‘There is no single variable that can be used to describe health, and health cannot be measured directly’ . We aim to define - both conceptually and empirically - BioPsychoSocial (BPS) health function and related risks in the context of ageing, and to map it to specific health-related outcomes including falls, cognitive impairment, burden of longstanding diseases, and reliance on tertiary care. In so doing, we take two previously tested questionnaires [2,3,4,5] and carry out a secondary empirical evaluation to adapt and combine their items into a condensed scoring system for use in capturing BPS health risk and managing status. This work is conceived through dialogue with an interdisciplinary team (programmers, clinicians, government officials, social scientists and psychometricians) for the purposes of improving program implementation. It is based on a dynamic model of health functioning.
Specifically, we seek to better understand risk status of older people by measuring BPS health loads that weigh them down, so as to best intervene to help protect or use program levers that will buffer, or lift people, out of harm’s way as they age. We draw on a case detection pilot intervention in Singapore, which is part of the Community for Successful Ageing (ComSA)  initiative. ComSA consists of a two pronged, yet overarching, intervention which offers Community Development courses and activities for proactive Third agers  and Care Management for more vulnerable Fourth agers . By Third Agers we refer to those older people who are post-retirement and living the classically defined period between mostly having given up working life and onset of the Forth Age, where limiting health conditions and other adversities conflate to make independent life harder.
ComSA aims to help older people to maintain health for as long as possible, also helping them to build up reserves of resources and support, and to adapt to inevitable changes when they do come. This positioning of successful ageing, is outlined in the ComSA Program Framework, Additional file 1: Figure S1. and sits within a longstanding tradition of defining and striving for successful ageing to be a dynamic and evolving process, as elaborated below. Although the program implementation has followed a broad dichotomising of service platforms, targeting largely more proactive health maintenance programming to those already managing well, and adaptive services to those who are more vulnerable, health experiences are not always so neatly divided. Therefore, the ComSA delivery system also allows for some shifting between services and activities across these two platforms, as appropriate.
Our measurement approach, using the BPS Risk Screener, is also embedded within the ComSA program framework. The measure helps to allocate programme participants to services and to meaningfully tailor interventions using an evidenced based delivery system.
To explicate this approach, we present its theoretical and empirical underpinning in three parts. First, we situate this work within the context of literature on healthy and successful ageing. Building on this, we define the B, P, and S domains, and how they can combine to make a person vulnerable at older ages, and position our approach in relation to frailty and related measures. Secondly, we operationalize the three domains in term of questionnaire items, as well as show how we will capture their interrelationships using a dynamic scoring system. We then validate the BPS Risk Screener against health-related outcomes. Finally, we discuss our findings in relation to existing instruments for capturing health and quality of life at older ages.
Recent conceptualizations of successful ageing increasingly move away from defining it as simply living longer while staving off disease and biological decline [9,10,11]. A systematic review of the literature on successful ageing from 1987 to 2013  identified 16 out of 67 articles as arguing for a more holistic definition for successful ageing, and for these to include psychological and social domains. For example, they cite Young et al.  definition of successful ageing as the ability to use physical and social adaptive strategies to ‘achieve a sense of well-being, high self-assessed quality of life, and a personal sense of fulfilment, even in the presence of disability and illness’. This idea of adapting and compensating for losses as we age, earlier described by Baltes & Baltes , similarly underlies Kahana and Kahana’s proactivity model [14, 15].
The proactivity model emphasizes having and using social, financial and psychological resources, to adapt to stressors in old age and maintain quality of life . These ideas reflect the notion of active ageing advanced by the WHO [16, 17]. This is defined as ‘the process of optimizing opportunities for health, participation and security in order to enhance quality of life as people age’, which emphasizes actions across multiple sectors, with the goal of keeping older people in their communities, and contributing to building social capital . Put together, this body of literature echo’s Antonovskey’s longstanding conception of salutogenesis, or health as more than simply the absence of disease, but a dynamic process whereby psychosocial asset can promote recovery, or sustain physical health ; a view also supported by George Engle in his classic positioning of the Biopsychosocial model .
A more critical stance on these concepts also needs to acknowledge the unequal access to resources, and marginalization of some older adults, across differing sociocultural contexts [20,21,22]. Capturing risks through a comprehensive BPS risk screener (identifying who is vulnerable, as much as how to capture vulnerability) can render not only needs but lived inequalities of older people more transparent for intervention, policy and planning. Our approach draws upon this history of theory and research to ultimately operationalize the dynamic nature of ageing and health. It acknowledges that the notion of a disease-free old age is unrealistic for many individuals [8, 23], and that access to resources and the ‘starting points’ for intervention are unique and will differ for each person.
Defining BPS health and related risks at older ages
We describe BPS health after the World Health Organisations (WHO) [24, 25], as: ‘a set of dynamic features [emphasis our own] and dimensions that can be measured’. This definition also accounts explicitly for homeostasis, meaning a system or person’s ability to ‘recalibrate’ or ‘bounce back’, in the face of disruptions. As such, following Huber et al. , health is defined as follows:
Biological health (B): ‘In the physical domain, a healthy organism is capable of ‘allostasis’—the maintenance of physiological homoeostasis’.
Psychological health (P): ‘In the mental domain [factors] that contributes to a successful capacity to cope, recover from strong psychological stresses.
Social health (S): ‘In the social domain, people’s capacity to fulfil their potential and obligations’; ‘to participate in social activities’.
Thus, risk is conceived as: the presence of Bio-functional degeneration that can result in either cognitive (dementia), physical (illness) or impairments (limiting activities of daily living); as well as poor Psycho-emotional function and coping resulting in a lack of capacity to recover from strong psychological stresses; and inadequate Socio-interpersonal networks in the form of quantity and quality of relationships, lack of support and empowerment, and capacity to live independently. Risks in each BPS domain are both distinct, as well as inter-related as they can add up, or offset one another within and across the domains. This relationship is further elaborated in relation to the Load-Levers-Lift process, and used to operationalize the scoring system of the BPS questionnaire items.
Vulnerability is explicitly distinguished from frailty. Vulnerability, a term transposed from developmental studies  can ensue in an older person from any unique BPS combination. It is simply, and broadly conceived as an older person’s risk of being unable to manage. For example, an older person may have limiting long-standing illness but many psycho-social buffers, or strong social support and emotional coping. On the other hand, an older person who is physically robust, may have many P and S problems such as social isolation or depression. According to our definition of vulnerability, an older person who is physically unwell but otherwise robust will not be vulnerable. Conversely, they can be vulnerable without being physically unwell.
Therefore, our concept of vulnerability differs from frailty, which has primarily been associated with bio-functional states, such as slow walking speed, tiredness, weakness and decreased physical activity , and has thus been termed a geriatric syndrome . Some frailty instruments have been developed to capture B and some P and S item, and to be inclusive and multifaceted [29, 30] such as the Tilburg Frailty Indicator or TIF . Nevertheless, recent systematic reviews of frailty instruments [32, 33] show frailty tools are still mainly positioned to capture chronological age-related bio-medical deteriorations. For instance, the Physical Frailty Phenotype instrument  is the most popular instrument catalogued in a 2016 review . All identified frailty instruments indexed health problems at older ages or measured a latent concept frailty, and none of them sought to capture dynamic effects.
The Loads-Levers-Lifts process (Additional file 2: Figure S2) describes a ‘see-saw’ effect in which poor health in the various BPS domains can be conceptualized as loads, making an older person vulnerable. While fewer loads in each BPS domain will protect the person, and provide a better starting point. As loads accumulate across domains, adaptive capability of the older person will start to be depleted. We define adaptive capability as having the resources and ability to maintain and overcome health-related deficits. This will help strengthen a person’s basic intrinsic capacity  in the face of inevitable changes at older ages. This phenomenon can also be likened to filling a protective basket with a constellation of lifts, as depicted in Additional file 2: Figure S2. The heavier the loads dragging people down to start with, the more the basket needs filling to help people manage successfully into and during the Fourth Age.
Levers are targeted interventions that help to fill these baskets, and keep loads as light as possible, thus building adaptive capability. Our proposed model follows the resilience research tradition [23, 26, 35,36,37,38,39] which clearly positions successful ageing as a dynamic and modifiable process. Resilience is defined as ‘doing well despite adversity’ [37,38,39] and will be achieved when loads are meaningfully offset. Resilience is an important concept in the approach that we propose, with a long history as a research tradition . Resilience in developmental studies can be described as an accidental discovery, that came about when researchers studying children growing up in very vulnerable conditions, were surprised to find a certain proportion of them consistently, and across studies, surpassed all expectations.
This discovery lead to the quest to identify exactly how, and why these children were special. It has since become evident that this ‘ordinary magic’  will be reproduced at any age, across the whole life course, and in the face of varying adversities. Studies of resilience at older ages for example demonstrate how resilient older people can be identified [23, 37,38,39] and their ageing experiences distinguished from more vulnerable ones [36, 37]. Our research takes the stance that what underscores the resilience phenomenon is not so much an invisible constellation of protective traits, but being able to leverage enough lift to tip back the balance in an individuals’ favour. The starting point to rendering these processes explicit will be to accurately capture individual loads, and hence this construct, is the focus of the current study.
Measuring ‘loads’: A theoretically derived scoring system
The BPS Risk Screener ranges capturing scores on those who are managing or ‘doing well’, to those that are at risk or living with ‘overwhelming problem’, in other words detecting the range or ‘weight’ of health loads. This range is captured in a unique scoring system that forthcoming analyses validates. The scoring approach was constructed iteratively from our theory base, pilot administration in the community, and statistical scoping and sensitivity analysis to find the best way to simply yet meaningful capture the BPS interrelations. Additional file 3: Figure S3a-b provides a schematic to explain the scoring structure.
We derive ‘some’ vs. ‘a lot’ of health problems benchmarks from population norms (statistical averages) within the individual B, P, and S domains to determine what we call managing counts, see 3a. We then sum managing counts across individual domains into an overall managing score, see 3b, to capture the BPS risk categories. The term ‘managing’ is chosen to report the scores because it was judged more sensitive than the term ‘risk’ score when sharing results with older people themselves.
The objectives of the forthcoming empirical validation of the Risk Screener are threefold:
To identify the specific BPS factors and related items that map to our theoretically defined domains;
To examine individual B, P, and S predictors and additive BPS effects in relation to our theoretical stance that health is multi-faceted and self-reported health would therefore be significantly associated with all three domains;
To further examine associations of our managing/risk scores with: falls, cognitive impairment, burden of longstanding diseases, and reliance on tertiary care outcomes.