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September 8, 2025
Background:
A previous meta-analysis found that children born to mothers with diabetes had a 34% higher risk of developing ADHD compared to those born to non-diabetic mothers.
However, previous studies suffered methodological limitations, such as small sample sizes, case-control or cross-sectional designs, and insufficient adjustment for key confounders such as maternal socio-economic status, mental health conditions, obesity, and substance use disorders.
Moreover, many studies relied on self-reported maternal diabetes, and on non-clinical ADHD assessments, such as parental reports or screening tools, which are prone to bias and inaccuracies.
Furthermore, the role of maternal antidiabetic medication use in relation to ADHD risk has rarely been examined. Antidiabetic medications are effective in controlling high blood sugar during pregnancy, but many can cross the placenta and the blood-brain barrier, raising concerns about potential effects on fetal brain development.
Study:
To address these gaps, an Australian study team used a large cohort of linked health administrative data from New South Wales to investigate both the association between maternal diabetes and the risk of ADHD and the independent effect of prenatal exposure to antidiabetic medications.
The study encompassed all mother-child pairs born from 2003 through 2005, with follow-up conducted through 2018 to monitor hospital admissions related to ADHD. That yielded a final cohort of almost 230,000 mother-child pairs.
The team adjusted for potential confounders including maternal age, socioeconomic status, previous children, pregnancy-related hypertension, caesarean delivery, birth order and plurality, maternal anxiety, depression, schizophrenia, bipolar disorder, substance use (alcohol, tobacco, stimulants, opioids, cannabis), and child factors such as Apgar score, sex, prematurity, and low birth weight.
Results:
For maternal diabetes overall, there was no significant association with offspring ADHD. That was also true when broken down into pre-existing maternal diabetes and gestational (pregnancy-induced) diabetes.
In a subset of 11,668 mother-child pairs, including 3,210 involving exposure to antidiabetic medications, there was likewise no significant association with offspring ADHD.
Conclusion:
The team concluded, “Our findings did not support the hypothesis that maternal diabetes increases the risk of ADHD in children. Additionally, maternal use of antidiabetic medication was not associated with ADHD.”
This study highlights the importance of high-quality research. A previous meta-analysis linking ADHD and maternal diabetes did not appropriately adjust for confounders and cited many small studies that may have included biased self-report scales. This large, registry-based cohort study of nearly 230,000 mother–child pairs found no evidence that maternal diabetes—whether pre-existing or gestational—or prenatal exposure to antidiabetic medications was associated with subsequent offspring ADHD as measured by hospital-recorded ADHD outcomes. The study’s strengths include its population scale, prolonged follow-up, and extensive adjustment for maternal and perinatal confounders (including maternal mental health and substance-use disorders), which address many limitations of earlier, smaller studies that reported elevated risks.
Yitayish Damtie, Kim Betts, Berihun Assefa Dachew, Getinet Ayanoa, and Rosa Alati, “The association between maternal diabetes, antidiabetic medication use, and severe ADHD requiring inpatient care: A registry-based cohort study,” Journal of Psychosomatic Research (2025), 195:112167, https://doi.org/10.1016/j.jpsychores.2025.112167.
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The report "Attention-Deficit/Hyperactivity Disorder Diagnosis, Treatment, and Telehealth Use in Adults" published in the CDC's Morbidity and Mortality Weekly Report provides a detailed examination of the prevalence and treatment of ADHD among U.S. adults based on data collected by the National Center for Health Statistics Rapid Surveys System during October–November 2023. This data is crucial as it offers updated estimates on the prevalence of ADHD in adults, a condition often regarded as primarily affecting children, and highlights the ongoing challenges in accessing ADHD-related treatments, including telehealth services and medication availability.
The methods used in this study involved the National Center for Health Statistics (NCHS) Rapid Surveys System (RSS), which gathers data to approximate the national representation of U.S. adults through two commercial survey panels: the AmeriSpeak Panel from NORC at the University of Chicago and Ipsos’s KnowledgePanel. The data were collected via online and telephone interviews from 7,046 adults. The responses were weighted to reflect the total U.S. adult population, ensuring that the results approximate national estimates. In identifying adults with current ADHD, respondents were asked if they had ever been diagnosed with ADHD and, if so, whether they currently had the condition. The study also collected data on treatment types (including stimulant and nonstimulant medications), telehealth use, and demographic variables such as age, education, race, and household income.
The results showed that approximately 6.0% of U.S. adults, or an estimated 15.5 million people, had a current ADHD diagnosis. Notably, more than half of the adults with ADHD reported receiving their diagnosis during adulthood (age ≥18 years), indicating that diagnosis can occur well beyond childhood. Analysis of demographics showed significant differences between adults with ADHD and those without; adults with ADHD were more likely to be younger, with 84.5% under the age of 50. Adults with ADHD were also less likely to have completed a bachelor's degree and more likely to have a household income below the federal poverty level compared to those without ADHD. Regarding treatment, the report found that approximately one-third of adults with ADHD were untreated, and around one-third received both medication and behavioral treatment. Among those receiving pharmacological treatment, 33.4% used stimulant medications, and 71.5% of these individuals reported difficulties in getting their prescriptions filled due to medication unavailability, reflecting recent stimulant shortages in the United States. Additionally, nearly half of adults with ADHD had used telehealth services for ADHD-related care, including obtaining prescriptions and receiving counseling or therapy.
The discussion emphasizes the public health implications of these findings. ADHD is often diagnosed late, with many individuals not receiving a diagnosis until adulthood, which underscores the need for improved awareness and early identification of ADHD symptoms across the life course. Moreover, the high prevalence of untreated ADHD and the barriers to accessing stimulant medications reveal significant gaps in the healthcare system's ability to support adults with ADHD. These gaps can contribute to poorer outcomes, such as increased risk of injury, substance use, and social impairment. The report also highlights the role of telehealth, which became more prominent during the COVID-19 pandemic. Telehealth appears to provide a viable solution for expanding access to ADHD diagnosis and treatment, though challenges remain regarding the quality of care and potential for misuse. The authors suggest that improved clinical care guidelines for adults with ADHD could help reduce delays in diagnosis and treatment access, thus improving long-term outcomes for affected individuals.
In conclusion, the study provides a comprehensive view of the prevalence, treatment, and telehealth use for ADHD among adults in the U.S. These data are crucial for guiding clinical care and shaping policies related to medication access and telehealth services. The findings underscore the importance of ensuring an adequate supply of stimulant medications and reducing barriers to ADHD care, ultimately enhancing the quality of life for adults with this condition. The good news is that many adults with ADHD are being diagnosed and treated. It is, however, concerning that many are not treated and that many of those treated with stimulants were impacted by the stimulant shortage.
For more details, see: https://www.cdc.gov/mmwr/volumes/73/wr/mm7340a1.htm
Noting that “evidence on the association between ADHD and a physical condition associated with obesity, namely type 2 diabetes mellitus (T2D), is sparse and has not been meta-analysed yet,” a European study team performed a systematic search of the peer-reviewed medical literature followed by a meta-analysis, and then a nationwide population study.
Unlike type 1 diabetes, which is an auto-immune disease, type 2 diabetes is believed to be primarily related to lifestyle, associated with insufficient exercise, overconsumption of highly processed foods, and especially with large amounts of refined sugar. This leads to insulin resistance and excessively high blood glucose levels that damage the body and greatly lower life expectancy.
Because difficulty with impulse control is a symptom of ADHD, one might hypothesize that individuals with ADHD would be more likely to develop type-2 diabetes.
The meta-analysis of four cohort studies encompassing more than 5.7 million persons of all ages spread over three continents (in the U.S., Taiwan, and Sweden) seemed to point in that direction. It found that individuals with ADHD had more than twice the odds of developing type 2 diabetes than normally developing peers. There was no sign of publication bias, but between-study variability (heterogeneity) was moderately high.
The nationwide population study of over 4.2 million Swedish adults came up with the same result when adjusting only for sex and birth year.
Within the Swedish cohort there were 1.3 million families with at least two full siblings. Comparisons among siblings with and without ADHD again showed those with ADHD having more than twice the odds of developing type 2 diabetes. That indicated there was little in the way of familial confounding.
However, further adjusting for education, psychiatric comorbidity, and antipsychotic drugs dropped those higher odds among those with ADHD in the overall population to negligible (13% higher) and barely significant levels.
The drops were particularly pronounced for psychiatric comorbidities, especially anxiety, depression, and substance use disorders, all of which had equal impacts.
The authors concluded, “This study revealed a significant association between ADHD and T2D [type 2 diabetes] that was largely due to psychiatric comorbidities, in particular SUD [substance use disorders], depression, and anxiety. Our findings suggest that clinicians need to be aware of the increased risk of developing T2D in individuals with ADHD and that psychiatric comorbidities may be the main driver of this association. Appropriate identification and treatment of these psychiatric comorbidities may reduce the risk for developing T2D in ADHD, together with efforts to intervene on other modifiable T2D risk factors (e.g., unhealthy lifestyle habits and use of antipsychotics, which are common in ADHD), and to devise individual programs to increase physical activity. Considering the significant economic burden of ADHD and T2D, a better understanding of this relationship is essential for targeted interventions or prevention programs with the potential for a positive impact on both public health and the lives of persons living with ADHD.”
Our recent study, published in the Journal of Clinical Medicine, aims to shed light on an under-recognized challenge faced by many adults with Type 1 diabetes (T1D): attention-deficit/hyperactivity disorder (ADHD) symptoms.
We surveyed over 2,000 adults with T1D using the Adult Self-Report Scale (ASRS) for ADHD and analyzed their medical records. Of those who responded, nearly one-third met the criteria for ADHD symptoms—far higher than the general population average. Notably, only about 15% had a formal diagnosis or were receiving treatment.
The findings are striking: individuals with higher ADHD symptom scores had significantly worse blood sugar control, as indicated by higher HbA1c levels. Those flagged as "ASRS positive" were more than twice as likely to have poor glycemic control (HbA1c ≥ 8.0%). They also reported higher levels of depressive symptoms.
As expected, ADHD symptoms decreased with age but remained more common than in the general public. No strong links were found between ADHD symptoms and other cardiometabolic issues.
This study highlights a previously overlooked yet highly significant factor in diabetes management. ADHD-related difficulties—such as forgetfulness, inattention, or impulsivity—can make managing a complex condition like T1D more difficult. The researchers call for more screening and awareness of ADHD in adults with diabetes, which could lead to better mental health and improved blood sugar outcomes.
Takeaway: If you or a loved one with T1D struggles with focus, organization, or consistent self-care, it may be worth exploring whether ADHD could be part of the picture. Early identification and support are crucial to managing this common comorbidity.
Stimulant medications have long been considered the default first-line treatment for attention-deficit/hyperactivity disorder (ADHD). Clinical guidelines, prescribing practices, and public narratives all reinforce the idea that stimulants should be tried first, with non-stimulants reserved for cases where stimulants fail or are poorly tolerated.
I recently partnered with leading ADHD researcher Jeffrey Newcorn for a Nature Mental Health commentary on the subject. We argue that this hierarchy deserves reexamination. It is important to note that our position is not anti-stimulant. Rather, we call into question whether the evidence truly supports treating non-stimulants as secondary options, and we propose that both classes should be considered equal first-line treatments.
Stimulants have earned their reputation as the go-to drug of choice for ADHD. They are among the most effective medications in psychiatry, reliably reducing core ADHD symptoms and improving daily functioning when properly titrated and monitored. However, when stimulant and non-stimulant medications are compared more closely, the gap between them appears smaller than commonly assumed.
Meta-analyses often report slightly higher average response rates for stimulants, but head-to-head trials where patients are directly randomized to one medication versus another frequently find no statistically significant differences in symptom improvement or tolerability. Network meta-analyses similarly show that while some stimulant formulations have modest advantages, these differences are small and inconsistent, particularly in adults.
When translated into clinical terms, the advantage of stimulants becomes even more modest. Based on existing data, approximately eight patients would need to be treated with a stimulant rather than a non-stimulant for one additional person to experience a meaningful benefit. This corresponds to only a 56% probability that a given patient will respond better to a stimulant than to a non-stimulant. This difference is not what we would refer to as “clinically significant.”
One reason non-stimulants may appear less effective is the way efficacy is typically reported. Most comparisons rely on standardized mean differences, a method of averages that may mask heterogeneity of treatment effects. In reality, ADHD medications do not work uniformly across patients.
For example, evidence suggests that response to some non-stimulants, such as atomoxetine, is bimodal: this means that many patients respond extremely well, while others respond poorly, with few in between. When this happens, average effect sizes can obscure the fact that a substantial subgroup benefits just as much as they would from a stimulant. In other words, non-stimulants are not necessarily less effective across the board, but that they are simply different in who they help.
In our commentary, we also highlight structural issues in ADHD research. Stimulant trials are particularly vulnerable to unblinding, as their immediate and observable physiological effects can reveal treatment assignment, potentially inflating perceived efficacy. Non-stimulants, with slower onset and subtler effects, are less prone to this bias.
Additionally, many randomized trials exclude patients with common psychiatric comorbidities such as anxiety, depression, or substance-use disorders. Using co-diagnoses as exclusion criteria for clinical trials on ADHD medications is nonviable when considering the large number of ADHD patients who also have other diagnoses. Real-world data suggest that a large proportion of individuals with ADHD would not qualify for typical trials, limiting how well results generalize to everyday clinical practice.
Standard evaluations of medication tolerability focus on side effects experienced by patients, but this narrow lens misses broader societal consequences. Stimulants are Schedule II controlled substances, which introduces logistical barriers, regulatory burdens, supply vulnerabilities, and administrative strain for both patients and clinicians.
When used as directed, stimulant medications do not increase risk of substance-use disorders (and, in fact, tend to reduce these rates); however, as ADHD awareness has spread and stimulants are more widely prescribed, non-medical use of prescription stimulants has become more widespread, particularly among adolescents and young adults. Non-stimulants do not carry these risks.
Non-stimulants are not without drawbacks themselves, however. They typically take longer to work and have higher non-response rates, making them less suitable in situations where rapid results are essential. These limitations, however, do not justify relegating them to second-line status across the board.
This is a call for abandoning a one-size-fits-all approach. Instead, future guidelines should present stimulant and non-stimulant medications as equally valid starting points, clearly outlining trade-offs related to onset, efficacy, misuse risk, and practical burden.
The evidence already supports this shift. The remaining challenge is aligning clinical practice and policy with what the data, and patient-centered care, are increasingly telling us.
Today, most treatment guidelines recommend starting ADHD treatment with stimulant medications. These medicines often work quickly and can be very effective, but they do not help every child, and they can have bothersome side effects, such as appetite loss, sleep problems, or mood changes. Families also worry about long-term effects, the possibility of misuse or abuse, as well as the recent nationwide stimulant shortages. Non-stimulant medications are available, but they are usually used only after stimulants have not been effective.
This stimulant-first approach means that many patients who would respond well to a non-stimulant will end up on a stimulant medication anyway. This study addresses this issue by testing two different ways of starting medication treatment for school-age children with attention-deficit/hyperactivity disorder (ADHD). We want to know whether beginning with a non-stimulant medicine can work as well as the “stimulant-first” approach, which is currently used by most prescribers.
From this study, we hope to learn:
Our goal is to give families and clinicians clear, practical evidence to support a truly shared decision: “Given this specific child, should we start with a stimulant or a non-stimulant?”
Who will be in the study?
We will enroll about 1,000 children and adolescents, ages 6 to 16, who:
We will include children with common co-occurring conditions (such as anxiety, depression, learning or developmental disorders) so that the results reflect the “real-world” children seen in clinics, not just highly selected research volunteers.
How will the treatments be assigned?
This is a randomized comparative effectiveness trial, which means:
Parents and clinicians will know which type of medicine the child is taking, as in usual care. However, the experts who rate how much each child has improved using our main outcome measure will not be told which treatment strategy the child received. This helps keep their ratings unbiased.
What will participants be asked to do?
Each family will be followed for 12 months. We will collect information at:
At these times:
We will also track:
Data will be entered into a secure, HIPAA-compliant research database. Study staff at each site will work closely with families to make participation as convenient as possible, including offering flexible visit schedules and electronic options for completing forms when feasible.
How will we analyze the results?
Using standard statistical methods, we will:
All analyses will follow the “intention-to-treat” principle, meaning we compare children based on the strategy they were originally assigned to, even if their medication is later changed. This mirrors real-world decision-making: once you choose a starting strategy, what tends to happen over time?
Why is this study necessary now?
This study addresses a critical, timely gap in ADHD care:
In short, this study is needed now to move ADHD medication decisions beyond “one-size-fits-all.” By rigorously comparing stimulant-first and non-stimulant-first strategies in real-world settings, and by focusing on what matters most to children and families overall functioning, side effects, and long-term well-being, we aim to give patients, parents, and clinicians the information they need to choose the best starting treatment for each child.
This project was conceived by Professor Stephen V. Faraone, PhD (SUNY Upstate Medical University, Department of Psychiatry, Syracuse, NY) and Professor Jeffrey H. Newcorn, MD (Icahn School of Medicine at Mount Sinai, Department of Psychiatry, New York, NY). It will be conducted at nine sites across the USA.
EBI-ADHD:
If you live with ADHD, treat ADHD, or write about ADHD, you’ve probably run into the same problem: there’s a ton of research on treatments, but it’s scattered across hundreds of papers that don’t talk to each other. The EBI-ADHD website fixes that.
EBI-ADHD (Evidence-Based Interventions for ADHD) is a free, interactive platform that pulls together the best available research on how ADHD treatments work and how safe they are. It’s built for clinicians, people with ADHD and their families, and guideline developers who need clear, comparable information rather than a pile of PDFs. EBI-ADHD Database The site is powered by 200+ meta-analyses covering 50,000+ participants and more than 30 different interventions. These include medications, psychological therapies, brain-stimulation approaches, and lifestyle or “complementary” options.
The heart of the site is an interactive dashboard. You can:
The dashboard then shows an evidence matrix: a table where each cell is a specific treatment–outcome–time-point combination. Each cell tells you two things at a glance:
Clicking a cell opens more detail: effect sizes, the underlying meta-analysis, and how the certainty rating was decided.
EBI-ADHD is not just a curated list of papers. It’s built on a formal umbrella review of ADHD interventions, published in The BMJ in 2025. That review re-analyzed 221 meta-analyses using a standardized statistical pipeline and rating system.
The platform was co-created with 100+ clinicians and 100+ people with lived ADHD experience from around 30 countries and follows the broader U-REACH framework for turning complex evidence into accessible digital tools.
Why it Matters
ADHD is one of the most studied conditions in mental health, yet decisions in everyday practice are still often driven by habit, marketing, or selective reading of the literature. EBI-ADHD offers something different: a transparent, continuously updated map of what we actually know about ADHD treatments and how sure we are about it.
In short, it’s a tool to move conversations about ADHD care from “I heard this works” to “Here’s what the best current evidence shows, and let’s decide together what matters most for you.”
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