Rachel Ganly

I am a first-year DPhil student in Sociology at the University of Oxford’s Leverhulme Centre for Demographic Science. My research interests are social stratification, family formation and other topics in social demography more broadly. Prior to my DPhil studies, I spent several years working for PathFinders in Hong Kong, an organization which assists domestic workers during pregnancy and childbirth. I hold an MPhil in Social Science from Hong Kong University of Science and Technology, and BSc in Mathematics from the University of Bath.  
My DPhil project is supported by the Leverhulme Trust Biopsychosocial Doctoral Scholarship Programme, ‘Moving Beyond Inequality’, which aims to reduce the impact of social disadvantages on children’s life chances. My project aims to contribute to understanding about (1) how exposure to adverse events during pregnancy impacts birth and early-life outcomes, (2) whether these effects are heterogeneous across social groups with different levels of social disadvantage, and (3) why these effects may be heterogenous. These causal effects are critical to understand, because health at birth and early cognitive outcomes are a key predictor of health and socioeconomic attainment over the life course. 

Moreover, a growing body of interdisciplinary research suggests that maternal social disadvantage leads to poorer birth outcomes. This may operate through a variety of factors such as greater levels of exposure to environmental stressors such as pollution, violence and economic hardship, poorer health behaviours and worse underlying maternal health - including higher exposure to, or response to, the effects of pandemics. Understanding the complex and interconnected social processes which operate alongside these biological mechanisms is thus critical for improving social outcomes and informing policy.  

However, disentangling the causal pathways between socio-economic status, in-utero health and early-life outcomes is often complicated by the issue of confounding due to unobserved or unmeasured variables. In order to more carefully examine these effects, my research uses longitudinal, linked administrative data from Sweden and Finland, which includes medical records of children and parents, pregnancy and birth records, as well as education, occupation and income data across the entire population. The data therefore allows clearer causal identification of the potential mechanisms through which adverse events may have affected health at birth. In addition, it enables us to better understand the influence of underlying parental health on these impacts, and to examine whether parental behaviours in pregnancy or early childhood may have compensated or reinforced effects of a disruption. 

One key part of this DPhil project will be examining the impact of exposure to the COVID-19 pandemic during pregnancy on children’s early life outcomes. The pandemic was a shock likely to affect infant health in-utero through multiple pathways, including maternal infection, stress and anxiety, and economic adversity. For example, medical research suggests that maternal COVID-19 infection during pregnancy may have impacted intrauterine growth and/or induced early delivery, leading to adverse effects for new born children. In addition, acute stress response could be triggered in expectant mothers who experience a lockdown, the death of a relative or friend due to COVID-19, or who endure economic adversity due to, for example, job loss. Experiencing acute stress triggers the production of increased stress hormones, which can result in lower birth weight and a shorter gestational period. Moreover, the impact of these factors may be different amongst different socio-economic and demographic groups. The research uses a Difference-in-Differences (DiD) design to examine whether exposure to COVID-19 in-utero affected key measures of health at birth and whether the timing of the in-utero exposure mattered. It also aims to use machine learning methods, and parametric and nonparametric techniques to investigate whether and why the effect of COVID-19 exposure was heterogeneous by measures of socioeconomic status.  

My thesis aims to help illuminate whether and how exogenous shocks might have differential impacts on children’s early life outcomes, and how intergenerational disadvantage is transmitted in early life, even in countries with highly developed social welfare systems and equal access to healthcare such as Sweden and Finland. The research is thus not only of academic significance but is important for guiding public policy which can mitigate social inequality and improve individual wellbeing.  


Rachel Ganly is supervised by Professor Melinda Mills.