Travel Time and Stillbirths in Nigeria: A Spatial Analysis

Stillbirths remain a significant yet under-prioritised public health issue in Nigeria, which impacts women and their families. In 2021, 182,000 babies in Nigeria died after 28 weeks of pregnancy, either before labour began or during childbirth. These are known as stillbirths, and they accounted for nearly 10 percent of all stillbirths worldwide that year. Imo State, in southeast Nigeria, presents a striking paradox. Although it has the highest access to maternal health services in the region, it also records one of the highest rates of stillbirths. My DPhil research, the first case-control study on this issue in Imo State, found that women who were referred between hospitals had nearly four times the risk of experiencing a stillbirth. This suggests that delays in reaching appropriate care, especially during labour, may be a major contributing factor. Building on this research, I now plan to study how travel time to health facilities affects the chances of stillbirth compared with livebirths. One critical gap in understanding stillbirths is what happens between the time a woman decides to seek care and when she actually arrives at a hospital. These are known as “Type II delays” and are particularly important in fast-growing urban areas like Imo State. A ground-breaking study in Lagos, Nigeria, by my proposed mentor, Associate Professor Banke-Thomas, showed that longer travel times significantly increased the risk of stillbirth among women who arrived in emergency situations. His research used data from 3,378 births, including 408 stillbirths. To carry out similar research, I will need advanced training in spatial epidemiology, which studies how geography and health outcomes are linked. I plan to take specialist courses at the London School of Hygiene and Tropical Medicine, where I will also have the chance to learn from experts like Chris Grundy, a leading human geographer. These courses will equip me to analyse travel time data using two key sources. One is my existing dataset from my PhD, which includes 432 stillbirths and 381 livebirths. The second is an innovative dataset developed by my mentor using Google data to calculate more realistic estimates of how long it takes to reach care. I also bring relevant experience from my time as a research fellow on the OnTIME project, which studied access to emergency obstetric care across Nigeria, including Imo State. Although that project found that 97.3 percent of women in Imo live within 30 minutes of a hospital, a travel time of more than 10 minutes was linked to a higher risk of stillbirth in the Lagos study. This link has not yet been explored in Imo State, and my project aims to address this gap. By combining advanced spatial tools with real-world data, this research will provide vital insights into how travel time affects stillbirths. I will also examine whether babies who die before labour starts (antepartum stillbirths) are affected differently than those who die during labour (intrapartum stillbirths). This distinction will help highlight critical gaps in access and responsiveness of emergency obstetric care and inform targeted solutions in Imo State. The one-year fellowship will provide a strong foundation for my future career. I plan to publish my findings in a peer-reviewed journal and share them at public health forums. Ultimately, this study will help reduce preventable stillbirths by ensuring women can reach life-saving care in time.