31 research outputs found

    Phenotypic Responses to a Lifestyle Intervention Do Not Account for Inter-Individual Variability in Glucose Tolerance for Individuals at High Risk of Type 2 Diabetes

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    Background: Lifestyle interventions have been shown to delay or prevent the onset of type 2 diabetes among high risk adults. A better understanding of the variability in physiological responses would support the matching of individuals with the best type of intervention in future prevention programmes, in order to optimize risk reduction. The purpose of this study was to determine if phenotypic characteristics at baseline or following a 12 weeks lifestyle intervention could explain the inter-individual variability in change in glucose tolerance in individuals with high risk for type 2 diabetes.Methods: In total, 285 subjects with normal glucose tolerance (NGT, FINDRISC score > 12), impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) were recruited for a 12 weeks lifestyle intervention. Glucose tolerance, insulin sensitivity, anthropometric characteristics and aerobic fitness were measured. Variability of responses was examined by grouping participants by baseline glycemic status, by cluster analysis based on the change in glucose tolerance and by Principal Component Analysis (PCA).Results: In agreement with other studies, the mean response to the 12 weeks intervention was positive for the majority of parameters. Overall, 89% improved BMI, 80% waist circumference, and 81% body fat while only 64% improved fasting plasma glucose and 60% 2 h glucose. The impact of the intervention by glycaemic group did not show any phenotypic differences in response between NGT, IFG, and IGT. A hierarchical cluster analysis of change in glucose tolerance identified four sub-groups of “responders” (high and moderate) and “non-responders” (no response or deteriorated) but there were few differences in baseline clincal and physiological parameters or in response to the intervention to explain the overall variance. A further PCA analysis of 19 clinical and physiological univariables could explain less than half (48%) of total variability.Conclusion: We found that phenotypic characteristics from standard clinical and physiological parameters were not sufficient to account for the inter-individual variability in glucose tolerance following a 12 weeks lifestyle intervention in inidivuals at high risk for type 2 diabetes. Further work is required to identify biomarkers that complement phenotypic traits and better predict the response to glucose tolerance

    Towards the integration and development of a cross-European research network and infrastructure:the DEterminants of DIet and Physical ACtivity (DEDIPAC) Knowledge Hub

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    To address major societal challenges and enhance cooperation in research across Europe, the European Commission has initiated and facilitated ‘joint programming’. Joint programming is a process by which Member States engage in defining, developing and implementing a common strategic research agenda, based on a shared vision of how to address major societal challenges that no Member State is capable of resolving independently. Setting up a Joint Programming Initiative (JPI) should also contribute to avoiding unnecessary overlap and repetition of research, and enable and enhance the development and use of standardised research methods, procedures and data management. The Determinants of Diet and Physical Activity (DEDIPAC) Knowledge Hub (KH) is the first act of the European JPI ‘A Healthy Diet for a Healthy Life’. The objective of DEDIPAC is to contribute to improving understanding of the determinants of dietary, physical activity and sedentary behaviours. DEDIPAC KH is a multi-disciplinary consortium of 46 consortia and organisations supported by joint programming grants from 12 countries across Europe. The work is divided into three thematic areas: (I) assessment and harmonisation of methods for future research, surveillance and monitoring, and for evaluation of interventions and policies; (II) determinants of dietary, physical activity and sedentary behaviours across the life course and in vulnerable groups; and (III) evaluation and benchmarking of public health and policy interventions aimed at improving dietary, physical activity and sedentary behaviours. In the first three years, DEDIPAC KH will organise, develop, share and harmonise expertise, methods, measures, data and other infrastructure. This should further European research and improve the broad multi-disciplinary approach needed to study the interactions between multilevel determinants in influencing dietary, physical activity and sedentary behaviours. Insights will be translated into more effective interventions and policies for the promotion of healthier behaviours and more effective monitoring and evaluation of the impacts of such intervention

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

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    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

    Towards the integration and development of a cross-European research network and infrastructure: the DEterminants of DIet and Physical ACtivity (DEDIPAC) Knowledge Hub

    Get PDF
    To address major societal challenges and enhance cooperation in research across Europe, the European Commission has initiated and facilitated `joint programming’. Joint programming is a process by which Member States engage in defining, developing and implementing a common strategic research agenda, based on a shared vision of how to address major societal challenges that no Member State is capable of resolving independently. Setting up a Joint Programming Initiative (JPI) should also contribute to avoiding unnecessary overlap and repetition of research, and enable and enhance the development and use of standardised research methods, procedures and data management. The Determinants of Diet and Physical Activity (DEDIPAC) Knowledge Hub (KH) is the first act of the European JPI `A Healthy Diet for a Healthy Life’. The objective of DEDIPAC is to contribute to improving understanding of the determinants of dietary, physical activity and sedentary behaviours. DEDIPAC KH is a multi-disciplinary consortium of 46 consortia and organisations supported by joint programming grants from 12 countries across Europe. The work is divided into three thematic areas: (I) assessment and harmonisation of methods for future research, surveillance and monitoring, and for evaluation of interventions and policies; (II) determinants of dietary, physical activity and sedentary behaviours across the life course and in vulnerable groups; and (III) evaluation and benchmarking of public health and policy interventions aimed at improving dietary, physical activity and sedentary behaviours. In the first three years, DEDIPAC KH will organise, develop, share and harmonise expertise, methods, measures, data and other infrastructure. This should further European research and improve the broad multi-disciplinary approach needed to study the interactions between multilevel determinants in influencing dietary, physical activity and sedentary behaviours. Insights will be translated into more effective interventions and policies for the promotion of healthier behaviours and more effective monitoring and evaluation of the impacts of such interventions

    Energy expenditure and affect responses to different types of active video game and exercise - Fig 3

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    <p><b>A.</b> State of core flow immediately after the trials. All data presented as mean ± SEM. *significantly different than SS-EX and MOD-EX, <i>P</i> < 0.05. <b>b</b> Differences in psychological well-being before and immediately after the trials (PWB post diff) and before and 20 min after trial completion (PWB 20 min post diff). „ significantly different than all other trials, <i>P</i> < 0.05. <b>c</b> Enjoyment at 15 and 29 min, and average scores. *significantly different than SS-EX and MOD-EX, <i>P</i> < 0.01. <b>d.</b> Rate of perceived exertion (RPE) at 15 and 29 min and average scores. „ significantly different than all other trials, <i>P</i> < 0.05; ѱ significantly different than ET-VG, <i>P</i> < 0.05;.§ significantly different than MOD-EX and ET-VG, <i>P</i> < 0.01. All data presented as mean ± SEM.</p
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