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Introduction Many urban residents in low- and middle-income countries live in unfavorable conditions with few healthcare facilities, calling to question the long-held view of urban advantage in health, healthcare access and utilization. We explore the patterns of healthcare utilization in these deprived neighborhoods by studying three such settlements in Nigeria. Methods The study was conducted in three slums in Southwestern Nigeria, categorized as migrant, indigenous or cosmopolitan, based on their characteristics. Using observational data of those who needed healthcare and used in-patient or out-patient services in the 12 months preceding the survey, frequencies, percentages and odds-ratios were used to show the study participants’ environmental and population characteristics, relative to their patterns of healthcare use. Results A total of 1,634 residents from the three slums participated, distributed as 763 (migrant), 459 (indigenous) and 412 (cosmopolitan). Residents from the migrant (OR = 0.70, 95%CI: 0.51 to 0.97) and indigenous (OR = 0.65, 95%CI: 0.45 to 0.93) slums were less likely to have used formal healthcare facilities than those from the cosmopolitan slum. Slum residents were more likely to use formal healthcare facilities for maternal and perinatal conditions, and generalized pains, than for communicable (OR = 0.50, 95%CI: 0.34 to 0.72) and non-communicable diseases (OR = 0.61, 95%CI: 0.41 to 0.91). The unemployed had higher odds (OR = 1.45, 95%CI: 1.08 to 1.93) of using formal healthcare facilities than those currently employed. Conclusion The cosmopolitan slum, situated in a major financial center and national economic hub, had a higher proportion of formal healthcare facility usage than the migrant and indigenous slums where about half of families were classified as poor. The urban advantage premise and Anderson behavioral model remain a practical explanatory framework, although they may not explain healthcare use in all possible slum types in Africa. A context-within-context approach is important for addressing healthcare utilization challenges in slums in sub-Saharan Africa.
This study is part of a multi-country study under the Global Health Research Unit on Improving Health in Slums. The survey methodology and map description for each study site have been published in detail elsewhere [38, 42]. The survey adopted a cross-sectional design within three purposively selected slums in the urbanized cities of Southwestern Nigeria. We summarized the slum characteristics and reclassified them as follows: A total of 1500, 1001 and 977 adult participants responded to the survey questions in the migrant, indigenous and cosmopolitan slums, respectively. Of these survey respondents, those who responded that they needed healthcare were 892 (59.7%) in the migrant slum, 573 (52.2%) in the indigenous slum and 497 (50.9%) in the cosmopolitan slum. Out of those who needed care, 880, 560 and 482 participants in the migrant, indigenous and cosmopolitan slum reported receiving care in-patient or out-patient services. For this study, we focused on those who indicated that they needed healthcare, used in-patient and out-patient services and specified the healthcare facility used in the 12 months preceding the survey. Participants relying on home remedies were also excluded from the analysis. Those who met these criteria in the three slums were 763 (migrant), 459 (indigenous) and 412 (cosmopolitan) slum residents. Ethical approval was obtained from the Research Ethics Committee of the Oyo State Ministry of Health (AD13/479/657) and of Lagos State (LREC.06/10/993) as well as from the University of Warwick Biomedical and Scientific Research Ethics Sub-Committee (REGO-2017-2043 AM01). In addition, we obtained written consent from each of the participants. The survey instruments were uploaded into an Open Data Kit (ODK) application. All interviews were conducted in either English or the local language spoken in each slum, Yoruba or Hausa. Trained research assistants used the ODK forms to collect information from participants about household healthcare utilization. Field supervisors ensured quality control of data. Data uploaded to the server were cleaned to eliminate errors. The dependent variable for this study is the healthcare facility accessed. Slum residents were asked whether they had sought healthcare in the preceding 12 months and, if so, to provide details about their most recent visit to health services, including where they had sought care. We classified their answers by types of healthcare facility used: formal healthcare facility (public and private hospitals/clinics/primary healthcare centers and registered pharmacies) or informal healthcare facility (patent medicine vendors and traditional care). The independent variables were presenting medical complaints, age, gender, marital status, education, employment status, household poverty and health insurance coverage. Presenting medical complaints were grouped into communicable diseases (including malaria, tuberculosis and HIV), maternal and perinatal conditions, non-communicable diseases (including hypertension, diabetes and cancer) and generalized pain/others. Education was grouped into below secondary; secondary and tertiary. Employment status was categorized into employed and not employed while household poverty was measured as spent less than US$1.90 per day or spent US$1.90 and above per day. The health insurance coverage responses were yes or no). The participant’s age was grouped into young adulthood: 18–35 years; middle age: 36 to 55 years; older adulthood: 56 years or older, Gender of the participant was either male or female and marital status was grouped into married/cohabiting; divorced/separated/widowed; never married/cohabited. This was an exploratory analysis using observational data of slum residents who indicated that they needed healthcare, used in-patient and out-patient services, and specified the healthcare facility used in the 12 months preceding the survey We used descriptive statistics (frequency and percentages) to show the study participants’ environmental and population characteristics and pattern of health care use among the slum residents. We further explored the odds of formal healthcare service use among different slums by presenting medical complaints, age, sex, marital status, education, employment status and household poverty and health insurance coverage using unadjusted logistic regression. We used IBM SPSS software for the statistical analysis.
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