Unmasking inequalities: Sub-national maternal and child mortality data from two urban slums in Lagos, Nigeria tells the story

Nigeria has one of the highest maternal mortality ratios in the world as well as high perinatal mortality. Unfortunately, the country does not have the resources to assess this critical indicator with the conventional health information system and measuring its progress toward the goal of ending preventable maternal deaths is almost impossible. Médecins Sans Frontières (MSF) conducted a cross-sectional study to assess maternal and perinatal mortality in Makoko Riverine and Badia East, two of the most vulnerable slums of Lagos. The study was a cross-sectional, community-based household survey. Nearly 4,000 households were surveyed. The sisterhood method was utilized to estimate maternal mortality and the preceding births technique was used to estimate newborn and child mortality. Questions regarding health seeking behavior were posed to female interviewees and self-reported data were collected. Data was collected from 3963 respondents for a total of 7018 sisters ever married. The maternal mortality ratio was calculated at 1,050/100,000 live births (95% CI: 894-1215), and the lifetime risk of maternal death at 1:18. The neonatal mortality rate was extracted from 1967 pregnancies reported and was estimated at 28.4/1,000; infant mortality at 43.8/1,000 and under-five mortality at 103/1,000. Living in Badia, giving birth at home and belonging to the Egun ethnic group were associated with higher perinatal mortality. Half of the last pregnancies were reportedly delivered in private health facilities. Proximity to home was the main influencing factor (32.4%) associated with delivery at the health facility. The maternal mortality ratio found in these urban slum populations within Lagos is extremely high, compared to the figure estimated for Lagos State of 545 per 100,000 live births. Urgent attention is required to address these neglected and vulnerable neighborhoods. Efforts should be invested in obtaining data from poor, marginalized, and hard-to-reach populations in order to identify pockets of marginalization needing additional resources and tailored approaches to guarantee equitable treatment and timely access to quality health services for vulnerable groups. This study demonstrates the importance of sub-regional, disaggregated data to identify and redress inequities that exist among poor, remote, vulnerable populations-as in the urban slums of Lagos.