73 research outputs found

    Sleep and energy intake in early childhood

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    Background And Objectives: Shorter sleep is associated with higher weight in children, but little is known about the mechanisms. The aim of this study was to test the hypothesis that shorter sleep was associated with higher energy intake in early childhood. Methods: Participants were 1303 families from the Gemini twin birth cohort. Sleep duration was measured using the Brief Infant Sleep Questionnaire when the children were 16 months old. Total energy intake (kcal per day) and grams per day of fat, carbohydrate and protein were derived from 3-day diet diaries completed by parents when children were 21 months old. Results: Shorter nighttime sleep was associated with higher total energy intake (P for linear trend=0.005). Children sleeping <10 h consumed around 50 kcal per day more than those sleeping 11–<12 h a night (the optimal sleep duration for children of this age). Differences in energy intake were maintained after adjustment for confounders. As a percentage of total energy intake, there were no significant differences in macronutrient intake by sleep duration. The association between sleep and weight was not significant at this age (P=0.13). Conclusions: This study provides the first evidence that shorter nighttime sleep duration has a linear association with higher energy intake early in life. That the effect is observed before emergence of associations between sleep and weight indicates that differences in energy intake may be a mechanism through which sleep influences weight gain

    Short sleep duration and obesity among Australian children

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    Extent: 6p.Background: There is limited information on sleep duration and obesity among Australian children. The objective of the study is to cross-sectionally examine the relationship between sleep duration and obesity in Australian children aged 5 to 15 years. Methods: Data were collected using the South Australian Monitoring and Surveillance System between January 2004 and December 2008. Each month a representative random sample of South Australians are selected from the Electronic White Pages with interviews conducted using Computer Assisted Telephone Interviewing (CATI). Within each household, the person who was last to have a birthday was selected for interview. Parents reported the number of hours their children slept each day. Obesity was defined according to the International Obesity Task Force (IOTF) definition based on BMI calculated from reported body weight and height. Results: Overall, parents of 3495 children aged 5-15 years (mean 10.7 years, 50.3% boys) were interviewed. The prevalence of obesity was 7.7% (8.9% in boys, 6.6% in girls). In multivariate analysis after adjusting for sociodemographic variables, intake of fruit and vegetables, physical activity and inactivity, the odds ratio (OR) for obesity comparing sleeping <9 hours with ≥10 hours was 2.23 (95% CI 1.04-4.76) among boys, 1.70(0.78-3.73) among girls, and 1.97(1.15-3.38) in both genders. The association between short sleep (<9 hours) and obesity was stronger in the younger age group. No significant association between short sleep and obesity was found among children aged 13-15. There was also an additive interaction between short sleep and low level of physical activity. Conclusion: Short sleep duration is associated with increased obesity in children especially among younger age groups and boys.Zumin Shi, Anne W Taylor, Tiffany K Gill, Jane Tuckerman, Robert Adams and James Marti

    Effects of circadian disruption on physiology and pathology: from bench to clinic (and back)

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    Nested within the hypothalamus, the suprachiasmatic nuclei (SCN) represent a central biological clock that regulates daily and circadian (i.e., close to 24 h) rhythms in mammals. Besides the SCN, a number of peripheral oscillators throughout the body control local rhythms and are usually kept in pace by the central clock. In order to represent an adaptive value, circadian rhythms must be entrained by environmental signals or zeitgebers, the main one being the daily light?dark (LD) cycle. The SCN adopt a stable phase relationship with the LD cycle that, when challenged, results in abrupt or chronic changes in overt rhythms and, in turn, in physiological, behavioral, and metabolic variables. Changes in entrainment, both acute and chronic, may have severe consequences in human performance and pathological outcome. Indeed, animal models of desynchronization have become a useful tool to understand such changes and to evaluate potential treatments in human subjects. Here we review a number of alterations in circadian entrainment, including jet lag, social jet lag (i.e., desynchronization between body rhythms and normal time schedules), shift work, and exposure to nocturnal light, both in human subjects and in laboratory animals. Finally, we focus on the health consequences related to circadian/entrainment disorders and propose a number of approaches for the management of circadian desynchronization.Fil: Chiesa, Juan José. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Duhart, José Manuel. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Casiraghi, Leandro Pablo. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Paladino, Natalia. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Bussi, Ivana Leda. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Golombek, Diego Andrés. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

    Body mass index and musculoskeletal pain: is there a connection?

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