June 13, 2025

Study Finds Association Between Childhood ADHD and Poor Dental Health

The Spanish National Health Survey tracks health care outcomes through representative samples of the Spanish population. 

A Spanish research team used survey data to explore the relationship between ADHD symptoms and dental and gum health in a representative sample of 3,402 Spanish children aged 6 to 14.

While previous studies have found associations between ADHD and poor dental health, they have not fully accounted for such important determinants of poor oral health as socioeconomic status, dental hygiene, or diet. 

The team therefore adjusted for sociodemographic factors, lifestyle variables, and oral hygiene behaviors. More specifically, they adjusted for sex, age, social class, parental education, exposure to tobacco smoke, consumption of sweets, consumption of sugary drinks, use of asthma or allergy medication, adequate oral hygiene behavior of children, adherence to regular dental visits, parental adequate oral hygiene behavior, and parental adherence to regular dental visits.

With those adjustments, children with ADHD symptoms had over twice the incidence of dental caries (cavities) as their counterparts without ADHD symptoms.

Tooth extractions and dental restorations also occurred with over 40% greater frequency in children with ADHD symptoms.

Gum bleeding, a sign of gum disease, was more than 60% more common among children with ADHD symptoms than among their non-ADHD peers.

Importantly, excluding children with daily sugar consumption, which left 1,693 children in the sample, made no difference in the outcome for cavities.

Excluding children with poor oral hygiene habits, which left 1,657 children in the sample, those with ADHD had 2.5-fold more caries than their non-ADHD counterparts.

Excluding children of low social class, which left 1,827 children in the sample, those with ADHD had 2.6-fold more caries than their non-ADHD counterparts.

Turning to a different method to address potential confounding factors, the team used nearest-neighbor propensity score matching to create virtual controls. This compared 461 children with ADHD to 461 carefully matched children without ADHD.

This time, children with ADHD symptoms had just under twice the incidence of cavities as their counterparts without ADHD symptoms, but 60% more tooth extractions and about 75% more dental restorations. The difference in gum bleeding became nonsignificant.

Noting that “The increased risk of caries was maintained when the analyses were restricted to middle/high social class families and children with low sugar intake, good oral hygiene behaviors and regular dental visits,” the team concluded, “Children with ADHD symptoms in Spain had worse oral health indicators than those without ADHD symptoms. Our results suggest that the association of ADHD symptoms with caries was independent of socioeconomic level, cariogenic diet, frequency of toothbrushing, and dental visits.”

Lucía Fernández-Arce, José Manuel Martínez-Pérez, Miguel García-Villarino, María Del Mar Fernández-Álvarez, Rubén Martín-Payo, and Alberto Lana, “Symptoms of Attention Deficit Hyperactivity Disorder and Oral Health Problems among Children in Spain,” Caries Research (2025), 59(1):35-45, https://doi.org/10.1159/000541013.

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Exploring Gut Microbiota and Diet in Autism and ADHD: What Does the Research Say?


In recent years, there has been growing interest in understanding the connection between our gut microbiota (the community of microorganisms in our digestive system) and various neurodevelopmental disorders like autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD). A new study by Shunya Kurokawa and colleagues dives deeper into this area, comparing dietary diversity and gut microbial diversity among children with ASD, ADHD, their normally-developing siblings, and unrelated volunteer controls. Let's unpack what they found and what it means.

The Study Setup

The researchers recruited children aged 6-12 years diagnosed with ASD and/or ADHD, along with their non-ASD/ADHD siblings and the unrelated non-ASD/ADHD volunteers. The diagnoses were confirmed using standardized assessments like the Autism Diagnostic Observation Schedule-2 (ADOS-2). The study looked at gut microbial diversity using advanced DNA extraction and sequencing techniques, comparing alpha-diversity indices (which reflect the variety and evenness of microbial species within each gut sample) across different groups. They also assessed dietary diversity through standardized questionnaires.

Key Findings

The study included 98 subjects, comprising children with ASD, ADHD, both ASD and ADHD, their non-ASD/ADHD siblings, and the unrelated controls. Here's what they discovered:

Gut Microbial Diversity: The researchers found significant differences in alpha-diversity indices (like Chao 1 and Shannon index) among the groups. Notably, children with ASD had lower gut microbial diversity compared to unrelated neurotypical controls. This suggests disorder-specific differences in gut microbiota, particularly in children with ASD.

Dietary Diversity: Surprisingly, dietary diversity (assessed using the Shannon index) did not differ significantly among the groups. This finding implies that while gut microbial diversity showed disorder-specific patterns, diet diversity itself might not be the primary factor driving these differences.

What Does This Mean?

The study highlights intriguing connections between gut microbiota and neurodevelopmental disorders like ASD and ADHD. The lower gut microbial diversity observed in children with ASD points towards potential links between gut health and the pathophysiology of ASD. Understanding these connections is crucial for developing targeted therapeutic interventions.

Implications and Future Directions

This research underscores the importance of considering gut microbiota in the context of neurodevelopmental disorders. Moving forward, future studies should account for factors like co-occurrence of ASD and ADHD, as well as carefully control for dietary influences. This will help unravel the complex interplay between gut microbiota, diet, and neurodevelopmental disorders, paving the way for innovative treatments and interventions.

In summary, studies like this shed light on the intricate relationship between our gut health, diet, and brain function. By unraveling these connections, researchers are opening new avenues for understanding and potentially treating conditions like ASD and ADHD.

April 9, 2024

Dose-dependent Association Found Between Childhood General Anesthesia and ADHD

Childhood General Anesthesia and Subsequent Diagnoses of ADHD

In December 2016, the U.S. Food and Drug Administration (FDA) warned “that repeated or lengthy use of general anesthetic and sedation drugs during surgeries or procedures in children younger than 3 years or in pregnant women during their third trimester may affect the development of children’s brains.” The FDA adds, “Health care professionals should balance the benefits of appropriate anesthesia against the potential risks, especially for procedures lasting longer than 3 hours or if multiple procedures are required in children under 3 years,” and “Studies in pregnant and young animals have shown that using these drugs for more than 3 hours caused widespread loss of brain nerve cells.”

That raises a concern that such exposure could lead to increased risk of psychiatric disorders, including ADHD.

Noting “There are inconsistent reports regarding the association between general anesthesia and adverse neurodevelopmental and behavioral disorders in children,” a South Korean study team conducted a nationwide population study to explore possible associations through the country’s single-payer health insurance database that covers roughly 97% of all residents.

The team looked at the cohort of all children born in Korea between 2008 and 2009, and followed them until December 31, 2017. They identified 93,717 children in this cohort who during surgery received general anesthesia with endotracheal intubation (a tube inserted down the trachea), and matched them with an equal number of children who were not exposed to general anesthesia.

The team matched the unexposed group with the exposed group by age, sex, birth weight, residential area at birth, and economic status.

They then assessed both groups for subsequent diagnoses of ADHD.

In general, children exposed to general anesthesia were found to have a 40% greater risk of subsequently being diagnosed with ADHD than their unexposed peers.

This effect was found to be dose dependent by several measures:

  • Duration of surgery: two-to-three-hour surgeries were associated with a 50% greater risk of subsequent ADHD, and surgeries of more than three hours with a 60% greater risk.
  • Number of exposures: two exposures were associated with a 54% increased risk, and three or more exposures with a 67% greater risk.
  • Placement in an Intensive Care Unit was associated with a 60% greater risk of ADHD.

All three measures were highly significant.

The authors concluded, “exposure to general anesthesia with ETI [endotracheal intubation] in children is associated with an increased risk of ADHD … We must recognize the possible neurodevelopmental risk resulting from general anesthesia exposure, inform patients and parents regarding this risk, and emphasize the importance of close monitoring of mental health. However, the risk from anesthesia exposure is not superior to the importance of medical procedures. Specific research is needed for the development of safer anesthetic drugs and doses.”

June 20, 2024

What the MAHA Report Gets Right—and Wrong—About ADHD and Children's Health

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.

Some of the Good Ideas in the MAHA Report:

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.

What MAHA Says About ADHD:

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 ADHDand other references given below.

✔️ Accurate: ADHD diagnoses are increasing.

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.

❌ Misleading: ADHD is caused by processed food, screen time, or chemical exposures.

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.

How the MAHA Report Could Still Help People with ADHD:

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.

May 28, 2025

Finding Order in the Complexity of ADHD: A Brain Imaging Study Identifies Three Neurobiological Subtypes

ADHD is one of the most common neurodevelopmental disorders in children, yet anyone familiar with this disorder, from clinicians and researchers to parents and patients, knows how differently it can manifest from one individual to the next. One person diagnosed with ADHD may primarily struggle with focus and staying on-task; another may find it nearly impossible to regulate their impulses or even start tasks; a third may frequently find themselves frozen with overwhelm and subject to emotional reactivity…

These are not just variations in severity; they may reflect genuinely different patterns of brain organization.

Our current diagnostic system groups all of these presentations under a single label (ADHD), with three behavioral subtypes (Hyperactive, Inattentive, and Combined) defined by symptom checklists. This framework has real clinical value of course, but it was built from behavioral observation rather than neurobiology, and may leave room for substantial heterogeneity to remain unexplained. In a new study, published in JAMA Psychiatry, researchers asked whether it’s possible to identify distinct neurobiologically subgroups within ADHD by analyzing patterns of brain structure, and whether those subgroups would map onto meaningful clinical differences.

How the Brain Was Analyzed

Researchers analyzed structural MRI scans from 446 children with ADHD and 708 typically-developing children across multiple research sites. From each scan, they constructed a morphometric similarity network; that is, a map of how different brain regions resemble one another in their structural properties. These networks reflect underlying biological organization, including shared patterns of cellular architecture and gene expression across brain regions.

From each individual's network, the research team calculated three properties that capture how each brain region functions within the broader network: how many connections it has, how efficiently it communicates with other regions, and how well it bridges different functional communities in the brain. Regions that score highly on these measures are sometimes called "hubs" and they play particularly influential roles in how information is integrated across the brain.

Rather than comparing the ADHD group to controls as a whole and looking for average differences, they used a normative modeling approach. This works similarly to a growth chart in pediatric medicine: instead of asking whether a child is above or below the group average, it asks how much a given child deviates from the expected range for their age and sex. This allows for individual variation across the ADHD group rather than flattening it into a single average profile.

The team then applied a data-driven clustering algorithm to these individual deviation profiles, allowing the data to reveal whether subgroups of children with ADHD shared similar patterns of brain network atypicality, without using any clinical symptom information to guide the clustering.

The Results:

Three stable, reproducible subtypes emerged from this analysis.

The first subtype was characterized by the most widespread differences from the normative range, particularly in regions connecting the medial prefrontal cortex to the pallidum (a deep brain structure involved in motivation and emotional regulation). Children in this group had the highest levels of both inattention and hyperactivity/impulsivity, and over a four-year follow-up period showed more persistent difficulties with emotional self-regulation than the other groups. They also had a higher rate of mood disorder comorbidity during follow-up, though this difference did not reach statistical significance given the sample size. The brain deviation patterns of this subtype showed correspondence with the spatial distributions of several neurotransmitter systems, including serotonin, dopamine, and acetylcholine, all of which have been previously implicated in ADHD pathophysiology.

The second subtype showed alterations concentrated in the anterior cingulate cortex and pallidum, a circuit involved in action control and response selection. This subtype had a predominantly hyperactive/impulsive profile, and its brain deviation patterns were associated with glutamate and cannabinoid receptor distributions.

The third subtype showed more focal differences in the superior frontal gyrus, a region involved in sustained attention. This subtype had a predominantly inattentive profile, with brain patterns linked to a specific serotonin receptor subtype.

A particularly important observation was that these brain-derived groupings aligned with clinically meaningful symptom differences, even though no symptom information was used in the clustering process. The fact that an analysis of brain structure alone arrived at groupings that correspond to recognizable clinical patterns is meaningful evidence that these subtypes reflect genuine neurobiological differences rather than statistical noise.

Replication in an Independent Sample

Scientific findings are only as trustworthy as their ability to replicate. The research team tested this clustering model in an entirely independent cohort of 554 children with ADHD from the Healthy Brain Network, a large, publicly available dataset collected under different conditions. The three subtypes were successfully identified in this new sample, with strong correlations between the brain deviation patterns observed in the original and validation cohorts. Differences in hyperactivity/impulsivity across subtypes were consistent with the discovery cohort, providing meaningful external validation of the approach.

What This Does and Doesn't Mean

It is important to be clear about what these findings do and do not imply. This study does not establish that these three subtypes are categorically distinct biological entities with sharp boundaries. They probably represent distinguishable regions along an underlying continuum of neurobiological variation. The neurochemical associations reported are exploratory and spatial in nature; they describe correspondences between brain deviation maps and neurotransmitter receptor density maps derived from separate imaging studies, and do not directly establish that any particular neurotransmitter system is altered in each subtype, nor do they currently inform treatment decisions.

The samples were not entirely medication-naive, and the strict comorbidity exclusion criteria may limit how well these findings generalize to typical clinical populations where comorbidities are the rule rather than the exception. All data came from research sites in the United States and China, and broader generalizability remains to be established.

What the study does demonstrate is that structured neurobiological heterogeneity exists within the ADHD diagnosis, that it can be reliably detected using brain imaging and data-driven methods, and that it aligns with meaningful clinical differences. The subtype defined by the most extensive brain network differences and the most severe, persistent clinical profile may be of particular importance, representing a group that could benefit most from early identification and targeted support.

The longer-term goal of this line of research is to move toward a more biologically grounded understanding of ADHD that complements existing diagnostic approaches and that may ultimately help guide more individualized treatment decisions. That goal, for now, remains a research ambition rather than a clinical reality, but this study takes a meaningful step in that direction.    

March 31, 2026

ADHD and Blood Pressure Medication: Why Staying on Treatment Is Harder, and What Might Help

Managing high blood pressure requires more than just getting a prescription; it means taking medication consistently, day after day, often for years. For people with ADHD, that kind of routine can be genuinely difficult. In our new study, published in BMC Medicine, we set out to understand just how much ADHD affects whether people stick with their blood pressure medication, and whether ADHD treatment itself might make a difference.

Why This Question Matters

Hypertension affects nearly a third of adults worldwide and is one of the leading drivers of heart disease and stroke. At the same time, ADHD, long thought of as a childhood disorder, affects around 2.5% of adults and is increasingly recognized as a risk factor for cardiovascular problems, including high blood pressure. Yet no large-scale study had ever examined whether having ADHD affects how well people follow through with their blood pressure treatment. We wanted to fill that gap.

What We Did

We analyzed health records from over 12 million adults across seven countries, Australia, Denmark, the Netherlands, Norway, Sweden, the UK, and the US, who had started antihypertensive (blood pressure-lowering) medication between 2010 and 2020. About 320,000 of them had ADHD. We tracked two things: whether they stopped their blood pressure medication entirely within five years, and whether they were taking it consistently enough (covering at least 80% of days) over one, two, and five years of follow-up.

What We Found

Across nearly all countries, adults with ADHD were more likely to stop their blood pressure medication and less likely to take it consistently. Overall, those with ADHD had about a 14% higher rate of discontinuing treatment within five years, and were 45% more likely to have poor adherence in the first year, a gap that widened to 64% by the five-year mark. These patterns were most pronounced in middle-aged and older adults.

Interestingly, young adults with ADHD were actually slightly less likely to discontinue treatment than their peers without ADHD, a finding we think may reflect the fact that younger people with ADHD are often more actively engaged with healthcare systems, especially given the cardiovascular monitoring that comes with ADHD medication use.

Perhaps the most encouraging finding was this: among people with ADHD who were also taking ADHD medication, adherence to blood pressure treatment was substantially better. Those on ADHD medication were about 38% less likely to have poor adherence at one year, and nearly 50% less likely at five years. While we can't establish causation from this type of study, one plausible explanation is that treating ADHD, reducing inattention and impulsivity, makes it easier to maintain the routines that consistent medication use requires. It's also possible that people on ADHD medication simply have more regular contact with healthcare providers, which keeps other health problems better monitored and managed.

What This Means in Practice

The core ADHD symptoms of inattention and poor organization are precisely the traits that make long-term medication adherence difficult. Add in the complexity of managing multiple disorders and medications, and it's easy to see why people with ADHD face extra challenges. Our findings suggest that clinicians treating adults with ADHD for cardiovascular disorders should be aware of these challenges and consider tailored support strategies, things like regular follow-up appointments, patient education, and tools that help with routine and organization.

There's also a broader message here about the potential ripple effects of treating ADHD well. Supporting someone in managing their ADHD may not just improve their attention and daily functioning; it may also help them take better care of their physical health, including disorders as serious as hypertension.

Future research should explore which specific support strategies are most effective, and whether these findings hold in lower- and middle-income countries where the data don't yet exist.

Why Do So Many People with ADHD Stop Taking Their Medication? Our New Study Sheds Light on the Role of Genetics

If you or someone you know has ADHD, you may be familiar with the challenge of staying on medication. Stimulants like methylphenidate (Ritalin) are the most common and effective treatment for ADHD, but a surprisingly large number of people stop taking them within the first year. In our new study, published in Translational Psychiatry, we sought to determine whether a person's genetic makeup plays a role in the development of the disorder.

What We Did

We analyzed data from over 18,000 people with ADHD in Denmark, all of whom had started stimulant medication. We tracked whether they stopped treatment within the first year, defined as going more than six months without filling a prescription. Nearly 4 in 10 (39%) had discontinued by that point. We then looked at their genetic data to see whether DNA differences could help explain who was more likely to stop.

What We Found

The short answer is: genetics does play a role, but it's modest. No single gene had a dramatic effect. Instead, we found that a collection of small genetic influences—distributed across the genome—contributed to the likelihood of stopping treatment early.

One of the most consistent findings was that people with a higher genetic predisposition for psychiatric disorders like schizophrenia, depression, or general mental health difficulties were more likely to discontinue their medication. This was true across all age groups. Interestingly, having a higher genetic risk for ADHD itself was not associated with stopping treatment, suggesting that the genetics of having ADHD and the genetics of staying on medication are quite different things.

We also found that the genetic picture looks different depending on age. In children under 16, body weight genetics (BMI) played a surprising role, children with a genetic tendency toward higher weight were actually less likely to stop, possibly because stimulant-related appetite suppression is less of a problem for them. In older adolescents and adults, higher genetic potential for educational attainment and IQ was linked to staying on treatment, possibly reflecting better access to information and healthcare support.

On the rare variant side, we found a tentative signal that people who stopped treatment had fewer disruptive variants in genes involved in dopamine, the brain chemical that stimulants work on. This might mean that those who continue on medication genuinely have more disruption in their dopamine system and benefit more from stimulant treatment.

What This Means

Our findings suggest that stopping ADHD medication early isn't simply a matter of willpower or forgetting to take a pill. Biology matters. A person's broader genetic vulnerabilities, particularly for other psychiatric disorders, may make it harder to stay on treatment, perhaps because of side effects, poor response, or the complexity of managing multiple mental health challenges at once.

We're still far from being able to use genetics to predict who will stop their medication, the effects we found are real but small, and much of the variation in treatment persistence remains unexplained. But this work is a step toward understanding the biological foundations of treatment challenges in ADHD, and hopefully toward more personalized approaches to care in the future.

Larger studies and research that can distinguish why people stop (side effects versus poor response versus practical barriers), will be the next steps.