In this Ukrainian cohort, subjects belonging to the morning chronotype exhibited distinct dietary patterns characterized by a more balanced diet and an earlier timing of the last eating occasion. Specifically, morning chronotypes reported lower fat intake, higher carbohydrate consumption, and a reduced intake of animal protein-rich foods. Despite being older in age, morning individuals spent less time in sedentary activities and demonstrated a greater alignment with their biological clock, as reflected by smaller SJL. Moreover, being a morning chronotype was associated with improved metabolic parameters and predicted better overall metabolic health. Importantly, these effects remained significant even after accounting for confounding factors such as sex, age, physical activity, and BMI.
Consistent with previous findings, morning subjects in this study consumed less fat and more carbohydrate compared to evening subjects11,12,13. Interestingly, we observed a lower consumption of animal protein in morning chronotypes, which has not been investigated in previous studies. Linear regression between the continuous MEQ score and nutrient intake models adjusted for confounders confirm the observed group differences; lower consumption of fat, animal protein were consistently associated with higher MEQ scores, i.e., morning chronotypes. The results of the present study partially align with Mota et al., who reported a decrease in total protein intake in medical residents with higher MEQ scores14. The lower intakes of fat and animal protein in morning subjects may be attributed to a lower overall intake of animal foods, which is supported by a decreased consumption of processed meat, eggs, and cheese in morning vs. evening chronotypes. A lower intake of meat was also found in morning-type young Japanese women as compared to those of evening-type, although the percentage of energy from protein showed an opposite trend13. Regarding fish intake, we did not observe any differences between chronotypes, which is consistent with the findings by Sato-Mito et al.13 and is contrary to studies by Kanerva et al.12. This discrepancy could be due to the low consumption of fish and seafood the present study population as compared to national consumption rates15. In addition, higher carbohydrate, fiber and bread intake were observed in morning chronotypes, yet these differences were maintained only for carbohydrate in linear regression models after adjustment for confounders. As shown in previous studies, MEQ scores were positively associated with dietary fiber intake in Finnish12 and Mexican11 populations, whereas no association was found in the Spanish population11. Furthermore, in a subgroup of the same Finnish population, a more detailed analysis showed a positive association with fiber intake only for morning meals, but not for the whole day16. Regarding cereal intake, previous results have been somewhat contradictory8. For example, higher intakes of cereals and whole grains were positively associated with MEQ scores in several studies6,12. However, another study found no association with cereals, bread, and pasta14. Previous studies analyzing healthy diet indices showed that morning chronotypes are more adherent to plant-based dietary patten such as Mediterranean diet17,18 and have higher healthy plant-based diet index scores that partially corresponds to our results19. The observed discrepancies between nutrient and food group intake may be related to geographic (particularly latitude) and therefore climatic and cultural influences on dietary patterns, limiting the comparability of existing data. On the other hand, these discrepancies highlight the importance of assessing overall dietary quality. Combining food diaries with healthy diet indices would provide a more comprehensive assessment of the association between chronotype and diet, as food records offer valuable quantitative data, while adherence to a healthy dietary pattern may have stronger predictive potential than the consumption of individual foods18.
We did not observe differences in metabolic profiles in the between-group comparison of the two chronotypes. However, these differences became apparent upon further multivariate regression analysis adjusted for age, sex, and physical activity, as was observed by others20,21. Consistent with previous findings, regression models in the present study found a relationship between higher MEQ scores and lower BMI6,18,22, triglycerides11, and blood glucose22. No association was found between chronotype and hypertension. Partially in line with our results, a recent systematic review found that evening chronotypes exhibited higher concentrations of blood glucose, glycated hemoglobin, triglycerides, and LDL-C, while no significant differences were observed for anthropometric measurements, arterial blood pressure, insulin, the homeostatic model assessment of insulin resistance (HOMA-IR), total cholesterol, and HDL-C5. In contrast to others, we observed lower WC and higher HDL-C associated with morning type and no difference in LDL-C. The reported association between a more morning chronotype and lower odds of being metabolically unhealthy in the present study confirms recent findings of the positive association between the evening chronotype and MetS6,11,20.
The underlying mechanisms for the metabolic effect of diurnal dietary differences in distinct chronotypes are based on the circadian physiology of metabolism and the zeitgeber effect of food23,24. For example, diet-induced thermogenesis and insulin sensitivity vary throughout the day with their impairment in the evening25,26, late dinner time causes lower lipolysis and dietary fatty acid oxidation in the postprandial period27 meaning a greater metabolic load of the late meal. Distinct eating patterns (i.e., meal timing and regularity, meal skipping, as well as diurnal fluctuations of nutrient intake) shown in several studies may also contribute to differences in cardiometabolic health between chronotypes6,13,16,28,29. In the current study, the first and last eating occasions were analyzed, with the last food intake being significantly earlier in the morning subjects. Furthermore, it could be suggested that a late meal schedule may misalign metabolic functions controlled by tissue clocks with a central pacemaker controlled by the environmental light–dark cycle. This misalignment has been recognized as a cause of the higher incidence of metabolic disease in shift workers30 and has been confirmed in studies using simulated night shift work31, however, it still needs to be investigated in evening chronotypes. Thus, we suggest that metabolic disorders are less common for subjects with the morning chronotype due to a healthier diet and an earlier last eating occasion.
Modifiable lifestyle factors, such as physical activity and smoking, differ between chronotypes and may influence metabolic risk18,20. Morning types tend to be more physically active6,7,18,20,32, while evening types show a higher proportion of smokers20,32. In our cohort, morning chronotypes spent less time sitting, however, the proportion of current smokers was the same. Sleep parameters and circadian misalignment also contribute to adverse health outcomes in evening chronotypes. Evening chronotypes often experience poor sleep quality and sleep insufficiency3,20,33, but in other studies the effect of chronotype on sleep quality is inconsistent7,34. Moreover, studies have shown that sleep duration and sufficiency do not modify the association between chronotype and metabolic disorders32,34,35. In our study, sleep duration differed only on workdays, with shorter duration for evening types, while sleep quality was unaffected.
Circadian misalignment caused by work schedules is quantified using SJL, which reflects the discrepancy between biological and social clocks. Morning types in the present study had lower SJL, consistent with earlier findings3,33. Greater SJL has been previously associated with unhealthy lifestyles and poorer metabolic profiles36,37,38. Higher SJL was also linked to less adherence to the Mediterranean diet, increased likelihood of skipping breakfast and higher energy intake36,38. However, the relationship between SJL, diet, and obesity is unclear among different chronotype groups39. Therefore, the impact of SJL on health outcomes in evening types remains uncertain. Other measures of circadian discrepancy may be necessary to assess the circadian misalignment in these individuals.
This study has several limitations. Firstly, the cross-sectional design restricts our ability to establish causal relationships. Additionally, the assessment of individual chronotypes relied on a subjective questionnaire rather than objective measures such as dim light melatonin onset (DLMO). Nevertheless, previous research has demonstrated a significant correlation between the validated MEQ used in this study and DLMO40. It should be noted that the median MEQ score (58 points) used to categorize our sample falls on the borderline between morning and intermediate chronotypes. Thus, our findings primarily compare morning and intermediate MEQ types, challenging the assumption that the intermediate type is metabolically neutral, as suggested in previous studies that mainly focused on extreme chronotypes. Another limitation pertains to the self-reported nature of sleep-related variables, introducing the potential for participant bias. Additionally, the study is constrained by a small sample size. Future studies incorporating actigraphy or polysomnography can help overcome these limitations. Recognizing the multifaceted nature of estimating food consumption, we concur that various errors may arise not only from methodological considerations but also from factors such as differences in the actual nutrient content of foods and variations in individual responses to nutrients. In light of these complexities, our results regarding dietary intake associations should be interpreted with caution. Moreover, the present study and did not explore diurnal changes in dietary composition, warranting further investigation.
Despite these limitations, the present study has notable strengths. The inclusion of both middle-aged and elderly subjects with a wide range of metabolic phenotypes enhances the generalizability of our findings. The use of weighed 7-day food diaries for dietary intake analysis provides a more accurate assessment compared to methods such as the FFQ or 24-h recalls. Furthermore, energy-adjusted nutrient intake was employed for between-group comparisons and regression analysis, reducing external variation caused by individual metabolic rates.
In conclusion, the present data provide evidence for a different dietary pattern in morning chronotypes. The dietary composition observed in morning-type individuals, characterized by lower fat and animal protein intake and an earlier last eating occasion, may contribute to the associations between a higher chronotype score and a more favorable metabolic profile. Importantly, the association of morning chronotype with lower BMI, waist circumference, fasting triglycerides and glucose, and better overall metabolic health was independent of age and lifestyle differences. However, the underlying mechanisms of such effects remain to be elucidated. Longitudinal studies should investigate whether dietary and eating patterns mediate the metabolic effects of a specific chronotype. Additionally, interventional studies with different eating patterns considering meal timing and nutrient distribution are needed to clarify the mechanisms and causality of these associations.