Many People with Severe Obesity Face Medical Discrimination, Study Finds
Key Takeaways:
- A new study reveals that over 40% of clinics in the United States refused to schedule an appointment for a hypothetical patient with severe obesity.
- More than half of practices surveyed lacked the basic facilities or equipment required to provide appropriate care to patients with a body mass index (BMI) of 60 or greater.
- Researchers warn that discrimination and inadequate resources may contribute to poorer health outcomes, including delayed cancer detection, among people living with severe obesity.
Widespread discrimination in clinical settings
People living with severe obesity frequently encounter discrimination and barriers when seeking medical care, according to a new study published in the Annals of Internal Medicine. Researchers reported that about 2 in 5 (41%) clinics refused to schedule an appointment for a hypothetical patient weighing 465 pounds.
One receptionist at an orthopaedic surgeon’s office stated: “We’ve reached our limit for bariatric patients at this site,” without offering further explanation.
The study highlights a critical issue in access to care: beyond outright refusals, more than half of clinics (52%) did not have the equipment or facilities necessary to provide basic medical care for patients with very high body weights. Severe obesity is defined as a BMI of 40 or higher, with extremely severe obesity considered a BMI of 60 or greater.
Lack of facilities and equipment
Many clinics lacked essential infrastructure, including examination tables or chairs that could safely support higher weights, wide enough doorways and hallways for patient mobility, and appropriately sized medical gowns.
Dr Tara Lagu, senior author of the study and adjunct lecturer of medicine and medical social sciences at Northwestern University Feinberg School of Medicine in Chicago, emphasised the harmful impact of such deficiencies:
“Patients living with severe obesity are likely already struggling with shame and difficulty navigating the world. To tell a patient that they can’t be examined on a table, or can’t wear a gown, or need to stand during an appointment makes what should be a safe place and the experience of seeing a doctor humiliating and degrading. We need to acknowledge, as a profession, that all people deserve better than this.”
Affected population and health risks
According to the researchers, approximately 1 in every 270 Americans – close to 1 million adults – lives with extremely severe obesity (BMI ≥ 60). These individuals are two to three times more likely to experience significant health problems compared with the general population.
Despite this increased risk, previous studies have shown that people with obesity are less likely to receive preventive health services such as cancer screenings. Dr Lagu explained:
“Obesity affects cancer screenings, and failure to screen can result in later cancer detection. We’re always attributing worse outcomes in higher-weight patients to weight itself, but more and more studies are now pointing to worse care, lack of care or being care avoidant as possible reasons for these delays.”
Study design and findings
To investigate barriers to care, researchers used a “secret shopper” approach, in which callers attempted to schedule an appointment for a hypothetical patient weighing 465 pounds. They contacted 300 clinics across four metropolitan areas – Boston, Cleveland, Houston, and Portland, Oregon. The study covered five specialties: dermatology, endocrinology, obstetrics and gynaecology, orthopaedic surgery, and ear, nose, and throat (ENT).
Lead researcher Dr Molly Hales, a physician at University of Chicago Medicine, noted that the caller questions were intentionally designed to suggest possible urgent medical needs:
“We designed some of the questions our callers asked to be red flags for a receptionist to think, ‘I should really schedule this person,’ because the questions suggested the patient might have cancer and need an urgent workup.”
Despite this, only 59% of clinics overall were willing to schedule the appointment. ENT specialists were least likely to agree, with only 48% offering an appointment, while endocrinologists were most likely to accept and to have suitable facilities.
Humiliating workarounds
Even among clinics that agreed to see the hypothetical patient, around 1 in 6 (16%) suggested workarounds that could be humiliating, such as requiring the patient to stand during the exam or to use a sheet instead of a gown.
Dr Hales observed:
“Our numbers likely underestimate the magnitude of the problem. Likely, very few high-weight patients who are scheduling appointments know to even ask if they can be accommodated based on their weight, and they might be hesitant to ask these questions or advocate for themselves because of the social stigma.”
Potential solutions
The researchers highlighted that a Clinical Environment Checklist has been developed to guide outpatient clinics in ensuring they can provide appropriate care for patients with obesity. However, it has not been widely adopted.
Dr Hales noted:
“They designed the checklist to be used by general outpatient clinics and tested it in both primary care and subspecialty settings, so it’s a good resource for clinics in determining where there are opportunities for improvement.”
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New Study Finds Wearables May Reshape Obesity Care
Key Takeaways:
- A new study from Northwestern University demonstrates how wearable devices can identify five distinct overeating patterns in people living with obesity, paving the way for more personalised interventions.
- The HabitSense body camera and NeckSense necklace provide unprecedented yet privacy-conscious insights into real-world eating behaviour.
- Researchers emphasise that overeating is not simply a matter of willpower but is shaped by complex emotional, environmental and behavioural factors.
Rethinking obesity treatment through technology
What if a smartwatch, necklace or discreet camera could sense when someone is about to overeat, and instead gently encourage healthier decisions?
Northwestern University scientists are exploring this idea through a pioneering lifestyle medicine programme that combines wearable technology with behavioural analysis. The approach uses three different devices – a necklace, a wristband and a body-mounted camera – to capture eating habits in natural settings, with privacy firmly safeguarded.
“Overeating is a major contributor to obesity, yet most treatments overlook the unconscious habits that drive it,” explained corresponding author Nabil Alshurafa, Associate Professor of Behavioural Medicine at Northwestern University Feinberg School of Medicine and, by courtesy, of Computer Science and Electrical and Computer Engineering at Northwestern’s McCormick School of Engineering.
Five distinct overeating patterns identified
In the study, published in npj Digital Medicine (part of the Nature Portfolio), 60 adults living with obesity wore the three sensors and logged contextual information – such as mood, activity and social setting – using a smartphone app over a two-week period. The project generated thousands of hours of data, revealing that overeating typically followed one of five recurring patterns:
- Take-out feasting – heavy consumption of delivered or takeaway meals.
- Evening restaurant revelry – social dining leading to excessive intake.
- Evening craving – compulsive late-night snacking.
- Uncontrolled pleasure eating – spontaneous binges driven by enjoyment.
- Stress-driven evening nibbling – grazing triggered by anxiety.
“These patterns reflect the complex dance between environment, emotion and habit,” said Alshurafa. “What’s amazing is now we have a roadmap for personalised interventions.”
A step towards personalised interventions
The findings create a foundation for future clinical practice, in which individuals may be profiled according to their dominant overeating pattern and then matched with tailored interventions.
Lead author Farzad Shahabi, a PhD student in Computer Science and member of Alshurafa’s laboratory, highlighted the significance:
“What struck me most was how overeating isn’t just about willpower. Using passive sensing, we were able to uncover hidden consumption patterns in people’s real-world behaviour that are emotional, behavioural and contextual. Seeing the patterns emerge from the data felt like turning on a light in a room we’ve all been stumbling through for decades. Our long-term vision is to move beyond one-size-fits-all solutions and toward a world in which health technology feels less like a prescription and more like a partnership.”
HabitSense – A body camera with built-in privacy
The project’s roots date back to when Alshurafa borrowed a police body camera from Northwestern’s campus police. He modified it to record only food-related actions, creating what is now called HabitSense.
HabitSense is the first patented Activity-Oriented Camera (AOC), which uses thermal sensors to activate recording solely when food enters the field of view. Unlike conventional egocentric cameras that capture everything from the wearer’s perspective, AOCs record actions rather than scenes. This innovation preserves bystander privacy while still collecting critical behavioural data.
NeckSense – Recording eating behaviours in real time
Participants also wore NeckSense, a necklace designed by Alshurafa and his team. NeckSense is the first technology able to passively and precisely monitor multiple eating behaviours. It can detect when someone is eating, how many bites they take, their chewing rate and the frequency with which their hand moves to their mouth. This provides researchers with highly detailed insight into real-world eating events.
A wrist-worn activity tracker – similar to a Fitbit or Apple Watch – completed the three-sensor system.
From personal struggles to scientific mission
Alshurafa’s scientific interest in obesity stems from his own personal journey. Throughout his younger life, his weight fluctuated by 40 to 50 pounds, with repeated attempts at dieting often undermined by late-night binge eating in front of the television.
“I tried to turn my personal struggle into a scientific mission that promises to reshape obesity treatment,” he reflected. “By merging computer science, behavioural medicine and a dash of Jane Goodall–style curiosity, we’re working to lead the way toward truly personalised, habit-based health care. This study marks only the beginning of a journey toward smarter and more compassionate interventions for millions grappling with overeating.”
Study team and support
The research team behind this project brought together a wide range of expertise from Northwestern and beyond. Contributors included PhD student in computer science Boyang Wei, HABits Lab research study coordinator Chris Romano, and undergraduate student Rowan McCloskey. They were joined by adjunct faculty members Annie Lin of the University of Minnesota and Mahdi Pedram of the University of North Texas, as well as former Northwestern faculty member Tammy Stump, now at the University of Utah. Jacob Schauer, Assistant Professor of Preventive Medicine, also played a role, alongside computer science PhD student Glenn Fernandes and senior engineer Tanmeet Butani (MS ’23).
The study was funded by the US National Institutes of Health through the National Institute of Diabetes and Digestive and Kidney Diseases.
CCH insight:
This is a fascinating study, which shows how new technologies may be able to provide innovative digital solutions to health issues, in this case identifying behavioural patterns underpinning overeating. These results need to be verified in larger studies, and then interventions trialled to address the different eating patterns, so we are a long way from viable new interventions, but this is an intriguing addition to the development of precision treatments for obesity.
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Vanderbilt Researchers Use AI to Address Gaps in Long-Term Obesity Care
Key Takeaways:
- A $1 million Eli Lilly grant will fund a two-year Vanderbilt University Medical Center (VUMC) project using artificial intelligence (AI) to address gaps in obesity care.
- The initiative will analyse electronic health records (EHRs), survey patients and clinicians, and build a multi-agent AI system to develop evidence-based strategies for improving long-term engagement.
- A patient-facing mobile application will be designed and piloted in VUMC obesity clinics to support shared decision-making and sustained weight management.
Major investment in addressing gaps in care
Vanderbilt University Medical Center (VUMC) has secured a $1 million grant from Eli Lilly and Company to fund a two-year research project aimed at improving continuity of care for people living with obesity. The initiative seeks to understand why many individuals discontinue treatment and to create scalable solutions to help them stay engaged in long-term care.
“Obesity is a chronic, relapsing condition that requires ongoing management, yet too often it is treated episodically because of barriers like delayed medication access,” explained You Chen, PhD, Associate Professor of Biomedical Informatics and the project’s Principal Investigator for informatics and technology. “We’re combining data-driven insights, stakeholder input and multi-agent AI to understand where continuity breaks down and to design evidence-based interventions that keep patients engaged.”
Data-driven insights and stakeholder engagement
In its first year, the research team will analyse VUMC’s electronic health records to identify patterns distinguishing people who remain in continuous follow-up from those who disengage. Patient and clinician surveys will be conducted to capture real-world barriers to care, including logistical, financial and psychological challenges.
The findings will be integrated into a multi-agent AI system, featuring simulated physician, nurse and dietitian agents. This system will generate and prioritise strategies for maintaining engagement, which will then be reviewed by panels of clinicians, informaticians and patient representatives.
Patient-facing app to support engagement
The second year of the project will focus on designing and piloting a mobile application to be used in VUMC obesity clinics. This app is intended to help patients view and interpret their own health data, complete pre-visit tasks, and communicate more effectively with their care teams.
“By helping patients view and interpret their own data, complete previsit tasks, and communicate more effectively with care teams, the app will aim to strengthen shared decision-making and sustain engagement over time,” said Chen.
Clinical leadership and broader impact
The project’s clinical lead is Gitanjali Srivastava, MD, Professor of Medicine in the Division of Diabetes, Endocrinology and Metabolism.
“Medicine has evolved, and we need to adapt to new technological advances while catering to patient needs,” Srivastava stated. “It’s about designing practical tools and processes that fit naturally into patients’ lives and clinicians’ workflows, ultimately supporting healthier weight management over time.”
Chen emphasised that the project is intended to be scalable across health systems. The researchers believe that the human–AI collaborative approach developed through this project could serve as a reproducible framework for improving continuity of care for other chronic conditions that require long-term management.
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