NUTRITION ISSUES IN GASTROENTEROLOGY, SERIES #226

Reducing Weight Bias in GI Practice to Improve the Clinician/Patient Relationship

October 2022 • Volume XLVI, Issue 10
Beth Rosen

Read Article

Weight bias is negative beliefs and stereotypes based on a person’s weight, size, or shape that impacts the way practitioners provide care. Research shows that weight bias is physically and psychologically harmful to patients and can lead to missed diagnoses and inadequate care. This article addresses the limitations of using fatness as a measure of health, and the danger of perpetuating the assumption that higher weight is synonymous with poorer health. Risks of this assumption encompass weight cycling and its impact on health, as well as the direct impact of weight bias on overall wellness. Included are suggestions for shifting from a weight-centric care approach to a weight-inclusive paradigm in order to create an environment where all patients receive equitable care when visiting their healthcare provider, regardless of their size.

Weight Bias in GI Practice: How it Jeopardizes the Clinician/Patient Relationship

Weight bias, also called weight stigma, obesity stigma, and anti-fat bias is defined as, “negative weight-related attitudes and beliefs that manifest as stereotypes, rejection, prejudice, and discrimination towards individuals of higher weights”.1 Our culture is rife with explicit weight bias – on television, in magazines, and on social media – from body shaming celebrities to public health campaigns proclaiming a “war on obesity.” Weight bias has penetrated and perpetuated in our healthcare system. In many cases this is unintentional harm, but harm is caused nonetheless. There is considerable evidence that reveals that weight bias influences the attitudes of the practitioner including interpersonal communication, perceptions of compliance, diagnosis and treatment, judgment, and decisionmaking.2,3,4 These attitudes impact the quality of care a patient receives, despite best intentions to do no harm.

Implicit Bias and Compromised Care

Implicit bias – unlike explicit bias which is a conscious prejudice – is an unconscious evaluation of others based on characteristics such as race, gender, or size. The lack of awareness surrounding implicit bias is a concern in healthcare because it impacts the care of those

targeted.5 In a scoping review, care of those who experienced weight bias from healthcare providers had a lower rate of use of healthcare services and delayed medical intervention to avoid patronizing and discourteous treatment.5 Patients have experienced their health concerns attributed solely to their weight, which can lead to weight stigma and results in the avoidance of future care as well.5 Nearly 55% of women living in bigger bodies reported delaying or canceling an appointment if they anticipated being weighed during their visit.5 These experiences are not rare. In a study of almost 5,000 first-year medical students from 49 medical schools across the country, implicit weight bias was comparable to explicit bias against racial minorities, while their explicit bias for larger-bodied people was more negative when measured against attitudes for race, sexuality, and socioeconomic status.6 Implicit bias compromises care for those impacted, both through the avoidance and/or delay of health care, and the quality of care provided by the biased health care professional. It can result in reduced quality and quantity of care, and less patient-centered care, which can impact the patient’s trust in the provider and their recommendations.4 Research shows that providers recommend weight loss and exercise more often for patients with larger bodies as compared to those with average-sized bodies, focusing on body size rather than medical interventions to treat or manage diagnoses.7 Implicit bias can cause lasting harm; physicians may overattribute symptoms and problems to body size, or misdiagnose a patient, or fail to follow up with testing and symptom management options beyond weight loss recommendations.4

Body Terminology

For the purposes of this article, the terms “obesity” and “overweight” to describe people with bigger bodies will be used with quotations to denote how they can be stigmatizing. These terms are based on the Body Mass Index (BMI) which is considered to be flawed and not intended to measure the risk of health problems of populations, nor the health of individuals.8 Language is critical; these words can perpetuate weight bias by their definitions alone: “Obesity” stems from the Latin phrase “eaten itself fat.” This assumes that everyone in a larger body is so because of a lack of willpower, overeating, laziness, and a disregard for health.5,9 The term “overweight” assumes that there is a correct weight that all bodies should be at for a particular height and being above that weight is correlated with the same stereotypes as “obesity.” Many in the fat liberation movement have reclaimed the word “fat” and use it as a body descriptor, not unlike “tall” or “muscular.”10 Other preferred terms include, “in a larger/bigger body,” or, “at a higher weight.” It is not recommended to use “fat” as a body descriptor unless your client has asked you to use it, otherwise, it could be seen as adding Ancel Keys studied 7,500 white men in order to find the most useful of the then-available ways to measure body fat during regular office visits.11 He changed the name to Body Mass Index and noted in his research that it detected “obesity” correctly to, or causing, weight stigma or bias.

Limitations of Body Size Classification

Body size classification is measured using the BMI which was created 200 years ago by a Belgian physicist looking to measure the “ideal man”.11 It was called Quetelet’s Index and it was designed to measure statistics within a population and not fatness in individuals. In the 1970s, researcher only 50% of the time.11

BMI has obvious limitations:

  • It does not take into consideration fat versus fat-free mass.
  • Age is not adjusted for, where muscle and bone deteriorate over time.
  • There are also differences in body composition based on gender, fitness level, and race, yet none of these are accounted for in the BMI which uses only height and weight in the calculation. 

There is an abundance of epidemiological research showing that “obesity” is associated with longer survival with diabetes, cancer, and cardiovascular diseases than thinner people with the same diagnoses.12,13,14 It has also been observed that seniors who fall into the “overweight” category often live longer than their thinner counterparts and the mortality rate of those with a BMI >30kg/m2 has declined over time.15 In a meta-analysis of 2.88 million people conducted by the Center for Disease Control (CDC), the lowest all-cause mortality rate was within the “overweight” category, and the highest hazard ratio was in the “underweight” category.12 Data from multiple studies show that using BMI to determine health miscategorizes the majority of healthy people; in 2008, the number was 51%,16 and in 2020, that number increased to 74%.16,17

Nearly 60 years later, this flawed calculation is being used to measure fatness in almost every medical office.

Assumptions and Risks Weight-Centric Healthcare

Our current healthcare model can be considered using a weight-centric, or weight-normative, approach – the terms are used interchangeably – which emphasizes weight as a determinant of health, and weight loss as a prescription for treatment of poor health. This model puts the responsibility for health and the maintenance of health on the patient.18 There are two obvious risks to this approach: Focusing on weight can lead to missing the true condition because weight is blamed for the chief complaint and weight loss is prescribed as treatment. When “lose weight and exercise” is prescribed and weight loss is not achieved or sustained by the patient, they may cease participation in health-promoting behaviors that can improve health markers, like including fiber and being active.18

The Assumption: higher weights are synonymous with poorer health

The main assumption made in weight-centric healthcare that contributes to and perpetuates weight bias is that higher weight is synonymous with poorer health. While much research exists that correlates fatness with disease states, causation cannot be assumed.18,19 Often, these studies neglect to control for factors such as fitness level, activity, nutrient intake, weight cycling, socioeconomic status, and experienced or internalized weight bias.

In a meta-analysis of over one million people, those in the “overweight” category and “obese class 1” category had lower all-cause mortality rates than those in the “normal” and “overweight” categories.12 In all BMI categories, sedentary behavior was linked with mortality – this is the absence of a health behavior, independent of weight.12 In another study that focuses just on weight, liposuction was used to remove fat to determine if insulin sensitivity was positively impacted. The researchers concluded that decreasing abdominal fat on its own does not improve metabolic markers for health. This is just one example of how weight loss on its own does not improve health.20

The Risks: weight cycling

Weight cycling,  or “yo-yo” dieting, is the common term for losing and gaining weight over many attempts without sustained weight loss. Attempts to lose weight are more common amongst, and more commonly prescribed to, patients with big bodies. Weight cycling increases inflammation, and inflammation increases the risk of many diseases.18,21 It also increases emotional distress, maladaptive and disordered eating behaviors, Binge Eating Disorder, and is a predictor of future weight gain.18  The National Institutes of Health (NIH) published a report stating that ⅓ – ⅔ of weight is regained within one year and almost all is regained within five years after ending a diet.25 Another study determined that ⅓ – ⅔ of dieters regain more weight than they lost on their diets.22 One of the largest reviews of the impact of weight cycling was the Framingham Heart Study. More than 5000 people were examined over a 32-year period. The results indicated that weight cycling was strongly linked to overall mortality, and mortality and morbidity related to coronary heart disease.23 A similar result was found in a study where individuals with “obesity” did not attempt weight loss and did not have a higher risk of death as compared to the subjects in the “normal” BMI category.24 Despite these findings, weight loss continues to be prescribed as a first-line treatment for a multitude of symptoms and diagnoses, even though weight loss is technically not a health behavior or within a person’s total control. Many of the studies that link weight loss to improved health do not control for the health behaviors that participants may have engaged in that led to a reduction in weight, for instance, adding or increasing the frequency of exercise, the consumption of fruits and vegetables, and establishing regular sleep habits, which are actual health behaviors that can result in improved biochemical markers for health, independent of weight.

The Risks: weight bias

Possibly the most important risk to understand from the assumption that a higher weight indicates poor health is the increased experience of weight bias. Examples of weight bias in healthcare include providers making assumptions about a patient’s health and lack of appropriate equipment such as blood pressure cuffs for larger bodies among others (see Table 1).17,18

There are many health risks linked to weight stigma. The most notable is that weight stigma can lead to weight gain.22,25,26,27 Other risks of weight stigma include increased chronic stress, which is linked to increased cardiovascular disease and diabetes, increased inflammation, increased anxiety, mood disorders, Binge Eating Disorder, and cardiac dysregulation.17,21 Weight bias also promotes negative body image and low self-esteem.21 Partaking in health behaviors is undermined by weight bias; people in larger bodies who have experienced stigma may avoid the gym or exercising where others can see them.

Practical Approaches to Reducing Weight Bias

If healthcare practitioners move away from using weight as a determinant of health, there is an opportunity to include all bodies in the quest for good health. The main tenet of the weight inclusive paradigm is that every body is capable of striving for health and well-being, independent of weight, given equitable access to non-stigmatizing health care.28 This model focuses on health behaviors to achieve health rather than weight loss, and is, in its nature, avoidant of weight bias.21

Health At Every Size®

The Health At Every Size® (HAES®) approach is one example of a weight-inclusive model. The Association for Size Diversity and Health describes this model as, “A continuously evolving alternative to the weight-centered approach to treating clients and patients of all sizes. It is also a movement working to promote size-acceptance, to end weight discrimination, and to lessen the cultural obsession with weight loss and thinness.28” HAES® is made up of five principles:

  1. Weight Inclusivity: Accept and respect the inherent diversity of body shapes and sizes and reject the idealizing or pathologizing of specific weights.
  2. Health Enhancement: Support health policies that improve and equalize access to information and services, and personal practices that improve human well-being, including attention to individual physical, economic, social, spiritual, and emotional needs.
  3. Respectful Care: Acknowledge our biases, and work to end weight discrimination, weight stigma, and weight bias.
  4. Eating for Well-Being: Promote flexible, individualized eating based on hunger, satiety, nutritional needs, and pleasure, rather than any externally regulated eating plan focused on weight control. 
  5. Life-Enhancing Movement: Support physical activities that allow people of all sizes, abilities, and interests to engage in joyful movement, to the degree that they choose.

This approach has been studied in several randomized controlled trials with a similar conclusion: The HAES® approach is associated with statistically significant and clinically relevant improvements in blood pressure, blood lipids, selfesteem, body image, energy expenditure, eating behaviors, and eating disorder pathology.29,30,31 Promoting body acceptance and self-worth, a focus on internal versus external cues, the effects of food choices on well-being, and choosing movement activities that allowed them to enjoy their bodies were included in the counseling.

Intuitive eating

The Intuitive Eating approach evolved out of the HAES® model in 1995. The creators of the Intuitive Eating principles, both highly experienced registered dietitians and eating disorder experts (Evelyn Tribole and Elyse Resch), describe it as, “a self-care eating framework, which integrates instinct, emotion, and rational thought.  Intuitive Eating is a weight-inclusive, evidence-based model with a validated assessment scale and over 100 studies to date”.32 Intuitive Eating is based on Interoceptive Awareness, which is a person’s ability to perceive physical sensations that arise within the body. This is the body’s direct experience with getting needs met. Dieting and intentional weight loss activities promote the opposite of this. Therefore,

dieting is considered cognitive dissonance; when thoughts, actions, and speech do not align with the body’s needs. Ten Intuitive Eating principles guide people to stop dieting, and instead begin to trust their body’s cues, nourish themselves, move in ways that bring joy, respect their bodies, and care for them using health

Table 3. Recommended Reading

behaviors, regardless of size. To date, there are thousands of Certified Intuitive Eating Counselors across the globe and many other practitioners who have adopted Intuitive Eating into their practices with patients (see Table 2).

Patient-centered care

Changes in our healthcare system have impacted the patient-provider relationship.33 Reductions in reimbursement and the increase in administrative tasks have reduced face-to-face time with patients leading to reduced satisfaction, and increased frustration and stigmatization by both the provider and patient.33 Patient-Centered Care consists of three tenets: Communication, partnership, and health promotion.34 Benefits of this model include improved patient satisfaction, reduced cost, and greater health outcomes.34 A weightinclusive approach can be incorporated under the “communication” tenet. Exploration of the patient’s symptoms and experiences within the patient-provider relationship can provide space for implementing a healthcare plan that considers these experiences and reduces the risk of failed health outcomes.34 The goal to implement effective patient-centered care can be met by implementing training skills training to provide care, both at the medical school and medical practice levels to reduce bias and increase satisfaction and health.33

Practicing Weight-Inclusive Care

In addition to the Health At Every Size®, Intuitive Eating principles and techniques, and Patient Centered Care, there are practical tools to encourage patients to participate in health behaviors that are not only backed by research, but also reduce the harm caused by weight bias.

Examine biases

All humans carry both implicit and explicit bias. Harvard University’s Project Implicit administers free, online testing of implicit weight bias (see Table 2). The National Institutes of Health (NIH) offers both online testing and training for reducing implicit bias (see Table 2). Consider providing testing and training for providers, administrators, and those in direct patient care to reduce harm.

Understand the complex pathophysiology of body size

The old adage of “calories in vs. calories out,” or the “energy balance model” leaves out the endocrine, metabolic, and nervous system signals that impact eating and energy needs.35 Research shows that genetics and heritability are responsible for approximately 75% of what makes up BMI.35 In a study of over 4000 identical twins, intentional weight loss activities led to a higher weight and BMI compared to the twin who did not participate in weight loss activities.27 Weight gain was accelerated over time with the increase in attempts to lose weight.27 Consider moving away from using BMI as a determinant of health and incorporating HAES® and Intuitive Eating principles for health behaviors instead.

Rethink the necessity of the scale

Being weighed at the doctor’s office is one of the chief reasons people with bigger bodies, especially women, avoid seeking care.36 Use the tenets of patient-centered care and explain the necessity for a weigh-in. Honor the right of patients to refuse being weighed and/or the discussion of weight, should they so choose. If a change in weight is related to a diagnosis, asking the patient about unintended weight gain or loss may be a substitute for the scale. When patients express a desire not to know their weight, honor this request by covering up the number during the visit, and in other places where a patient may be able to view it (patient portals, and in discharge papers). When trust is breached, there is a risk of harm to the patient.

Change the language

Using person-first language is becoming more standard in our field and can minimize bias. Instead of using the words “obese” and “overweight” to describe people, remember that people are not the disease (a person is not “cancerous,” they are a person-first, who has cancer). 

Create a weight-inclusive office space

Changes to the office setting can have a big impact. Equipment and furniture that is appropriate for larger body sizes means having blood pressure cuffs for all arm sizes, armless seating in the waiting room, and office seating designed to hold weight over 250 pounds.

Prescribe health behaviors

Instead of prescribing weight loss, consider discussing health behaviors that are within your patient’s control. “Lose weight and exercise” is a prescription for harmful care. Referrals to weightinclusive registered dietitians (Table 2) can help them focus on improving health without a focus on weight. Consider taking a curious approach to asking about what patients do for movement before telling someone to simply “exercise more.”

Screen for disordered eating behaviors

People with a history of weight cycling may also possess maladaptive eating behaviors. Patients with suspected eating disorders should be referred to a specialist so they can get the help they need to recover from the eating disorder before treating their GI issues.37 Screening tools include Eating Attitudes Test (EAT-26), Eating Disorder Examination Questionnaire (EDE-Q), and the Coeliac Disease Food Attitudes and Behaviors Scale (CD-FAB) (see Table 2).

CONCLUSIONS

Using fatness as a measure of health perpetuates weight stigma and implicit bias. Using stigmatizing language, BMI as a measure of health, and prescribing weight loss as treatment to the patient can impact the patient-provider relationship negatively. Shifting to a weight-inclusive paradigm that includes principles of Health At Every Size®, Intuitive Eating, and Patient-Centered Care can reduce these risks and fosters health promotion, equitable care, and harm reduction in GI practices. Making this change includes examining biases, changing the language used during patient and peer consults, reducing the emphasis on weight, screening for eating disorders, and creating a weight-inclusive space throughout the office. There is still much work to be done by healthcare providers and researchers, but the tips and resources provided here are a good start to reducing weight bias. For more resources see Table 3.

References

  1. Tylka TL, Kroon Van Diest AM: The Intuitive Eating Scale-2: item refinement and psychometric evaluation with college women and men. J Couns Psychol 2013;60:137–153.
  2. Tomiyama AJ, Carr D, Granberg EM, et al: How and why weight stigma drives the obesity ‘epidemic’ and harms health. BMC Med 2018;16:123.
  3. Udo T, Purcell K, Grilo CM: Perceived weight discrimination and chronic medical conditions in adults with overweight and obesity. Int J Clin Pract 2016;70:1003-1011.
  4. Phelan SM, Burgess DJ, Yeazel MW, et al: Impact of weight bias and stigma on quality of care and outcomes for patients with obesity. Obes Rev 2015;16:319-326.
  5. Lawrence BJ, Kerr D, Pollard CM, et al: Weight bias among health care professionals: A systematic review and meta-analysis. Obesity 2021;29:1802-1812.
  6. Phelan SM, Dovidio JF, Puhl RM, et al: Implicit and explicit weight bias in a national sample of 4,732 medical students: the medical student CHANGES study. Obesity 2014;22:1201-1208.
  7. Seymour J, Barnes JL, Schumacher J, et al: A Qualitative Exploration of Weight Bias and Quality of Health Care Among Health Care Professionals Using Hypothetical Patient Scenarios. Inquiry 2018;55:46958018774171.
  8. Bosy-Westphal A, Müller MJ: Diagnosis of obesity based on body composition-associated health risks-Time for a change in paradigm. Obes Rev 2021;22 Suppl 2:e13190.
  9. Hilbert A, Rief W, Braehler E: Stigmatizing attitudes toward obesity in a representative population-based sample. Obesity 2008;16:15291534.
  10. Kwan S. Framing the Fat Body: Contested Meanings between Government, Activists, and Industry. Sociol Inq 2009;79:25-50.
  11. Garabed E: Adolphe Quetelet (1796–1874)—the average man and indices of obesity. Nephrol Dial Transplant 2008;23:47–51.
  12. Flegal KM, Kit BK, Orpana H, et al: Association of all-cause mortality with overweight and obesity using standard body mass index categories: a systematic review and meta-analysis. JAMA 2013;309(1):71-82.
  13. Lennon H, Sperrin M, Badrick E, et al: The Obesity Paradox in Cancer: a Review. Curr Oncol Rep 2016;18(9):56.
  14. Elagizi A, Kachur S, Lavie CJ, et al: An Overview and Update on Obesity and the Obesity Paradox in Cardiovascular Diseases. Prog Cardiovasc Dis 2018;61:142-150.
  15. Zheng H, Echave P, Mehta N, et al: Life-long body mass index trajectories and mortality in two generations. Ann Epidemiol 2021;56:18-25.
  16. Wildman RP, Muntner P, Reynolds K, et al: The obese without cardiometabolic risk factor clustering and the normal weight with cardiometabolic risk factor clustering: prevalence and correlates of 2 phenotypes among the US population (NHANES 1999-2004). Arch Intern Med 2009;168:1617–1624.
  17. Hunger JM, Smith JP, Tomiyama AJ: An Evidence-Based Rationale for Adopting Weight-Inclusive Health Policy. Soc Issues Policy Rev 2020;14:73-107.
  18. Tylka TL, Annunziato RA, Burgard D, et al: The weightinclusive versus weight-normative approach to health: evaluating the evidence for prioritizing well-being over weight loss. J Obes. 2014;2014:983495.
  19. Hoerger TJ. Controversies in obesity mortality: a tale of two studies. Health Promot Econ 2006;1:1–4
  20. Klein S, Fontana L, Young VL, et al: Absence of an effect of liposuction on insulin action and risk factors for coronary heart disease. N Engl J Med 2004;350:2549-2557.
  21. Bacon L, Aphramor L: Weight science: evaluating the evidence for a paradigm shift. Nutr J 2011;10:69.
  22. Mann T, Tomiyama AJ, Westling E, et al: Medicare’s search for effective obesity treatments: diets are not the answer. Am Psychol 2007;62:220-233.
  23. Lissner L, Odell P, D’Agostino R, et al: Variability of Body Weight and Health Outcomes in the Framingham Population. N Engl J Med 1991;324:1839-1844.
  24. Hotchkiss J, Leyland A: The relationship between body size and mortality in the linked Scottish Health Surveys: cross-sectional surveys with follow-up. Int J Obes 2011;35:838–851.
  25. NIH Technology Assessment Conference Panel: Methods for voluntary weight loss and control. Ann Intern Med 1992;116:942-949.
  26. Department of Health and Aging. National and Medical Research Council. Clinical practice guidelines for the management of overweight and obesity in adults, adolescents and children in Australia, Melbourne 2013:161.
  27. Pietiläinen, KH, Saarni, SE, Kaprio, J, et al: Does dieting make you fat? A twin study. Int Jour Obes 2005;36:456–464.
  28. ASDAH | Committed to Size Diversity in Health and HAES®.
    (n.d.). Retrieved June 25, 2022, from ASDAH website: http://www. asdah.org
  29. Tanco S, Linden W, Earle T: Well-being and morbid obesity in women: a controlled therapy evaluation. Int J Eat Disord 1998;23:325-339.
  30. Bacon L, Stern JS, Van Loan MD, et al: Size acceptance and intuitive eating improve health for obese, female chronic dieters. J Am Diet Assoc 2005;105:929-936.
  31. Provencher V, Bégin C, Tremblay A, et al: Health-At-Every-Size and eating behaviors: 1-year follow-up results of a size acceptance intervention. J Am Diet Assoc 2009;109:1854-1861.
  32. Tribole E, Resch E: Intuitive Eating: A Recovery Book for the Chronic Dieter: Rediscover the Pleasures of Eating and Rebuild Your Body Image. St. Martin’s Paperbacks; 1996.
  33. Drossman DA, Ruddy J: Improving Patient-Provider Relationships to Improve Health Care. Clin Gastroenterol Hepatol 2020;18:14171426.
  34. Constand MK, MacDermid JC, Dal Bello-Haas V, et al: Scoping review of patient-centered care approaches in healthcare. BMC Health Serv Res 2014;14:271.
  35. Hall KD, Farooqi IS, Friedman JM, et al: The energy balance model of obesity: beyond calories in, calories out. Am J Clin Nutr 2022;115:1243-1254.
  36. Drury CA, Louis M: Exploring the association between body weight, stigma of obesity, and health care avoidance. J Am Acad Nurse Pract 2002;14:554-561.
  37. Santonicola A, Gagliardi M, Guarino M, et al: Eating Disorders and Gastrointestinal Diseases. Nutrients 2019;11:3038.

Download Tables, Images & References