-medication or related informal practices. In the bivariate models, consultation was significantly associated with male parenthood, health insurance for the child, non-biological caregiving, higher income brackets, and the use of motorized or public transport. By contrast, walking, lack of transport, and lack of information reduced the odds of formal consultation. In adjusted models, older parental age remained negatively associated with consultation, whereas male sex, Protestant affiliation, higher monthly income, older child age, public transport use, and some disease contexts increased the likelihood of consultation. Perceptions of service quality showed mixed and sometimes paradoxical effects: courtesy encouraged consultation, but long waiting times consistently reduced it, while evaluations of care quality were not uniformly associated with formal care-seeking. Overall, access to pediatric services in Kinshasa is jointly structured by socio-economic resources, mobility conditions, perceived constraints, and uneven urban geography. Policies that improve transport access, reduce waiting time, strengthen financial protection, and correct spatial disparities in service distribution could increase timely pediatric care utilization.

References

Agresti, A. (2018). An introduction to categorical data analysis (3rd ed.). Wiley.
Andersen, R. M. (1995). Revisiting the behavioral model and access to medical care: Does it matter? Journal of Health and Social Behavior, 36(1), 1–10.
Cochran, W. G. (1977). Sampling techniques (3rd ed.). Wiley.
Colvin, C. J., Smith, H. J., Swartz, A., Ahs, J., de Heer, J., Opiyo, N., ... & George, A. (2013). Understanding care-seeking for child illness in sub-Saharan Africa: A systematic review and conceptual framework based on qualitative research. Social Science & Medicine, 86, 66–78.
De Boeck, F., & Plissart, M. F. (2014). Kinshasa: Tales of the invisible city. Leuven University Press.
Gilson, L. (2003). Trust and the development of health care as a social institution. Social Science & Medicine, 56(7), 1453–1468.
Hosmer, D. W., Lemeshow, S., & Sturdivant, R. X. (2013). Applied logistic regression (3rd ed.). Wiley.
Hussain, S., & Malik, F. (2016). Self-medication practices: A threat to health care system. African Journal of Pharmacy and Pharmacology, 10(45), 983–988.
Kish, L. (1965). Survey sampling. Wiley.
Lagomarsino, G., Garabrant, A., Adyas, A., Muga, R., & Otoo, N. (2012). Moving towards universal health coverage: Health insurance reforms in nine developing countries in Africa and Asia. The Lancet, 380(9845), 933–943.
Lohr, S. L. (2010). Sampling: Design and analysis (2nd ed.). Brooks/Cole.
Menard, S. (2002). Applied logistic regression analysis (2nd ed.). Sage.
Molyneux, C., Murira, G., Masha, J., & Snow, R. W. (2002). Intra-household relations and treatment decision-making for childhood illness: A Kenyan case study. Journal of Biosocial Science, 34(1), 109–131.
Noor, A. M., Zurovac, D., Hay, S. I., Ochola, S. A., & Snow, R. W. (2006). Defining equity in physical access to clinical services using geographical information systems as part of malaria planning and monitoring in Kenya. Tropical Medicine & International Health, 11(7), 1115–1125.
Penchansky, R., & Thomas, J. W. (1981). The concept of access: Definition and relationship to consumer satisfaction. Medical Care, 19(2), 127–140.
Peng, C.-Y. J., Lee, K. L., & Ingersoll, G. M. (2002). An introduction to logistic regression analysis and reporting. The Journal of Educational Research, 96(1), 3–14.
Peters, D. H., Garg, A., Bloom, G., Walker, D. G., Brieger, W., & Rahman, M. H. (2008). Poverty and access to health care in developing countries. Annals of the New York Academy of Sciences, 1136, 161–171.
Tanser, F., Gijsbertsen, B., & Herbst, K. (2006). Modelling and understanding primary healthcare accessibility and utilization in rural South Africa: An exploration using a geographical information system. Social Science & Medicine, 63(3), 691–705.
Tatem, A. J., Noor, A. M., & Hay, S. I. (2012). Assessing spatial accessibility to health services in sub-Saharan Africa. Tropical Medicine & International Health, 17(5), 618–626.
World Health Organization. (2022). World health statistics 2022: Monitoring health for the SDGs. WHO.