Associations of Skipping Breakfast, Lunch, and Dinner with Weight Gain and Overweight/Obesity in University Students: A Retrospective Cohort Study

Abstract

Although multiple studies have identified skipping breakfast as a risk factor for weight gain, there is limited evidence on the clinical impact of skipping lunch and dinner on weight gain. This retrospective cohort study including 17,573 male and 8860 female university students at a national university in Japan, assessed the association of the frequency of breakfast, lunch, and dinner with the incidence of weight gain (≥10%) and overweight/obesity (body mass index ≥ 25 kg/m²), using annual participant health checkup data. Within the observation period of 3.0 ± 0.9 years, the incidence of ≥10% weight gain was observed in 1896 (10.8%) men and 1518 (17.1%) women, respectively. Skipping dinner was identified as a significant predictor of weight gain in multivariable-adjusted Poisson regression models for both men and women (skipping ≥ occasionally vs. eating every day, adjusted incidence rate ratios, 1.45 (95% confidence interval: 1.04-2.01) and 1.67 (1.33-2.09) in male and female students, respectively), whereas skipping breakfast and lunch were not. Similarly, skipping dinner, not breakfast or lunch, was associated with overweight/obesity (1.74 (1.07-2.84) and 1.68 (1.02-2.78) in men and women, respectively). In conclusion, skipping dinner predicted the incidence of weight gain and overweight/obesity in university students.

Keywords: breakfast skipping; dinner skipping; lunch skipping; meal frequency; overweight/obesity; retrospective cohort study; weight gain.

Figure 1

Flow diagram of inclusion and exclusion of study participants. BMI, body mass index.

Figure 2

Dinner frequency and the cumulative probabilities of the incidence of ≥10% weight gain (a,b) and BMI ≥ 25 kg/m² (c,d) in male (a,c) and female (b,d) students. BMI, body mass index.

Figure 3

Meal frequency and incidence of ≥10%weight gain (a,b) and body mass index (BMI) ≥ 25 kg/m² (c,d). BMI, body mass index. Model 1, unadjusted. Model 2, adjusted for admission year (2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, and 2015), age (18, 19, 20, and ≥21 years), BMI (kg/m²), smoking status (non-smokers and smokers), drinking status (non-drinkers and drinkers), dinner time (before 7 PM, 7–9 PM, 9–11 PM, and after 11 PM), and sleep duration on weekdays (<5, 5–6, 6–7, 7–8, and ≥8 h). Model 3, adjusted for covariates in model 2 and frequencies of breakfast, lunch, and dinner (e.g., breakfast frequency was adjusted for lunch and dinner frequencies). * Not adjusted for smokers because of no incidence of the outcome in smokers (n = 13).

Figure 4

Baseline dinner frequency and dinner frequency 1 and 3 years after admission in male (a) and (b) female students. Dark and pale gray bars indicate the proportion of eating dinner every day and skipping dinner ≥ occasionally, respectively. In both male and female students, baseline dinner frequency reflected dinner frequency 1 and 3 years after admission almost perfectly (Gwet’s AC1 coefficient > 0.8).