Age and gender differences in circadian phenotypes

Introduction: It is well known that people exhibit a circadian rhythm in a number of physiological and neurobehavioral functions. This endogenous rhythm can be described on the base of phase, amplitude and stability of the rhythm and trait-individual differences can be found in these circadian rhythm parameters. Phase measurements have drawn a lot of research attention, whereas little emphasis was placed on the other circadian rhythm parameters. Objectives: This study was draft up to further examine age, gender and shiftwork differences in regard to circadian rhythm parameters. Methods: Subjects: 1305 subjects filled in the online survey measuring circadian type parameters. The mean age of the total sample was 31 years (SD=13), with an age range of 12-90 years. Men made up 29% of the sample (N=337) and had a mean age of 33 years (SD=14), women made up 71% of the sample (N=928) and had a mean age of 32 years (SD=13). Of the total sample 10% (N=131) worked in shifts, of which 41% men (N=54) and 59% women (N=77). Measurements: Subjects were asked to complete five questionnaires online: the Circadian Type Inventory (CTI| Di Milia, Smith, & Folkard, P&ID, 2004), the Circadian Amplitude and Phase Scale (CAPS| Di Milia, Folkard, Hill, & Walker, CI, 2010), the Pittsburgh Sleep Quality Index (PSQI| Buysse, Reynolds, Monk, Berman, & Kupfer, PR, 1989), the Composite Scale of Morningness (CSM| Smith, Reilly, & Midkiff, JoAP, 1989), the Epworth Sleepiness Scale (ESS| Johns, S, 1991) in combination with additive questions about demographic characteristics. Here we will only focus on results regarding CTI and CAPS. Statistics: To look more closely into age, gender and shiftwork variations in circadian rhythm parameters MANOVA's were performed with circadian rhythm parameters as dependent variables, gender and shiftwork as fixed factors and age as covariate. Results: CTI Using Pillai's trace, there was a significant effect of the inter-individual variables of age (V = .086, F(2,1298) = 61.241, p Separate univariate ANOVA's revealed an age effect regarding circadian languidity, whereby younger age was associated with more languidity (F(1,1299) = 115.441, p CAPS The multivariate models for age (V = .047, F(3,1297) = 21.298, p An effect of age and gender was found on all parameters. Age was positively associated with morningness (F(1,1301) = 5.981, p Conclusion: Our results indicate a small but significant association between older age and morningness, strength of preference and time awareness. These variables are expected to reflect daytime impairment and the susceptibility to rhythm disturbances, which in turn are associated with increased age (Di Milia, Folkard, Hill & Walker, CI, 2010; Kerkhof, BP, 1985). In contrast, we found a decrease in languidity to be associated with an increase in age, however this association also remains rather modest. Gender effects in circadian rhythm parameters were found; men seem to show more flexibility of the circadian rhythm and a lower strength of preference. Both parameters can be associated with a more flexible circadian regulation. These findings corroborate with the finding that the circadian system is more flexible in men in comparison with women (Natale & Danese, BRR, 2002). Furthermore a difference in circadian flexibility was found between shift workers and non-shift workers. This finding may be explained by the self-selection effect often reported in shift work research, whereby more tolerant people start and stay engaged in shift work, in combination with the reported association between circadian flexibility and shift work tolerance (Knutsson & Åkerstedt, W&S, 1992; Di Milia, Smith & Folkard, P&ID, 2005).