Title of PhD project / theme
The effects of extreme heat and climate change on maternal and neonatal health in sub-Saharan Africa.
Brief description of project / theme
There is growing evidence that exposure to high ambient temperatures during pregnancy adversely affects maternal and neonatal health.1, 2 However, to date there is very little evidence on impacts in low-income settings in sub-Saharan Africa despite the high burden of maternal and neonatal deaths and increasing vulnerability to environmental factors.
This PhD will quantify the impacts of current and future climates on maternal, perinatal and neonatal health outcomes in sub-Saharan Africa. The project will examine effects of heat exposure on a range of rare outcomes – including pre-eclampsia, antepartum haemorrhage, puerperal infections, premature rupture of membranes, and early neonatal death – where the use of multiple datasets will ensure sufficient power to estimate effects robustly. The work will identify important ambient temperature thresholds above which adverse effects become apparent, explore possible effects of cumulative heat exposure during pregnancy, and examine the role of effect modifiers in order to characterise groups of pregnant women and neonates most at risk of heat-related conditions. The PhD candidate will then use these and other findings to estimate health-burdens attributable to extreme temperature that can be used to support action on prevention measures. The project will assess the impact of climate scenarios on maternal and neonatal health, taking into account the rapid demographic and social changes anticipated in Africa in the coming decades.
The primary approach for data analysis will be to use time-to-event (survival) analysis, which will make use of the gestational age information available for each birth. Cross-basis functions will be used to model possible non-linear and delayed effects of exposure. For other outcomes where gestation time is unimportant, data will be collapsed by date of event, and then zero-inflated Poisson regression will be conducted on the daily number of events, adjusting for season, air pollution and other time-varying confounders.
This project will use longitudinal datasets from health surveillance programmes, birth registries, and large cohort studies, which will be linked with meteorological observations or climate reanalysis data based on time (day of event) and space (location). Daily climate model data from the CMIP6 projections will be used to estimate future burdens attributable to climate change by region.
This PhD will be embedded within an established collaboration on maternal health and climate change. The collaboration addresses key knowledge gaps to improve adaptation to high temperatures and to increase resilience in health systems in sub-Saharan Africa. The PhD candidate will benefit from the expertise of this larger collaboration, with lead investigators Prof Mathew Chersich and Dr Shakoor Hajat on the advisory panel. The candidate will also benefit from established links stakeholders to ensure maximum impact of their research.
CHAMNHA consortium (Climate, Heat and Maternal and Neonatal Health in Africa), 2020-2023, funded by the Belmont Forum. Kovats, Filippi, Chersich, Hajat, Part.
Center DSI-Africa Research Hub, funded by US National Institutes of Health. 2021-2025. Chersich.
Associations between high temperatures in pregnancy and risk of preterm birth, low birth weight, and stillbirths: systematic review and meta-analysis. Chersich MF, et al, Climate Change and Heat-Health Study Group. 2020. BMJ 2020; 371:m3811
Maternal and newborn health risks of climate change: A call for awareness and global action. Roos N, Kovats S, Hajat S, Filippi V, Chersich M et al., CHAMNHA Consortium. 2021. Acta obstetricia et gynecologica Scandinavica
The role of LSHTM and NU in this collaborative project
The student will be based mostly at LSHTM for training and data analysis but will spend at least 6 months at Nagasaki University for supplemental training and supervisory inputs, including broadening of clinical knowledge. Full supervisory meetings will be conducted remotely every month. Lead supervisors will also meet with the student every fortnight.
Advisory committee members will include Dr Mitsuaki Matsui, expert on maternal health at Nagasaki University, and members of the wider research collaboration will provide additional expertise (Prof Matthew Chersich, Dr Shakoor Hajat). The project will benefit from the larger CHAMNHA/Hub consortia, and engagement with MARCH (Centre on Maternal Health) and the Centre on Planetary Health and Climate Change (WHO Collaborating Centre on Climate Change) at LSHTM.
Particular prior educational requirements for a student undertaking this project
The candidate should have a Master’s degree in epidemiology, public health or related subject, and be trained in handling large datasets and conducting quantitative analysis. An interest in global environmental health and/or maternal and neonatal health research is desirable.
Skills we expect a student to develop/acquire whilst pursuing this project
Advanced statistical analysis in environmental and maternal epidemiology; large-scale data management; software programming skills; writing peer-reviewed papers, other scientific outputs and policy briefs; conducting systematic literature reviews; communication skills.