Association of diet, lifestyle, and chronotype with metabolic health in Ukrainian adults: a cross-sectional study

Human activity has always been intrinsically connected to the natural rhythms of sleep-wakefulness, which are regulated by the sunlight and day length. However, the rise of technology, globalization and the demands of modern life have led to an increasing number of people working late into the night, far out of sync with their natural physiological rhythms. This may lead to chronic misalignment between internal circadian rhythms and local time, which is further exacerbated by artificial lighting that enables activity at any time of the day. The adverse metabolic consequences of this mismatch have been well-studied in shift workers^1,2. Chronotypes, which reflect inter-individual differences in synchronization with the light–dark cycle, categorize individuals as either "larks" or "owls." Morning types, or larks, generally tend to go to bed earlier than evening types on both workdays and during their free days^3,4. Distinct chronotypes exhibit metabolic profiles that differ in regard to blood glucose, glycated hemoglobin, triglycerides, and low-density lipoprotein cholesterol (LDL-C) concentrations. Notably, individuals with an evening chronotype have an increased risk for cardiometabolic diseases, as highlighted in a recent review⁵. Lifestyle factors such as dietary patterns, meal schedules, physical activity, and sleep timing—rather than genetic predisposition—influence the energy metabolism in evening chronotypes⁶. In fact, evening-type individuals tend to be less physically active and engage in poor eating behaviors, such as emotional and stress-related eating^6,7. Evening chronotypes are prone to unhealthy eating patterns (i.e., delaying meal timing, skipping breakfast, irregular food intake) and lower overall diet quality, as evidenced by more frequent consumption of fast food, energy drinks, and alcohol^8,9. This observation is corroborated by their low adherence to healthy dietary patterns¹⁰.

Despite numerous studies investigating the nutritional aspects of different chronotypes^8,9, there is a scarcity of research focusing on the consumption of major food groups and detailed nutrient intake. Furthermore, the findings from these studies have yielded conflicting results, particularly regarding specific food groups. Variations in the consumption of grains, fruit, and fish between evening and morning chronotypes have been reported inconsistently across different studies⁸. Regarding macronutrients, most studies did not find significant differences in total energy and fat intake between chronotypes, although protein intake was either similar to or lower in evening chronotypes. Total carbohydrate intake was similar in chronotypes in half of the previous conducted studies, while others reported both lower or higher carbohydrate intake in the evening compared to morning chronotypes⁸. These discrepancies can be attributed to variations in methodological approaches, as most studies relied on food frequency questionnaires (FFQs) and other questionnaires to collect data on food groups and nutrient intake. Only a limited number of studies utilized more accurate methods, such as weighed food records.

Therefore, the objective of the cross-sectional study was to investigate the association between chronotypes, dietary intake (i.e., macronutrient and food groups), and blood parameters of glucose and lipid metabolism in individuals with a wide range of metabolic phenotypes.

A total of 110 subjects were included in the final analytical sample (Supplementary Fig.), of whom 44.5% were defined as morning type, 47.3% belonged to neither evening nor morning (intermediate) type, and 8.2% were defined as evening type. For further analysis considering the small number of subjects belonging to the evening type the sample was dichotomized around the median Morningness-Eveningness Questionnaire (MEQ) score into morning chronotype (≥ 58 points) and evening chronotype (< 58) groups. Subjects in the morning group were predominantly (87.5%) morning chronotype with a mean MEQ score of 63.5 ± 3.9, and subjects in the evening group were predominantly (88.3%) intermediate type with a mean MEQ score of 48.7 ± 7.0 (p < 0.001 for mean MEQ score). Thus, the between-group comparison reflects the difference between morning and intermediate types rather than between morning and evening types of original MEQ. S1

Sleep onset time was significantly lower in morning chronotypes both on work days and free days (p < 0.001), which was consistent with an earlier time of MSFsc, a sleep debt corrected mid-sleep point (p < 0.001, Table 1). Sleep duration in morning-type subjects was slightly longer on working days (p = 0.045). There was no difference on days off. Social jetlag (SJL) was lower in morning chronotypes compared to evening chronotypes (p = 0.036). Sleep quality, as measured by the Pittsburgh Sleep Quality Index (PSQI) total score, and the number of subjects with poor overall sleep quality (PSQI score greater than 5) was the same in both chronotype groups. Both groups had similar levels of physical activity according to total Metabolic Equivalent of Tasks (MET) minutes per week assessed by International Physical Activity Questionnaire (IPAQ). However, the number of hours spent sitting was lower in the morning types (p = 0.016).

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 subjects^11–13. 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 studies^6,12. 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 diet^17,18 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 others^20,21. Consistent with previous findings, regression models in the present study found a relationship between higher MEQ scores and lower BMI^6,18,22, 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 MetS^6,11,20.

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 food^23,24. For example, diet-induced thermogenesis and insulin sensitivity vary throughout the day with their impairment in the evening^25,26, 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 chronotypes^{6,13,16,28,29}. 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 risk^18,20. Morning types tend to be more physically active^6,7,18,20,32, while evening types show a higher proportion of smokers^20,32. 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 insufficiency^3,20,33, but in other studies the effect of chronotype on sleep quality is inconsistent^7,34. Moreover, studies have shown that sleep duration and sufficiency do not modify the association between chronotype and metabolic disorders^32,34,35. 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 findings^3,33. Greater SJL has been previously associated with unhealthy lifestyles and poorer metabolic profiles^36–38. Higher SJL was also linked to less adherence to the Mediterranean diet, increased likelihood of skipping breakfast and higher energy intake^36,38. 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.