Identifying and sharing data for secondary data analysis of physical activity, sedentary behaviour and their determinants across the life course in Europe: general principles and an example from DEDIPAC

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Abstract

Background

The utilisation of available cross-European data for secondary data analyses on physical activity, sedentary behaviours and their underlying determinants may benefit from the wide variation that exists across Europe in terms of these behaviours and their determinants. Such reuse of existing data for further research requires Findable; Accessible; Interoperable; Reusable (FAIR) data management and stewardship. We here describe the inventory and development of a comprehensive European dataset compendium and the process towards cross-European secondary data analyses of pooled data on physical activity, sedentary behaviour and their correlates across the life course.

Methods

A five-step methodology was followed by the European Determinants of Diet and Physical Activity (DEDIPAC) Knowledge Hub, covering the (1) identification of relevant datasets across Europe, (2) development of a compendium including details on the design, study population, measures and level of accessibility of data from each study, (3) definition of key topics and approaches for secondary analyses, (4) process of gaining access to datasets and (5) pooling and harmonisation of the data and the development of a data harmonisation platform.

Results

A total of 114 unique datasets were found for inclusion within the DEDIPAC compendium. Of these datasets, 14 were eventually obtained and reused to address 10 exemplar research questions. The DEDIPAC data harmonisation platform proved to be useful for pooling, but in general, harmonisation was often restricted to just a few core (crude) outcome variables and some individual-level sociodemographic correlates of these behaviours.

Conclusions

Obtaining, pooling and harmonising data for secondary data analyses proved to be difficult and sometimes even impossible. Compliance to FAIR data management and stewardship principles currently appears to be limited for research in the field of physical activity and sedentary behaviour. We discuss some of the reasons why this might be the case and present recommendations based on our experience.

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

Grainne O'Donoghue, Camille Perchoux, Keitly Mensah … (2016)

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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DataSHIELD: taking the analysis to the data, not the data to the analysis

Amadou Gaye, Yannick Marcon, Julia Isaeva … (2014)

Background: Research in modern biomedicine and social science requires sample sizes so large that they can often only be achieved through a pooled co-analysis of data from several studies. But the pooling of information from individuals in a central database that may be queried by researchers raises important ethico-legal questions and can be controversial. In the UK this has been highlighted by recent debate and controversy relating to the UK’s proposed ‘care.data’ initiative, and these issues reflect important societal and professional concerns about privacy, confidentiality and intellectual property. DataSHIELD provides a novel technological solution that can circumvent some of the most basic challenges in facilitating the access of researchers and other healthcare professionals to individual-level data. Methods: Commands are sent from a central analysis computer (AC) to several data computers (DCs) storing the data to be co-analysed. The data sets are analysed simultaneously but in parallel. The separate parallelized analyses are linked by non-disclosive summary statistics and commands transmitted back and forth between the DCs and the AC. This paper describes the technical implementation of DataSHIELD using a modified R statistical environment linked to an Opal database deployed behind the computer firewall of each DC. Analysis is controlled through a standard R environment at the AC. Results: Based on this Opal/R implementation, DataSHIELD is currently used by the Healthy Obese Project and the Environmental Core Project (BioSHaRE-EU) for the federated analysis of 10 data sets across eight European countries, and this illustrates the opportunities and challenges presented by the DataSHIELD approach. Conclusions: DataSHIELD facilitates important research in settings where: (i) a co-analysis of individual-level data from several studies is scientifically necessary but governance restrictions prohibit the release or sharing of some of the required data, and/or render data access unacceptably slow; (ii) a research group (e.g. in a developing nation) is particularly vulnerable to loss of intellectual property—the researchers want to fully share the information held in their data with national and international collaborators, but do not wish to hand over the physical data themselves; and (iii) a data set is to be included in an individual-level co-analysis but the physical size of the data precludes direct transfer to a new site for analysis.

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A systematic review of determinants of sedentary behaviour in youth: a DEDIPAC-study

Annabel Stierlin, Sara De Lepeleere, Greet Cardon … (2015)

Sedentary behaviour (SB) has emerged as a potential risk factor for metabolic health in youth. Knowledge on the determinants of SB in youth is necessary to inform future intervention development to reduce SB. A systematic review was conducted to identify predictors and determinants of SB in youth. Pubmed, Embase, CINAHL, PsycINFO and Web of Science were searched, limiting to articles in English, published between January 2000 and May 2014. The search strategy was based on four key elements and their synonyms: (a) sedentary behaviour, (b) determinants, (c) types of sedentary behaviours, (d) types of determinants. The full protocol is available from PROSPERO (PROSPERO 2014:CRD42014009823). Cross-sectional studies were excluded. The analysis was guided by the socio-ecological model. 37 studies were selected out of 2654 identified papers from the systematic literature search. Most studies were conducted in Europe (n = 13), USA (n = 11), and Australia (n = 10). The study quality, using the Qualsyst tool, was high with a median of 82 % (IQR: 74–91 %). Multiple potential determinants were studied in only one or two studies. Determinants were found at the individual, interpersonal, environmental and policy level but few studies examined a comprehensive set of factors at different levels of influences. Evidence was found for age being positively associated with total SB, and weight status and baseline assessment of screen time being positively associated with screen time (at follow-up). A higher playground density and a higher availability of play and sports equipment at school were consistently related to an increased total SB, although these consistent findings come from single studies. Evidence was also reported for the presence of safe places to cross roads and lengthening morning and lunch breaks being associated with less total SB. Future interventions to decrease SB levels should especially target children with overweight or obesity and should start at a young age. However, since the relationship of many determinants with SB remains inconsistent, there is still a need for more longitudinal research on determinants of SB in youth. Electronic supplementary material The online version of this article (doi:10.1186/s12966-015-0291-4) contains supplementary material, which is available to authorized users.

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Author and article information

Journal

Journal ID (nlm-ta): BMJ Open

Journal ID (iso-abbrev): BMJ Open

Journal ID (hwp): bmjopen

Journal ID (publisher-id): bmjopen

Title: BMJ Open

Publisher: BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )

ISSN (Electronic): 2044-6055

Publication date Collection: 2017

Publication date (Electronic): 22 October 2017

Volume: 7

Issue: 10

Electronic Location Identifier: e017489

Affiliations

[1 ] departmentDepartment of Epidemiology and Biostatistics , AmsterdamPublic Health research institute, VU University Medical Center , Amsterdam, Netherlands

[2 ] departmentDepartment of Physical Education and Sport Sciences , Centre for Physical Activity and Health Research, University of Limerick , Limerick, Ireland

[3 ] Institute of Sport, Exercise and Active Living, Victoria University , Melbourne, Victoria, Australia

[4 ] departmentDepartment of Psychology , Bournemouth University , Bournemouth, UK

[5 ] departmentDepartment of Movement and Sports Sciences , Ghent University , Ghent, Belgium

[6 ] departmentDepartment of Public and Occupational Health , AmsterdamPublic Health research institute, VU University Medical Center , Amsterdam, Netherlands

[7 ] departmentCentre for Preventive Medicine , School of Health and Human Performance, Dublin City University , Dublin, Ireland

[8 ] departmentDepartment of Movement, Human and Health Sciences , University of Rome Foro Italico , Rome, Italy

[9 ] departmentDepartment of Nutrition, Pitie-Salpetriere hospital (AP-HP) , Institute of Cardiometabolism and Nutrition (ICAN), University Pierre et Marie Curie-Paris6 , Paris, France

[10 ] Institute of Applied Health Research, School of Health and Life Sciences, Glasgow Caledonian University , Glasgow, UK

[11 ] Amsterdam School for Communication Research, University of Amsterdam , Amsterdam, Netherlands

Author notes

[Correspondence to ] Dr Jeroen Lakerveld; j.lakerveld@ 123456vumc.nl

Article

Publisher ID: bmjopen-2017-017489

DOI: 10.1136/bmjopen-2017-017489

PMC ID: 5665252

PubMed ID: 29061620

SO-VID: c1d5c83a-be67-4f18-a095-4dd34930f0a3

License:

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

History

Date received : 01 May 2017

Date revision received : 17 August 2017

Date accepted : 20 September 2017

Funding

Funded by: Research Foundation – Flanders;

Funded by: The Medical Research Council (MRC);

Funded by: Institut National de la Recherche Agronomique (INRA);

Funded by: Federal Ministry of Education and Research;

Funded by: Ministry of Education, University and Research;

Funded by: : The Netherlands Organisation for Health Research and Development (ZonMw);

Funded by: The Health Research Board (HRB);

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ScienceOpen disciplines: Medicine

Keywords: epidemiology,preventive medicine,public health

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ScienceOpen disciplines: Medicine

Keywords: epidemiology, preventive medicine, public health

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Identifying and sharing data for secondary data analysis of physical activity, sedentary behaviour and their determinants across the life course in Europe: general principles and an example from DEDIPAC

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Abstract

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Jiangsu Journal of Preventive Medicine

Most cited references 19

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

DataSHIELD: taking the analysis to the data, not the data to the analysis

A systematic review of determinants of sedentary behaviour in youth: a DEDIPAC-study

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