Lifelong Health Research Theme, University of Surrey – Written evidence (INQ0017)
Comments in response to individual questions as follows:
There is much yet to learn in order to understand the biological processes of ageing. Progress in animal models has not been sufficiently translated into humans. Our health-related research is so often focussed on individual diseases, yet there are underlying biological failures which can predispose to multiple different morbidities. Complexity of the biological mechanisms behind ageing means that often we need to look at different areas of biology holistically. There are areas of biology that can still surprise us with respect to novel dependencies, for example a recent paper has linked obesity and poor glucose control with the presence of a particular type of immune cell in the gut. We have been recently encouraged to see that charities for arthritis, MS and diabetes have joined forces, with the help of the British Society for Immunology, the Wellcome Trust and the MRC, to form “Connect Immune” to fund research on underlying biological causes common to autoimmune diseases. We would like to see more of such initiatives and believe that areas of biology that have broad-reaching effects and therefore have a lot of potential for impact with respect to amelioration of age-related ill health, are:
For further information, a good concise overview in answer to this question can be found in the 2018 Nature review by Professor Dame Linda Partridge
A major barrier to assessing the efficacy of potential treatments is the lack of tractable and efficient biomarkers to measure “biological age”. Without such biomarkers it is difficult to measure the effects of any intervention. The University of Surrey collaborated on a recent study identifying metabolic biomarkers of ageing, these may be more tractable if our biosensor technology can be integrated here.
There are some promising molecules already in use for single diseases that could be used for a more general health improvement, including mTOR inhibitors such as rapamycin and other rapalogues, senolytics to remove senescent cells, metformin to modify glucose homeostasis. However, picking targets central to multiple cellular pathways has the disadvantage of potential side effects so dose and balance of these would need to be carefully researched.
Some aspects of age-related frailty may be more associated with physical “wear and tear” than with biological mechanisms. Musculoskeletal disorders are an example where early life damage to joints can translate into osteoarthritic (OA) complaints in later life. Musculoskeletal disorders are the UK’s second most prevalent cause of disability, affecting 1 in 2 of the over 65’s, and lead to chronic pain and restriction of activities of daily living. Once mobility becomes restricted then other health conditions associated with lack of activity, such as cardiovascular disease, susceptibility to falls etc will follow. Despite this burden, and perhaps because the conditions tend to be chronic and insidious, there is a paucity of research on treatments such as cartilage regeneration which could have far reaching impact throughout life.
We still do not fully understand the demographic differences in HLW. Not all inequality differences will be lifestyle choices. For example, fuel poverty has been identified as a serious issue more prevalent in UK and Ireland than in the rest of Europe – as assessed by excess winter deaths. In some respects, it could be easier to change economic disparities within a community than to change social behaviours.
In health care, technologies for remote monitoring and managing of health-related symptoms and events (e.g. UTIs) have enormous promise (e.g. the TIHM for Dementia project). Based on machine learning and with potential for integrating different technological devices, systems can provide a degree of personalisation within a technological solution, being modifiable to adapt to changing circumstances (e.g. disease progression). Biosensor technology is improving and has the potential to save time and enable earlier diagnoses, and our experts in materials chemistry can produce efficient wearable sensors. Responsible and secure use of AI and big data collation in medical applications will transform diagnostic efficiencies and enable more personalised treatments. The University of Surrey has substantial expertise in such health technologies. They will also transform the way we carry out research. For example, we can closely monitor local environments, with respect to air quality, temperature, humidity, light and measure appropriate concomitant biomarkers of health in order to identify what aspects of the local environment could best be changed to improve healthy living.
Older adults are particularly enthusiastic to embrace technologies that enhance self-care and independence rather than dependence. Personal monitoring to identify health issues before they become severe may be useful (e.g. early detection of UTIs may reduce the incidence of confusion and falls). As a note of caution, and in partial answer to your question 7, we do see that older people are often lonely and we need to be careful that technology does not exacerbate this situation. Tractable and acceptable technologies to combat loneliness will require co-design with cohorts of older people.
Technology needs to support the work of healthcare professionals and not add to it. It also needs to be compatible with existing systems. Design of technology needs to be done in conjunction with older people, and with carers of older people, to ensure that the innovators clearly understand the needs of older people. We need to be inclusive, with a diversity of older people in the co-design to ensure that disparities are not exacerbated by designing only for the section of older people more amenable to technology. Implementation of the technologies needs adequate time to learn and try them out. As mentioned above, the loss of human contact is potentially a major drawback of facilitating technologies and research on the Alexa/Google-type interfaces in this regard is required.
Establishing what would count as suitable evidence on which to commission a technology is important. Studies employing multidisciplinary interactions between user groups, technology developers, primary and secondary health professionals, care workers, policy influencers etc are required to properly understand the potential of a health technology. Commissioning of a technology that measures aspects of health, in a care setting in order to prevent and manage health-related issues requires joined up thinking between primary/secondary health care and social care.
Measuring Healthy Life expectancy (HLE) is fraught with problems of assessment. The self-reported healthy life expectancy can vary with the expectations of the individual, while NHS data records only those conditions that are deemed serious enough to warrant treatment. Ageing is accompanied by numerous changes in health which are not in themselves severe enough to warrant a visit to the GP, but in combination contribute to a decline in physical ability. Notwithstanding this, the ONS has collected date on HLE since 2011, and their data shows a proportional decrease, rather than increase, in HLE over a 6 year period. Some significant interventions would be needed to reverse this trend and gain an additional 5 years of HLE in the next 15 years. The recent government guidelines on exercise for health are welcome, and nutritional guidelines are gaining some traction but changing the behaviours of people such that they choose to follow health guidelines is still a problem.
Life Expectancy (LE) continues to differ between different sectors of the population. ONS data from 2014 shows that in 1991 there was a range of 8.3 years between the highest and lowest LE in different local authorities of England and Wales. In 2005, at the time of the last House of Lords report on the Scientific aspects of ageing, the figure was 8.5 years, and in 2014 8.6 years.
Identifying the causes of inequality in HLE and Life Expectancy (LE) is complex. In addition to our point about economic disparity above (paragraph 5, Q4), there are lifestyle factors. The ONS analyses HLE data by region, which varies even more than total LE data, and makes predictions as to the effects of changing lifestyle behaviours on HLE:
At a regional population level they find clear associations between HLE and smoking, alcohol-related hospital admissions, nutrition, physical activity. Therefore, targeting regions with poor indicators for public health campaigns should bring maximal benefit in terms of increased HLE.
Estimates of HLE gain (independently) are:
The above predictions would come with numerous caveats regarding change in health expectations, independence of data, confirming links between the factors and HLE at an individual level. Again, in reference as our comments above, health psychology studies to understand how to persuade people to follow health advice are required.
16 September 2019
 Doi: 10.1371/journal.pcbi.1006639
 Doi: 10.1371/journal.pone.0195605
 Doi: 10.1038/s41467-019-11370-y
 DOI: 10.1016/j.snb.2019.01.088
 DOI: 10.3390/nu11030539