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May 28, 2025
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The U.S. government released a sweeping document titled The MAHA Report: Making Our Children Healthy Again, developed by the President’s “Make America Healthy Again” Commission. Chaired by public figures and physicians with ties to the current administration, the report presents a broad diagnosis of what it calls a national health crisis among children. It cites rising rates of obesity, diabetes, allergies, mental illness, neurodevelopmental disorders, and chronic disease as signs of a generation at risk.
The report's overarching goal is to shift U.S. health policy away from reactive, pharmaceutical-based care and toward prevention, resilience, and long-term well-being. It emphasizes reforming the food system, reducing environmental chemical exposure, addressing lifestyle factors like physical inactivity and screen overuse, and rethinking what it calls the “overmedicalization” of American children.
While some of the report’s arguments are steeped in political rhetoric and controversial claims—particularly around vaccines and mental health diagnoses—others are rooted in well-established public health science. This blog aims to highlight where the MAHA Report gets the science right, especially as it relates to childhood health and ADHD.
Although the MAHA Report contains several debatable assertions, it also outlines six key public health priorities that are well-supported by decades of research. If implemented thoughtfully, these recommendations might make a meaningful difference in the health of American children:
Reduce Ultra-Processed Food (UPF) Consumption
UPFs now make up nearly 70% of children’s daily calories. These foods are high in added sugars, refined starches, unhealthy fats, and chemical additives, but low in nutrients. Studies—including a 2019 NIH-controlled feeding study—show that UPFs promote weight gain, overeating, and metabolic dysfunction. What can help: Tax incentives for fresh food retailers, improved school meals, front-of-pack labeling, and food industry regulation.
Promote Physical Activity and Limiting Sedentary Time
Most American children don’t get the recommended 60 minutes of physical activity per day. This contributes to obesity, cardiovascular risk, and even mental health issues. Physical activity is known to improve attention, mood, sleep, and self-regulation. What can help: Mandatory daily PE, school recess policies, walkable community infrastructure, and screen-time education.
Addressing Sleep Deprivation
Teens today sleep less than they did a decade ago, in part due to screen use and early school start times. Sleep loss is linked to depression, suicide risk, poor academic performance, and metabolic problems. What can help: Later school start times, family education about sleep hygiene, and limits on evening screen exposure.
Improving Maternal and Early Childhood Nutrition
The report indirectly supports actions that are backed by strong evidence: encouraging breastfeeding, supporting maternal whole-food diets, and improving infant nutrition. These are known to reduce chronic disease risk later in life.
ADHD is one of the most discussed neurodevelopmental disorders in the MAHA Report, but many of its claims about ADHD are misleading, oversimplified, or inconsistent with decades of scientific evidence, much of which is described in the International Consensus Statement on ADHD, and other references given below.
This is true. Diagnosis rates have risen over the past two decades, due in part to better recognition, broadened diagnostic criteria, and changes in healthcare access. Diagnosis rates in some parts of the country are too high, but we don’t know why. That should be addressed and investigated. MAHA attributes increasing diagnoses to ‘overmedicalization’. That is a hypothesis worth testing but not a conclusion we can draw from available data.
These have been associated with ADHD but have not been documented as causes. ADHD is highly heritable, with genetic factors accounting for 70–80% of the risk. Unlike genetic studies, environmental risk studies are compromised by confounding variables. There are good reasons to address these issues but doing so is unlikely to reduce diagnostic rates of ADHD.
❌ Inaccurate: ADHD medications don’t work long-term.
The report criticizes stimulant use but fails to note that ADHD medications are among the most effective psychiatric treatments, especially when consistently used. They cite the MTA study’s long term outcome study of kids assigned to medication vs. placebo as showing medications don’t work in the long term. But that comparison is flawed because during the follow-up period, many kids on medication stopped taking them and many on placebo started taking medications. Many studies document that medications for ADHD protect against many real-world outcomes such as accidental injuries, substance abuse and even premature death.
Despite the issues discussed above, the MAHA Report can indirectly help children and adults with ADHD by pushing for systemic changes that reduce ultra-processed food consumption, increase physical activity, and motivate better sleep practices.
In other words, you don’t need to reject the diagnosis of ADHD to support broader changes in how we feed, educate, and care for children. A more supportive, less toxic environment benefits everyone—including those with ADHD.
The MAHA Report; https://www.whitehouse.gov/wp-content/uploads/2025/05/WH-The-MAHA-Report-Assessment.pdf
The World Federation of ADHD International Consensus Statement: 208 Evidence-based conclusions about the disorder. Neuroscience and Biobehavioral Reviews, Sept 2021, Issue 128, pages 789-818. doi: 10.1016/j.neubiorev.2021.01.02
Faraone SV, Bellgrove MA, Brikell I, et al. Attention-deficit/hyperactivity disorder. Nat Rev Dis Primers 2024; 10(1): 11.
Faraone SV. Understanding Environmental Exposures and ADHD: a Pathway Forward. Prev Sci 2024.
Perfluoroalkylated substances (PFASs), commonly known as "forever chemicals" in the media, are pollutants that do not break down in the environment. Their chemical structure includes fluorine atoms bonded to carbon, which makes them effective at repelling water. This property has led to their use in water-repellent clothing, stain-resistant carpets and furniture, and nonstick cookware.
However, the same chemical structure that makes PFASs useful also makes them a concern for human and animal health, as there are no natural biological processes to remove them from the body. Once ingested, they accumulate and become more concentrated at each level of the food chain. PFASs can also cross the placental barrier, raising concerns about potential harm to developing embryos and fetuses.
A Chinese research team conducted a systematic review of the medical literature to examine if there is a link between maternal exposure to PFASs and an increased risk of ADHD in children. They analyzed data from several studies:
- A meta-analysis of five studies involving 2,513 mother-child pairs found no increase in ADHD risk from exposure to PFOA (perfluorooctanoate) or PFOS (perfluorooctane sulfonate). The consistency across these studies was high, with little variation and no evidence of publication bias.
- Another meta-analysis of three studies with 995 mother-child pairs also showed no increase in ADHD risk from exposure to PFNA (perfluorononanoate) or PFHxS (perfluorohexane sulfonate), with similarly negligible variation between studies and no publication bias.
- In an analysis comparing the highest and lowest quartiles of maternal exposure, a slight increase in ADHD risk was observed with PFOA exposure, while a slight decrease was noted with PFOS exposure. Both findings were marginally significant and may be due to the small sample sizes.
The researchers concluded that more studies are needed to confirm these findings due to the limited evidence available.
This New York Times article, “5 Takeaways from New Research about ADHD”, earns a poor grade for accuracy. Let’s break down their (often misleading and frequently inaccurate) claims about ADHD.
The Claim: A.D.H.D. is hard to define/ No ADHD Biomarkers exist
The Reality: The claim that ADHD is hard to define “because scientists haven’t found a single biological marker” is misleading at best. While it is true that no biomarker exists, decades of rigorous research using structured clinical interviews and standardized rating scales show that ADHD is reliably diagnosed. Decades of validation research consistently show that ADHD is indeed a biologically-based disorder. One does not need a biomarker to draw that conclusion and recent research about ADHD has not changed that conclusion.
Additionally, research has in fact confirmed that genetics do play a role in the development of ADHD and several genes associated with ADHD have been identified.
The Claim: The efficacy of medication wanes over time
The Reality: The article’s statement that medications like Adderall or Ritalin only provide short-term benefits that fade over time is wrong. It relies almost entirely on one study—the Multimodal Treatment Study of ADHD (MTA). In the MTA study, the relative advantage of medication over behavioral treatments diminished after 36 months. This was largely because many patients who had not initially been given medication stopped taking it and many who had only been treated with behavior therapy suddenly began taking medication. The MTA shows that patients frequently switched treatments. It does not overturn other data documenting that these medications are highly effective. Moreover, many longitudinal studies clearly demonstrate sustained benefits of ADHD medications in reducing core symptoms, psychiatric comorbidity, substance abuse, and serious negative outcomes, including accidents, and school dropout rates. A study of nearly 150,000 people with ADHD in Sweden concluded “Among individuals diagnosed with ADHD, medication initiation was associated with significantly lower all-cause mortality, particularly for death due to unnatural causes”. The NY Times’ claim that medications lose their beneficial effects over time ignores compelling evidence to the contrary.
The Claim: Medications don’t help children with ADHD learn
The Reality: ADHD medications are proven to reliably improve attention, increase time spent on tasks, and reduce disruptive behavior, all critical factors directly linked to better academic performance.The article’s assertion that ADHD medications improve only classroom behavior and do not actually help students learn also oversimplifies and misunderstands the research evidence. While medication alone might not boost IQ or cognitive ability in a direct sense, extensive research confirms significant objective improvements in academic productivity and educational success—contrary to the claim made in the article that the medication’s effect is merely emotional or perceptual, rather than genuinely educational.
For example, a study of students with ADHD who were using medication intermittingly concluded “Individuals with ADHD had higher scores on the higher education entrance tests during periods they were taking ADHD medication vs non-medicated periods. These findings suggest that ADHD medications may help ameliorate educationally relevant outcomes in individuals with ADHD.”
The Claim: Changing a child’s environment can change his or her symptoms.
The Reality: The Times article asserts that ADHD symptoms are influenced by environmental fluctuations and thus might not have their roots in neurobiology. We have known for many years that the symptoms of ADHD fluctuate with environmental demands. The interpretation of this given by the NY Times is misleading because it confuses symptom variability with underlying causes. Many disorders with well-established biological origins are sensitive to environmental factors, yet their biology remains undisputed.
For example, hypertension is unquestionably a biologically based condition involving genetic and physiological factors. However, it is also well-known that environmental stressors, dietary
habits, and lifestyle factors can significantly worsen or improve hypertension. Similarly, asthma is biologically rooted in inflammation and airway hyper-reactivity, but environmental triggers such as allergens, pollution, or even emotional stress clearly impact symptom severity. Just as these environmental influences on hypertension or asthma do not negate their biological basis, the responsiveness of ADHD symptoms to environmental fluctuations (e.g., improvements in classroom structure, supportive home life) does not imply that ADHD lacks neurobiological roots. Rather, it underscores that ADHD, like many medical conditions, emerges from the interplay between underlying biological vulnerabilities and environmental influences.
Claim: There is no clear dividing line between those who have A.D.H.D. and those who don’t.
The Reality: This is absolutely and resoundingly false. The article’s suggestion that ADHD diagnosis is arbitrary because ADHD symptoms exist on a continuum rather than as a clear-cut, binary condition is misleading. Although it is true that ADHD symptoms—like inattention, hyperactivity, and impulsivity—do vary continuously across the population, the existence of this continuum does not make the diagnosis arbitrary or invalidate the disorder’s biological basis. Many well-established medical conditions show the same pattern. For instance, hypertension (high blood pressure) and hypercholesterolemia (high cholesterol) both involve measures that are continuously distributed. Blood pressure and cholesterol levels exist along a continuum, yet clear diagnostic thresholds have been carefully established through decades of clinical research. Their continuous distribution does not lead clinicians to question whether these conditions have biological origins or whether diagnosing an individual with hypertension or hypercholesterolemia is arbitrary. Rather, it underscores that clinical decisions and diagnostic thresholds are established using evidence about what levels lead to meaningful impairment or increased risk of negative health outcomes. Similarly, the diagnosis of ADHD has been meticulously defined and refined over many decades using extensive empirical research, structured clinical interviews, and validated rating scales. The diagnostic criteria developed by experts carefully delineate the point at which symptoms become severe enough to cause significant impairment in an individual’s daily functioning. Far from being arbitrary, these thresholds reflect robust scientific evidence that individuals meeting these criteria face increased risks for the serious impairments in life including accidents, suicide and premature death.
The existence of milder forms of ADHD does not undermine the validity of the diagnosis; rather, it emphasizes the clinical reality that people experience varying degrees of symptom severity.
Moreover, acknowledging variability in severity has always been a core principle in medicine. Clinicians routinely adjust treatments to meet individual patient needs. Not everyone diagnosed with hypertension receives identical medication regimens, nor does everyone with elevated cholesterol get prescribed the same intervention. Similarly, people with ADHD receive personalized treatment plans tailored to the severity of their symptoms, their specific impairments, and their individual circumstances. This personalization is not evidence of arbitrariness; it is precisely how evidence-based medicine is practiced. In sum, the continuous nature of ADHD symptoms is fully compatible with a biologically-based diagnosis that has substantial evidence for validity, and acknowledging symptom variability does not render diagnosis arbitrary or diminish its clinical importance.
In sum, readers seeking a balanced, evidence-based understanding of ADHD deserve clearer, more careful reporting. By overstating diagnostic uncertainty, selectively interpreting research about medication efficacy, and inaccurately portraying the educational benefits of medication, this article presents an overly simplistic, misleading picture of ADHD.
Attention Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder that significantly impacts children’s academic performance, social interactions, and overall quality of life (QoL). While medication is the standard treatment, it often comes with side effects and may not always provide sufficient benefits. A new systematic review and meta-analysis aims to investigate whether physical activity can offer a viable and effective alternative or complement to medication.
About the Study
This protocol, developed in line with the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA) guidelines, focuses on randomized clinical trials involving children and adolescents (ages 3–18) diagnosed with ADHD or hyperkinetic disorder. The study's goal is to evaluate the effects of physical activity on:
Unlike earlier reviews, which often included non-randomized trials or imposed limits on activity types, this analysis takes a more robust and inclusive approach. It is the first of its kind to examine QoL as an outcome while also incorporating trial sequential analysis—a method to assess evidence strength over time.
Why Physical Activity?
Physical activity is believed to impact the same brain systems targeted by ADHD medications, particularly the catecholaminergic system. This overlap suggests that exercise could play a key role in managing symptoms, potentially reducing reliance on medication or enhancing its effects.
Methodology Highlights
Significance and Dissemination
The results of this systematic review will provide critical insights into how physical activity could improve outcomes for children and adolescents with ADHD. It is also notable as the first review in this field to prioritize quality of life—a crucial, often-overlooked measure of treatment success.
The findings will be published in peer-reviewed journals and presented at relevant conferences to inform clinicians, educators, and families.
Conclusion
As concerns about the limitations of ADHD medication grow, exploring alternatives like physical activity becomes increasingly important. This systematic review has the potential to shape future treatment strategies, offering children with ADHD a chance for better symptom management and a higher quality of life.
For centuries, we’ve called the eyes the "windows to the soul," but for modern neurologists, they are quite literally a window into the brain. The retina and the central nervous system share the same embryonic origins, developing from the same neural tissue in the womb. Because of this deep biological connection, the back of your eye acts as a non-invasive map of your brain's health, displaying a complex web of nerves and blood vessels that can (theoretically!) mirror certain neurodevelopmental conditions.
Recently, a buzz rippled through the mental health community when a study published in partnership with Seoul National University Bundang Hospital claimed a massive breakthrough. Researchers developed an Artificial Intelligence (AI) model that could screen children for Attention-Deficit/Hyperactivity Disorder (ADHD) using nothing more than a simple retinal photograph. The study, which prospectively recruited children from Severance Hospital and Eunpyeong St. Mary’s Hospital, produced results that were staggering: the AI reportedly achieved an accuracy rate of 96.9%!
In the world of medical testing, scientists use a metric called AUROC (Area Under the Receiver Operating Characteristic) to measure how well a test works.
An AUROC of 96.9% is a near-perfect score, suggesting a tool is ready for immediate, real-world deployment. While headlines promised a revolution in mental health screening, a deeper look into this research and the study’s design has exposed that this 96.9% AUROC was more likely evidence of a flawed methodology rather than a biological reality.
To build their screening tool, researchers analyzed over 1,100 retinal images using a digital pipeline called AutoMorph and a machine-learning model known as XGBoost. The AI was trained to hunt for physical signals of the "Dopamine Connection." Dopamine is the primary neurotransmitter involved in ADHD, but it is also essential to the eye. It regulates synaptic formation, retinal blood flow, and vascular endothelial regulation. Because dopamine dysregulation influences how blood vessels grow and remodel, the study hypothesized that an ADHD brain would leave a unique "fingerprint" on the retinal vasculature, resulting in denser, thicker vessel structures.
On paper, the logic was sound: use AI to spot the subtle vascular remodeling caused by dopaminergic shifts. But a closer look at the investigation revealed that the AI wasn't just spotting ADHD; it was over-indexing on technical noise.
The most significant "smoking gun" flagged by critics is a massive temporal mismatch. In other words, there was a severe disparity in the timeframes and conditions under which the retinal images for the two comparison groups were collected. For an AI to learn a biological condition, it must compare groups under identical technical conditions. Instead, this study created a time-traveling dataset:
A scientific study is only as reliable as its control group. The control in any experiment acts as a baseline against which the study group is compared. In this case, the control group should be composed of children without any neurodevelopmental disorders, or of “typically developing” children.
In this study, the control group wasn't composed of healthy children from the community. Instead, they were patients visiting a tertiary ophthalmology clinic. Children visiting a specialist eye hospital are rarely "typical." They are there because they have symptomatic eye issues. This introduced a massive selection bias involving three major confounders:
When training AI, you must never allow the "test questions" to leak into the "study material." The researchers, however, committed a fundamental violation of machine learning hygiene known as Eye-to-Eye Data Leakage. The study split the data by the eye rather than by the participant.
Human eyes are highly correlated; the left eye is a near-mirror of the right. If a child's left eye was used for training and their right eye was used for testing, the AI was effectively "cheating." Instead of learning the general traits of ADHD, the model was potentially memorizing individuals. This error artificially balloons accuracy metrics.
The true test of medical AI is diagnostic specificity, or differential diagnosis. This refers to the ability to tell one condition apart from another. While the model claimed 96.9% accuracy against a flawed control group, its performance collapsed when faced with real-world complexity.
When the researchers asked the AI to differentiate between ADHD and Autism Spectrum Disorder (ASD), the accuracy plummeted to a poor 63% AUROC. In real-world clinical settings, an accuracy of 63% is dangerously close to a 50% coin flip. Since ADHD frequently co-occurs with ASD, anxiety, or intellectual disabilities, an AI that cannot handle these "clinical differentials" is functionally useless in a doctor's office. The failure at this stage proves the model was likely detecting technical quirks of the dataset rather than a unique biological marker for ADHD.
To move from the lab to the clinic, we must establish a foundation built on rigor rather than high-speed data scraping. Moving forward, we must demand these 3 Pillars of Trusted Medical AI :
The dream of a quick eye scan to diagnose ADHD is not dead, but it must be rescued from "fast science" shortcuts and buzzy headlines.
Background:
One of the more persistent concerns among parents of children with ADHD is whether stimulant medications will stunt their child's growth. A large Israeli cohort study now offers some of the most rigorous reassurance to date, and its methodology sets it apart from earlier research.
The question has long been complicated by a more fundamental uncertainty: do growth differences in children with ADHD stem from the condition itself, from stimulant treatment, or from factors present before any medication is ever prescribed? Without a clear answer, clinicians and families have faced a genuine dilemma when weighing the benefits of stimulant therapy against potential long-term physical costs.
Most previous studies compounded this difficulty by comparing group-average heights, which ignores the crucial variable of genetic potential. A child who is short relative to the general population may simply have short parents. Failing to account for this introduces systematic bias and can make medications appear more harmful than they are.
The Study:
The Israeli research team addressed this directly. Using health records from a nationwide provider, they assembled a retrospective cohort of children born between 1995 and 2003, following them through 2023. This amount of time was long enough for all participants to have reached adult stature (defined as 17 or older for females, 19 or older for males). Their sample included 5,671 children with untreated ADHD, 11,846 who received stimulant treatment, and 47,258 non-ADHD controls. Children who took stimulants for only one to two months, or who had chronic medical conditions requiring long-term medication, were excluded to avoid confounding the results.
Crucially, adult height was evaluated not against population norms but against each individual's expected height, calculated from parental heights using the Tanner-Goldstein-Whitehouse method, a standard approach for estimating genetic height potential via mid-parental height.
When the researchers compared adult heights across the three groups using analysis of variance (ANOVA), they did find statistically significant differences. But statistical significance, particularly in studies with tens of thousands of participants, does not automatically translate into clinical significance. The effect sizes were consistently very small, and the absolute differences were under one centimeter, which is a margin considered clinically negligible.
Their conclusion is measured but clear: after accounting for genetic growth potential, neither an ADHD diagnosis nor stimulant treatment was associated with meaningful reductions in adult height. The findings, they argue, support prioritizing behavioral and functional outcomes when making treatment decisions, since the risk of clinically significant height loss appears to be minimal.
The Take-Away:
For families navigating ADHD treatment, the practical implication is significant: concerns about permanent growth suppression, while understandable, should not be the primary driver of whether or how long a child receives stimulant therapy.
A recent meta-analysis examined how well cognitive behavioral therapy (CBT) improves not just symptoms, but everyday functioning and quality of life in adults with ADHD.
The Background:
ADHD in adults affects far more than attention or impulsivity. It often disrupts key areas of life:
These broad impacts highlight a key issue: reducing symptoms does not automatically translate into better day-to-day functioning.
CBT is a structured, skills-based therapy that helps people:
While both medication (especially stimulants) and CBT improve core ADHD symptoms, CBT is particularly aimed at improving real-world functioning.
The Study:
The researchers analyzed studies involving adults diagnosed with ADHD (or showing clinically significant symptoms). They included:
They focused specifically on outcomes beyond symptoms:
The Results:
1. Strongest Effects: Occupational functioning
CBT showed consistently strong improvements in work-related functioning compared to control groups, both immediately after treatment and at follow-up. This was the most robust finding across domains.
2. Moderate Improvement: Global Functional Impairment
CBT led to moderate improvements in overall daily functioning, with some evidence that gains persist over time. In studies tracking individuals over time, improvements were even stronger at follow-up.
3. Modest Gains: Social Relationships
CBT produced small to moderate improvements in social functioning. Benefits were present both after treatment and at follow-up, but were less pronounced than in work-related outcomes.
4. Limited Effects: Academic Functioning
There were moderate short-term gains when CBT was compared to control groups, but these did not persist at follow-up. Within-subject studies showed only small improvements overall.
5. Modest and Inconsistent Effects: Quality of Life
Improvements in quality of life were small when compared to control groups and often did not last. However, studies tracking individuals over time showed moderate improvements, suggesting some benefit that may not always show up clearly in between-group comparisons.
Overall, the findings suggest:
One notable nuance: CBT did not always outperform other active treatments (like medication or other therapies). This suggests that while CBT is effective, its benefits may partly overlap with broader therapeutic or support effects rather than relying on a single, unique mechanism.
The Take-Away:
CBT is a valuable, evidence-based treatment for adults with ADHD, especially for improving work functioning and overall daily life management. However, its impact on relationships, academic outcomes, and quality of life is more limited and less consistent, pointing to the need for more targeted or combined approaches in those areas.
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