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      Real-time Mobile Monitoring of the Dynamic Associations Among Motor Activity, Energy, Mood, and Sleep in Adults With Bipolar Disorder

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          Abstract

          Biologic systems involved in the regulation of motor activity are intricately linked with other homeostatic systems such as sleep, feeding behavior, energy, and mood. Mobile monitoring technology (eg, actigraphy and ecological momentary assessment devices) allows the assessment of these multiple systems in real time. However, most clinical studies of mental disorders that use mobile devices have not focused on the dynamic associations between these systems.

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          Most cited references56

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          Physical activity and cardiorespiratory fitness as major markers of cardiovascular risk: their independent and interwoven importance to health status.

          The evolution from hunting and gathering to agriculture, followed by industrialization, has had a profound effect on human physical activity (PA) patterns. Current PA patterns are undoubtedly the lowest they have been in human history, with particularly marked declines in recent generations, and future projections indicate further declines around the globe. Non-communicable health problems that afflict current societies are fundamentally attributable to the fact that PA patterns are markedly different than those for which humans were genetically adapted. The advent of modern statistics and epidemiological methods has made it possible to quantify the independent effects of cardiorespiratory fitness (CRF) and PA on health outcomes. Based on more than five decades of epidemiological studies, it is now widely accepted that higher PA patterns and levels of CRF are associated with better health outcomes. This review will discuss the evidence supporting the premise that PA and CRF are independent risk factors for cardiovascular disease (CVD) as well as the interplay between both PA and CRF and other CVD risk factors. A particular focus will be given to the interplay between CRF, metabolic risk and obesity.
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            Is Open Access

            A systematic review of correlates of sedentary behaviour in adults aged 18–65 years: a socio-ecological approach

            Background Recent research shows that sedentary behaviour is associated with adverse cardio-metabolic consequences even among those considered sufficiently physically active. In order to successfully develop interventions to address this unhealthy behaviour, factors that influence sedentariness need to be identified and fully understood. The aim of this review is to identify individual, social, environmental, and policy-related determinants or correlates of sedentary behaviours among adults aged 18–65 years. Methods PubMed, Embase, CINAHL, PsycINFO and Web of Science were searched for articles published between January 2000 and September 2015. The search strategy was based on four key elements and their synonyms: (a) sedentary behaviour (b) correlates (c) types of sedentary behaviours (d) types of correlates. Articles were included if information relating to sedentary behaviour in adults (18–65 years) was reported. Studies on samples selected by disease were excluded. The full protocol is available from PROSPERO (PROSPERO 2014:CRD42014009823). Results 74 original studies were identified out of 4041: 71 observational, two qualitative and one experimental study. Sedentary behaviour was primarily measured as self-reported screen leisure time and total sitting time. In 15 studies, objectively measured total sedentary time was reported: accelerometry (n = 14) and heart rate (n = 1). Individual level factors such as age, physical activity levels, body mass index, socio-economic status and mood were all significantly correlated with sedentariness. A trend towards increased amounts of leisure screen time was identified in those married or cohabiting while having children resulted in less total sitting time. Several environmental correlates were identified including proximity of green space, neighbourhood walkability and safety and weather. Conclusions Results provide further evidence relating to several already recognised individual level factors and preliminary evidence relating to social and environmental factors that should be further investigated. Most studies relied upon cross-sectional design limiting causal inference and the heterogeneity of the sedentary measures prevented direct comparison of findings. Future research necessitates longitudinal study designs, exploration of policy-related factors, further exploration of environmental factors, analysis of inter-relationships between identified factors and better classification of sedentary behaviour domains. Electronic supplementary material The online version of this article (doi:10.1186/s12889-016-2841-3) contains supplementary material, which is available to authorized users.
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              Physiological adaptations to weight loss and factors favouring weight regain

              F Greenway (2015)
              Obesity is a major global health problem and predisposes individuals to several comorbidities that can affect life expectancy. Interventions based on lifestyle modification (for example, improved diet and exercise) are integral components in the management of obesity. However, although weight loss can be achieved through dietary restriction and/or increased physical activity, over the long term many individuals regain weight. The aim of this article is to review the research into the processes and mechanisms that underpin weight regain after weight loss and comment on future strategies to address them. Maintenance of body weight is regulated by the interaction of a number of processes, encompassing homoeostatic, environmental and behavioural factors. In homoeostatic regulation, the hypothalamus has a central role in integrating signals regarding food intake, energy balance and body weight, while an ‘obesogenic' environment and behavioural patterns exert effects on the amount and type of food intake and physical activity. The roles of other environmental factors are also now being considered, including sleep debt and iatrogenic effects of medications, many of which warrant further investigation. Unfortunately, physiological adaptations to weight loss favour weight regain. These changes include perturbations in the levels of circulating appetite-related hormones and energy homoeostasis, in addition to alterations in nutrient metabolism and subjective appetite. To maintain weight loss, individuals must adhere to behaviours that counteract physiological adaptations and other factors favouring weight regain. It is difficult to overcome physiology with behaviour. Weight loss medications and surgery change the physiology of body weight regulation and are the best chance for long-term success. An increased understanding of the physiology of weight loss and regain will underpin the development of future strategies to support overweight and obese individuals in their efforts to achieve and maintain weight loss.
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                Author and article information

                Journal
                JAMA Psychiatry
                JAMA Psychiatry
                American Medical Association (AMA)
                2168-622X
                December 12 2018
                Affiliations
                [1 ]Genetic Epidemiology Research Branch, Intramural Research Program, National Institute of Mental Health, Bethesda, Maryland
                [2 ]University of Bordeaux, National Center for Scientific Research, Bordeaux, France
                [3 ]EPHE PSL Research University, Paris, France
                [4 ]Brain & Mind Centre, University of Sydney, Sydney, New South Wales, Australia
                [5 ]Department of Biostatistics, University of Pennsylvania, Philadelphia
                [6 ]Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
                [7 ]Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, People's Republic of China
                [8 ]Department of Psychiatry and EMGO Institute for Health and Care Research, VU University Medical Centre, Amsterdam, the Netherlands
                [9 ]Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
                [10 ]National Institute of Drug Abuse, Bethesda, Maryland
                [11 ]Laboratory of Neuroimaging, National Institute of Alcohol Abuse and Alcoholism, Bethesda, Maryland
                Article
                10.1001/jamapsychiatry.2018.3546
                6439734
                30540352
                71a3ac95-7980-4aa2-83cc-92c6740ad5bb
                © 2018
                History

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