Predicting the actigraphy-based acrophase using the Morningness–Eveningness Questionnaire (MEQ) in college students of North Italy

Abstract

ABSTRACTActigraphy is the reference objective method to measure circadian rhythmicity. One simpler subjective approach to assess the circadian typology is the Morningness–Eveningness Questionnaire (MEQ) by Horne and Ostberg. In this study, we compared the MEQ score against the actigraphy-based circadian parameters MESOR, amplitude and acrophase in a sample of 54 students of the University of Milan in Northern Italy. MEQ and the acrophase resulted strongly and inversely associated (r = −0.84, p < 0.0001), and their relationship exhibited a clear-cut linear trend. We thus used linear regression to develop an equation enabling us to predict the value of the acrophase from the MEQ score. The parameters of the regression model were precisely estimated, with the slope of the regression line being significantly different from 0 (p < 0.0001). The best-fit linear equation was: acrophase (min) = 1238.7–5.49·MEQ, indicating that each additional point in the MEQ score corresponded to a shortening of the acrophase of approximately 5 min. The coefficient of determination, R2, was 0.70. The residuals were evenly distributed and did not show any systematic pattern, thus indicating that the linear model yielded a good, balanced prediction of the acrophase throughout the range of the MEQ score. In particular, the model was able to accurately predict the mean values of the acrophase in the three chronotypes (Morning-, Neither-, and Evening-types) in which the study subjects were categorized. Both the confidence and prediction limits associated to the regression line were calculated, thus providing an assessment of the uncertainty associated with the prediction of the model. In particular, the size of the two-sided prediction limits for the acrophase was about ±100 min in the midrange of the MEQ score. Finally, k-fold cross-validation showed that both the model’s predictive ability on new data and the model’s stability to changes in the data set used for parameter estimation were good. In conclusion, the actigraphy-based acrophase can be predicted using the MEQ score in a population of college students of North Italy.