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Introduction The European population is rapidly ageing. In order to handle substantial future challenges in the healthcare system, we need to shift focus from treatment towards health promotion. The PreventIT project has adapted the Lifestyle-integrated Exercise (LiFE) programme and developed an intervention for healthy young older adults at risk of accelerated functional decline. The intervention targets balance, muscle strength and physical activity, and is delivered either via a smartphone application (enhanced LiFE, eLiFE) or by use of paper manuals (adapted LiFE, aLiFE)., Methods and analysis The PreventIT study is a multicentre, three-armed feasibility randomised controlled trial, comparing eLiFE and aLiFE against a control group that receives international guidelines of physical activity. It is performed in three European cities in Norway, Germany, and The Netherlands. The primary objective is to assess the feasibility and usability of the interventions, and to assess changes in daily life function as measured by the Late-Life Function and Disability Instrument scale and a physical behaviour complexity metric. Participants are assessed at baseline, after the 6 months intervention period and at 1 year after randomisation. Men and women between 61 and 70 years of age are randomly drawn from regional registries and respondents screened for risk of functional decline to recruit and randomise 180 participants (60 participants per study arm)., Ethics and dissemination Ethical approval was received at all three trial sites. Baseline results are intended to be published by late 2018, with final study findings expected in early 2019. Subgroup and further in-depth analyses will subsequently be published.

The emerging mHealth applications, incorporating wearable sensors, enables continuous monitoring of physical activity (PA). This study aimed at analyzing the relevance of a multivariate complexity metric in assessment of functional change in younger older adults. Thirty individuals (60&ndash, 70 years old) participated in a 4-week home-based exercise intervention. The Community Balance and Mobility Scale (CBMS) was used for clinical assessment of the participants&rsquo, functional balance and mobility performance pre- and post- intervention. Accelerometers worn on the low back were used to register PA of one week before and in the third week of the intervention. Changes in conventional univariate PA metrics (percentage of walking and sedentary time, step counts, mean cadence) and complexity were compared to the change as measured by the CBMS. Statistical analyses (21 participants) showed significant rank correlation between the change as measured by complexity and CBMS (&rho, = 0.47, p = 0.03). Smoothing the activity output improved the correlation (&rho, = 0.58, p = 0.01). In contrast, change in univariate PA metrics did not show correlations. These findings demonstrate the high potential of the complexity metric being useful and more sensitive than conventional PA metrics for assessing functional changes in younger older adults.

Background: Early identification of people at risk of functional decline is essential for delivering targeted preventive interventions. Objective: The aim of this study is to identify and predict trajectories of functional decline over 9 years in males and females aged 60–70 years. Methods: We included 403 community-dwelling participants from the InCHIANTI study and 395 from the LASA study aged 60–70 years at baseline, of whom the majority reported no functional decline at baseline (median 0, interquartile range 0–1). Participants were included if they reported data on ≥ 2 measurements of functional ability during a 9-year follow-up. Functional ability was scored with 6 self-reported items on activities of daily living. We performed latent class growth analysis to identify trajectories of functional decline and applied multinomial regression models to develop prediction models of identified trajectories. Analyses were stratified for sex. Results: Three distinct trajectories were identified: no/little decline (219 males, 241 females), intermediate decline (114 males, 158 females), and severe decline (36 males, 30 females). Higher gait speed showed decreased risk of functional limitations in males (intermediate limitations, odds ratio [OR] 0.74, 95% CI 0.57–0.97; severe limitations, OR 0.42, 95% CI 0.26–0.66). The final model in males further included the predictors fear of falling and alcohol intake (no/little decline, area under the receiver operating curve [AUC] 0.68, 95% CI 0.62–0.73; intermediate decline, AUC 0.63, 95% CI 0.56–0.69; severe decline, AUC 0.79, 95% CI 0.71–0.87). In females, higher gait speed showed a decreased risk of intermediate limitations (OR 0.51, 95% CI 0.38–0.68) and severe limitations (OR 0.18, 95% CI 0.07–0.44). Other predictors in females were age, living alone, economic satisfaction, balance, physical activity, BMI, and cardiovascular disease (no/little decline, AUC 0.80, 95% CI 0.75–0.85; intermediate decline, AUC 0.74, 95% CI 0.69–0.79; severe decline, AUC 0.95, 95% CI 0.91–0.99). Conclusion: Already in people aged 60–70 years, 3 distinct trajectories of functional decline were identified in these cohorts over a 9-year follow-up. Predictors of trajectories differed between males and females, except for gait speed. Identification of people at risk is the basis for targeting interventions. © 2017 The Author(s) Published by S. Karger AG, Basel. Th is article is licensed under the Creative Commons AttributionNonCommercial-NoDerivatives 4.0 International License (CC BYNC-ND) (http://www.karger.com/Services/OpenAccessLicense). Usage and distribution for commercial purposes as well as any distribution of modifi ed material requires written permission.