A friend posted an article on her Facebook page discussing a recent research study out of Sweden showing that people on the autism spectrum have a decreased life expectancy. This friend has a child with autism. Autism coupled with learning disability, according to this study, is associated with the largest decrease in life expectancy. This friend’s child has learning disabilities along with autism.
My friend is scared.
On top of her worries about social isolation of her child due to her conditions, on top of worrying about her child’s place in society as she becomes an adult, on top of the fears of every parent about their children’s health and wellbeing and risks in general, my friend has had dumped on her frightening data clearly relating specifically to her daughter.
Only it doesn’t relate specifically to her daughter.
It is an aggregation of data that compares medical and mortality statistics of a pool of 27 thousand people with autism with that of a comparison group of 2-and-a-half million people without diagnoses of autism. It is not specifically about my friend’s child.
But it is about my friend’s child, because it is about every person with autism.
That’s the thing about statistics. They are about everyone, yet they are about no one in particular. That’s an aspect of practicing medicine in a world full of data that is particularly challenging, fascinating, and maddening. And people not practicing medicine have a similarly challenging, fascinating, and maddening time navigating this world of information.
Problem is, humans are extraordinarily complex. First, there’s the biological complexity of any multicellular organism, the variability due to genetics, the effects of environment, the interplay of internal and external forces. Then there’s psychology — individual predilections, societal influences — and how much of each of those is due to inborn versus external influences of the individual or of the interacting individuals of society? Even seemingly simple questions can become metaphysical; why are x and y correlated? Does x cause y? Does y cause x? Does a third thing cause both x and y? Do the combination of a third, forth, and fifth thing cause x under some conditions and y under a different set of conditions, some of which overlap the conditions which predispose x to be affected? Is there something inherent in x or y or both that lead to their association? What, if anything about the properties of x or y or the conditions that combine to give rise to certain outcomes are modifiable?
If my patient or my child or my neighbor ostensibly fits into a category being described in a general news article reporting on a scientific study, how much weight and credence do I give to it? What about a medical or scientific journal article? Does that specific person truly fit that category? If so, in what ways? In what ways does he not exactly fit? How important is the closeness of the fit? Even if a seemingly perfect fit, what does that actually mean for a specific individual? What exactly did the researchers look at? What did they miss?
The autism mortality article wasn’t meant for my friend. It wasn’t meant for the parent of a specific child with autism. It wasn’t written to alarm her. It was meant for society. It was meant for those who would influence the allocation of funds for medical research and social policy development.
Which means that the article was meant for my friend: a parent of a specific child with autism, a person who advocates for funding of research and services and societal support. It was meant to alarm/alert all of us, and my friend is one of all of us.
My job as a doctor is to take data and apply it to real people. To dissect the data, to judge the quality of research, to integrate it with what makes scientific and physiologic sense, to humanize it. My job as a friend, a neighbor, a family member, a general citizen of Earth, is to comfort and support others. So here is my reaction to that particular article as it relates to the person who posted it and to her daughter:
The article refers to a correlational study looking at aggregate numbers. Although the numbers and conclusions are laid out as straightforward, the actual data and meaning are exceedingly complicated. The study is a start, a call to look more closely at an overall population and see where dangers are. It is a study of averages; it is not a study of individuals. It leaves ever so many more questions than answers. It does not know your daughter. It does not know you and your husband and your other children. It does not know your child’s teachers or doctors. It does not know your social supports. Although this study does not know all of the above, it can help you as it draws attention to necessary lines of inquiry regarding a population (of which your child is a member) that needs serious attention.
This study was done in Sweden. We do not know how the data extrapolate to other countries. Are there genetic or cultural characteristics in the overall Swedish population that could affect these data? The data showed different main causes of premature death in two different populations of those with autism: those with learning difficulties and those without. We do not know if these differences hold true globally, and we do not know what other differences or characteristics play a part.
There may be specific age-related spikes for the most common causes of mortality which could skew the data. Distribution of data points is extremely important to investigate, not just averages. At what else did the researchers look? At what did they not look?
There are people looking at important questions: How can we begin discerning the causes of the disparities? How can we ameliorate the causes?
So many questions. So few answers so far. So glad people are asking the questions that will lead us to information that will help individual people, and, in turn, will help a population at large. And sending strength to all who look at a headline with numbers and in those numbers can’t help but see the face of their child.
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