This study aimed to investigate the causal effect of dietary habits on COVID-19 susceptibility, hospitalisation and severity. We used data from a large-scale diet dataset and the COVID-19 Host Genetics Initiative to estimate causal relationships using Mendelian randomisation. The inverse variance weighted (IVW) method was used as the main analysis. For COVID-19 susceptibility, IVW estimates indicated that milk (OR: 0·82; 95 % CI (0·68, 0·98); P = 0·032), unsalted peanut (OR: 0·53; 95 % CI (0·35, 0·82); P = 0·004), beef (OR: 0·59; 95 % CI (0·41, 0·84); P = 0·004), pork (OR: 0·63; 95 % CI (0·42, 0·93); P = 0·022) and processed meat (OR: 0·76; 95 % CI (0·63, 0·92); P = 0·005) were causally associated with reduced COVID-19 susceptibility, while coffee (OR: 1·23; 95 % CI (1·04, 1·45); P = 0·017) and tea (OR: 1·17; 95 % CI (1·05, 1·31); P = 0·006) were causally associated with increased risk. For COVID-19 hospitalisation, beef (OR: 0·51; 95 % CI (0·26, 0·98); P = 0·042) showed negative correlations, while tea (OR: 1·54; 95 % CI (1·16, 2·04); P = 0·003), dried fruit (OR: 2·08; 95 % CI (1·37, 3·15); P = 0·001) and red wine (OR: 2·35; 95 % CI (1·29, 4·27); P = 0·005) showed positive correlations. For COVID-19 severity, coffee (OR: 2·16; 95 % CI (1·25, 3·76); P = 0·006), dried fruit (OR: 1·98; 95 % CI (1·16, 3·37); P = 0·012) and red wine (OR: 2·84; 95 % CI (1·21, 6·68); P = 0·017) showed an increased risk. These findings were confirmed to be robust through sensitivity analyses. Our findings established a causal relationship between dietary habits and COVID-19 susceptibility, hospitalisation and severity.