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The effects of extreme heat and climate change on maternal and neonatal health outcomes in low-income settings - NU/LSHTM project

Title of PhD project / theme

The effects of extreme heat and climate change on maternal and neonatal health outcomes in low-income settings

Supervisory team

LSHTM: Shakoor Hajat (Lead) Shakoor.Hajat@lshtm.ac.uk,
Veronique Filippi Veronique.Filippi@lshtm.ac.uk, Sari Kovats Sari.Kovats@lshtm.ac.uk

NU: Chris Fook Sheng Ng chrisng@nagasaki-u.ac.jp, Mitsuaki Matsui mmatsui@nagasaki-u.ac.jp

Brief description of project / theme

Against the backdrop of a changing climate, there are growing concerns that exposure to high ambient temperatures during pregnancy adversely affects maternal and neonatal health (MNH).1 However, to date there is very little evidence on impacts in low-income settings, despite the fact that maternal and neonatal deaths in these settings are frequent, facilities can experience high indoor temperatures, health systems have low adaptive capacity and access to services is increasingly disrupted by climate events.

This PhD will assess the impacts of current and future climate conditions on maternal, perinatal and neonatal health outcomes in low-income settings, in particular the effects of rare outcomes – such as 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 where adverse effects become apparent and explore possible effects of cumulative exposure and the role of modifiers in order to characterise groups of pregnant women and neonates most at risk of heat-related conditions. The primary approach will be to use a time-to-event study (survival analysis). This 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 Poisson time-series regression analysis conducted on the daily number of events, adjusting for season, air pollution and other time-varying confounders.

This PhD will form one part of the larger CHAMNHA (Climate, Heat And Maternal and Neonatal Health) study which is a three-year research project funded by the Belmont Forum, led by an inter-disciplinary and inter-sectoral research team representing expertise in epidemiology, biostatistics, climatology, and social sciences. The consortium addresses key knowledge gaps in Sub-Saharan African countries to improve adaptation to high temperatures and to increase resilience in health care systems. The PhD candidate will benefit from the expertise of this larger study as well as links to stakeholders to ensure maximum impact of their research.

  1. Chersich M, Pham MD, Areal A, Haghighi M, Manyuchi A, Swift C, Wernecke B, Robinson M, Hetem R, Boeckmann M, Hajat S. Does exposure to high temperatures in pregnancy increase risk for preterm birth, low birth weight and still births? A systematic review and meta-analysis. BMJ; in press.

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 monthly as well as fortnightly zoom meetings with the lead-supervisors. Advisory committee members will be appointed either internal or external to NU and LSHTM for additional expertise as necessary. The project will benefit from the larger CHAMNHA project and will ensure an enhanced research and training experience for the PhD student as well as for the two host institutions.

Particular prior educational requirements for a student undertaking this project

The candidate should have a Masters 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 and other scientific outputs and policy briefs; conducting systematic literature reviews; communication skills.