The Social Determinants of Health in the Digital Age
- Our social environment significantly shapes our health. Digital technology has the potential to unearth a new, deeper understanding of this process and help us better understand our own health.
- Technology is a double-edged sword. Greater transparency and accountability are required to understand the complex effects that the digital world is having on our health.
- The timing is now right for a new era of technology-enabled preventative medicine.
Health is Socially Determined
It can be overwhelming trying to weigh up the importance of all of the health decisions we make on a daily basis. We agonise over diets, exercise plans and alcohol consumption. In doing so, it can become easy to overlook what really shapes our health.
Our individual health choices (what you eat, whether you smoke) tell us only part of the story. Similarly, decades of research have shown that your doctor, nearest hospital and health system only contribute to a small fraction of your overall health.
To really understand human health, we need to zoom out. The World Health Organisation (WHO) explains that the strongest drivers of human health are “the conditions in which people are born, grow, live, work and age”.
This model, termed the social determinants of health, demonstrates how the specific conditions that make up your world — where you live, where you work, who you live with and what you encounter day to day — provide more than just the backdrop of your life. These key pillars of your life ‘get under your skin’, affecting you biologically and significantly influencing your health.
We all understand that there are certain risk factors for specific diseases. The social determinants of health can be considered the ‘upstream’ social and economic conditions in which these medical risk factors develop, the so called ‘causes of the causes’.
The ‘downstream’ consequences of these factors are our health outcomes — such as when we die or how many years of healthy living we enjoy — and evidence shows that the social determinants are consistently the strongest predictors of our health outcomes.
Take socioeconomic status as a key example — health outcomes change predictably according to socioeconomic status, with outcomes improving the higher up somebody is on the socioeconomic ladder.
This means that there are not only health inequalities between richer and poorer countries (i.e. the United States vs. Sierra Leone) but also within countries. In London, cycle 20 minutes from affluent Knightsbridge to Church Street in North Westminster (a poorer area in a neighbouring borough) and the difference in male life expectancy falls by 19 years.
This is much more complex than simply rich versus poor. Even in wealthy societies with a social safety net designed to protect people from poverty and a robust public healthcare system, your place on the social ladder or hierarchy will directly determine your health.
There is a clear ‘gradient’ in health outcomes observed between each rung on the ladder from richest to poorest, an effect that can be simply mapped as one takes the train east from the financial centre of London to areas of increasing social deprivation.
The Whitehall studies helped pioneer this concept of the ‘social gradient’ of human health. They showed that even within a single, large bureaucratic organisation in a rich country (in this case, the UK civil service) the further down the professional ladder (and so the lower one’s socioeconomic status), the higher the risk of heart disease and mortality.
The implications of this are sobering. Even accounting for specific risk factors like smoking, it is your social class, workplace, neighbourhood and social environment in combination affect your health outcomes dramatically.
These findings have gone on to influence health policy worldwide and a comprehensive body of research has proven the correlation between the social determinants of health and health outcomes.
At the same time, key pieces of the puzzle have remained elusive. How exactly do the conditions of your working life, social world and neighbourhood get under your skin? How does the social and the economic become the psychological and the biological, leading to specific health outcomes? The “unexplained” differences (grey sections in the chart above) have yet to be fully unpacked.
Despite the impressive insight and persistence of the epidemiologists who pioneered this research, for years there has been a lack of data probing deeper into the social determinants to answer fundamental questions about how the world around us shapes our health.
This is where the digital comes into play.
The Digital Revolution
In the West, digital technology has rapidly permeated every aspect of our lives and continues to do so at an ever accelerating rate. As recently as 2004, not a single one of us had an iPhone or Android smartphone, or had ever used Google maps, Facebook, Twitter or Instagram.
Since then, technological progress across the board (in software, hardware, processing power, “big data”, machine learning, etc) has ushered in significant changes in the way we live. This has also changed the way our lives can be recorded and analysed.
Previously, detailed information about our daily life would be lost unless proactively and painstakingly recorded by researchers, who would then pore over the specific data they had collected.
Contrast this with our world in 2019 — every day we create vast data trails that reveal incredibly detailed information about every aspect of our lives simply by carrying and using our smartphones.
With the rapid rise of the ‘Internet of Things’ (wearable technology and ‘smart’ home appliances) we will soon provide even more intimate behavioural and biometric data. This abundance of data was unimaginable only a generation before. As Michal Kosniski explained, there now exist vast data that “scientists would not ever be able to collect”.
Given how much of our daily life now relies upon our smartphone, computer and other digital products, digital technologies enable unprecedented analysis of human behaviour. Such analysis is made possible with advances in statistical science, computing power and machine learning techniques applied to very large data sets (‘big data’).
As an example, a team based at Facebook is analysing patterns of behaviour rendered from our smartphone use and digital footprint to predict and mitigate the risk of suicide. Putting aside for a moment the valid ethical concerns here, such a project could only ever be conceived given the ubiquitous use of digital technology alongside the advent of big data (Facebook’s 2.4 billion users being a perfect example of how incredible scale can enable new insights).
In fact, the argument has even been made that in the setting of abundant data points on millions of subjects, the scientific method as we know it can be subverted. Bullish advocates of the power of big data argue that the hypothesis of a given experiment may become less important if you have the computing power, statistical tools and expertise to interrogate and unearth patterns and meaning from these vast data sets.
This technology now presents an incredible opportunity to explain exactly how the world around us impacts our health and wellbeing.
Digital Technology: The Lens & The Director
When you consider the way that technology companies (and increasingly all companies) already use our data to improve their business models, it is plain to see that there is incredible potential to use the data we create each day to better understand how social determinants shape our health outcomes.
At the same time, the other half of this story that we already know and are starting to better understand, is that the companies who provide our smartphones, wearables and apps do not design them to have a neutral impact on our lives. Digital technology is already playing a powerful and pervasive role in affecting, changing and influencing human environments and behaviour, driven by the agenda and imperatives of technology companies.
And so, digital technology has a dual role to play when it comes to the social determinants of health. To explain this with an analogy, if our lives are a film, digital technology can be both (i) the camera lens and (ii) the movie director in shaping our health.
As the lens, digital technology presents a tantalising new window for understanding the mechanisms by which the social, psychological and biological interact and affect each other to produce different health outcomes.
As a simple example, by aggregating data on food purchases, weight, social interactions, step count and location, along with simple biological parameters like blood pressure, it is possible to create what has been termed a ‘digital biomarker’ to offer highly personalised, dynamic and real time insights about the risk of a given disease.
Insights afforded by the analysis and mining of this vast quantity of data promise to open up new frontiers in public health research, revealing how the upstream inputs in our lives impact our downstream health outcomes. In many cases, the raw material for this analysis, our data, is already there.
However, like a movie director manipulating our actions from behind the camera, the digital world changes, warps and molds our lives — our commute, our company meeting, our family dinner, our run in the park. Technology companies are now able to “engineer the context around a particular (desired) behaviour and force change that way”. In the words of one prominent technologist, “we are learning how to write the music, and then we let the music make them (our users) dance.” As such, digital technology can now play a key role in influencing the countless decisions that cumulatively impact our health outcomes.
The Digital Determinants of Health
Digital technology is here to stay. When it comes to the social determinants of health, the dual role of digital technology requires careful and deliberate efforts to realise the potential benefits of “the lens” whilst simultaneously being cautious of the influence of “the director,’’ the ever-present mediator and influence in our lives.
Currently, the largest and most comprehensive datasets about our behaviour are under lock and key of the corporations profiting from these insights into our lives. Shoshanna Zuboff describes the asymmetry of power in this status quo where “this data is about us, but it is not for us”.
In an age where almost every aspect of human life creates a data point, it must not only be private companies who can harness these insights into our behaviour, emotions and decision-making processes. This data is about us, and so it should be evident to all citizens that it must also be available to support important research in the public interest, including the social determinants of health.
Our data needs to be made available to academic institutions, non-profits and other organisations able to leverage this to deepen our understanding of human health. In the UK, organisations such as the Turing Institute and the Wellcome Trust are driving the conversation on the ethical use of personal data in medical research. Revisiting issues around consent, ownership of data and privacy are vital; this next leap needs robust public debate.
At the same time, what about the ‘director’ and the direct impact of digital technology on our health (both physical and mental)? If we accept that digital technology is affecting our behaviour and social interactions, decades of public health research tell us it also plays a role in determining our health. Untangling the complexity of the relationship between technology and our health will be difficult. We are currently in a situation similar to when big tobacco relied on a lack of scientific evidence explaining the effects of smoking on health. However, this time around the data itself is privately held on the servers of large technology companies. To understand the health impact of ubiquitous digital technology on our lives first requires a level of transparency and accountability that is currently off the table. Can we trust technology companies to tell us if they discover that their products are measurably harming us?
Taking a step back, it is vital to remember that the social determinants of health (the upstream social and economic conditions that create our health outcomes) are not the result of any natural law, nor do they exist in a vacuum; they are a direct result of policy choices and power structures, and “often shaped by public policies that reflect prevailing political ideologies” of that time and place.
The same can also be said about digital technologies — how they are used or mis-used in society is also a reflection of policy choices, ideology, inequality and power. Technology itself is “neutral”, it can be designed for and ‘optimised for’ different aims, whether to obtain valuable insight focused on the public good or purely to predict and shape our behaviour for commercial gain.
What Next?
We’ve discussed the social determinants of health, recognising that what truly affects our health is the world around us, much more than any doctor, hospital or health insurance plan. There is a social gradient to health, with social and economic conditions being the key drivers of health outcomes.
In countries where the use of digital technology is universal and deeply embedded in daily life, there is an real opportunity to use this data from every aspect of our lives to explain how the world around us (the social determinants) impacts our health outcomes. Realising this will require rethinking who and what this data is for.
Effective use of this data also requires a shift in the status quo of in the way we think about health — moving the emphasis away from treatment of disease and towards preventing it in the first place.
Prevention means addressing the ‘upstream’, root causes of disease, i.e. the social determinants of health and health inequalities. There has been impressive success in improving health outcomes in some of the world’s poorest countries using targeted upstream interventions, with progressive health and social policies focused on poverty reduction, early years interventions and the fundamentals of preventative medicine. When adopted by Western countries, policies focused on the social determinants of health have led to healthier populations.
Recent North American data shows how US States that spend more on higher social services versus medical services actually outperform their counterparts in areas such as obesity, asthma, mental health, cancer and diabetes.
In the US, there has been growing support for value-based models of healthcare, where improved outcomes and value for the patient are incentivised over costly individual procedures or treatments. This model places great emphasis on prevention for improving population health, with insurers and providers taking a greater stake in the overall patient journey and ownership for keeping people healthy and out of hospital.
For example, the large US insurer Blue Cross Blue Shield has explicitly adopted the social determinants of health as part of it’s strategy for Medicare in North Carolina by addressing food insecurity, poor transport links and boosting social care amongst it’s most vulnerable populations.
This approach becomes really exciting when the proven effectiveness of preventative medicine is paired with the power of big data, enabling greater depth, breadth and specificity in delivery of services. One company taking this approach is CityBlock in the US, who have partnered with local healthcare providers to use the power of data to deliver targeted health and social care services focused on prevention.
The great achievement of the social determinants of health is that they compelled politicians and public health experts to focus on prevention and how the social and economic factors that fundamentally shape our health. By harnessing the potential of our personal data to better understand these upstream determinants of our health, there is the scope to provide policy makers and healthcare organisations with compelling new insights and improved capabilities.
The great hope here is not only to create a more effective and equitable public health policy, but to deliver this to populations at scale during a time of rapid social, economic and technological change.
