Associations of chronotype and socio-demographic factors with timing of eating in finnish preschool-aged children

The present study explored the associations between chronotype tendency, SES, parents’ work hours, age, and sex as potential determinants of various chrononutrition factors in Finnish preschool children aged 3–6 years. Among the examined determinants, chronotype tendency was found to have the most substantial associations with key outcomes including the timing of first and last EOs, the duration of the fasting window, morning and evening latency, the number of EOs, and the eating and energy midpoints. In comparison, SES, parents’ work hours, age, and sex showed both weaker and fewer associations with the same outcomes. Weekday results largely aligned with the 3-day mean findings, with a few notable differences. No association was observed between children with intermediate and evening chronotype tendencies in terms of the energy midpoint timing during weekdays. Additionally, maternal work hours were associated with chrononutrition variables only during weekdays, while fathers’ work hours were associated only during weekend days. On weekends, differences in the number of EOs and duration of morning latency were significant between boys and girls.

Chronotype

Chronotype tendency showed an association with several chrononutrition variables. Individuals with an earlier chronotype had earlier timings for their first and last EOs, as well as earlier eating and energy midpoints. This finding aligns with previous results from a cross-sectional study conducted on school-aged children in China [23]. Contrary to an earlier study conducted on 496 children aged 7–11 years in Hong Kong, which indicated that children with evening chronotype tendency are more likely to skip breakfast, leading to longer morning latency [24], our study found that during weekdays, children with morning chronotype tendencies exhibited the longest morning latency while children with evening chronotype tendencies had the shortest morning latency. One explanation could be that the children in our study were younger than in the previous research and therefore had less autonomy regarding timing. No association was found between chronotype tendency and the duration of morning latency on weekend days in the current study. This suggests that the shorter morning latency on weekdays observed among children with later chronotype tendencies may be attributed to a structured preschool schedule, which leaves them with less time between waking up and having their first EO compared to children with earlier chronotype tendencies. In accordance with results in the previous studies conducted in Asian children aged 7–12 years [23, 24], children with morning chronotype tendencies in our study had the earliest first EO, while children with evening chronotype tendencies had the latest first EO. In agreement with the earlier findings in older children [23, 24], children with evening chronotype tendencies in this study had their last EO an hour later in the day than children with morning chronotype tendencies. Although later eating times are generally assumed to shorten the fasting window [45], this was not evident in our sample, as no significant difference in the duration of the fasting window was observed between the groups on neither weekdays nor weekends. This discrepancy may be explained by the fact that children with an evening chronotype tendency experienced longer evening latency compared to their morning counterparts, averaging a difference of 31 min on weekdays and 1 h and 27 min on weekends.

Children identified as having a morning chronotype tendency tend to consume a greater proportion of their daily energy intake earlier in the day [30]. This aligns with our results, which showed that children with morning chronotype tendencies achieved both their energy and eating midpoints earlier than their evening counterparts. The differences in eating timing between chronotypes are often more pronounced on weekends, when individuals are not bound by structured schedules, such as preschool commitments, allowing families to follow their natural preferences [21]. A previous review concluded that adults with a morning chronotype typically exhibit a more consistent eating schedule, while evening chronotypes tend to shift their eating habits later on weekends compared to weekdays [2]. Similarly, the current study observed a notable shift in eating behaviour on weekends, with pronounced differences between chronotype tendencies regarding first and last EOs, energy midpoint, and evening latency. Additionally, it was found that children with evening chronotype tendencies had fewer EOs during the weekend compared to children with intermediate or morning chronotype tendencies, although this pattern did not hold during the week. This phenomenon may be attributed to children with evening chronotype tendencies waking up later on weekends [2], which may lead to later energy intake. Consequently, these individuals may not feel hungry in the morning, making them more likely to skip breakfast and lunch, thereby resulting in fewer EOs overall [8, 46]. Nonetheless, it is important to consider the role of parents, as young children may lack the autonomy to decide whether to skip EOs.

SES and parents’ work hours

Children from high SES backgrounds exhibited later energy midpoints on both weekdays and weekends, while other chrononutrition variables showed no notable differences between the SES groups. Higher SES families may have more structured daily schedules with later dinner times, aligning with parental work hours and children’s extracurricular activities. An Australian online study on children aged 6 months to 6 years, found that eating dinner later was not associated with high SES, but the parents rated the importance of family meals higher and also had a higher frequency of family meals [47]. Hence, the family mealtime environments and behaviours may impact the children’s energy intake at mealtimes. Children from lower SES backgrounds tend to rely more on meals provided at preschool, with ECEC meals appearing to help balance differences in dietary quality between children of different socioeconomic groups (DAGIS, unpublished result). Most research concerning children has primarily concentrated on SES’s association with nutritional intake [1, 38, 48], rather than on the timing of food consumption. Nonetheless, children with lower SES have been linked to higher likelihood of skipping meals, particularly breakfast, when compared to their higher SES counterparts [49, 50]. This was not observed in the current study. A possible explanation would be that, in addition to lunch and snacks, breakfast is provided free of charge at ECEC centers in Finland.

Parents’ work hours were modestly associated with the chrononutrition variables in this study. Mothers’ work hours were more influential during the week, while fathers’ hours had a stronger association with the chrononutrition patterns on the weekend. Several studies have shown that fathers spend more time with their children during weekends compared to weekdays [51, 52], and therefore, might have a bigger impact on the timing of food intake on free days. A population-based cohort in Taiwan found that preschool-aged children whose parents worked nonstandard hours were less likely to eat breakfast regularly [22], which is in accordance with our findings, where children with mothers working shifts were associated with later first EOs and a longer fasting window on weekdays compared to children with mothers working regular hours. Parents’ shift work tends to disrupt schedules more during weekdays because of the set routines e.g., preschool, while families have more flexibility during the weekend [53]. During the weekend days, children with nonworking fathers had later last EOs compared to those with working fathers, possibly due to more flexible routines.

Age and sex

Results from the present study indicated that age and sex were only associated with differences in the chrononutrition variables observed on weekend days. Children in the younger age group had a shorter fasting window, on average 12h12min compared to children in the older age group whose fasting window on average lasted 12h36min. An explanation for the longer fasting window duration in the older children is a potentially longer sleep duration on weekend nights compared to the younger age group children. By age 5, 94% of children no longer take naps [54]; thus, more participants in the younger age group may still be napping daily, leading to fewer hours of night time sleep and affecting the duration of the nightly fasting window [55].

This study found no differences between the sexes during weekdays, but on weekend days, boys had a longer morning latency and fewer EOs compared to girls. No previous research on preschool-aged children comparing the sexes regarding chrononutrition factors was found. However, a Polish study on preschool-aged children found that parents were more concerned with managing their daughters’ overall eating habits than their sons’ [56], perhaps explaining their shorter morning latency in the current study. An observational study in the U.S conducted on kindergarteners showed that girls tend to seek parental approval more often and are praised more frequently than boys by their mothers when eating [57]. Boys might prefer to engage in other activities after waking up, such as playing or using electronic devices, which might delay their first EO and lead to fewer EOs overall. More research is needed to draw conclusions about differences between the sexes regarding morning latency and the frequency of EOs, as skipping breakfast and a lower number of EOs are associated with overweight [12, 58], and studies show that overweight is more prevalent in boys compared to girls [59, 60].

Strengths and limitations

It is important to recognize certain limitations inherent in this study. First, the families participating in this study had higher levels of education compared to national averages [61], potentially impacting the generalizability to our findings. All participants attended preschool, so the results might differ for children cared for at home. However, since the majority (78.6%) of Finnish children aged 3–5 attend preschool [62], the generalizability of the findings remains largely intact. Second, the cut-off scores for chronotype tendencies in this study are specific to our sample, as participants were grouped based on the lowest and highest 10th percentiles, a method previously used in the DAGIS study [63]. While this approach assumes a normal distribution of chronotypes similar to the broader population, the cut-off scores might not align with those of the entire population of children the same age. Furthermore, with conservative prevalence estimates set at 10%, there is a possibility that some children with morning or evening chronotype tendencies were categorized into the intermediate chronotype group. However, through this approach, we most likely captured true positives in the morning and evening chronotype tendency groups, and in addition, the analyses were also conducted with chronotype as a continuous variable. While weekend night sleep data were utilized to determine chronotype, we cannot guarantee that children were not awakened on weekend mornings for example due to scheduled activities such as hobbies. Additionally, we did not collect data on parental chronotypes, which may influence the children’s schedules for timing of sleep and food intake. Third, the study’s cross-sectional nature means that causality cannot be concluded from the findings, as it only captures data at a single point in time.

To our knowledge no previous research has examined the determinants of chrononutrition factors in preschool aged children. The strengths of the current study include its relatively large sample situated in both rural and urban areas of Finland. Participants’ parents and preschool personnel recorded food and beverage intake in real time, while actigraphy was used to measure sleep, reducing recall bias. Food records were collected on the same dates as three of the 7 days of actigraphy data, encompassing both weekdays and weekends. This simultaneous data collection provided a more accurate representation of chrononutrition variables. Including both weekdays and weekends allowed for a comprehensive view of how the determinants of chrononutrition patterns varied between weekdays and weekends.

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