The WRISK project regularly asks contributors to share their perspectives on a range of issues related to risk communication in pregnancy to further understanding of the challenges faced by scientists, clinicians, policy makers, and of course women themselves when trying to navigate risk messaging. These represent individual and personal viewpoints, and are aimed at encouraging reflection and discussion, rather than reaching conclusions.
In this blog, Peter Tennant and Tomasina Stacey share their research on what ‘risk’ means, and the misconceptions surrounding it. Peter is a Health Data Scientist at Leeds University and Tomasina is a Reader in Midwifery Science at the University of Huddersfield.
For most people, ‘taking a risk’ means doing something that might backfire. And if something is ‘high risk’ then you’ve taken a major gamble with a high chance of losing and/or losing big. So, if your doctor or midwife tells you that you’re at ‘high risk’, it seems fair to assume the worst and plan accordingly. Except you’d probably be wrong. Because what they meant – or thought they meant – would likely differ from most people’s idea of ‘high risk’.
This is because ‘risk’ can mean many things to many different people. So much that it’s entirely possible (indeed common) for someone to be called ‘high risk’, yet still have a very low chance of anything bad happening! To understand this, we need to consider what a statistician means by ‘risk’. To a statistician, ‘risk’ (or more formally ‘absolute risk’) simply means the ‘chance’, ‘probability’, or ‘likelihood’ of something happening. To a statistician, ‘risk’ is neutral term, it doesn’t imply high or low. And it doesn’t imply a good or bad outcome.
In fact, understanding whether a ‘risk’ is high or low, or good or bad, is meaningless without context (e.g. what we want to avoid) and comparison (i.e. ‘high risk’ compared with who?). Imagine, for example, we said the ‘risk of rain on Sunday was 1%’. That would be good news if you were planning a BBQ. But pretty bad news if you lived near a forest that was currently on fire. Similarly, while one couple having ‘unprotected sex’ might be very worried about a 5% ‘risk’ of pregnancy, another ‘trying for a baby’ might consider the same ‘risk’ frustratingly low.
Absolute risks, relative risks, and risk differences
But surely it gets easier if we consider the risk of something universally bad happening, like stillbirth? Now we can all agree that any ‘risk‘ is bad, right? Well… Only in theory. Because the reality is that there is almost always some risk. So, what we describe as high or low or good or bad can only really be described in reference to something else. To do this, statisticians have both the ‘risk difference’ and the ‘relative risk’, which describes the extra risk (compared to a chosen reference group) in absolute terms or relative terms respectively.
To give an example, we’ll consider the risk of stillbirth in women with body mass index (BMI) values above 30kg/m2 (commonly considered ‘obese’) compared with women with BMI values between 18.5kg/m2 and 25kg/m2 (commonly considered ‘healthy’). On average, women with ‘obese’ BMIs have a higher risk of stillbirth than women with ‘healthy’ BMIs. Indeed, in the UK, the risk of stillbirth in women with obese BMIs is around 7.5 in 1000 (or 1 in 133) and the risk in women with healthy BMIs is around 3.5 in 1000 (or 1 in 285) [1]. So, if you go by ‘relative risk’, you’d say the risk of stillbirth is over twice as high in women with obese BMIs than women with healthy BMIs, which sounds quite dramatic. But if you go by ‘risk difference’, you’d say women with obese BMIs have a 0.4% higher risk than women with health BMIs, which sounds quite low.
Risk and the complex individual
Things get murkier the further you move from the sterile statistical space to the complex climate of the clinic. Because all these concepts – absolute risk, relative risk, risk difference – are statistical ideas. And statistics is about understanding and making comparisons between groups of people, not individual people. So, while statistics is invaluable for predicting and planning services, and recognising better and worse practice overall, the relevance of a particular statistic for an individual doctor, midwife, family, or woman facing an individual-level decision is far more questionable.
Let’s return to the example of obesity, but this time to consider a specific woman with an obese BMI. Is she at ‘high risk’ of stillbirth compared to the general population? Well, the statistics reported above suggest she has twice the risk compared to an otherwise identical version of herself with a ‘healthy’ BMI. But BMI as a measure, isn’t actually meant to be used to estimate individual-level risks. And you’d need to know a lot more about her to have a remotely decent estimate of her individual-level ‘risk’. What’s her age? What’s her ethnicity? How much does she drink? How much does she smoke? Does she live with the father? Does he smoke? How old is he? And on and on it would go. And even if you knew everything there was to know and were able to calculate confidently that, for instance, she had four times the risk of stillbirth to an otherwise ‘healthy’ women, she’d still be 98+% likely to avoid a stillbirth.
Towards better terminology
All of which raises the question; is ‘risk’ the right word? And is it right to describe someone as ‘high risk’ if they’re still most likely to have a healthy and positive experience? We think there are serious conflicts between the statistical and common understandings of ‘risk’ that might be reduced by using any of ‘chance’, ‘probability’, or ‘likelihood’. And headline-grabbing – but highly misleading – ‘relative risks’ need discarding entirely.
References
1 Statistics about stillbirth. Tommy’s, 2019. Available at: https://www.tommys.org/our-organisation/charity-research/pregnancy-statistics/stillbirth
2 Chu et al. Maternal obesity and risk of stillbirth: a meta-analysis. Am J Obstet Gynecol. 2007;197(3):223-8.
3 Adult obesity, overweight and waist circumference, by region and sex. Health Survey for England, 2017. Available at: https://digital.nhs.uk/data-and-information/publications/statistical/health-survey-for-england/2017
Footnotes
[1] Estimated from a combination of the reported risk of stillbirth in 2017 (reference 1) together with the relative risk of obesity (reference 2) and the distribution of BMI in adult women of childbearing age (reference 3).
It is good to come across this. I am a retired Obstetrician who was and is passionate about empowering patients and specifically pregnant women so that they can make their own decisions. part of that is explaining the problems of their pregnancy to them. And as soon as you introduce “risk” then I found I could get into very complicated waters. And with the medico-legal world being so very challenging it became an even more loaded dice as to what and how to say things.
Your article helped me to understand why I was getting into trouble – the statistical meaning of risk v the colloquial meaning and how that gets muddled up.
I wrote a few articles about the drive towards elective C section debate and a book on the psychological challenges in Obstetrics and Gynecology ( which i want to write again for women themselves rather than profession who medicalise it) and risk came into all these subjects. I wanted to write more about risk but who would read it and how would i put it to help women understand what they were needing to here and process into something meaningful for them and their pregnancy.
It remains a challenge for all aspects of the medical profession and so this is a helpful start. I have joined my local Patient participation group and continue my work that way ( though still want to write my book!). I will continue to bear in mind this article.
Do send me a link for your blog.