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      The impact of physical activity on healthy ageing trajectories: evidence from eight cohort studies

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          Abstract

          Background

          Research has suggested the positive impact of physical activity on health and wellbeing in older age, yet few studies have investigated the associations between physical activity and heterogeneous trajectories of healthy ageing. We aimed to identify how physical activity can influence healthy ageing trajectories using a harmonised dataset of eight ageing cohorts across the world.

          Methods

          Based on a harmonised dataset of eight ageing cohorts in Australia, USA, Mexico, Japan, South Korea, and Europe, comprising 130,521 older adults ( M age = 62.81, SD age = 10.06) followed-up up to 10 years ( M follow-up = 5.47, SD follow-up = 3.22) , we employed growth mixture modelling to identify latent classes of people with different trajectories of healthy ageing scores, which incorporated 41 items of health and functioning. Multinomial logistic regression modelling was used to investigate the associations between physical activity and different types of trajectories adjusting for sociodemographic characteristics and other lifestyle behaviours.

          Results

          Three latent classes of healthy ageing trajectories were identified: two with stable trajectories with high (71.4%) or low (25.2%) starting points and one with a high starting point but a fast decline over time (3.4%). Engagement in any level of physical activity was associated with decreased odds of being in the low stable (OR: 0.18; 95% CI: 0.17, 0.19) and fast decline trajectories groups (OR: 0.44; 95% CI: 0.39, 0.50) compared to the high stable trajectory group. These results were replicated with alternative physical activity operationalisations, as well as in sensitivity analyses using reduced samples.

          Conclusions

          Our findings suggest a positive impact of physical activity on healthy ageing, attenuating declines in health and functioning. Physical activity promotion should be a key focus of healthy ageing policies to prevent disability and fast deterioration in health.

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          Most cited references39

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          Frailty in elderly people

          Frailty is the most problematic expression of population ageing. It is a state of vulnerability to poor resolution of homoeostasis after a stressor event and is a consequence of cumulative decline in many physiological systems during a lifetime. This cumulative decline depletes homoeostatic reserves until minor stressor events trigger disproportionate changes in health status. In landmark studies, investigators have developed valid models of frailty and these models have allowed epidemiological investigations that show the association between frailty and adverse health outcomes. We need to develop more efficient methods to detect frailty and measure its severity in routine clinical practice, especially methods that are useful for primary care. Such progress would greatly inform the appropriate selection of elderly people for invasive procedures or drug treatments and would be the basis for a shift in the care of frail elderly people towards more appropriate goal-directed care. Copyright © 2013 Elsevier Ltd. All rights reserved.
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            Deciding on the Number of Classes in Latent Class Analysis and Growth Mixture Modeling: A Monte Carlo Simulation Study

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                Author and article information

                Contributors
                dario.moreno@kcl.ac.uk
                Journal
                Int J Behav Nutr Phys Act
                Int J Behav Nutr Phys Act
                The International Journal of Behavioral Nutrition and Physical Activity
                BioMed Central (London )
                1479-5868
                16 July 2020
                16 July 2020
                2020
                : 17
                : 92
                Affiliations
                [1 ]GRID grid.13097.3c, ISNI 0000 0001 2322 6764, Department of Health Service and Population Research, , King’s College London, Institute of Psychiatry, Psychology and Neuroscience, David Goldberg Centre, ; De Crespigny Park, London, SE5 8AF UK
                [2 ]GRID grid.8991.9, ISNI 0000 0004 0425 469X, Department of Infectious Disease Epidemiology, , London School of Hygiene & Tropical Medicine, Faculty of Epidemiology and Population Health, ; London, UK
                [3 ]GRID grid.428876.7, Parc Sanitari Sant Joan de Déu, , Universitat de Barcelona. Fundació Sant Joan de Déu, ; Dr Antoni Pujades, 42, 08830, Sant Boi de Llobregat, Barcelona, Spain
                [4 ]GRID grid.469673.9, Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, ; Madrid, Spain
                [5 ]GRID grid.15823.3d, ISNI 0000 0004 0622 2843, Department of Nutrition and Dietetics, , School of Health Science and Education, Harokopio University, ; Athens, Greece
                Author information
                http://orcid.org/0000-0003-0459-657X
                Article
                995
                10.1186/s12966-020-00995-8
                7364650
                32677960
                4bb2b79c-ca6f-43d4-999e-baeef80a8bed
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.

                History
                : 5 March 2020
                : 7 July 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100007601, Horizon 2020;
                Award ID: 635316
                Categories
                Research
                Custom metadata
                © The Author(s) 2020

                Nutrition & Dietetics
                growth mixture modelling,lifestyle behaviours,health metric,data harmonisation,physical activity

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