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October 29, 2024
Attention-Deficit/Hyperactivity Disorder (ADHD) remains a prevalent condition among children and adolescents in the United States. A recent analysis based on the National Health Interview Survey (NHIS), conducted by the National Center for Health Statistics at the CDC, provides an updated look at ADHD prevalence from 2018 to 2021. Here’s a closer look at what the data reveals.
The NHIS is an annual survey primarily conducted through face-to-face interviews in respondents’ homes. Telephone interviews are used as a substitute in cases where travel is impractical. For each family interviewed, one child aged 3-17 is randomly selected for the survey through a computer program. Over the four years studied (2018-2021), a total of 26,422 households with children or adolescents participated.
The analysis found that 9.5% of children and adolescents in the United States had been diagnosed with ADHD, based on reports from family members. However, the prevalence varied significantly with age:
The increase in ADHD diagnosis with age underscores the importance of monitoring children’s developmental needs as they progress through school and adolescence.
The survey revealed a notable difference in ADHD prevalence between genders, with 12.4% of males diagnosed compared to 6.6% of females—nearly a two-to-one gap. This aligns with previous research indicating that ADHD is more frequently diagnosed in boys than girls, though awareness of how ADHD presents differently across genders is growing.
Family income played a significant role in ADHD prevalence, particularly among lower-income groups:
This pattern suggests that socioeconomic factors might influence the diagnosis and management of ADHD, with lower-income families possibly experiencing greater barriers to early diagnosis or consistent treatment.
Geographic location also impacted ADHD rates. Prevalence was highest in the South (11.3%), followed by the Midwest (10%), the Northeast (9.1%), and significantly lower in the West (6.9%). These variations could reflect regional differences in healthcare access, diagnostic practices, or cultural attitudes towards ADHD.
Despite these variations in demographics, the overall prevalence of ADHD remained relatively stable across the study period from 2018 to 2021, showing no significant changes by year.
The findings from this updated analysis provide a clearer picture of ADHD’s prevalence across different demographic groups in the United States. They highlight the need for tailored approaches to diagnosis and care, taking into account factors like age, gender, income, and geographic location. With ADHD being a common condition affecting nearly 1 in 10 children, ongoing research and support for families are crucial to ensure that those with ADHD receive the care and resources they need.
This study reinforces the importance of awareness and early intervention, especially for families in underserved regions or those facing economic challenges. As clinicians and educators continue to support children with ADHD, understanding these demographic trends can help in creating more equitable access to diagnosis and treatment.
Qian Li, Yanmei Li, Juan Zheng, Xiaofang Yan, Jitian Huang, Yingxia Xu, Xia Zeng, Tianran Shen, Xiaohui Xing, Qingsong Chen, and Wenhan Yang, “Prevalence and trends of developmental disabilities among US children and adolescents aged 3 to 17 years, 2018–2021,” Scientific Reports (2023) 13: 17254, https://doi.org/10.1038/s41598-023-44472-1.
A transcontinental study team (California, Texas, Florida) used a nationally representative sample – the 2018 National Survey of Children’s Health – to query 26,205 caregivers of youth aged 3 to 17 years old to explore inequities in ADHD diagnosis.
With increasing accessibility of the internet in the U.S., more than 80% of adults now search for health information online. Recognizing that search engine data could help clarify patterns of inequity, the team also consulted Google Trends.
The team noted at the outset that “[d]ocumenting the true prevalence of ADHD remains challenging in light of problems of overdiagnosis (e.g., following quick screening rather than full evaluation incorporating multi-informant and multi-method data given limited resources) and underdiagnosis (e.g., reflecting inequities in healthcare and education systems).” Underdiagnosis is known to be influenced by lack or inadequacy of health insurance, inadequate public health funding, stigma, sociocultural expectations in some ethnic groups, and structural racism, among other factors.
After controlling for poverty status, highest education in household, child’s sex, and child’s age, the team reported that Black youth were a quarter (22%) less likely to receive ADHD diagnoses than their white peers. Latino/Hispanic youth were a third (32%) less likely and Asian youth three-quarters (73%) less likely to receive ADHD diagnoses than their white peers.
The team also found that state-level online search interest in ADHD was positively associated with ADHD diagnoses, after controlling for race/ethnicity, poverty status, highest education in household, child’s sex, and child’s age. However, the odds ratio was low (1.01), “suggesting the need for additional evaluation.” Furthermore, “There was no interaction between individual-level racial/ethnic background and state-level information-seeking patterns. … the state-level online information-seeking variation did not affect the odds that youth of color would have a current ADHD diagnosis over and above other included characteristics.”
That could be due in part to the gap in high-speed broadband access between Black and Hispanic in contrast to white populations, but that would not explain the even larger gaps in diagnosis for Asian youth, who tend to come from more prosperous backgrounds.
The team concluded, “Persistent racial/ethnic inequities warrant systematic changes in policy and clinical care that can attend to the needs of underserved communities. The digital divide adds complexity to persistent racial/ethnic and socioeconomic inequities in ADHD diagnosis …”
A cohort study looked at over five million adults, and over 850,000 children between the ages of five and eleven, who received care at Kaiser Permanente Northern California during the ten-year period from the beginning of 2007 through the end of 2016. At any given time, KPNC serves roughly four million persons. It is representative of the population of the region, except for the highest and lowest income strata.
Among adults rates of ADHD diagnosis rose from 0.43% to 0.96%. Among children the diagnosis rates rose from 2.96% to 3.74%, ending up almost four times as high as for adults.
Non-Hispanic whites had the highest adult rates throughout, increasing from 0.67% in 2007 to 1.42% in 2016. American Indian or Alaska Native (AIAN) had the second highest rates, rising from 0.56% to 1.14%. Blacks and Hispanics had roughly comparable rates of diagnosis, the former rising from 0.22% to 0.69%, the latter from 0.25% to 0.65%. The lowest rates were among Asians (rising from 0.11% to 0.35%) and Native Hawaiian or other Pacific Islanders (increasing from 0.11% to 0.39%).
Odds of diagnosis dropped steeply with age among adults. Relative to 18-24-year-olds, 25-34-year-olds were 1/6th less likely to be diagnosed with ADHD, 35-44-year-olds 1/3rd less likely, 45-54-year-olds less than half as likely, 55-64-year-olds less than a quarter as likely, and those over 65 about a twentieth as likely. This is consistent with other studies reporting and age dependent decline in the diagnosis.
Adults with the highest levels of education were twice as likely to be diagnosed as those with the lowest levels. But variations in median household income had almost no effect. Women were marginally less likely to be diagnosed than men.
ADHD is associated with some other psychiatric disorders. Compared with normally developing adults, and adjusted for confounders, those with ADHD were five times as likely to have an eating disorder, over four times as likely to be diagnosed with bipolar disorder or depression, more than twice as likely to suffer from anxiety, but only slightly more likely to abuse drugs or alcohol.
The authors speculate that rising rates of diagnosis could reflect increasing recognition of ADHD in adults by physicians and other clinicians as well as growing public awareness of ADHD during the decade under study. Turning to the strong differences among ethnicities, they note, Racial/ethnic differences could also reflect differential rates of treatment seeking or access to care. Racial/ethnic background is known to play an important role in opinions on mental health services, health care utilization, and physician preferences. In addition, rates of diagnosis- seeking to obtain stimulant medication for nonmedical use may be more common among white vs nonwhite patients. They conclude, greater consideration must be placed on cultural influences on health care seeking and delivery, along with an increased understanding of the various social, psychological, and biological differences among races/ethnicities as well as culturally sensitive approaches to identify and treat ADHD in the total population.
But the main take home message of this work is that most cases of ADHD in adults are not being diagnosed by clinicians. We know from population studies, worldwide, that about three percent of adults suffer from the disorder. This study found that less than 1 percent are diagnosed by their doctors. Clearly, more education is needed to teach clinicians how to identify, diagnose and treat ADHD in adults.
There is a well-documented gap between the known prevalence of adult ADHD and rates of diagnosis and treatment. In Germany, epidemiological studies of nationally representative community samples have found prevalence rates ranging from 3.1% to 4.7%. Yet, studies of publicly insured individuals aged 18 to 69 years old report rates of diagnosed ADHD between 0.04% and 0.4%. So, even in a country with universal health insurance, more than nine out of ten adults with ADHD go undiagnosed.
Many factors contribute to under-diagnosis: stigma, culturally influenced perceptions, and lack of motivation by those affected. Another crucial factor is the lack of recognition of ADHD symptoms by clinicians.
A research team surveyed 144 psychologists, 32 physicians, and two occupational therapists. Almost three in five participants were psychotherapists, a quarter were neuropsychologists, and one in seven were psychiatrists.
Four out of five clinicians stated they had received only a few hours of ADHD-specific training. One in four stated they had not examined guidelines for diagnosing ADHD. A lack of formal training among the vast majority, and unfamiliarity with current diagnostic guidelines in a significant minority, were surprising findings among clinicians who regularly work with adults with ADHD.
Many clinicians had difficulty identifying core features of adult ADHD as defined by the DSM-5 and International Classification of Diseases, Tenth Revision (ICD-10). Roughly one in five stated that hyperactivity had little relevance to adult ADHD. The only core feature correctly identified by more than half the respondents was having difficulties concentrating. Impairments in social behavior or aggression and memory impairment were not identified as being clearly relevant or irrelevant to adult ADHD.
The authors concluded that these findings appear to indicate some uncertainty or at least a lack of consensus among clinicians about what symptoms are relevant to ADHD in adulthood, and it is likely that this uncertainty contributes to diagnostic inaccuracy.
Most respondents reported using self-report scales of ADHD symptoms and using unstructured interviews. While slightly more than half agreed that collateral reports are important to diagnosis, only about a third reported regularly using them. This is a problem given the limited accuracy of self-reported childhood symptoms for documenting the childhood-onset of the disorder. Semi-structured interviews are also known to improve the accuracy of diagnosis, but are rarely used in clinical practice.
Over half of psychologists and a quarter of physicians reported using cognitive or neuropsychological testing, even though this is at variance with German (and other) guidelines, which specify that such testing is suitable for clarifying strengths and weaknesses, but not for ruling out or confirming a diagnosis of ADHD. The European Consensus Statement also states that cognitive/neuropsychological testing should only be used as a secondary or supplementary assessment tool.
While three out of four clinicians recommended stimulant drug treatment, psychologists tended to be more hesitant to do so. This is likely because German psychologists receive little training in pharmacotherapy, and do not have prescription privileges. Given the demonstrated efficacy of stimulant treatment, this points to a need to better educate psychologists in this regard.
Almost three in four respondents cited a lack of clinician knowledge and experience as a barrier to ADHD diagnosis. Most clinicians also stated they were either uncertain or only somewhat certain of their ability to diagnose ADHD. That suggests that more extensive ADHD-specific training is needed.
A limitation of the survey was the relatively low participation by physicians. It is also likely that the findings are not reflective of practices in ADHD specialty clinics.
The authors concluded, Further training is needed to improve clinicians' understanding of ADHD in adulthood and to align diagnostic practices with guideline recommendations. Whereas discrepancies between respondents regarding the relative importance of peripheral symptoms (e.g., memory problems) were most common, a lack of consensus was found even for core symptoms listed by diagnostic criteria. Particularly among psychologists improved awareness regarding the benefits of stimulant medications is needed to bring their treatment recommendations in line with evidence-based guidelines.
A recent Wall Street Journal article raised alarms by concluding that many children who start medication for ADHD will later end up on several psychiatric drugs. It’s an emotional topic that will make many parents, teachers, and even doctors worry: “Are we putting kids on a conveyor belt of medications?”
The article seeks to shine a light on the use of more than one psychiatric medication for children with ADHD. My biggest worry about the article is that it presents itself as a scientific study because they analyzed a database. It is not a scientific study. It is a journalistic investigation that does not meet the standards of a scientific report..
The WJS brings attention to several issues that parents and prescribers should think about. It documents that some kids with ADHD are on more than one psychiatric medication, and some are receiving drugs like antipsychotics, which have serious side effects. Is that appropriate? Access to good therapy, careful evaluation, and follow-up care can be lacking, especially for low-income families. Can that be improved? On that level, the article is doing something valuable: it’s shining a spotlight on potential problems.
It is, of course, fine for a journalist to raise questions, but it is not OK for them to pretend that they’ve done a scientific investigation that proves anything. Journalism pretending to be science is both bad science and bad journalism.
Journalism vs. Science: Why Peer Review Matters
Journalists can get big datasets, hire data journalists, and present numbers that look scientific. But consider the differences between Journalism and Science. These types of articles are usually checked by editors and fact-checkers. Their main goals are:
Is this fact basically correct?
Are we being fair?
Are we avoiding legal problems?
But editors are not qualified to evaluate scientific data analysis methods. Scientific reports are evaluated by experts who are not part of the project. They ask tough questions like:
Exactly how did you define ADHD?
How did you handle missing data?
Did you address confounding?
Did you confuse correlation with causation?
If the authors of the study cannot address these and other technical issues, the paper is rejected.
The WSJ article has the veneer of science but lacks its methodology.
Correlation vs. Causation: A Classic Trap
The article’s storyline goes something like this: A kid starts ADHD medication. She has additional problems or side effects caused by the ADHD medications. Because of that, the prescriber adds more drugs. That leads to the patient being put on several drugs. Although it is true that some ADHD youth are on multiple drugs, the WSJ is wrong to conclude that the medications for ADHD cause this to occur. That simply confuses correlation with causation, which only the most naïve scientist would do.
In science, this problem is called confounding. It means other factors (like how severe or complex a child’s condition is) explain the results, not just the thing we’re focused on (medication for ADHD).
The WSJ analyzed a database of prescriptions. They did not survey the prescribers who made the prescriptions of the patients who received them. So they cannot conclude that ADHD medication caused the later prescriptions, or that the later medications were unnecessary or inappropriate.
Other explanations are very likely. It has been well documented that youth with ADHD are at high risk for developing other disorders such as anxiety, depression, and substance use. The kids in the WSJ database might have developed these disorders and needed several medications. A peer-reviewed article in a scientific journal would be expected to adjust for other diagnoses. If that is not possible, as it is in the case of the WSJ’s database, a journal would not allow the author to make strong conclusions about cause-and-effect.
Powerful Stories Don’t Always Mean Typical Stories
The article includes emotional accounts of children who seemed harmed by being put on multiple psychiatric drugs. Strong, emotional stories can make rare events feel common. They also frighten parents and patients, which might lead some to decline appropriate care.
These stories matter. They remind us that each data point is a real person. But these stories are the weakest form of data. They can raise important questions and lead scientists to design definitive studies, but we cannot use them to draw conclusions about the experiences of other patients. These stories serve as a warning about the importance of finding a qualified provider, not as against the use of multiple medications. That decision should be made by the parent or adult patient based on an informed discussion with the prescriber.
Many children and adults with ADHD benefit from multiple medications. The WSJ does not tell those stories, which creates an unbalanced and misleading presentation.
Newspapers frequently publish stories that send the message: “Beware! Doctors are practicing medicine in a way that will harm you and your family.” They then use case studies to prove their point. The title of the article is, itself, emotional clickbait designed to get more readers and advertising revenue. Don’t be confused by such journalistic trickery.
What Should We Conclude?
Here’s a balanced way to read the article. It is true that some patients are prescribed more than one medication for mental health problems. But the article does not tell us whether this prescribing practice is or is not warranted for most patients. I agree that the use of antipsychotic medications needs careful justification and close monitoring. I also agree that patients on multiple medications should be monitored closely to see if some of the medications can be eliminated. Many prescribers do exactly that, but the WSJ did not tell their stories.
It is not appropriate to conclude that ADHD medications typically cause combined pharmacotherapy or to suggest that combined pharmacotherapy is usually bad. The data presented by the WSJ does not adequately address these concerns. It does not prove that medications for ADHD cause dangerous medication cascades.
We have to remember that even when a journalist analyzes data, that is not the same as a peer-reviewed scientific study. Journalism pretending to be science is both bad science and bad journalism.
Oppositional Defiant Disorder (ODD)—a pattern of chronic irritability, anger, arguing, or defiance—is one of the most challenging behavioral conditions families and clinicians face.
A new study involving 2,400 children ages 3–17 offers one of the clearest pictures yet. Using parent-reported data from the Pediatric Behavior Scale, researchers compared how often ODD appears in Autism spectrum disorder (ASD), ADHD-Combined presentation (ADHD-C), ADHD-Inattentive presentation (ADHD-I), and those with both ASD and ADHD.
Results:
Children with ADHD-Combined presentation show both hyperactivity/impulsivity and inattention. They had the highest ODD rates of any single diagnosis: 53% of kids with ADHD-Combined met criteria for ODD.
But when autism was added to ADHD-Combined, the prevalence jumped to 62%. This group also had the highest overall ODD scores, suggesting more severe or more impairing symptoms.
This synergy matters: while autism alone increases ODD risk, the presence of ADHD-Combined is what pushes prevalence into the majority range. Other groups showed lower, but still significant, rates of ODD:
These findings echo what clinicians often see: children with inattentive ADHD, while struggling significantly with attention and learning, tend to show fewer behavioral conflict patterns than those with hyperactive/impulsive symptoms.
It is important to note that ODD is considered to have two main components. Across all diagnostic groups, ODD consistently broke down into these two components: either Irritable/Angry (emotion-based) or Oppositional/Defiant (behavior-based). But the balance between these components differed depending on diagnosis. Notably, Autism + ADHD-Combined showed higher levels of the irritable/angry component than ADHD-Combined alone. The oppositional/defiant component did not differ much between groups. This suggests that autism elevates the emotional side of ODD more than the behavioral side, which is important for clinicians to note before tailoring interventions.
The study notes that autism, ADHD, and ODD often cluster together, with 55–90% comorbidity in some combinations.
As the authors explain, “The high co-occurrence of ADHD-Combined in autism (80% in our study) largely explains the high prevalence of ODD in autism.”
Clinical Implications: Why This Study Matters
The researchers point to a straightforward recommendation: clinicians shouldn’t evaluate these conditions in isolation. A child referred for autism concerns might also be struggling with ADHD. A child referred for ADHD might have undiagnosed ODD. And ignoring one disorder can undermine treatment for the others.
Evidence-based interventions (behavioral therapy, parent training, school supports, and/or medication) can reduce symptoms across all three diagnoses while improving long-term outcomes, including overall quality of life.
Background:
Sleep is more than simple rest. When discussing sleep, we tend to focus on the quantity rather than the quality, how many hours of sleep we get versus the quality or depth of sleep. Duration is an important part of the picture, but understanding the stages of sleep and how certain mental health disorders affect those stages is a crucial part of the discussion.
Sleep is an active mental process where the brain goes through distinct phases of complex electrical rhythms. These phases can be broken down into non-rapid eye movement (NREM) and rapid eye movement (REM). The non-rapid eye movement phase consists of three stages of the four stages of sleep, referred to as N1, N2(light sleep), and N3(deep sleep). N4 is the REM phase, during which time vivid dreaming typically occurs.
Two of the most important measurable brain rhythms occur during non-rapid eye movement (NREM) sleep. These electrical rhythms are referred to as slow waves and sleep spindles. Slow waves reflect deep, restorative sleep, while spindles are brief bursts of brain activity that support memory and learning.
The Study:
A new research review has compiled data on how these sleep oscillations differ across psychiatric conditions. The findings suggest that subtle changes in nightly brain rhythms may hold important clues about a range of disorders, from ADHD to schizophrenia.
The Results:
People with ADHD showed increased slow-spindle activity, meaning those brief bursts of NREM activity were more frequent or stronger than in people without ADHD. Why this happens isn’t fully understood, but it may reflect differences in how the ADHD brain organizes information during sleep. Evidence for slow-wave abnormalities was mixed, suggesting that deep sleep disruption is not a consistent hallmark of ADHD.
Among individuals with autism spectrum disorder (ASD), results were less consistent. However, some studies pointed to lower “spindle chirp” (the subtle shift in spindle frequency over time) and reduced slow-wave amplitude. Lower amplitude suggests that the brain’s deep-sleep signals may be weaker or less synchronized. Researchers are still working to understand how these patterns relate to sensory processing, learning differences, or daytime behavior.
People with depression tended to show reduced slow-wave activity and fewer or weaker sleep spindles, but this pattern appeared most strongly in patients taking antidepressant medications. Since antidepressants can influence sleep architecture, researchers are careful not to overinterpret the changes. Nevertheless, these changes raise interesting questions about how both depression and its treatments shape the sleeping brain.
In post-traumatic stress disorder (PTSD), the trend moved in the opposite direction. Patients showed higher spindle frequency and activity, and these changes were linked to symptom severity which suggests that the brain may be “overactive” during sleep in ways that relate to hyperarousal or intrusive memories. This strengthens the idea that sleep physiology plays a role in how traumatic memories are processed.
The clearest and most reliable findings emerged in psychotic disorders, including schizophrenia. Across multiple studies, individuals showed: Lower spindle density (fewer spindles overall), reduced spindle amplitude and duration, correlations with symptom severity, and cognitive deficits.
Lower slow-wave activity also appeared, especially in the early phases of illness. These results echo earlier research suggesting that sleep spindles, which are generated by thalamocortical circuits, might offer a window into the neural disruptions that underlie psychosis.
The Take-Away:
The review concludes with a key message: While sleep disturbances are clearly present across psychiatric conditions, the field needs larger, better-standardized, and more longitudinal studies. With more consistent methods and longer follow-ups, researchers may be able to determine whether these oscillations can serve as reliable biomarkers or future treatment targets.
For now, the take-home message is that the effects of these mental health disorders on sleep are real and measurable.
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