Undergraduate students experience a form of circadian misalignment - known as "social jetlag" - that represents the discrepancy in timing between their circadian and social clocks. Whilst social jetlag is not dependent upon chronotype, the two phenomena tend to be related; evening types show a tendency to have a greater social jetlag, for example. Moreover, evening types have been found to be more likely to have inadequate eating habits than do morning types. The objective of this study was to examine the relationship between chronotype, social jetlag, perceived sleep debt and dietary intake in Brazilian undergraduate students. The chronotype was derived from mid-sleep time on free days (MSF) at the weekend. Social jetlag was calculated as the absolute difference between mid-sleep time on weekdays and weekends. Perceived sleep debt was calculated using the difference between students' preferred weekday sleep duration and their self-reported actual weekday sleep duration. Correlations were found between chronotype and breakfast time (r = 0.24, p = 0.003) and lunch time (r = 0.19, p = 0.01). Multiple regression analyses showed that chronotype was positively associated with consumption of meat (β = 0.21; p = 0.003); social jetlag was negatively associated with consumption of beans (β = -0.16; p = 0.02) and perceived sleep debt was positively associated with consumption of beverages (β = 0.15; p = 0.02) and dairy products (β = 0.17; p = 0.01) and negatively associated with consumption of cereals and pasta (β = -0.16; p = 0.02). It is concluded that, in undergraduate students, chronotype (MSF), social jetlag and perceived sleep debt can influence the type and amount of some food groups consumed at mealtimes.

The aim of this study was to compare anthropometry and food intake patterns in bus drivers working during the day and night. One hundred and fifty males (81 night workers and 69 day workers) participated in the study. Dietary intake was assessed using a validated semi-quantitative food frequency questionnaire. Measurements of height, weight, waist circumference (WC), systolic and diastolic blood pressure, blood glucose, and lipid profile were obtained. A significant difference between groups was observed for mean WC (98.5 ± 10.7 cm in day workers versus 103.2 ± 9.7 cm in night workers; p = 0.005). Night workers had higher prevalence of being overweight and obese (BMI ≥ 25 kg/m(2)) than day workers (78.2% day workers versus 90.2% night workers; p = 0.004) and increased WC (>94 cm) (72.4% day workers versus 86.4% night workers; p = 0.03). Significant differences were found for meat consumption (2.3 servings ±0.9 for night workers versus 2.0 servings ±0.7 day workers, p = 0.04) and fruit intake (0.9 servings ±0.4 for night workers versus 0.7 servings for day workers ±0.5; p = 0.006). Night workers had a lower intake of vegetables than recommended compared to day workers (100 versus 92.7%, respectively, p = 0.01) and higher intake of oil (40.7 versus 24.6%, p = 0.03). Multivariate logistic regression analysis indicated that night work was associated with being overweight (OR = 2.94, 95% IC: 1.14-7.66, p = 0.03) and abnormal values of WC (OR = 2.82, 95% IC: 1.20-6.69, p = 0.009) after adjusting for potential confounders. It is concluded that night workers had a higher prevalence and risk of being overweight/obese and increased WC compared with day workers. Night workers also presented a higher proportion of inappropriate intakes of food groups when compared to day workers, even though both groups were eating poor diets. These results demonstrate the need of lifestyle-intervention programs in these workers.

The literature widely recognizes that shift workers have more health complaints than the general population. The objective of this study was to describe the prevalence of sleep complaints and verify the polysomnographic (PSG) variables of shift workers in two Brazilian nuclear power plants. We carried out a subjective evaluation with a sleep questionnaire. Based on these results, the interviewees that reported sleep-related complaints were referred for polysomnographic evaluation. Of the 327 volunteers initially evaluated by the sleep questionnaire, 113 (35%) reported sleep complaints; they were significantly older, had higher body mass index (BMI), and worked more years on shifts than those without sleep complaints. Of these 113, 90 met criteria for various sleep disorders: 30 (9%) showed obstructive sleep apnea (OSA), 18 (5.5%) showed limb movement, and 42 (13%) evidenced both sleep problems and had a significantly higher proportion of sleep stage 1 and arousals compared with the 23 shift workers that had no indices of sleep problems. The present study found that 90 (27.5%) of the evaluated participants met the PSG criteria of some type of clinical sleep disorder. This high proportion should be investigated for associations with other aspects of work, such as working hours, working schedule, years performing shift work, and access to health services. Due to the strong association between sleep disorders and the incidence of fatigue and sleepiness, the evaluation of the sleep patterns and complaints of shift workers is essential and should be considered to be one of the basic strategies of industry to prevent accidents.

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Study Objectives: This study aimed to analyze the association between habitual meal timing and sleep parameters, as well as habitual meal timing and apnea severity in individuals with obstructive sleep apnea (OSA). Methods: Patients in whom mild to severe OSA was diagnosed were included in the study (n = 296). Sleep parameters were analyzed by polysomnography. Dietary pattern was obtained by a food frequency questionnaire and meal timing of the participants. Individuals with OSA were categorized by meal timing (early, late, and skippers). Results: Dinner timing was associated with sleep latency (β = 0.130, P = .022), apnea-hypopnea index (AHI) (β = 1.284, P = .033) and poor sleep quality (β = 1.140, P = .015). Breakfast timing was associated with wake after sleep onset (WASO) (β = 3.567, P = .003), stage N1 sleep (β = 0.130, P < .001), and stage R sleep (β = −1.189, P = .001). Lunch timing also was associated with stage N1 sleep (β = 0.095, P = .025), sleep latency (β = 0.293, P = .001), and daytime sleepiness (β = 1.267, P = .009). Compared to early eaters, late eaters presented lower duration of stage R sleep and greater values of sleep latency, WASO, stage N1 sleep, and AHI, in addition to increased risk of poor sleep quality and daytime sleepiness (P < .005). Conclusions: Late meal timing was associated with worse sleep pattern and quality and apnea severity than early meal timing. Despite some of these results having limited clinical significance, they can lead to a better understanding about how meal timing affects OSA and sleep parameters.