In the UK, the All-Party Parliamentary Group (APPG) for Longevity has secured funding for its Open Life Data project, which aims to create a framework for effective and ethical collection of health-related data on a national level.
The UK appears to be one of the first countries to start taking aging seriously in politics and government. The UK government has named its aging society one of the four Grand Challenges facing the country and has announced the lofty goal of extending healthy life expectancy nation-wide by five years. Even though a recent report by the House of Lords accuses the government of failing to keep the pace needed to fulfill this promise, the UK is still ahead of many other developed countries in understanding the importance of fighting aging.
One of the main drivers of this change has been the APPG for Longevity. A year ago, the group published its Health of the Nation strategy, which included the Open Life Data Framework as a key element. The group has now secured funding for this project from the Health Foundation nonprofit.
The Open Life Data Framework
The Open Life Data Framework is described in the strategy as “a collaborative ecosystem to stimulate social and business model innovation using ethical data models.” As Tina Woods, a social entrepreneur and one of the founders of APPG, explains, this involves finding ways to collect and share health-related data more efficiently and responsibly.
Due to publish in September 2021, the Framework will address the growing recognition by scientists and policymakers of the need to broaden the data ecosystem to encompass the wider determinants of health and leverage insights from ethnically diverse populations across the life course to deliver improved health and healthspan.
Non-health data: just as important?
While the importance of gathering health data is self-evident, there has been a growing understanding that non-health data may affects health as well.
Woods defines non-health data as:
…the data gathered by wearables and smartphone apps, but also shopping purchases, social media and banking transactions. It represents all data being captured in our lives as ‘data exhaust’ by tech giants but also ‘exposome’ data to catalogue the complex environmental exposures we are subjected to throughout our lives, including our diet, lifestyle factors, and social influences, and our body’s response to these challenges.
Data in health and medical records represents as little as 15% of the determinants of our health. With 85% of the determinants lying outside healthcare systems, encompassing behavioral, social, economic, and genetic factors, there is also a pressing need to focus on wider non-health data.
Gathering more data can finesse our understanding of healthspan-affecting factors, such as physical activity . Consider another example: it is known that stress is associated with worse health and shorter lifespan . Wearable tech allows us to constantly monitor stress, identify typical stressful situations, and help people avoid them. Air quality is another environmental factor, and cross-linked with the person’s location data, it can be used to study and predict the impact of air pollution on our health, both as individuals and as nations.
Gathering health data? No sweat
Today, wearables are mostly associated with non-health data, but they can produce valuable health data as well. While most wearables are still general-purpose devices that can monitor only basic parameters such as heart rate, a growing number of startups aim much higher. As an article in Nature describes , experimental gadgets extract biochemical data from sweat and epidermis, monitor hydration levels, perform non-invasive glucose measuring, etc. The availability of such data can revolutionize medicine in two ways. First, it will allow physicians to assess patients’ conditions constantly rather than during a visit to the clinic. Second, it will shift the focus towards self-care, making people more aware of their health and assigning them an active role in preserving it. Just think of what non-invasive glucose measuring can do to steer people towards healthier diets.
Privacy and equality
Yet, all this is for nothing if people are reluctant to share their data. While this reluctance is often fueled by legitimate concerns, data gathered from people’s devices can help them stay healthier. This means that we need a healthier (pun intended) attitude to data privacy. Indeed, one of the stated goals of the Open Life Data Framework is to “build public trust in the use of data for individual and collective health and social care purposes”.
Data Saves Lives is another notable European project that educates people on the importance of sharing their health data. The project’s vision is stated as “a Europe where trustworthy data sharing supports health and scientific research to meet the needs of patients and address the challenges faced by our healthcare systems”.
The Open Life Data Framework’s authors also discuss inequality. The COVID pandemic has underscored the vast differences in overall health and in health outcomes among groups divided by race, gender, and income. Gathering more data will help scientists, physicians, and governing bodies better understand and address those differences.
Advances in wearable technology and AI have resulted in an exponential growth in the amount of health-related data being collected. Effective and safe ways of gathering, sharing, and using such data can revolutionize healthcare. The work of APPG for Longevity, and the Open Life Data Framework in particular, provide an encouraging example of the governmental involvement needed to implement those changes. For further reading on how technology and AI are affecting healthcare, check out our interview with Tina Woods and our review of her recently published book “Live Longer with AI”.
 Hart, D. A., & Zernicke, R. F. (2020). Optimal human functioning requires exercise across the lifespan: mobility in a 1g environment is intrinsic to the integrity of multiple biological systems. Frontiers in physiology, 11, 156.
 Lupien, S. J., McEwen, B. S., Gunnar, M. R., & Heim, C. (2009). Effects of stress throughout the lifespan on the brain, behaviour and cognition. Nature reviews neuroscience, 10(6), 434-445.
 Seshadri, D. R., Li, R. T., Voos, J. E., Rowbottom, J. R., Alfes, C. M., Zorman, C. A., & Drummond, C. K. (2019). Wearable sensors for monitoring the physiological and biochemical profile of the athlete. NPJ digital medicine, 2(1), 1-16.