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November 29, 2021
Sweden has a national single-payer health insurance system that includes virtually the entire population. It also has a system of national registers that track every resident from birth to death. That makes it possible to conduct nationwide population studies with a very high degree of precision and reliability.
In addition, one of the national registers is the Swedish Twin Register. Tracking all twins in the population enables studies to evaluate the degree to which observed associations may be attributable to genetic influences and to familial confounding. The twin method relies on the different levels of genetic relatedness between monozygotic ("identical") twins, who are genetically identical, and dizygotic ("fraternal") twins, who share on average half of their genetic variation (as do ordinary full siblings).
A Swedish team of researchers identified 42,582 Swedish twins born between 1959 and 1985, and who were, therefore, adults by the time of the study (20-47 years old). Of these, 24,872 (three out of five) completed a web-based survey with 1,300 questions covering lifestyle and mental and physical health. Out of this group, 17,999 provided information on ADHD symptoms and food frequency.
Self-reported ADHD symptoms came from nine inattention components and nine hyperactivity/impulsivity components, covering the 18 DSM- IV symptoms of ADHD.
The food frequency questionnaire included 94 food items, with the following frequency categories: never, 1-3 times/month, 1-2 times/week, 3-4 times/week, 5-6 times/week, 1 time/day, 2 times/day, 3 times/day.
In the raw data, the two subtypes of ADHD exhibited very similar associations. Both had significant associations with unhealthy diets. Both were more likely to be eating foods high in added sugar, and neglecting fruits and vegetables while eating more meat and fats.
After adjusting for the degree of relatedness of twins (whether monozygotic or dizygotic) and controlling for the other ADHD subtype, the associations remained statistically significant for inattention, but diminished to negligible levels or became statistically non-significant for hyperactivity/impulsivity.
Even for persons with inattention symptoms, adjusted correlations were small (never exceeding r = 0.10), with the strongest associations being for overall unhealthy eating habits (r = 0.09), eating foods high in added sugar (r = 0.10) or high in fat (r = 0.05), and neglecting fruits and vegetables (r = 0.06). All other associations became statistically non-significant.
For persons with hyperactivity/impulsivity symptoms, the only associations that remained statistically significant - but at tiny effect sizes - were unhealthy dietary patterns (r = 0.04) and consumption of foods high in added sugar (r = 0.03).
The further genetic analysis, therefore, focused on the strongest associations, between ADHD subtypes on the one hand, and unhealthy dietary patterns and eating foods high in added sugar on the other hand. The heritability estimates (the fraction of phenotypic covariance explained by genetic influences) were 44%, 40%, and 37% for inattention and high-sugar food, inattention and unhealthy dietary patterns, and hyperactivity/impulsivity and high-sugar food, respectively.
When examining only differences between pairs of monozygotic("identical") twins, the correlations became stronger for inattention, rising to r = 0.12 for unhealthy eating habits and r = 0.13 for consumption of foods high in added sugar. For hyperactivity/impulsivity symptoms, the association with unhealthy eating habits was weaker, and the association with consumption of foods high in added sugar became statistically insignificant.
The authors concluded, "we identified positive associations between self-reported trait dimensions of ADHD and intake of seafood, high-fat food, high-sugar food, high-protein food, and an unhealthy dietary pattern, and negative associations with consumption of fruits, vegetables, and a healthy dietary pattern. However, all the associations are small in magnitude. These associations were stronger for inattention compared to hyperactivity/ impulsivity. This pattern of associations was also reflected at the etiological level, where we found a slightly stronger genetic correlation between inattention with dietary habits and hyperactivity/impulsivity with dietary habits. Non-shared environmental influences also contributed to the overlap between ADHD symptom dimensions and consumption of high-sugar food and unhealthy dietary pattern. However, shared environmental influences probably contributed relatively little to the associations between ADHD symptoms and dietary habits. ... significant MZ twin intraplate differences also provided support for a potential causal link between inattention and dietary habits.
Lin Li, Mark J. Taylor, Katarina Bälter, Ralf Kuja-Halkola, Qi Chen, Tor-Arne Hegvik, Ashley E. Tate, Zheng Chang, Alejandro Arias-Vásquez, Catharina A. Hartman, Henrik Larsson, "Attentiondeficit/hyperactivity disorder symptoms and dietary habits in adulthood: A large populationbased twin study in Sweden," American Journal of Medical Genetics (2020) Vol.183, Issue 8, 475-485, https://doi.org/10.1002/ajmg.b.32825.
The Background:
Concerns remain about how ADHD and methylphenidate (MPH) use might affect children's health and growth, and especially how it may affect their adult height. While some studies suggest disrupted growth and a possible biological mechanism, the impact of ADHD prevalence and MPH use is still unclear. Children with ADHD may develop unhealthy habits – irregular eating, low physical activity, and poor sleep – that can contribute to obesity and reduced height. MPH’s appetite-suppressing effect can lead to skipped meals or overeating. Since growth hormone is mainly released during deep sleep, chronic sleep deprivation could plausibly slow growth and impair height development; however, a clear link between ADHD, MPH use, overweight, and shorter stature has never been firmly established.
The Study:
South Korea has a single payer health insurance system that covers more than 97% of its population. A Korean research team used the National Health Insurance Service database to perform a nationwide population study to explore this topic further.
The study involved 34,850 children, of whom 12,866 were diagnosed with ADHD. Of these children, 6,816 (53%) had received methylphenidate treatment, while 6,050 (47%) had not. Each patient with ADHD was precisely matched 1:1 by age, sex, and income level to a control participant without ADHD. The sex ratio was comparable in all groups.The team used Body Mass Index (BMI) as an indicator of overweight and obesity.
The Results:
The researchers found that being diagnosed with ADHD was associated with 50% greater odds of being overweight or obese as young adults, and over 70% greater odds of severe obesity (BMI > 30) compared to matched non-ADHD controls, regardless of whether or not they were medicated.
Those diagnosed with ADHD, but not on methylphenidate, had 40% greater odds of being overweight or obese, and over 55% greater odds of becoming severely obese, relative to matched non-ADHD controls.
Methylphenidate users had 60% greater odds of being overweight or obese, and over 85% greater odds of becoming severely obese, relative to matched non-ADHD controls.
There were signs of a dose-response effect. Less than a year’s exposure to methylphenidate was associated with roughly 75% greater odds of becoming severely obese, whereas exposure over a year or more raised the odds 2.3-fold, relative to matched non-ADHD controls. Using MPH increased the prevalence of overweight from 43.2% to 46.5%, with a greater prevalence among those using MPH for more than one year (50.5%).
It is important to note that most of this effect was from ADHD itself, with methylphenidate only assuming a predominant role in severe obesity among those with longer-term exposure to the medicine.
As for height, children with ADHD were no more likely to be short of stature than matched non-ADHD controls. Being prescribed methylphenidate was associated with slightly greater odds (7%) of being short of stature, but there was no dose-response relationship.
Conclusion:
The team concluded, “patients with ADHD, particularly those treated with MPH, had a higher BMI and shorter height at adulthood than individuals without ADHD. Although the observed height difference was clinically small in both sexes and age groups, the findings suggest that long-term MPH exposure may be associated with growth and body composition, highlighting the need for regular monitoring of growth.” They also point out that “Despite these findings, the clinical relevance should be interpreted with caution. In our cohort, the mean difference in height was less than 1 cm (eg, maximum −0.6 cm in females) below commonly accepted thresholds for clinical significance.” Likewise, increases in overweight/BMI were small.
One problem with interpreting the BMI/obesity results is that some of the genetic variants that cause ADHD also cause obesity. If that genetic load increases with severity of ADHD than the results from this study are confounded because those with more severe ADHD are more likely to be treated than those with less severe ADHD.
Due to these small effects along with the many study limitations noted by the authors, these results should be considered alongside the well-established benefits of methylphenidate treatment.
What do we mean by expert? In simple terms, an expert possesses in-depth knowledge and specialized training in a particular field. In order to be considered an expert in any field, a person must have both deep knowledge of and competence in their specific area of expertise. Experts have a background that includes education, research, and experience. In the world of mental health and psychology, this typically means formal credentials (a PhD, MD, etc) in addition to years of study, peer-reviewed publications, and/or extensive clinical experience.
Experts are recognized by their peers (and often by the public) as reliable authorities on a specific topic. Experts usually don’t make big claims without evidence; instead, they cite studies and speak cautiously about what the evidence shows.
Tip: Those looking for likes and clicks will often speak in absolutes (e.g., “refined sugar makes your ADHD worse, but the Keto Diet will eliminate ADHD symptoms”) while experts will use language that emphasizes evidence (e.g., “research has proven that there is no ‘ADHD Diet’, but some evidence has suggested that certain individuals with ADHD may benefit from such dietary interventions as limiting food coloring or increasing omega fatty acids.”)
Social media has created an incredible opportunity for those with ADHD to gain access to invaluable resources, including the creation of communities by and for those with ADHD. Many people with ADHD report feeling empowered and less alone by connecting with others online. These online social platforms provide a space for those with ADHD to share their own perspectives and their lived experience with the disorder. Both inside and outside of mental health-related communities, social media is a powerful tool for sharing information, reducing stigma, and helping people find community. When someone posts about their own ADHD challenges or tips, it can reassure others that they’re not the only ones facing these issues. This kind of peer support is valuable and affirming.
It is vital for those consuming this media, however, to remember that user-generated content on social media is not vetted or regulated. Short TikTok or Instagram videos are designed to grab attention, not to teach nuance or cite scientific studies. As it turns out, most popular ADHD posts are misleading or overly simplistic, at best. One analysis of ADHD TikTok videos found that over half were found to be “misleading” by professionals. Because social feeds reinforces what we already believe (the “echo chamber” effect, or confirmation bias), we can easily see only content that seems to confirm our own experiences, beliefs, or fears.
Stories aren’t a substitute for expert guidance.
It’s important to recognize the difference between personal experience and general expertise. Having ADHD makes you an expert on your ADHD, but it does not make you an expert on ADHD for everyone. Personal stories are not scientific facts. Even if someone’s personal journey is true, the same advice or experience may not apply to others. For instance, a strategy that helps one person focus might have no effect– or possibly even a negative effect– on someone else.
Researchers have found that most ADHD content on social media is based on creators’ own experiences, not on systematic research. In one study, almost every TikTok ADHD creator who listed credentials actually just cited their personal story. Worse, about 95% of those videos never noted that their tips might not apply to everyone (journals.plos.org.) In other words, they sound absolute even though they really only reflect one person’s situation. It’s easy to misunderstand the condition if we take those singular experiences as universal facts.
So how can you tell when someone is speaking from expertise rather than personal experience or hearsay? Experienced professionals usually speak cautiously, rather than in absolutes. They tend to say things like “research suggests,” “some studies show,” or “evidence indicates,” rather than claiming something always or never happens. As one health-communication guide puts it, a sign of a trustworthy source is that they do not speak in absolutes; instead, they use qualifiers like “may,” “might,” or refer to specific studies. For example, an expert might say, “Some people with ADHD may have difficulty with organization,” instead of “ADHD people always lose things.”
Real experts also cite evidence. In science and psychology, experts usually share knowledge through peer-reviewed articles, textbooks, or professional conferences – not just social media posts. Reliable health information is typically backed by references to studies published in reputable journals.
If someone makes a claim online, ask: Do they point to research, or is it just their own testimony? This is why it’s wise to prefer content where the author is a recognized authority (like a doctor or researcher) and where references to scientific studies or official guidelines are provided. In fact, advice from sites ending in “.gov”, “.edu”, or “.org” (government, university, or professional organizations) tends to be more reliable than random blogs. When in doubt, look up who wrote the material and whether it cites peer-reviewed research.
When navigating mental health information online, remember these key points:
If you see sweeping statements like “This one habit will predict if you have ADHD” or “Eliminating this one food will cure your ADHD symptoms”--- that’s a red flag. Instead, the hallmark of expert advice is a tone of humility (“evidence suggests,” “it appears that,” etc.), clear references to studies or consensus statements, and an acknowledgment that individual differences exist.
At the same time, we need to acknowledge that community voices are incredibly valuable – they help us feel understood and less alone. The goal is not to dismiss personal stories, but to balance them with facts and evidence-based information. Let lived experience spark questions, but verify important advice with credible sources. Follow trusted organizations (for example, the National Institutes of Health, CDC, or ADHD specialist groups) and mental health professionals who communicate carefully. Use the online ADHD community for support and sharing tips, but remember it’s just one piece of the puzzle.
By being a savvy reader (checking credentials, looking for cited evidence, and spotting overgeneralizations), you can make the most of online ADHD content. In doing so, you give yourself both the empathy of community and the accuracy of real expertise. That way, you’ll be well-equipped to separate helpful insights from hype and to keep learning from both personal stories and science-based experts.
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.
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