Objectives The objective of this research was to develop and test a low-burden method to gather diet quality data that is comparable across countries, consistently implemented, and easily understood by respondents. A common method for collecting dietary diversity data consists of open-ended food group questions, e.g., Yesterday, did you eat any porridge, bread, rice, pastaor otherfoods made from grains? Our hypotheses were (1) the majority of consumption of each food group could be represented by a few foods in each country setting (sentinel foods); (2) respondents who did not eat the listed examples might misclassify other foods they ate as belonging to the same food group. We sought to refine the method by modifying each question to be closed-ended. Methods We developed a 26-item diet quality questionnaire (DQ-Q), where each yes/no question asks about consumption of a distinct food group in the previous day or night. We tested the first hypothesis using 24-hour nationally representative dietary intake data from Brazil (Individual Food Intake Survey 2008–2009) and the United States (NHANES 2009–2014). We categorized each food and beverage item into the 26 food groups of the DQ-Q, and identified the most commonly consumed foods in each. Individuals were categorized according to whether they had consumed at least one item in each food group (1) or not (0). We tested the second hypothesis through 82 cognitive interviews in five languages São Paulo and New York City, in which we compared responses to closed-ended sentinel food questions to open-ended food group questions. Results On average, 1–7 sentinel foods captured 96–97% of people who consumed each food group (range 85–100%). Respondents in both countries sometimes miscategorized foods when asked open-ended food group questions, and open-ended questions presented an additional cognitive burden. The DQ-Q took 3–5 minutes to administer. Conclusions The DQ-Q is a rapid low-burden method to collect diet quality data. Closed-ended questions using sentinel foods capture the vast majority of consumption and are better understood by respondents than open-ended list-based methods, for measuring dietary diversity and other aspects of diet related to NCD risk. Funding Sources Funding for this work was provided by the Global Alliance for Improved Nutrition (GAIN) and the Swiss Agency for Development and Cooperation (SDC).