Hybrid methods are a suitable option to extract dietary patterns associated with health outcomes. This study aimed to identify dietary patterns of Brazilian adults (20-59 years old; n=28,153) related to dietary components associated with the risk of obesity. Data from the 2017-2018 Brazilian National Dietary Survey were analyzed. Food consumption was obtained through 24-hour recall. Dietary patterns were extracted using partial least squares regression. The selected response variables were energy density (ED), percentage of total fat (%TF), and fiber density (FD). In addition, 32 food groups were established as predictor variables. The first dietary pattern, named as energy-dense and low-fiber (ED-LF), included with positive factor loadings: solid fats, breads, added-sugar beverages, fast foods, sauces, pasta, and cheeses, and with negative factor loadings: rice, beans, vegetables, water, and fruits. Higher adherence to the ED-LF dietary pattern was observed for individuals >40 years old, from urban areas, in the highest income level, who were not on a diet, reporting away-from-home food consumption, and having ≥1 snack/day. Eating patterns with similar characteristics are often associated with an increased risk of obesity. The results are consistent with recommendations to increase the consumption of fresh foods and to reduce ultra-processed products.