**2. Obesity**

### **2.1 The obesity pandemic**

Over the past 40 years, there has been a sharp rise in worldwide obesity with prevalence nearly tripling since 1975 [4]. According to the World Health Organization (WHO), overweight and obesity are defined as having abnormal or excessive fat accumulation that may impair health [4]. Studies show the global obesity epidemic is worsening. In 2016, nearly 2 billion adults over 18 years worldwide were overweight and of these, over 650 million were obese [4].

Prevalence of obesity and severe obesity in the U.S. continue to rise [5]. Currently, the rates of obesity exceed 30% in most sex and adult age groups, whereas its prevalence has reached 17% among children and adolescents, defined as a BMI exceeding the 95th percentile [6]. In 2017–2018, it was estimated that 42.4% of U.S. adults aged 20 and over were obese (**Figure 1**) and 9.2% were severely obese [7] (**Figure 2**), and these may be underestimated. In a study comparing rates of obesity diagnosis to national rates of obesity based on BMI data from the Behavioral Risk Factor Surveillance System, the authors found that obesity is largely underdiagnosed and undertreated in clinical settings [8].

#### **Figure 1.**

*Prevalence of obesity among adults aged 20 and over, by sex and age: United States, 2017–2018. Notes: Estimates for adults aged 20 and over were age-adjusted by the direct method to the 2000 U.S. Census population using the age groups 20–39, 40–59, and 60 and over. Crude estimates are 42.5% for total, 43.0% for men, and 42.1% for women. Figure 1 is adapted from data table at: https://www.cdc.gov/nchs/data/databriefs/db360\_tables-508. pdf#1 [Accessed: 13 August 2020]. Source: National Center for Health Statistics (NCHS), National Health and Nutrition Examination Survey, 2017–2018.*

**79**

*Obesity Acceptance: Body Positivity and Clinical Risk Factors*

Over the past 20 years, mean weight, waist circumference (WC), and BMI among U.S. adults over aged 20 increased across all age groups for non-Hispanic white and Mexican-American men and women, and for non-Hispanic black women [9]. Men had more obesity among those aged 20–39 and 40–59 than women in the same respective age groups, and less obesity among those 60 and over compared to women of the same age group [7]. However, none of the reported differences were significant. On the contrary, during this same time period, women reportedly had a higher overall prevalence of severe obesity than men, with significant differences in

*Age-adjusted prevalence of severe obesity among adults aged 20 and over, by sex, age, and race and Hispanic* 

*Significantly different from men. 2*

*origin groups. Notes: Estimates for adults aged 20 and over were age-adjusted by the direct method to the 2000 U.S. Census population using the age groups 20–39, 40–59, and 60 and over. Crude estimates are 9.0% for total, 6.8% for men, and 11.1% for women. Figure 2 is adapted from data table at: https://www.cdc.gov/nchs/ data/databriefs/db360\_tables-508.pdf#3 [Accessed: 03 August 2020]. Source: Figure adapted from National Center for Health Statistics (NCHS), National Health and Nutrition Examination Survey, 2017–2018.*

BMI is a useful inexpensive tool that has long been used to assess overweight, obesity, and risk for diseases that occur resulting from excess body fat. The internationally accepted standard cut-off points for defining a healthy or unhealthy weight

BMI is not without its limitations, often overestimating body fat in individuals with more muscle tissue, while underestimating body fat in individuals who have lost muscle [10]. Another challenge with using BMI as an adiposity metric is that it is unable to estimate percent body fat nor can it differentiate fat distribution for a given BMI, which can vary across age groups, sex, and race/ethnicity [11–13]. Results from some epidemiological investigations have even justified implementing adjustments to the cut-off values for classifying obesity and elevated WC among racial/ethnic populations [5, 14]. Lastly, using BMI percentile cutoffs to determine obesity and morbid obesity becomes especially problematic among children as it fails to consider large head size and high torso-to-leg ratio in the pediatric population [15]. The

. The prevailing BMI classifications are

*Significantly different from adults aged* 

*Significantly different from all other race and Hispanic-*

), over-

) [5].

), obesityClass II

), normal weight (BMI of 18.5–24.9 kg/m2

), obesityClass I (BMI of 30.0–34.9 kg/m2

), and extreme obesityClass III (BMI ≥ 40.0 kg/m2

age groups race/ethnicity, and sex [7] (**Figure 2**).

*Significantly different from adults ages 40-59. 4*

is when body mass index (BMI) is 25 kg/m2

underweight (BMI < 18.5 kg/m2

weight (BMI of 25.0–29.9 kg/m2

(BMI of 35.0–39.9 kg/m2

**Figure 2.**

*20-39. 3*

*origin: United States, 2017–2018. 1*

**2.2 Body mass index and other body composition methods**

*DOI: http://dx.doi.org/10.5772/intechopen.93540*

*Obesity Acceptance: Body Positivity and Clinical Risk Factors DOI: http://dx.doi.org/10.5772/intechopen.93540*

#### **Figure 2.**

*Cardiac Diseases - Novel Aspects of Cardiac Risk, Cardiorenal Pathology and Cardiac Interventions*

Positive body image is indeed a necessary component of overall health and an important factor in determining one's ability to reach weight loss goals. An imperative complement to these movements, however, is adequate health literacy, or an ability to read, comprehend, and use information in a manner that promotes and maintains good health [3]. It is only with proper knowledge of what constitutes a clinical definition of "normal" weight versus higher weights associated with increased CVD risk, coupled with mindful weight management, regular exercise, monitoring blood pressure (BP), and maintenance of blood sugar, that will con-

Over the past 40 years, there has been a sharp rise in worldwide obesity with prevalence nearly tripling since 1975 [4]. According to the World Health Organization (WHO), overweight and obesity are defined as having abnormal or excessive fat accumulation that may impair health [4]. Studies show the global obesity epidemic is worsening. In 2016, nearly 2 billion adults over 18 years world-

Prevalence of obesity and severe obesity in the U.S. continue to rise [5]. Currently, the rates of obesity exceed 30% in most sex and adult age groups,

whereas its prevalence has reached 17% among children and adolescents, defined as a BMI exceeding the 95th percentile [6]. In 2017–2018, it was estimated that 42.4% of U.S. adults aged 20 and over were obese (**Figure 1**) and 9.2% were severely obese [7] (**Figure 2**), and these may be underestimated. In a study comparing rates of obesity diagnosis to national rates of obesity based on BMI data from the Behavioral Risk Factor Surveillance System, the authors found that obesity is largely underdi-

*Prevalence of obesity among adults aged 20 and over, by sex and age: United States, 2017–2018. Notes: Estimates for adults aged 20 and over were age-adjusted by the direct method to the 2000 U.S. Census population using the age groups 20–39, 40–59, and 60 and over. Crude estimates are 42.5% for total, 43.0% for men, and 42.1% for women. Figure 1 is adapted from data table at: https://www.cdc.gov/nchs/data/databriefs/db360\_tables-508. pdf#1 [Accessed: 13 August 2020]. Source: National Center for Health Statistics (NCHS), National Health and* 

wide were overweight and of these, over 650 million were obese [4].

agnosed and undertreated in clinical settings [8].

tinue progress toward reducing CVD risk.

**2. Obesity**

**2.1 The obesity pandemic**

**78**

**Figure 1.**

*Nutrition Examination Survey, 2017–2018.*

*Age-adjusted prevalence of severe obesity among adults aged 20 and over, by sex, age, and race and Hispanic origin: United States, 2017–2018. 1 Significantly different from men. 2 Significantly different from adults aged 20-39. 3 Significantly different from adults ages 40-59. 4 Significantly different from all other race and Hispanicorigin groups. Notes: Estimates for adults aged 20 and over were age-adjusted by the direct method to the 2000 U.S. Census population using the age groups 20–39, 40–59, and 60 and over. Crude estimates are 9.0% for total, 6.8% for men, and 11.1% for women. Figure 2 is adapted from data table at: https://www.cdc.gov/nchs/ data/databriefs/db360\_tables-508.pdf#3 [Accessed: 03 August 2020]. Source: Figure adapted from National Center for Health Statistics (NCHS), National Health and Nutrition Examination Survey, 2017–2018.*

Over the past 20 years, mean weight, waist circumference (WC), and BMI among U.S. adults over aged 20 increased across all age groups for non-Hispanic white and Mexican-American men and women, and for non-Hispanic black women [9]. Men had more obesity among those aged 20–39 and 40–59 than women in the same respective age groups, and less obesity among those 60 and over compared to women of the same age group [7]. However, none of the reported differences were significant. On the contrary, during this same time period, women reportedly had a higher overall prevalence of severe obesity than men, with significant differences in age groups race/ethnicity, and sex [7] (**Figure 2**).

#### **2.2 Body mass index and other body composition methods**

BMI is a useful inexpensive tool that has long been used to assess overweight, obesity, and risk for diseases that occur resulting from excess body fat. The internationally accepted standard cut-off points for defining a healthy or unhealthy weight is when body mass index (BMI) is 25 kg/m2 . The prevailing BMI classifications are underweight (BMI < 18.5 kg/m2 ), normal weight (BMI of 18.5–24.9 kg/m2 ), overweight (BMI of 25.0–29.9 kg/m2 ), obesityClass I (BMI of 30.0–34.9 kg/m2 ), obesityClass II (BMI of 35.0–39.9 kg/m2 ), and extreme obesityClass III (BMI ≥ 40.0 kg/m2 ) [5].

BMI is not without its limitations, often overestimating body fat in individuals with more muscle tissue, while underestimating body fat in individuals who have lost muscle [10]. Another challenge with using BMI as an adiposity metric is that it is unable to estimate percent body fat nor can it differentiate fat distribution for a given BMI, which can vary across age groups, sex, and race/ethnicity [11–13]. Results from some epidemiological investigations have even justified implementing adjustments to the cut-off values for classifying obesity and elevated WC among racial/ethnic populations [5, 14]. Lastly, using BMI percentile cutoffs to determine obesity and morbid obesity becomes especially problematic among children as it fails to consider large head size and high torso-to-leg ratio in the pediatric population [15]. The

variation of high BMIz values, due to sex and age, make it very difficult to interpret the high BMIz levels (and changes in these levels) among children with severe obesity, possibly leading to incorrect conclusions [16]. Despite its limitations, BMI is used in most clinical settings and is correlated to more direct measures of body fat, such as underwater weighing and dual energy X-ray absorptiometry [17].

When predicting cardiometabolic disease, many studies demonstrate the use of WC, a measure of visceral adipose tissue and commonly used to calculate waistto-hip ratio, as a preferred approach over BMI for estimating body fat [5, 18]. A WC ≥ 102 cm in men and ≥ 88 cm in women can be an indicator of increased risk for type 2 diabetes, HTN, and CVD, even among individuals with normal weight [19]. Other studies have suggested a combination of adiposity metrics more efficiently identifies all CVD risk factors [20], while some have found the use of either BMI or WC as the index of adiposity identifying the same persons, with equal utility [21].

Many sophisticated direct volumetric techniques are available for body composition assessment that vary in sensitivity and specificity. For example, some more expensive methods include tracer dilution, bioelectrical impedance plethysmography, densitometry, dual-energy X-ray absorptiometry (DEXA), and air displacement plethysmography [22]. Still, other tools that can better visualize and quantify tissues, organs, muscle, and adipose tissue include imaging techniques such as nuclear magnetic resonance and computed tomography [14, 22]. However, in most clinical settings, BMI along with other simple, non-invasive anthropometric measures are used.

## **2.3 Factors driving obesity**

On a physiological level, obesity is the result of an energy imbalance between calories consumed and the calories expended, creating an energy surplus and a state of positive energy balance resulting in excess body weight [1]. Obesity also arises from poor health behaviors (e.g., poor sleep habits, diet, physical activity), genetic and epigenetic factors, gut microbiota, and a failure of health care professionals to advise people with obesity on appropriate courses of action for weight reduction [13, 23, 24]. Other "obesogenic" environmental drivers of obesity include marketing of inexpensive nutrient-poor foods, sedentary places of employment, industrialization, mechanized transportation, and urbanization [1].

An indirect driver of increasing BMI is the increasing trend in mean body weight without corresponding increases in height over time. According to the National Health Statistics Report, there is a rising trend in BMI with no significant change in height, with even slight decreases in height among some racial/ethnic groups [9]. For example, among all men, mean height significantly increased from 1999 to 2000 (175.6 cm) to 2003 to 2004 (176.6 cm) and subsequently decreased until 2015–2016 (175.4 cm) [9]. Among all male racial/ethnic groups, only non-Hispanic black men experienced a significant decrease in mean height from 1999 to 2000 (176.0 cm) to 2015 to 2016 (175.5 cm). In contrast, among all women, no significant linear trends were observed over the same time period or for any racial/ethnic subgroup [9].

### **2.4 Obesity-related health risks and comorbidities**

It is widely recognized that cardiovascular risk and metabolic complications are due to a constellation of obesity, physical inactivity, and primary HTN [25]. Compared to those with a healthy or normal weight, people with obesity are at especially increased risk for many adverse health outcomes, including high BP, higher levels of low-density lipoprotein cholesterol, lower levels of high-density

**81**

**Figure 3.**

*Obesity-related health risks and comorbidities [7, 24, 26].*

*Obesity Acceptance: Body Positivity and Clinical Risk Factors*

lipoprotein (HDL) cholesterol, type 2 diabetes, stroke, sleep apnea, and poor quality of life [7, 24, 26] (**Figure 3**). Obesity has also been linked to cancers of the esophagus, colon and rectum, liver, gallbladder and biliary tract, pancreas, breast, uterus, ovary, kidney, and thyroid. [26]. Individuals with severe obesity are further susceptible to obesity-related complications, such as coronary heart disease and

excess body weight accounted for about 4 million deaths worldwide, with an additional 120 million disability-adjusted life-years [26]. Higher BMI classified as overweight and not obese is also associated with mortality. Over one-third of global deaths and disability-adjusted life-years were related to BMI classified as over-

) [26].

A systematic evaluation of the health effects of high BMI revealed that in 2015,

In a U.S. study using National Health and Nutrition Examination Survey data examining the prevalence of 11 common chronic conditions, obesity experienced the largest significantly increased trend of any condition over the past 25 years (1998–2014) [27]. Due to its pervasiveness and its detrimental impact on morbidity and mortality, obesity is included as a chronic condition in multimorbidity models

Although obesity, particularly visceral adiposity, is typically associated with metabolic dysfunction and cardiometabolic diseases, there are some obesity

*DOI: http://dx.doi.org/10.5772/intechopen.93540*

end-stage renal disease [7].

weight (less than 30 kg/m<sup>2</sup>

rather than as a control factor [27].

**2.5 Characterization of metabolic profiles**

#### *Obesity Acceptance: Body Positivity and Clinical Risk Factors DOI: http://dx.doi.org/10.5772/intechopen.93540*

*Cardiac Diseases - Novel Aspects of Cardiac Risk, Cardiorenal Pathology and Cardiac Interventions*

variation of high BMIz values, due to sex and age, make it very difficult to interpret the high BMIz levels (and changes in these levels) among children with severe obesity, possibly leading to incorrect conclusions [16]. Despite its limitations, BMI is used in most clinical settings and is correlated to more direct measures of body fat,

When predicting cardiometabolic disease, many studies demonstrate the use of WC, a measure of visceral adipose tissue and commonly used to calculate waistto-hip ratio, as a preferred approach over BMI for estimating body fat [5, 18]. A WC ≥ 102 cm in men and ≥ 88 cm in women can be an indicator of increased risk for type 2 diabetes, HTN, and CVD, even among individuals with normal weight [19]. Other studies have suggested a combination of adiposity metrics more efficiently identifies all CVD risk factors [20], while some have found the use of either BMI or WC as the index of adiposity identifying the same persons, with

Many sophisticated direct volumetric techniques are available for body composition assessment that vary in sensitivity and specificity. For example, some more expensive methods include tracer dilution, bioelectrical impedance plethysmography, densitometry, dual-energy X-ray absorptiometry (DEXA), and air displacement plethysmography [22]. Still, other tools that can better visualize and quantify tissues, organs, muscle, and adipose tissue include imaging techniques such as nuclear magnetic resonance and computed tomography [14, 22]. However, in most clinical settings, BMI along with other simple, non-invasive anthropometric

On a physiological level, obesity is the result of an energy imbalance between calories consumed and the calories expended, creating an energy surplus and a state of positive energy balance resulting in excess body weight [1]. Obesity also arises from poor health behaviors (e.g., poor sleep habits, diet, physical activity), genetic and epigenetic factors, gut microbiota, and a failure of health care professionals to advise people with obesity on appropriate courses of action for weight reduction [13, 23, 24]. Other "obesogenic" environmental drivers of obesity include marketing of inexpensive nutrient-poor foods, sedentary places of employment,

An indirect driver of increasing BMI is the increasing trend in mean body weight

without corresponding increases in height over time. According to the National Health Statistics Report, there is a rising trend in BMI with no significant change in height, with even slight decreases in height among some racial/ethnic groups [9]. For example, among all men, mean height significantly increased from 1999 to 2000 (175.6 cm) to 2003 to 2004 (176.6 cm) and subsequently decreased until 2015–2016 (175.4 cm) [9]. Among all male racial/ethnic groups, only non-Hispanic black men experienced a significant decrease in mean height from 1999 to 2000 (176.0 cm) to 2015 to 2016 (175.5 cm). In contrast, among all women, no significant linear trends were observed over the same time period or for any racial/ethnic subgroup [9].

It is widely recognized that cardiovascular risk and metabolic complications are due to a constellation of obesity, physical inactivity, and primary HTN [25]. Compared to those with a healthy or normal weight, people with obesity are at especially increased risk for many adverse health outcomes, including high BP, higher levels of low-density lipoprotein cholesterol, lower levels of high-density

industrialization, mechanized transportation, and urbanization [1].

**2.4 Obesity-related health risks and comorbidities**

such as underwater weighing and dual energy X-ray absorptiometry [17].

**80**

equal utility [21].

measures are used.

**2.3 Factors driving obesity**

lipoprotein (HDL) cholesterol, type 2 diabetes, stroke, sleep apnea, and poor quality of life [7, 24, 26] (**Figure 3**). Obesity has also been linked to cancers of the esophagus, colon and rectum, liver, gallbladder and biliary tract, pancreas, breast, uterus, ovary, kidney, and thyroid. [26]. Individuals with severe obesity are further susceptible to obesity-related complications, such as coronary heart disease and end-stage renal disease [7].

A systematic evaluation of the health effects of high BMI revealed that in 2015, excess body weight accounted for about 4 million deaths worldwide, with an additional 120 million disability-adjusted life-years [26]. Higher BMI classified as overweight and not obese is also associated with mortality. Over one-third of global deaths and disability-adjusted life-years were related to BMI classified as overweight (less than 30 kg/m<sup>2</sup> ) [26].

In a U.S. study using National Health and Nutrition Examination Survey data examining the prevalence of 11 common chronic conditions, obesity experienced the largest significantly increased trend of any condition over the past 25 years (1998–2014) [27]. Due to its pervasiveness and its detrimental impact on morbidity and mortality, obesity is included as a chronic condition in multimorbidity models rather than as a control factor [27].
