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It was the start of the fall semester of my sophomore year of college.
At my small women’s college, the previous semester’s gossip had been about our classmate, S*. She had gone from being very thin to noticeably gaining a lot of weight in a few months. The rumors were that S was pregnant and gave birth over summer break. As a busy biology premed major, this was my first time hearing the news. So when I saw her standing in the hallway, back to her previous weight, I was excited for her.
In true extravert fashion, I commented on the baby and her new size. But no sooner had the words left my mouth than I regretted them.
The hall grew awkwardly silent as S’s face flushed and she asked, “Excuse me?!” Instantly I knew that the rumors weren’t true.
Thankfully, at that moment, the classroom opened and we walked in. Whew! After class, S asked if we could talk. She explained that she had a thyroid tumor and struggled to adjust to the treatments, which caused her weight fluctuations. She had never been pregnant.
My awkward statement had been the first time anyone on campus had directly mentioned her weight, though she suspected that people were talking about her. We became fast friends after this rocky beginning. Although we lost touch after college, S taught me an invaluable lesson about making assumptions about people’s weight: Ask before you assume.
Now, years later, as an internist and obesity specialist, this lesson continues to be reinforced daily.
In daily life, comments about weight can be perceived as rude. In the clinical setting, however, assumptions about weight are a form of weight bias. Weight bias can lead to weight stigma and even be dangerous to health care.
Let’s discuss the insidious influence of weight bias in health care through two commonly used phrases and then look at a few solutions to address weight bias in health care individually and systematically.
Common weight bias assumptions
“Great job, you lost weight!” In checking your patient’s vital signs, you notice that this patient with obesity has a significant weight change. You congratulate them upon entering the room. Unfortunately, their weight loss was a result of minimal eating after losing a loved one. This isn’t healthy weight loss. One of the adverse effects of weight bias is that it infers that weight loss is always a good thing, especially in people with larger bodies. This is a dangerous presumption. Let’s remember that the body favors fat storage, hence why “unintentional weight loss” is a recognized medical condition prompting evaluation. We have to be careful not to celebrate weight loss “at all costs,” such as fad diets that haven’t been shown to improve health outcomes.
Furthermore, patients who lose weight quickly (more than 4-8 lb/month) require closer follow-up and evaluation for secondary causes of weight loss. Patients may lose weight at a faster rate with the new antiobesity medications, but clinicians still should ensure that age-appropriate health maintenance screening is done and be vigilant for secondary causes of weight changes.
“Have you tried losing weight yet?” Three times. That’s how many times Chanté Burkett went to her doctor about her painful, enlarging firm stomach. She was advised to continue working on weight loss, which she did diligently. But Ms. Burkett’s abdomen kept growing and her concerns were dismissed. A visit to urgent care and a CT scan revealed that Ms. Burkett’s excess abdominal “fat” was a 13-lb mucinous cystadenoma. Sadly, cases like hers aren’t rare, isolated events. Weight bias can cause anchoring on one diagnosis, preventing consideration of other diagnostic possibilities. Even worse, anchoring will lead to the wrong intervention, such as prescribing weight loss for presumed increased adiposity instead of ordering the appropriate testing.
It’s also essential to recognize that, even if someone does have the disease of obesity, weight loss isn’t the solution to every medical concern. Even if weight loss is helpful, other, more pressing treatments may still be necessary. Telling a person with obesity who has an acute complaint to “just lose weight” is comparable to telling a patient with coronary artery disease who presents with an 80% vessel occlusion and chest pain to follow a low-fat diet. In both cases, you need to address the acute concern appropriately, then focus on the chronic treatment.
Ways to reduce clinical weight bias
How do you reduce clinical weight bias?
Ask, don’t assume. The information from the scale is simply data. Instead of judging it positively or negatively and creating a story, ask the patient. An unbiased way to approach the conversation is to say, “Great to see you. You seem [positive adjective of choice]. How have you been?” Wait until the vitals section to objectively discuss weight unless the patient offers the discussion earlier or their chief complaint lists a weight-related concern.
Order necessary tests to evaluate weight. Weight is the vital sign that people wear externally, so we feel that we can readily interpret it without any further assessment. However, resist the urge to interpret scale data without context. Keeping an open mind helps prevent anchoring and missing critical clues in the clinical history.
Address weight changes effectively. Sometimes there is an indication to prescribe weight loss as part of the treatment plan. However, remember that weight loss isn’t simply “calories in vs. calories out.” Obesity is a complex medical disease that requires a multimodal treatment approach. As clinicians, we have access to the most powerful tools for weight loss. Unfortunately, weight bias contributes to limited prescribing of metabolic medications (“antiobesity medications” or AOMs). In addition, systemic weight bias prevents insurance coverage of AOMs. The Treat and Reduce Obesity Act has been introduced into Congress to help improve life-transforming access to AOMs.
Acknowledge your bias. Our experiences make us all susceptible to bias. The Harvard Weight Implicit Association Test is free and a helpful way to assess your level of weight bias. I take it annually to ensure that I remain objective in my practice.
Addressing weight bias needs to extend beyond the individual level.
Systemically, health care needs to address the following:
Language. Use people-centered language. For example, “People aren’t obese. They have obesity.”
Accessibility. Health care settings must be comfortable and accessible for people of all sizes. Furthermore, improvements to access the services that comprehensive obesity care requires, such as AOMs, bariatric procedures and bariatric surgery, mental health care, nutrition, fitness specialists, health coaches, and more, are needed.
Education. Medical students and trainees have to learn the newest obesity science and know how to treat obesity effectively. Acknowledge and address biased tools. Recent data have shown that some of our screening tools, such as body mass index, have inherent bias. It’s time to focus on using improved diagnostic tools and personalized treatments.
We are at a pivotal time in our scientific understanding of body weight regulation and the disease of obesity. Clinical weight bias is primarily rooted in flawed science influenced by biased cultural norms and other forms of discrimination, such as racial and gender bias. We must move past assumptions to give our patients the optimal individualized care they need. So next time you observe a weight change, instead of commenting on their weight, say, “Great to see you! How have you been?”
S*: Initial has been changed to protect privacy.
Dr. Gonsahn-Bollie is an integrative obesity specialist focused on individualized solutions for emotional and biological overeating. Connect with her at www.embraceyouweightloss.com or on Instagram @embraceyoumd. Her bestselling book, “Embrace You: Your Guide to Transforming Weight Loss Misconceptions Into Lifelong Wellness”, was Healthline.com’s Best Overall Weight Loss Book of 2022 and one of Livestrong.com’s 8 Best Weight-Loss Books to Read in 2022. She has disclosed no relevant financial relationships. A version of this article originally appeared on Medscape.com.
It was the start of the fall semester of my sophomore year of college.
At my small women’s college, the previous semester’s gossip had been about our classmate, S*. She had gone from being very thin to noticeably gaining a lot of weight in a few months. The rumors were that S was pregnant and gave birth over summer break. As a busy biology premed major, this was my first time hearing the news. So when I saw her standing in the hallway, back to her previous weight, I was excited for her.
In true extravert fashion, I commented on the baby and her new size. But no sooner had the words left my mouth than I regretted them.
The hall grew awkwardly silent as S’s face flushed and she asked, “Excuse me?!” Instantly I knew that the rumors weren’t true.
Thankfully, at that moment, the classroom opened and we walked in. Whew! After class, S asked if we could talk. She explained that she had a thyroid tumor and struggled to adjust to the treatments, which caused her weight fluctuations. She had never been pregnant.
My awkward statement had been the first time anyone on campus had directly mentioned her weight, though she suspected that people were talking about her. We became fast friends after this rocky beginning. Although we lost touch after college, S taught me an invaluable lesson about making assumptions about people’s weight: Ask before you assume.
Now, years later, as an internist and obesity specialist, this lesson continues to be reinforced daily.
In daily life, comments about weight can be perceived as rude. In the clinical setting, however, assumptions about weight are a form of weight bias. Weight bias can lead to weight stigma and even be dangerous to health care.
Let’s discuss the insidious influence of weight bias in health care through two commonly used phrases and then look at a few solutions to address weight bias in health care individually and systematically.
Common weight bias assumptions
“Great job, you lost weight!” In checking your patient’s vital signs, you notice that this patient with obesity has a significant weight change. You congratulate them upon entering the room. Unfortunately, their weight loss was a result of minimal eating after losing a loved one. This isn’t healthy weight loss. One of the adverse effects of weight bias is that it infers that weight loss is always a good thing, especially in people with larger bodies. This is a dangerous presumption. Let’s remember that the body favors fat storage, hence why “unintentional weight loss” is a recognized medical condition prompting evaluation. We have to be careful not to celebrate weight loss “at all costs,” such as fad diets that haven’t been shown to improve health outcomes.
Furthermore, patients who lose weight quickly (more than 4-8 lb/month) require closer follow-up and evaluation for secondary causes of weight loss. Patients may lose weight at a faster rate with the new antiobesity medications, but clinicians still should ensure that age-appropriate health maintenance screening is done and be vigilant for secondary causes of weight changes.
“Have you tried losing weight yet?” Three times. That’s how many times Chanté Burkett went to her doctor about her painful, enlarging firm stomach. She was advised to continue working on weight loss, which she did diligently. But Ms. Burkett’s abdomen kept growing and her concerns were dismissed. A visit to urgent care and a CT scan revealed that Ms. Burkett’s excess abdominal “fat” was a 13-lb mucinous cystadenoma. Sadly, cases like hers aren’t rare, isolated events. Weight bias can cause anchoring on one diagnosis, preventing consideration of other diagnostic possibilities. Even worse, anchoring will lead to the wrong intervention, such as prescribing weight loss for presumed increased adiposity instead of ordering the appropriate testing.
It’s also essential to recognize that, even if someone does have the disease of obesity, weight loss isn’t the solution to every medical concern. Even if weight loss is helpful, other, more pressing treatments may still be necessary. Telling a person with obesity who has an acute complaint to “just lose weight” is comparable to telling a patient with coronary artery disease who presents with an 80% vessel occlusion and chest pain to follow a low-fat diet. In both cases, you need to address the acute concern appropriately, then focus on the chronic treatment.
Ways to reduce clinical weight bias
How do you reduce clinical weight bias?
Ask, don’t assume. The information from the scale is simply data. Instead of judging it positively or negatively and creating a story, ask the patient. An unbiased way to approach the conversation is to say, “Great to see you. You seem [positive adjective of choice]. How have you been?” Wait until the vitals section to objectively discuss weight unless the patient offers the discussion earlier or their chief complaint lists a weight-related concern.
Order necessary tests to evaluate weight. Weight is the vital sign that people wear externally, so we feel that we can readily interpret it without any further assessment. However, resist the urge to interpret scale data without context. Keeping an open mind helps prevent anchoring and missing critical clues in the clinical history.
Address weight changes effectively. Sometimes there is an indication to prescribe weight loss as part of the treatment plan. However, remember that weight loss isn’t simply “calories in vs. calories out.” Obesity is a complex medical disease that requires a multimodal treatment approach. As clinicians, we have access to the most powerful tools for weight loss. Unfortunately, weight bias contributes to limited prescribing of metabolic medications (“antiobesity medications” or AOMs). In addition, systemic weight bias prevents insurance coverage of AOMs. The Treat and Reduce Obesity Act has been introduced into Congress to help improve life-transforming access to AOMs.
Acknowledge your bias. Our experiences make us all susceptible to bias. The Harvard Weight Implicit Association Test is free and a helpful way to assess your level of weight bias. I take it annually to ensure that I remain objective in my practice.
Addressing weight bias needs to extend beyond the individual level.
Systemically, health care needs to address the following:
Language. Use people-centered language. For example, “People aren’t obese. They have obesity.”
Accessibility. Health care settings must be comfortable and accessible for people of all sizes. Furthermore, improvements to access the services that comprehensive obesity care requires, such as AOMs, bariatric procedures and bariatric surgery, mental health care, nutrition, fitness specialists, health coaches, and more, are needed.
Education. Medical students and trainees have to learn the newest obesity science and know how to treat obesity effectively. Acknowledge and address biased tools. Recent data have shown that some of our screening tools, such as body mass index, have inherent bias. It’s time to focus on using improved diagnostic tools and personalized treatments.
We are at a pivotal time in our scientific understanding of body weight regulation and the disease of obesity. Clinical weight bias is primarily rooted in flawed science influenced by biased cultural norms and other forms of discrimination, such as racial and gender bias. We must move past assumptions to give our patients the optimal individualized care they need. So next time you observe a weight change, instead of commenting on their weight, say, “Great to see you! How have you been?”
S*: Initial has been changed to protect privacy.
Dr. Gonsahn-Bollie is an integrative obesity specialist focused on individualized solutions for emotional and biological overeating. Connect with her at www.embraceyouweightloss.com or on Instagram @embraceyoumd. Her bestselling book, “Embrace You: Your Guide to Transforming Weight Loss Misconceptions Into Lifelong Wellness”, was Healthline.com’s Best Overall Weight Loss Book of 2022 and one of Livestrong.com’s 8 Best Weight-Loss Books to Read in 2022. She has disclosed no relevant financial relationships. A version of this article originally appeared on Medscape.com.
It was the start of the fall semester of my sophomore year of college.
At my small women’s college, the previous semester’s gossip had been about our classmate, S*. She had gone from being very thin to noticeably gaining a lot of weight in a few months. The rumors were that S was pregnant and gave birth over summer break. As a busy biology premed major, this was my first time hearing the news. So when I saw her standing in the hallway, back to her previous weight, I was excited for her.
In true extravert fashion, I commented on the baby and her new size. But no sooner had the words left my mouth than I regretted them.
The hall grew awkwardly silent as S’s face flushed and she asked, “Excuse me?!” Instantly I knew that the rumors weren’t true.
Thankfully, at that moment, the classroom opened and we walked in. Whew! After class, S asked if we could talk. She explained that she had a thyroid tumor and struggled to adjust to the treatments, which caused her weight fluctuations. She had never been pregnant.
My awkward statement had been the first time anyone on campus had directly mentioned her weight, though she suspected that people were talking about her. We became fast friends after this rocky beginning. Although we lost touch after college, S taught me an invaluable lesson about making assumptions about people’s weight: Ask before you assume.
Now, years later, as an internist and obesity specialist, this lesson continues to be reinforced daily.
In daily life, comments about weight can be perceived as rude. In the clinical setting, however, assumptions about weight are a form of weight bias. Weight bias can lead to weight stigma and even be dangerous to health care.
Let’s discuss the insidious influence of weight bias in health care through two commonly used phrases and then look at a few solutions to address weight bias in health care individually and systematically.
Common weight bias assumptions
“Great job, you lost weight!” In checking your patient’s vital signs, you notice that this patient with obesity has a significant weight change. You congratulate them upon entering the room. Unfortunately, their weight loss was a result of minimal eating after losing a loved one. This isn’t healthy weight loss. One of the adverse effects of weight bias is that it infers that weight loss is always a good thing, especially in people with larger bodies. This is a dangerous presumption. Let’s remember that the body favors fat storage, hence why “unintentional weight loss” is a recognized medical condition prompting evaluation. We have to be careful not to celebrate weight loss “at all costs,” such as fad diets that haven’t been shown to improve health outcomes.
Furthermore, patients who lose weight quickly (more than 4-8 lb/month) require closer follow-up and evaluation for secondary causes of weight loss. Patients may lose weight at a faster rate with the new antiobesity medications, but clinicians still should ensure that age-appropriate health maintenance screening is done and be vigilant for secondary causes of weight changes.
“Have you tried losing weight yet?” Three times. That’s how many times Chanté Burkett went to her doctor about her painful, enlarging firm stomach. She was advised to continue working on weight loss, which she did diligently. But Ms. Burkett’s abdomen kept growing and her concerns were dismissed. A visit to urgent care and a CT scan revealed that Ms. Burkett’s excess abdominal “fat” was a 13-lb mucinous cystadenoma. Sadly, cases like hers aren’t rare, isolated events. Weight bias can cause anchoring on one diagnosis, preventing consideration of other diagnostic possibilities. Even worse, anchoring will lead to the wrong intervention, such as prescribing weight loss for presumed increased adiposity instead of ordering the appropriate testing.
It’s also essential to recognize that, even if someone does have the disease of obesity, weight loss isn’t the solution to every medical concern. Even if weight loss is helpful, other, more pressing treatments may still be necessary. Telling a person with obesity who has an acute complaint to “just lose weight” is comparable to telling a patient with coronary artery disease who presents with an 80% vessel occlusion and chest pain to follow a low-fat diet. In both cases, you need to address the acute concern appropriately, then focus on the chronic treatment.
Ways to reduce clinical weight bias
How do you reduce clinical weight bias?
Ask, don’t assume. The information from the scale is simply data. Instead of judging it positively or negatively and creating a story, ask the patient. An unbiased way to approach the conversation is to say, “Great to see you. You seem [positive adjective of choice]. How have you been?” Wait until the vitals section to objectively discuss weight unless the patient offers the discussion earlier or their chief complaint lists a weight-related concern.
Order necessary tests to evaluate weight. Weight is the vital sign that people wear externally, so we feel that we can readily interpret it without any further assessment. However, resist the urge to interpret scale data without context. Keeping an open mind helps prevent anchoring and missing critical clues in the clinical history.
Address weight changes effectively. Sometimes there is an indication to prescribe weight loss as part of the treatment plan. However, remember that weight loss isn’t simply “calories in vs. calories out.” Obesity is a complex medical disease that requires a multimodal treatment approach. As clinicians, we have access to the most powerful tools for weight loss. Unfortunately, weight bias contributes to limited prescribing of metabolic medications (“antiobesity medications” or AOMs). In addition, systemic weight bias prevents insurance coverage of AOMs. The Treat and Reduce Obesity Act has been introduced into Congress to help improve life-transforming access to AOMs.
Acknowledge your bias. Our experiences make us all susceptible to bias. The Harvard Weight Implicit Association Test is free and a helpful way to assess your level of weight bias. I take it annually to ensure that I remain objective in my practice.
Addressing weight bias needs to extend beyond the individual level.
Systemically, health care needs to address the following:
Language. Use people-centered language. For example, “People aren’t obese. They have obesity.”
Accessibility. Health care settings must be comfortable and accessible for people of all sizes. Furthermore, improvements to access the services that comprehensive obesity care requires, such as AOMs, bariatric procedures and bariatric surgery, mental health care, nutrition, fitness specialists, health coaches, and more, are needed.
Education. Medical students and trainees have to learn the newest obesity science and know how to treat obesity effectively. Acknowledge and address biased tools. Recent data have shown that some of our screening tools, such as body mass index, have inherent bias. It’s time to focus on using improved diagnostic tools and personalized treatments.
We are at a pivotal time in our scientific understanding of body weight regulation and the disease of obesity. Clinical weight bias is primarily rooted in flawed science influenced by biased cultural norms and other forms of discrimination, such as racial and gender bias. We must move past assumptions to give our patients the optimal individualized care they need. So next time you observe a weight change, instead of commenting on their weight, say, “Great to see you! How have you been?”
S*: Initial has been changed to protect privacy.
Dr. Gonsahn-Bollie is an integrative obesity specialist focused on individualized solutions for emotional and biological overeating. Connect with her at www.embraceyouweightloss.com or on Instagram @embraceyoumd. Her bestselling book, “Embrace You: Your Guide to Transforming Weight Loss Misconceptions Into Lifelong Wellness”, was Healthline.com’s Best Overall Weight Loss Book of 2022 and one of Livestrong.com’s 8 Best Weight-Loss Books to Read in 2022. She has disclosed no relevant financial relationships. A version of this article originally appeared on Medscape.com.