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Bar graphs of zCSM and zMSFsc ( z -scores) by photoperiod at birth. n = 2905. zCSM: high values indicate morningness, low values indicate eveningness; zMSFsc: high values indicate late midpoint of sleep (eveningness), low values indicate early midpoint of sleep (morningness). The significant differences ( t test) are indicated by asterisk (CSM: p = .024; MSFsc: p = .004).
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Individuals differ in their circadian preferences (chronotype). There is evidence in the literature to support a season-of-birth effect on chronotype but the evidence is not convincing. In part, the relationship is obscured by a number of methodological differences between studies, including the measures used to define morningness, the way in which...
Contexts in source publication
Context 1
... amount of daylight for each of these categories can be found in Figure 1. The estimates of daylight length for Heidelberg, Germany, were obtained from the National Oceanic and Atmospheric Administration Solar Calculator (USA). The increasing and decreasing groups appear to show the same amount of daylight (albeit in a reversed order), whereas the long and short photoperiod groups show a marked difference in daylight hours. We assume that the photoperiod-at-birth effect on chronotype reflects a quadratic function of chronotype mean values across a 1-yr cycle and in a cosine function over a span of several years. Figure 1 depicts a theoretical justification for the underlying quadratic function. We used SPSS 20 (IBM, Somers, NY, USA) for data analyses. Statistical tests were two-tailed with the type 1 error set at 5%. Correlations were assessed using the Pearson ’ s correlation coefficient ( r ). To check for bias in the data, we first conducted three univariate analyses of variance (ANOVAs) to assess the role of PAB on age, CSM scores, and MSFsc clock times. A multivariate analysis of covari- ance (MANCOVA) was used to test our hypothesis concerning the quadratic function of PAB on chronotype (CSM, MSFsc). We controlled for year of birth and gender. Next, in order to fit a multicycle cosine regression to the data, we standardized the CSM and MSFsc values for each year of birth (zCSM, zMSFsc), using the save standardized values option in the descriptives command with spilt file for year of birth activated. The respondents were evenly spread over the 73 birth months from July 1993 to July 1999. Females (n = 1422) and males (n = 1483) were evenly distributed across each photoperiod group and year. The overall mean age was 13.56 yrs (SD, ±1.66) and no gender differences were found. The mean CSM score was 34.17 (SD, ±7.25). The mean MSFsc was 04:19 h (SD, ±1 h 26 min). There were significant correlations between age and CSM ( r = − .306, p < .001) as well as age and MSFsc ( r = .349, p < .001). The ANOVA testing the photoperiod groups and age showed that pupils born in the long photoperiod were significantly younger (13.23 yrs) than those born during the decreasing (13.79 yrs; p < .001), short ( p < .001), and increasing ( p = .021) photoperiods. Although we found no differences between photoperiod groups using the raw CSM and MSFsc values, we obtained consistent significant results when we used the standardized values. Figure 2 (panel A) suggests a quadratic pattern for the zCSM means. The lowest values for chronotype were apparent in the increasing and highest values were apparent in the decreasing photoperiod groups ( t test, p = .024). Similarly, Figure 2 (panel B) also identified a quadratic pattern for the zMSFsc means. Again, the increasing period was associated with eveningness whereas the decreasing period was associated with morningness ( t test, p = .004). Table 1 reports on the results of the MANOVA. There was a nonsignificant main effect (Wilks ’ λ ) found for the PAB ( p = .073) and a significant main effect for year of birth ( p < .001) as well as gender ( p < .001). The interactions were not significant and thus not included in the model. PAB was a significant predictor of MSFsc ( p = .021) but not CSM ( p = .076). In the MANOVA, we also tested for the presence of a quadratic equation using the contrasts polynomial option. A quadratic solution for the PAB was significant for CSM ( p = .024) and MSFsc ( p = .016). Figure 3 (panel A) depicts the estimated marginal means for the CSM by PAB and year of birth. Eveningness orientation is suggested to ascend from youngest to oldest age groups and CSM scores are the lowest for those born February to April. A similar curved pattern was found for the MSFsc (not shown). Panel B estimates the curved pattern on the MSFsc by gender, with latest bedtimes for males born February to April. Both panels of Figure 3 show a quadratic pattern where adolescents born during the increasing photoperiod tend to report stronger eveningness orientation. In order to visually explore the effect of PAB on chronotype, we employed two nonlinear cosine regressions with PAB categories for each year from July 93 to July 99. These patterns can be found in Figure 4. Panel A shows the relationship between PAB and standardized CSM scores and panel B shows PAB and standardized MSFsc clock times, respectively. The results suggested a PAB effect (zCSM: R 2 = .003; zMSFsc: R 2 = .004). The data in panel A (CSM) suggest that the amplitude of the CSM values decreases with increasing age. We have shown that our photoperiod grouping is capable of detecting a season-of-birth effect on chronotype among adolescents. There was a small significant effect when using either CSM or MSFsc as the indicators of chronotype. However, the effect was only detectable when comparing extreme groups ( increasing vs. decreasing photoperiod) or when applying a quadratic or cosine function to the data. Comparing extreme groups, we found that adolescents born in increasing photoperiod (Feb – Apr) were later chronotypes (CSM, MSFsc) than those born in decreasing photoperiod (Aug – Oct). However, we found no differences in adolescent ’ s chronotype between long and short PAB. The hypothesis of a 1-yr cycle quadratic PAB pattern in CSM and MSFsc was confirmed by the MANCOVA. The amount of variance in chronotype explained by PAB was small, as expected from other studies. Judging the cosine zCSM curve from visual inspection, it seems that the zCSM scores ’ fitting to the cosine function was better in the younger pupils. Compared with the zCSM curve, the curve of the zMSFsc seemed to be less stable. The fit of the CSM scores to the cosine function in the younger age groups suggests that the influence of PAB on chronotype is stronger in younger pupils and seems to be washed out by hormonal and environmental changes in adolescence, e.g., puberty (Colrain et al., 2011) and changing social roles (Cofer et al., 1999). We proposed that the link between PAB and chronotype may be obscured by a number of methodological issues. We have addressed most of these limitations but nonetheless conclude that there is only a small effect of the photoperiod on chronotype. One of our criticisms of the literature is that the categorization of the photoperiod was inaccurate. In contrast, our approach better captures the changes in daylight across the year (see Figure 1) and provides us with a better test of the photoperiod hypothesis. Our approach can be further refined provided that the actual day of birth is collected and we urge future studies to do so. A second criticism is the variety of tools employed to measure chronotype and in reply we used two different measures. We found highly consistent results, with both CSM and MSFsc forming a quadratic pattern in line with our hypothesis. The MSFsc yielded better results in the MANCOVA. However, judging from visual inspection, the CSM appeared to mirror the multicycle cosine pattern more accurately. Another criticism of these types of studies is that effects of birth season on circadian typology in the children may be greater in accordance with latitude where children were born and raised, for example, Harada et al. (2011) did not find the link to morningness orientation in adolescents and adults, but in children aged 2 – 12 yrs in lower latitude (33°N). This association may be mediated by underlying ...
Context 2
... amount of daylight for each of these categories can be found in Figure 1. The estimates of daylight length for Heidelberg, Germany, were obtained from the National Oceanic and Atmospheric Administration Solar Calculator (USA). The increasing and decreasing groups appear to show the same amount of daylight (albeit in a reversed order), whereas the long and short photoperiod groups show a marked difference in daylight hours. We assume that the photoperiod-at-birth effect on chronotype reflects a quadratic function of chronotype mean values across a 1-yr cycle and in a cosine function over a span of several years. Figure 1 depicts a theoretical justification for the underlying quadratic function. We used SPSS 20 (IBM, Somers, NY, USA) for data analyses. Statistical tests were two-tailed with the type 1 error set at 5%. Correlations were assessed using the Pearson ’ s correlation coefficient ( r ). To check for bias in the data, we first conducted three univariate analyses of variance (ANOVAs) to assess the role of PAB on age, CSM scores, and MSFsc clock times. A multivariate analysis of covari- ance (MANCOVA) was used to test our hypothesis concerning the quadratic function of PAB on chronotype (CSM, MSFsc). We controlled for year of birth and gender. Next, in order to fit a multicycle cosine regression to the data, we standardized the CSM and MSFsc values for each year of birth (zCSM, zMSFsc), using the save standardized values option in the descriptives command with spilt file for year of birth activated. The respondents were evenly spread over the 73 birth months from July 1993 to July 1999. Females (n = 1422) and males (n = 1483) were evenly distributed across each photoperiod group and year. The overall mean age was 13.56 yrs (SD, ±1.66) and no gender differences were found. The mean CSM score was 34.17 (SD, ±7.25). The mean MSFsc was 04:19 h (SD, ±1 h 26 min). There were significant correlations between age and CSM ( r = − .306, p < .001) as well as age and MSFsc ( r = .349, p < .001). The ANOVA testing the photoperiod groups and age showed that pupils born in the long photoperiod were significantly younger (13.23 yrs) than those born during the decreasing (13.79 yrs; p < .001), short ( p < .001), and increasing ( p = .021) photoperiods. Although we found no differences between photoperiod groups using the raw CSM and MSFsc values, we obtained consistent significant results when we used the standardized values. Figure 2 (panel A) suggests a quadratic pattern for the zCSM means. The lowest values for chronotype were apparent in the increasing and highest values were apparent in the decreasing photoperiod groups ( t test, p = .024). Similarly, Figure 2 (panel B) also identified a quadratic pattern for the zMSFsc means. Again, the increasing period was associated with eveningness whereas the decreasing period was associated with morningness ( t test, p = .004). Table 1 reports on the results of the MANOVA. There was a nonsignificant main effect (Wilks ’ λ ) found for the PAB ( p = .073) and a significant main effect for year of birth ( p < .001) as well as gender ( p < .001). The interactions were not significant and thus not included in the model. PAB was a significant predictor of MSFsc ( p = .021) but not CSM ( p = .076). In the MANOVA, we also tested for the presence of a quadratic equation using the contrasts polynomial option. A quadratic solution for the PAB was significant for CSM ( p = .024) and MSFsc ( p = .016). Figure 3 (panel A) depicts the estimated marginal means for the CSM by PAB and year of birth. Eveningness orientation is suggested to ascend from youngest to oldest age groups and CSM scores are the lowest for those born February to April. A similar curved pattern was found for the MSFsc (not shown). Panel B estimates the curved pattern on the MSFsc by gender, with latest bedtimes for males born February to April. Both panels of Figure 3 show a quadratic pattern where adolescents born during the increasing photoperiod tend to report stronger eveningness orientation. In order to visually explore the effect of PAB on chronotype, we employed two nonlinear cosine regressions with PAB categories for each year from July 93 to July 99. These patterns can be found in Figure 4. Panel A shows the relationship between PAB and standardized CSM scores and panel B shows PAB and standardized MSFsc clock times, respectively. The results suggested a PAB effect (zCSM: R 2 = .003; zMSFsc: R 2 = .004). The data in panel A (CSM) suggest that the amplitude of the CSM values decreases with increasing age. We have shown that our photoperiod grouping is capable of detecting a season-of-birth effect on chronotype among adolescents. There was a small significant effect when using either CSM or MSFsc as the indicators of chronotype. However, the effect was only detectable when comparing extreme groups ( increasing vs. decreasing photoperiod) or when applying a quadratic or cosine function to the data. Comparing extreme groups, we found that adolescents born in increasing photoperiod (Feb – Apr) were later chronotypes (CSM, MSFsc) than those born in decreasing photoperiod (Aug – Oct). However, we found no differences in adolescent ’ s chronotype between long and short PAB. The hypothesis of a 1-yr cycle quadratic PAB pattern in CSM and MSFsc was confirmed by the MANCOVA. The amount of variance in chronotype explained by PAB was small, as expected from other studies. Judging the cosine zCSM curve from visual inspection, it seems that the zCSM scores ’ fitting to the cosine function was better in the younger pupils. Compared with the zCSM curve, the curve of the zMSFsc seemed to be less stable. The fit of the CSM scores to the cosine function in the younger age groups suggests that the influence of PAB on chronotype is stronger in younger pupils and seems to be washed out by hormonal and environmental changes in adolescence, e.g., puberty (Colrain et al., 2011) and changing social roles (Cofer et al., 1999). We proposed that the link between PAB and chronotype may be obscured by a number of methodological issues. We have addressed most of these limitations but nonetheless conclude that there is only a small effect of the photoperiod on chronotype. One of our criticisms of the literature is that the categorization of the photoperiod was inaccurate. In contrast, our approach better captures the changes in daylight across the year (see Figure 1) and provides us with a better test of the photoperiod hypothesis. Our approach can be further refined provided that the actual day of birth is collected and we urge future studies to do so. A second criticism is the variety of tools employed to measure chronotype and in reply we used two different measures. We found highly consistent results, with both CSM and MSFsc forming a quadratic pattern in line with our hypothesis. The MSFsc yielded better results in the MANCOVA. However, judging from visual inspection, the CSM appeared to mirror the multicycle cosine pattern more accurately. Another criticism of these types of studies is that effects of birth season on circadian typology in the children may be greater in accordance with latitude where children were born and raised, for example, Harada et al. (2011) did not find the link to morningness orientation in adolescents and adults, but in children aged 2 – 12 yrs in lower latitude (33°N). This association may be mediated by underlying physiological mechanisms such as latitudinal differences in serotonin synthesis and the greater prevalence of seasonal affective disorder in higher latitudes (Mersch et al., 1999). Concerning our study, this is less of a problem, ...
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Background
Veterinary cardiology, especially electrocardiography, has shown major advancements for all animal species. Consequently, the number of ovine species used as experimental animals has increased to date. Few studies have been published on ovine systematic electrocardiography, particularly with respect to lamb physiology and neonatology. Th...
Citations
... Light exposure is considered to be the main zeitgeber that synchronizes the central clock. In order to assess the impact of the light-dark cycle on the circadian system, several studies have focused on the influence of the photoperiod on chronotype variations 16,17 . Differences in chronotypes by latitudes have been described, showing that the timing of this biomarker is at least, partially, dependent on this environmental factor 18,19 . ...
Chronotype is a reliable biomarker for studying the influence of external zeitgebers on circadian entrainment. Assessment of chronotype variation in participants exposed to extreme photoperiods may be useful to investigate how changes in light–dark cycle modulate the circadian system. This study aimed to examine chronotype and sleep changes during a winter campaign at the Argentine Antarctic station Belgrano II. A sample of 82 men who overwintered in Antarctica completed the Munich Chronotype Questionnaire during March (daylight length: 18.6 h), May (daylight length: 2.8 h), July (daylight length: 0 h), September (daylight length: 14.5 h), November (daylight length: 24 h). The main results showed a decrease in sleep duration and a delay in chronotype and social jetlag during the polar night, highlighting the influence of social cues and the impact of the lack of natural light on circadian rhythms.
... Studies in the literature show that birth is a factor affecting the function of the adult circadian system (15)(16)(17). Some studies report that factors such as sunrise, sunset and day length significantly affect the chronotype of children and adolescents (18,19). Therefore, there is a need for studies investigating how the exposure time of newborns to light affects the chronotype (20). ...
Introduction: Biological changes in human metabolism due to daylight and heat are expressed as circadian rhythm, and its classification according to individuals and their genetic differences is called chronotype. In recent years, there has been an increase in studies examining the relationship between circadian rhythm and birth. Purpose: This study’s first aim was to investigate the relationship between the chronotypes of mothers and time of birth, season, meridians in which they were born, and the gender of their babies. Its second aim was to examine the relationship between the birth times and chronotypes of pregnant women and the time of their deliveries.
Method: The study was conducted among women presented to Alanya Training and Research Hospital Gynecology and Obstetrics Polyclinic between 01.02.2022 and 31.03.2022. The study included 147 women remembering the date and time of delivery. Participants were selected among the mothers who gave a normal birth, did not have labor induction, whose birth started with spontaneous contractions, and had a healthy pregnancy. A questionnaire form including sociodemographic characteristics, obstetric information, and Horne and Östberg's Morningness- Eveningness scale were applied face to face. One-way ANOVA, Chi-Square, and logistic regression analyses were employed to analyze the data.
Results: The chronotypes of the participants revealed that 45 women (30.6%) were morning type, 90 women were intermediate type (61.2%), and 12 women were evening type (8.2%). No difference was found between the chronotype scores of the mothers and the birth hours of their babies (p = .324). There was no difference between mothers' chronotype scores and birth meridians (p = .842). In addition, no significant relationship was found between the mothers' own birth hours and the birth hours of their babies (p= .050).
Conclusion: There was no relationship between birth time, season, gender, birth meridian, and chronotype. The limitation of the study may be related to the recall bias, the effect of confounding factors, and the sample size. However, we think it is an interesting field in terms of providing a different perspective on the differences in performance and mood of people with further studies regarding chronotype.
... Although the distinction of chronotypes is quite easy, most people are I-types rather than at the ends of this continuum (5). The individual differences in chronotypes seem to be influenced by age (6), gender (7), inherited (8), perinatal (9), and environmental factors to some extent (10). ...
Objective
This study aimed to investigate the chronotypes and their relationship with sleep disturbances and mental distress among college students.
Methods
Students from a university in Guangzhou, China, were recruited through a cross-sectional online survey. Data were collected by self-reported questionnaires including socio-demographics, lifestyles and health conditions, sleep patterns on weekdays and weekends, as well as the reduced Morningness-Eveningness Questionnaire (rMEQ), the Insomnia Severity Index, the Epworth Sleepiness Scale, the Beck Depression Inventory-13, and the Zung Self-Rating Anxiety Scale. Multivariate analyses were performed to examine the associations of chronotypes with sleep compensation, sleep disturbances, and mental distress.
Results
A total of 1,607 questionnaires were received, among which 1,569 (97.6%) were valid for further analysis. Among these participants [mean age 19.86 ± 1.16 (15–27) years], morning types (M-types), intermediate types (I-types), and evening types (E-types) accounted for 14.9, 71.5, and 13.6%, respectively. The regression analysis revealed that E-types were positively associated with long sleep compensation on weekends (adjusted OR 2.443, 95%CI 1.740-3.429) compared with I-types, while M-types were the opposite (adjusted OR 0.623, 95%CI 0.392–0.990). E-types were also positively correlated with insomnia symptoms (adjusted OR 2.000, 95%CI 1.428–2.801), depressive symptoms (adjusted OR 2.068, 95%CI 1.496–2.858), and anxiety symptoms (adjusted OR 2.188, 95%CI 1.387–3.451). However, no significant association was found between chronotypes and excessive daytime sleepiness.
Conclusion
Our study found that E-types were associated with long sleep compensation on weekends and insomnia, depression, and anxiety symptoms. Our findings emphasized the importance of early recognition and intervention of E-types and their accompanied sleep problems and mental distress.
... Gender, marital status (dichotomous) and season of birth (dichotomous, summer vs. other seasons) were included as covariates in all regression models. Numerous studies to date have linked season of birth to circadian preferences (Adan et al. 2012;Didikoglu et al. 2019;Natale and Adan 1999;Natale et al. 2009;Tegowska et al. 2006;Tonetti et al. 2011;Vitale et al. 2015;Vollmer et al. 2012). Furthermore, longitudinal associations between season of birth and the change of circadian preferences with age have been shown (Didikoglu et al. 2019). ...
Circadian preferences have been associated with mental health as well as social and physical health in recent years. However, factors associated with circadian preferences have not been fully elucidated. The main aim of this study is to investigate the associations of childhood trauma and attachment styles with circadian preferences. A total of 673 participants were evaluated using the Morningness–Eveningness Questionnaire (MEQ), the Childhood Trauma Questionnaire 28 (CTQ-28), and the Experiences in Close Relationships-Revised (ECR-R) questionnaire. The results indicated that 14.9% (n = 100) of the participants were morning type, 20.6% (n = 139) were evening type, and 64.5% (n = 434) were intermediate type. Both childhood trauma and attachment-related anxiety/avoidance scores were associated with being evening type (p < .01). Moreover, attachment-related anxiety and avoidance fully mediated the association between childhood trauma and circadian preferences. The present study showed that attachment styles might be associated with circadian preferences. Further studies are needed to replicate these results and to infer explanatory mechanisms for these cross-sectional associations.
... Chronotype and other timing characteristics of the CTS can differ by ethnicity, sex, and age (Archer et al. 2018;Eastman et al. 2015; Erren and Lewis 2019; Roenneberg et al. 2003). When chronotype was considered, no association with season of birth was observed in one UK Biobank study (Didikoglu et al. 2020), but small season of birth associations with chronotype or sleep-timing preferences have been observed elsewhere; however, such observations are mostly made in children, adolescents, or University students (Borisenkov et al. 2012;Harada et al. 2011;Natale and Adan 1999;Natale et al. 2002Natale et al. , 2009Natale and Di Milia 2011;Tonetti et al. 2011;Vollmer et al. 2012) in comparison to older adults in the UK Biobank. Of note, the authors of these studies consider season of birth as a proxy for perinatal photoperiod specifically, as opposed to other environmental stimuli. ...
... Differences in method of season of birth categorization (e.g., Winter = Nov, Dec, Jan vs. Winter = Dec, Jan, Feb) may play a role concerning whether and how associations with chronotype can be detected. Some studies note differences between typically longer or shorter seasons and others note differences between whether photoperiod is increasing or decreasing across the season (Vollmer et al. 2012). Utilization of the joint population distribution of individual perinatal photoperiod characteristics and more accuracy as to time windows of susceptibility are potentially required to sufficiently ascertain whether perinatal photoperiod can be copredictive (in addition to factors such as genetic differences (Archer et al. 2018)) of chronotype. ...
Experimental studies indicate that perinatal light may imprint the circadian timing system, subsequently affect later life physiology, and possibly disease risk. We combined individual time-of-year of birth and corresponding latitude to determine perinatal photoperiod characteristics for UK Biobank participants (n = 460,761) and tested for associations with diabetes mellitus (DM, the pathophysiology of which is often linked with circadian disruption) and chronotype (a trait co-governed by the circadian timing system) prevalence in a cross-sectional investigation. The UK Biobank is a population-based cohort with a 5.5% participation rate (~9.2 million individuals were invited into the study between 2006 and 2010). We defined three groups based on photoperiods experienced in the 3rd trimester of pregnancy and first 3 months post-birth time windows: (1) those who exclusively experienced non-extreme photoperiods (NEP, 8–16 hours), (2) those who experienced at least one extreme short photoperiod (ESP, <8 hours), and those who experienced at least one extreme long photoperiod (ELP, >16 hours). For individuals in each group and time window, mean daily photoperiod and relative photoperiod range (relative = relative to the mean) were calculated. Inclusion of relative photoperiod range adds dispersion information (relative change of photoperiods) to statistical models. Multivariable and multinomial logistic regression analyses were used to estimate odds ratios (ORs) and corresponding 95% confidence intervals (CIs). Increased 3rd trimester relative range was associated with decreased odds of DM (OR 0.63 95%CI 0.49–0.81) in the NEP group, but increased odds of DM were detected for the ESP (OR 1.34, 95%CI 0.96–1.86) and ELP groups (OR 1.32, 95%CI 0.78–2.22). Increased 3rd trimester relative range was associated with increased odds of being a “Morning” (OR 1.20, 95%CI 1.02–1.41) or “Evening” (OR 1.43, 95%CI 1.21–1.69) chronotype in the NEP group, but this was not observed in other groups. Additionally, different effect sizes and directions of association with DM were observed in different strata of ethnicity and chronotype and statistically significant odds ratio modifications were detected. In conclusion, perinatal photoperiod associations with DM and chronotype prevalence are detected in the UK Biobank. NEP, ESP, and ELP differences are speculated to be caused by a non-linear dose-response to photoperiods from 0–24 hours or by confounding due to artificial light playing a dominant role in ESP individuals and seeking darkness in ELP individuals. Ethnicity and chronotype may be important effect modifiers of perinatal photoperiod associations with DM. Potential for selection biases due to low UK Biobank participation rate disallows stating conclusions too strongly. Overall, further studies are needed to confirm different perinatal photoperiod associations with DM and chronotype. Further investigations into the hypothesized imprinting mechanism are also warranted.
... A major strength is the use of accelerometry to objectively capture physical activity, nighttime sleep duration, and sleep onset consistency. Many studies rely on maternal self-report of toddler sleep [45,65] and physical activity [66], which often overestimates sleep and physical activity [67][68][69]. In the current study, we used objective measures to collect data over multiple time points within a sample of toddlers at risk for health disparities. ...
Background
Habits surrounding health behaviors (i.e., sleep, physical activity, diet) are developed in toddlerhood. Lack of consistent health habits may increase obesity risk among toddlers in low-income families.
Purpose
To compare the role of sleep onset consistency, physical activity and diet quality as mediators between household poverty and toddler weight.
Methods
Two hundred and seven toddlers (mean age = 20.2 months, 46% female, 68.1% Black) participating in an obesity prevention trial were assessed at three time points over 12 months. Using Actical accelerometers, we assessed sleep and physical activity at each time point for up to 1 week. We defined sleep onset consistency as the standard deviation of sleep onset across all days. We calculated the Healthy Eating Index-2015 from a 24-hr dietary recall. We used WHO standards to calculate BMI-for-age z-scores from toddlers’ weight/length, and calculated poverty ratio from parent-reported income and family size. Multilevel mediation models tested toddler sleep onset consistency, physical activity, and diet quality as mediators between household poverty and toddler BMI z-score.
Results
Toddlers from households with higher poverty ratios had more inconsistent sleep onset times. Toddlers with more inconsistent sleep onset times had higher BMI z-scores across all timepoints, even when accounting for physical activity and diet quality. Sleep onset consistency indirectly explained the association between household poverty and BMI z-score.
Conclusions
Inconsistent sleep schedules could help explain the association between poverty and BMI. Future research should examine strategies to support low-income families to develop and maintain routines as a mechanism to prevent obesity and reduce disparities.
Trial registration number
NCT02615158.
... When sunlight reaches the retina, it provides the internal circadian clock with information about the time of day, thereby leading to daylight entrainment [2]. Dawn is most predominantly linked to daylight entrainment [3] and especially changes in daylength are thought to influence the circadian system [4]. Potential alterations in clock alignment could be reflected indirectly in inattention via sleep duration [5], and even modest misalignment of the clock from sleep/wake behavior can result in poorer quality of sleep [6]. ...
Prevalence rates of attention-deficit/hyperactivity disorder (ADHD) differ with geographical areas varying in sunlight intensity. Sun- or daylight reaching the retina establishes entrainment of the circadian clock to daylight. Changes herein, hence, alterations in clock alignment, could be reflected indirectly in inattention via sleep duration. We here studied (1) annual variation in inattention at treatment initiation; (2) annual variation in response to ADHD treatment [methylphenidate (MPH)] by day of treatment initiation; and (3) dose dependence. We predicted least baseline inattention during a period of high sunlight intensity implying more room for improvement (i.e., a better treatment response) when sunlight intensity is low. These hypotheses were not confirmed. High-dose treated patients, however, had significantly better attention after treatment than low-dosed treated patients, only when treated in the period from winter to summer solstice. Change in solar irradiance (SI) during low-dosed treatment period was negatively related to attentional improvement. The above described findings were primarily found in inattention ratings and replicated in omission errors on a continuous performance task. Daylight and inattention have been proposed to be related via mediation of the circadian system. One mechanism of MPH may be to enhance sensitivity to the diurnal entrainment to sunlight and the question can be raised whether appropriate lighting could potentiate the effects of stimulants.
... Studies in rodent models have shown that postnatal seasonal day length programs later-life biological rhythms by changing the transcription of clock genes which in turn influences the circadian pacemaker and the period of the rhythm (Brooks and Canal, 2013;Ciarleglio et al., 2011). In humans, epidemiological studies have reported that increasing day length is associated with evening preferences (Natale and Adan, 1999;Tonetti et al., 2011;Vollmer et al., 2012). However, the literature is not consistent. ...
... Natale and Adan first suggested that chronotype may be a trait which is programmed by season of birth, with an increased day length being associated with an evening chronotype (Natale and Adan, 1999). Subsequent studies have attempted to test this hypothesis, although the results have been mixed, with some replicating the original finding (Natale and Adan, 1999;Tonetti et al., 2011;Vollmer et al., 2012;Natale et al., 2009;Vitale et al., 2015), some reporting that long day length was associated with morning preferences (Didikoglu et al., 2019;Tegowska et al., 2006), and others finding no association (Huang et al., 2015;Touchette et al., 2008). Explanation for the inconsistency include the different methodologies used. ...
... Explanation for the inconsistency include the different methodologies used. Firstly, the classification of seasons, the measurement of chronotype and statistical methods to compare between groups are different (Tonetti et al., 2011;Vollmer et al., 2012;Vitale et al., 2015). Secondly, the mean age of the cohorts vary between studies (Didikoglu et al., 2019;Huang et al., 2015;Touchette et al., 2008;Vitale et al., 2015). ...
Human chronotype, the temporal pattern of daily behaviors, is influenced by postnatal seasonal programming and ageing. The aim of this study was to investigate genetic variants that are associated with season of birth programming and longitudinal chronotype change. Longitudinal sleep timing and genotype data from 1449 participants were collected for up to 27 years. Gene-environment interaction analysis was performed for 445 candidate single nucleotide polymorphisms that have previously been associated with chronotype. Associations were tested using linear mixed model. We identified 67 suggestively significant genomic loci that have genotype-ageing interaction and 25 genomic loci that may have genotype-season of birth interaction in determining chronotype. We attempted to replicate the results using longitudinal data of the UK Biobank from approximately 30,000 participants. Biological functions of these genes suggest that epigenetic regulation of gene expression and neural development may have roles in these processes. The strongest associated gene for sleep trajectories was ALKBH5, which has functions of DNA repair and epigenetic regulation. A potential candidate gene for postnatal seasonal programming was SIRT1, which has previously been implicated in postnatal programming, ageing and longevity. Genetic diversity may explain the heterogeneity in ageing-related change of sleep timing and postnatal environmental programming of later-life chronotype.
... Eveningness is more likely to occur in individuals born in spring/summer compared to those born in any other season (34,35,41). Yet, another study highlighted more specifically the importance of changes in daylight, where eveningness was more common in individuals born in months mostly associated with increasing day length (February to April [August to October in the Southern hemisphere]) compared to months associated with long, decreasing, or short day length (36). Acute effects of sunlight exposure that occur throughout the lifespan may still modulate the enduring effects of phase-sensitive learning after birth. ...
... Instead of studying the diagnosis of ADHD, we here used an approach covering inattention levels from clinical levels in ADHD patients to levels observed in healthy individuals, which is a more dynamic phenotype that allows for population level variability and may be potentially closer to the hypothesized 'circadian pathway' (13,14). To reduce heterogeneity, analyses focused on 18-50 years, as previous research showed a rapid shift in circadian typology from morningness to eveningness with increasing age in adolescents (36,(44)(45)(46)(47), returning back in the years after that (48). From around the age of 50, even further phase advancing is observed (48). ...
Daylight is the strongest synchronizer of human circadian rhythms. The circadian pathway hypothesis posits that synchrony between daylight and the circadian system relates to (in)attention. The dopamine neurotransmitter system is implicated in regulating the circadian system as well as in (attention)-deficit hyperactivity disorder [ADHD]. We studied the role of functional genetic variation in the gene encoding of dopamine-receptor-D4 (DRD4) in the relationship between inattention and seasonal daylight (changes). Gene-by-environment (GxE) mega-analyses were performed across eight studies including 3757 adult participants (with and without ADHD). We tested 1) the Spring-focus hypothesis, in which attention in 7R-carriers normalizes with increasing daylight levels preceding measurement, 2) the Summer-born ADHD hypothesis, in which 7R-carriers report more inattention when born in spring/summer than in autumn/winter, 3) the Winter-born ADHD hypothesis, opposing the second hypothesis. The Spring-focus hypothesis was upheld (1386 ADHD, 760 controls; d=- 0.16 between periods); 7R-carriers reported even less inattention than 7R-non-carriers after winter solstice (d=0.27 between genotype-groups). Results were diagnosis-independent. Sensitivity analyses at individual study level confirmed the circannual patterns for 7R- carriers. Incorporating geographic changes into the independent measure, we also calculated changes in sunlight levels. This approach likewise showed that inattention correlated negatively with increasing light levels in 7R-carriers (r=-.135). Results emphasize peripheral effects of dopamine and the effects of (seasonal) daylight changes on cognition.
... Several studies using rodent models have demonstrated that the programming effects of postnatal light experience on circadian behavior can be explained by long-term changes in neuropeptide and clock gene expression in the suprachiasmatic nucleus of the brain, the principal circadian pacemaker in mammals (Brooks and Canal 2013). Humans born in long photoperiods have been shown to be associated with evening-type chronotype in several studies (Mongrain et al. 2006;Natale and Adan 1999;Natale et al. 2009;Tonetti et al. 2011;Vollmer et al. 2012). Our data support the hypothesis that season of birth impacts the circadian system, but interestingly we have here found that being born under a long photoperiod causes morningness. ...
... Our data support the hypothesis that season of birth impacts the circadian system, but interestingly we have here found that being born under a long photoperiod causes morningness. Previous studies investigating chronotype and season of birth have tended to use younger populations (<30 years of age) in relatively lower latitudes (Mongrain et al. 2006;Natale and Adan 1999;Natale et al. 2009;Tonetti et al. 2011;Vollmer et al. 2012). Variations in methods used to classify chronotype and season also differ in the literature (Tonetti et al. 2011;Vollmer et al. 2012). ...
... Previous studies investigating chronotype and season of birth have tended to use younger populations (<30 years of age) in relatively lower latitudes (Mongrain et al. 2006;Natale and Adan 1999;Natale et al. 2009;Tonetti et al. 2011;Vollmer et al. 2012). Variations in methods used to classify chronotype and season also differ in the literature (Tonetti et al. 2011;Vollmer et al. 2012). Nevertheless, the large sample size and longitudinal approach in the current study strongly support our findings. ...
Evening-oriented sleep timing preferences have been associated with risk of diabetes, cardiovascular diseases, obesity, psychiatric disorders, and increased mortality. This research aims to explore the relationship between diurnal preferences (chronotype), daily habits, metabolic health, and mortality, using longitudinal data from The University of Manchester Longitudinal Study of Cognition in Normal Healthy Old Age (6375 participants at inception, recruited in the North of England) with a long follow-up period (up to 35.5 years). Mixed models were used to investigate the influence of aging, socio-demographic, and seasonal factors on sleep timing. Results show that sleep timing shifted towards earlier time with aging. Test seasons influence chronotype of older adults but working schedules challenge seasonality of sleep timing. Moreover, the season of birth may set chronotype in adulthood. Individual chronotype trajectories were clustered using latent class analysis and analyzed against metabolic health and mortality. We observed a higher risk of hypertension in the evening-type cluster compared to morning-type individuals (Odds ratio = 1.88, 95%CI = 1.02/3.47, p = .04). Evening-type cluster was also associated with traits related to lower health such as reduced sport participation, increased risk of depression and psychoticism personality, late eating, and increased smoking and alcohol usage. Finally, Cox regression of proportional hazards was used to study the effects of chronotype on longevity after adjusting for sleep duration, age, gender, smoking, alcohol usage, general health, and social class. The survival analysis (82.6% censored by death) revealed that evening-type chronotype increased the likelihood of mortality (Hazard ratio = 1.15, 95%CI = 1.04/1.26, p = .005). Taken together, chronotype is influenced by aging and seasonal effects. Evening-type preference may have detrimental outcomes for human well-being and longevity.
