Although populations around the world are rapidly ageing, evidence that increasing longevity is being accompanied by an extended period of good health is scarce. A coherent and focused public health response that spans multiple sectors and stakeholders is urgently needed. To guide this global response, WHO has released the first World report on ageing and health, reviewing current knowledge and gaps and providing a public health framework for action. The report is built around a redefinition of healthy ageing that centres on the notion of functional ability: the combination of the intrinsic capacity of the individual, relevant environmental characteristics, and the interactions between the individual and these characteristics. This Health Policy highlights key findings and recommendations from the report.

BackgroundSarcopenia is increasingly recognized as a correlate of ageing and is associated with increased likelihood of adverse outcomes including falls, fractures, frailty and mortality. Several tools have been recommended to assess muscle mass, muscle strength and physical performance in clinical trials. Whilst these tools have proven to be accurate and reliable in investigational settings, many are not easily applied to daily practice.MethodsThis paper is based on literature reviews performed by members of the European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis (ESCEO) working group on frailty and sarcopenia. Face-to-face meetings were afterwards organized for the whole group to make amendments and discuss further recommendations.ResultsThis paper proposes some user-friendly and inexpensive methods that can be used to assess sarcopenia in real-life settings. Healthcare providers, particularly in primary care, should consider an assessment of sarcopenia in individuals at increased risk; suggested tools for assessing risk include the Red Flag Method, the SARC-F questionnaire, the SMI method or different prediction equations. Management of sarcopenia should primarily be patient centered and involve the combination of both resistance and endurance based activity programmes with or without dietary interventions. Development of a number of pharmacological interventions is also in progress.ConclusionsAssessment of sarcopenia in individuals with risk factors, symptoms and/or conditions exposing them to the risk of disability will become particularly important in the near future.

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Exploratory graph analysis (EGA) is a new technique that was recently proposed within the framework of network psychometrics to estimate the number of factors underlying multivariate data. Unlike other methods, EGA produces a visual guide-network plot-that not only indicates the number of dimensions to retain, but also which items cluster together and their level of association. Although previous studies have found EGA to be superior to traditional methods, they are limited in the conditions considered. These issues are here addressed through an extensive simulation study that incorporates a wide range of plausible structures that may be found in practice, including continuous and dichotomous data, and unidimensional and multidimensional structures. Additionally, two new EGA techniques are presented, one that extends EGA to also deal with unidimensional structures, and the other based on the triangulated maximally filtered graph approach (EGAtmfg). Both EGA techniques are compared with five widely used factor analytic techniques. Overall, EGA and EGAtmfg are found to perform as well as the most accurate traditional method, parallel analysis, and to produce the best large-sample properties of all the methods evaluated. To facilitate the use and application of EGA, we present a straightforward R tutorial on how to apply and interpret EGA, using scores from a well-known psychological instrument: the Marlowe-Crowne Social Desirability Scale.

Healthy ageing can be defined as "the process of developing and maintaining the functional ability that enables wellbeing in older age". Functional ability (i.e., the health-related attributes that enable people to be and to do what they have reason to value) is determined by intrinsic capacity (i.e., the composite of all the physical and mental capacities of an individual), the environment (i.e., all the factors in the extrinsic world that form the context of an individual's life), and the interactions between the two. This innovative model recently proposed by the World Health Organization has the potential to substantially modify the way in which clinical practice is currently conducted, shifting from disease-centered toward function-centered paradigms. By overcoming the multiple limitations affecting the construct of disease, this novel framework may allow the worldwide dissemination of a more proactive and function-based approach toward achieving optimal health status. In order to facilitate the translation of the current theoretical model into practice, it is important to identify the inner nature of its constituting constructs. In this article, we consider intrinsic capacity. Using the International Classification of Functioning, Disability and Health (ICF) framework as background and taking into account available evidence, five domains (i.e., locomotion, vitality, cognition, psychological, sensory) are identified as pivotal for capturing the individual's intrinsic capacity (and therefore also reserves) and, through this, pave the way for its objective measurement.

In most countries, a fundamental shift in the focus of clinical care for older people is needed. Instead of trying to manage numerous diseases and symptoms in a disjointed fashion, the emphasis should be on interventions that optimize older people’s physical and mental capacities over their life course and that enable them to do the things they value. This, in turn, requires a change in the way services are organized: there should be more integration within the health system and between health and social services. Existing organizational structures do not have to merge; rather, a wide array of service providers must work together in a more coordinated fashion. The evidence suggests that integrated health and social care for older people contributes to better health outcomes at a cost equivalent to usual care, thereby giving a better return on investment than more familiar ways of working. Moreover, older people can participate in, and contribute to, society for longer. Integration at the level of clinical care is especially important: older people should undergo comprehensive assessments with the goal of optimizing functional ability and care plans should be shared among all providers. At the health system level, integrated care requires: (i) supportive policy, plans and regulatory frameworks; (ii) workforce development; (iii) investment in information and communication technologies; and (iv) the use of pooled budgets, bundled payments and contractual incentives. However, action can be taken at all levels of health care from front-line providers through to senior leaders – everyone has a role to play.

ObjectiveThe World Health Organization (WHO) recently proposed an Integrated Care for Older People approach to guide health systems and services in better supporting functional ability of older people. A knowledge gap remains in the key elements of integrated care approaches used in health and social care delivery systems for older populations. The objective of this review was to identify and describe the key elements of integrated care models for elderly people reported in the literature.DesignReview of reviews using a systematic search method.MethodsA systematic search was performed in MEDLINE and the Cochrane database in June 2017. Reviews of interventions aimed at care integration at the clinical (micro), organisational/service (meso) or health system (macro) levels for people aged ≥60 years were included. Non-Cochrane reviews published before 2015 were excluded. Reviews were assessed for quality using the Assessment of Multiple Systematic Reviews (AMSTAR) 1 tool.ResultsFifteen reviews (11 systematic reviews, of which six were Cochrane reviews) were included, representing 219 primary studies. Three reviews (20%) included only randomised controlled trials (RCT), while 10 reviews (65%) included both RCTs and non-RCTs. The region where the largest number of primary studies originated was North America (n=89, 47.6%), followed by Europe (n=60, 32.1%) and Oceania (n=31, 16.6%). Eleven (73%) reviews focused on clinical ‘micro’ and organisational ‘meso’ care integration strategies. The most commonly reported elements of integrated care models were multidisciplinary teams, comprehensive assessment and case management. Nurses, physiotherapists, general practitioners and social workers were the most commonly reported service providers. Methodological quality was variable (AMSTAR scores: 1–11). Seven (47%) reviews were scored as high quality (AMSTAR score ≥8).ConclusionEvidence of elements of integrated care for older people focuses particularly on micro clinical care integration processes, while there is a relative lack of information regarding the meso organisational and macro system-level care integration strategies.

The accurate identification of the content and number of latent factors underlying multivariate data is an important endeavor in many areas of Psychology and related fields. Recently, a new dimensionality assessment technique based on network psychometrics was proposed (Exploratory Graph Analysis, EGA), but a measure to check the fit of the dimensionality structure to the data estimated via EGA is still lacking. Although traditional factor-analytic fit measures are widespread, recent research has identified limitations for their effectiveness in categorical variables. Here, we propose three new fit measures (termed entropy fit indices) that combines information theory, quantum information theory and structural analysis: Entropy Fit Index (EFI), EFI with Von Neumman Entropy (EFI.vn) and Total EFI.vn (TEFI.vn). The first can be estimated in complete datasets using Shannon entropy, while EFI.vn and TEFI.vn can be estimated in correlation matrices using quantum information metrics. We show, through several simulations, that TEFI.vn, EFI.vn and EFI are as accurate or more accurate than traditional fit measures when identifying the number of simulated latent factors. However, in conditions where more factors are extracted than the number of factors simulated, only TEFI.vn presents a very high accuracy. In addition, we provide an applied example that demonstrates how the new fit measures can be used with a real-world dataset, using exploratory graph analysis.