Why Are Autism Rates Steadily Rising?
Stefania Sterling was just 21 when she had her son, Charlie. She was young and healthy, with no genetic issues apparent in either her or her husband's family, so she expected Charlie to be typical.
"It is surprising that the prevalence of a significant disorder like autism has risen so consistently over a relatively brief period."
It wasn't until she went to a Mommy and Me music class when he was one, and she saw all the other one-year-olds walking, that she realized how different her son was. He could barely crawl, didn't speak, and made no eye contact. By the time he was three, he was diagnosed as being on the lower functioning end of the autism spectrum.
She isn't sure why it happened – and researchers, too, are still trying to understand the basis of the complex condition. Studies suggest that genes can act together with influences from the environment to affect development in ways that lead to Autism Spectrum Disorder (ASD). But rates of ASD are rising dramatically, making the need to figure out why it's happening all the more urgent.
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Indeed, the CDC's latest autism report, released last week, which uses 2016 data, found that the prevalence of ASD in four-year-old children was one in 64 children, or 15.6 affected children per 1,000. That's more than the 14.1 rate they found in 2014, for the 11 states included in the study. New Jersey, as in years past, was the highest, with 25.3 per 1,000, compared to Missouri, which had just 8.8 per 1,000.
The rate for eight-year-olds had risen as well. Researchers found the ASD prevalence nationwide was 18.5 per 1,000, or one in 54, about 10 percent higher than the 16.8 rate found in 2014. New Jersey, again, was the highest, at one in 32 kids, compared to Colorado, which had the lowest rate, at one in 76 kids. For New Jersey, that's a 175 percent rise from the baseline number taken in 2000, when the state had just one in 101 kids.
"It is surprising that the prevalence of a significant disorder like autism has risen so consistently over a relatively brief period," said Walter Zahorodny, an associate professor of pediatrics at Rutgers New Jersey Medical School, who was involved in collecting the data.
The study echoed the findings of a surprising 2011 study in South Korea that found 1 in every 38 students had ASD. That was the the first comprehensive study of autism prevalence using a total population sample: A team of investigators from the U.S., South Korea, and Canada looked at 55,000 children ages 7 to 12 living in a community in South Korea and found that 2.64 percent of them had some level of autism.
Searching for Answers
Scientists can't put their finger on why rates are rising. Some say it's better diagnosis. That is, it's not that more people have autism. It's that we're better at detecting it. Others attribute it to changes in the diagnostic criteria. Specifically, the May 2013 update of the Diagnostic and Statistical Manual of Mental Disorders-5 -- the standard classification of mental disorders -- removed the communication deficit from the autism definition, which made more children fall under that category. Cynical observers believe physicians and therapists are handing out the diagnosis more freely to allow access to services available only to children with autism, but that are also effective for other children.
Alycia Halladay, chief science officer for the Autism Science Foundation in New York, said she wishes there were just one answer, but there's not. While she believes the rising ASD numbers are due in part to factors like better diagnosis and a change in the definition, she does not believe that accounts for the entire rise in prevalence. As for the high numbers in New Jersey, she said the state has always had a higher prevalence of autism compared to other states. It is also one of the few states that does a good job at recording cases of autism in its educational records, meaning that children in New Jersey are more likely to be counted compared to kids in other states.
"Not every state is as good as New Jersey," she said. "That accounts for some of the difference compared to elsewhere, but we don't know if it's all of the difference in prevalence, or most of it, or what."
"What we do know is that vaccinations do not cause autism."
There is simply no defined proven reason for these increases, said Scott Badesch, outgoing president and CEO of the Autism Society of America.
"There are suggestions that it is based on better diagnosis, but there are also suggestions that the incidence of autism is in fact increasing due to reasons that have yet been determined," he said, adding, "What we do know is that vaccinations do not cause autism."
Zahorodny, the pediatrics professor, believes something is going on beyond better detection or evolving definitions.
"Changes in awareness and shifts in how children are identified or diagnosed are relevant, but they only take you so far in accounting for an increase of this magnitude," he said. "We don't know what is driving the surge in autism recorded by the ADDM Network and others."
He suggested that the increase in prevalence could be due to non-genetic environmental triggers or risk factors we do not yet know about, citing possibilities including parental age, prematurity, low birth rate, multiplicity, breech presentation, or C-section delivery. It may not be one, but rather several factors combined, he said.
"Increases in ASD prevalence have affected the whole population, so the triggers or risks must be very widely dispersed across all strata," he added.
There are studies that find new risk factors for ASD almost on a daily basis, said Idan Menashe, assistant professor in the Department of Health at Ben-Gurion University of the Negev, the fastest growing research university in Israel.
"There are plenty of studies that find new genetic variants (and new genes)," he said. In addition, various prenatal and perinatal risk factors are associated with a risk of ASD. He cited a study his university conducted last year on the relationship between C-section births and ASD, which found that exposure to general anesthesia may explain the association.
Whatever the cause, health practitioners are seeing the consequences in real time.
"People say rates are higher because of the changes in the diagnostic criteria," said Dr. Roseann Capanna-Hodge, a psychologist in Ridgefield, CT. "And they say it's easier for children to get identified. I say that's not the truth and that I've been doing this for 30 years, and that even 10 years ago, I did not see the level of autism that I do see today."
Sure, we're better at detecting autism, she added, but the detection improvements have largely occurred at the low- to mid- level part of the spectrum. The higher rates of autism are occurring at the more severe end, in her experience.
A Polarizing Theory
Among the more controversial risk factors scientists are exploring is the role environmental toxins may play in the development of autism. Some scientists, doctors and mental health experts suspect that toxins like heavy metals, pesticides, chemicals, or pollution may interrupt the way genes are expressed or the way endocrine systems function, manifesting in symptoms of autism. But others firmly resist such claims, at least until more evidence comes forth. To date, studies have been mixed and many have been more associative than causative.
"Today, scientists are still trying to figure out whether there are other environmental changes that can explain this rise, but studies of this question didn't provide any conclusive answer," said Menashe, who also serves as the scientific director of the National Autism Research Center at BGU.
"It's not everything that makes Charlie. He's just like any other kid."
That inconclusiveness has not dissuaded some doctors from taking the perspective that toxins do play a role. "Autism rates are rising because there is a mismatch between our genes and our environment," said Julia Getzelman, a pediatrician in San Francisco. "The majority of our evolution didn't include the kinds of toxic hits we are experiencing. The planet has changed drastically in just the last 75 years –- it has become more and more polluted with tens of thousands of unregulated chemicals being used by industry that are having effects on our most vulnerable."
She cites BPA, an industrial chemical that has been used since the 1960s to make certain plastics and resins. A large body of research, she says, has shown its impact on human health and the endocrine system. BPA binds to our own hormone receptors, so it may negatively impact the thyroid and brain. A study in 2015 was the first to identify a link between BPA and some children with autism, but the relationship was associative, not causative. Meanwhile, the Food and Drug Administration maintains that BPA is safe at the current levels occurring in food, based on its ongoing review of the available scientific evidence.
Michael Mooney, President of St. Louis-based Delta Genesis, a non-profit organization that treats children struggling with neurodevelopmental delays like autism, suspects a strong role for epigenetics, which refers to changes in how genes are expressed as a result of environmental influences, lifestyle behaviors, age, or disease states.
He believes some children are genetically predisposed to the disorder, and some unknown influence or combination of influences pushes them over the edge, triggering epigenetic changes that result in symptoms of autism.
For Stefania Sterling, it doesn't really matter how or why she had an autistic child. That's only one part of Charlie.
"It's not everything that makes Charlie," she said. "He's just like any other kid. He comes with happy moments. He comes with sad moments. Just like my other three kids."
Two years, six million deaths and still counting, scientists are searching for answers to prevent another COVID-19-like tragedy from ever occurring again. And it’s a gargantuan task.
Our disturbed ecosystems are creating more favorable conditions for the spread of infectious disease. Global warming, deforestation, rising sea levels and flooding have contributed to a rise in mosquito-borne infections and longer tick seasons. Disease-carrying animals are in closer range to other species and humans as they migrate to escape the heat. Bats are thought to have carried the SARS-CoV-2 virus to Wuhan, either directly or through another host animal, but thousands of novel viruses are lurking within other wild creatures.
Understanding how climate change contributes to the spread of disease is critical in predicting and thwarting future calamities. But the problem is that predictive models aren’t yet where they need to be for forecasting with certainty beyond the next year, as we could for weather, for instance.
The association between climate and infectious disease is poorly understood, says Irina Tezaur, a computational scientist at Sandia National Laboratories. “Correlations have been observed but it’s not known if these correlations translate to causal relationships.”
To make accurate longer-term predictions, scientists need more empirical data, multiple datasets specific to locations and diseases, and the ability to calculate risks that depend on unpredictable nature and human behavior. Another obstacle is that climate scientists and epidemiologists are not collaborating effectively, so some researchers are calling for a multidisciplinary approach, a new field called Outbreak Science.
Climate scientists are far ahead of epidemiologists in gathering essential data.
Earth System Models—combining the interactions of atmosphere, ocean, land, ice and biosphere—have been in place for two decades to monitor the effects of global climate change. These models must be combined with epidemiological and human model research, areas that are easily skewed by unpredictable elements, from extreme weather events to public environmental policy shifts.
“There is never just one driver in tracking the impact of climate on infectious disease,” says Joacim Rocklöv, a professor at the Heidelberg Institute of Global Health & Heidelberg Interdisciplinary Centre for Scientific Computing in Germany. Rocklöv has studied how climate affects vector-borne diseases—those transmitted to humans by mosquitoes, ticks or fleas. “You need to disentangle the variables to find out how much difference climate makes to the outcome and how much is other factors.” Determinants from deforestation to population density to lack of healthcare access influence the spread of disease.
Even though climate change is not the primary driver of infectious disease today, it poses a major threat to public health in the future, says Rocklöv.
The promise of predictive modeling
“Models are simplifications of a system we’re trying to understand,” says Jeremy Hess, who directs the Center for Health and the Global Environment at University of Washington in Seattle. “They’re tools for learning that improve over time with new observations.”
Accurate predictions depend on high-quality, long-term observational data but models must start with assumptions. “It’s not possible to apply an evidence-based approach for the next 40 years,” says Rocklöv. “Using models to experiment and learn is the only way to figure out what climate means for infectious disease. We collect data and analyze what already happened. What we do today will not make a difference for several decades.”
To improve accuracy, scientists develop and draw on thousands of models to cover as many scenarios as possible. One model may capture the dynamics of disease transmission while another focuses on immunity data or ocean influences or seasonal components of a virus. Further, each model needs to be disease-specific and often location-specific to be useful.
“All models have biases so it’s important to use a suite of models,” Tezaur stresses.
The modeling scientist chooses the drivers of change and parameters based on the question explored. The drivers could be increased precipitation, poverty or mosquito prevalence, for instance. Later, the scientist may need to isolate the effect of one driver so that will require another model.
There have been some related successes, such as the latest models for mosquito-borne diseases like Dengue, Zika and malaria as well as those for flu and tick-borne diseases, says Hess.
Rocklöv was part of a research team that used test data from 2018 and 2019 to identify regions at risk for West Nile virus outbreaks. Using AI, scientists were able to forecast outbreaks of the virus for the entire transmission season in Europe. “In the end, we want data-driven models; that’s what AI can accomplish,” says Rocklöv. Other researchers are making an important headway in creating a framework to predict novel host–parasite interactions.
Modeling studies can run months, years or decades. “The scientist is working with layers of data. The challenge is how to transform and couple different models together on a planetary scale,” says Jeanne Fair, a scientist at Los Alamos National Laboratory, Biosecurity and Public Health, in New Mexico.
Disease forecasting will require a significant investment into the infrastructure needed to collect data about the environment, vectors, and hosts a tall spatial and temporal resolutions.
And it’s a constantly changing picture. A modeling study in an April 2022 issue of Nature predicted that thousands of animals will migrate to cooler locales as temperatures rise. This means that various species will come into closer contact with people and other mammals for the first time. This is likely to increase the risk of emerging infectious disease transmitted from animals to humans, especially in Africa and Asia.
Other things can happen too. Global warming could precipitate viral mutations or new infectious diseases that don’t respond to antimicrobial treatments. Insecticide-resistant mosquitoes could evolve. Weather-related food insecurity could increase malnutrition and weaken people’s immune systems. And the impact of an epidemic will be worse if it co-occurs during a heatwave, flood, or drought, says Hess.
The devil is in the climate variables
Solid predictions about the future of climate and disease are not possible with so many uncertainties. Difficult-to-measure drivers must be added to the empirical model mix, such as land and water use, ecosystem changes or the public’s willingness to accept a vaccine or practice social distancing. Nor is there any precedent for calculating the effect of climate changes that are accelerating at a faster speed than ever before.
The most critical climate variables thought to influence disease spread are temperature, precipitation, humidity, sunshine and wind, according to Tezaur’s research. And then there are variables within variables. Influenza scientists, for example, found that warm winters were predictors of the most severe flu seasons in the following year.
The human factor may be the most challenging determinant. To what degree will people curtail greenhouse gas emissions, if at all? The swift development of effective COVID-19 vaccines was a game-changer, but will scientists be able to repeat it during the next pandemic? Plus, no model could predict the amount of internet-fueled COVID-19 misinformation, Fair noted. To tackle this issue, infectious disease teams are looking to include more sociologists and political scientists in their modeling.
Addressing the gaps
Currently, researchers are focusing on the near future, predicting for next year, says Fair. “When it comes to long-term, that’s where we have the most work to do.” While scientists cannot foresee how political influences and misinformation spread will affect models, they are positioned to make headway in collecting and assessing new data streams that have never been merged.
Disease forecasting will require a significant investment into the infrastructure needed to collect data about the environment, vectors, and hosts at all spatial and temporal resolutions, Fair and her co-authors stated in their recent study. For example real-time data on mosquito prevalence and diversity in various settings and times is limited or non-existent. Fair also would like to see standards set in mosquito data collection in every country. “Standardizing across the US would be a huge accomplishment,” she says.
Understanding how climate change contributes to the spread of disease is critical for thwarting future calamities.
Jeanne Fair
Hess points to a dearth of data in local and regional datasets about how extreme weather events play out in different geographic locations. His research indicates that Africa and the Middle East experienced substantial climate shifts, for example, but are unrepresented in the evidentiary database, which limits conclusions. “A model for dengue may be good in Singapore but not necessarily in Port-au-Prince,” Hess explains. And, he adds, scientists need a way of evaluating models for how effective they are.
The hope, Rocklöv says, is that in the future we will have data-driven models rather than theoretical ones. In turn, sharper statistical analyses can inform resource allocation and intervention strategies to prevent outbreaks.
Most of all, experts emphasize that epidemiologists and climate scientists must stop working in silos. If scientists can successfully merge epidemiological data with climatic, biological, environmental, ecological and demographic data, they will make better predictions about complex disease patterns. Modeling “cross talk” and among disciplines and, in some cases, refusal to release data between countries is hindering discovery and advances.
It’s time for bold transdisciplinary action, says Hess. He points to initiatives that need funding in disease surveillance and control; developing and testing interventions; community education and social mobilization; decision-support analytics to predict when and where infections will emerge; advanced methodologies to improve modeling; training scientists in data management and integrated surveillance.
Establishing a new field of Outbreak Science to coordinate collaboration would accelerate progress. Investment in decision-support modeling tools for public health teams, policy makers, and other long-term planning stakeholders is imperative, too. We need to invest in programs that encourage people from climate modeling and epidemiology to work together in a cohesive fashion, says Tezaur. Joining forces is the only way to solve the formidable challenges ahead.
This article originally appeared in One Health/One Planet, a single-issue magazine that explores how climate change and other environmental shifts are increasing vulnerabilities to infectious diseases by land and by sea. The magazine probes how scientists are making progress with leaders in other fields toward solutions that embrace diverse perspectives and the interconnectedness of all lifeforms and the planet.
Scientists use AI to predict how hospital stays will go
The Friday Five covers five stories in research that you may have missed this week. There are plenty of controversies and troubling ethical issues in science – and we get into many of them in our online magazine – but this news roundup focuses on scientific creativity and progress to give you a therapeutic dose of inspiration headed into the weekend.
Here are the promising studies covered in this week's Friday Five:
- The problem with bedtime munching
- Scientists use AI to predict how stays in hospitals will go
- How to armor the shields of our livers against cancer
- One big step to save the world: turn one kind of plastic into another
- The perfect recipe for tiny brains
And an honorable mention this week: Bigger is better when it comes to super neurons in super agers