Examining the correlates of meal skipping in Australian young adults
journal contributionposted on 2019-04-03, 00:00 authored by Felicity Pendergast, Katherine LivingstoneKatherine Livingstone, Tony WorsleyTony Worsley, Sarah McNaughtonSarah McNaughton
BACKGROUND: Meal skipping is associated with diet-related chronic disease risk and is highly prevalent in young adults. Despite this, the correlates of meal skipping in this population group are unknown. Therefore, the aim of this study was to examine the prevalence and correlates of meal skipping in young adults. METHODS: Young adults aged 18-30 years (n = 578) (24% male, 76% female) used 'FoodNow', a purpose designed real-time smartphone application to record food and beverage consumption over four non-consecutive days. The day following each reporting day, participants were asked about their previous day's eating occasions; if any eating occasions were not reported or if any were skipped. These data were used to categorise participants into specific meal skippers (breakfast, lunch and/or dinner skipper). Participants also completed an online questionnaire, which contained measures of correlates from the social-ecological framework across the individual, social-environmental and physical-environment domains. Logistic regression analyses were used to examine associations between specific meal skipping behaviours and measured correlates. RESULTS: Individual domain correlates (education status, smoking status and time scarcity) were associated with varying meal skipping behaviours, while no correlates from the social-environmental or physical-environmental domains of the social-ecological framework were associated with any meal skipping behaviours. Participants with a university education were less likely to be a meal skipper (any meal) (OR = 0.46; 95%CI: 0.22, 0.95; p = 0.035), while those who previously or currently smoked cigarettes were more likely to be breakfast skippers (OR = 1.10; 95%CI: 1.15, 3.86; p = 0.016) compared to those who had never smoked before. Those who are time scarce were more likely to be either breakfast (OR = 1.12; 95%CI: 1.00, 1.26; p = 0.036) or lunch skippers (OR = 1.11; 95% CI: 1.01, 1.23; p = 0.033). No variables were significantly associated with dinner skipping. CONCLUSIONS: The findings suggest that the correlates of meal skipping vary according to the specific meal skipped. University education status needs to be considered when designing interventions aimed at the reduction of meal skipping among young adults, while correlates such as time management and smoking status may offer potential behaviour change targets within these interventions.