Background: There is a growing consensus that the neighbourhood food environment may be an important risk factor for diet and diet-related health. In the UK, however, the evidence for such a relationship is mixed. The aim of this PhD was to explore the relationship between the neighbourhood food environment and food and drink purchasing, and how this relationship changed during the COVID- 19 pandemic. This was achieved through the following objectives: 1) to ascertain changes in food and drink purchasing patterns during the COVID-19 pandemic; 2) to explore associations between the neighbourhood food environment and purchases before and 3) during the COVID-19 pandemic; and 4) to explore associations between area deprivation and exposure to online food delivery services during the COVID-19 pandemic. All objectives considered whether effects varied by region. Methods: Studies employed longitudinal and cross-sectional designs and a range of regression and spatial analysis techniques. Primary outcomes were food and drink purchasing derived from a consumer panel reporting food and drink items purchased for at-home consumption (n=2,118 households) and for out-of-home (OOH) consumption (n=447 individuals) in London and the North of England for January 2019 to June 2020. Population density, area deprivation, and neighbourhood food environment exposure were obtained from publicly available data sources. Digital food environment exposure was derived from three online food delivery platforms. Results: Considerable changes in weekly food and drink purchasing were observed during the pandemic, including a 17% (95% CI 15 to 20) increase in total energy purchased, and increases in alcoholic beverage purchases, which were greatest among highest usual purchasers (708 ml, 95% CI 381 to 1,035 ml). These changes, however, were not associated with the neighbourhood food environment, as associations between neighbourhood food environment exposure and purchasing were observed neither before nor during pandemic restrictions in 2020. The only associations observed were between higher distance to OOH outlets and reduced purchasing of ultra-processed foods in 2019 (IR 0.989, 95% CI 0.982 to 0.997), and between higher density of chain supermarkets in the neighbourhood and a reduction in total energy purchased (IR 0.982, 95% CI 0.969 to 0.995). Further, the effects of food environment exposures on alcohol purchasing were observed to vary by geographical context in 2019. Exposure to online food delivery services was associated with area deprivation, with higher deprivation associated with higher exposure in the North of England and vice versa in London. During the first year of the pandemic, exposure increased by 113%, but existing geographical inequalities were not widened. Conclusions: This project contributes to the neighbourhood food environment literature by exploiting the pandemic as natural experiment, utilising granular, causally proximal outcome data, and exploring changes the digital food environment. In line with previous work, findings indicate that there may not be a universal effect of the neighbourhood food environment. Geographical exposure-effect heterogeneity needs to be explicitly addressed in research and policy. Future research is needed to monitor dietary changes following the pandemic, and policy may consider focussing efforts on elements of the food environment other than the residential neighbourhood, including the inequalities in exposure to the digital food environment.