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      MINDMAP: establishing an integrated database infrastructure for research in ageing, mental well-being, and the urban environment


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          Urbanization and ageing have important implications for public mental health and well-being. Cities pose major challenges for older citizens, but also offer opportunities to develop, test, and implement policies, services, infrastructure, and interventions that promote mental well-being. The MINDMAP project aims to identify the opportunities and challenges posed by urban environmental characteristics for the promotion and management of mental well-being and cognitive function of older individuals.


          MINDMAP aims to achieve its research objectives by bringing together longitudinal studies from 11 countries covering over 35 cities linked to databases of area-level environmental exposures and social and urban policy indicators. The infrastructure supporting integration of this data will allow multiple MINDMAP investigators to safely and remotely co-analyse individual-level and area-level data.

          Individual-level data is derived from baseline and follow-up measurements of ten participating cohort studies and provides information on mental well-being outcomes, sociodemographic variables, health behaviour characteristics, social factors, measures of frailty, physical function indicators, and chronic conditions, as well as blood derived clinical biochemistry-based biomarkers and genetic biomarkers. Area-level information on physical environment characteristics (e.g. green spaces, transportation), socioeconomic and sociodemographic characteristics (e.g. neighbourhood income, residential segregation, residential density), and social environment characteristics (e.g. social cohesion, criminality) and national and urban social policies is derived from publically available sources such as geoportals and administrative databases.

          The linkage, harmonization, and analysis of data from different sources are being carried out using piloted tools to optimize the validity of the research results and transparency of the methodology.


          MINDMAP is a novel research collaboration that is combining population-based cohort data with publicly available datasets not typically used for ageing and mental well-being research. Integration of various data sources and observational units into a single platform will help to explain the differences in ageing-related mental and cognitive disorders both within as well as between cities in Europe, the US, Canada, and Russia and to assess the causal pathways and interactions between the urban environment and the individual determinants of mental well-being and cognitive ageing in older adults.

          Electronic supplementary material

          The online version of this article (10.1186/s12889-018-5031-7) contains supplementary material, which is available to authorized users.

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          Most cited references32

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          Global burden of disease attributable to mental and substance use disorders: findings from the Global Burden of Disease Study 2010

          The Lancet, 382(9904), 1575-1586
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            Mostly Harmless Econometrics

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              Cohort Profile: the HUNT Study, Norway.

              The HUNT Study includes large total population-based cohorts from the 1980ies, covering 125 000 Norwegian participants; HUNT1 (1984-86), HUNT2 (1995-97) and HUNT3 (2006-08). The study was primarily set up to address arterial hypertension, diabetes, screening of tuberculosis, and quality of life. However, the scope has expanded over time. In the latest survey a state of the art biobank was established, with availability of biomaterial for decades ahead. The three population based surveys now contribute to important knowledge regarding health related lifestyle, prevalence and incidence of somatic and mental illness and disease, health determinants, and associations between disease phenotypes and genotypes. Every citizen of Nord-Trøndelag County in Norway being 20 years or older, have been invited to all the surveys for adults. Participants may be linked in families and followed up longitudinally between the surveys and in several national health- and other registers covering the total population. The HUNT Study includes data from questionnaires, interviews, clinical measurements and biological samples (blood and urine). The questionnaires included questions on socioeconomic conditions, health related behaviours, symptoms, illnesses and diseases. Data from the HUNT Study are available for researchers who satisfy some basic requirements (www.ntnu.edu/hunt), whether affiliated in Norway or abroad.

                Author and article information

                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                19 January 2018
                19 January 2018
                : 18
                : 158
                [1 ]ISNI 000000040459992X, GRID grid.5645.2, Department of Public Health, , Erasmus MC, University Medical Center Rotterdam, ; P.O. Box 2040, 3000 CA Rotterdam, The Netherlands
                [2 ]ISNI 0000 0000 9064 4811, GRID grid.63984.30, Research Institute of the McGill University Health Centre, ; Montreal, Canada
                [3 ]ISNI 0000 0004 0587 0574, GRID grid.416786.a, Swiss Tropical and Public Health Institute, ; Basel, Switzerland
                [4 ]ISNI 0000 0004 1937 0642, GRID grid.6612.3, University of Basel, ; Basel, Switzerland
                [5 ]Department of Global Health and Social Medicine, King’s College London, London, UK
                [6 ]ISNI 0000000121901201, GRID grid.83440.3b, Department of Epidemiology and Public Health, ; University College London, London, UK
                [7 ]ISNI 0000000121866389, GRID grid.7429.8, Inserm, UMR_S 1136, Pierre Louis Institute of Epidemiology and Public Health, ; Paris, France
                [8 ]ISNI 0000 0001 1955 3500, GRID grid.5805.8, Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1136, Pierre Louis Institute of Epidemiology and Public Health, ; Paris, France
                [9 ]Epidemiology Unit, ASL TO3, Piedmont Region, Grugliasco, Turin, Italy
                [10 ]ISNI 0000 0001 2336 6580, GRID grid.7605.4, Department of Clinical and Biological Science, , University of Turin, ; Turin, Italy
                [11 ]ISNI 0000 0001 2287 2617, GRID grid.9026.d, Geriatrics Centre, Scientific Department at the University of Hamburg, ; Hamburg, Germany
                [12 ]Albertinen-Haus, Hamburg, Germany
                [13 ]ISNI 0000 0001 2181 3113, GRID grid.166341.7, Drexel University Dornsife School of Public Health, ; Philadelphia, PA USA
                [14 ]ISNI 0000 0001 0686 3219, GRID grid.466632.3, Department of Epidemiology and Biostatistics, , EMGO+ Institute for Health and Care Research, VU University Medical Center, ; Amsterdam, The Netherlands
                [15 ]ISNI 0000 0001 0789 5319, GRID grid.13063.37, Department of Social Policy, , London School of Economics and Political Science, ; London, UK
                [16 ]ISNI 0000 0001 1516 2393, GRID grid.5947.f, HUNT Research Centre, Department of Public Health and General Practice, , Faculty of Medicine, Norwegian University of Science and Technology (NTNU), ; Levanger, Norway
                [17 ]ISNI 0000 0004 0627 3093, GRID grid.414625.0, Levanger Hospital, Nord-Trøndelag Hospital Trust, ; Levanger, Norway
                [18 ]ISNI 0000 0004 0410 2071, GRID grid.7737.4, Population Research Unit, Department of Social Research, , University of Helsinki, ; Helsinki, Finland
                [19 ]ISNI 0000 0004 1936 8227, GRID grid.25073.33, Canadian Longitudinal Study on Aging, Department of Health Research Methods, Evidence and Impact, , McMaster University, ; Hamilton, Canada
                [20 ]ISNI 0000000120346234, GRID grid.5477.1, Department of Human Geography and Spatial Planning, , Utrecht University, ; Utrecht, The Netherlands
                © The Author(s). 2018

                Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                : 30 September 2017
                : 4 January 2018
                Funded by: Horizon 2020 HORIZON 2020 research and innovation action
                Award ID: 667661
                Award Recipient :
                Study Protocol
                Custom metadata
                © The Author(s) 2018

                Public health
                ageing,mental well-being,urban health,database,data integration,cohort studies
                Public health
                ageing, mental well-being, urban health, database, data integration, cohort studies


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