Circadian rhythms, metabolic processes and dietary intake are inextricably linked. Timing of food intake is a modifiable temporal cue for the circadian system and may be influenced by numerous factors, including individual chronotype – an indicator of an individual’s circadian rhythm in relation to the light–dark cycle. This scoping review examines temporal patterns of eating across chronotypes and assesses tools that have been used to collect data on temporal patterns of eating and chronotype. A systematic search identified thirty-six studies in which aspects of temporal patterns of eating, including meal timings; meal skipping; energy distribution across the day; meal frequency; time interval between meals, or meals and wake/sleep times; midpoint of food/energy intake; meal regularity; and duration of eating window, were presented in relation to chronotype. Findings indicate that, compared with morning chronotypes, evening chronotypes tend to skip meals more frequently, have later mealtimes, and distribute greater energy intake towards later times of the day. More studies should explore the difference in meal regularity and duration of eating window amongst chronotypes. Currently, tools used in collecting data on chronotype and temporal patterns of eating are varied, limiting the direct comparison of findings between studies. Development of a standardised assessment tool will allow future studies to confidently compare findings to inform the development and assessment of guidelines that provide recommendations on temporal patterns of eating for optimal health.

Unusual meal timing has been associated with a higher prevalence of chronic disease. Those at greater risk include shift workers and evening chronotypes. This study aimed to validate the content of a Chrononutrition Questionnaire for shift and non-shift workers to identify temporal patterns of eating in relation to chronotype. Content validity was determined using a Delphi study of three rounds. Experts rated the relevance of, and provided feedback on, 46 items across seven outcomes: meal regularity, times of first eating occasion, last eating occasion, largest meal, main meals/snacks, wake, and sleep, which were edited in response. Items with greater than 70% consensus of relevance were accepted. Rounds one, two, and three had 28, 26, and 24 experts, respectively. Across three rounds, no outcomes were irrelevant, but seven were merged into three for ease of usage, and two sections were added for experts to rate and comment on. In the final round, all but one of 29 items achieved greater than 70% consensus of relevance with no further changes. The Chrononutrition Questionnaire was deemed relevant to experts in circadian biology and chrononutrition, and could represent a convenient tool to assess temporal patterns of eating in relation to chronotype in future studies.

Many studies assert a negative influence of inappropriate maternal diet and nutritional status during pregnancy on offspring, not only in utero but throughout life, because of the role in the programing of noncommunicable diseases. Telomere length is a biomarker of aging, and shorter telomeres are associated with chronic disease later in life. Maternal nutrition and nutritional status may be an important determinant of offspring telomere length. A systematic review was conducted to determine the effect of maternal nutrition and nutritional status in pregnancy on offspring telomere length. This systematic review was conducted according to PRISMA guidelines. Database searches of PubMed, CINAHL, Scopus, Medline, and Web of Science were performed. Included studies assessed the association between maternal nutrition (dietary intake and nutritional status) during pregnancy and offspring telomere length measured in cord blood, serum, plasma, and peripheral blood mononuclear cells. Three authors screened and determined the quality of the articles; disagreements were resolved by a fourth author. All authors compared the compiled data. Seven studies were extracted and evaluated. Studies comprised a double-blind placebo-controlled trial (n = 1), prospective cohort studies (n = 5), and a cross-sectional study (n = 1). Higher circulating maternal folate and 25-hydroxyvitamin D₃ concentrations, along with higher maternal dietary caffeine intakes, were associated with longer offspring telomere length, whereas higher dietary intake of carbohydrate, folate, n-3 polyunsaturated fatty acids, vitamin C, or sodium was not. The limited but suggestive evidence highlights the need for further research to be conducted in this area, particularly longitudinal studies involving larger cohorts of pregnant women. PROSPERO registration no. CRD42019136506

Background/Objectives: Shift work and chronotype influence timing and type of food consumed, yet their combined influence is unclear. This study determined differences between temporal patterns of eating (times of first (FEO), last (LEO), and largest eating occasions (LarEO), duration of eating window (DEW), eating frequency) and nutrient intake of night shift workers on and off shift and the additional influence of chronotype. Methods: Participants (46.6 ± 10.2 years, BMI: 33.9 ± 5.6 kg/m², male/female: 57/72) completed work/sleep/food diaries, and the Composite Scale of Morningness. Dietary profiles were characterized by day type as follows: morning shift (MS), 1st night shift (1stNS), subsequent night shifts (SNS), 1st day off after night shifts (1stDONS), or other days off (DO). Results: Across day types, there were significant differences in FEO (p < 0.001), LEO (p < 0.001), LarEO (p = 0.025), DEW (p < 0.001), eating frequency (p = 0.003), total energy (p = 0.022), and fibre intake (p < 0.001). Compared to MS, all night shifts had later FEO, LEO, and LarEO; 1stNS had longer DEW and higher fibre but no differences in frequency, energy, and macronutrient intake. Greater morningness was associated with earlier FEO, LEO, LarEO, and lower %energy from fat and saturated fat. Effect of chronotype on temporal eating patterns was not different across day types; there was a significant, positive relationship between morningness and %energy from carbohydrate (%Energy_CHO) on MS (p = 0.004) and 1stDONS (p = 0.040). Conclusions: Dietary habits of night shift workers vary by shift schedule and degree of morningness. Further studies will confirm if shift schedule is more influential than chronotype on shift workers’ dietary habits.

Purpose: This study aimed to explore dietary profiles of a night shift working population with overweight/obesity and the impact of different shift work schedules (rotating vs. fixed night) on their diet. Methods: Participants from a randomised controlled trial (SWIFt trial) provided 7-day food diaries at study enrolment. Mean energy intakes (EI), and mean percentage of EI as nutrients (macronutrients, saturated fat, added sugar, alcohol) grams of fibre and milligrams of sodium, were assessed against recommendations for Australian adults. Energy intake was assessed for underreporting. Regression analyses were performed on nutrient intakes whilst controlling for individual and lifestyle factors (age, gender, BMI, physical activity, shift work exposure, occupation and shift schedule). Results: The diet of night shift workers ( N = 245, aged 46.8 ± 9.8 (mean ± SD) years and 53% female) was characterised as high in fat, saturated fat and sodium, while low in carbohydrate and fibre compared with recommendations, regardless of shift work schedule. However, the mean 24 h EI of rotating shift workers was higher than fixed night workers (9329 ± 2915 kJ/day vs. 8025 ± 2383 kJ/day, p < 0.001), even after assessing plausible EI reporters only ( n = 130) (10968 ± 2411 kJ/day vs. 9307 ± 2070 kJ/day, p < 0.001). Furthermore, those performing rotating schedules presented with higher sodium and alcohol consumption. Conclusion: These findings support the evidence of shift work being associated with poorer dietary profiles, which likely contribute towards worsened metabolic health amongst night shift workers. Dietary strategies that target problematic eating habits and address unique challenges of working shift schedules are needed to mitigate metabolic health risk in shift working populations.