Exploring frailty, mental health and related outcomes: a multi-cultural population-based approach to ageing.

We are facing an unparalleled change in demographics, where people are increasingly living longer. This phenomenon is occurring across the whole globe, but at a different pace. Rich countries have experienced a steadier increase in the number of older adults, whereas low and middle-income countries are facing a much more rapid transition.

Frailty is closely linked to older age. Although the word 'frail' has become part of our day-to-day vocabulary, geriatricians and the wider medical community have seen far less agreement as to what constitutes a frailty syndrome. The past two decades have seen remarkable advances in understanding this condition, with a number of definitions been put forward. Having a solid and appropriate definition of frailty is extremely important, as without such definition most clinicians would fall back on instinct and experience to identify frail patients. Although there has been considerable progress in the understanding of this condition, most of the work has been carried out in high-income countries and has been mainly driven by clinical insights. It is therefore not known whether the criteria that are currently used in those settings could be used in low and middle-income countries.

In this project I aim to investigate whether the current definitions of frailty could be applied to diverse settings, including developing countries, and whether these definitions are good at predicting a range of outcomes. These outcomes include death, illness, disability, cognitive decline and usage of health care. A significant part of the research will focus on the contribution of common mental disorders, such as anxiety and depression, to frailty. The study of anxiety and depression in later life has been relatively neglected, because of an emphasis on acute psychiatric disorders in younger life and the dementias in older age. However these conditions are extremely common in older age and have been associated with higher level of disability, hospitalisation, and lower quality of life. More treatment and research in those conditions should be made a national priority.

The research will be novel using a comprehensive and integrative approach in respect to cognitive, physical and psychological age-related changes, and using cutting-edge statistical analytical procedures. This project will also be using data from three large population-based studies carried out in diverse settings. One was carried out across a number of low and middle-income countries in Latin America and Asia. The other two were conducted in the Netherlands and Scotland. The findings from this research will help in developing tools that may help clinicians in predicting the course of illness and its treatment, but also policy-makers and commissioners in planning health care facilities and prioritise resources.

There is considerable debate on the definition of frailty, a syndrome that is strongly associated with age and that is often associated with an increased risk of poor outcomes. There is very little evidence that the construct and predictive validity of the different definitions of frailty apply to low and middle-income countries, places where the demographic transition is occurring most rapidly. Other conditions that have often been neglected in the epidemiological literature of those settings are Common Mental Disorders (CMD), which criteria partially overlap with those of frailty. A main limitation in the frailty field is that early operationalisations have been mainly driven by clinical insights, with rather simplistic theoretical underpinnings, and no empirical support other than for predictive validity. Using data from a large international and multi-cultural population-based survey, the 10/66, I plan to investigate the construct and predictive validity of current definitions of frailty, particularly focusing on the contribution of CMD to frailty and to identify sub-phenotypes that are most closely aligned to cognitive and physical frailty. Replication cohorts that I am also planning to use to validate and compare the findings are the Longitudinal Aging Study Amsterdam (LASA) and the Lothian Birth Cohorts. The approach is integrative and comprehensive with respect to age-related changes in cognitive, physical and psychological domains. It also uses sophisticated statistical analytical procedures to explore the construct validity of frailty, and the relationship between specific domains of frailty and different policy relevant outcomes. Risk predictions models to aid clinicians and policy-makers will also be built at the end of the project. This project will provide strong evidence in understanding the impact of frailty and common mental disorders on ageing populations and to identify potential pathways and modifiable factors for intervention.

This project aims to have an impact on on clinicians, policy makers and older adults living in the community, and not solely on the academic community.

1) Research community: a better understanding of the construct and predictive validity of frailty across cultures will address one of the main limitations of the research in this field so far, which is the over-reliance on data from high-income populations. The findings from this project will partly tackle the large bias that has affected research on frailty.

2) Clinicians: an aim of the project is to create risk prediction models based on frailty status to understand likely outcomes that individuals may face. This is based on specific predictor profiles. Clinicians could easily adopt these tools to supplement decision-making in their day-to-day practice.

3) Policy makers will benefit from these models too. In fact, they could use them to estimate what type of services need to be introduced in a population to cope with certain conditions. Another direct implication of this project that is relevant to policy makers is the production of prevalence and incidence estimates of frailty in each country, which can then be used to decide how many services and personnel are needed to deal efficiently with the issue.

4) In the longer term, older adults living in the community will also see the benefits of this research. The identification of potential modifiable risk factors associated with frailty, anxiety and depression will undoubtedly lead to new interventions aimed at reducing the burden and the outcomes associated with these conditions. People at high risk for frailty may also be identified at an earlier stage by clinicians using the prediction models. This may lead to better management of their conditions and ultimately longer healthy (free of morbidity) life expectancy.

The benefits to the research community could be seen directly in the first two years of the fellowship, when the first results from the research are expected to be published. The risk prediction models will be designed in the last year of the fellowship, and I believe that their impact on clinical care could be seen shortly after a period of proper validation.