Are broken bones, loneliness and poor sleep really hidden killers?

"Revealed, the five hidden killers that could send you to an early grave," the Daily Mail reports. These "hidden killers" include loneliness and poor sleep. But this is a simplistic take on complex research aiming to identify new ways of classifying health and wellbeing.

The research assessed the health and lifestyle of 3,000 US adults aged 57 to 85 years, then reassessed how many were incapacitated or had died five years later.

The researchers then compared two models to see which better categorised the participants' health status and risk.

The first mainly looked at the presence of diseases. The second model was more comprehensive, and included wider measures such as psychological wellbeing, mobility and health behaviours.

Overall, two-thirds of the sample was classed as being in "robust" good health when using the medical disease model, but many of these fell into more vulnerable risk groups when using a more comprehensive risk model.

The comprehensive model identified poor mental health, including depression, isolation and memory problems, and frailty and mobility problems as being predictive of mortality – "hidden killers" in newspaper speak – factors that would be largely overlooked if you only focused on physical diseases.

The findings suggest a comprehensive view of a person's health and wellbeing is needed when looking at their risk status and trying to target appropriate medical care and support.

Wellbeing and quality of life is not simply a case of whether or not someone has a physical illness. 

Where did the story come from?

The study was carried out by researchers from the University of Chicago, and was funded by the same institution and the US National Institute of Aging.

It was published in the peer-reviewed journal, PNAS, and the article is openly available for access.

The Daily Mail, The Sun and Metro articles are generally representative of the study's findings on loneliness, fractures and mobility problems.

But none of the papers grasped the point of the study – an attempt to create more complex and subtle models of wellbeing.

What kind of research was this?

This cohort study aimed to look at the best way of defining population health.

The researchers explained how the World Health Organization (WHO) defines health as a "state of complete physical, mental and social wellbeing and not merely the absence of disease or infirmity".

However, despite this there has been little rigorous attempt to use this definition to measure and assess population health. More often, what is described as the "medical model" is used to measure health, which focuses solely on disease diagnoses.

The researchers propose a "comprehensive model" that also considers psychological wellbeing and function as being a better fit to the WHO classification.

The researchers applied both of these models to US survey data to see how population health was defined by the different methods.   

What did the research involve?

The research involved a large, nationally representative sample of 3,005 older US adults aged 57 to 85 years who lived in the community and were taking part in the National Social Life, Health and Aging Project (NSHAP).

The participants were interviewed and completed a questionnaire about their health and lifestyle, as well as having body measures taken.

The researchers then used two different models to categorise the state of a person's health.

The medical model looked at specific diseases:

• heart disease
• cancer
• lung disease
• stroke
• diabetes
• kidney disease
• liver disease
• arthritis
• high blood pressure
• asthma
• thyroid disease

The comprehensive model also included 35 additional measures that encompassed five broad dimensions of health and wellbeing:

• health behaviour – smoking, exercise, sleep
• psychological health – depression, memory
• sensory abilities – vision, hearing
• neuroimmunity – chronic inflammation
• mobility or frailty – including fractures

The researchers followed these people up five years later. They then identified a few distinct health classes or categories within these models that encompassed several of the disease and wellbeing features, and most reliably indicated a person's health and mortality risk.  

What were the basic results?

The researchers identified five distinct health classes within the medical model that had significant and independent effects on mortality.

The first two classes were people who had undiagnosed high blood pressure (hypertension) and a single non-cardiovascular disease. These were the least vulnerable, or most "robust", health groups.

The intermediate (third) risk group were those with poorly controlled diabetes. The two most vulnerable groups (four and five) were those who had both cardiovascular disease and diabetes, or who had extensive medical illnesses.

People in the first two robust classes had around a 15% risk of being physically incapacitated or dead after five years, compared with 35% in the top extensive illness group.   

In the comprehensive model, six distinct classes arose – again, the first two classes were the least vulnerable, or most robust; classes three and four had an intermediate risk; and five and six were the most vulnerable.

The six classes were:

1. robust obese – obese but generally in good health
2. one minor condition – stomach ulcer, thyroid problems, bladder problems
3. broken bones – people with osteoporosis
4. poor mental health – depression, poor memory and loneliness
5. diabetes, hypertension and immobility
6. extensive medical illnesses and frailty

Almost a quarter of this older US population (22%) were in the first robust obese group. These people often had undiagnosed hypertension as measured by a home device, but, other than this, few other diseases and only a 6% risk of dying after five years.

The second group were not obese and had a minor condition – one not considered to have high mortality risk – and a 16% risk of death.

The two middle classes of the comprehensive model – those with fractures or osteoporosis and poor mental health – included 28% of this US population, despite being, as the researchers say, "largely ignored" by the medical model.   

The last two, most vulnerable, classes had the most compatibility with the vulnerable classes of the medical model, but still more people were reclassified as vulnerable when using the comprehensive model.

People in the most vulnerable sixth group had a 44% risk of dying within five years.

Overall, the medical model classified two-thirds of the older US population as being in robust health. Only half of these people went into the robust classes of the comprehensive model.

These findings suggest that factors such as poor mental health, bone fractures, and sensory and mobility problems are very important to consider when categorising vulnerability and mortality risk.

How did the researchers interpret the results?

The researchers concluded that the comprehensive model identifies new classes of people with mortality risk, such as those with broken bones or poor mental health, who are largely overlooked by medical models that only focus on disease.

They said that: "This approach provides a method for broadly reconceptualising health, which may inform health policy", with implications for medical care, prevention and resource allocation.   

Conclusion

As the researchers say, the WHO definition of health encompasses physical, mental and social wellbeing – not just the presence or absence of disease.

But how often are these extra dimensions taken into account when assessing a person's health status?

In this sample of older adults, just looking at their disease status puts the majority of them into an apparently "robust" health group.

Yet when you consider the additional dimensions of psychological health and wellbeing, you seem to get a much better indication of those who were at higher or lower risk of dying or being incapacitated in the coming five years.

The "hidden killers" the media refer to are factors such as frailty and fractures, and depression and loneliness, which would be overlooked if you looked at disease diagnoses alone.  

This suggests that a comprehensive view of a person's health and wellbeing is needed if you are looking at their risk status, and trying to target appropriate medical care and support.

But you can't say from the results of a study like this that these factors are being overlooked within healthcare.

For example, just because a medical risk model looking at physical diseases alone hasn't looked at these factors as a risk indicator doesn't necessarily mean that the people with these conditions have not been diagnosed in medical practice and are not receiving appropriate care and treatment.

The media term "hidden" in this context is therefore a bit misleading – as is the term "killer".

Of course, factors like loneliness and depression aren't necessarily going to lead to death directly, but could be associated with other poor health factors that together contribute to mortality risk.

Although this is a large, nationally representative sample, these are all older US adults. The six predictive classes the researchers identified to indicate robust, intermediate or vulnerable risk status may not be the same if people from another country were examined, or a population of middle-aged or younger adults.

It would be interesting and useful if researchers carried out a similar analysis on various groups within the UK population.

The study is a valuable contribution to how we define health and wellbeing. However, whether it has any direct implications in terms of health assessment, screening and diagnosis is unknown at this stage.