Obesity Hypoventilation Syndrome: From Physiologic Principles to Clinical Practice

Obesity Hypoventilation Syndrome: From Physiologic Principles to Clinical Practice summarizes the current state of knowledge regarding the epidemiology, physiology and treatment of obesity hypoventilation syndrome (OHS). Currently, the identification and management of OHS is suboptimal, especially in the acute setting, hence the misdiagnosis or mislabeling of the problem has a significant impact on patient outcomes. This volume brings together all aspects of assessment and management into a main resource for understanding the complex physiological and clinical consequences of this condition.

• Provides one page chapter summaries that cover epidemiology, physiology and treatment options
• Presents an easy to use reference on obesity hypoventilation syndrome, including symptoms
• Contains chapters with detailed discussions of topics, including color images, graphs and tables that summarize current research

• Language: English
• Publisher: Academic Press
• Release date: Jul 26, 2020
• ISBN: 9780128152911

Book preview

expectations.

Part I

Historical and social introduction

Chapter 1: Obesity: A social and public policy perspective

Carolyn T. Bramantea; Kimberly A. Gudzuneb    a General Internal Medicine and Pediatrics, University of Minnesota, Minneapolis, MN, United States

b General Internal Medicine, Johns Hopkins University, Baltimore, MD, United States

Abstract

Obesity is one of the most common chronic conditions that clinicians encounter, and it is associated with many comorbidities. Many factors contribute to the development of obesity in any one individual. These include both forces within the individual’s control and macrolevel forces outside the individual’s control. The macrolevel forces include influences at the interpersonal, organizational, community, and society levels. Appreciating these many influences may help clinicians approach patients with obesity without bias or judgment, recognize the challenges they face, and treat them with respect.

Keywords

Obesity; Social determinants of health; Health disparities

The obesity epidemic

Obesity has reached epidemic proportions across the globe, and the most recent estimates approximate that 40% of the U.S. population has obesity.¹ Obesity is defined as having a body mass index (BMI) greater than 30 kg/m² and can also be categorized into Class I (BMI: 30–34.9 kg/m²), Class II (BMI: 35–39.9 kg/m²), Class III (BMI: ≥  40 kg/m²), Class IV (BMI: ≥  50 kg/m²), and Class V (BMI: ≥  60 kg/m²). In the health care setting, obesity is one of the most common chronic health conditions that a clinician is likely to encounter.², ³

In particular, Class III obesity is associated with greater mortality and morbidity,⁴ including the development of obesity hypoventilation syndrome.⁵ The overall prevalence of Class III obesity in the United States was 7.7% of adults in 2015–16, which has increased from 5.7% of adults in 2007–08.⁶ The prevalence of Class IV obesity, more than doubled from 2000 to 2010.⁷ A BMI of 40 kg/m² or greater is an indication for bariatric surgery (or a BMI ≥ 35 kg/m² with one obesity-related comorbidity), but risks of surgical complications increase with BMI > 60 kg/m².⁸ Obesity, and in particular Class III obesity or above, is more common among persons with low socioeconomic background.⁹, ¹⁰

Disparities in obesity and related conditions

While rates of obesity are high among all racial and ethnic groups, they are particularly high among U.S. minorities. These disparities start in childhood, with obesity being more common in Native American (31%), Latino (22%), and Black (21%) youth, and less common among White (16%) and Asian (13%) children.¹¹ These differences persist into adulthood, with obesity being more common among Native American, Latino, and Black adults than among White and Asian adults (Fig. 1.1).⁶, ¹²

Fig. 1.1 Age-adjusted prevalence of obesity among U.S. adults over age 20 years by race: 2015–16. Source Center for Disease Control Summary Health Statistics 2017.

These disparities in obesity are significant given the association between obesity and other chronic diseases. Obesity causes negative outcomes in nearly all organ systems. It increases the risk of cardiovascular disease, including stroke, myocardial infarction, hypertension, and high cholesterol. It also increases the risk of diabetes, renal disease, certain cancers, infertility, birth defects, gallbladder disease, arthritis, and sleep apnea.⁴, ¹³–¹⁶, In addition to having higher rates of obesity, minorities also often have higher rates of these related comorbidities.¹⁷

Obesity prevalence is influenced by environmental factors such as the physical/built environment, the social environment, and economic status.¹⁸, ¹⁹ For example, proximity to grocery stores, exercise facilities, and parks has been associated with lower BMI.²⁰–²⁴ The availability of grocery stores and recreation facilities is limited in neighborhoods with low socioeconomic status (SES), limiting access to healthy foods and opportunity to exercise for their predominantly minority residents.²⁵–²⁷ This probably explains why obesity disproportionately impacts residents of low SES, frequently minority neighborhoods.²⁸, ²⁹ Ultimately, these disparities highlight the complex biopsychosocial influences that contribute to obesity, and therefore, we will consider obesity in the context of the social ecological model.

Overview of social ecological model

The social ecological model is a conceptual framework for understanding the multilevel factors that affect behavior and health.³⁰ This model has been adapted to understand many different diseases, including obesity and its related comorbidities.³¹, ³² In this chapter, we will consider how individual, interpersonal, organizational, community, and policy-level factors may influence an individual’s risk of developing obesity (Fig. 1.2).

Fig. 1.2 Adapted social ecological model of obesity.

Individual-level influences on obesity

At the individual level, there are biologic, genetic, psychologic, and behavioral factors that predispose individuals to developing obesity. Biologically, the drive to consume food is affected by neurohormonal feedback mechanisms in the brain and gastrointestinal system,³³ which are formed by influences from the environment, lifestyle, genetics, and the cortico-limbic system via learning-memory and award-emotion connections.³³ When food is ingested, hormones from the gut reach the caudal brainstem and hypothalamus, which then affect autonomic controls, energy balance, and satiation.³³ A review paper by Lenard and Berthoud depicts the interactions of these feedback mechanisms, which are affected by genetic, epigenetic, environmental, and lifestyle forces.³³

From a genetic standpoint, true monogenetic or syndromic causes of obesity are rare (Box 1.1). Of these rare causes of obesity, Prader-Wili, Bardet-Biedle, Albright Hereditary Osteodystrophy, and mutations in proopiomelanocortin neurons, leptin receptors, and leptin deficiency, are often associated with class III obesity, which may result in a greater risk of obesity hypoventilation.³³, ³⁴

Box 1.1

Monogenetic and syndromic obesity

•Monogenetic mutations:

oProopiomelanocortin (POMC) neurons

oMelanocortin 4 receptor (MC4R)

oCongenital leptin and receptor deficiency

•Syndromes linked with obesity:

oPrader-Willi syndrome

oBardet-Biedl syndrome

oFragile X syndrome

oBeckwith-Wiedemann syndrome

oCohen syndrome

oAlbright Hereditary Osteodystrophy syndrome

oAlstrom syndrome

For most individuals, genetic predispositions to obesity are theorized to derive from complex, polygenetic, non-Mendelian, causes.³⁵ There are also epigenetic influences that increase one’s chance of developing obesity.³⁵ An example of epigenetic influence is the nutritional state of the intrauterine environment: maternal undernutrition or overnutrition causes fetal programming that increases risk of obesity, cardiovascular disease (including hypertension, coronary artery disease, and heart failure),³⁶ and diabetes mellitus later in life.³⁷

Psychologic influences play a part in the corticolimbic system that affects the drive to eat. This system is programed by early life experiences, memories, and patterns of reward and emotions associated with food.³³ Depression and anxiety are common causes of overeating because they lead to failure of self-regulation and an inability to participate in weight-management activities such as exercise, procuring healthy foods, and preparing healthful meals.³⁸ Additionally, many medications used to treat depression, anxiety, and other psychologic diseases often cause weight gain.³⁹

Finally, behavioral factors, such as patterns of eating, physical activity, and sleep habits, contribute to the development of excess adiposity.¹³ Patterns of eating behavior are the most significant behavioral contributor to energy imbalance.⁴⁰, ⁴¹ Physical activity (exercise and nonexercise activity thermogenesis [small movements throughout the day]) contributes to short-term as well as long-term energy expenditure by helping individuals build lean muscle mass, which raises one’s resting metabolic rate.¹³ Both eating and physical activity are affected by sleep, as insufficient or poor-quality sleep makes individuals less likely to engage in healthy eating and physical activity. Thus, treating sleep disorders are important for treating obesity.

Interpersonal-level influences

An individual’s social network can influence health and adiposity.⁴² In theory, social norms and behavioral modeling about diet and exercise from other people influence individuals’ choices.⁴² For example, adolescents with overweight are twice as likely to have friends who also have overweight.⁴³ According to data from the Framingham Heart Study, adults are 57% more likely to develop obesity if a friend develops obesity, 40% more likely if a sibling develops obesity, and 37% more likely if a spouse develops obesity.⁴⁴

Family relationships are important for understanding childhood obesity, given the genetic, behavioral, psychologic, and social correlates within a household. Children whose parents have overweight or obesity are more likely to have overweight or obesity themselves.⁴⁵, ⁴⁶ Regardless of a child’s current weight, obesity in a parent more than doubles the risk for that child developing obesity in adolescence and adulthood.⁴⁷, ⁴⁸ Intergenerational transfer of obesity is likely multicomponent, involving the aforementioned factors as well as the transfer of the gut microbiota.⁴⁹ Microbiota transmitted to a baby during vaginal delivery help establish the biodiversity of the intestinal microbiome, which is consider to be an endocrine organ.⁵⁰ Dysbiosis of the gut microbiome (i.e., through lack of microbiome diversity because of C-section delivery), can alter the production of gastrointestinal peptides that signal satiety in the brain, resulting in increased food intake.⁵⁰

Finally, a household’s economic status also influences obesity, as poverty leads to greater risk of obesity in developed countries.⁵¹ For example, in a low-income U.S. county where the household income is around $25,000, the prevalence of obesity was 37%. In contrast, in a U.S. county with a median income >$100,000, the prevalence of obesity was 16%. One explanation for this relationship between poverty and obesity is food insecurity.⁵² In concept, food security means that all household members have access at all times to enough food for an active, healthy life.⁵³ Food insecurity ranges from the reduction of the quality, variety, or desirability of diet, with little or no indication of reduced food intake, to the repeated incidents of disrupted eating patterns and reduced food intake.⁵⁴ Food insecurity is associated with obesity, through increased food consumption when food is available (opportunistic eating), and because many inexpensive foods in the US are calorie-dense.⁵²

Organizational-level influences

The health care system is an important organizational structure that influences the experiences of patients with obesity. We will consider several aspects within the health care system, including challenges related to clinicians (diagnosing obesity, treating obesity, and weight bias) as well as challenges related the physical setting of a health care facility.

Most of the interactions between patients and health care systems are largely with clinicians. And despite the frequency with which clinicians see patients with obesity, they often fail to diagnose it. One study found that only a third of patients with obesity receive a diagnosis of obesity and that these patients were more likely to receive weight-related counseling.⁵⁵ Therefore, the formal recognition of obesity is the first step to manage it.¹³, ⁵⁶

Weight loss is an important intervention for many chronic diseases.⁵⁷ Yet, clinicians are often not well prepared to help their patients lose weight. Clinicians cite the lack of time and skills as well as the lack of reimbursement for weight management services as barriers to providing weight loss counseling to patients with obesity.⁵⁸ When patient encounters are examined, clinicians often fail to correctly use evidence-based counseling strategies that have been shown to improve behavior and reduce weight such as the 5A’s (Box 1.2) or motivational interviewing.⁵⁹, ⁶⁰

Box 1.2

Examples of the 5A’s model for behavior change for weight management

⁵¹

Over the last decade, four new weight-loss medications have received approval from the Food and Drug Administration for long-term use to treat obesity. Clinicians may not be familiar enough with these medications to prescribe them to their patients—most primary care physicians report not knowing about weight loss medications, surgery, or community resources for weight loss.⁶¹ Despite the high prevalence of obesity among primary care patients,³ only 2% of a cohort of insured patients were prescribed weight loss medications.⁶² Lack of insurance coverage for these medications is also a challenge because most patients cannot afford paying for them out of pocket.

Another challenge to the patient-clinician relationship is weight bias. Stigma and discrimination against individuals with obesity are very common in the United States and occur at rates similar to the rates of racial discrimination.⁶³ Rates of implicit and explicit bias among medical students toward patients with obesity are similar to rates of racial discrimination, and higher than rates of discrimination toward persons who use IV drugs.⁶⁴

Weight bias increases as BMI increases. In a study of the barriers to routine gynecologic cancer screening of women with obesity, less than 15% of women with BMI 25–35 kg/m² reported encountering disrespectful treatment and negative attitudes from providers.⁶⁵ In contrast, more than 30% of women with a BMI > 45 kg/m² reported disrespectful treatment and 45% reported negative attitude from providers.⁶⁵ The association between BMI and bias was also present from the perspective of physicians, as primary care clinicians have reported having lower levels of respect for patients with obesity.⁶⁶ Studies have documented that clinicians and health care personnel hold negative attitudes towards patients with obesity.⁶⁷, ⁶⁸ This is of import for patients with obesity hypoventilation syndrome who are at high risk for experiencing weight stigma because of their very high BMIs. Unfortunately, there are no studies on weight bias specifically in patients with sleep apnea.

Rapport between patients and clinicians is critical to successful counseling. Biased clinicians build less rapport with patients who have obesity, which may reduce the effectiveness of their behavioral counseling.⁶⁹ Patients who perceive that their clinicians judge them negatively because of their weight were less likely to achieve a clinically significant weight loss.⁷⁰ It also appears that experiencing weight bias contributes to doctor-shopping behaviors by patients with obesity, which in turn increases in their health care utilization.⁷¹ Clinician weight bias may also delay performing recommended preventive services such as cancer screening in patients with obesity.⁶⁵

Weight bias originates not only from interactions with health care personnel but also from the physical space in a clinic. For example, patients’ bodies may not be safely accommodated by the chairs available in the waiting and examination rooms, the width and maneuverability of walkways, and the design of the examination tables. These physical space factors might explain why 66% of primary-care clinicians reporting being frustrated when they deal with patients with obesity and in 82% reporting that it is challenging to examine patients with obesity.⁶¹ Among women who delay recommended preventive healthcare, 82% do so because of their weight.⁶⁵ Basic medical devices like scales or blood pressure cuffs may not be available in the appropriate sizes needed to perform accurate assessments. Additionally, the weight limits on other medical equipment, such as MRI machines and CT scans, reduce the ability of patients with high BMIs to access these forms of imaging. Forty-six percent of patients report they delay medical care because of medical equipment as basic as exam gowns do not accommodate their sizes.⁶⁵

Weight bias and stigmatizing experiences have been associated with poorer health among patients with obesity.⁷² Individuals report negative emotional sequelae of weight bias, and they can even internalize this weight bias, resulting in negative thoughts about themselves. In the US, it is estimated that 40% of adults with overweight or obesity have internalized this bias.⁷² In a systematic review by Pearl and Puhl, internalization of bias was strongly associated with negative mental health outcomes and a possible association with physical health outcomes.⁷² One important consequence of internalized weight bias is that it hinders maintenance of weight loss.⁷³

A strong relationship between patients and their clinicians improves patients’ self-efficacy and adherence to treatment recommendations such as weight-management suggestions.⁷⁴ Weight bias is associated with decreased emotional connection between clinicians and patients,⁶⁹ and may further worsen health disparities among patients with obesity.

Given these organizational-level influences, health systems must improve the quality of care for patients with obesity. A health system may begin to address weight bias by making sure its physical environment and personnel meet the needs of patients with obesity.⁷⁵ Health systems should in their clinics prioritize providing physical space and equipment that are compatible with individuals of any size. Currently, there is a significant lack among health care professionals of weight-bias awareness and training,⁷⁶ and as discussed earlier clinicians have knowledge and skills gaps related to obesity management.⁶¹ Health systems could promote training in weight management to improve their clinicians’ comfort and ability to appropriately and sensitively address obesity with their patients, because even brief interventions have been shown to reduce weight bias among medical trainees.⁷⁷ Lastly, health systems and clinicians can play an important role in advocating for insurance coverage for weight management therapies and medications.

Community-level influences

Community-level factors are often elements that an individual cannot control but have a substantial influence on the individual’s behaviors and health. Health is affected by the housing situation of the community—for example, public housing residents are disproportionately affected by obesity and cardiovascular disease.²² In 1992, the U.S. congress authorized the Moving to Opportunity (MTO) for Fair Housing program. MTO allowed the Department of Housing and Urban Development to provide rental assistance to Americans living in low-income housing to move to higher-income neighborhoods. During the MTO demonstration project, public housing residents who were given the opportunity to move to higher-income neighborhoods had significantly lower risk of severe obesity after 10 years as compared to individuals who stayed in low-income public housing communities.⁷⁸ The results of this study suggest that changing community factors can affect obesity risk.

The built environment can also influence physical activity and diet. One’s ability to be physical active is partly explained by one’s access to green space, sidewalks, and recreational areas.²⁰, ²¹ Community levels of crime also affect one’s ability to be physically active in one’s neighborhood. Neighborhood violent crime is associated with a 21% increased odds of developing metabolic syndrome.⁷⁹ Conversely, greater access to grocery stores is associated with lower rates of obesity.²⁵ Examples of community-level interventions to address these types of built environment barriers include creating more walking paths and neighborhood parks.⁸⁰, ⁸¹ To date, these types of interventions typically have small effects on BMI at a population level.⁸⁰, ⁸¹ For example, a multiprong community-wide intervention to increase physical activity resulted in only a 0.5 unit decrease in BMI z-score.⁸⁰

Society-level influences

Lastly, society-level influences such as health care policies can influence individuals’ weight status. An example of a health policy change with implications for obesity is the expanded coverage benefit for obesity screening and counseling among Medicare beneficiaries in 2011.⁸² This covered benefit may attempt to address, in part, the challenge of lack of insurance coverage for services cited by clinicians. While this is generally a positive development in obesity management, there are several shortcomings in the benefits’ design and the effectiveness of this new coverage is unknown.⁸³ For example, the reimbursement rate is low (approximately $25.00 for 15 min of counseling by a clinician),⁸⁴ and it requires that the counseling for weight management occurs in a primary care setting.⁸³ Other societal level influences include policy interventions that attempt to improve public health, such as taxes on sugar sweetened beverages and cap-and-trade policy to reduce added sugar.⁸⁵, ⁸⁶ In a recent study of children, taxes on sugar sweetened beverages reduced the BMI by 0.085 kg/m². The mechanism by which this is achieved is debatable.⁸⁵ It may be related to using the extra tax revenue to pay for obesity prevention efforts rather than to a direct effect of the tax on the consumption of sugar sweetened bevereges.⁸⁵

Key points

•Obesity is pervasive and significantly increases morbidity.

•The disparities in obesity prevalence by race, socioeconomic background, and neighborhood highlight the complex biopsychosocial influences behind it.

•Factors at the individual, interpersonal, organizational, community, and society levels have implications for the development of obesity.

•Appreciating these many influences may lead clinicians to approach patients with obesity without bias or judgment and to treat them with respect.

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Chapter 2: History of obesity hypoventilation

Stephen W. Littletona,b    a Division of Pulmonary and Critical Care, Loyola University Medical Center, Maywood, IL, United States

b Division of Pulmonary and Critical Care, Hines VA Hospital, Hines, IL, United States

Abstract

An examination of the history of obesity-hypoventilation syndrome requires a diverse review of history and the history of science, and of literature. There were remarkably accurate descriptions of patients who were likely to have obesity-hypoventilation syndrome for many centuries. As scientists in the 17th and 18th centuries began to understand the composition of air, our understanding of respiration also advanced. The development of the polysomnogram and arterial blood gas testing finalized our ability to reliably quantify and diagnose this syndrome.

Keywords

Obesity; Hypoventilation; Pulmonary physiology; History

Respiration and the ancient Greeks

By the end of the ancient Greek empire, the Greeks had developed a surprisingly accurate description of the respiratory system, and how that system interacts with the circulatory system. Early accounts were less accurate, though. One of the first descriptions was by the philosopher Empedocles (492–432 BCE), who described breathing by comparing it to a clepsydra, or water clock (Ref. 1, p. 145). This analogy suggests that it was the rhythmic quality of breathing that was most striking to this early philosopher. Later, Hippocrates (450–380 BCE), drawing from a humoral concept first proposed by Empedocles, posited that man is composed of four elements: black bile, yellow bile, blood, and phlegm. Plato (427–347 BCE) accepted this elemental description and went on to note the importance of air, and proposed the purpose of the lungs: to provide the body with that air. When there is an excess of phlegm, and phlegm impedes breathing, several different pathophysiologies can arise (Ref. 1, p. 347).

Hippocrates also wrote that blood vessels contained more than blood, but also a kind of air called pneuma. The function of the blood vessels is to transmit this pneuma to the body in order to cool it and, finally, depositing it to the brain allowed intelligence (Ref. 1, pp. 349–350). Dissection then became more common, and Herophilus of Chalcedon first differentiated arteries from veins, and stated that the arteries contained blood and pneuma, but the veins only blood.

Later still, Erasistratus, an early anatomist, described a circulatory system where pneuma from the lungs traveled to the left ventricle of the heart through the pulmonary vein. Galen (200–130 BCE) refined Erasistratus’ model, stating inspired air was altered by the lungs to a pneuma-like