A groundbreaking systems-level study reveals that the connection between ADHD and obesity isn’t just biological — it’s urban. City size, services, and structure can disrupt or intensify how impulsivity translates into physical health.
Key Points at a Glance
- ADHD contributes to obesity via reduced physical activity, shaped by city factors
- Larger cities offer more mental health services and education, reducing obesity risk
- City-level metrics like SAMIs uncover where urban health systems over- or underperform
- Regional disparities highlight how culture and policy impact behavioral health
We often think of obesity as a product of individual behavior or biology. But what if the layout of your city, the availability of mental health care, and even local education levels play just as significant a role? According to new research published in PLOS Complex Systems, the link between ADHD and obesity may be driven not just by impulsivity or genetics, but also by the complex dynamics of urban life.
The study, led by NYU Tandon School of Engineering in collaboration with Italy’s Istituto Superiore di Sanità, took a radically different approach to analyzing public health data. By applying mathematical tools from complexity science — specifically urban scaling laws — researchers examined data from 915 U.S. cities to explore how ADHD influences obesity, and how that relationship is modified by city characteristics.
Their findings are illuminating. Both ADHD and obesity decrease on a per-capita basis as cities grow, a phenomenon known as sublinear scaling. In contrast, access to mental health services and higher education increase faster than population size, suggesting that larger cities deliver disproportionately more in these critical areas. But to go beyond averages, the researchers developed and used Scale-Adjusted Metropolitan Indicators (SAMIs), a novel metric that reveals whether cities outperform or underperform relative to what urban scaling would predict.
Using these tools, the team uncovered a causal chain: ADHD leads to increased physical inactivity, which then raises obesity risk. However, access to mental health care mitigates this inactivity, indirectly lowering obesity rates. Higher levels of college education also correlated with more physical activity and better mental health access, showing how interdependent these urban features are.
“Without accounting for population effects, we’d be making the wrong assumptions about what drives health,” explains senior author Maurizio Porfiri, Director of NYU’s Center for Urban Science + Progress. “Our approach filters out the noise of city size to uncover how environments actually influence behavior and health outcomes.”
What emerges is a dynamic ecosystem where impulsivity, infrastructure, education, and healthcare interact — and where city design and policy can either reinforce or sever harmful pathways between mental and physical health. The SAMI framework not only reveals which cities are defying or failing expectations, but also points policymakers toward effective local interventions.
For instance, the study found that cities in the Southeastern and Southwestern U.S. show greater disparities than others. In many cases, neighboring cities had vastly different obesity or ADHD prevalence, mental health access, or food insecurity levels — a finding that suggests policy and resource allocation may have more impact than geography or demographics alone.
To validate their findings, the team analyzed data from more than 19,000 children from the National Survey of Children’s Health. Consistently, children with more severe ADHD were more likely to be obese, especially when household education was low and physical activity was minimal. The same causal relationships seen across cities played out on the individual level, strengthening the case for systemic change.
The implications of this work are far-reaching. It highlights how health is not just about personal responsibility or medical care, but also about the environments we inhabit. Cities are not passive backdrops; they actively shape how risk factors like ADHD unfold.
This isn’t Porfiri’s first foray into urban complexity. Previous work from his group applied similar tools to understand firearm ownership and violence across U.S. cities — showing again how urban metrics can challenge intuitive assumptions. In both cases, the message is clear: smart cities require smarter analytics.
By combining engineering, data science, and public health, this study demonstrates how advanced analytics can open entirely new frontiers in understanding — and ultimately solving — some of society’s most persistent health challenges.
Source: NYU Tandon School of Engineering
