自闭症诊断数为何上升？研究者渐趋一致的解释

Autism spectrum disorder affects how people communicate, interact with others, and experience the sensory world. The condition is also defined by restricted interests and repetitive behaviors. Over the past few decades, the number of people diagnosed with this condition has grown at an astonishing rate. To the general public, this steep upward curve often looks like an epidemic.

Schools, medical clinics, and families are seeing more children and adults receiving an autism diagnosis than ever before. This rapid rise has sparked a complex debate among scientists, medical professionals, and the public. To understand this debate, we have to look closely at what researchers are actually measuring.

When scientists talk about rising autism numbers, they are usually talking about “diagnosed cases,” which simply means the number of people who have been given a medical label. This is different from “prevalence under identical methods,” which refers to the number of people who meet the criteria when a population is screened in a consistent, uniform way. Finally, there is the “underlying incidence,” which is the actual, biological rate at which people develop the condition.

No study actually measures underlying incidence because there is no biological test for autism. Most research relies on counting diagnosed cases. Only one study in the collection discussed here measures prevalence under identical methods across time. This article looks at twenty papers published between 2011 and 2026, a selection rather than a comprehensive survey, and at what each one can and cannot tell us about whether the occurrence of autism is rising or whether society is simply naming it more frequently.

Documenting the Global Rise in Diagnoses

The sheer volume of new diagnoses is a well-documented phenomenon. In the United States, a paper by Yan and colleagues in the Journal of Autism and Developmental Disorders examined national health survey data and observed an upward trend in diagnoses among children and adolescents between 2013 and 2022. By the end of the study period, they estimated that nearly four percent of children in the surveyed group had received an autism label. It is worth noting that this study relied on parent-reported physician diagnoses and had household response rates hovering around fifty percent.

To understand the global picture, researchers often use a systematic review, which combines data from dozens of previous research projects to find a common average. A global systematic review by Zeidan and colleagues in Autism Research reported a median estimate that about one percent of people in the populations studied have autism. However, this median combines highly diverse study estimates that span from 1.09 to 436 per 10,000 people. Zeidan and colleagues attribute this four-hundred-fold spread to differences in study design, ascertainment method, and sociodemographic context rather than to underlying biological variation.

Another large review by Talantseva and colleagues in Frontiers in Psychiatry calculated a slightly lower pooled prevalence but noted a marked increase over time. Their analysis found that the study method accounted for much of the variation in these numbers. Studies using active record-review surveillance found rates of 1.22 percent, while health insurance databases yielded only 0.35 percent.

When researchers look at specific primary care systems, the growth is staggering. A study by Russell and colleagues in the Journal of Child Psychology and Psychiatry examined primary care records in England and Northern Ireland. They found a 787 percent increase in the incidence of recorded autism diagnoses between 1998 and 2018.

One finding ran against expectation. If the rise were driven by clinicians catching cases earlier, the average age at diagnosis should have fallen. Instead it climbed, from 9.6 years to 14.5 years over the same period. The authors note that this runs counter to the assumption that rising numbers reflect earlier detection in childhood.

Who Is Receiving the Diagnosis Now?

The study by Russell and colleagues highlighted a major shift in exactly who is being diagnosed. Historically, autism was identified almost exclusively in young children. The British researchers found that the steepest growth in new diagnoses occurred among adults and females.

The changing demographics are also apparent in research from Sweden’s registry-based health system. A paper by Fyfe and colleagues in The BMJ tracked the medical records of 2,756,779 children born in Sweden between 1985 and 2020. The researchers noted that they excluded about 26 percent of children whose parents were not both born in Sweden.

The Swedish researchers noticed a substantial change in the male-to-female ratio. While young boys were still diagnosed at higher rates than young girls, the ratio inverted in late adolescence and early adulthood. By the 2020 to 2022 period, more females than males were being diagnosed between the ages of 15 and 24, with the numbers reaching parity at older ages. The researchers projected that the cumulative rate of diagnosis would reach parity between males and females by age 20 in the year 2024.

Debating the Drivers: Catch-Up or Threshold-Lowering?

Researchers disagree on how to interpret this changing demographic data. Fyfe and colleagues view the rising female diagnoses as a “catch-up” effect. They suggest that girls were historically underdiagnosed, and the medical field is now correcting that oversight.

Other researchers test similar ideas but arrive at different conclusions. Determining whether funding drives diagnosis is normally impossible, since no one can randomly assign a disability benefit to some regions and withhold it from others. Australia inadvertently ran the experiment anyway. The National Disability Insurance Scheme arrived region by region between 2013 and 2020, on a timetable set by negotiations between state and federal governments rather than by anything to do with local autism rates. Ranjan and Breunig, writing in the Journal of Health Economics, used that staggered rollout to compare regions where the scheme had arrived against regions still waiting. One of the authors disclosed being on unpaid leave from the agency administering the scheme.

Ranjan and Breunig found a regional difference-in-differences estimate of 0.56 percentage points. Extrapolated nationally against a counterfactual model, they estimated that the funding scheme accounted for a 32 percent increase in reported autism prevalence. The policy effect was actually larger in males than in females, concentrated in metropolitan areas, and did not result in an earlier age of diagnosis. Because of this pattern, they concluded that a lowered recognition threshold explains the data better than a female catch-up effect.

The Australian data also speaks to how funding shapes clinical practice. The researchers note that since 2018, more children have entered the scheme with an autism diagnosis than actually have a diagnosis from a Medicare-registered health professional, suggesting that assessments increasingly come from providers outside that system. One expert at the agency administering the scheme is quoted in the paper saying that the emerging business model relies on “rapid-fire private diagnoses in exchange for the agreement to provide services to individuals afterwards.”

Diagnostic Substitution and Changing Definitions

As the threshold for recognition lowers, the definitions in medical manuals have also evolved. A foundational review by Matson and Kozlowski in Research in Autism Spectrum Disorders points to the broadening of diagnostic criteria. The authors documented how the definition of autism expanded from the third to the fourth edition of the diagnostic manual, specifically with the addition of Asperger’s Disorder in 1994.

Writing in 2011, Matson and Kozlowski actually forecast that merging these subcategories in the upcoming fifth edition would push rates down, with people becoming seemingly cured of the condition. Ranjan and Breunig cite several international studies consistent with this prediction, showing that the fifth edition actually produced decreases or no change in the numbers diagnosed. In their reading, the definition changes in the 1990s drove much more of the initial expansion.

Matson and Kozlowski also point to a phenomenon called diagnostic substitution. Decades ago, a child with severe developmental delays might have received a generic label of intellectual disability. Today, that same child is much more likely to be assessed specifically for autism. Studies have tried to quantify both effects. King and Bearman attributed 26.4 percent of the California increase to criteria changes alone, while Coo found that one-third of British Columbia diagnoses between 1996 and 2004 involved a switch from another diagnostic category.

However, Ranjan and Breunig tested this substitution theory in their Australian data and found that it explains very little of the modern surge. When autism rates surged following the new funding scheme, intellectual disability diagnoses actually increased alongside them, and medicated ADHD rates fell only slightly. They conclude that doctors are not simply swapping labels, but are adding new diagnoses.

What Happens When You Screen Everyone

If researchers want to know whether the underlying occurrence of autism is changing, counting administrative medical records presents difficulties. A study by Kim and colleagues in JAMA Pediatrics takes a different approach, using a prospective design in which the screening and diagnostic methods stayed constant across all twelve birth cohorts. Because nothing about the measurement changed, the figures are comparable over time in a way that administrative counts are not.

Across twelve years, Kim and colleagues screened every seven-year-old entering elementary school in a single South Korean city, 62,081 children in total, rather than waiting for families to seek help. While only about 42 percent of screen-positive children completed the full clinical assessment, the researchers used machine learning models to estimate the status of the remaining children. When they looked at the total number of children who met the criteria for the condition, they found a prevalence of roughly 2 to 3 percent.

This number is far higher than the 1 percent median or 0.72 percent pooled average reported by Zeidan and Talantseva. Kim and colleagues attribute the difference to their case-finding method, which identified many children who had never come to clinical attention. The proportion of children meeting diagnostic criteria under constant measurement remained flat across the twelve cohorts, and the minor fluctuations they observed were not statistically significant.

The researchers did note that more children were moving from the “undiagnosed” group into the “diagnosed” group over time. They conclude that detection-related factors may contribute substantially to the increases reported by typical medical surveillance.

What Kind of Cases Are Driving the Rise?

A second line of evidence concerns the composition of the diagnosed population, which has changed as much as its size. If a new environmental exposure were causing a massive spike in autism, we would expect to see a rise across all levels of severity, including cognitively impaired cases.

In her paper in Psychological Medicine, Uta Frith notes Swedish data showing that the share of diagnosed cases with an intellectual disability fell from over 55 percent in 2001 to under seven percent in 2020. A review by Lyall and colleagues in the Annual Review of Public Health points out that intellectual disability historically accompanied about 70 percent of autism cases, but dropped to about 30 percent by 2012. Lyall and colleagues observe that much of the increase over the preceding decade occurred in milder cases, with less dramatic change in the prevalence of autism accompanied by intellectual disability.

The South Korean study by Kim and colleagues provides a related snapshot of their participants. They found that 33 percent of children who had been diagnosed through traditional medical services had an intellectual disability, compared to only 6 percent of the previously unidentified cases found through population screening.

Cultural Shifts and Diagnostic Drift

As the diagnosed population shifts toward milder presentations, society’s perception of autism has fundamentally changed. Frith argues that the concept of autism has become semantically unstable. She discusses how the neurodiversity movement has successfully reduced stigma, but also how social media has turned autism into a popular cultural identity.

Frith suggests that a concept called “looping” is occurring. As society redefines what autism looks like, people begin to interpret their own everyday struggles through that lens. While some argue that historical diagnostic criteria were based entirely on young boys, Frith pushes back on this pure male-norming account, noting that Temple Grandin has been a widely accepted prototype of the condition for decades.

A paper by Croce and Fusaro in Frontiers in Psychiatry provides a dual-risk framework for understanding this shift in adult clinics. They argue that under-diagnosis in women and minorities is a real problem, and recognizing the female phenotype is one of the major clinical achievements of the past fifteen years. At the same time, they warn of overdiagnosis in adults who might actually be experiencing personality disorders or complex trauma.

Croce and Fusaro describe a heuristic distillation of recent biological evidence, dividing the condition into two informal categories. They note that these types are dimensional rather than strict categories, with many intermediate cases, and they are not formally codified in diagnostic manuals. “Type I” represents the historical definition, which includes early childhood onset and a higher rate of genetic mutations. “Type II” represents a milder, polygenic form that overlaps heavily with general mental health conditions.

The authors note that the concept of “camouflaging” or masking social struggles is often used to diagnose women with autism. However, they cite research by Milner showing that camouflaging tracks a continuous trait dimension in individuals with high autistic traits but no formal diagnosis. It is not specific to autism. Because conditions like ADHD with affective dysregulation, complex PTSD, and borderline personality disorder also cause intense emotional reactions, sensory sensitivity, and social difficulties, they argue that doctors relying only on self-report questionnaires may mislabel patients.

What Croce and Fusaro Recommend

To address this diagnostic drift, Croce and Fusaro propose a set of minimum evidentiary standards for adult assessment. They argue that a proper evaluation requires a developmental history from two independent informants, multi-context behavioral observation, and neuropsychological profiling. They also recommend granular sensory assessment and a systematic consideration of alternative diagnoses, treating any autism diagnosis as revisable over time.

To ensure that uncertainty never becomes a denial of care, they propose stepped triage and parallel referral systems. For under-resourced services, they offer a scaled-down version of these standards. These recommendations aim to protect patients, as mislabeling in their view deprives individuals of the psychological treatments that would actually help them.

Risk Factors Versus Population Trends

When looking at the fraction of cases that might represent a true biological increase, it is important to distinguish between individual risk factors and population-level trends. A risk factor can be real and causal, but it will only drive a rising population trend if the exposure itself becomes more common.

Genetics play a massive role in who develops autism. A comprehensive review by Wang and Wang in All Life notes that the condition is estimated to be between 40 and 90 percent heritable. A paper by Love and colleagues in BMC Medicine similarly places the heritability estimate at around 50 percent.

Genetics and environment are not separate stories. Love and colleagues describe evidence that specific genetic variants may modify how prenatal exposures affect development, though they caution that only a handful of such studies exist and none has been replicated. This gene-environment interaction provides a bridge between inherited traits and outside influences.

Among the environmental risk factors these reviews identify, some have themselves become more common in recent decades. Lyall and colleagues describe advanced parental age as one of the most consistently replicated perinatal risk factors, with independent contributions from both mothers and fathers. Love and colleagues report that maternal obesity and gestational diabetes are each associated with increased odds of autism in offspring. All three have risen across the same populations and the same period in which diagnoses climbed.

Maternal Health and the Environment

The environment inside the womb is highly sensitive to changes in maternal health. Love and colleagues explore how severe infections during pregnancy can cause maternal immune activation. When a pregnant woman’s immune system fights an infection, her body releases proteins called cytokines. Excess cytokines can cross the placenta and enter the fetal brain, potentially altering how neural pathways form.

The authors also discuss how maternal obesity and gestational diabetes create a state of chronic, low-grade inflammation. This inflammation can disrupt the function of mitochondria, which are the energy-producing factories inside human cells. Because brain development requires massive amounts of energy, mitochondrial stress can have lasting impacts.

Outside the human body, a meta-analysis by Duque-Cartagena and colleagues in BMC Public Health reviewed studies looking at environmental pollutants. They found modest relative risks for nitrogen dioxide at 1.20 and copper at 1.08. The relative risk for PCB 138 was larger at 1.84 but had a wide confidence interval due to the low number of studies. Other findings, like mono-3-carboxypropyl phthalate and monobutyl phthalate, were reported as beta coefficients, while exposure to organophosphates and carbamates was negatively associated with the condition.

It is important to note, however, that the authors rated the certainty of evidence as low or very low across every analysis, citing massive variation between studies and a high risk of publication bias. They call for standardized exposure windows and detection methods before firmer conclusions can be drawn.

Causes That Have Been Tested and Not Supported

One environmental exposure attracts more public attention than any other. Lyall and colleagues summarize the historical evidence on vaccines, including multiple Institute of Medicine reports and independent reviews covering 67 studies. They state that there is no association between vaccines and autism.

Recent large-scale studies have reinforced these historical findings while finding no support for several other widely publicized suspects. A study by Burstain and colleagues in The Pediatric Infectious Disease Journal analyzed electronic health records from over 2.5 million American children to test whether receiving the measles, mumps, and rubella vaccine before age two was linked to childhood autism. Using an age-anchored design that compared vaccinated and unvaccinated children within specific developmental windows, the researchers found a hazard ratio of 0.97, which is not statistically distinguishable from no effect. “For the average person, this study can now say with very strong certainty that children in the US who receive the MMR vaccine between 11.5 and 24 months of age do not have any increased risk of developing autism,” Burstain told PsyPost.

Immunizations administered during pregnancy have similarly shown no link to developmental issues. A prospective study by Saade and Hughes in Pregnancy followed 434 toddlers divided into matched pairs based on whether their mothers received an mRNA COVID-19 vaccine during or shortly before gestation. At 18 to 30 months of age, the two groups had statistically equivalent scores on general developmental screenings and showed no statistical difference in autism risk on toddler checklists. “Neurodevelopment outcomes in children born to mothers who received the COVID-19 vaccine during or shortly before pregnancy did not differ from those born to mothers who did not receive the vaccine,” Saade explained.

Researchers have also scrutinized medications taken during pregnancy, such as specific types of antidepressants or antibiotics. In their review, Love and colleagues flag a major issue in this research called confounding by indication, where the underlying maternal illness rather than the treatment accounts for an apparent link. When studies adjust for a mother’s pre-existing psychiatric conditions, the association between antidepressants and autism weakens, and the fact that using these medications before conception is also associated with autism points to the maternal condition itself.

A cohort study by McIlvride and colleagues in PLOS Medicine examined this question by linking health and school records for 167,447 children in Wales to separate prenatal antidepressant prescriptions from maternal depression. When children of mothers with treated depression were compared directly to children of mothers with untreated depression, the differences in autism and ADHD rates were not statistically significant. “This study does not show that depression or antidepressant use during pregnancy causes autism or ADHD in children,” McIlvride told PsyPost, noting that any remaining association with broader educational needs could reflect the fact that “women who are taking antidepressants will have more severe depression.”

A similar problem of family and medical confounding explains the controversy surrounding prenatal acetaminophen, the active ingredient in Tylenol, which drew heightened scrutiny following federal announcements and proposed label updates linking the pain reliever to autism. An umbrella review by Tayebi-Hillali and colleagues in Developmental Medicine & Child Neurology synthesized seven meta-analyses encompassing over three million participants and reanalyzed the primary studies by their risk of bias. When the researchers restricted their analysis to high-quality studies with low bias, the risk ratio for autism dropped from 1.17 down to 1.05. “Associations that initially appeared consistent were substantially attenuated when we excluded lower-quality reviews and primary studies at higher risk of bias,” Tayebi-Hillali said, adding that “in observational studies, a risk ratio this small can readily be explained by bias, without the drug playing any role at all.”

To isolate the medication from shared genetics and household environment, a study by Luo and colleagues in JAMA Internal Medicine used a sibling-matched design, comparing 124,333 siblings in Hong Kong whose mothers were prescribed acetaminophen during one pregnancy but not another. Because siblings share a genetic background and home life, this approach holds constant the unmeasured family traits that distort standard comparisons across different households. While an unmatched comparison of the full population showed a slight increase in risk, the sibling analysis yielded a hazard ratio of 1.00 for autism, indicating no difference between exposed and unexposed siblings.

The researchers also ran a negative control analysis, checking whether maternal acetaminophen prescriptions in the year before pregnancy, when the drug could not directly affect a fetus, showed a similar statistical link. Finding the same apparent association before conception demonstrated that the signal was driven by confounding rather than the medication. “After accounting more closely for shared family factors, we found no evidence that acetaminophen use during pregnancy increased a child’s risk of autism or ADHD,” Luo and co-author Eric Yuk Fai Wan told PsyPost, concluding that the unadjusted link reflects “underlying characteristics of the women or families who use the medicine, rather than a direct effect of acetaminophen itself.”

Scientists have also investigated procedures performed on newborn boys, such as neonatal circumcision, following public speculation and older observational reports suggesting that surgical pain or infant acetaminophen use might raise autism rates. A study by McGrath and colleagues in JAMA Pediatrics tracked 2,771 boys across 14 U.S. sites and found that after adjusting for demographic and family factors, hospital circumcision within 28 days of birth was not associated with autism diagnoses or elevated behavioral scores. The researchers also noted that only 4 percent of circumcised infants with pain management records received acetaminophen during the procedure, making a pathway from the surgery through the pain reliever unlikely. “We observed no association between circumcision and autism in boys, but it remains important to evaluate the safety of common medical procedures,” McGrath said.

What These Studies Can and Cannot Show

These twenty papers span different countries, decades, health systems, and research designs, and none of them settles the question on its own. Yan’s figures come from parent report in a survey with roughly fifty percent response, while Fyfe’s cohort excludes about a quarter of Swedish births. Kim’s screening covers a single city, with machine learning filling in the status of children who did not complete assessment.

Other studies carry their own caveats. Duque-Cartagena and colleagues rate their pollutant evidence as low or very low certainty throughout, and observational studies of prenatal medications must rely on statistical adjustments because randomized trials in pregnant women are unethical. Ranjan and Breunig examine a funding scheme with no direct equivalent in most countries, meaning readers must weigh these methodological differences rather than simply averaging the results.

Synthesizing the Science

The medical and scientific communities are looking at the same rising numbers, but they interpret them in different ways. Authors like Frith and Croce argue that a portion of newly diagnosed people may not have the condition at all, and are being mislabeled at the cost of correct treatment. They suggest that diagnostic drift is pulling people with ADHD, complex trauma, or personality disorders into the autism spectrum.

Other researchers focus on the expansion of diagnostic boundaries in the 1990s and on shifting administrative practices. Several of these papers converge on a similar conclusion. Kim, Russell, Matson, Talantseva, and Ranjan each attribute most of the rising trend to some combination of better case-finding, financial incentives, expanded criteria, and a demographic shift toward adults and females. Notably, the review by Lyall and colleagues, which is frequently cited by those exploring environmental risk factors, explicitly attributes much of the reported increase to changes in reporting practices. The drop in the proportion of cases involving intellectual disability points in the same direction, though Russell and colleagues caution that an actual increase in autism incidence cannot be entirely ruled out.

At the same time, several of the exposures most often proposed in public debate, including childhood vaccines, prenatal pain relievers, and antidepressants, have now been examined in large cohorts and sibling-matched designs without finding support for a causal link. That narrows the range of biological explanations still in play, leaving rising factors like advanced parental age, maternal obesity, and systemic inflammation as the credible candidates for a modest increase in underlying risk. As science continues to refine how we measure both the environment and the human brain, the balance between shifting medical labels and biological changes will continue to come into sharper focus.

References

The paper, “Individualized disability support schemes and their impact on autism diagnoses,” was authored by Maathumai Ranjan and Robert Breunig (2026) in the Journal of Health Economics.

The paper, “The increasing prevalence of autism spectrum disorders,” was authored by Johnny L. Matson and Alison M. Kozlowski (2011) in Research in Autism Spectrum Disorders.

The paper, “Prevalence of Autism Spectrum Disorder Among Children and Adolescents in the United States from 2021 to 2022,” was authored by Xiaofang Yan, Yanmei Li, Qishan Li, Qian Li, Guifeng Xu, Jinhua Lu, and Wenhan Yang (2024) in the Journal of Autism and Developmental Disorders.

The paper, “The Changing Epidemiology of Autism Spectrum Disorders,” was authored by Kristen Lyall, Lisa Croen, Julie Daniels, M. Daniele Fallin, Christine Ladd-Acosta, Brian K. Lee, Bo Y. Park, Nathaniel W. Snyder, Diana Schendel, Heather Volk, Gayle C. Windham, and Craig Newschaffer (2017) in the Annual Review of Public Health.

The paper, “Global prevalence of autism: A systematic review update,” was authored by Jinan Zeidan, Eric Fombonne, Julie Scorah, Alaa Ibrahim, Maureen S. Durkin, Shekhar Saxena, Afiqah Yusuf, Andy Shih, and Mayada Elsabbagh (2022) in Autism Research.

The paper, “Autism spectrum disorder: has it lost its meaning and is it leading to misdiagnosis?,” was authored by Uta Frith (2026) in Psychological Medicine.

The paper, “Time trends in the male to female ratio for autism incidence: population based, prospectively collected, birth cohort study,” was authored by Caroline Fyfe, Henric Winell, Joseph Dougherty, David H Gutmann, Alexander Kolevzon, Natasha Marrus, Kristina Tedroff, Tychele N Turner, Lauren A Weiss, Benjamin H K Yip, Weiyao Yin, and Sven Sandin (2026) in The BMJ.

The paper, “Time trends in autism diagnosis over 20 years: a UK population-based cohort study,” was authored by Ginny Russell, Sal Stapley, Tamsin Newlove-Delgado, Andrew Salmon, Rhianna White, Fiona Warren, Anita Pearson, and Tamsin Ford (2022) in the Journal of Child Psychology and Psychiatry.

The paper, “Cumulative Incidence and Prevalence of Autism Spectrum Disorder,” was authored by Young Shin Kim, Xiao Liu, Joshua Chang, Yun-Joo Koh, Jihyun Kim, Yuji Choi, Yoon Jae Cho, Eric Fombonne, and Bennett L. Leventhal (2026) in JAMA Pediatrics.

The paper, “The global prevalence of autism spectrum disorder: A three-level meta-analysis,” was authored by Oksana I. Talantseva, Raisa S. Romanova, Ekaterina M. Shurdova, Tatiana A. Dolgorukova, Polina S. Sologub, Olga S. Titova, Daria F. Kleeva, and Elena L. Grigorenko (2023) in Frontiers in Psychiatry.

The paper, “Diagnostic inflation in autism spectrum disorder: an epistemological and methodological reappraisal,” was authored by Luigi Croce and Irene Fusaro (2026) in Frontiers in Psychiatry.

The paper, “Environmental pollutants as risk factors for autism spectrum disorders: a systematic review and meta-analysis of cohort studies,” was authored by Tatiana Duque-Cartagena, Marcello Dala Bernardina Dalla, Eduardo Mundstock, Felipe Kalil Neto, Sergio Angelo Rojas Espinoza, Sara Kvitko de Moura, Gabriele Zanirati, Alexandre Vontobel Padoin, Juan Gabriel Piñeros Jimenez, Airton Tetelbom Stein, Wilson Cañon-Montañez, and Rita Mattiello (2024) in BMC Public Health.

The paper, “Prenatal environmental risk factors for autism spectrum disorder and their potential mechanisms,” was authored by Chloe Love, Luba Sominsky, Martin O’Hely, Michael Berk, Peter Vuillermin, and Samantha L. Dawson (2024) in BMC Medicine.

The paper, “The growing challenge of autism spectrum disorder: a comprehensive review of etiology, diagnosis, and therapy in children,” was authored by Chunyuan Wang and Hong Wang (2024) in All Life.

The paper, “Association Between First MMR Vaccination Before Age 2 Years and Childhood Autism in a U.S. EHR Cohort of 2.5 Million Children,” was authored by Todd L. Burstain, Dale Jacques, and Jennifer M. Burstain (2026) in The Pediatric Infectious Disease Journal.

The paper, “Neonatal Medical Male Circumcision and Child Autism Diagnosis,” was authored by Monica McGrath, Xiuhong Li, Lisa P. Jacobson, Bennett Leventhal, Judy L. Aschner, Brennan Baker, Karla Cardoso Garcia, Aisha S. Dickerson, Amy J. Elliott, Jody Ganiban, Amanda Goodrich, Daniel B. Horton, Melinda Jarnecke, Sarah Keim, Brian K. Lee, Courtney D. Lynch, Mark Klebanoff, Abdul-Manaf Mutaru, Ruby H. N. Nguyen, Rebecca J. Schmidt, Hyeong-Moo Shin, Lauren C. Shuffrey, Jonathan L. Slaughter, Annemarie Stroustrup, Zhaozhong Zhu, Aaron A. R. Tobian, and M. Kate Grabowski (2026) in JAMA Pediatrics.

The paper, “Prenatal exposure to maternal depression and antidepressants and neurodevelopmental outcomes: A population cohort study,” was authored by Saraid McIlvride, Neha Rao, Sarjit Singh, Scott M. Nelson, Jill P. Pell, and Michael Fleming (2026) in PLOS Medicine.

The paper, “Prenatal exposure to paracetamol and the risk of autism and attention-deficit/hyperactivity disorder: An umbrella review and meta-meta-analysis,” was authored by Hoda Tayebi-Hillali, María Blanco-Suárez, Berta Rivas-Mundiña, Jacobo Limeres-Posse, Márcio Diniz-Freitas, and Pedro Diz-Dios (2026) in Developmental Medicine & Child Neurology.

The paper, “Prenatal Acetaminophen (Paracetamol) Use and the Risk of Autism and/or Attention-Deficit/Hyperactivity Disorder Among Sibling-Matched Cohorts,” was authored by Shan Luo, Qiaowa Gong, Yujie Ai, Jiayue Zhang, Linda Chan, William Chi Wai Wong, Patrick Ip, Esther Wai Yin Chan, Peter Tanuseputro, Ian Chi Kei Wong, and Eric Yuk Fai Wan (2026) in JAMA Internal Medicine.

The paper, “Association Between SARS-CoV-2 Vaccine in Pregnancy and Child Neurodevelopment at 18–30 Months,” was authored by George R. Saade and Brenna L. Hughes (2026) in Pregnancy.