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Variation of circadian activity rhythm according to body mass index in children
Affiliation:1. Department of Psychology, University of Bologna, Viale Berti Pichat 5, 40127, Bologna, Italy;2. Department of Experimental, Diagnostic and Specialty Medicine, DIMES, University of Bologna, Viale Berti Pichat 5, 40127, Bologna, Italy;3. Department of Biomedical and Neuromotor Sciences, DIBINEM, University of Bologna, Via Altura 3, 40139, Bologna, Italy;4. Department of Psychology, University of Campania “Luigi Vanvitelli”, Viale Ellittico 31, 81100, Caserta, Italy;5. Laboratório de Cronobiologia e Sono Do Hospital de Clínicas de Porto Alegre (HCPA), Universidade Federal Do Rio Grande Do Sul (UFRGS), Ramiro Barcelos 2350, CEP 90035-003, Porto Alegre, Rio Grande do Sul, Brazil;6. Programa de Pós-Graduação Em Psiquiatria e Ciências Do Comportamento, Faculdade de Medicina, UFRGS, Ramiro Barcelos 2350, CEP 90035-003, Porto Alegre, Rio Grande do Sul, Brazil
Abstract:Background/objectivesThis study aimed to examine the variations of circadian activity rhythm of children according to objective body mass index (BMI) values, using a novel statistical framework (ie, Functional Linear Modeling, FLM), separately for school- and weekend days.MethodsA total of 107 participants (60 females; mean age: 10.25 ± 0.48 years) wore an actigraph for seven days during a regular school-week. While valid actigraphic data during school days were available for each of these children, this number decreased to 53 (31 females; mean age: 10.28 ± 0.51 years) during weekend days.ResultsExamining the school days, significantly higher motor activity in participants with higher BMI was observed from around 4:00 a.m. to 6:00 a.m., with a peak about 5:00 a.m. On the contrary, applying the FLM to the weekend days actigraphic data, no significantly different variation of circadian activity rhythm was observed, according to BMI.ConclusionsIn this specific sample of children, during school days, higher BMI is associated with higher activity level in a specific time window in the second half of nocturnal sleep. The lack of significant findings during weekend days could be explained because of higher variability of get-up time and/or the reduced sample size. Future longitudinal studies could explore if the higher motor activity in that specific time window qualifies as a predictive marker of the development of overweight and obesity. If so, early preventive strategies directed towards those at higher risk could be effectively implemented.
Keywords:Actigraphy  Body mass index  Childhood  Circadian rhythms  Functional linear modeling  Motor activity
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