Principal component analysis (PCA) is a popular method of dietary patterns analysis, but our understanding of its use to describe changes in dietary patterns over time is limited. Using a FFQ, we assessed the diets of 12,572 nonpregnant women aged 20-34 y from Southampton, UK, of whom 2270 and 2649 became pregnant and provided complete dietary data in early and late pregnancy, respectively. Intakes of white bread, breakfast cereals, cakes and biscuits, processed meat, crisps, fruit and fruit juices, sweet spreads, confectionery, hot chocolate drinks, puddings, cream, milk, cheese, full-fat spread, cooking fats and salad oils, red meat, and soft drinks increased in pregnancy. Intakes of rice and pasta, liver and kidney, vegetables, nuts, diet cola, tea and coffee, boiled potatoes, and crackers decreased in pregnancy. PCA at each time point produced 2 consistent dietary patterns, labeled prudent and high-energy. At each time point in pregnancy, and for both the prudent and high-energy patterns, we derived 2 dietary pattern scores for each woman: a natural score, based on the pattern defined at that time point, and an applied score, based on the pattern defined before pregnancy. Applied scores are preferred to natural scores to characterize changes in dietary patterns over time because the scale of measurement remains constant. Using applied scores, there was a very small mean decrease in prudent diet score in pregnancy and a very small mean increase in high-energy diet score in late pregnancy, indicating little overall change in dietary patterns in pregnancy.