BACKGROUND: This cross-sectional study examined meal patterns based on daily energy intake distribution and their associations with nutrient and food intake, diet quality, and body mass index (BMI). METHODS: Body height, weight, habitual dietary intake and the Healthy Eating Index (HEI)-2020 score by eating occasion were assessed using the validated Meal-based Diet History Questionnaire among employees (465 males and 193 females aged 20-75 years) in the Tokyo Metropolitan Area. Meal patterns were extracted based on % energy intake from breakfast, lunch, dinner, and snacks using K-means clustering by sex. Dietary intake, HEI-2020 score, and BMI were then compared between sex-specific meal patterns. RESULTS: The identified patterns were "large lunch and dinner" (n = 299), "three meals-balanced" (n = 97), and "large dinner" (n = 69) patterns in males and "large dinner" (n = 79); "large afternoon snack" (n = 54) and "large lunch" (n = 60) patterns in females. The HEI-2020 scores were the highest for dinner, followed by breakfast, lunch, and snacks in any meal pattern. Males with the "large dinner" pattern had lower intakes of rice, bread, carbohydrates, dietary fibre, and thiamine; higher intake of alcoholic beverages; and higher HEI-2020 scores than those with other patterns. Females with a "large dinner" pattern had a lower intake of bread, confectionery, total and saturated fats, and carbohydrates; higher intake of fish, meat, and alcoholic beverages; higher HEI-2020 scores; and lower BMI. Thus, a meal pattern with higher energy intake distribution at dinner was associated with higher diet quality among males and females and lower BMI among females in Japanese workers. CONCLUSIONS These findings suggest that improving the quality of the meal with the highest energy contribution could help enhance overall dietary quality and metabolism.
Humans ; Female ; Male ; Middle Aged ; Adult ; Energy Intake ; Body Mass Index ; Cross-Sectional Studies ; Aged ; Meals ; Young Adult ; Tokyo ; Feeding Behavior ; Diet/statistics & numerical data*