Determinants of diet and physical activity (DEDIPAC): a summary of findings

Abstract

The establishment of the Determinants of Diet and Physical Activity (DEDIPAC) Knowledge Hub, 2013–2016, was the first action taken by the ‘Healthy Diet for a Healthy Life’ European Joint Programming Initiative. DEDIPAC aimed to provide better insight into the determinants of diet, physical activity and sedentary behaviour across the life course, i.e. insight into the causes of the causes of important, non-communicable diseases across Europe and beyond. DEDIPAC was launched in late 2013, and delivered its final report in late 2016. In this paper we give an overview of what was achieved in terms of furthering measurement and monitoring, providing overviews of the state-of-the-art in the field, and building toolboxes for further research and practice. Additionally, we propose some of the next steps that are now required to move forward in this field, arguing in favour of 1) sustaining the Knowledge Hub and developing it into a European virtual research institute and knowledge centre for determinants of behavioural nutrition and physical activity with close links to other parts of the world; 2) establishing a cohort study of families across all regions of Europe focusing specifically on the individual and contextual determinants of major, non-communicable disease; and 3) furthering DEDIPAC’s work on nutrition, physical activity, and sedentary behaviour policy evaluation and benchmarking across Europe by aligning with other international initiatives and by supporting harmonisation of pan-European surveillance.

Associations of self-reported physical activity and anxiety symptoms and status among 7,874 Irish adults across harmonised datasets: a DEDIPAC-study

“…The selection of participating studies has been described elsewhere [44]. Briefly, the platform for the current research was the DEterminants of DIet and Physical ACtivity Knowledge Hub (DEDIPAC-KH) [45,46]. Within DEDIPAC, accessible cross-sectional datasets with relevant data on physical activity and anxiety were identified in a large compendium for harmonisation [47].…”

“…Covariates were selected based on known associations with physical activity or anxiety [34,45,[55][56][57]. These included age (50-59, 60-69, 70-79, and 80+ years), sex (male or female), and BMI categorized as using established WHO thresholds (i.e., underweight: < 18.5 kg.m − 2 ; normal weight: 18.5-24.99 kg.m − 2 ; overweight: 25-29.99 kg.m − 2 ; obese: ≥30 kg.m − 2 ) [58].…”

Association between objectively measured physical behaviour and neck‐ and/or low back pain: A systematic review

“…Self‐reported physical behaviour is prone to bias and misclassification (Gupta et al, 2017; Lagersted‐Olsen et al, 2014; Pedersen, Kitic, Bird, Mainsbridge, & Cooley, 2016), and it is strongly advocated that objective measurements (e.g. accelerometery) should be implemented in cohort studies when possible to obtain more valid estimates of physical behaviour in relation to health outcomes (Brug et al, 2017; Perruchoud et al, 2014). The number of studies with long‐term objective measurements of physical behaviour has increased substantially during recent years (Silfee et al, 2018).…”

Computer Vision-Based Unobtrusive Physical Activity Monitoring in School by Room-Level Physical Activity Estimation: A Method Proposition

“…Accelerometers have seen wide and methodologically varied application in PA research [33][34][35][36][37]. Although accelerometers provide rather good indication of PA intensity and sedentary behavior, especially when combined with additional sensors such as inclinometers and gyroscopes, decisions related to sensor data management and analysis remain somewhat subjective [37][38][39][40]. Specifically, devices of different manufacturers calculate activity counts using different formulae (which are not always published), and there is no consensus on parameters of recording and methods of aggregating acceleration data to reflect comparably [41] the concepts of moderate and vigorous PA.…”